146 Commits

Author SHA1 Message Date
github-actions[bot] fc6f0a1a7b bump: version 0.1.0 → 0.1.1 [skip ci] 2025-11-08 00:22:06 +00:00
Dark-Alex-17 21873da278 docs: Fixed a typo in the CI badge path 2025-11-07 17:17:57 -07:00
Dark-Alex-17 d1cd6be2c9 docs: Fixed some confusing wording in the global configuration example file 2025-11-07 16:57:49 -07:00
github-actions[bot] 0c0ae41bca bump: version 0.0.1 → 0.1.0 [skip ci] 2025-11-07 23:47:37 +00:00
Dark-Alex-17 c9ed7a904a ci: Final release checks before open sourcing the repo 2025-11-07 16:43:50 -07:00
Dark-Alex-17 d200a8f554 Merge remote-tracking branch 'origin/main' 2025-11-07 16:24:47 -07:00
Dark-Alex-17 3d04c8fcf1 docs: Fixed a typo in the Vault documentation 2025-11-07 16:24:42 -07:00
github-actions[bot] f53f165d91 bump: version 0.0.1 → 0.1.0 [skip ci] 2025-11-07 23:19:04 +00:00
Dark-Alex-17 e5645e4064 ci: Prepare for release 2025-11-07 16:18:16 -07:00
Dark-Alex-17 95e15ca8c4 bump: version 0.0.1 → 0.1.0 2025-11-07 16:11:14 -07:00
Dark-Alex-17 dbf7329e87 refactor: Updated to the most recent Rust version with 2024 syntax 2025-11-07 15:50:55 -07:00
github-actions[bot] ed6c3ae431 bump: version 0.1.0 → 0.2.0 [skip ci] 2025-11-07 22:04:11 +00:00
Dark-Alex-17 214d2ecc67 ci: Bumped the patch version 2025-11-07 15:03:31 -07:00
Dark-Alex-17 29c95671de build: bumped the crate version 2025-11-07 14:59:41 -07:00
Dark-Alex-17 238f93a096 docs: Added badges for Loki 2025-11-07 14:24:25 -07:00
Dark-Alex-17 c76877e7b3 ci: Fixed typo in commit message for homebrew tap 2025-11-07 14:24:13 -07:00
Dark-Alex-17 12e5a9c5aa build: Renamed the crate to loki-ai since loki is taken 2025-11-07 14:16:02 -07:00
Dark-Alex-17 7f4be2ca3f ci: Created the homebrew installation steps 2025-11-07 13:53:28 -07:00
Dark-Alex-17 29ffe12d8c ci: Created the release pipeline 2025-11-07 13:51:53 -07:00
Dark-Alex-17 d34bed4f15 docs: Updated the README to credit the AIChat team and to offer quick links to get around the docs 2025-11-07 13:49:26 -07:00
Dark-Alex-17 aec7ea7e80 docs: Wrote migration documentation for users coming from AIChat 2025-11-07 13:49:02 -07:00
Dark-Alex-17 5938e1af29 docs: Added a simple gif to show what the models table looks like for tab completions 2025-11-07 13:48:48 -07:00
Dark-Alex-17 60902297c5 docs: Replaced the copy gif with one that better shows that the content is copied to your clipboard 2025-11-07 13:48:30 -07:00
Dark-Alex-17 12a95aa6fa docs: Updated the continue gif to use a prompt that makes more sense 2025-11-07 13:48:09 -07:00
Dark-Alex-17 78fc459a97 docs: Updated the set gif to show the up-to-date settings names 2025-11-07 13:47:57 -07:00
Dark-Alex-17 281565804c docs: Updated the regenerate gif to use the up-to-date settings names 2025-11-07 13:47:41 -07:00
Dark-Alex-17 33a32fd9c8 docs: Created docs for the REPL 2025-11-07 13:47:20 -07:00
Dark-Alex-17 b64aad55e9 docs: Documented all available environment variables 2025-11-07 13:47:10 -07:00
Dark-Alex-17 2392958114 docs: Added back in the conversation starters gif for the agent docs 2025-11-07 13:46:53 -07:00
Dark-Alex-17 ec04e8e24a docs: Made an example agent gif to show how they work (and variables) 2025-11-07 13:46:35 -07:00
Dark-Alex-17 4e14ee7f50 docs: Created documentation for agents 2025-11-07 13:46:16 -07:00
Dark-Alex-17 7ba4ab0608 docs: Added a screenshot of the tools overrides settings 2025-11-07 13:46:00 -07:00
Dark-Alex-17 fd816112fb docs: Created docs about both built-in and custom tools for function calling capabilities 2025-11-07 13:45:45 -07:00
Dark-Alex-17 d0ee85be40 docs: Documented how to create custom tools in Python, and how custom tools are created and used 2025-11-07 13:45:23 -07:00
Dark-Alex-17 9448704af3 docs: Documented how to create custom Bash-based tools 2025-11-07 13:45:01 -07:00
Dark-Alex-17 9dad9d6ca8 docs: Added back in forgotten gif of a session 2025-11-07 13:44:44 -07:00
Dark-Alex-17 3f41abed7c docs: documentation on how sessions work in Loki 2025-11-07 13:44:32 -07:00
Dark-Alex-17 debcbab445 docs: Created a demo gif of how to use roles in general 2025-11-07 13:44:16 -07:00
Dark-Alex-17 7fcabf1de7 docs: Created a demo gif of a temporary prompt role 2025-11-07 13:44:00 -07:00
Dark-Alex-17 e116a1841d docs: Documented roles 2025-11-07 13:43:37 -07:00
Dark-Alex-17 cd3103ca14 docs: created a gif that demonstrates macro functionality 2025-11-07 13:43:26 -07:00
Dark-Alex-17 50d07a4b13 docs: Removed a forgotten TODO comment 2025-11-07 13:43:09 -07:00
Dark-Alex-17 ed1352936e docs: created a screenshot of the global settings overrides for MCP servers 2025-11-07 13:42:36 -07:00
Dark-Alex-17 f4b4156a0c docs: created screenshots for both ephemeral and persistent RAG 2025-11-07 13:42:15 -07:00
Dark-Alex-17 5cf2cce0e3 docs: documented RAG 2025-11-07 13:41:50 -07:00
Dark-Alex-17 249453d829 docs: Created docs that explain how to use MCP servers with Loki 2025-11-07 13:41:19 -07:00
Dark-Alex-17 c14939cecc docs: created docs for Loki's macro system 2025-11-07 13:40:48 -07:00
Dark-Alex-17 72f516abb1 docs: documented how to use custom themes 2025-11-07 13:40:25 -07:00
Dark-Alex-17 66478ed264 docs: documented how to create custom REPL prompts 2025-11-07 13:40:10 -07:00
Dark-Alex-17 6b10dff41d docs: documented the now built-in bash helper script and the tools it comes with 2025-11-07 13:39:53 -07:00
Dark-Alex-17 f8cc736482 docs: created documentation for how to patch requests via configuration settings 2025-11-07 13:39:04 -07:00
Dark-Alex-17 a0794fecfc docs: created documentation for client configurations 2025-11-07 13:38:34 -07:00
Dark-Alex-17 c68059e5b3 docs: updated the vault demo screenshots and gifs 2025-11-07 13:38:22 -07:00
Dark-Alex-17 832ca6b0de docs: Added screenshots for select custom themes 2025-11-07 13:37:56 -07:00
Dark-Alex-17 89ee43830e docs: Added documentation for secret injection support into environment variables for agents 2025-11-07 12:28:11 -07:00
Dark-Alex-17 f7cf13901e docs: Added an explain-shell screenshot 2025-11-07 12:26:43 -07:00
Dark-Alex-17 ad41fa93fb docs: Fixed a typo in the shell integrations documentation 2025-11-07 12:25:26 -07:00
Dark-Alex-17 617b7dcd49 docs: Created license 2025-11-07 11:48:19 -07:00
Dark-Alex-17 417ea032c4 ci: Created Loki installation scripts 2025-11-07 11:48:08 -07:00
Dark-Alex-17 b77bb6e200 refactor: Changed the name of the summary_prompt setting to summary_context_prompt 2025-11-07 11:13:58 -07:00
Dark-Alex-17 1fa3b4a600 refactor: Renamed summarize_prompt setting to summarization_prompt 2025-11-07 11:09:48 -07:00
Dark-Alex-17 99bd502f62 refactor: Renamed the compress_threshold setting to compression_threshold 2025-11-07 11:06:20 -07:00
Dark-Alex-17 25a271dc95 style: Applied formatting 2025-11-06 18:19:25 -07:00
Dark-Alex-17 5002ac7716 refactor: Migrated around the location of some of the more large documents for documentation 2025-11-06 18:02:17 -07:00
Dark-Alex-17 d92a559460 docs: Updated the global configuration example to have a separate section for the REPL prompts 2025-11-06 16:24:20 -07:00
Dark-Alex-17 3d571e1a31 docs: Fixed a typo in the description of the stream setting 2025-11-06 16:10:44 -07:00
Dark-Alex-17 d338daa4b6 docs: Referenced the vault documentation in the example config 2025-11-06 16:09:21 -07:00
Dark-Alex-17 6f802c2a58 docs: Created a separate, dedicated section of the example configuration file for the vault 2025-11-06 16:08:20 -07:00
Dark-Alex-17 a3f0168817 docs: Improved the documentation for sessions and the examples in the global configuration example 2025-11-06 15:55:38 -07:00
Dark-Alex-17 677702655f docs: Improved the documentation of preludes and their purpose in the example global configuration file 2025-11-06 15:48:44 -07:00
Dark-Alex-17 b0bbd0c083 docs: Improved the documentation of the behavior-related settings of the global configuration file example 2025-11-06 15:47:30 -07:00
Dark-Alex-17 5cbf23a1f4 docs: Improved wording in the example agent configuration 2025-11-06 13:55:44 -07:00
Dark-Alex-17 39eb9b34ec docs: Updated the example agent configuration to show the new global_tools and mcp_servers environment variables 2025-11-06 13:31:25 -07:00
Dark-Alex-17 5da8616518 feat: Added the agents directory to sysinfo output 2025-11-06 13:22:13 -07:00
Dark-Alex-17 b267fe05cd docs: Fixed a typo in the Vertex AI client configuration example in the example global configuration file 2025-11-06 13:07:34 -07:00
Dark-Alex-17 29f7ebe559 Added environment variables for agents for the global_tools and mcp_servers settings 2025-11-06 12:16:36 -07:00
Dark-Alex-17 bbffaca511 docs: Updated the example global configuration file with some better examples for RAG 2025-11-06 10:49:51 -07:00
Dark-Alex-17 80532836c3 docs: Created an example macro configuration file 2025-11-05 16:55:04 -07:00
Dark-Alex-17 9474f4f322 feat: Added built-in macros 2025-11-05 16:28:56 -07:00
Dark-Alex-17 93a09d3a9f bug: Removed deprecated experimentation for MCP sampling 2025-11-05 16:12:04 -07:00
Dark-Alex-17 e3935ce699 style: Added an import for Anyhow's Result in the macros module 2025-11-05 15:52:44 -07:00
Dark-Alex-17 58c15e7833 refactor: Factored out the macros structs from the large config module 2025-11-05 15:50:39 -07:00
Dark-Alex-17 fd2b7f3aa0 bug: Fixed a bug with the spacing of info output now that function_calling_support is a longer name 2025-11-05 15:41:49 -07:00
Dark-Alex-17 5ccbc629d1 feat: Updated the example role configuration file to also have the prompt field 2025-11-05 15:25:01 -07:00
Dark-Alex-17 e98ff5e8e5 feat: Updated the code role 2025-11-05 15:24:45 -07:00
Dark-Alex-17 a6fffa7b57 refactor: Refactored mcp_servers and function_calling to mcp_server_support and function_calling_support to make the purpose of the fields more clear 2025-11-04 13:17:58 -07:00
Dark-Alex-17 3ac153dd06 refactor: Refactored the use_mcp_servers field to enabled_mcp_servers to make the purpose of the field more clear 2025-11-04 12:51:41 -07:00
Dark-Alex-17 8db3108c94 Merge branch 'main' of github.com:Dark-Alex-17/loki 2025-11-04 12:37:32 -07:00
Dark-Alex-17 e25ff4ad19 refactor: Refactored use_tools field to enabled_tools field to make the use of the field more clear 2025-11-04 12:37:14 -07:00
Dark-Alex-17 21e76c6461 Refactored the use_tools field to enabled_tools to make field uses and functions more clear 2025-11-04 12:36:31 -07:00
Dark-Alex-17 103aa1a432 docs: Updated the config.example.yaml to have an example of how to use the visible_tools array 2025-11-04 12:10:17 -07:00
Dark-Alex-17 d2f4fefcf3 refactor: Removed the use of the tools.txt file and added tool visibility declarations to the global configuration file 2025-11-04 12:07:58 -07:00
Dark-Alex-17 629527988d refactor: Agents that depend on global tools now have all binaries compiled and stored in the agent's bin directory so multiple agents can run at once 2025-11-04 11:29:59 -07:00
Dark-Alex-17 7f520f1346 feat: Secret injection as environment variables into agent tools 2025-11-03 15:10:34 -07:00
Dark-Alex-17 e28619b55a feat: Removed the server functionality 2025-11-03 14:25:55 -07:00
Dark-Alex-17 f474e6130e feat: Require Vault set up for first-time setup so all passed in secrets can be encrypted right off the bat 2025-10-27 12:00:27 -06:00
Dark-Alex-17 4b5bcb45ac style: Re-applied formatting to make Clippy happy 2025-10-24 15:05:42 -06:00
Dark-Alex-17 50565a0f17 refactor: Removed the git MCP server and used the newer, better mcp-server-docker for local docker integration 2025-10-24 14:38:13 -06:00
Dark-Alex-17 cf37db4fa2 docs: Added in forgotten MCP server configuration values to the example config 2025-10-24 14:16:13 -06:00
Dark-Alex-17 ad9b4097ef Created an Elvish integration script 2025-10-24 11:28:31 -06:00
Dark-Alex-17 c22c01c6c3 refactor: Renamed the argument for the --completions flag to SHELL 2025-10-24 10:58:28 -06:00
Dark-Alex-17 31f7f50c4a feat: Added static completions via a --completions flag 2025-10-24 10:56:34 -06:00
Dark-Alex-17 a7f6ed4b16 refactor: Updated the instructions for the jira-helper agent 2025-10-23 10:07:50 -06:00
Dark-Alex-17 73ada5a221 bug: Fixed a bug when passing tools to Claude for tools that don't have any inputs 2025-10-21 10:04:38 -06:00
Dark-Alex-17 2f96256893 bug: Fixed a bug that was duplicating entries of all the functions for agents between MCP and tools 2025-10-20 15:30:29 -06:00
Dark-Alex-17 23d9e0775f ci: Updated to only include basic ARM64 and x86_64 architectures 2025-10-17 13:30:42 -06:00
Dark-Alex-17 72ade39144 bug: corrected a typo for sourcing the prompt utility bash script in the built-in tools 2025-10-16 15:48:53 -06:00
Dark-Alex-17 ec64c68777 fix: Corrected a typo for sourcing the bash utility script in some agent definitions 2025-10-16 15:47:07 -06:00
Dark-Alex-17 80932e069f chore: update the models.yaml 2025-10-16 15:20:33 -06:00
Dark-Alex-17 2f9b154b07 refactor: Modified the default PS1 look 2025-10-16 15:08:48 -06:00
Dark-Alex-17 20bf911732 style: Cleaned up some linting issues for Windows 2025-10-16 13:30:30 -06:00
Dark-Alex-17 65a3dbb228 style: Applied formatting 2025-10-16 13:01:37 -06:00
Dark-Alex-17 5844cc93ca refactor: Fixed a linting issue for Windows builds 2025-10-16 12:44:50 -06:00
Dark-Alex-17 4d23ce58c4 docs: Updated outdated API links in the config example 2025-10-16 12:38:07 -06:00
Dark-Alex-17 2bb592d5f6 feat: Support for secret injection into the global config file (API keys, for example) 2025-10-16 12:30:18 -06:00
Dark-Alex-17 3146b20c15 feat: Improved MCP handling toggle handling 2025-10-15 18:36:54 -06:00
Dark-Alex-17 455cf67750 feat: Secret injection into the MCP configuration 2025-10-15 16:06:59 -06:00
Dark-Alex-17 a6d6a877b0 feat: added REPL support for interacting with the Loki vault 2025-10-15 15:15:04 -06:00
Dark-Alex-17 a7bd54471c feat: Integrated gman with Loki to create a vault and added flags to configure the Loki vault 2025-10-14 18:00:11 -06:00
Dark-Alex-17 fe5f803163 Applied formatting 2025-10-10 15:32:51 -06:00
Dark-Alex-17 66a9b5362a bug: Automatically mark all extracted tools as executable 2025-10-10 15:30:58 -06:00
Dark-Alex-17 f3569cf68b docs: Created an example role configuration 2025-10-10 15:15:11 -06:00
Dark-Alex-17 2573f14726 feat: Added a default session to the jira helper to make interaction more natural 2025-10-10 15:03:26 -06:00
Dark-Alex-17 f1fb2d6abf style: applied formatting 2025-10-10 15:01:55 -06:00
Dark-Alex-17 4934e0ff0a refactor: Changed the name of agent_prelude to agent_session to make its purpose more clear 2025-10-10 15:01:44 -06:00
Dark-Alex-17 f772a80501 style: Applied consistent formatting to agent changes 2025-10-10 14:48:10 -06:00
Dark-Alex-17 8950843be2 feat: Created the repo-analyzer role 2025-10-10 14:43:18 -06:00
Dark-Alex-17 9b89e68908 feat: Created the coder and sql agents 2025-10-10 13:38:47 -06:00
Dark-Alex-17 ba134ca53f feat: Cleaned the built-in functions to not have leftover dependencies 2025-10-10 13:38:27 -06:00
Dark-Alex-17 21dbd9c057 feat: Created additional built-in roles for slack, repo analysis, and github 2025-10-10 13:38:03 -06:00
Dark-Alex-17 40a68f8e05 feat: Install built-in agents 2025-10-10 13:37:05 -06:00
Dark-Alex-17 37d861a631 refactor: Removed leftover javascript function support; will not implement 2025-10-10 10:22:05 -06:00
Dark-Alex-17 31f3e885ce docs: Fixed typo in Python execution docs 2025-10-10 10:05:09 -06:00
Dark-Alex-17 7ffaab2012 feat: Embedded baseline MCP config and global tools 2025-07-13 09:58:00 -06:00
Dark-Alex-17 35b7946b0d docs: Created the code of conduct 2025-07-06 10:59:27 -06:00
Dark-Alex-17 3a05a8e712 docs: Added the security policy 2025-07-06 10:58:02 -06:00
Dark-Alex-17 294a1149ef ci: Initialized commitizen configuration 2025-07-06 10:57:37 -06:00
Dark-Alex-17 8d80370014 docs: Added loki contribution guidelines 2025-07-06 10:55:52 -06:00
Dark-Alex-17 1cbdef36cf Created an .actrc file to make local CI/CD testing easier 2025-07-06 10:54:16 -06:00
Dark-Alex-17 4c8accbfc1 Removed the hestia CLI since it is no longer needed 2025-07-06 10:53:44 -06:00
Dark-Alex-17 c4c2d9cb93 Updated gitignore 2025-07-06 10:53:00 -06:00
Dark-Alex-17 7aed112326 Create issue templates and CI/CD workflows 2025-07-06 10:51:04 -06:00
Dark-Alex-17 216a3d53cd Baseline project 2025-07-06 10:45:42 -06:00
Dark-Alex-17 e0823b343b Created initial assets 2025-07-06 10:43:34 -06:00
Dark-Alex-17 cb0bc65ee4 Created initial assets 2025-07-06 10:42:46 -06:00
Dark-Alex-17 5b9ab6636f Initial commit 2025-07-06 10:41:42 -06:00
221 changed files with 39441 additions and 2 deletions
+4
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@@ -0,0 +1,4 @@
--artifact-server-path=./.act/artifacts
--cache-server-path=./.act/cache
--container-options --privileged
--env ACT=true
+10
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@@ -0,0 +1,10 @@
[tool.commitizen]
name = "cz_conventional_commits"
tag_format = "v$version"
version_scheme = "semver"
version_provider = "cargo"
update_changelog_on_bump = true
major_version_zero = true
[tool.commitizen.hooks]
pre-commit = "git add Cargo.toml Cargo.lock"
+1
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@@ -0,0 +1 @@
github: Dark-Alex-17
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---
name: Blank Issue
about: Create a blank issue.
---
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name: Bug Report
description: Create a report to help us improve
labels: bug
body:
- type: markdown
attributes:
value: Thank you for filing a bug report!
- type: textarea
id: problem
attributes:
label: Summary
description: >
Please provide a short summary of the bug, along with any information
you feel relevant to replicate the bug.
validations:
required: true
- type: textarea
id: reproduction-steps
attributes:
label: Reproduction Steps
value: |
I tried this:
1. `loki`
I expected this to happen:
Instead, this happened:
- type: textarea
id: loki-log
attributes:
label: Loki log
description: Include the Loki log file to help diagnose the issue. (`loki --info` to see the log_path)
value: |
| OS | Log file location |
| ------- | ----------------------------------------------------- |
| Linux | `~/.cache/loki/loki.log` |
| Mac | `~/Library/Logs/loki/loki.log` |
| Windows | `C:\Users\<User>\AppData\Local\loki\loki.log` |
```
please provide a copy of your loki log file here if possible; you may need to redact some of the lines
```
- type: input
id: platform
attributes:
label: Platform
placeholder: Linux / macOS / Windows
validations:
required: true
- type: input
id: terminal-emulator
attributes:
label: Terminal Emulator
placeholder: wezterm 20220101-133340-7edc5b5a
validations:
required: true
- type: input
id: loki-version
attributes:
label: Loki Version
description: >
Loki version (`loki --version` if using a release, `git describe` if building
from main).
**Make sure that you are using the [latest loki release](https://github.com/Dark-Alex-17/loki/releases) or a newer main build**
placeholder: "loki 0.1.0"
validations:
required: true
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---
name: Enhancement
about: Suggest an improvement
title: ''
labels: enhancement
assignees: ''
---
<!--
Your enhancement may already be reported!
Please search on the issue tracker before creating a new issue.
If this is an idea for a feature, please open an "Idea" Discussion instead.
-->
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name: CI
on:
pull_request:
branches:
- '*'
push:
branches:
- main
defaults:
run:
shell: bash
jobs:
all:
name: All
strategy:
matrix:
os:
- ubuntu-latest
- macos-latest
- windows-latest
runs-on: ${{matrix.os}}
env:
RUSTFLAGS: --deny warnings
steps:
- uses: actions/checkout@v4
- name: Install Rust Toolchain Components
uses: dtolnay/rust-toolchain@stable
- uses: Swatinem/rust-cache@v2
- name: Test
run: cargo test --all
- name: Clippy
run: cargo clippy --all --all-targets -- -D warnings
- name: Format
run: cargo fmt --all --check
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name: Create release
permissions:
pull-requests: write
contents: write
on:
workflow_dispatch:
inputs:
bump_type:
description: "Specify the type of version bump"
required: true
default: "patch"
type: choice
options:
- patch
- minor
- major
jobs:
bump-version:
name: bump-version
runs-on: ubuntu-latest
steps:
- name: Configure SSH for Git
if: env.ACT != 'true'
run: |
mkdir -p ~/.ssh
echo "${{ secrets.RELEASE_BOT_SSH_KEY }}" > ~/.ssh/id_ed25519
chmod 600 ~/.ssh/id_ed25519
ssh-keyscan -H github.com >> ~/.ssh/known_hosts
- name: Checkout repository
if: env.ACT != 'true'
uses: actions/checkout@v3
with:
ssh-key: ${{ secrets.RELEASE_BOT_SSH_KEY }}
fetch-depth: 0
- name: Checkout repository
if: env.ACT == 'true'
uses: actions/checkout@v3
with:
fetch-depth: 0
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: "3.10"
- name: Install Commitizen
run: |
python -m pip install --upgrade pip
pip install commitizen
npm install -g conventional-changelog-cli
- name: Configure Git user
run: |
git config user.name "github-actions[bot]"
git config user.email "github-actions[bot]@users.noreply.github.com"
- name: Bump version with Commitizen
run: |
cz bump --yes --increment ${{ github.event.inputs.bump_type }}
- name: Amend commit message to include '[skip ci]'
run: |
git commit --amend --no-edit -m "$(git log -1 --pretty=%B) [skip ci]"
- name: Install Rust stable
uses: dtolnay/rust-toolchain@stable
- name: Get the new version tag
id: version
run: |
mkdir -p artifacts
NEW_TAG=$(cz version --project)
echo "New version: $NEW_TAG"
echo "version=$NEW_TAG" >> $GITHUB_ENV
echo "$NEW_TAG" > artifacts/release-version
- name: Get the previous version tag
id: prev_version
run: |
PREV_TAG=$(git describe --tags --abbrev=0 ${GITHUB_SHA}^)
echo "Previous tag: $PREV_TAG"
echo "prev_version=$PREV_TAG" >> $GITHUB_ENV
- name: Bump Cargo.toml version
shell: bash
working-directory: ${{ github.workspace }}
env:
VERSION: ${{ env.version }}
run: |
set -euo pipefail
: "${VERSION:?env.version is empty}"
# Ignore Act's local artifact dir noise
echo artifacts/ >> .git/info/exclude || true
# Edit the version line right after name="loki"
sed -E -i '
/^[[:space:]]*name[[:space:]]*=[[:space:]]*"loki"[[:space:]]*$/ {
n
s|^[[:space:]]*version[[:space:]]*=[[:space:]]*"[^"]*"|version = "'"$VERSION"'"|
}
' Cargo.toml
cargo update || true
# Git config that helps in Act
git config user.name "github-actions[bot]"
git config user.email "github-actions[bot]@users.noreply.github.com"
git config --global --add safe.directory "$GITHUB_WORKSPACE"
git status --porcelain
git diff --name-only -- Cargo.toml Cargo.lock || true
if ! git diff --quiet -- Cargo.toml Cargo.lock; then
git add -u -- Cargo.toml Cargo.lock
git commit -m "chore: bump Cargo.toml to $VERSION"
else
echo "No changes to commit (already at $VERSION)"
fi
- name: Generate changelog for the version bump
id: changelog
run: |
conventional-changelog -p conventionalcommits -i CHANGELOG.md --from ${{ env.prev_version }} --to v${{ env.version }} > artifacts/changelog.md
- name: Push changes
if: env.ACT != 'true'
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: |
git push origin --follow-tags
- name: Upload artifacts
uses: actions/upload-artifact@v4
with:
path: artifacts
- name: Upload the changed Cargo files (Act)
if: env.ACT == 'true'
uses: actions/upload-artifact@v4
with:
name: bumped-cargo-files
path: |
Cargo.toml
Cargo.lock
publish-github-release:
name: build-release
needs: [bump-version]
runs-on: ${{ matrix.os }}
env:
RUST_BACKTRACE: 1
BUILD_CMD: cargo
strategy:
fail-fast: true
matrix:
include:
- target: aarch64-unknown-linux-musl
os: ubuntu-latest
use-cross: true
cargo-flags: ""
- target: aarch64-apple-darwin
os: macos-latest
use-cross: true
cargo-flags: ""
- target: aarch64-pc-windows-msvc
os: windows-latest
use-cross: true
cargo-flags: ""
- target: x86_64-apple-darwin
os: macos-latest
cargo-flags: ""
- target: x86_64-pc-windows-msvc
os: windows-latest
cargo-flags: ""
- target: x86_64-unknown-linux-musl
os: ubuntu-latest
use-cross: true
cargo-flags: ""
- target: x86_64-unknown-linux-gnu
os: ubuntu-latest
cargo-flags: ""
steps:
- name: Check if actor is repository owner
if: ${{ github.actor != github.repository_owner && env.ACT != 'true' }}
run: |
echo "You are not authorized to run this workflow."
exit 1
- name: Checkout repository
uses: actions/checkout@v4
with:
fetch-depth: 1
- name: Ensure repository is up-to-date
if: env.ACT != 'true'
run: |
git fetch --all
git pull
- name: Download all artifacts
uses: actions/download-artifact@v4
with:
path: artifacts
merge-multiple: true
- name: Ensure repository is up-to-date
if: env.ACT != 'true'
run: |
git fetch --all
git pull
- name: Set environment variables
shell: bash
run: |
release_version="$(cat ./artifacts/release-version)"
echo "RELEASE_VERSION=$release_version" >> $GITHUB_ENV
- name: Validate release environment variables
run: |
echo "Release version: ${{ env.RELEASE_VERSION }}"
echo "Changelog body: $(cat artifacts/changelog.md)"
- name: Get bumped Cargo files (Act)
if: env.ACT == 'true'
uses: actions/download-artifact@v4
with:
name: bumped-cargo-files
path: ${{ github.workspace }}
- uses: dtolnay/rust-toolchain@stable
name: Set Rust toolchain
with:
targets: ${{ matrix.target }}
- name: Install cross
if: matrix.use-cross
uses: taiki-e/install-action@v2
with:
tool: cross
- name: Overwrite build command env variable
if: matrix.use-cross
shell: bash
run: echo "BUILD_CMD=cross" >> $GITHUB_ENV
- name: Install latest LLVM/Clang
if: matrix.os == 'ubuntu-latest'
run: |
wget https://apt.llvm.org/llvm.sh
chmod +x llvm.sh
# omit the version to get the latest stable for your Ubuntu (24.04 "noble" on ubuntu-latest)
sudo ./llvm.sh all
# ensure libclang dev package is present (adjust the "22" if a newer major exists)
sudo apt-get update
sudo apt-get install -y libclang-20-dev libclang-dev
- name: Show Version Information (Rust, cargo, GCC)
shell: bash
run: |
gcc --version || true
rustup -V
rustup toolchain list
rustup default
cargo -V
rustc -V
- name: Build
shell: bash
run: $BUILD_CMD build --locked --release --target=${{ matrix.target }} ${{ matrix.cargo-flags }}
- name: Verify file
shell: bash
run: |
file target/${{ matrix.target }}/release/loki
- name: Test
if: matrix.target != 'aarch64-apple-darwin' && matrix.target != 'aarch64-pc-windows-msvc'
shell: bash
run: |
set -euxo pipefail
if [[ "${{ matrix.use-cross || 'false' }}" == 'true' ]]; then
cross test --release --locked --target=${{ matrix.target }} --verbose
else
cargo test --release --locked --target=${{ matrix.target }} --verbose
fi
- name: Build Archive
shell: bash
id: package
env:
target: ${{ matrix.target }}
run: |
set -euxo pipefail
bin=${GITHUB_REPOSITORY##*/}
dist_dir=`pwd`/dist
name=$bin-$target
executable=target/$target/release/$bin
if [[ "$RUNNER_OS" == "Windows" ]]; then
executable=$executable.exe
fi
mkdir $dist_dir
cp $executable $dist_dir
cd $dist_dir
if [[ "$RUNNER_OS" == "Windows" ]]; then
archive=$dist_dir/$name.zip
sha=$dist_dir/$name.sha256
7z a $archive *
certutil -hashfile $archive sha256 | grep -E [A-Fa-f0-9]{64} > $sha
echo "archive=dist/$name.zip" >> $GITHUB_OUTPUT
echo "sha=dist/$name.sha256" >> $GITHUB_OUTPUT
else
archive=$dist_dir/$name.tar.gz
sha=$dist_dir/$name.sha256
tar -czf $archive *
shasum -a 256 $archive > $sha
echo "archive=dist/$name.tar.gz" >> $GITHUB_OUTPUT
echo "sha=dist/$name.sha256" >> $GITHUB_OUTPUT
fi
- name: Publish Archive and SHA
if: env.ACT != 'true'
uses: softprops/action-gh-release@v2
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
with:
files: |
${{ steps.package.outputs.archive }}
${{ steps.package.outputs.sha }}
tag_name: v${{ env.RELEASE_VERSION }}
name: "v${{ env.RELEASE_VERSION }}"
body_path: artifacts/changelog.md
prerelease: false
- name: Add artifacts
shell: bash
run: |
[[ -d artifacts ]] || mkdir -p artifacts
cp ${{ steps.package.outputs.archive }} artifacts/
cp ${{ steps.package.outputs.sha }} artifacts/
- name: Upload artifacts
uses: actions/upload-artifact@v4
with:
name: artifacts-v${{ env.RELEASE_VERSION }}-${{ matrix.target }}
path: artifacts
overwrite: true
publish-homebrew-formula:
needs: [publish-github-release]
name: Update Homebrew formulas
runs-on: ubuntu-latest
steps:
- name: Check if actor is repository owner
if: ${{ github.actor != github.repository_owner && env.ACT != 'true' }}
run: |
echo "You are not authorized to run this workflow."
exit 1
- name: Checkout repository
uses: actions/checkout@v4
with:
fetch-depth: 1
- name: Get release artifacts
uses: actions/download-artifact@v4
with:
path: artifacts
merge-multiple: true
- name: Set release assets and version
shell: bash
run: |
# Set environment variables
macos_sha="$(cat ./artifacts/loki-x86_64-apple-darwin.sha256 | awk '{print $1}')"
echo "MACOS_SHA=$macos_sha" >> $GITHUB_ENV
macos_sha_arm="$(cat ./artifacts/loki-aarch64-apple-darwin.sha256 | awk '{print $1}')"
echo "MACOS_SHA_ARM=$macos_sha_arm" >> $GITHUB_ENV
linux_sha="$(cat ./artifacts/loki-x86_64-unknown-linux-musl.sha256 | awk '{print $1}')"
echo "LINUX_SHA=$linux_sha" >> $GITHUB_ENV
release_version="$(cat ./artifacts/release-version)"
echo "RELEASE_VERSION=$release_version" >> $GITHUB_ENV
- name: Validate release environment variables
run: |
echo "Release SHA macos: ${{ env.MACOS_SHA }}"
echo "Release SHA macos-arm: ${{ env.MACOS_SHA_ARM }}"
echo "Release SHA linux musl: ${{ env.LINUX_SHA }}"
echo "Release version: ${{ env.RELEASE_VERSION }}"
- name: Execute Homebrew packaging script
if: env.ACT != 'true'
run: |
# run packaging script
python "./deployment/homebrew/packager.py" ${{ env.RELEASE_VERSION }} "./deployment/homebrew/loki.rb.template" "./loki.rb" ${{ env.MACOS_SHA }} ${{ env.MACOS_SHA_ARM }} ${{ env.LINUX_SHA }}
- name: Push changes to Homebrew tap
if: env.ACT != 'true'
env:
TOKEN: ${{ secrets.LOKI_GITHUB_TOKEN }}
run: |
# push to Git
git config --global user.name "Dark-Alex-17"
git config --global user.email "alex.j.tusa@gmail.com"
git clone https://Dark-Alex-17:${{ secrets.LOKI_GITHUB_TOKEN }}@github.com/Dark-Alex-17/homebrew-loki.git
rm homebrew-loki/Formula/loki.rb
cp loki.rb homebrew-loki/Formula
cd homebrew-loki
git add .
git diff-index --quiet HEAD || git commit -am "Update formula for Loki release ${{ env.RELEASE_VERSION }}"
git push https://$TOKEN@github.com/Dark-Alex-17/homebrew-loki.git
publish-crate:
needs: publish-github-release
name: Publish Crate
runs-on: ubuntu-latest
steps:
- name: Check if actor is repository owner
if: ${{ github.actor != github.repository_owner && env.ACT != 'true' }}
run: |
echo "You are not authorized to run this workflow."
exit 1
- name: Checkout
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Get bumped Cargo files (Act)
if: env.ACT == 'true'
uses: actions/download-artifact@v4
with:
name: bumped-cargo-files
path: ${{ github.workspace }}
- name: Ensure repository is up-to-date
if: env.ACT != 'true'
run: |
git fetch --all
git pull
- name: Install Rust stable
uses: dtolnay/rust-toolchain@stable
- uses: katyo/publish-crates@v2
if: env.ACT != 'true'
with:
registry-token: ${{ secrets.CARGO_REGISTRY_TOKEN }}
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/target
/tmp
/.env
!cli/**
/.idea/
/loki.iml
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# Default ignored files
/shelf/
/workspace.xml
# Editor-based HTTP Client requests
/httpRequests/
# Datasource local storage ignored files
/dataSources/
/dataSources.local.xml
# Zeppelin ignored files
/ZeppelinRemoteNotebooks/
+8
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repos:
- hooks:
- id: commitizen
- id: commitizen-branch
stages:
- pre-push
repo: https://github.com/commitizen-tools/commitizen
rev: v3.30.0
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## v0.1.1 (2025-11-08)
## v0.1.0 (2025-11-07)
### Refactor
- Updated to the most recent Rust version with 2024 syntax
## v0.0.1 (2025-11-07)
### Feat
- Added the agents directory to sysinfo output
- Added built-in macros
- Updated the example role configuration file to also have the prompt field
- Updated the code role
- Secret injection as environment variables into agent tools
- Removed the server functionality
- Require Vault set up for first-time setup so all passed in secrets can be encrypted right off the bat
- Added static completions via a --completions flag
- Support for secret injection into the global config file (API keys, for example)
- Improved MCP handling toggle handling
- Secret injection into the MCP configuration
- added REPL support for interacting with the Loki vault
- Integrated gman with Loki to create a vault and added flags to configure the Loki vault
- Added a default session to the jira helper to make interaction more natural
- Created the repo-analyzer role
- Created the coder and sql agents
- Cleaned the built-in functions to not have leftover dependencies
- Created additional built-in roles for slack, repo analysis, and github
- Install built-in agents
- Embedded baseline MCP config and global tools
### Fix
- Corrected a typo for sourcing the bash utility script in some agent definitions
### Refactor
- Changed the name of the summary_prompt setting to summary_context_prompt
- Renamed summarize_prompt setting to summarization_prompt
- Renamed the compress_threshold setting to compression_threshold
- Migrated around the location of some of the more large documents for documentation
- Factored out the macros structs from the large config module
- Refactored mcp_servers and function_calling to mcp_server_support and function_calling_support to make the purpose of the fields more clear
- Refactored the use_mcp_servers field to enabled_mcp_servers to make the purpose of the field more clear
- Refactored use_tools field to enabled_tools field to make the use of the field more clear
- Removed the use of the tools.txt file and added tool visibility declarations to the global configuration file
- Agents that depend on global tools now have all binaries compiled and stored in the agent's bin directory so multiple agents can run at once
- Removed the git MCP server and used the newer, better mcp-server-docker for local docker integration
- Renamed the argument for the --completions flag to SHELL
- Updated the instructions for the jira-helper agent
- Modified the default PS1 look
- Fixed a linting issue for Windows builds
- Changed the name of agent_prelude to agent_session to make its purpose more clear
- Removed leftover javascript function support; will not implement
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# Contributor Covenant Code of Conduct
## Our Pledge
We as members, contributors, and leaders pledge to make participation in our
community a harassment-free experience for everyone, regardless of age, body
size, visible or invisible disability, ethnicity, sex characteristics, gender
identity and expression, level of experience, education, socio-economic status,
nationality, personal appearance, race, religion, or sexual identity
and orientation.
We pledge to act and interact in ways that contribute to an open, welcoming,
diverse, inclusive, and healthy community.
## Our Standards
Examples of behavior that contributes to a positive environment for our
community include:
* Demonstrating empathy and kindness toward other people
* Being respectful of differing opinions, viewpoints, and experiences
* Giving and gracefully accepting constructive feedback
* Accepting responsibility and apologizing to those affected by our mistakes,
and learning from the experience
* Focusing on what is best not just for us as individuals, but for the
overall community
Examples of unacceptable behavior include:
* The use of sexualized language or imagery, and sexual attention or
advances of any kind
* Trolling, insulting or derogatory comments, and personal or political attacks
* Public or private harassment
* Publishing others' private information, such as a physical or email
address, without their explicit permission
* Other conduct which could reasonably be considered inappropriate in a
professional setting
## Enforcement Responsibilities
Community leaders are responsible for clarifying and enforcing our standards of
acceptable behavior and will take appropriate and fair corrective action in
response to any behavior that they deem inappropriate, threatening, offensive,
or harmful.
Community leaders have the right and responsibility to remove, edit, or reject
comments, commits, code, wiki edits, issues, and other contributions that are
not aligned to this Code of Conduct, and will communicate reasons for moderation
decisions when appropriate.
## Scope
This Code of Conduct applies within all community spaces, and also applies when
an individual is officially representing the community in public spaces.
Examples of representing our community include using an official e-mail address,
posting via an official social media account, or acting as an appointed
representative at an online or offline event.
## Enforcement
Instances of abusive, harassing, or otherwise unacceptable behavior may be
reported to the community leaders responsible for enforcement at
alex.j.tusa@gmail.com.
All complaints will be reviewed and investigated promptly and fairly.
All community leaders are obligated to respect the privacy and security of the
reporter of any incident.
## Enforcement Guidelines
Community leaders will follow these Community Impact Guidelines in determining
the consequences for any action they deem in violation of this Code of Conduct:
### 1. Correction
**Community Impact**: Use of inappropriate language or other behavior deemed
unprofessional or unwelcome in the community.
**Consequence**: A private, written warning from community leaders, providing
clarity around the nature of the violation and an explanation of why the
behavior was inappropriate. A public apology may be requested.
### 2. Warning
**Community Impact**: A violation through a single incident or series
of actions.
**Consequence**: A warning with consequences for continued behavior. No
interaction with the people involved, including unsolicited interaction with
those enforcing the Code of Conduct, for a specified period of time. This
includes avoiding interactions in community spaces as well as external channels
like social media. Violating these terms may lead to a temporary or
permanent ban.
### 3. Temporary Ban
**Community Impact**: A serious violation of community standards, including
sustained inappropriate behavior.
**Consequence**: A temporary ban from any sort of interaction or public
communication with the community for a specified period of time. No public or
private interaction with the people involved, including unsolicited interaction
with those enforcing the Code of Conduct, is allowed during this period.
Violating these terms may lead to a permanent ban.
### 4. Permanent Ban
**Community Impact**: Demonstrating a pattern of violation of community
standards, including sustained inappropriate behavior, harassment of an
individual, or aggression toward or disparagement of classes of individuals.
**Consequence**: A permanent ban from any sort of public interaction within
the community.
## Attribution
This Code of Conduct is adapted from the [Contributor Covenant][homepage],
version 2.0, available at
https://www.contributor-covenant.org/version/2/0/code_of_conduct.html.
Community Impact Guidelines were inspired by [Mozilla's code of conduct
enforcement ladder](https://github.com/mozilla/diversity).
[homepage]: https://www.contributor-covenant.org
For answers to common questions about this code of conduct, see the FAQ at
https://www.contributor-covenant.org/faq. Translations are available at
https://www.contributor-covenant.org/translations.
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# Contributing
Contributors are very welcome! **No contribution is too small and all contributions are valued.**
## Rust
You'll need to have the stable Rust toolchain installed in order to develop Loki.
The Rust toolchain (stable) can be installed via rustup using the following command:
```shell
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
```
This will install `rustup`, `rustc` and `cargo`. For more information, refer to the [official Rust installation documentation](https://www.rust-lang.org/tools/install).
## Commitizen
[Commitizen](https://github.com/commitizen-tools/commitizen?tab=readme-ov-file) is a nifty tool that helps us write better commit messages. It ensures that our
commits have a consistent style and makes it easier to generate CHANGELOGS. Additionally,
Commitizen is used to run pre-commit checks to enforce style constraints.
To install `commitizen` and the `pre-commit` prerequisite, run the following command:
```shell
python3 -m pip install commitizen pre-commit
```
### Commitizen Quick Guide
To see an example commit to get an idea for the Commitizen style, run:
```shell
cz example
```
To see the allowed types of commits and their descriptions, run:
```shell
cz info
```
If you'd like to create a commit using Commitizen with an interactive prompt to help you get
comfortable with the style, use:
```shell
cz commit
```
## Setup workspace
1. Clone this repo
2. Run `cargo test` to set up hooks
3. Make changes
4. Run the application using `make run` or `cargo run`
5. Commit changes. This will trigger pre-commit hooks that will run format, test and lint. If there are errors or
warnings from Clippy, please fix them.
6. Push your code to a new branch named after the feature/bug/etc. you're adding. This will trigger pre-push hooks that
will run lint and test.
7. Create a PR
### CI/CD Testing with Act
If you also are planning on testing out your changes before pushing them with [Act](https://github.com/nektos/act), you will need to set up `act`,
`docker`, and configure your local system to run different architectures:
1. Install `docker` by following the instructions on the [official Docker installation page](https://docs.docker.com/get-docker/).
2. Install `act` by following the instructions on the [official Act installation page](https://nektosact.com/installation/index.html).
3. Install `binfmt` on your system once so that `act` can run the correct architecture for the CI/CD workflows.
You can do this by running:
```shell
sudo docker run --rm --privileged tonistiigi/binfmt --install all
```
Then, you can run workflows locally without having to commit and see if the GitHub action passes or fails.
**For example**: To test the [release.yml](.github/workflows/release.yaml) workflow locally, you can run:
```shell
act -W .github/workflows/release.yml --input_type bump=minor
```
## Questions? Reach out to me!
If you encounter any questions while developing Loki, please don't hesitate to reach out to me at
alex.j.tusa@gmail.com. I'm happy to help contributors in any way I can, regardless of if they're new or experienced!
Generated
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+138
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[package]
name = "loki-ai"
version = "0.1.1"
edition = "2024"
authors = ["Alex Clarke <alex.j.tusa@gmail.com>"]
description = "An all-in-one, batteries included LLM CLI Tool"
keywords = ["chatgpt", "llm", "cli", "ai", "repl"]
homepage = "https://github.com/Dark-Alex-17/loki"
repository = "https://github.com/Dark-Alex-17/loki"
categories = ["command-line-utilities"]
readme = "README.md"
license = "MIT"
rust-version = "1.89.0"
exclude = [".github", "CONTRIBUTING.md"]
[dependencies]
anyhow = "1.0.69"
bytes = "1.4.0"
clap = { version = "4.5.40", features = ["cargo", "derive", "wrap_help"] }
dirs = "6.0.0"
futures-util = "0.3.29"
inquire = "0.7.0"
is-terminal = "0.4.9"
reedline = "0.40.0"
serde = { version = "1.0.152", features = ["derive"] }
serde_json = { version = "1.0.93", features = ["preserve_order"] }
serde_yaml = "0.9.17"
tokio = { version = "1.34.0", features = [
"rt",
"time",
"macros",
"signal",
"rt-multi-thread",
"full",
] }
tokio-graceful = "0.2.2"
tokio-stream = { version = "0.1.15", default-features = false, features = [
"sync",
] }
crossterm = "0.28.1"
chrono = "0.4.23"
bincode = { version = "2.0.0", features = [
"serde",
"std",
], default-features = false }
parking_lot = "0.12.1"
fancy-regex = "0.14.0"
base64 = "0.22.0"
nu-ansi-term = "0.50.0"
async-trait = "0.1.74"
textwrap = "0.16.0"
ansi_colours = "1.2.2"
reqwest-eventsource = "0.6.0"
log = "0.4.28"
log4rs = { version = "1.4.0", features = ["file_appender"] }
shell-words = "1.1.0"
sha2 = "0.10.8"
unicode-width = "0.2.0"
async-recursion = "1.1.1"
http = "1.1.0"
http-body-util = "0.1"
hyper = { version = "1.0", features = ["full"] }
hyper-util = { version = "0.1", features = ["server-auto", "client-legacy"] }
time = { version = "0.3.36", features = ["macros"] }
indexmap = { version = "2.2.6", features = ["serde"] }
hmac = "0.12.1"
aws-smithy-eventstream = "0.60.4"
urlencoding = "2.1.3"
unicode-segmentation = "1.11.0"
json-patch = { version = "4.0.0", default-features = false }
bitflags = "2.5.0"
path-absolutize = "3.1.1"
hnsw_rs = "0.3.0"
rayon = "1.10.0"
uuid = { version = "1.9.1", features = ["v4"] }
scraper = { version = "0.23.1", default-features = false, features = [
"deterministic",
] }
sys-locale = "0.3.1"
html_to_markdown = "0.1.0"
rust-embed = "8.5.0"
os_info = { version = "3.8.2", default-features = false }
bm25 = { version = "2.0.1", features = ["parallelism"] }
which = "8.0.0"
fuzzy-matcher = "0.3.7"
terminal-colorsaurus = "0.4.8"
duct = "1.0.0"
argc = "1.23.0"
strum_macros = "0.27.2"
indoc = "2.0.6"
rmcp = { version = "0.6.1", features = ["client", "transport-child-process"] }
num_cpus = "1.17.0"
rustpython-parser = "0.4.0"
rustpython-ast = "0.4.0"
colored = "3.0.0"
clap_complete = { version = "4.5.58", features = ["unstable-dynamic"] }
gman = "0.2.3"
clap_complete_nushell = "4.5.9"
[dependencies.reqwest]
version = "0.12.0"
features = [
"json",
"multipart",
"socks",
"rustls-tls",
"rustls-tls-native-roots",
]
default-features = false
[dependencies.syntect]
version = "5.0.0"
default-features = false
features = ["parsing", "regex-onig", "plist-load"]
[target.'cfg(target_os = "macos")'.dependencies]
crossterm = { version = "0.28.1", features = ["use-dev-tty"] }
[target.'cfg(target_os = "linux")'.dependencies]
arboard = { version = "3.3.0", default-features = false, features = [
"wayland-data-control",
] }
[target.'cfg(not(any(target_os = "linux", target_os = "android", target_os = "emscripten")))'.dependencies]
arboard = { version = "3.3.0", default-features = false }
[dev-dependencies]
pretty_assertions = "1.4.0"
rand = "0.9.0"
[[bin]]
name = "loki"
path = "src/main.rs"
[profile.release]
lto = true
strip = true
opt-level = "z"
+22
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The MIT License (MIT)
Copyright (c) 2025 sigoden
Copyright (c) 2025 Alexander J. Clarke
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
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# loki
An all-in-one, batteries included LLM CLI tool
# Loki: All-in-one, batteries-included LLM CLI Tool
![Test](https://github.com/Dark-Alex-17/loki/actions/workflows/ci.yaml/badge.svg)
![LOC](https://tokei.rs/b1/github/Dark-Alex-17/loki?category=code)
[![crates.io link](https://img.shields.io/crates/v/loki-ai.svg)](https://crates.io/crates/loki-ai)
![Release](https://img.shields.io/github/v/release/Dark-Alex-17/loki?color=%23c694ff)
![Crate.io downloads](https://img.shields.io/crates/d/loki-ai?label=Crate%20downloads)
[![GitHub Downloads](https://img.shields.io/github/downloads/Dark-Alex-17/loki/total.svg?label=GitHub%20downloads)](https://github.com/Dark-Alex-17/loki/releases)
Loki is an all-in-one, batteries-included, LLM CLI tool featuring Shell Assistant, CLI & REPL Mode, RAG, AI Tools &
Agents, and More.
It is designed to include a number of useful agents, roles, macros, and more so users can get up and running with Loki
in as little time as possible.
![Agent example](./docs/images/agents/sql.gif)
Coming from [AIChat](https://github.com/sigoden/aichat)? Follow the [migration guide](./docs/AICHAT-MIGRATION.md) to get started.
## Quick Links
* [AIChat Migration Guide](./docs/AICHAT-MIGRATION.md): Coming from AIChat? Follow the migration guide to get started.
* [History](#history): A history of how Loki came to be.
* [Installation](#install): Install Loki
* [Getting Started](#getting-started): Get started with Loki by doing first-run setup steps.
* [REPL](./docs/REPL.md): Interactive Read-Eval-Print Loop for conversational interactions with LLMs and Loki.
* [Custom REPL Prompt](./docs/REPL-PROMPT.md): Customize the REPL prompt to provide useful contextual information.
* [Vault](./docs/VAULT.md): Securely store and manage sensitive information such as API keys and credentials.
* [Shell Integrations](./docs/SHELL-INTEGRATIONS.md): Seamlessly integrate Loki with your shell environment for enhanced command-line assistance.
* [Function Calling](./docs/function-calling/TOOLS.md#Tools): Leverage function calling capabilities to extend Loki's functionality with custom tools
* [Creating Custom Tools](./docs/function-calling/CUSTOM-TOOLS.md): You can create your own custom tools to enhance Loki's capabilities.
* [Create Custom Python Tools](./docs/function-calling/CUSTOM-TOOLS.md#custom-python-based-tools)
* [Create Custom Bash Tools](./docs/function-calling/CUSTOM-BASH-TOOLS.md)
* [Bash Prompt Utilities](./docs/function-calling/BASH-PROMPT-HELPERS.md)
* [First-Class MCP Server Support](./docs/function-calling/MCP-SERVERS.md): Easily connect and interact with MCP servers for advanced functionality.
* [Macros](./docs/MACROS.md): Automate repetitive tasks and workflows with Loki "scripts" (macros).
* [RAG](./docs/RAG.md): Retrieval-Augmented Generation for enhanced information retrieval and generation.
* [Sessions](/docs/SESSIONS.md): Manage and persist conversational contexts and settings across multiple interactions.
* [Roles](./docs/ROLES.md): Customize model behavior for specific tasks or domains.
* [Agents](/docs/AGENTS.md): Leverage AI agents to perform complex tasks and workflows.
* [Environment Variables](./docs/ENVIRONMENT-VARIABLES.md): Override and customize your Loki configuration at runtime with environment variables.
* [Client Configurations](./docs/clients/CLIENTS.md): Configuration instructions for various LLM providers.
* [Patching API Requests](./docs/clients/PATCHES.md): Learn how to patch API requests for advanced customization.
* [Custom Themes](./docs/THEMES.md): Change the look and feel of Loki to your preferences with custom themes.
---
## History
Loki originally started as a fork of the fantastic [AIChat CLI](https://github.com/sigoden/aichat). The purpose was to
simply fix a bug in how MCP servers worked with AIChat so that I could specify different ones for agents. However, it
has since evolved far beyond that and become a passion project with a life of its own!
Loki now has first class MCP server support (with support for local and remote servers alike), a built-in vault for
interpolating secrets in configuration files, built-in agents, built-in macros, dynamic tab completions, integrated
custom functions (no `argc` dependency), improved documentation, and much more with many more plans for the future!
The original kudos goes out to all the developers of the wonderful AIChat project!
---
## Prerequisites
Loki requires the following tools to be installed on your system:
* [jq](https://github.com/jqlang/jq)
* `brew install jq`
* [jira (optional)](https://github.com/ankitpokhrel/jira-cli/wiki/Installation) (For the `jira-helper` agent)
* `brew tap ankitpokhrel/jira-cli && brew install jira-cli`
* You'll need to [create a JIRA API token](https://id.atlassian.com/manage-profile/security/api-tokens) for authentication
* Then, save it as an environment variable to your shell profile:
```sh
# ~/.bashrc or ~/.zshrc
export JIRA_API_TOKEN="your_jira_api_token_here"
```
* Then run `jira init`, select installation type as `cloud`, and provide the required details to generate a config
file for the Jira CLI.
* [usql](https://github.com/xo/usql) (For the `sql` agent)
* `brew install xo/xo/usql`
* [docker](https://docs.docker.com/engine/install/)
* [uv](https://docs.astral.sh/uv/getting-started/installation/)
* `curl -LsSf https://astral.sh/uv/install.sh | sh`
These tools are used to provide various functionalities within Loki, such as document processing, JSON manipulation,
interaction with Jira, and they are used within agents and tools.
## Install
### Cargo
If you have Cargo installed, then you can install `loki` from Crates.io:
```shell
cargo install loki-ai # Binary name is `loki`
# If you encounter issues installing, try installing with '--locked'
cargo install --locked loki-ai
```
### Homebrew (Mac/Linux)
To install Loki from Homebrew, install the `loki` tap. Then you'll be able to install `loki`:
```shell
brew tap Dark-Alex-17/loki
brew install loki
# If you need to be more specific, use:
brew install Dark-Alex-17/loki/loki
```
To upgrade `loki` using Homebrew:
```shell
brew upgrade loki
```
### Scripts
#### Linux/MacOS (`bash`)
You can use the following command to run a bash script that downloads and installs the latest version of `loki` for your
OS (Linux/MacOS) and architecture (x86_64/arm64):
```shell
curl -fsSL https://raw.githubusercontent.com/Dark-Alex-17/loki/main/install_loki.sh | bash
```
#### Windows/Linux/MacOS (`PowerShell`)
You can use the following command to run a PowerShell script that downloads and installs the latest version of `loki`
for your OS (Windows/Linux/MacOS) and architecture (x86_64/arm64):
```powershell
powershell -NoProfile -ExecutionPolicy Bypass -Command "iwr -useb https://raw.githubusercontent.com/Dark-Alex-17/loki/main/scripts/install_loki.ps1 | iex"
```
### Manual
Binaries are available on the [releases](https://github.com/Dark-Alex-17/loki/releases) page for the following platforms:
| Platform | Architecture(s) |
|----------------|-----------------|
| macOS | x86_64, arm64 |
| Linux GNU/MUSL | x86_64, aarch64 |
| Windows | x86_64, aarch64 |
#### Windows Instructions
To use a binary from the releases page on Windows, do the following:
1. Download the latest [binary](https://github.com/Dark-Alex-17/loki/releases) for your OS.
2. Use 7-Zip or TarTool to unpack the Tar file.
3. Run the executable `loki.exe`!
#### Linux/MacOS Instructions
To use a binary from the releases page on Linux/MacOS, do the following:
1. Download the latest [binary](https://github.com/Dark-Alex-17/loki/releases) for your OS.
2. `cd` to the directory where you downloaded the binary.
3. Extract the binary with `tar -C /usr/local/bin -xzf loki-<arch>.tar.gz` (Note: This may require `sudo`)
4. Now you can run `loki`!
## Getting Started
After installation, you can generate the configuration files and directories by simply running:
```sh
loki --info
```
Then, you need to set up the Loki vault by creating a vault password file. Loki will do this for you automatically and
guide you through the process when you first attempt to access the vault. So, to get started, you can run:
```sh
loki --list-secrets
```
### First Time Setup
In order for Loki to function correctly, you'll need to add a few secrets to the Loki vault so the MCP servers can
function.
**GitHub MCP Server:**
* `GITHUB_PERSONAL_ACCESS_TOKEN` - A GitHub Personal Access Token with `repo` and `workflow` scopes.
See [Creating a GitHub Personal Access Token](https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens)
#### Add the secrets to the Loki vault
You can add the secrets to the Loki vault using the following commands (First time use will prompt you to create a vault
password file):
```sh
loki --add-secret GITHUB_PERSONAL_ACCESS_TOKEN
```
### Tab-Completions
You can also enable tab completions to make using Loki easier. To do so, add the following to your shell profile:
```shell
# Bash
# (add to: `~/.bashrc`)
source <(COMPLETE=bash loki)
# Zsh
# (add to: `~/.zshrc`)
source <(COMPLETE=zsh loki)
# Fish
# (add to: `~/.config/fish/config.fish`)
source <(COMPLETE=fish loki | psub)
# Elvish
# (add to: `~/.elvish/rc.elv`)
eval (E:COMPLETE=elvish loki | slurp)
# PowerShell
# (add to: `$PROFILE`)
$env:COMPLETE = "powershell"
loki | Out-String | Invoke-Expression
```
### Shell Integration
You can integrate Loki's Shell Assistant into your shell for enhanced command-line assistance. Add the code in the
corresponding [shell integration script](./scripts/shell-integration) to your shell. Then, you can invoke Loki to convert natural language to
shell commands by pressing `Alt-e`. For example:
```shell
$ find all markdown files<Alt-e>
# Will be converted to:
find . -name "*.md"
```
## Configuration
The location of the global Loki configuration varies between systems, so you can use the following command to find your
`config.yaml` file:
```shell
loki --info | grep 'config_file' | awk '{print $2}'
```
The configuration file consists of a number of settings. To see a full example configuration file with every setting
defined, refer to the [example configuration file](./config.example.yaml).
### Default LLM
The following settings are available to configure the default LLM that is used when you start Loki, and its
hyperparameters:
| Setting | Description |
|---------------|---------------------------------------------------------------------------------------------------------------------------------------------------------|
| `model` | The default LLM to use when no model is provided |
| `temperature` | The default `temperature` parameter for all models (0,1); Used unless explicitly overridden |
| `top_p` | The default `top_p` hyperparameter value to use for all models, with a range of (0,1) (or (0,2) for some models); <br>Used unless explicitly overridden |
### CLI Behavior
You can use the following settings to modify the behavior of Loki:
| Setting | Default Value | Description |
|---------------|---------------|-------------------------------------------------------------------------------------------------------------------------------------|
| `stream` | `true` | Controls whether to use stream-style APIs when querying for completions from LLM providers |
| `save` | `true` | Controls whether to save each query/response to every model to `messages.md` for posterity; Useful for debugging |
| `keybindings` | `emacs` | Specifies which keybinding schema to use; can either be `emacs` or `vi` |
| `editor` | `null` | What text editor Loki should use to edit the input buffer or session (e.g. `vim`, `emacs`, `nano`, `hx`); <br>Defaults to `$EDITOR` |
| `wrap` | `no` | Controls whether text is wrapped (can be `no`, `auto`, or some `<max_width>` |
| `wrap_code` | `false` | Enables or disables the wrapping of code blocks |
### Preludes
Preludes let you define the default behavior for the different operating modes of Loki. The available settings are
shown below:
| Setting | Description |
|-----------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| `repl_prelude` | This setting lets you specify a default `session` or `role` to use when starting Loki in [REPL](./docs/REPL.md) mode. <br>Values can be <ul><li>`role:<name>` to define a role</li><li>`session:<name>` to define a session</li><li>`<session>:<role>` to define both a session and a role to use</li></ul> |
| `cmd_prelude` | This setting lets you specify a default `session` or `role` to use when running one-off queries in Loki via the CLI. <br>Values can be <ul><li>`role:<name>` to define a role</li><li>`session:<name>` to define a session</li><li>`<session>:<role>` to define both a session and a role to use</li></ul> |
| `agent_session` | This setting is used to specify a default session that all agents should start into, unless otherwise specified in the agent configuration. (e.g. `temp`, `default`) |
### Appearance
The appearance of Loki can be modified using the following settings:
| Setting | Default Value | Description |
|---------------|---------------|------------------------------------------------------|
| `highlight` | `true` | This setting enables or disables syntax highlighting |
| `light_theme` | `false` | This setting toggles light mode in Loki |
### Miscellaneous Settings
| Setting | Default Value | Description |
|----------------------|---------------|------------------------------------------------------------------------------------------------------------------|
| `user_agent` | `null` | The name of the `User-Agent` that should be passed in the `User-Agent` header on all requests to model providers |
| `save_shell_history` | `true` | Enables or disables REPL command history |
## Creator
* [Alex Clarke](https://github.com/Dark-Alex-17)
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# Security Policy
## Supported Versions
Only latest version of the software will be supported with security patches.
| Version | Supported |
| -------- | ------------------ |
| latest | :white_check_mark: |
## Reporting a Vulnerability
If you find a vulnerability, please reach out to me via email (alex.j.tusa@gmail.com).
If you yourself decide you'd like to tackle a fix, please submit a PR with the fix and I'll review it as soon as
possible.
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# Coder
An AI agent that assists you with your coding tasks.
## Features
- 🏗️ Intelligent project structure creation and management
- 🖼️ Convert screenshots into clean, functional code
- 📁 Comprehensive file system operations (create folders, files, read/write files)
- 🧐 Advanced code analysis and improvement suggestions
- 📊 Precise diff-based file editing for controlled code modifications
## Similar Projects
- https://github.com/Doriandarko/claude-engineer
- https://github.com/paul-gauthier/aider
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name: Coder
description: An AI agent that assists you with your coding tasks
version: 0.1.0
global_tools:
- fs_mkdir.sh
- fs_ls.sh
- fs_patch.sh
- fs_cat.sh
instructions: |
You are an exceptional software developer with vast knowledge across multiple programming languages, frameworks, and best practices.
Your capabilities include:
1. Creating and managing project structures
2. Writing, debugging, and improving code across multiple languages
3. Providing architectural insights and applying design patterns
4. Staying current with the latest technologies and best practices
5. Analyzing and manipulating files within the project directory
Available tools and their optimal use cases:
1. fs_mkdir: Create new directories in the project structure.
2. fs_create: Generate new files with specified contents.
3. fs_patch: Examine and modify existing files.
4. fs_cat: View the contents of existing files without making changes.
5. fs_ls: Understand the current project structure or locate specific files.
Tool Usage Guidelines:
- Always use the most appropriate tool for the task at hand.
- For file modifications, use fs_patch. Read the file first, then apply changes if needed.
- After making changes, always review the diff output to ensure accuracy.
Project Creation and Management:
1. Start by creating a root folder for new projects.
2. Create necessary subdirectories and files within the root folder.
3. Organize the project structure logically, following best practices for the specific project type.
Code Editing Best Practices:
1. Always read the file content before making changes.
2. Analyze the code and determine necessary modifications.
3. Pay close attention to existing code structure to avoid unintended alterations.
4. Review changes thoroughly after each modification.
Always strive for accuracy, clarity, and efficiency in your responses and actions.
Answer the user's request using relevant tools (if they are available). Before calling a tool, do some analysis within <thinking></thinking> tags. First, think about which of the provided tools is the relevant tool to answer the user's request. Second, go through each of the required parameters of the relevant tool and determine if the user has directly provided or given enough information to infer a value. When deciding if the parameter can be inferred, carefully consider all the context to see if it supports a specific value. If all of the required parameters are present or can be reasonably inferred, close the thinking tag and proceed with the tool call. BUT, if one of the values for a required parameter is missing, DO NOT invoke the function (not even with fillers for the missing params) and instead, ask the user to provide the missing parameters. DO NOT ask for more information on optional parameters if it is not provided.
Do not reflect on the quality of the returned search results in your response.
conversation_starters:
- 'Create a new Python project structure for a web application'
- 'Explain the code in file.py and suggest improvements'
- 'Search for the latest best practices in React development'
- 'Help me debug this error: [paste your error message]'
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#!/usr/bin/env bash
set -e
# @env LLM_OUTPUT=/dev/stdout The output path
# shellcheck disable=SC1090
source "$LLM_PROMPT_UTILS_FILE"
# @cmd Create a new file at the specified path with the given contents.
# @option --path! The path where the file should be created
# @option --contents! The contents of the file
# shellcheck disable=SC2154
fs_create() {
guard_path "$argc_path" "Create '$argc_path'?"
mkdir -p "$(dirname "$argc_path")"
printf "%s" "$argc_contents" > "$argc_path"
echo "File created: $argc_path" >> "$LLM_OUTPUT"
}
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# Demo
This agent serves as a demo to guide agent development and showcase various agent capabilities.
To enable tools, Loki will look for the first `tools.py` or `tools.sh` file it finds in this directory.
The base configuration using `tools.py`. To switch to using `tools.sh`, rename or remove `tools.py`.
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name: Demo
description: An AI agent that demonstrates agent capabilities
version: 0.1.0
global_tools:
- execute_command.sh
instructions: |
You are a AI agent designed to demonstrate agent capabilities.
<tools>
{{__tools__}}
</tools>
<system>
os: {{__os__}}
os_family: {{__os_family__}}
arch: {{__arch__}}
shell: {{__shell__}}
locale: {{__locale__}}
now: {{__now__}}
cwd: {{__cwd__}}
</system>
<user>
username: {{username}}
</user>
variables:
- name: username
description: Your user name
conversation_starters:
- What is my username?
- What is my current shell?
- What is my ip?
- How much disk space is left on my PC??
- How to create an agent?
documents:
- README.md
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import urllib.request
def get_ipinfo():
"""
Get the ip info
"""
with urllib.request.urlopen("https://httpbin.org/ip") as response:
data = response.read()
return data.decode('utf-8')
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#!/usr/bin/env bash
set -e
# @env LLM_OUTPUT=/dev/stdout The output path
# @cmd Get the ip info
get_ipinfo() {
curl -fsSL https://httpbin.org/ip >> "$LLM_OUTPUT"
}
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# Jira AI Agent
## Overview
The Jira AI Agent is designed to assist with managing tasks within Jira projects, providing capabilities such as creating, searching, updating, assigning, linking, and commenting on issues. Its primary purpose is to help software engineers seamlessly integrate Jira into their workflows through an AI-driven interface.
## Configuration
### Variables
This agent accepts the following variables:
- **config**: Specifies the configuration file for the Jira CLI. This configuration should be located at `~/.config/.jira/<config_name>.yml`. Example: `work`.
- **project**: The Jira project key where operations are executed. Example: `PAN`.
### Customization
#### For a User's Specific Jira Instance
1. **Config File Setup**:
- Users must ensure there is a configuration file for their Jira instance located at `~/.config/.jira/`. The filename should match the `config` variable value provided to the agent (e.g., for `config` set to `work`, ensure a `work.yml` exists).
2. **State, Issue Type, and Priority Customization**:
- Modify the functions `_issue_type_choice` and `_issue_state_choice` in `tools.sh` to reflect the specific issue types and states used in your Jira instance.
- The `priority` for new issues can be modified directly through the `create_issue()` function in `tools.sh` with options set to the values available in your Jira instance (e.g., Medium, Highest, etc.).
## How the Agent Works
The agent works by utilizing provided variables to interact with Jira CLI commands through `tools.sh`. The `config` variable links directly to a `.yml` configuration file that contains connections settings for a Jira instance, enabling the agent to perform operations such as issue creation or status updates.
- **Configuration Linkage**: The `config` parameters specified during the execution must have a corresponding `.yml` configuration file at `~/.config/.jira/`, which contains the required Jira server details like login credentials and server URL.
- **Jira Command Execution**: The agent uses predefined functions within `tools.sh` to execute Jira operations. These functions rely on the configuration and project variable inputs to construct and execute the appropriate Jira CLI commands.
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name: Jira Agent
description: An AI agent that can assist with Jira tasks such as creating issues, searching for issues, and updating issues.
version: 0.1.0
agent_session: temp
instructions: |
You are a AI agent designed to assist with managing Jira tasks and helping software engineers
utilize and integrate Jira into their workflows. You can create, search, update, assign, link, and comment on issues in Jira.
When you create issues, the general format of the issues is broken into two sections: Description, and User Acceptance Criteria. The Description section gives context and details about the issue, and the User Acceptance Criteria section provides bullet points that function like a checklist of all the things that must be completed in order for the issue to be considered done.
Create issues under the {{project}} Jira project.
Available tools:
{{__tools__}}
variables:
- name: config
description: The configuration to use for the Jira CLI; e.g. work
- name: project
description: The Jira project to operate on; e.g. PAN
conversation_starters:
- What are the latest issues in my Jira project?
- Can you create a new Jira issue for me?
- What are my open Jira issues?
- Can you search for issues with the label "bug" in my Jira project?
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#!/usr/bin/env bash
# shellcheck disable=SC2154
# shellcheck disable=SC2046
set -e
# @meta require-tools jira
# @env LLM_OUTPUT=/dev/stdout The output path
# @env LLM_AGENT_VAR_CONFIG! The configuration to use for the Jira CLI; e.g. work
# @env LLM_AGENT_VAR_PROJECT! The Jira project to operate on; e.g. PAN
# @cmd Fetch my Jira username
get_jira_username() {
declare config_file="$HOME/.config/.jira/${LLM_AGENT_VAR_CONFIG}.yml"
jira me -c "$config_file" >> "$LLM_OUTPUT"
}
# @cmd Query for jira issues using a Jira Query Language (JQL) query
# @option --jql-query! The Jira Query Language query to execute
# @option --project! $LLM_AGENT_VAR_PROJECT <PROJECT> Jira project to operate on; e.g. PAN
query_jira_issues() {
declare config_file="$HOME"/.config/.jira/"${LLM_AGENT_VAR_CONFIG}".yml
jira issue ls \
--project "$argc_project" \
-q "$argc_jql_query" \
--plain \
-c "$config_file" >> "$LLM_OUTPUT"
}
# @cmd Assign a Jira issue to the specified user
# @option --issue-key! The Jira issue key, e.g. ISSUE-1
# @option --assignee! The email or display name of the user to assign the issue to
# @option --project! $LLM_AGENT_VAR_PROJECT <PROJECT> Jira project to operate on; e.g. PAN
assign_jira_issue() {
declare config_file="$HOME"/.config/.jira/"${LLM_AGENT_VAR_CONFIG}".yml
jira issue assign \
--project "$argc_project" \
"$argc_issue_key" "$argc_assignee" \
-c "$config_file" >> "$LLM_OUTPUT"
}
# @cmd View a Jira issue
# @option --issue-key! The Jira issue key, e.g. ISSUE-1
# @option --project! $LLM_AGENT_VAR_PROJECT <PROJECT> Jira project to operate on; e.g. PAN
view_issue() {
declare config_file="$HOME"/.config/.jira/"${LLM_AGENT_VAR_CONFIG}".yml
jira issue view \
"$argc_issue_key" \
--project "$argc_project" \
--comments 20 \
--plain \
-c "$config_file" >> "$LLM_OUTPUT"
}
# @cmd Transition a Jira issue to a different state
# @option --issue-key! The Jira issue key, e.g. ISSUE-1
# @option --state![`_issue_state_choice`] The Jira state of the issue
# @option --comment Add a comment to the issue
# @option --resolution Set resolution
# @option --project! $LLM_AGENT_VAR_PROJECT <PROJECT> Jira project to operate on; e.g. PAN
transition_issue() {
declare config_file="$HOME"/.config/.jira/"${LLM_AGENT_VAR_CONFIG}".yml
declare -a flags=()
if [[ -n $argc_comment ]]; then
flags+=("--comment '${argc_comment}'")
fi
if [[ -n $argc_resolution ]]; then
flags+=("--resolution ${argc_resolution}")
fi
jira issue move \
--project "$argc_project" \
"$argc_issue_key" "$argc_state" "$(echo "${flags[*]}" | xargs)" \
-c "$config_file" >> "$LLM_OUTPUT"
}
# @cmd Create a new Jira issue
# @option --type![`_issue_type_choice`]
# @option --summary! Issue summary or title
# @option --description! Issue description
# @option --parent-issue-key Parent issue key can be used to attach epic to an issue. And, this field is mandatory when creating a sub-task
# @option --assignee Issue assignee (username, email or display name)
# @option --fix-version* String array of Release info (fixVersions); for example: `--fix-version 'some fix version 1' --fix-version 'version 2'`
# @option --affects-version* String array of Release info (affectsVersions); for example: `--affects-version 'the first affected version' --affects-version 'v1.2.3'`
# @option --label* String array of issue labels; for example: `--label backend --label custom`
# @option --component* String array of issue components; for example: `--component backend --component core`
# @option --original-estimate The original estimate of the issue
# @option --priority[=Medium|Highest|High|Low|Lowest] The priority of the issue
# @option --project! $LLM_AGENT_VAR_PROJECT <PROJECT> Jira project to operate on; e.g. PAN
create_issue() {
declare config_file="$HOME"/.config/.jira/"${LLM_AGENT_VAR_CONFIG}".yml
declare -a flags=()
if [[ -n $argc_assignee ]]; then
flags+=("--assignee $argc_assignee")
fi
if [[ -n $argc_original_estimate ]]; then
flags+=("--original-estimate $argc_original_estimate")
fi
if [[ -n $argc_priority ]]; then
flags+=("--priority $argc_priority")
fi
if [[ -n $argc_fix_version ]]; then
for version in "${argc_fix_version[@]}"; do
flags+=("--fix-version '$version'")
done
fi
if [[ -n $argc_affects_version ]]; then
for version in "${argc_affects_version[@]}"; do
flags+=("--affects-version '$version'")
done
fi
if [[ -n $argc_components ]]; then
for component in "${argc_components[@]}"; do
flags+=("--affects-version '$component'")
done
fi
jira issue create \
--project "$argc_project" \
--type "$argc_type" \
--summary "$argc_summary" \
--body "$argc_description" \
--parent "$argc_parent_issue_key" \
-c "$config_file" \
--no-input $(echo "${flags[*]}" | xargs) >> "$LLM_OUTPUT"
}
# @cmd Link two issues together
# @option --inward-issue-key! Issue key of the source issue, eg: ISSUE-1
# @option --outward-issue-key! Issue key of the target issue, eg: ISSUE-2
# @option --issue-link-type! Relationship between two issues, eg: Duplicates, Blocks etc.
# @option --project! $LLM_AGENT_VAR_PROJECT <PROJECT> Jira project to operate on; e.g. PAN
link_issues() {
declare config_file="$HOME"/.config/.jira/"${LLM_AGENT_VAR_CONFIG}".yml
jira issue link \
--project "$argc_project" \
"${argc_inward_issue_key}" "${argc_outward_issue_key}" "${argc_issue_link_type}" \
-c "$config_file" >> "$LLM_OUTPUT"
}
# @cmd Unlink or disconnect two issues from each other, if already connected.
# @option --inward-issue-key! Issue key of the source issue, eg: ISSUE-1
# @option --outward-issue-key! Issue key of the target issue, eg: ISSUE-2.
# @option --project! $LLM_AGENT_VAR_PROJECT <PROJECT> Jira project to operate on; e.g. PAN
unlink_issues() {
declare config_file="$HOME"/.config/.jira/"${LLM_AGENT_VAR_CONFIG}".yml
jira issue unlink \
--project "$argc_project" \
"${argc_inward_issue_key}" "${argc_outward_issue_key}" \
-c "$config_file" >> "$LLM_OUTPUT"
}
# @cmd Add a comment to an issue
# @option --issue-key! Issue key of the source issue, eg: ISSUE-1
# @option --comment-body! Body of the comment you want to add
# @option --project! $LLM_AGENT_VAR_PROJECT <PROJECT> Jira project to operate on; e.g. PAN
add_comment_to_issue() {
declare config_file="$HOME"/.config/.jira/"${LLM_AGENT_VAR_CONFIG}".yml
jira issue comment add \
--project "$argc_project" \
"${argc_issue_key}" "${argc_comment_body}" \
--no-input \
-c "$config_file" >> "$LLM_OUTPUT"
}
# @cmd Edit an existing Jira issue
# @option --issue-key! The Jira issue key, e.g. ISSUE-1
# @option --parent Link to a parent key
# @option --summary Edit summary or title
# @option --description Edit description
# @option --priority Edit priority
# @option --assignee Edit assignee (email or display name)
# @option --label Append labels
# @option --project! $LLM_AGENT_VAR_PROJECT <PROJECT> Jira project to operate on; e.g. PAN
edit_issue() {
declare config_file="$HOME"/.config/.jira/"${LLM_AGENT_VAR_CONFIG}".yml
declare -a flags=()
if [[ -n $argc_parent ]]; then
flags+=("--parent $argc_parent")
fi
if [[ -n $argc_summary ]]; then
flags+=("--summary $argc_summary")
fi
if [[ -n $argc_description ]]; then
flags+=("--body $argc_description")
fi
if [[ -n $argc_priority ]]; then
flags+=("--priority $argc_priority")
fi
if [[ -n $argc_assignee ]]; then
flags+=("--assignee $argc_assignee")
fi
if [[ -n $argc_label ]]; then
flags+=("--label $argc_label")
fi
jira issue edit \
--project "$argc_project" \
"$argc_issue_key" $(echo "${flags[*]}" | xargs) \
--no-input \
-c "$config_file" >> "$LLM_OUTPUT"
}
_issue_type_choice() {
if [[ $LLM_AGENT_VAR_CONFIG == "work" ]]; then
echo "Story"
echo "Task"
echo "Bug"
echo "Technical Debt"
echo "Sub-task"
elif [[ $LLM_AGENT_VAR_CONFIG == "sideproject" ]]; then
echo "Task"
echo "Story"
echo "Bug"
echo "Epic"
fi
}
_issue_state_choice() {
if [[ $LLM_AGENT_VAR_CONFIG == "work" ]]; then
echo "Ready for Dev"
echo "CODE REVIEW"
echo "IN PROGRESS"
echo "Backlog"
echo "Done"
echo "TESTING"
elif [[ $LLM_AGENT_VAR_CONFIG == "sideproject" ]]; then
echo "IN CLARIFICATION"
echo "NEED TO CLARIFY"
echo "READY TO WORK"
echo "RELEASE BACKLOG"
echo "REOPEN"
echo "CODE REVIEW"
echo "IN PROGRESS"
echo "IN TESTING"
echo "TO TEST"
echo "DONE"
fi
}
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# SQL
An AI agent that helps you manage a SQL database.
> The tool script uses [usql](https://github.com/xo/usql) to interact with SQL, it supports all mainstream databases.
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name: Sql
description: An AI agent that helps you manage any SQL database
version: 0.1.0
instructions: |
You are an AI agent that manages a SQL database.
Prefix all referenced tables with the name of the schema that they are in.
For all sqlite databases, prefix each table name with 'main' as the schema
Available tools:
{{__tools__}}
variables:
- name: dsn
description: The database connection url. e.g. pgsql://user:pass@host:port
conversation_starters:
- What you can do?
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#!/usr/bin/env bash
set -e
# @meta require-tools usql
# @env LLM_OUTPUT=/dev/stdout The output path
# @env LLM_AGENT_VAR_DSN! The database connection url. e.g. pgsql://user:pass@host:port
# shellcheck disable=SC1090
source "$LLM_PROMPT_UTILS_FILE"
# @cmd Execute a SELECT query
# @option --query! SELECT SQL query to execute
read_query() {
# shellcheck disable=SC2154
if ! grep -qi '^select' <<<"$argc_query"; then
error "only SELECT queries are allowed" >&2
exit 1
fi
_run_sql "$argc_query"
}
# @cmd Execute an SQL query
# @option --query! SQL query to execute
write_query() {
guard_operation "Execute SQL?"
_run_sql "$argc_query"
}
# @cmd List all tables
list_tables() {
_run_sql "\dt+"
}
# @cmd Get the schema information for a specific table
# @option --table-name! Name of the table to describe
describe_table() {
# shellcheck disable=SC2154
_run_sql "\d $argc_table_name"
}
_run_sql() {
usql "$LLM_AGENT_VAR_DSN" -c "$1" >> "$LLM_OUTPUT"
}
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{
"mcpServers": {
"github": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"GITHUB_PERSONAL_ACCESS_TOKEN",
"ghcr.io/github/github-mcp-server"
],
"env": {
"GITHUB_PERSONAL_ACCESS_TOKEN": "{{GITHUB_PERSONAL_ACCESS_TOKEN}}"
}
},
"docker": {
"command": "uvx",
"args": ["mcp-server-docker"]
},
"slack": {
"command": "npx",
"args": ["-y", "slack-mcp-server@latest", "--transport", "stdio"],
"env": {
"SLACK_MCP_XOXC_TOKEN": "{{SLACK_MCP_XOXC_TOKEN}}",
"SLACK_MCP_XOXD_TOKEN": "{{SLACK_MCP_XOXD_TOKEN}}",
"SLACK_MCP_ADD_MESSAGE_TOOL": true
}
}
}
}
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#!/usr/bin/env python
# Usage: ./{agent_name}.py <agent-func> <agent-data>
import os
import re
import json
import sys
import importlib.util
from pathlib import Path
def _ensure_cwd_venv():
cwd = Path.cwd()
venv_dir = cwd / ".venv"
if not venv_dir.is_dir():
return
py = venv_dir / ("Scripts/python.exe" if os.name == "nt" else "bin/python")
if not py.exists():
return
if Path(sys.prefix).resolve() == venv_dir.resolve():
return
os.execv(str(py), [str(py)] + sys.argv)
_ensure_cwd_venv()
def main():
(agent_func, raw_data) = parse_argv()
agent_data = parse_raw_data(raw_data)
root_dir = "{config_dir}"
setup_env(root_dir, agent_func)
agent_tools_path = os.path.join(root_dir, "agents/{agent_name}/tools.py")
run(agent_tools_path, agent_func, agent_data)
def parse_raw_data(data):
if not data:
raise ValueError("No JSON data")
try:
return json.loads(data)
except Exception:
raise ValueError("Invalid JSON data")
def parse_argv():
agent_func = sys.argv[1]
agent_data = sys.argv[2]
if (not agent_data) or (not agent_func):
print("Usage: ./{agent_name}.py <agent-func> <agent-data>", file=sys.stderr)
sys.exit(1)
return agent_func, agent_data
def setup_env(root_dir, agent_func):
load_env(os.path.join(root_dir, ".env"))
os.environ["LLM_ROOT_DIR"] = root_dir
os.environ["LLM_AGENT_NAME"] = "{agent_name}"
os.environ["LLM_AGENT_FUNC"] = agent_func
os.environ["LLM_AGENT_ROOT_DIR"] = os.path.join(root_dir, "agents", "{agent_name}")
os.environ["LLM_AGENT_CACHE_DIR"] = os.path.join(root_dir, "cache", "{agent_name}")
def load_env(file_path):
try:
with open(file_path, "r") as f:
lines = f.readlines()
except:
return
env_vars = {}
for line in lines:
line = line.strip()
if line.startswith("#") or not line:
continue
key, *value_parts = line.split("=")
env_name = key.strip()
if env_name not in os.environ:
env_value = "=".join(value_parts).strip()
if (env_value.startswith('"') and env_value.endswith('"')) or (env_value.startswith("'") and env_value.endswith("'")):
env_value = env_value[1:-1]
env_vars[env_name] = env_value
os.environ.update(env_vars)
def run(agent_path, agent_func, agent_data):
spec = importlib.util.spec_from_file_location(
os.path.basename(agent_path), agent_path
)
mod = importlib.util.module_from_spec(spec)
spec.loader.exec_module(mod)
if not hasattr(mod, agent_func):
raise Exception(f"Not module function '{agent_func}' at '{agent_path}'")
value = getattr(mod, agent_func)(**agent_data)
return_to_llm(value)
dump_result('{agent_name}' + f':{agent_func}')
def return_to_llm(value):
if value is None:
return
if "LLM_OUTPUT" in os.environ:
writer = open(os.environ["LLM_OUTPUT"], "w")
else:
writer = sys.stdout
value_type = type(value).__name__
if value_type in ("str", "int", "float", "bool"):
writer.write(str(value))
elif value_type == "dict" or value_type == "list":
value_str = json.dumps(value, indent=2)
assert value == json.loads(value_str)
writer.write(value_str)
def dump_result(name):
if (not os.getenv("LLM_DUMP_RESULTS")) or (not os.getenv("LLM_OUTPUT")) or (not os.isatty(1)):
return
show_result = False
try:
if re.search(rf'\b({os.environ["LLM_DUMP_RESULTS"]})\b', name):
show_result = True
except:
pass
if not show_result:
return
try:
with open(os.environ["LLM_OUTPUT"], "r", encoding="utf-8") as f:
data = f.read()
except:
return
print(f"\x1b[2m----------------------\n{data}\n----------------------\x1b[0m")
if __name__ == "__main__":
main()
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#!/usr/bin/env bash
# Usage: ./{agent_name}.sh <agent-func> <agent-data>
set -e
main() {
root_dir="{config_dir}"
parse_argv "$@"
setup_env
tools_path="$root_dir/agents/{agent_name}/tools.sh"
run
}
parse_argv() {
agent_func="$1"
agent_data="$2"
if [[ -z "$agent_data" ]] || [[ -z "$agent_func" ]]; then
die "usage: ./{agent_name}.sh <agent-func> <agent-data>"
fi
}
setup_env() {
load_env "$root_dir/.env"
export LLM_ROOT_DIR="$root_dir"
export LLM_AGENT_NAME="{agent_name}"
export LLM_AGENT_FUNC="$agent_func"
export LLM_AGENT_ROOT_DIR="$LLM_ROOT_DIR/agents/{agent_name}"
export LLM_AGENT_CACHE_DIR="$LLM_ROOT_DIR/cache/{agent_name}"
export LLM_PROMPT_UTILS_FILE="{prompt_utils_file}"
}
load_env() {
local env_file="$1" env_vars
if [[ -f "$env_file" ]]; then
while IFS='=' read -r key value; do
if [[ "$key" == $'#'* ]] || [[ -z "$key" ]]; then
continue
fi
if [[ -z "${!key+x}" ]]; then
env_vars="$env_vars $key=$value"
fi
done < <(cat "$env_file"; echo "")
if [[ -n "$env_vars" ]]; then
eval "export $env_vars"
fi
fi
}
run() {
if [[ -z "$agent_data" ]]; then
die "error: no JSON data"
fi
if [[ "$OS" == "Windows_NT" ]]; then
set -o igncr
tools_path="$(cygpath -w "$tools_path")"
tool_data="$(echo "$tool_data" | sed 's/\\/\\\\/g')"
fi
jq_script="$(cat <<-'EOF'
def escape_shell_word:
tostring
| gsub("'"; "'\"'\"'")
| gsub("\n"; "'$'\\n''")
| "'\(.)'";
def to_args:
to_entries | .[] |
(.key | split("_") | join("-")) as $key |
if .value | type == "array" then
.value | .[] | "--\($key) \(. | escape_shell_word)"
elif .value | type == "boolean" then
if .value then "--\($key)" else "" end
else
"--\($key) \(.value | escape_shell_word)"
end;
[ to_args ] | join(" ")
EOF
)"
args="$(echo "$agent_data" | jq -r "$jq_script" 2>/dev/null)" || {
die "error: invalid JSON data"
}
if [[ -z "$LLM_OUTPUT" ]]; then
is_temp_llm_output=1
# shellcheck disable=SC2155
export LLM_OUTPUT="$(mktemp)"
fi
eval "'$tools_path' '$agent_func' $args"
if [[ "$is_temp_llm_output" -eq 1 ]]; then
cat "$LLM_OUTPUT"
else
dump_result "{agent_name}:${LLM_AGENT_FUNC}"
fi
}
dump_result() {
if [[ "$LLM_OUTPUT" == "/dev/stdout" ]] || [[ -z "$LLM_DUMP_RESULTS" ]] || [[ ! -t 1 ]]; then
return;
fi
if grep -q -w -E "$LLM_DUMP_RESULTS" <<<"$1"; then
cat <<EOF
$(echo -e "\e[2m")----------------------
$(cat "$LLM_OUTPUT")
----------------------$(echo -e "\e[0m")
EOF
fi
}
die() {
echo "$*" >&2
exit 1
}
main "$@"
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#!/usr/bin/env python
# Usage: ./{function_name}.py <tool-data>
import os
import re
import json
import sys
import importlib.util
from pathlib import Path
def _ensure_cwd_venv():
cwd = Path.cwd()
venv_dir = cwd / ".venv"
if not venv_dir.is_dir():
return
py = venv_dir / ("Scripts/python.exe" if os.name == "nt" else "bin/python")
if not py.exists():
return
if Path(sys.prefix).resolve() == venv_dir.resolve():
return
os.execv(str(py), [str(py)] + sys.argv)
_ensure_cwd_venv()
def main():
raw_data = parse_argv()
tool_data = parse_raw_data(raw_data)
root_dir = "{root_dir}"
setup_env(root_dir)
tool_path = "{tool_path}.py"
run(tool_path, "run", tool_data)
def parse_raw_data(data):
if not data:
raise ValueError("No JSON data")
try:
return json.loads(data)
except Exception:
raise ValueError("Invalid JSON data")
def parse_argv():
argv = sys.argv[:] + [None] * max(0, 2 - len(sys.argv))
tool_data = argv[1]
if (not tool_data):
print("Usage: ./{function_name}.py <tool-data>", file=sys.stderr)
sys.exit(1)
return tool_data
def setup_env(root_dir):
load_env(os.path.join(root_dir, ".env"))
os.environ["LLM_ROOT_DIR"] = root_dir
os.environ["LLM_TOOL_NAME"] = "{function_name}"
os.environ["LLM_TOOL_CACHE_DIR"] = os.path.join(root_dir, "cache", "{function_name}")
def load_env(file_path):
try:
with open(file_path, "r") as f:
lines = f.readlines()
except:
return
env_vars = {}
for line in lines:
line = line.strip()
if line.startswith("#") or not line:
continue
key, *value_parts = line.split("=")
env_name = key.strip()
if env_name not in os.environ:
env_value = "=".join(value_parts).strip()
if (env_value.startswith('"') and env_value.endswith('"')) or (env_value.startswith("'") and env_value.endswith("'")):
env_value = env_value[1:-1]
env_vars[env_name] = env_value
os.environ.update(env_vars)
def run(tool_path, tool_func, tool_data):
spec = importlib.util.spec_from_file_location(
os.path.basename(tool_path), tool_path
)
mod = importlib.util.module_from_spec(spec)
spec.loader.exec_module(mod)
if not hasattr(mod, tool_func):
raise Exception(f"No module function '{tool_func}' at '{tool_path}'")
value = getattr(mod, tool_func)(**tool_data)
return_to_llm(value)
dump_result("{function_name}")
def return_to_llm(value):
if value is None:
return
if "LLM_OUTPUT" in os.environ:
writer = open(os.environ["LLM_OUTPUT"], "w")
else:
writer = sys.stdout
value_type = type(value).__name__
if value_type in ("str", "int", "float", "bool"):
writer.write(str(value))
elif value_type == "dict" or value_type == "list":
value_str = json.dumps(value, indent=2)
assert value == json.loads(value_str)
writer.write(value_str)
def dump_result(name):
if (not os.getenv("LLM_DUMP_RESULTS")) or (not os.getenv("LLM_OUTPUT")) or (not os.isatty(1)):
return
show_result = False
try:
if re.search(rf'\b({os.environ["LLM_DUMP_RESULTS"]})\b', name):
show_result = True
except:
pass
if not show_result:
return
try:
with open(os.environ["LLM_OUTPUT"], "r", encoding="utf-8") as f:
data = f.read()
except:
return
print(f"\x1b[2m----------------------\n{data}\n----------------------\x1b[0m")
if __name__ == "__main__":
main()
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#!/usr/bin/env bash
# Usage: ./{function_name}.sh <tool-data>
set -e
main() {
root_dir="{root_dir}"
parse_argv "$@"
setup_env
tool_path="{tool_path}.sh"
run
}
parse_argv() {
tool_data="$1"
if [[ -z "$tool_data" ]]; then
die "usage: ./{function_name}.sh <tool-data>"
fi
}
setup_env() {
load_env "$root_dir/.env"
export LLM_ROOT_DIR="$root_dir"
export LLM_TOOL_NAME="{function_name}"
export LLM_TOOL_CACHE_DIR="$LLM_ROOT_DIR/cache/{function_name}"
export LLM_PROMPT_UTILS_FILE="{prompt_utils_file}"
}
load_env() {
local env_file="$1" env_vars
if [[ -f "$env_file" ]]; then
while IFS='=' read -r key value; do
if [[ "$key" == $'#'* ]] || [[ -z "$key" ]]; then
continue
fi
if [[ -z "${!key+x}" ]]; then
env_vars="$env_vars $key=$value"
fi
done < <(cat "$env_file"; echo "")
if [[ -n "$env_vars" ]]; then
eval "export $env_vars"
fi
fi
}
run() {
if [[ -z "$tool_data" ]]; then
die "error: no JSON data"
fi
if [[ "$OS" == "Windows_NT" ]]; then
set -o igncr
tool_path="$(cygpath -w "$tool_path")"
tool_data="$(echo "$tool_data" | sed 's/\\/\\\\/g')"
fi
jq_script="$(cat <<-'EOF'
def escape_shell_word:
tostring
| gsub("'"; "'\"'\"'")
| gsub("\n"; "'$'\\n''")
| "'\(.)'";
def to_args:
to_entries | .[] |
(.key | split("_") | join("-")) as $key |
if .value | type == "array" then
.value | .[] | "--\($key) \(. | escape_shell_word)"
elif .value | type == "boolean" then
if .value then "--\($key)" else "" end
else
"--\($key) \(.value | escape_shell_word)"
end;
[ to_args ] | join(" ")
EOF
)"
args="$(echo "$tool_data" | jq -r "$jq_script" 2>/dev/null)" || {
die "error: invalid JSON data"
}
if [[ -z "$LLM_OUTPUT" ]]; then
is_temp_llm_output=1
# shellcheck disable=SC2155
export LLM_OUTPUT="$(mktemp)"
fi
eval "'$tool_path' $args"
if [[ "$is_temp_llm_output" -eq 1 ]]; then
cat "$LLM_OUTPUT"
else
dump_result "{function_name}"
fi
}
dump_result() {
if [[ "$LLM_OUTPUT" == "/dev/stdout" ]] || [[ -z "$LLM_DUMP_RESULTS" ]] || [[ ! -t 1 ]]; then
return;
fi
if grep -q -w -E "$LLM_DUMP_RESULTS" <<<"$1"; then
cat <<EOF
$(echo -e "\e[2m")----------------------
$(cat "$LLM_OUTPUT")
----------------------$(echo -e "\e[0m")
EOF
fi
}
die() {
echo "$*" >&2
exit 1
}
main "$@"
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@@ -0,0 +1,38 @@
import os
from typing import List, Literal, Optional
def run(
string: str,
string_enum: Literal["foo", "bar"],
boolean: bool,
integer: int,
number: float,
array: List[str],
string_optional: Optional[str] = None,
array_optional: Optional[List[str]] = None,
):
"""Demonstrates how to create a tool using Python and how to use comments.
Args:
string: Define a required string property
string_enum: Define a required string property with enum
boolean: Define a required boolean property
integer: Define a required integer property
number: Define a required number property
array: Define a required string array property
string_optional: Define an optional string property
array_optional: Define an optional string array property
"""
output = f"""string: {string}
string_enum: {string_enum}
string_optional: {string_optional}
boolean: {boolean}
integer: {integer}
number: {number}
array: {array}
array_optional: {array_optional}"""
for key, value in os.environ.items():
if key.startswith("LLM_"):
output = f"{output}\n{key}: {value}"
return output
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#!/usr/bin/env bash
set -e
# @describe Demonstrate how to create a tool using Bash and how to use comment tags.
# @option --string! Define a required string property
# @option --string-enum![foo|bar] Define a required string property with enum
# @option --string-optional Define a optional string property
# @flag --boolean Define a boolean property
# @option --integer! <INT> Define a required integer property
# @option --number! <NUM> Define a required number property
# @option --array+ <VALUE> Define a required string array property
# @option --array-optional* Define a optional string array property
# @env LLM_OUTPUT=/dev/stdout The output path
# shellcheck disable=SC2154
main() {
cat <<EOF >> "$LLM_OUTPUT"
string: ${argc_string}
string_enum: ${argc_string_enum}
string_optional: ${argc_string_optional}
boolean: ${argc_boolean}
integer: ${argc_integer}
number: ${argc_number}
array: ${argc_array[@]}
array_optional: ${argc_array_optional[@]}
$(printenv | grep '^LLM_')
EOF
}
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#!/usr/bin/env bash
set -e
# @describe Execute the shell command.
# @option --command! The command to execute.
# @env LLM_OUTPUT=/dev/stdout The output path
# shellcheck disable=SC1090
source "$LLM_PROMPT_UTILS_FILE"
main() {
guard_operation
# shellcheck disable=SC2154
eval "$argc_command" >> "$LLM_OUTPUT"
}
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import ast
import io
from contextlib import redirect_stdout
def run(code: str):
"""Execute the given Python code.
Args:
code: The Python code to execute, such as `print("hello world")`
"""
output = io.StringIO()
with redirect_stdout(output):
value = exec_with_return(code, {}, {})
if value is not None:
output.write(str(value))
return output.getvalue()
def exec_with_return(code: str, globals: dict, locals: dict):
a = ast.parse(code)
last_expression = None
if a.body:
if isinstance(a_last := a.body[-1], ast.Expr):
last_expression = ast.unparse(a.body.pop())
elif isinstance(a_last, ast.Assign):
last_expression = ast.unparse(a_last.targets[0])
elif isinstance(a_last, (ast.AnnAssign, ast.AugAssign)):
last_expression = ast.unparse(a_last.target)
exec(ast.unparse(a), globals, locals)
if last_expression:
return eval(last_expression, globals, locals)
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#!/usr/bin/env bash
set -e
# @describe Execute sql code.
# @option --code! The code to execute.
# @meta require-tools usql
# @env USQL_DSN! The database connection url. e.g. pgsql://user:pass@host:port
# @env LLM_OUTPUT=/dev/stdout The output path
# shellcheck disable=SC1090
source "$LLM_PROMPT_UTILS_FILE"
# shellcheck disable=SC2154
main() {
if ! grep -qi '^select' <<<"$argc_code"; then
guard_operation ""
fi
usql -c "$argc_code" "$USQL_DSN" >> "$LLM_OUTPUT"
}
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#!/usr/bin/env bash
set -e
# @describe Extract the content from a given URL.
# @option --url! The URL to scrape.
# @meta require-tools pandoc
# @env LLM_OUTPUT=/dev/stdout The output path
# shellcheck disable=SC2154
main() {
# span and div tags are dropped from the HTML https://pandoc.org/MANUAL.html#raw-htmltex and sed removes any inline SVG images in image tags from the Markdown content.
curl -fsSL "$argc_url" | \
pandoc -f html-native_divs-native_spans -t gfm-raw_html --wrap=none | \
sed -E 's/!\[[^]]*\]\([^)]*\)//g' \
>> "$LLM_OUTPUT"
}
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#!/usr/bin/env bash
set -e
# @describe Extract the content from a given URL.
# @option --url! The URL to scrape.
# @env JINA_API_KEY Your Jina API key
# @env LLM_OUTPUT=/dev/stdout The output path
# shellcheck disable=SC2154
main() {
curl_args=()
if [[ -n "$JINA_API_KEY" ]]; then
curl_args+=("-H" "Authorization: Bearer $JINA_API_KEY")
fi
curl -fsSL "${curl_args[@]}" "https://r.jina.ai/$argc_url" >> "$LLM_OUTPUT"
}
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#!/usr/bin/env bash
set -e
# @describe Read the contents of a file at the specified path.
# Use this when you need to examine the contents of an existing file.
# @option --path! The path of the file to read
# @env LLM_OUTPUT=/dev/stdout The output path
main() {
# shellcheck disable=SC2154
cat "$argc_path" >> "$LLM_OUTPUT"
}
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#!/usr/bin/env bash
set -e
# @describe List all files and directories at the specified path.
# @option --path! The path of the directory to list
# @env LLM_OUTPUT=/dev/stdout The output path
main() {
# shellcheck disable=SC2154
ls -1 "$argc_path" >> "$LLM_OUTPUT"
}
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#!/usr/bin/env bash
set -e
# @describe Create a new directory at the specified path.
# @option --path! The path of the directory to create
# @env LLM_OUTPUT=/dev/stdout The output path
main() {
# shellcheck disable=SC2154
mkdir -p "$argc_path"
echo "Directory created: $argc_path" >> "$LLM_OUTPUT"
}
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#!/usr/bin/env bash
set -e
# @describe Apply a patch to a file at the specified path.
# This can be used to edit a file without having to rewrite the whole file.
# @option --path! The path of the file to apply the patch to
# @option --contents! The patch to apply to the file
# @env LLM_OUTPUT=/dev/stdout The output path
# shellcheck disable=SC1090
source "$LLM_PROMPT_UTILS_FILE"
# shellcheck disable=SC2154
main() {
if [[ ! -f "$argc_path" ]]; then
error "Unable to find the specified file: $argc_path"
exit 1
fi
new_contents="$(patch_file "$argc_path" <(printf "%s" "$argc_contents"))"
printf "%s" "$new_contents" | git diff --no-index "$argc_path" - || true
guard_operation "Apply changes?"
printf "%s" "$new_contents" > "$argc_path"
info "Applied the patch to: $argc_path" >> "$LLM_OUTPUT"
}
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#!/usr/bin/env bash
set -e
# @describe Remove the file or directory at the specified path.
# @option --path! The path of the file or directory to remove
# @env LLM_OUTPUT=/dev/stdout The output path
# shellcheck disable=SC1090
source "$LLM_PROMPT_UTILS_FILE"
# shellcheck disable=SC2154
main() {
if [[ -f "$argc_path" ]]; then
guard_path "$argc_path" "Remove '$argc_path'?"
rm -rf "$argc_path"
fi
echo "Path removed: $argc_path" >> "$LLM_OUTPUT"
}
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#!/usr/bin/env bash
set -e
# @describe Write the full file contents to a file at the specified path.
# @option --path! The path of the file to write to
# @option --contents! The full contents to write to the file
# @env LLM_OUTPUT=/dev/stdout The output path
# shellcheck disable=SC1090
source "$LLM_PROMPT_UTILS_FILE"
# shellcheck disable=SC2154
main() {
if [[ -f "$argc_path" ]]; then
printf "%s" "$argc_contents" | git diff --no-index "$argc_path" - || true
guard_operation "Apply changes?"
else
guard_path "$argc_path" "Write '$argc_path'?"
mkdir -p "$(dirname "$argc_path")"
fi
printf "%s" "$argc_contents" > "$argc_path"
echo "The File contents were written to: $argc_path" >> "$LLM_OUTPUT"
}
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#!/usr/bin/env bash
set -e
# @describe Get the current time.
# @env LLM_OUTPUT=/dev/stdout The output path
main() {
date >> "$LLM_OUTPUT"
}
@@ -0,0 +1,35 @@
import os
from pathlib import Path
from typing import Optional
from urllib.parse import quote_plus
from urllib.request import urlopen
def run(
location: str,
llm_output: Optional[str] = None,
) -> str:
"""Get the current weather in a given location
Args:
location (str): The city and optionally the state or country (e.g., "London", "San Francisco, CA").
Returns:
str: A single-line formatted weather string from wttr.in (``format=4`` with metric units).
"""
url = f"https://wttr.in/{quote_plus(location)}?format=4&M"
with urlopen(url, timeout=10) as resp:
weather = resp.read().decode("utf-8", errors="replace")
dest = llm_output if llm_output is not None else os.environ.get("LLM_OUTPUT", "/dev/stdout")
if dest not in {"-", "/dev/stdout"}:
path = Path(dest)
path.parent.mkdir(parents=True, exist_ok=True)
with path.open("a", encoding="utf-8") as fh:
fh.write(weather)
else:
pass
return weather
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#!/usr/bin/env bash
set -e
# @describe Get the current weather in a given location.
# @option --location! The city and optionally the state or country, e.g., "London", "San Francisco, CA".
# @env LLM_OUTPUT=/dev/stdout The output path
main() {
curl -fsSL "https://wttr.in/$(echo "$argc_location" | sed 's/ /+/g')?format=4&M" \
>> "$LLM_OUTPUT"
}
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#!/usr/bin/env bash
set -e
# @meta require-tools jira
# @describe Query for jira issues using a Jira Query Language (JQL) query
# @option --jql-query! The Jira Query Language query to execute
# @env LLM_OUTPUT=/dev/stdout The output path
main() {
jira issue ls -q "$argc_jql_query" --plain >> "$LLM_OUTPUT"
}
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#!/usr/bin/env bash
set -e
# @describe Search arXiv using the given search query and return the top papers.
# @option --query! The search query.
# @env ARXIV_MAX_RESULTS=3 The max results to return.
# @env LLM_OUTPUT=/dev/stdout The output path
main() {
# shellcheck disable=SC2154
encoded_query="$(jq -nr --arg q "$argc_query" '$q|@uri')"
url="http://export.arxiv.org/api/query?search_query=all:$encoded_query&max_results=$ARXIV_MAX_RESULTS"
curl -fsSL "$url" >> "$LLM_OUTPUT"
}
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#!/usr/bin/env bash
set -e
# @describe Search Wikipedia using the given search query.
# Use it to get detailed information about a public figure, interpretation of a complex scientific concept or in-depth connectivity of a significant historical event, etc.
# @option --query! The search query.
# @env LLM_OUTPUT=/dev/stdout The output path
# shellcheck disable=SC2154
main() {
encoded_query="$(jq -nr --arg q "$argc_query" '$q|@uri')"
base_url="https://en.wikipedia.org/w/api.php"
url="$base_url?action=query&list=search&srprop=&srlimit=1&limit=1&srsearch=$encoded_query&srinfo=suggestion&format=json"
json="$(curl -fsSL "$url")"
# suggestion="$(echo "$json" | jq -r '.query.searchinfo.suggestion // empty')"
title="$(echo "$json" | jq -r '.query.search[0].title // empty')"
pageid="$(echo "$json" | jq -r '.query.search[0].pageid // empty')"
if [[ -z "$title" || -z "$pageid" ]]; then
echo "error: no results for '$argc_query'" >&2
exit 1
fi
title="$(echo "$title" | tr ' ' '_')"
url="$base_url?action=query&prop=extracts&explaintext=&titles=$title&exintro=&format=json"
curl -fsSL "$url" | jq -r '.query.pages["'"$pageid"'"].extract' >> "$LLM_OUTPUT"
}
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#!/usr/bin/env bash
set -e
# @describe Get an answer to a question using Wolfram Alpha. The input query should be in English.
# Use it to answer user questions that require computation, detailed facts, data analysis, or complex queries.
# @option --query! The search/computation query to pass to Wolfram Alpha
# @env WOLFRAM_API_ID! Your Wolfram Alpha API ID
# @env LLM_OUTPUT=/dev/stdout The output path
# shellcheck disable=SC2154
main() {
encoded_query="$(jq -nr --arg q "$argc_query" '$q|@uri')"
url="https://api.wolframalpha.com/v2/query?appid=${WOLFRAM_API_ID}&input=$encoded_query&output=json&format=plaintext"
curl -fsSL "$url" | jq '[.queryresult | .pods[] | {title:.title, values:[.subpods[].plaintext | select(. != "")]}]' \
>> "$LLM_OUTPUT"
}
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#!/usr/bin/env bash
set -e
# @describe Send an email.
# @option --recipient! The recipient of the email.
# @option --subject! The subject of the email.
# @option --body! The body of the email.
# @env EMAIL_SMTP_ADDR! The SMTP Address, e.g. smtps://smtp.gmail.com:465
# @env EMAIL_SMTP_USER! The SMTP User, e.g. alice@gmail.com
# @env EMAIL_SMTP_PASS! The SMTP Password
# @env EMAIL_SENDER_NAME The sender's name
# @env LLM_OUTPUT=/dev/stdout The output path
# shellcheck disable=SC2154
main() {
sender_name="${EMAIL_SENDER_NAME:-$(echo "$EMAIL_SMTP_USER" | awk -F'@' '{print $1}')}"
printf "%s\n" "From: $sender_name <$EMAIL_SMTP_USER>
To: $argc_recipient
Subject: $argc_subject
$argc_body" | \
curl -fsS --ssl-reqd \
--url "$EMAIL_SMTP_ADDR" \
--user "$EMAIL_SMTP_USER:$EMAIL_SMTP_PASS" \
--mail-from "$EMAIL_SMTP_USER" \
--mail-rcpt "$argc_recipient" \
--upload-file -
echo "Email sent successfully" >> "$LLM_OUTPUT"
}
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#!/usr/bin/env bash
set -e
# @describe Send SMS or Twilio Messaging Channels messages using the Twilio API.
# @option --to-number! The recipient's phone number. Prefix it with 'whatsapp:' for WhatsApp messages, e.g. whatsapp:+1234567890
# @option --message! The content of the message to be sent
# @env TWILIO_ACCOUNT_SID! The twilio account sid
# @env TWILIO_AUTH_TOKEN! The twilio auth token
# @env TWILIO_FROM_NUMBER! The twilio from number
# @env LLM_OUTPUT=/dev/stdout The output path
# shellcheck disable=SC2154
main() {
from_number="$TWILIO_FROM_NUMBER"
to_number="$argc_to_number"
if [[ "$to_number" == 'whatsapp:'* ]]; then
from_number="whatsapp:$from_number"
fi
if [[ "$to_number" != 'whatsapp:'* && "$to_number" != '+'* ]]; then
to_number="+$to_number"
fi
res="$(curl -s -X POST "https://api.twilio.com/2010-04-01/Accounts/$TWILIO_ACCOUNT_SID/Messages.json" \
-u "$TWILIO_ACCOUNT_SID:$TWILIO_AUTH_TOKEN" \
-w "\n%{http_code}" \
--data-urlencode "From=$from_number" \
--data-urlencode "To=$to_number" \
--data-urlencode "Body=$argc_message")"
status="$(echo "$res" | tail -n 1)"
body="$(echo "$res" | head -n -1)"
if [[ "$status" -ge 200 && "$status" -lt 300 ]]; then
if [[ "$(echo "$body" | jq -r 'has("sid")')" == "true" ]]; then
echo "Message sent successfully" >> "$LLM_OUTPUT"
else
_die "error: $body"
fi
else
_die "error: $body"
fi
}
_die() {
echo "$*" >&2
exit 1
}
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#!/usr/bin/env bash
set -e
# @describe Perform a web search to get up-to-date information or additional context.
# Use this when you need current information or feel a search could provide a better answer.
# @option --query! The search query.
# @meta require-tools loki
# @env WEB_SEARCH_MODEL=gemini:gemini-2.5-flash The model for web-searching.
#
# supported loki models:
# - gemini:gemini-2.0-*
# - vertexai:gemini-*
# - perplexity:*
# - ernie:*
# @env LLM_OUTPUT=/dev/stdout The output path
# shellcheck disable=SC2154
main() {
client="${WEB_SEARCH_MODEL%%:*}"
if [[ "$client" == "gemini" ]]; then
export LOKI_PATCH_GEMINI_CHAT_COMPLETIONS='{".*":{"body":{"tools":[{"google_search":{}}]}}}'
elif [[ "$client" == "vertexai" ]]; then
export LOKI_PATCH_VERTEXAI_CHAT_COMPLETIONS='{
"gemini-1.5-.*":{"body":{"tools":[{"googleSearchRetrieval":{}}]}},
"gemini-2.0-.*":{"body":{"tools":[{"google_search":{}}]}}
}'
elif [[ "$client" == "ernie" ]]; then
export LOKI_PATCH_ERNIE_CHAT_COMPLETIONS='{".*":{"body":{"web_search":{"enable":true}}}}'
fi
loki -m "$WEB_SEARCH_MODEL" "$argc_query" >> "$LLM_OUTPUT"
}
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#!/usr/bin/env bash
set -e
# @describe Perform a web search using the Perplexity API to get up-to-date information or additional context.
# Use this when you need current information or feel a search could provide a better answer.
# @option --query! The search query.
# @env PERPLEXITY_API_KEY! Your Perplexity API key
# @env PERPLEXITY_WEB_SEARCH_MODEL=llama-3.1-sonar-small-128k-online The LLM model to use for the search
# @env LLM_OUTPUT=/dev/stdout The output path
# shellcheck disable=SC2154
main() {
curl -fsS -X POST https://api.perplexity.ai/chat/completions \
-H "authorization: Bearer $PERPLEXITY_API_KEY" \
-H "accept: application/json" \
-H "content-type: application/json" \
--data '
{
"model": "'"$PERPLEXITY_WEB_SEARCH_MODEL"'",
"messages": [
{
"role": "user",
"content": "'"$argc_query"'"
}
]
}
' | \
jq -r '.choices[0].message.content' \
>> "$LLM_OUTPUT"
}
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#!/usr/bin/env bash
set -e
# @describe Perform a web search using the Tavily API to get up-to-date information or additional context.
# Use this when you need current information or feel a search could provide a better answer.
# @option --query! The search query.
# @env TAVILY_API_KEY! Your Tavile API key
# @env LLM_OUTPUT=/dev/stdout The output path The output path
# shellcheck disable=SC2154
main() {
curl -fsSL -X POST https://api.tavily.com/search \
-H "content-type: application/json" \
-d '
{
"api_key": "'"$TAVILY_API_KEY"'",
"query": "'"$argc_query"'",
"include_answer": true
}' | \
jq -r '.answer' >> "$LLM_OUTPUT"
}
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#!/usr/bin/env bash
# Bash helper utilities for prompting users.
# This is a modified version of the excellent Bash TUI toolkit
# (https://github.com/timo-reymann/bash-tui-toolkit)
#
# It includes the following functions for you to use in your
# bash tool commands:
#
# - password Password prompt
# - checked Checkbox
# - text Text input with validation
# - list Select an option from a given list
# - range Prompt the user for a value within a range
# - confirm Confirmation prompt
# - editor Open the user's preferred editor for input
# - detect_os Detect the current OS
# - get_opener Get the file opener for the current OS
# - open_link Open the given link in the default browser
# See https://github.com/timo-reymann/bash-tui-toolkit/blob/main/test.sh
# for examples on how to use these commands
#
# - guard_operation Prompt for permission to run an operation
# - guard_path Prompt for permission to perform path operations
# - patch_file Patch a file
# - error Log an error
# - warn Log a warning
# - info Log info
# - debug Log a debug message
# - trace Log a trace message
# - red Output given text in red
# - green Output given text in green
# - gold Output given text in gold
# - blue Output given text in blue
# - magenta Output given text in magenta
# - cyan Output given text in cyan
# - white Output given text in white
# shellcheck disable=SC2034
red=$(tput setaf 1)
green=$(tput setaf 2)
gold=$(tput setaf 3)
blue=$(tput setaf 4)
magenta=$(tput setaf 5)
cyan=$(tput setaf 6)
white=$(tput setaf 7)
default=$(tput sgr0)
gray=$(tput setaf 243)
bold=$(tput bold)
underlined=$(tput smul)
error() {
echo -e "${red}${bold}ERROR:${default}${red} $1${default}"
}
warn() {
echo -e "${gold}${bold}WARN:${default}${gold} $1${default}"
}
info() {
echo -e "${cyan}${bold}INFO:${default}${cyan} $1${default}"
}
debug() {
echo -e "${blue}${bold}DEBUG:${default}${blue} $1${default}"
}
trace() {
echo -e "${gray}${bold}TRACE:${default}${gray} $1${default}"
}
success() {
echo -e "${green}${bold}SUCCESS:${default}${green} $1${default}"
}
red() {
echo -e "${red}$1${default}"
}
green() {
echo -e "${green}$1${default}"
}
gold() {
echo -e "${gold}$1${default}"
}
blue() {
echo -e "${blue}$1${default}"
}
magenta() {
echo -e "${magenta}$1${default}"
}
cyan() {
echo -e "${cyan}$1${default}"
}
white() {
echo -e "${white}$1${default}"
}
_read_stdin() {
read -r "$@" </dev/tty
}
_get_cursor_row() {
declare IFS=';'
_read_stdin -sdR -p $'\E[6n' ROW COL
echo "${ROW#*[}"
}
_cursor_blink_on() {
echo -en "\033[?25h" >&2
}
_cursor_blink_off() {
echo -en "\033[?25l" >&2
}
_cursor_to() {
echo -en "\033[$1;$2H" >&2
}
# shellcheck disable=SC2154
_key_input() {
declare ESC=$'\033'
declare IFS=''
_read_stdin -rsn1 a
if [[ "$ESC" == "$a" ]]; then
_read_stdin -rsn2 b
fi
declare input="${a}${b}"
case "$input" in
"${ESC}[A" | "k") echo up ;;
"${ESC}[B" | "j") echo down ;;
"${ESC}[C" | "l") echo right ;;
"${ESC}[D" | "h") echo left ;;
'') echo enter ;;
' ') echo space ;;
esac
}
_new_line_foreach_item() {
count=0
while [[ $count -lt $1 ]]; do
echo "" >&2
((count++))
done
}
_prompt_text() {
echo -en "\033[32m?\033[0m\033[1m ${1}\033[0m " >&2
}
_decrement_selected() {
declare selected=$1
((selected--))
if [[ "${selected}" -lt 0 ]]; then
selected=$(($2 - 1))
fi
echo -n $selected
}
_increment_selected() {
declare selected=$1
((selected++))
if [[ "${selected}" -ge "${opts_count}" ]]; then
selected=0
fi
echo -n $selected
}
# shellcheck disable=SC2154
input() {
_prompt_text "$1"
echo -en "\033[36m\c" >&2
_read_stdin -r text
echo -n "${text}"
}
confirm() {
trap "stty echo; exit" EXIT
_prompt_text "$1 (y/N)"
echo -en "\033[36m\c " >&2
declare first_row
first_row=$(_get_cursor_row)
declare current_row
current_row=$((first_row - 1))
declare result=""
echo -n " " >&2
while true; do
echo -e "\033[1D\c " >&2
_read_stdin -n1 result
case "$result" in
y | Y)
echo -n 1
break
;;
n | N | *)
echo -n 0
break
;;
esac
done
echo -en "\033[0m" >&2
echo "" >&2
}
list() {
_prompt_text "$1 "
declare opts=("${@:2}")
declare opts_count=$(($# - 1))
_new_line_foreach_item "${#opts[@]}"
declare last_row
last_row=$(_get_cursor_row)
declare first_row
first_row=$((last_row - opts_count + 1))
trap "_cursor_blink_on; stty echo; exit" 2
_cursor_blink_off
declare selected=0
while true; do
declare idx=0
for opt in "${opts[@]}"; do
_cursor_to $((first_row + idx))
if [[ $idx -eq "$selected" ]]; then
printf "\033[0m\033[36m\033[0m \033[36m%s\033[0m" "$opt" >&2
else
printf " %s" "$opt" >&2
fi
((idx++))
done
case $(_key_input) in
enter) break ;;
up) selected=$(_decrement_selected "${selected}" "${opts_count}") ;;
down) selected=$(_increment_selected "${selected}" "${opts_count}") ;;
esac
done
echo -en "\n" >&2
_cursor_to "${last_row}"
_cursor_blink_on
echo -n "${selected}"
}
checkbox() {
_prompt_text "$1"
declare opts
opts=("${@:2}")
declare opts_count
opts_count=$(($# - 1))
_new_line_foreach_item "${#opts[@]}"
declare last_row
last_row=$(_get_cursor_row)
declare first_row
first_row=$((last_row - opts_count + 1))
trap "_cursor_blink_on; stty echo; exit" 2
_cursor_blink_off
declare selected=0
declare checked=()
while true; do
declare idx=0
for opt in "${opts[@]}"; do
_cursor_to $((first_row + idx))
declare icon="◯"
for item in "${checked[@]}"; do
if [[ "$item" == "$idx" ]]; then
icon="◉"
break
fi
done
if [[ $idx -eq "$selected" ]]; then
printf "%s \e[0m\e[36m\e[0m \e[36m%-50s\e[0m" "$icon" "$opt" >&2
else
printf "%s %-50s" "$icon" "$opt" >&2
fi
((idx++))
done
case $(_key_input) in
enter) break ;;
space)
declare found=0
for item in "${checked[@]}"; do
if [[ "$item" == "$selected" ]]; then
found=1
break
fi
done
if [ $found -eq 1 ]; then
checked=("${checked[@]/$selected/}")
else
checked+=("${selected}")
fi
;;
up) selected=$(_decrement_selected "${selected}" "${opts_count}") ;;
down) selected=$(_increment_selected "${selected}" "${opts_count}") ;;
esac
done
_cursor_to "${last_row}"
_cursor_blink_on
IFS="" echo -n "${checked[@]}"
}
password() {
_prompt_text "$1"
echo -en "\033[36m" >&2
declare password=''
declare IFS=
while _read_stdin -r -s -n1 char; do
[[ -z "${char}" ]] && {
printf '\n' >&2
break
}
if [[ "${char}" == $'\x7f' ]]; then
if [[ "${#password}" -gt 0 ]]; then
password="${password%?}"
echo -en '\b \b' >&2
fi
else
password+=$char
echo -en '*' >&2
fi
done
echo -en "\e[0m" >&2
echo -n "${password}"
}
editor() {
tmpfile=$(mktemp)
_prompt_text "$1"
echo "" >&2
"${EDITOR:-vi}" "${tmpfile}" >/dev/tty
echo -en "\033[36m" >&2
sed -e 's/^/ /' "${tmpfile}" >&2
echo -en "\033[0m" >&2
cat "${tmpfile}"
}
with_validate() {
while true; do
declare val
val="$(eval "$1")"
if ($2 "$val" >/dev/null); then
echo "$val"
break
else
show_error "$($2 "$val")"
fi
done
}
range() {
declare min="$2"
declare current="$3"
declare max="$4"
declare selected="${current}"
declare max_len_current
max_len_current=0
if [[ "${#min}" -gt "${#max}" ]]; then
max_len_current="${#min}"
else
max_len_current="${#max}"
fi
declare padding
padding="$(printf "%-${max_len_current}s" "")"
declare first_row
first_row=$(_get_cursor_row)
declare current_row
current_row=$((first_row - 1))
trap "_cursor_blink_on; stty echo; exit" 2
_cursor_blink_off
_check_range() {
val=$1
if [[ "$val" -gt "$max" ]]; then
val=$min
elif [[ "$val" -lt "$min" ]]; then
val=$max
fi
echo "$val"
}
while true; do
_prompt_text "$1"
printf "\033[37m%s\033[0m \033[1;90m\033[0m \033[36m%s%s\033[0m \033[1;90m\033[0m \033[37m%s\033[0m\n" "$min" "${padding:${#selected}}" "$selected" "$max" >&2
case $(_key_input) in
enter)
break
;;
left)
selected="$(_check_range $((selected - 1)))"
;;
right)
selected="$(_check_range $((selected + 1)))"
;;
esac
_cursor_to "$current_row"
done
echo "$selected"
}
validate_present() {
if [ "$1" != "" ]; then
return 0
else
error "Please specify the value"
return 1
fi
}
show_error() {
echo -e "\033[91;1m✘ $1\033[0m" >&2
}
show_success() {
echo -e "\033[92;1m✔ $1\033[0m" >&2
}
detect_os() {
case "$OSTYPE" in
solaris*) echo "solaris" ;;
darwin*) echo "macos" ;;
linux*) echo "linux" ;;
bsd*) echo "bsd" ;;
msys*) echo "windows" ;;
cygwin*) echo "windows" ;;
*) echo "unknown" ;;
esac
}
get_opener() {
declare cmd
case "$(detect_os)" in
macos) cmd="open" ;;
linux) cmd="xdg-open" ;;
windows) cmd="start" ;;
*) cmd="" ;;
esac
echo "$cmd"
}
open_link() {
cmd="$(get_opener)"
if [[ "$cmd" == "" ]]; then
error "Your platform is not supported for opening links."
red "Please open the following URL in your preferred browser:"
red " ${1}"
return 1
fi
$cmd "$1"
if [[ $? -eq 1 ]]; then
error "Failed to open your browser."
red "Please open the following URL in your browser:"
red "${1}"
return 1
fi
return 0
}
guard_operation() {
if [[ -t 1 ]]; then
ans="$(confirm "${1:-Are you sure you want to continue?}")"
if [[ "$ans" == 0 ]]; then
error "Operation aborted!" 2>&1
exit 1
fi
fi
}
# Here is an example of a patch block that can be applied to modify the file to request the user's name:
# --- a/hello.py
# +++ b/hello.py
# \@@ ... @@
# def hello():
# - print("Hello World")
# + name = input("What is your name? ")
# + print(f"Hello {name}")
patch_file() {
awk '
FNR == NR {
lines[FNR] = $0
next;
}
{
patchLines[FNR] = $0
}
END {
totalPatchLines=length(patchLines)
totalLines = length(lines)
patchLineIndex = 1
mode = "none"
while (patchLineIndex <= totalPatchLines) {
line = patchLines[patchLineIndex]
if (line ~ /^--- / || line ~ /^\+\+\+ /) {
patchLineIndex++
continue
}
if (line ~ /^@@ /) {
mode = "hunk"
hunkIndex++
patchLineIndex++
continue
}
if (mode == "hunk") {
while (patchLineIndex <= totalPatchLines && line ~ /^[-+ ]|^\s*$/ && line !~ /^--- /) {
sanitizedLine = substr(line, 2)
if (line !~ /^\+/) {
hunkTotalOriginalLines[hunkIndex]++;
hunkOriginalLines[hunkIndex,hunkTotalOriginalLines[hunkIndex]] = sanitizedLine
}
if (line !~ /^-/) {
hunkTotalUpdatedLines[hunkIndex]++;
hunkUpdatedLines[hunkIndex,hunkTotalUpdatedLines[hunkIndex]] = sanitizedLine
}
patchLineIndex++
line = patchLines[patchLineIndex]
}
mode = "none"
} else {
patchLineIndex++
}
}
if (hunkIndex == 0) {
print "error: no patch" > "/dev/stderr"
exit 1
}
totalHunks = hunkIndex
hunkIndex = 1
for (lineIndex = 1; lineIndex <= totalLines; lineIndex++) {
line = lines[lineIndex]
nextLineIndex = 0
if (hunkIndex <= totalHunks && line == hunkOriginalLines[hunkIndex,1]) {
nextLineIndex = lineIndex + 1
for (i = 2; i <= hunkTotalOriginalLines[hunkIndex]; i++) {
if (lines[nextLineIndex] != hunkOriginalLines[hunkIndex,i]) {
nextLineIndex = 0
break
}
nextLineIndex++
}
}
if (nextLineIndex > 0) {
for (i = 1; i <= hunkTotalUpdatedLines[hunkIndex]; i++) {
print hunkUpdatedLines[hunkIndex,i]
}
hunkIndex++
lineIndex = nextLineIndex - 1;
} else {
print line
}
}
if (hunkIndex != totalHunks + 1) {
print "error: unable to apply patch" > "/dev/stderr"
exit 1
}
}
function inspectHunks() {
print "/* Begin inspecting hunks"
for (i = 1; i <= totalHunks; i++) {
print ">>>>>> Original"
for (j = 1; j <= hunkTotalOriginalLines[i]; j++) {
print hunkOriginalLines[i,j]
}
print "======"
for (j = 1; j <= hunkTotalUpdatedLines[i]; j++) {
print hunkUpdatedLines[i,j]
}
print "<<<<<< Updated"
}
print "End inspecting hunks */\n"
}' "$1" "$2"
}
guard_path() {
if [[ "$#" -ne 2 ]]; then
echo "Usage: guard_path <path> <confirmation_prompt>" >&2
exit 1
fi
if [[ -t 1 ]]; then
path="$(_to_real_path "$1")"
confirmation_prompt="$2"
if [[ ! "$path" == "$(pwd)"* ]]; then
ans="$(confirm "$confirmation_prompt")"
if [[ "$ans" == 0 ]]; then
error "Operation aborted!" >&2
exit 1
fi
fi
fi
}
_to_real_path() {
path="$1"
if [[ $OS == "Windows_NT" ]]; then
path="$(cygpath -u "$path")"
fi
awk -v path="$path" -v pwd="$PWD" '
BEGIN {
if (path !~ /^\//) {
path = pwd "/" path
}
if (path ~ /\/\.{1,2}?$/) {
isDir = 1
}
split(path, parts, "/")
newPartsLength = 0
for (i = 1; i <= length(parts); i++) {
part = parts[i]
if (part == "..") {
if (newPartsLength > 0) {
delete newParts[newPartsLength--]
}
} else if (part != "." && part != "") {
newParts[++newPartsLength] = part
}
}
if (isDir == 1 || newPartsLength == 0) {
newParts[++newPartsLength] = ""
}
printf "/"
for (i = 1; i <= newPartsLength; i++) {
newPart = newParts[i]
printf newPart
if (i < newPartsLength) {
printf "/"
}
}
}'
}
@@ -0,0 +1,2 @@
steps:
- .file `git diff` -- generate a git commit message
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Output code only without comments or explanations.
### INPUT:
async sleep in js
### OUTPUT:
```javascript
async function timeout(ms) {
return new Promise(resolve => setTimeout(resolve, ms));
}
```
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As a professional Prompt Engineer, your role is to create effective and innovative prompts for interacting with AI models.
Your core skills include:
1. **CO-STAR Framework Application**: Utilize the CO-STAR framework to build efficient prompts, ensuring effective communication with large language models.
2. **Contextual Awareness**: Construct prompts that adapt to complex conversation contexts, ensuring relevant and coherent responses.
3. **Chain-of-Thought Prompting**: Create prompts that elicit AI models to demonstrate their reasoning process, enhancing the transparency and accuracy of answers.
4. **Zero-shot Learning**: Design prompts that enable AI models to perform specific tasks without requiring examples, reducing dependence on training data.
5. **Few-shot Learning**: Guide AI models to quickly learn and execute new tasks through a few examples.
Your output format should include:
- **Context**: Provide comprehensive background information for the task to ensure the AI understands the specific scenario and offers relevant feedback.
- **Objective**: Clearly define the task objective, guiding the AI to focus on achieving specific goals.
- **Style**: Specify writing styles according to requirements, such as imitating a particular person or industry expert.
- **Tone**: Set an appropriate emotional tone to ensure the AI's response aligns with the expected emotional context.
- **Audience**: Tailor AI responses for a specific audience, ensuring content appropriateness and ease of understanding.
- **Response**: Specify output formats for easy execution of downstream tasks, such as lists, JSON, or professional reports.
- **Workflow**: Instruct the AI on how to step-by-step complete tasks, clarifying inputs, outputs, and specific actions for each step.
- **Examples**: Show a case of input and output that fits the scenario.
Your workflow should be:
1. Extract key information from user requests to determine design objectives.
2. Based on user needs, create prompts that meet requirements, with each part being professional and detailed.
3. Must only output the newly generated and optimized prompts, without explanation, without wrapping it in markdown code block.
My first request is: __INPUT__
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Create a concise, 3-6 word title.
**Notes**:
- Avoid quotation marks or emojis
- RESPOND ONLY WITH TITLE SLUG TEXT
**Examples**:
stock-market-trends
perfect-chocolate-chip-recipe
remote-work-productivity-tips
video-game-development-insights
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Provide a terse, single sentence description of the given shell command.
Describe each argument and option of the command.
Provide short responses in about 80 words.
APPLY MARKDOWN formatting when possible.
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---
enabled_tools: all
---
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---
enabled_mcp_servers: github
---
You are expert GitHub assistant designed to assist users with GitHub related tasks. You can perform various
tasks related to GitHub, such as creating issues, searching for issues, and providing information about repositories.
You can also interact with other tools to enhance your capabilities.
When asked to perform an operation, always try to use the available tools first. When determining which tools are
available to complete a user request, you should look at substrings instead of full names to help you determine
relevance; Also be sure that for all MCP tools (always named 'mcp_list_*' or 'mcp_invoke_*'), you list the available
tools first before selecting one to use.
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---
enabled_mcp_servers: all
---
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---
name: repo-analyzer
enabled_tools: fs_cat,fs_ls,fs_write,fs_patch,execute_command
---
**Context:** The task requires the AI to analyze the {{__cwd__}} repository and provide comprehensive insights into
various aspects such as directory structure, design patterns, coding conventions, libraries, architecture, module
organization, build/test commands, naming conventions, testing practices, commit & pull request guidelines, and
security/configuration settings. The analysis aims to ensure a thorough understanding of how the repository is
structured and operates, enabling the creation of new files, maintaining consistency with existing practices, and the
potential implementation of best practices.
Should the root directory contain a `LOKI.md` file, this was generated by Loki and should be used as a reference
point for all analysis, style questions, etc.
**Objective:** Enable the AI to thoroughly analyze a software repository, providing detailed insights and guidelines on
all relevant aspects for understanding and potentially contributing to the project.
**Style:** Technical analysis with clarity and precision, ensuring comprehensibility for developers and technical
professionals.
**Tone:** Informative and neutral, focusing on factual presentation and technical details.
**Audience:** Software developers, technical leads, and quality assurance professionals looking to understand or
contribute to the project.
**Response:** Provide a detailed report format that includes sections for directory structure, coding conventions,
libraries, architecture, module organization, development commands, naming conventions, testing practices, commit
guidelines, and security considerations.
**Workflow:**
1. Identify and analyze the directory structure to map the organization and purpose of each section. (Should always start with the current directory `.`; i.e. {{__cwd__}})
2. Assess design patterns and coding conventions used within the repository.
3. Investigate libraries and dependencies to understand the ecosystem being used.
4. Examine the architecture to outline system organization and component interaction.
5. Review module organization to determine how different parts of the system integrate and communicate.
6. Identify build, test, and run commands specific to the repository.
7. Analyze naming conventions employed across the project to ensure conformity and clarity.
8. Study testing practices, including test frameworks, directory organization, and test naming strategies.
9. Review commit and pull request guidelines, focusing on best practices, commit types, and formatting.
10. Evaluate security and configuration settings, identifying best practices for data protection and maintaining backward compatibility.
**Examples:**
- Input: Repository URL where the analysis needs to be conducted.
- Output: A structured report detailing each aspect mentioned in the workflow, providing actionable insights and maintaining consistency with established practices.
**Agent-Specific instructions**: Keep changes minimal and consistent with existing structure. Follow this documents
scope across the repo. Do not rename public binaries or alter license headers. If adding dependencies, justify in the
PR description.
You can write files to the filesystem upon request from the user.
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Provide only {{__shell__}} commands for {{__os_distro__}} without any description.
Ensure the output is a valid {{__shell__}} command.
If there is a lack of details, provide most logical solution.
If multiple steps are required, try to combine them using '&&' (For PowerShell, use ';' instead).
Output only plain text without any markdown formatting or <think> or </think> tokens.
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---
enabled_mcp_servers: slack
temperature: 0.2
---
You are an expert Slack assistant designed to assist with Slack workspaces via the slack MCP server.
You can perform various tasks related to Slack, such as sending messages to channels, searching for messages, and
providing information about users. You can also interact with other tools to enhance your capabilities.
When sending messages to Slack channels, ensure that the messages are clear, concise, and relevant to the channel's
purpose. Use appropriate formatting and emojis to enhance the message's readability and engagement.
If ever a user references communicating with a specific person, you should always try to find that person's Slack
username and use that to send the message. If you cannot find that person's Slack username, you should ask the user to
provide it.
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# Agent-specific configuration
# Location `<loki-config-dir>/agents/<agent-name>/config.yaml`
#
# Available Environment Variables:
# - <agent-name>_MODEL
# - <agent-name>_TEMPERATURE
# - <agent-name>_TOP_P
# - <agent-name>_GLOBAL_TOOLS (as a JSON string array)
# - <agent-name>_MCP_SERVERS (as a JSON string array)
# - <agent-name>_AGENT_SESSION
# - <agent-name>_VARIABLES (as JSON array of key-value pairs; e.g. '[{"name": "username", "value": "alex"}]')
model: openai:gpt-4o # Specify the LLM to use
temperature: null # Set default temperature parameter, range (0, 1)
top_p: null # Set default top-p parameter, with a range of (0, 1) or (0, 2) depending on the model
agent_session: null # Set a session to use when starting the agent. (e.g. temp, default); defaults to globally set agent_session
name: <agent-name> # Name of the agent, used in the UI and logs
description: <description> # Description of the agent, used in the UI
version: 1 # Version of the agent
mcp_servers: # Optional list of MCP servers that the agent utilizes
- github # Corresponds to the name of an MCP server in the `<loki-config-dir>/functions/mcp.json` file
global_tools: # Optional list of additional global tools to enable for the agent; i.e. not tools specific to the agent
- web_search
- fs
- python
dynamic_instructions: false # Whether to use dynamic instructions for the agent; if false, static instructions are used
instructions: | # Static instructions for the agent; ignored if dynamic instructions are used
You are a AI agent designed to demonstrate agent capabilities.
<tools>
{{__tools__}}
</tools>
<system>
os: {{__os__}}
os_family: {{__os_family__}}
arch: {{__arch__}}
shell: {{__shell__}}
locale: {{__locale__}}
now: {{__now__}}
cwd: {{__cwd__}}
</system>
<user>
username: {{username}}
</user>
variables: # Optional variables for the agent
# The variables defined above like {{__variable_name__}} are automatically available
- name: username
description: Your user name
default: null # A default value for this variable; if null, the variable must be provided when starting the agent
conversation_starters: # Optional conversation starters for the agent
- What is the meaning of life?
- Tell me a joke.
- What is the capital of France?
- How do I make a cake?
- What is the best way to learn programming?
- How do I improve my writing skills?
- What are some good books to read?
- How do I stay motivated?
- What is the best way to exercise?
- How do I manage my time effectively?
documents: # Optional documents to load for the agent
- git:/some/repo # Explicitly tell Loki to use the 'git' document loader using an absolute path
- pdf:some-pdf-file.pdf # Explicitly tell Loki to use the 'pdf' document loader using a relative path
- https://some-website.com/some-page
- some-file.pdf # File with relative path to the <loki-config-dir>/agents/<agent-name> directory; i.e. file in the same directory as this config file
- ~/some-file.txt # File in the user's home directory
- /absolute/path/to/some-file.md # File with absolute path
- /absolute/path/**/NAME.txt # Find all NAME.txt files in the specified directory and all its subdirectories
- /absolute/path/to/*/README.md # Find all README.md files in all immediate subdirectories of the specified directory (depth=1)
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# ---- LLM ----
model: openai:gpt-4o # Specify the LLM to use
temperature: null # Set default temperature parameter (0, 1)
top_p: null # Set default top-p parameter, with a range of (0, 1) or (0, 2) depending on the model
# ---- Behavior ----
stream: true # Controls whether to use the stream-style APIs when querying for completions from LLM clients.
save: true # Indicates whether to persist the conversation to messages.md for posterity
keybindings: emacs # Choose keybinding style (emacs, vi)
editor: null # Specifies the editor used to edit the input buffer or session. (e.g. vim, emacs, nano, hx). Defaults to $EDITOR
wrap: no # Controls text wrapping (no, auto, <max-width>)
wrap_code: false # Enables or disables the wrapping of code blocks
# ---- Prelude ----
repl_prelude: null # Set a default session or role for REPL mode to use (e.g. role:<name>, session:<name>, <session>:<role>)
cmd_prelude: null # Set a default session or role for CMD mode to use (e.g. role:<name>, session:<name>, <session>:<role>)
agent_session: null # Set a session to use when starting an agent (e.g. temp, default)
# ---- Appearance ----
highlight: true # Controls syntax highlighting
light_theme: false # Activates a light color theme when true. env: LOKI_LIGHT_THEME
# ---- Miscellaneous ----
user_agent: null # Set User-Agent HTTP header, use `auto` for loki/<current-version>
save_shell_history: true # Whether to save shell execution command to the history file
sync_models_url: > # URL to sync model changes from
https://raw.githubusercontent.com/Dark-Alex-17/loki/refs/heads/main/models.yaml
# ---- REPL Prompt ----
# Custom REPL left/right prompts; see the [REPL Prompt Documentation](./docs/REPL-PROMPT.md) for more information
left_prompt:
'{color.red}{model}){color.green}{?session {?agent {agent}>}{session}{?role /}}{!session {?agent {agent}>}}{role}{?rag @{rag}}{color.cyan}{?session )}{!session >}{color.reset} '
right_prompt:
'{color.purple}{?session {?consume_tokens {consume_tokens}({consume_percent}%)}{!consume_tokens {consume_tokens}}}{color.reset}'
# ---- Vault ----
# See the [Vault documentation](./docs/VAULT.md) for more information on the Loki vault
vault_password_file: null # Path to a file containing the password for the Loki vault (cannot be a secret template)
# ---- Function Calling ----
# See the [Tools documentation](./docs/function-calling/TOOLS.md) for more details
function_calling: true # Enables or disables function calling (Globally).
mapping_tools: # Alias for a tool or toolset
fs: 'fs_cat,fs_ls,fs_mkdir,fs_rm,fs_write'
enabled_tools: null # Which tools to enable by default. (e.g. 'fs,web_search_loki')
visible_tools: # Which tools are visible to be compiled (and are thus able to be defined in 'enabled_tools')
# - demo_py.py
# - demo_sh.sh
- execute_command.sh
# - execute_py_code.py
# - execute_sql_code.sh
# - fetch_url_via_curl.sh
# - fetch_url_via_jina.sh
- fs_cat.sh
- fs_ls.sh
# - fs_mkdir.sh
# - fs_patch.sh
# - fs_write.sh
- get_current_time.sh
# - get_current_weather.py
- get_current_weather.sh
- query_jira_issues.sh
# - search_arxiv.sh
# - search_wikipedia.sh
# - search_wolframalpha.sh
# - send_mail.sh
# - send_twilio.sh
# - web_search_loki.sh
# - web_search_perplexity.sh
# - web_search_tavily.sh
# ---- MCP Servers ----
# See the [MCP Servers documentation](./docs/MCP-SERVERS.md) for more details
mcp_server_support: true # Enables or disables MCP servers (globally).
mapping_mcp_servers: # Alias for an MCP server or set of servers
git: github,gitmcp
enabled_mcp_servers: null # Which MCP servers to enable by default (e.g. 'github,slack')
# ---- Session ----
# See the [Session documentation](./docs/SESSIONS.md) for more information
save_session: null # Controls the persistence of the session. If true, auto save; if false, don't auto-save save; if null, ask the user what to do
compression_threshold: 4000 # Compress the session when the token count reaches or exceeds this threshold
summarization_prompt: > # The text prompt used for creating a concise summary of session message
'Summarize the discussion briefly in 200 words or less to use as a prompt for future context.'
summary_context_prompt: > # The text prompt used for including the summary of the entire session as context to the model
'This is a summary of the chat history as a recap: '
# ---- RAG ----
# See the [RAG Docs](./docs/RAG.md) for more details.
rag_embedding_model: null # Specifies the embedding model used for context retrieval
rag_reranker_model: null # Specifies the reranker model used for sorting retrieved documents; Loki uses Reciprocal Rank Fusion by default
rag_top_k: 5 # Specifies the number of documents to retrieve for answering queries
rag_chunk_size: null # Defines the size of chunks for document processing in characters
rag_chunk_overlap: null # Defines the overlap between chunks
# Defines the query structure using variables like __CONTEXT__ and __INPUT__ to tailor searches to specific needs
rag_template: |
Answer the query based on the context while respecting the rules. (user query, some textual context and rules, all inside xml tags)
<context>
__CONTEXT__
</context>
<rules>
- If you don't know, just say so.
- If you are not sure, ask for clarification.
- Answer in the same language as the user query.
- If the context appears unreadable or of poor quality, tell the user then answer as best as you can.
- If the answer is not in the context but you think you know the answer, explain that to the user then answer with your own knowledge.
- Answer directly and without using xml tags.
</rules>
<user_query>
__INPUT__
</user_query>
# Define document loaders to control how RAG and `.file`/`--file` load files of specific formats.
document_loaders:
# You can add custom loaders using the following syntax:
# <file-extension>: <command-to-load-the-file>
# Note: Use `$1` for input file and `$2` for output file. If `$2` is omitted, use stdout as output.
pdf: 'pdftotext $1 -' # Use pdftotext to convert a PDF file to text
# (see https://poppler.freedesktop.org for details on how to install pdftotext)
docx: 'pandoc --to plain $1' # Use pandoc to convert a .docx file to text
# (see https://pandoc.org for details on how to install pandoc)
jina: 'curl -fsSL https://r.jina.ai/$1 -H "Authorization: Bearer {{JINA_API_KEY}}' # Use Jina to translate a website into text;
# Requires a Jina API key to be added to the Loki vault
git: > # Use yek to load a git repository into the knowledgebase (https://github.com/bodo-run/yek)
sh -c "yek $1 --json | jq 'map({ path: .filename, contents: .content })'"
# ---- Clients ----
# See the [Clients documentation](./docs/clients/CLIENTS.md) for more details
clients:
# All clients have the following configuration:
# - type: xxxx
# name: xxxx # Only use it to distinguish clients with the same client type. Optional
# models:
# - name: xxxx # Chat model
# max_input_tokens: 100000
# supports_vision: true
# supports_function_calling: true
# - name: xxxx # Embedding model
# type: embedding
# default_chunk_size: 1500
# max_batch_size: 100
# - name: xxxx # Reranker model
# type: reranker
# patch: # Patch API calls
# chat_completions: # API type; Possible values: chat_completions, embeddings, and rerank
# <regex>: # The regex to match model names, e.g. '.*' 'gpt-4o' 'gpt-4o|gpt-4-.*'
# url: '' # Patch request URL
# body: # Patch request body
# <json>
# headers: # Patch request headers
# <key>: <value>
# extra:
# proxy: socks5://127.0.0.1:1080 # Set proxy
# connect_timeout: 10 # Set timeout in seconds for connect to api
# See https://platform.openai.com/docs/quickstart
- type: openai
api_base: https://api.openai.com/v1 # Optional
api_key: '{{OPENAI_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
organization_id: org-xxx # Optional
# For any platform compatible with OpenAI's API
- type: openai-compatible
name: ollama
api_base: http://localhost:11434/v1
api_key: '{{OLLAMA_API_KEY}}' # Optional; You can either hard-code or inject secrets from the Loki vault
models:
- name: deepseek-r1
max_input_tokens: 131072
- name: llama3.1
max_input_tokens: 128000
supports_function_calling: true
- name: llama3.2-vision
max_input_tokens: 131072
supports_vision: true
- name: nomic-embed-text
type: embedding
default_chunk_size: 1000
max_batch_size: 50
# See https://ai.google.dev/docs
- type: gemini
api_base: https://generativelanguage.googleapis.com/v1beta
api_key: '{{GEMINI_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
patch:
chat_completions:
'.*':
body:
safetySettings:
- category: HARM_CATEGORY_HARASSMENT
threshold: BLOCK_NONE
- category: HARM_CATEGORY_HATE_SPEECH
threshold: BLOCK_NONE
- category: HARM_CATEGORY_SEXUALLY_EXPLICIT
threshold: BLOCK_NONE
- category: HARM_CATEGORY_DANGEROUS_CONTENT
threshold: BLOCK_NONE
# See https://docs.anthropic.com/claude/reference/getting-started-with-the-api
- type: claude
api_base: https://api.anthropic.com/v1 # Optional
api_key: '{{ANTHROPIC_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
# See https://docs.mistral.ai/
- type: openai-compatible
name: mistral
api_base: https://api.mistral.ai/v1
api_key: '{{MISTRAL_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
# See https://docs.x.ai/docs
- type: openai-compatible
name: xai
api_base: https://api.x.ai/v1
api_key: '{{XAI_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
# See https://docs.ai21.com/docs/overview
- type: openai-compatible
name: ai12
api_base: https://api.ai21.com/studio/v1
api_key: '{{AI21_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
# See https://docs.cohere.com/docs/the-cohere-platform
- type: cohere
api_base: https://api.cohere.ai/v2 # Optional
api_key: '{{COHERE_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
# See https://docs.perplexity.ai/getting-started/overview
- type: openai-compatible
name: perplexity
api_base: https://api.perplexity.ai
api_key: '{{PERPLEXITY_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
# See https://console.groq.com/docs/quickstart
- type: openai-compatible
name: groq
api_base: https://api.groq.com/openai/v1
api_key: '{{GROQ_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
# See https://learn.microsoft.com/en-us/azure/ai-services/openai/chatgpt-quickstart
- type: azure-openai
api_base: https://{RESOURCE}.openai.azure.com
api_key: '{{AZURE_OPENAI_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
models:
- name: gpt-4o # Model deployment name
max_input_tokens: 128000
supports_vision: true
supports_function_calling: true
# See https://cloud.google.com/vertex-ai
- type: vertexai
project_id: xxx
location: xxx
# Specifies an application default credentials (adc) file
# Run `gcloud auth application-default login` to initialize the ADC file
# see https://cloud.google.com/docs/authentication/external/set-up-adc for more information
adc_file: <gcloud-config-dir>/application_default_credentials.json # Optional
patch:
chat_completions:
'gemini-.*':
body:
safetySettings:
- category: HARM_CATEGORY_HARASSMENT
threshold: BLOCK_ONLY_HIGH
- category: HARM_CATEGORY_HATE_SPEECH
threshold: BLOCK_ONLY_HIGH
- category: HARM_CATEGORY_SEXUALLY_EXPLICIT
threshold: BLOCK_ONLY_HIGH
- category: HARM_CATEGORY_DANGEROUS_CONTENT
threshold: BLOCK_ONLY_HIGH
# See https://docs.aws.amazon.com/bedrock/latest/userguide/
- type: bedrock
access_key_id: '{{AWS_ACCESS_KEY_ID}}' # You can either hard-code or inject secrets from the Loki vault
secret_access_key: '{{AWS_SECRET_ACCESS_KEY}}' # You can either hard-code or inject secrets from the Loki vault
region: xxx
session_token: xxx # Optional, only needed for temporary credentials
# See https://developers.cloudflare.com/workers-ai/
- type: openai-compatible
name: cloudflare
api_base: https://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/ai/v1
api_key: '{{CLOUDFLARE_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
# See https://cloud.baidu.com/doc/WENXINWORKSHOP/index.html
- type: openai-compatible
name: ernie
api_base: https://qianfan.baidubce.com/v2
api_key: '{{BAIDU_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
# See https://dashscope.aliyun.com/
- type: openai-compatible
name: qianwen
api_base: https://dashscope.aliyuncs.com/compatible-mode/v1
api_key: '{{ALIYUN_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
# See https://cloud.tencent.com/product/hunyuan
- type: openai-compatible
name: hunyuan
api_base: https://api.hunyuan.cloud.tencent.com/v1
api_key: '{{TENCENT_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
# See https://platform.moonshot.cn/docs/intro
- type: openai-compatible
name: moonshot
api_base: https://api.moonshot.cn/v1
api_key: '{{MOONSHOT_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
# See https://platform.deepseek.com/api-docs/
- type: openai-compatible
name: deepseek
api_base: https://api.deepseek.com
api_key: '{{DEEPSEEK_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
# See https://open.bigmodel.cn/dev/howuse/introduction
- type: openai-compatible
name: zhipuai
api_base: https://open.bigmodel.cn/api/paas/v4
api_key: '{{ZHIPUAI_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
# See https://platform.minimaxi.com/document/Fast%20access
- type: openai-compatible
name: minimax
api_base: https://api.minimax.chat/v1
api_key: '{{MINIMAX_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
# See https://openrouter.ai/docs#quick-start
- type: openai-compatible
name: openrouter
api_base: https://openrouter.ai/api/v1
api_key: '{{OPENROUTER_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
# See https://github.com/marketplace/models
- type: openai-compatible
name: github
api_base: https://models.inference.ai.azure.com
api_key: '{{GITHUB_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
# See https://deepinfra.com/docs
- type: openai-compatible
name: deepinfra
api_base: https://api.deepinfra.com/v1/openai
api_key: '{{DEEPINFRA_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
# ----- RAG dedicated -----
# See https://jina.ai
- type: openai-compatible
name: jina
api_base: https://api.jina.ai/v1
api_key: '{{JINA_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
# See https://docs.voyageai.com/docs/introduction
- type: openai-compatible
name: voyageai
api_base: https://api.voyageai.com/v1
api_key: '{{VOYAGEAI_API_KEY}}' # You can either hard-code or inject secrets from the Loki vault
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variables: # A list of positional variables that the macro uses
- name: positional_1 # The name of the positional variable.
default: null # Since no default value is provided, this argument is required; 'null' by default
rest: false # Do not collect all remaining arguments into this variable; 'false' by default
- name: positional_2_with_default_value
default: '2' # A default value for the positional argument if no value is provided
rest: false
- name: collect_remaining_args
rest: true # Collect all remaining arguments into this variable
# Since no 'default' is defined, at least one additional argument is required
steps: # The sequence of REPL commands to execute
- .info
- .agent {{positional_1}}
- What is 2 + {{positional_2_with_default_value}}?
- '{{collect_remaining_args}}'
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---
# Everything in this section is optional
name: <role-name> # The name of the role
model: openai:gpt-4o # The model to use for this role
temperature: 0.2 # The temperature to use for this role when querying the model
top_p: 0 # The top_p to use for this role when querying the model
enabled_tools: fs_ls,fs_cat # A comma-separated list of tools to enable for this role
enabled_mcp_servers: github,gitmcp # A comma-separated list of MCP servers to enable for this role
prompt: null # A custom prompt to use for this role that will immediately query
# the model for output instead of using the instructions below
---
You are an expert at doing things. This is where you write the instructions for the role.
+23
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# Documentation: https://docs.brew.sh/Formula-Cookbook
# https://rubydoc.brew.sh/Formula
class Loki < Formula
desc "All-in-one, batteries included LLM CLI tool"
homepage "https://github.com/Dark-Alex-17/loki"
if OS.mac? and Hardware::CPU.arm?
url "https://github.com/Dark-Alex-17/loki/releases/download/v$version/loki-aarch64-apple-darwin.tar.gz"
sha256 "$hash_mac_arm"
elsif OS.mac? and Hardware::CPU.intel?
url "https://github.com/Dark-Alex-17/loki/releases/download/v$version/loki-x86_64-apple-darwin.tar.gz"
sha256 "$hash_mac"
else
url "https://github.com/Dark-Alex-17/loki/releases/download/v$version/loki-x86_64-unknown-linux-musl.tar.gz"
sha256 "$hash_linux"
end
version "$version"
license "MIT"
def install
bin.install "loki"
ohai "You're done! Get started with \"loki --help\""
end
end
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import hashlib
import sys
from string import Template
args = sys.argv
version = args[1]
template_file_path = args[2]
generated_file_path = args[3]
# Deployment files
hash_mac = args[4].strip()
hash_mac_arm = args[5].strip()
hash_linux = args[6].strip()
print("Generating formula")
print(" VERSION: %s" % version)
print(" TEMPLATE PATH: %s" % template_file_path)
print(" SAVING AT: %s" % generated_file_path)
print(" MAC HASH: %s" % hash_mac)
print(" MAC ARM HASH: %s" % hash_mac_arm)
print(" LINUX HASH: %s" % hash_linux)
with open(template_file_path, "r") as template_file:
template = Template(template_file.read())
substitute = template.safe_substitute(version=version, hash_mac=hash_mac, hash_mac_arm=hash_mac_arm, hash_linux=hash_linux)
print("\n================== Generated package file ==================\n")
print(substitute)
print("\n============================================================\n")
with open(generated_file_path, "w") as generated_file:
generated_file.write(substitute)
+430
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# Agents
Agents in Loki follow the same style as OpenAI's GPTs. They consist of 3 parts:
* [Role](./ROLES.md) - Tell the LLM how to behave
* [RAG](./RAG.md) - Pre-built knowledge bases specifically for the agent
* [Function Calling](./function-calling/TOOLS.md#tools) ([#2](./function-calling/MCP-SERVERS.md)) - Extends the functionality of the LLM through custom functions it can call
![Agent example](./images/agents/sql.gif)
Agent configuration files are stored in the `agents` subdirectory of your Loki configuration directory. The location of
this directory varies between systems so you can use the following command to locate yours:
```shell
loki --info | grep 'agents_dir' | awk '{print $2}'
```
If you're looking for more example agents, refer to the [built-in agents](../assets/agents).
## Quick Links
<!--toc:start-->
- [Directory Structure](#directory-structure)
- [Metadata](#1-metadata)
- [2. Define the Instructions](#2-define-the-instructions)
- [Static Instructions](#static-instructions)
- [Special Variables](#special-variables)
- [User-Defined Variables](#user-defined-variables)
- [Dynamic Instructions](#dynamic-instructions)
- [Variables](#variables)
- [3. Initializing RAG](#3-initializing-rag)
- [4. Building Tools for Agents](#4-building-tools-for-agents)
- [Limitations](#limitations)
- [.env File Support](#env-file-support)
- [Python-Based Agent Tools](#python-based-agent-tools)
- [Bash-Based Agent Tools](#bash-based-agent-tools)
- [5. Conversation Starters](#5-conversation-starters)
- [Built-In Agents](#built-in-agents)
<!--toc:end-->
---
## Directory Structure
Agent configurations often have the following directory structure:
```
<loki-config-dir>/agents
└── my-agent
├── config.yaml
├── tools.sh
or
├── tools.py
```
This means that agent configurations often are only two files: the agent configuration file (`config.yaml`), and the
tool definitions (`agents/my-agent/tools.sh` or `tools.py`).
To see a full example configuration file, refer to the [example agent config file](../config.agent.example.yaml).
The best way to understand how an agent is built is to go step by step in the following manner:
---
## 1. Metadata
Agent configurations have the following settings available to customize each agent:
```yaml
# Model Configuration
model: openai:gpt-4o # Specify the LLM to use
temperature: null # Set default temperature parameter, range (0, 1)
top_p: null # Set default top-p parameter, with a range of (0, 1) or (0, 2), depending on the model
# Agent Metadata Configuration
agent_session: null # Set a session to use when starting the agent. (e.g. temp, default); defaults to globally set agent_session
# Agent Configuration
name: <agent-name> # Name of the agent, used in the UI and logs
description: <description> # Description of the agent, used in the UI
version: 1 # Version of the agent
# Function Calling Configuration
mcp_servers: # Optional list of MCP servers that the agent utilizes
- github # Corresponds to the name of an MCP server in the `<loki-config-dir>/functions/mcp.json` file
global_tools: # Optional list of additional global tools to enable for the agent; i.e. not tools specific to the agent
- web_search
- fs
- python
```
As mentioned previously: Agents utilize function calling to extend a model's capabilities. However, agents operate in
isolated environment, so in order for an agent to use a tool or MCP server that you have defined globally, you must
explicitly state which tools and/or MCP servers the agent uses. Otherwise, it is assumed that the agent doesn't use any
tools outside its own custom defined tools.
And if you don't define a `agents/my-agent/tools.sh` or `agents/my-agent/tools.py`, then the agent is really just a
`role`.
You'll notice there's no settings for agent-specific tooling. This is because they are handled separately and
automatically. See the [Building Tools for Agents](#4-building-tools-for-agents) section below for more information.
To see a full example configuration file, refer to the [example agent config file](../config.agent.example.yaml).
## 2. Define the Instructions
At their heart, agents function similarly to roles in that they tell the model how to behave. Agent configuration files
have the following settings for the instruction definitions:
```yaml
dynamic_instructions: # Whether to use dynamically generated instructions for the agent; if false, static instructions are used. False by default.
instructions: # Static instructions for the LLM; These are ignored if dynamic instructions are used
variables: # An array of optional variables that the agent expects and uses
```
### Static Instructions
By default, Loki agents use statically defined instructions. Think of them as being identical to the instructions for a
[role](./ROLES.md#instructions), because they virtually are.
**Example:**
```yaml
instructions: |
You are an AI agent designed to demonstrate agentic capabilities
```
Just like roles, agents support variable interpolation at runtime. There's two types of variables that can be
interpolated into the instructions at runtime: special variables (like roles have), and user-defined variables. Just
like roles, variables are interpolated into your instructions anywhere Loki sees the `{{variable}}` syntax.
#### Special Variables
The following special variables are provided by Loki at runtime and can be injected into your agent's instructions:
| Name | Description | Example |
|-----------------|---------------------------------------------------------------------|----------------------------|
| `__os__` | Operating system name | `linux` |
| `__os_family__` | Operating system family | `unix` |
| `__arch__` | System architecture | `x86_64` |
| `__shell__` | The current user's default shell | `bash` |
| `__locale__` | The current user's preferred language and region settings | `en-US` |
| `__now__` | Current timestamp in ISO 8601 format | `2025-11-07T10:15:44.268Z` |
| `__cwd__` | The current working directory | `/tmp` |
| `__tools__` | A list of the enabled tools (global + mcp servers + agent-specific) | |
#### User-Defined Variables
Agents also support user-defined variables that can be interpolated into the instructions, and are made available to any
agent-specific tools you define (see [Building Tools for Agents](#4-building-tools-for-agents) for more details on how to
create agent-specific tooling).
The `variables` setting in an agent's config has the following fields:
| Field | Required | Description |
|---------------|----------|----------------------------------------------------------------------------------------------------|
| `name` | * | The name of the variable |
| `description` | * | The description of the field |
| `default` | | A default value for the field. If left undefined, the user will be prompted for a value at runtime |
These variables can be referenced in both the agent's instructions, and in the tool definitions via `LLM_AGENT_VAR_<name>`.
**Example:**
```yaml
instructions: |
You are an agent who answers questions about a user's system.
<tools>
{{__tools__}}
</tools>
<system>
os: {{__os__}}
os_family: {{__os_family__}}
arch: {{__arch__}}
shell: {{__shell__}}
locale: {{__locale__}}
now: {{__now__}}
cwd: {{__cwd__}}
</system>
<user>
username: {{username}}
</user>
variables:
- name: username # Accessible from the tool definitions via the `LLM_AGENT_VAR_USERNAME` environment variable
description: Your user name
```
### Dynamic Instructions
Sometimes you may find it useful to dynamically generate instructions on startup. Whether that be via a call to Loki
itself to generate them, or by some other means. Loki supports this type of behavior using a special function defined
in your `agents/my-agent/tools.py` or `agents/my-agent/tools.sh`.
**Example: Instructions for a JSON-reader agent that specializes on each JSON input it receives**
`agents/json-reader/tools.py`:
```python
import json
from pathlib import Path
from genson import SchemaBuilder
def _instructions():
"""Generates instructions for the agent dynamically"""
value = input("Enter a JSON file path OR paste raw JSON: ").strip()
if not value:
raise SystemExit("A file path or JSON string is required.")
p = Path(value)
if p.exists() and p.is_file():
json_file_path = str(p.resolve())
json_text = p.read_text(encoding="utf-8")
else:
try:
json.loads(value)
except json.JSONDecodeError as e:
raise SystemExit(f"Input is neither a file nor valid JSON.\n{e}")
json_file_path = "<provided-inline-json>"
json_text = value
try:
data = json.loads(json_text)
except json.JSONDecodeError as e:
raise SystemExit(f"Provided content is not valid JSON.\n{e}")
builder = SchemaBuilder()
builder.add_object(data)
json_schema = builder.to_schema()
return f"""
You are an AI agent that can view and filter JSON data with jq.
## Context
json_file_path: {json_file_path}
json_schema: {json.dumps(json_schema, indent=2)}
"""
```
or
`agents/json-reader/tools.sh`:
```bash
#!/usr/bin/env bash
set -e
# @meta require-tools jq,genson
# @env LLM_OUTPUT=/dev/stdout The output path
# @cmd Generates instructions for the agent dynamically
_instructions() {
read -r -p "Enter a JSON file path OR paste raw JSON: " value
if [[ -z "${value}" ]]; then
echo "A file path or JSON string is required" >&2
exit 1
fi
json_file_path=""
inline_temp=""
cleanup() {
[[ -n "${inline_temp:-}" && -f "${inline_temp}" ]] && rm -f "${inline_temp}"
}
trap cleanup EXIT
if [[ -f "${value}" ]]; then
json_file_path="$(realpath "${value}")"
if ! jq empty "${json_file_path}" >/dev/null 2>&1; then
echo "Error: File does not contain valid JSON: ${json_file_path}" >&2
exit 1
fi
else
inline_temp="$(mktemp)"
printf "%s" "${value}" > "${inline_temp}"
if ! jq empty "${inline_temp}" >/dev/null 2>&1; then
echo "Error: Input is neither a file nor valid JSON." >&2
exit 1
fi
json_file_path="<provided-inline-json>"
fi
source_file="${json_file_path}"
if [[ "${json_file_path}" == "<provided-inline-json>" ]]; then
source_file="${inline_temp}"
fi
json_schema="$(genson < "${source_file}" | jq -c '.')"
cat <<EOF >> "$LLM_OUTPUT"
You are an AI agent that can view and filter JSON data with jq.
## Context
json_file_path: ${json_file_path}
json_schema: ${json_schema}
EOF
}
```
For more information on how to create custom tools for your agent and the structure of the `agent/my-agent/tools.sh` or
`agent/my-agent/tools.py` files, refer to the [Building Tools for Agents](#4-building-tools-for-agents) section below.
#### Variables
All the same variable interpolations supported by static instructions is also supported by dynamic instructions. For
more information on what variables are available and how to use them, refer to the [Special Variables](#special-variables)
and [User-Defined Variables](#user-defined-variables) sections above.
## 3. Initializing RAG
Each agent you create also has a dedicated knowledge base that adds additional context to your queries and helps the LLM
answer queries effectively. The documents to load into RAG are defined in the `documents` array of your agent
configuration file:
```yaml
documents:
- https://www.ohdsi.org/data-standardization/
- https://github.com/OHDSI/Vocabulary-v5.0/wiki/**
- OMOPCDM_ddl.sql # Relative path to agent (i.e. file lives at '<loki-config-dir>/agents/my-agent/OMOPCDM_ddl.sql')
```
These documents use the same syntax as those you'd define when constructing RAG normally. To see all the available types
of documents that Loki supports and how to use custom document loaders, refer to the [RAG documentation](./RAG.md#supported-document-sources).
Anytime your agent starts up, it will automatically be using the RAG you've defined here.
## 4. Building Tools for Agents
Building tools for agents is virtually identical to building custom tools, with one slight difference: instead of
defining a single function that gets executed at runtime (e.g. `main` for bash tools and `run` for Python tools), agent
tools define a number of *subcommands*.
### Limitations
You can only utilize either a bash-based `<loki-config-dir>/agents/my-agent/tools.sh` or a Python-based
`<loki-config-dir>/agents/my-agent/tools.py`. However, if it's easier to achieve a task in one language vs the other,
you're free to define other scripts in your agent's configuration directory and reference them from the main
`tools.py/sh` file. **Any scripts *not* named `tools.{py,sh}` will not be picked up by Loki's compiler**, meaning they
can be used like any other set of scripts.
It's important to keep in mind the following:
* **Do not give agents the same name as an executable**. Loki compiles the tools for each agent into a binary that it
temporarily places on your path during execution. If you have a binary with the same name as your agent, then your
shell may execute the existing binary instead of your agent's tools
* **`LLM_ROOT_DIR` points to the agent's configuration directory**. This is where agents differ slightly from normal
tools: The `LLM_ROOT_DIR` environment variable does *not* point to the `functions/tools` directory like it does in
global tools. Instead, it points to the agent's configuration directory, making it easier to source scripts and other
miscellaneous files
### .env File Support
When Loki loads an agent, it will also search the agent's configuration directory for a `.env` file. If found, all
environment variables defined in the file will be made available to the agent's tools.
### Python-Based Agent Tools
Python-based tools are defined exactly the same as they are for custom tool definitions. The only difference is that
instead of a single `run` function, you define as many as you like with whatever arguments you like.
**Example:**
`agents/my-agent/tools.py`
```python
import urllib.request
def get_ip_info():
"""
Get your IP information
"""
with urllib.request.urlopen("https://httpbin.org/ip") as response:
data = response.read()
return data.decode('utf-8')
def get_ip_address_from_aws():
"""
Find your public IP address using AWS
"""
with urllib.request.urlopen("https://checkip.amazonaws.com") as response:
data = response.read()
return data.decode('utf-8')
```
Loki automatically compiles these as separate functions for the LLM to call. No extra work is needed. Just make sure you
follow all the same steps to define each function as you would when creating custom Python tools.
For more information on how to build tools in Python, refer to the [custom Python tools documentation](./function-calling/CUSTOM-TOOLS.md#custom-python-based-tools)
### Bash-Based Agent Tools
Bash-based agent tools are virtually identical to custom bash tools, with only one difference. Instead of defining a
single entrypoint via the `main` function, you actually define as many subcommands as you like.
**Example:**
`agents/my-agent/tools.sh`
```bash
#!/usr/bin/env bash
# @env LLM_OUTPUT=/dev/stdout The output path
# @describe Discover network information about your computer and its place in the internet
# Use the `@cmd` annotation to define subcommands for your script.
# @cmd Get your IP information
get_ip_info() {
curl -fsSL https://httpbin.org/ip >> "$LLM_OUTPUT"
}
# @cmd Find your public IP address using AWS
get_ip_address_from_aws() {
curl -fsSL https://checkip.amazonaws.com >> "$LLM_OUTPUT"
}
```
To compile the script so it's executable and testable:
```bash
$ loki --build-tools
```
Then you can execute your script (assuming your current working directory is `agents/my-agent`):
```bash
$ ./tools.sh get_ip_info
$ ./tools.sh get_ip_address_from_aws
```
All other special annotations (`@env`, `@arg`, `@option` `@flags`) apply to subcommands as well, so be sure to follow
the same syntax ad formatting as is used to create custom bash tools globally.
For more information on how to write, [build and test](function-calling/CUSTOM-BASH-TOOLS.md#execute-and-test-your-bash-tools) tools in bash, refer to the
[custom bash tools documentation](function-calling/CUSTOM-BASH-TOOLS.md).
## 5. Conversation Starters
It's often helpful to also have some conversation starters so users know what kinds of things the agent is capable of
doing. These are available in the REPL via the `.starter` command and are selectable.
They are defined using the `conversation_starters` setting in your agent's configuration file:
**Example:**
`agents/my-agent/config.yaml`:
```yaml
conversation_starters:
- What is my username?
- What is my current shell?
- What is my ip?
- How much disk space is left on my PC??
- How to create an agent?
```
![Example Conversation Starters](./images/agents/conversation-starters.gif)
## Built-In Agents
Loki comes packaged with some useful built-in agents:
* `coder`: An agent to assist you with all your coding tasks
* `demo`: An example agent to use for reference when learning to create your own agents
* `jira-helper`: An agent that assists you with all your Jira-related tasks
* `sql`: A universal SQL agent that enables you to talk to any relational database in natural language
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# AIChat to Loki Migration Guide
Loki originally started as a fork of AIChat but has since evolved into its own separate project with separate goals.
As a result, there's some changes you'll need to make to your AIChat configuration to be able to use Loki.
Be sure you've followed the [first-time setup steps](../README.md#first-time-setup) so that the Loki configuration
directory and subdirectories exist and is populated with the built-in defaults.
## Global Configuration File
You should be able to copy/paste your AIChat configuration file into your Loki configuration directory. Since the
location of the Loki configuration directory varies between systems, you can use the following command to locate your
config directory:
```shell
loki --info | grep 'config_dir' | awk '{print $2}'
```
Then, you'll need to make the following changes:
* `function_calling` -> `function_calling_support`
* `use_tools` -> `enabled_tools`
* `agent_prelude` -> `agent_session`
* `compress_threshold` -> `compression_threshold`
* `summarize_prompt` -> `summarization_prompt`
* `summary_prompt` -> `summary_context_prompt`
## Roles
Locate your `roles` directory using the following command:
```shell
loki --info | grep 'roles_dir' | awk '{print $2}'
```
Update any roles that have `use_tools` to `enabled_tools`.
## Sessions
Locate your `sessions` directory using the following command:
```shell
loki --info | grep 'sessions_dir' | awk '{print $2}'
```
Update the following settings:
* `use_tools` -> `enabled_tools`
* `compress_threshold` -> `compression_threshold`
* `summarize_prompt` -> `summarization_prompt`
* `summary_prompt` -> `summary_context_prompt`
---
# LLM Functions Changes
Probably the most significant difference between AIChat and Loki is how tools are handled. So if you cloned the
[llm-functions](https://github.com/sigoden/llm-functions) repo, you'll need to make the following changes.
**Note: JavaScript functions are not supported in Loki.**
The following guide assumes you're using the `llm-functions` repository as your base for custom functions, and thus
follows that directory structure.
## Agents
Agents are now all handled in one place: the `agents` directory (`<loki-config-dir>/agents`):
```shell
loki --info | grep 'agents_dir' | awk '{print $2}'
```
And instead of separate `index.yaml` and `config.yaml` files, they're now both in a single `config.yaml` file.
So now for all of your agents, copy all the contents of those directories to the corresponding directory in the Loki
`agents` directory. Then make the following changes:
* Copy the contents of your `<aichat-config-dir>/functions/agents` directory into `<loki-config-dir/agents`
* Merge `index.yaml` into `config.yaml`
* If you never created a custom `config.yaml` file, then simply rename `index.yaml` to `config.yaml`
* If you've defined an `agent_prelude`, rename that field to `agent_session`
* Convert all JavaScript tools to either Python or Bash
* For Bash `tools.sh`: Remove the following line:
```bash
eval "$(argc --argc-eval "$0" "$@")"
```
* Any `tools.txt` files you have that define what global functions the agent uses is now replaced by the `global_tools`
field in the agent's `config.yaml`. So for example: If your `tools.txt` looks like this:
```text
fs_mkdir.sh
fs_ls.sh
fs_patch.sh
fs_cat.sh
```
then you need to add the following to your agent's `config.yaml`:
```yaml
global_tools:
- fs_mkdir.sh
- fs_ls.sh
- fs_patch.sh
- fs_cat.sh
```
* If you have any bash `tools.sh` that depend on the utility scripts in the `llm-functions` repository, they've been
replaced by built-in utility scripts. So use the following to replace any matching lines in your `tools.sh` files:
```bash
##################
## Scripts file ##
##################
ROOT_DIR="${LLM_ROOT_DIR:-$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)}"
# replace with
source "$LLM_PROMPT_UTILS_FILE"
#######################
## guard_path script ##
#######################
"$ROOT_DIR/utils/guard_path.sh"
# replace with
guard_path
############################
## guard_operation script ##
############################
"$ROOT_DIR/utils/guard_operation.sh"
# replace with
guard_operation
######################
## patch.awk script ##
######################
awk -f "$ROOT_DIR/utils/patch.awk"
# replace with
patch_file
```
When you're done with this migration, you should have the following:
* No more `functions/agents` directory
* No `functions/agents.txt` file (Loki assumes that if the agent directory exists, it is loadable)
* No `<loki-config-dir>/agents/<agent-name>/tools.txt`
* No `<loki-config-dir>/agents/<agent-name>/index.yaml`
## Functions
Loki consolidates much of the `llm-functions` repo functionality into one binary. So this means
* There's no need to have `argc` installed anymore
* No separate repository to manage
* No `tools.txt`
* No `functions.json`
* No `functions/mcp` directory at all
* No `functions/scripts`
Here's how to migrate your functions over to Loki from the `llm-functions` repository.
* Copy your AIChat `<aichat-config-dir>/functions` directory into your Loki config directory
* Delete the following files and directories from your `<loki-config-dir>/functions` directory:
* `scripts/`
* `agents.txt`
* `functions.json`
* `Argcfile.sh`
* `README.md` (irrelevant now)
* `LICENSE` (irrelevant now)
* `utils/guard_operation.sh`
* `utils/guard_path.sh`
* `utils/patch.awk`
* Everything in `tools.txt` now lives in the global config file under the `visible_tools` setting:
```text
get_current_weather.sh
execute_command.sh
web_search.sh
#execute_py_code.py
query_jira_issues.sh
```
becomes the following in your `<loki-config-dir>/config.yaml`
```yaml
visible_tools:
- get_current_weather.sh
- execute_command.sh
- web_search.sh
# - web_search.sh
- query_jira_issues.sh
```
* If you've defined a `functions/mcp.json` file, you can leave it alone.
* Similarly to agents, if you have any bash `tools.sh` that depend on the utility scripts in the `llm-functions`
repository, they've been replaced by built-in utility scripts. So use the following to replace any matching lines in
your `tools.sh` files:
```bash
##################
## Scripts file ##
##################
ROOT_DIR="${LLM_ROOT_DIR:-$(cd "$(dirname "${BASH_SOURCE[0]}")/.." && pwd)}"
# replace with
source "$LLM_PROMPT_UTILS_FILE"
#######################
## guard_path script ##
#######################
"$ROOT_DIR/utils/guard_path.sh"
# replace with
guard_path
############################
## guard_operation script ##
############################
"$ROOT_DIR/utils/guard_operation.sh"
# replace with
guard_operation
######################
## patch.awk script ##
######################
awk -f "$ROOT_DIR/utils/patch.awk"
# replace with
patch_file
```
Refer to the [custom bash tools docs](./function-calling/CUSTOM-BASH-TOOLS.md) to learn how to compile and test bash
tools in Loki without needing to use `argc`.
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# Environment Variables
Loki is designed to be highly dynamic and customizable. As a result, Loki utilizes a number of environment variables
that can be used to modify its behavior at runtime without needing to modify the existing configuration files.
Loki also supports defining environment variables via a `.env` file in the Loki configuration directory. This directory
varies between systems, so you can find the location of your configuration directory using the following command:
```shell
loki --info | grep 'config_dir' | awk '{print $2}'
```
## Quick Links
<!--toc:start-->
- [Global Configuration Related Variables](#global-configuration-related-variables)
- [Client Related Variables](#client-related-variables)
- [Files and Directory Related Variables](#files-and-directory-related-variables)
- [Agent Related Variables](#agent-related-variables)
- [Logging Related Variables](#logging-related-variables)
<!--toc:end-->
---
## Global Configuration Related Variables
All configuration items in the global config file have environment variables that can be overridden at runtime. To see
all configuration options and more thorough descriptions, refer to the [example config file](../config.example.yaml).
Below are the most commonly used configuration settings and their corresponding environment variables:
| Setting | Environment Variable |
|----------------------------|---------------------------------|
| `model` | `LOKI_MODEL` |
| `temperature` | `LOKI_TEMPERATURE` |
| `top_p` | `LOKI_TOP_P` |
| `stream` | `LOKI_STREAM` |
| `save` | `LOKI_SAVE` |
| `editor` | `LOKI_EDITOR` |
| `wrap` | `LOKI_WRAP` |
| `wrap_code` | `LOKI_WRAP_CODE` |
| `save_session` | `LOKI_SAVE_SESSION` |
| `compression_threshold` | `LOKI_COMPRESSION_THRESHOLD` |
| `function_calling_support` | `LOKI_FUNCTION_CALLING_SUPPORT` |
| `enabled_tools` | `LOKI_ENABLED_TOOLS` |
| `mcp_server_support` | `LOKI_MCP_SERVER_SUPPORT` |
| `enabled_mcp_servers` | `LOKI_ENABLED_MCP_SERVERS` |
| `rag_embedding_model` | `LOKI_RAG_EMBEDDING_MODEL` |
| `rag_reranker_model` | `LOKI_RAG_RERANKER_MODEL` |
| `rag_top_k` | `LOKI_RAG_TOP_K` |
| `rag_chunk_size` | `LOKI_RAG_CHUNK_SIZE` |
| `rag_chunk_overlap` | `LOKI_RAG_CHUNK_OVERLAP` |
| `highlight` | `LOKI_HIGHLIGHT` |
| `theme` | `LOKI_THEME` |
| `serve_addr` | `LOKI_SERVE_ADDR` |
| `user_agent` | `LOKI_USER_AGENT` |
| `save_shell_history` | `LOKI_SAVE_SHELL_HISTORY` |
| `sync_models_url` | `LOKI_SYNC_MODELS_URL` |
## Client Related Variables
The following environment variables are available for clients in Loki:
| Environment Variable | Description |
|----------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| `{client}_API_KEY` | For clients that require an API key, you can define the keys either through environment variables or <br>using the [vault](./VAULT.md). The variables are named after the client to which they apply; <br>e.g. `OPENAI_API_KEY`, `GEMINI_API_KEY`, etc. |
| `LOKI_PLATFORM` | Combine with `{client}_API_KEY` to run Loki without a configuration file. <br>This variable is ignored if a configuration file exists. |
| `LOKI_PATCH_{client}_CHAT_COMPLETIONS` | Patch chat completion requests to models on the corresponding client; Can modify the URL, body, <br>or headers. |
| `LOKI_SHELL` | Specify the shell that Loki should be using when executing commands |
## Files and Directory Related Variables
You can also customize the files and directories that Loki loads its configuration files from:
| Environment Variable | Description | Default Value |
|----------------------|------------------------------------------------------------------------|---------------------------------|
| `LOKI_CONFIG_DIR` | Customize the location of the Loki configuration directory. | `<user-config-dir>/loki` |
| `LOKI_ENV_FILE` | Customize the location of the `.env` file to load at startup. | `<loki-config-dir>/.env` |
| `LOKI_CONFIG_FILE` | Customize the location of the global `config.yaml` configuration file. | `<loki-config-dir>/config.yaml` |
| `LOKI_ROLES_DIR` | Customize the location of the `roles` directory. | `<loki-config-dir>/roles` |
| `LOKI_SESSIONS_DIR` | Customize the location of the `sessions` directory. | `<loki-config-dir>/sessions` |
| `LOKI_RAGS_DIR` | Customize the location of the `rags` directory. | `<loki-config-dir>/rags` |
| `LOKI_FUNCTIONS_DIR` | Customize the location of the `functions` directory. | `<loki-config-dir>/functions` |
## Agent Related Variables
You can also customize the location of full agent configurations using the following environment variables:
| Environment Variable | Description |
|------------------------------|-------------------------------------------------------------------------------------------------------------------------------------|
| `<AGENT_NAME>_CONFIG_FILE | Customize the location of the agent's configuration file; e.g. `SQL_CONFIG_FILE` |
| `<AGENT_NAME>_MODEL` | Customize the `model` used for the agent; e.g `SQL_MODEL` |
| `<AGENT_NAME>_TEMPERATURE` | Customize the `temperature` used for the agent; e.g. `SQL_TEMPERATURE` |
| `<AGENT_NAME>_TOP_P` | Customize the `top_p` used for the agent; e.g. `SQL_TOP_P` |
| `<AGENT_NAME>_GLOBAL_TOOLS` | Customize the `global_tools` that are enabled for the agent (a JSON string array); e.g. `SQL_GLOBAL_TOOLS` |
| `<AGENT_NAME>_MCP_SERVERS` | Customize the `mcp_servers` that are enabled for the agent (a JSON string array); e.g. `SQL_MCP_SERVERS` |
| `<AGENT_NAME>_AGENT_SESSION` | Customize the `agent_session` used with the agent; e.g. `SQL_SESSION` |
| `<AGENT_NAME>_INSTRUCTIONS` | Customize the `instructions` for the agent; e.g. `SQL_INSTRUCTIONS` |
| `<AGENT_NAME>_VARIABLES` | Customize the `variables` used for the agent (in JSON format of `[{"key1": "value1", "key2": "value2"}]`); <br>e.g. `SQL_VARIABLES` |
## Logging Related Variables
The following variables can be used to change the log level of Loki or the location of the log file:
| Environment Variable | Description | Default Value |
|----------------------|---------------------------------------------|----------------------------------|
| `LOKI_LOG_LEVEL` | Customize the log level of Loki | `INFO` |
| `LOKI_LOG_FILE` | Customize the location of the Loki log file | `<user-cache-dir>/loki/loki.log` |
**Pro-Tip:** You can always tail the Loki logs using the `--tail-logs` flag. If you need to disable color output, you
can also pass the `--disable-log-colors` flag as well.
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# Macros
Macros are essentially Loki "scripts"; that is, a predefined sequence of REPL commands that automate repetitive tasks or
workflows. Macros run in isolated environments, ensuring that the macros don't inherit any pre-existing role, session,
RAG, or agent state, and they will not affect your current context.
This isolation ensures that your workspace remains clean and unaffected by macro operations.
![Macro Example](./images/macros/macros-example.gif)
For more information on Loki's REPL, refer to the [REPL](./REPL.md) documentation.
## Quick Links
<!--toc:start-->
- [Macro Definition](#macro-definition)
- [Step Definitions](#step-definitions)
- [Macro Variables](#macro-variables)
- [Built-In Macros](#built-in-macros)
<!--toc:end-->
---
## Macro Definition
Macros are defined as YAML files in the `macros` subdirectory of your Loki configuration directory. The Loki configuration
directory can vary between systems, so to find the location of your macros config directory, you can use the following
command:
```shell
loki --info | grep 'macros_dir' | awk '{print $2}'
```
Macro definitions are broken into two parts: the `steps` of the macro, and an optional `variables` section that lets
users pass in variables to alter the behavior of the macro at runtime.
### Step Definitions
The step definitions for a macro are straightforward: They are simply the exact commands you would otherwise type in the
REPL.
**Example: Macro to generate a git commit message**
`macros/generate-commit-message.yaml`
```yaml
steps:
- .file `git diff` -- generate git commit message
```
Usage:
```shell
$ loki --macro generate-commit-message
>> .file `git diff` -- generate a git commit message
Add documentation on macros
```
For a full example configuration, refer to the [example macro configuration file](../config.macro.example.yaml) in the root of this project.
### Macro Variables
Sometimes it's useful to be able to modify the behavior of a macro at runtime. This is achieved with the `variables`
array of the macro definition.
To pass variables to a macro, since they are just Loki scripts, the syntax is the same as it is for any other scripting
language: You just pass them alongside your invocation.
**Example:**
```shell
$ loki --macro example-variable-macro first_argument second_argument
```
Each variable in the `variables` array has the following properties:
* `name` (Required): the name of the variable, which can be referenced in the actual steps of the macro using the
`{{name}}` syntax.
* `default` (Optional): A default value for the variable if no value is specified. If no default value is defined, and
no value is provided for the variable at runtime, Loki will error out.
* `rest` (Optional, Boolean): When set to `true`, this variable will collect all remaining arguments passed to the
macro. This behavior is only applicable when the variable is the last variable in the list. By default, this is
`false`.
The `variables` array is order-dependent; that is to say that all arguments passed to the macro are positional. So be
careful about the ordering if that is important to your macro's invocation.
**Example: Simple variable example to invoke an agent**
`macros/invoke-agent.yaml`
```yaml
variables:
- name: agent # No default value means this must be defined at runtime
- name: args
rest: true # All remaining arguments to the macro are collected into this variable
default: What can you do? # This is used if no value is passed at runtime
steps:
- .agent {{agent}}
- '{{args}}'
```
Usage:
```shell
$ loki --macro invoke-agent sql
# or
$ loki --macro invoke-agent sql What tables are available?
```
For a full example configuration, refer to the [example macro configuration file](../config.macro.example.yaml) in the root of this project.
## Built-In Macros
Loki comes packaged with some useful built-in macros. These are also good examples if you're looking for more examples
on how to make your own macros, so be sure to check out the [built-in macro definitions](../assets/macros) if you're
looking for more examples.
* `generate-commit-message` - Generate a Git commit message based on the staged changes in the current directory
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# RAG
Retrieval Augmented Generation (RAG) is a method of minimizing LLM hallucinations and extending the model's context
without consuming a significant portion of the context length. It uses documents and other additional resources that you
provide to give the model more context for all of your prompts.
Loki has a built-in vector database and full-text search engine to support RAG knowledge bases for your queries.
The generated knowledge bases are stored in the `rag` subdirectory of your Loki configuration directory. The location of
this directory varies by system, so you can use the following command to find your RAG directory:
```shell
loki --info | grep 'rags_dir' | awk '{print $2}'
```
## Quick Links
<!--toc:start-->
- [Usage](#usage)
- [Persistent RAG](#persistent-rag)
- [Ephemeral RAG](#ephemeral-rag)
- [How It Works](#how-it-works)
- [1. Build](#1-build)
- [2. Lookup](#2-lookup)
- [2a. Reranking (Optional)](#2a-reranking-optional)
- [3. Prompt](#3-prompt)
- [Supported Document Sources](#supported-document-sources)
- [Document Loaders](#document-loaders)
- [Document Loader Usage](#document-loader-usage)
- [Advanced Customizations](#advanced-customizations)
- [Embedding Model](#embedding-model)
- [Reranker](#reranker)
- [Chunk Size](#chunk-size)
- [Trade-Offs](#chunk-size-trade-offs)
- [Chunk Overlap](#chunk-overlap)
- [Top K](#top-k)
- [Trade-Offs](#top-k-trade-offs)
- [RAG Template](#rag-template)
<!--toc:end-->
---
## Usage
There's two ways to use RAG in Loki: A persistent RAG that can be loaded on-demand for queries, and an ephemeral one for
adding RAG to a single specific query.
### Persistent RAG
In the REPL, persistent RAG is initialized via the `.rag` command:
![Persistent RAG example](./images/rag/persistent-rag.gif)
The generated RAG is then saved to the `rag` subdirectory of the Loki configuration, and can then be loaded whenever you
want that knowledge base via either `.rag <name>` or `loki --rag <RAG>`.
### Ephemeral RAG
Short-lived RAG that is only used for a single session or query is loaded using `.file`/`--file`.
You can use it to either execute a prompt from a file, or for temporary RAG. The difference is the usage of the `--`
separator. If you only specify a filename and no `--` separator, Loki will know to read the file contents and pass them
as a query to the model. Otherwise, the `--` separator is read to indicate that this is the end of the list of documents
to load into the ephemeral RAG, and what follows is the query to pass to the model.
```shell
.file prompt.md # Read the file as a prompt
.file %% -- translate the last reply to italian
.file `git diff` -- generate a commit message
```
![Ephemeral RAG Example](./images/rag/ephemeral-rag.gif)
Once the session ends, this RAG will no longer be accessible and is only visible to the current session.
#### The `%%` Document Type
In addition to the usual documents that can be specified for persistent RAG, ephemeral RAG has a special `%%` value.
This value references the content of the last reply. So you can use it like this:
```shell
.file %% -- translate the last reply to italian
```
The `--` indicates that this is the end of your documents and the beginning of your prompt.
#### The `cmd` Document Type
Loki also lets you use command outputs for ephemeral RAG input. Simply enclose the command in backticks:
```shell
.file `git diff` -- generate a commit message
```
The `--` indicates that this is the end of your documents and the beginning of your prompt.
## How It Works
#### 1. Build
When you define RAG, Loki will first "build" the RAG. This means that Loki will consume the documents you specified and
generate [embeddings](https://huggingface.co/spaces/hesamation/primer-llm-embedding) for that text. This essentially just means that Loki translates the document into a language
the LLM can understand.
These embeddings are then stored in an in-memory vector database.
#### 2. Lookup
Loki sits between you and the model. So when you submit a prompt to the model, before Loki ever sends it, it will first
convert your prompt into embeddings (LLM language), and look for relevant snippets of text in the vector database.
Loki then passes the top `n`-snippets of text that it finds in the vector database as additional context to the model
before your prompt.
#### 2a. Reranking (Optional)
The lookup for relevant snippets of texts uses embeddings to find text that is semantically similar to your prompt, and
returns the top `n`-results. This often works fairly well, however these top results aren't always the most relevant for
answering the specific query.
Reranking improves these initial results (say, the top 20-100 text snippets) and re-scores them using a more
sophisticated model. The reranker model will rank documents by their actual usefulness for answering the query to ensure
the most relevant context is passed to the model alongside your query.
This reranking model can be customized for each RAG you build in Loki. See the [Custom Reranker](#reranker) section
below for more details on how to customize this.
#### 3. Prompt
Finally, the text snippets that were looked up in RAG are passed to the model as additional context to your prompt,
giving the model query-specific context to answer your question.
## Supported Document Sources
Loki supports a number of document sources that can be used for RAG:
| Source | Example | Comments |
|--------------------------|-----------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------|
| Files | `/tmp/dir1/file1;/tmp/dir1/file2` | |
| Directory | `/tmp/dir` | Picks up all files in a directory and all its subdirectories |
| Directory (extensions} | `/tmp/dir2/**/*.{md,txt}` | Finds all files in all subdirectories with the specified extensions |
| Recursive Filename | `/tmp/*/LOKI.md` | The following files will be picked up: <br><ul><li>`/tmp/dir1/LOKI.md`</li><li>`/tmp/dir2/subdir1/LOKI.md`</li><li>`/tmp/dir2/subdir2/LOKI.md`</li></ul> |
| URL | `https://www.ohdsi.org/data-standardization/` | Downloads and loads the specified webpage into the <br>knowledge base |
| Recursive URL (Websites) | `https://github.com/OHDSI/Vocabulary-v5.0/wiki/**` | Crawls all pages under the given URL and loads them <br>into the knowledge base |
| Document Loader (custom) | `jina:https://cloud.google.com/bigquery/docs/reference/standard-sql/` | Use a custom document loader to parse the given document |
## Document Loaders
Loki only has built-in support for loading text files. But that functionality can be extended to read all kinds of files
into your knowledge bases. These custom loaders are used by both RAG and for documents specified using the
`.file`/`--file` flags.
In the global configuration file, you can specify loaders for specific document types using the `document_loaders`
setting. Each loader is defined by specifying a name and then a command that Loki will execute to load the document.
The following variables are interpolated at runtime by Loki and can be used as placeholders in your command definitions:
* `$1` (Required) - The input file
* `$2` (Optional) - The output file. If omitted, `stdout` is used as the output destination
**Note:** It is your responsibility to ensure that any tools used to parse documents into text that Loki can read are
installed on your system and are available on your `$PATH`. Loki does not have any built-in way of installing
dependencies for document loaders for you.
The following are some example loaders:
```yaml
document_loaders:
pdf: 'pdftotext $1 -' # Use pdftotext to convert a PDF file to text
# (see https://poppler.freedesktop.org for details on how to install pdftotext)
docx: 'pandoc --to plain $1' # Use pandoc to convert a .docx file to text
# (see https://pandoc.org for details on how to install pandoc)
jina: 'curl -fsSL https://r.jina.ai/$1 -H "Authorization: Bearer {{JINA_API_KEY}}' # Use Jina to translate a website into text;
# Requires a Jina API key to be added to the Loki vault
git: > # Use yek to load a git repository into the knowledgebase (https://github.com/bodo-run/yek)
sh -c "yek $1 --json | jq 'map({ path: .filename, contents: .content })'"
```
### Document Loader Usage
Once you have your loaders defined, you can specify when Loki should use them by prefixing any RAG file/directory/URI
with the name of the loader.
**Example: Load a git repo into RAG**
![Git Repo Loader Example](./images/rag/git-loader.png)
**Example: Use pdf loader for ephemeral RAG**
```shell
$ loki --file pdf:some-file.pdf
```
## Advanced Customizations
For those familiar with RAG, Loki exposes a handful of advanced global settings that can be used to tweak your default
RAG configurations.
### Embedding Model
When Loki queries your RAG knowledge bases, it needs to first convert your query into embeddings. By default, Loki uses
the same embedding model that was used to create the knowledge base in the first place.
This can be customized to any other embedding model available in your configured clients by setting the
`rag_embedding_model` setting in your global Loki configuration file:
```yaml
rag_embedding_model: null # Specifies the embedding model used for context retrieval
```
### Reranker
By default, Loki uses [Reciprocal Rank Fusion (RRF)](https://www.elastic.co/docs/reference/elasticsearch/rest-apis/reciprocal-rank-fusion) to merge vector and keyword search results.
You can change the default reranker model to any other reranking model in your configured clients. To change the default
reranker model, simply change the value of the `rag_reranker_model` setting in your global configuration file:
```yaml
rag_reranker_model: null # By default,
```
### Chunk Size
In the context of RAG, the chunk size is the maximum length of each text chunk (measured in characters) that is created
when splitting documents. In Loki, this defaults to `2000` characters.
You can specify a different global default by setting the `rag_chunk_size` property in your global configuration file:
```yaml
rag_chunk_size: null # Defines the size of chunks for document processing in characters
```
#### Chunk Size Trade-Offs
Keep in mind the following trade-offs when changing the chunk size:
* **Smaller chunks (e.g. 256 characters):** More precise retrieval, better semantic focus, but may lack context or split
important information
* **Larger chunks (e.g. 1024 characters):** More context preserved, fewer chunks to manage, but less precise matching
and more noise in retrieved document
### Chunk Overlap
Chunk overlap in RAG is the number of characters that overlap between consecutive chunks to maintain continuity.
---
**Example:** If the following sentence is cut off at the end of one chunk
`I was doing fine until someone brought up`
You'll ideally want that full sentence to be picked up at the beginning of the next chunk to make sure the full meaning
is captured. So in this example, if your chunk overlap is 42 characters, then the start of the next chunk would look
like this:
`I was doing fine until someone brought up the game. <next sentence>`
---
Often, this value is 10%-20% of the chunk size.
By default, in Loki, this value is 5% the chunk size. You can override this and specify the default chunk overlap (in
characters) that Loki should use as a global default by setting the `rag_chunk_overlap` property in the global Loki
configuration file:
```yaml
rag_chunk_overlap: null # Defines the overlap between chunks
```
### Top K
In RAG, `top_k` represents the top `k`-chunks to return from the vector database query. Think of it like if you search
something on Google and only care about the top 10 results, that's what you'll use for your context.
In Loki, the default value for this is `5`. You can customize this global default by setting the `rag_top_k` property in
your global configuration file:
```yaml
rag_top_k: 5 # Specifies the number of documents to retrieve for answering queries
```
#### Top K Trade-Offs
When customizing this value, keep in mind the following trade-offs so you get the best performance:
* **Lower top_k (e.g. 3):** Faster, more focused context, lower cost, but risks missing relevant information
* **Higher top_k (e.g. 10):** More comprehensive coverage, but more noise, higher latency, increased token costs, and
potential context window constraints
### RAG Template
When you use RAG in Loki, after Loki performs the lookup for relevant chunks of text to add as context to your query, it
will add the retrieved text chunks as context to your query before sending it to the model. The format of this context
is determined by the `rag_template` setting in your global Loki configuration file.
This template utilizes two placeholders:
* `__INPUT__`: The user's actual query
* `__CONTEXT__`: The context retrieved from RAG
These placeholders are replaced with the corresponding values into the template and make up what's actually passed to
the model at query-time.
The default template that Loki uses is the following:
```text
Answer the query based on the context while respecting the rules. (user query, some textual context and rules, all inside xml tags)
<context>
__CONTEXT__
</context>
<rules>
- If you don't know, just say so.
- If you are not sure, ask for clarification.
- Answer in the same language as the user query.
- If the context appears unreadable or of poor quality, tell the user then answer as best as you can.
- If the answer is not in the context but you think you know the answer, explain that to the user then answer with your own knowledge.
- Answer directly and without using xml tags.
</rules>
<user_query>
__INPUT__
</user_query>
```
You can customize this template by specifying the `rag_template` setting in your global Loki configuration file. Your
template *must* include both the `__INPUT__` and `__CONTEXT__` placeholders in order for it to be valid.
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# Customize REPL Prompt
The prompt you see when you start the Loki REPL can be customized to your liking. This is achieved via the `left_prompt`
and `right_prompt` settings in the global Loki configuration file:
```yaml
left_prompt: '{color.red}{model}){color.green}{?session {?agent {agent}>}{session}{?role /}}{!session {?agent {agent}>}}{role}{?rag @{rag}}{color.cyan}{?session )}{!session >}{color.reset} '
right_prompt: '{color.purple}{?session {?consume_tokens {consume_tokens}({consume_percent}%)}{!consume_tokens {consume_tokens}}}{color.reset}'
```
The location of the global configuration file differs between systems, so you can use the following command to find your
global configuration file's location:
```shell
loki --info | grep 'config_file' | awk '{print $2}'
```
## Quick Links
<!--toc:start-->
- [Syntax](#syntax)
- [Variables](#variables)
<!--toc:end-->
## Syntax
The syntax for the prompts consists of plain text and templates contained in `{...}`. The plain text is
printed exactly as given.
The syntax for the templates `{...}` is as follows:
* `{variable}` - Replaced with the value of `variable`
* `{?variable <template>}` - Evaluate the `<template>` when `variable` is evaluated to `true`
* `{!variable <template>}` - Evaluate the `<template>` when `variable` is evaluated to `false`
Where a `<template>` is another expression consisting of plain text and/or more special computations inside `{...}`.
Variables are evaluated to also be "truthy"; that is, if a variable is undefined, it is considered to be the exact same
as if that variable's value was `false`.
**Example 1: Simple Boolean Usage**
For the prompt `{?variable yay}{!variable boo}`, if `variable=true`, then the output will be
```
yay
```
And if `variable=false`:
```
boo
```
**Example 2: Nested Expressions**
For the prompt `{?variable {!variable2 yay}>}`, and assuming
* `variable=true`
* `variable2=false`
the output will be
```
yay>
```
If `variable2=true`, the output will be empty.
If `variable=false`, the output will be empty.
## Variables
The following variables and output modifiers are available to you when you're creating your prompts:
```yaml
# Model Variables
model: openai:gpt-4 # The active model's full name
client_name: openai # The name of the client serving the active model
model_name: gpt-4 # The aliased name of the active model
max_input_tokens: 4096 # The maximum number of input tokens for the active model
# Configuration Variables
temperature: 1.0 # The temperature for the active model
top_p: 0.9 # The top_p for the active model
dry_run: true # Whether the given command is flagged to be a dry run
stream: false # Whether streaming responses are enabled
save: true # Whether shell history is saved
wrap: 120 # The number of characters to allow before wrapping around output to the next line
# Role Variables
role: code # The active role
# Session Variables
session: temp # The name of the active session
dirty: false # Whether the session settings have been updated but not persisted
consume_tokens: 200 # The number of tokens consumed
consume_percent: 1% # The percentage of tokens consumed to the maximum input tokens
user_messages_len: 0 # The total number of sent user messages
# RAG Variables
rag: temp # The name of the active RAG
# Agent Variables
agent: todo-sh # The name of the active agent
# ANSI COLORS
color.reset:
color.black:
color.dark_gray:
color.red:
color.light_red:
color.green:
color.light_green:
color.yellow:
color.light_yellow:
color.blue:
color.light_blue:
color.purple:
color.light_purple:
color.magenta:
color.light_magenta:
color.cyan:
color.light_cyan:
color.white:
color.light_gray:
```
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# Loki REPL Guide
In addition to being a CLI, Loki also has a built-in REPL (Read-Execute-Print-Loop). This enables users to quickly try
out prompts, commands, configurations, and everything in between without having to modify the same command every time.
You can enter the REPL by simply typing `loki` without any follow-up flags or arguments.
## Quick Links
<!--toc:start-->
- [Features](#features)
- [REPL Commands](#repl-commands)
- [`.model` - Change the current LLM](#model---change-the-current-llm)
- [`.role` - Role management](#role---role-management)
- [`.prompt` - Set a temporary role using a prompt](#prompt---set-a-temporary-role-using-a-prompt)
- [`.session` - Session management](#session---session-management)
- [`.agent` - Chat with an AI agent](#agent---chat-with-an-ai-agent)
- [`.rag` - Chat with documents](#rag---chat-with-documents)
- [`.macro` - Execute a macro](#macro---execute-a-macro)
- [`.file` - Read files and use them as input](#file---read-files-and-use-them-as-input)
- [`.vault` - Manage the Loki vault](#vault---manage-the-loki-vault)
- [`.continue` - Continue the previous response](#continue---continue-the-previous-response)
- [`.regenerate` - Regenerate the last response](#regenerate---regenerate-the-last-response)
- [`.copy` - Copy the last response to your clipboard](#copy---copy-the-last-response-to-your-clipboard)
- [`.set` - Adjust runtime settings](#set---adjust-runtime-settings)
- [`.edit` - Modify configuration files](#edit---modify-configuration-files)
- [`.delete` - Delete configurations from Loki](#delete---delete-configurations-from-loki)
- [`.info` - Display information about the current mode](#info---display-information-about-the-current-mode)
- [`.exit` - Exit an agent/role/session/rag or the Loki REPL itself](#exit---exit-an-agentrolesessionrag-or-the-loki-repl-itself)
- [`.help` - Show the help guide](#help---show-the-help-guide)
<!--toc:end-->
---
## Features
The REPL has features that are intended to make your Loki experience as easy and as enjoyable as possible! This includes
things like
* **Tab Autocompletion:** Every command in the REPL (i.e. everything that starts with a `.`) has fuzzy search auto
completions.
* `.<tab>` to complete REPL commands
* `.model <tab>` to complete chat models
* `.set <tab>` to complete configuration keys
* `.set key <tab>` to complete configuration values
* **Multi-Line Prompts:** You can also type prompts that span more than one line to help organize your thoughts. This
can be done in the following ways:
* `Ctrl-o` to open the current input buffer in your preferred editor (either the value of `editor` or `$EDITOR`)
* You can paste multi-line text
* You can type `:::` to start multi-line editing, and use `:::` to finish it.
* And finally, you can use hotkeys like `{ctrl/shift/alt}+enter` or `ctrl-j` to insert a new line directly in the
REPL.
* **History Search** Press `ctrl+r` to search the REPL history, and navigate it with `↑↓`
* **Configurable Keybindings:** You can switch between `emacs` style keybindings or `vi` style keybindings
* [**Custom REPL Prompt:**](./REPL-PROMPT.md) You can even customize the REPL prompt to display information about the
current context in the prompt
---
## REPL Commands
All REPL commands begin with a `.` to indicate that they're not part of a prompt. The following list details the
commands available in Loki:
### `.model` - Change the current LLM
When browsing models in the REPL, use the following legend to understand the purpose of each column in the model table:
```
openai:gpt-4o 128000 / 4096 | 5 / 15 👁 ⚒
| | | | | | └─ supports function calling
| | | | | └─ support vision (multi-modal)
| | | | └─ output price ($/1M)
| | | └─ input price ($/1M)
| | |
| | └─ max output tokens
| └─ max input tokens
└─ model id
```
![model](./images/repl/model.gif)
For more information about how to add models to Loki, refer to the [clients documentation](./clients/CLIENTS.md).
### `.role` - Role management
Loki offers the following commands to manage your roles:
| Command | Description |
|--------------|-------------------------------------------------------------------------|
| `.role` | Create or switch to a role |
| `.info role` | Show information about the active role |
| `.edit role` | Open the active role's configuration file in your preferred text editor |
| `.save role` | Save the active role and its configurations to a configuration file |
| `.exit role` | Exit the active role |
![role](./images/roles/code.gif)
For more information about roles in Loki and how to build them, refer to the [roles documentation](./ROLES.md).
### `.prompt` - Set a temporary role using a prompt
If you need to create a temporary role that you want to discard after use, you use `.prompt`. `.prompt`-based roles
cannot be persisted to a file and saved.
![prompt-role](./images/roles/prompt-role.gif)
### `.session` - Session management
Use the following commands to manage sessions in Loki:
| Command | Description |
|---------------------|---------------------------------------------------------------------------------------------|
| `.session` | Start or switch to a session |
| `.empty session` | Clear all messages for the active session |
| `.compress session` | Compress the session messages using the `summarization_prompt` setting in the global config |
| `.info session` | Display information about the active session |
| `.edit session` | Open the active session's configuration in your preferred text editor |
| `.save session` | Save the active session to a `session` configuration file |
| `.exit session` | Exit the active session |
![sessions](./images/sessions/sessions-example.gif)
For more information on sessions and how to use them in Loki, refer to the [sessions documentation](./SESSIONS.md).
### `.agent` - Chat with an AI agent
Loki lets you build OpenAI GPT-style agents. The following commands let you interact with and manage your agents in
Loki:
| Command | Description |
|----------------------|------------------------------------------------------------|
| `.agent` | Use an agent |
| `.starter` | Display and use conversation starters for the active agent |
| `.edit agent-config` | Open the agent configuration in your preferred text editor |
| `.info agent` | Display information about the active agent |
| `.exit agent` | Leave the active agent |
![agent](./images/agents/sql.gif)
For more information on agents in Loki and how to create them, refer to the [agents documentation](./AGENTS.md).
### `.rag` - Chat with documents
RAG (Retrieval Augmented Generation) enables you to load documents into the LLM so you can ask questions about it or
complete tasks using the documents as additional context.
| Command | Description |
|------------------|------------------------------------------------------------------------------|
| `.rag` | Initialize or access a RAG |
| `.edit rag-docs` | Add or remove documents from the active RAG using your preferred text editor |
| `.rebuild rag` | Rebuild the active RAG to accommodate document changes |
| `.sources rag` | Show a works-cited of the sources used in the last query |
| `.info rag` | Display information about the active RAG |
| `.exit rag` | Exit the active RAG |
![rag](./images/rag/persistent-rag.gif)
For more information about RAG in Loki and how to utilize it, refer to the [rag documentation](./RAG.md).
### `.macro` - Execute a macro
Macros in Loki are like "scripts" of commands that can be run in isolated environments; that means they do not use any
active settings and use the same settings they had when written. They are created/executed using the `.macro <name>`
command.
![macro](./images/macros/macros-example.gif)
For more information on macros in Loki and how to create them, refer to the [macros documentation](./MACROS.md).
### `.file` - Read files and use them as input
Loki lets you specify any number of documents that you can load and use as ephemeral RAG to chat with the LLM. To see
what files or values you can pass to it, simply run the command `.file` with no arguments:
```shell
openai:gpt-4o)> .file
Usage: .file <file|dir|url|%%|cmd>... [-- <text>...]
```
![ephemeral-rag](./images/rag/ephemeral-rag.gif)
For more information about ephemeral RAG, refer to the [ephemeral RAG documentation](./RAG.md#ephemeral-rag).
### `.vault` - Manage the Loki vault
The Loki vault lets users store sensitive secrets and credentials securely so that there's no plaintext secrets
anywhere in your configurations.
![vault](./images/vault/vault-demo.gif)
For more information about the Loki vault, refer to the [vault documentation](./VAULT.md).
### `.continue` - Continue the previous response
When you have a response that exceeds the context length, you can use the `.continue` command to continue the generation
of the last response.
![continue](./images/repl/continue.gif)
### `.regenerate` - Regenerate the last response
If ever your response is interrupted, or you want to try generating it again, you can use the `.regenerate` command to do
this without having to retype your query:
![regenerate](./images/repl/regenerate.gif)
### `.copy` - Copy the last response to your clipboard
If you're trying to copy the last response (like copying some code), you can use the `.copy` command to copy the entire
last response to your system clipboard:
![copy](./images/repl/copy.gif)
### `.set` - Adjust runtime settings
You can use `.set` to adjust select settings at runtime. This is useful when you're experimenting with settings and want
to know how they'll affect Loki. To persist the changes you make, be sure to update them in the global configuration
file.
![set](./images/repl/set.gif)
### `.edit` - Modify configuration files
The `.edit` command lets you modify configuration files for the current mode of the REPL. It will open the selected
configuration in your preferred text editor. It lets you modify the following configurations:
* `.edit config` - Modify the global configuration
* `.edit role` - Modify the active role's configuration
* `.edit session` - Modify the active session's configuration
* `.edit agent-config` - Modify the active agent's configuration
* `.edit rag-docs` - Add or remove documents from the active RAG
### `.delete` - Delete configurations from Loki
The `.delete` command allows you to delete entities in Loki without having to directly run `rm -rf` on the configuration
directory or file corresponding to the target entity. You can use it to delete the following entities:
* `.delete role` - Delete select roles
* `.delete session` - Delete select sessions
* `.delete macro` - Delete select macros
* `.delete rag` - Delete select RAGs
* `.delete agent-data` - Delete select agent's configurations and all tools
### `.info` - Display information about the current mode
The `.info` command provides useful information about different modes that Loki may be operating in. It's helpful if you
want a quick understanding of the system info, a role's configuration, an agent's configuration, etc.
The following entities are supported:
| Command | Description |
|-----------------|-------------------------------------------------------------|
| `.info` | Display system information (identical to the `--info` flag) |
| `.info role` | Display information about the active role |
| `.info session` | Display information about the active session |
| `.info agent` | Display information about the active agent |
| `.info rag` | Display information about the active RAG |
### `.exit` - Exit an agent/role/session/rag or the Loki REPL itself
The `.exit` command is used to move between modes in the Loki REPL.
| Command | Description |
|-----------------|-------------------------|
| `.exit role` | Exit the active role |
| `.exit session` | Exit the active session |
| `.exit agent` | Exit the active agent |
| `.exit rag` | Exit the active RAG |
| `.exit` | Exit the Loki REPL |
### `.help` - Show the help guide
Just like with any shell or REPL, you sometimes need a little help and want to know what commands are available to you.
That's when you use the `.help` command.
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# Roles
When customizing the behavior or LLMs, we use roles to "constrain" the responses or behavior of the LLM to whatever
purpose we desire.
Think of them kind of like a baby: That baby can grow up to do anything! Be a resume builder, teacher, engineer, etc.
The only difference is that with roles, we're explicitly telling the LLM what we want it to be. Also: the LLM is already
grown up so we don't have to wait!
![Role demo](./images/roles/code.gif)
## Quick Links
<!--toc:start-->
- [Role Definition](#role-definition)
- [Metadata Header](#metadata-header)
- [Instructions](#instructions)
- [Special Case: Metadata Header Only](#special-case-metadata-header-only)
- [Prompt Types](#prompt-types)
- [Embedded Prompts](#embedded-prompts)
- [System Prompts](#system-prompts)
- [Few-Shot Prompt](#few-shot-prompt)
- [Built-In Roles](#built-in-roles)
<!--toc:end-->
---
## Role Definition
Roles in Loki are Markdown files that live in the `roles` directory of your Loki configuration. Loki configuration
locations vary between systems, so you can use the following command to find the location of your roles configuration
directory:
```shell
loki --info | grep 'roles_dir' | awk '{print $2}'
```
All role configuration files have two parts: The metadata header, and the instructions.
**Example:** An expert resume builder role that specializes in helping users build and refine their resumes.
```markdown
---
# This is the metadata header
name: resume-builder
model: openai:gpt-4o
temperature: 0.2
top_p: 0
enabled_tools: fs_ls,fs_cat
enabled_mcp_servers: github
---
<!-- This is the instructions -->
You are an expert resume builder.
```
To see a full example configuration for a role, refer to the [example role configuration](../config.role.example.md)
file in the root of the repo.
### Metadata Header
The metadata header in all role configuration files is completely optional. It lets you define role-specific settings
for each role that make the model work the way you want for your role. This includes things like forcing your role to
always use a specific model, set of tools, and tailoring the hyperparameters of the model for your role.
The header consists of a YAML-formatted list of settings that let you customize the model behavior for your role. These
settings sit between `---` separators in your role configuration so Loki knows they're not part of the instructions you
want to feed the model.
The following table lists the available configuration settings and their default values (if undefined):
| Setting | Default | Description |
|-----------------------|----------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------|
| `name` | The name of the role markdown file | The name of the role |
| `model` | Default configured model or currently in-use model (REPL mode) | The preferred model to use with this role |
| `temperature` | Default `temperature` for the preferred model | Controls the creativity and randomness of the model's responses |
| `top_p` | Default `top_p` for the preferred model | Alternative way to control the model's output diversity, affecting the <br>probability distribution of tokens |
| `enabled_tools` | Global setting for `enabled_tools` | The tools that this role utilizes |
| `enabled_mcp_servers` | Global setting for `enabled_mcp_servers` | The MCP servers that this role utilizes |
| `prompt` | `null` | See [Prompt Types](#prompt-types) for detailed usage |
### Instructions
The instructions for a role is what you use to tell the model how you want it to behave. This typically consists of one
or two sentences, but can be more. To see some examples, look at the [built-in roles](../assets/roles) to see how they are defined.
**Pro-Tip:** The struggle to create good instructions for a role (or any other kind of instructions for your model) is
so common, that Loki comes with a role to help you write instructions for roles! Simply invoke the role to start
creating a role with the `create-prompt` role:
```shell
loki -r create-prompt
```
### Special Case: Metadata Header Only
When instructions are defined, the metadata header is optional. However sometimes we want a way to enable specific
functions or MCP servers when prompting different models. In this situation, you need only specify the metadata header
to just enable these settings as you like.
**Example: Role that enables all filesystem tools**
`roles/filesystem-functions.md`
```markdown
---
enabled_tools: fs_ls,fs_cat,fs_mkdir,fs_patch,fs_write
---
```
**Example: Role that enables the GitHub MCP server with the ollama:deepseek-r1 model**
`roles/github.md`
```markdown
---
model: ollama:deepseek-r1
enabled_mcp_servers: github
---
```
For more examples of this special use case of roles, you can look at the role configuration files for the following
built-in roles:
* [explain-shell](../assets/roles/explain-shell.md) - Explains cryptic shell commands in natural language
* [functions](../assets/roles/functions.md) - Enables all available functions (i.e. all globally `visible_functions`)
* [mcp-servers](../assets/roles/mcp-servers.md) - Enables all available MCP servers
## Special Variables
Loki has a set of built-in special variables that it will inject into your role's instructions if it finds them in the
`{{variable_name}}` syntax. The available special variables are listed below:
| Name | Description | Example |
|-----------------|-----------------------------------------------------------|----------------------------|
| `__os__` | Operating system name | `linux` |
| `__os_family__` | Operating system family | `unix` |
| `__arch__` | System architecture | `x86_64` |
| `__shell__` | The current user's default shell | `bash` |
| `__locale__` | The current user's preferred language and region settings | `en-US` |
| `__now__` | Current timestamp in ISO 8601 format | `2025-11-07T10:15:44.268Z` |
| `__cwd__` | The current working directory | `/tmp` |
## Prompt Types
In Loki, you can also create roles with pre-configured prompts so you can template prompts for your use cases. This is
the purpose of the `prompt` field in the role's metadata header.
There's three types of prompts you can create:
### Embedded Prompts
Embedded prompts let you create templated prompts for any input given to it. They are ideal for concise, input-driven
replies from the model. The input that users pass to Loki are injected into your prompt via a `__INPUT__` placeholder in
your prompt.
**Example: Role to convert the given input to TOML**
`roles/convert-to-toml.md`
```markdown
---
prompt: convert __INPUT__ to TOML
---
Convert the given input to TOML format. Exclude any markdown formatting or code blocks and only output code.
```
Usage:
```shell
$ loki -r json-to-toml '{"test":"hi me"}'
test = "hi me"
```
Without the instructions (i.e. the prompt after the metadata header), this role would simply generate the following
message for the model:
```json
[
{"role": "user", "content": "convert {\"test\":\"hi me\"} to TOML"}
]
```
### System Prompts
System prompts let you set the general context of the LLMs behavior. This is no different than other system prompts you
define in ChatGPT, Claude, Open WebUI, etc.
They are essentially Embedded Prompts without an `__INPUT__` placeholder.
**Example: Role to convert all input words to emoji**
`roles/emoji.md`
```markdown
---
prompt: convert my words to emojis
---
Convert all given input words into emojis
```
Usage:
```shell
$ loki -r emoji music joy
🎵 😊
```
Without the instructions (i.e. the prompt after the metadata header), this role would simply generate the following
messages for the model:
```json
[
{"role": "system", "content": "convert my words to emojis"},
{"role": "user", "content": "music joy"}
]
```
### Few-Shot Prompt
[Few-Shot prompting](https://www.promptingguide.ai/techniques/fewshot) is a technique to enable in-context learning for LLMs by providing examples in the prompt to steer
the model to better performance. In Loki, this is done as an extension of System Prompts.
**Example: Role to output code only**
`roles/code-generator.md`
~~~markdown
---
prompt: |-
Output code only without comments or explanations.
### INPUT:
async sleep in js
### OUTPUT:
```javascript
async function timeout(ms) {
return new Promise(resolve => setTimeout(resolve, ms));
}
```
---
Output code only in response to the user's request
~~~
Usage:
~~~shell
$ loki -r code-generator python add two numbers
```python
# Function to add two numbers
def add_numbers(num1, num2):
return num1 + num2
# Example usage
number1 = 5
number2 = 7
result = add_numbers(number1, number2)
print(f"The sum of {number1} and {number2} is {result}.")
```
~~~
Without the instructions (i.e. the prompt after the metadata header), this role would simply generate the following
messages for the model:
```json
[
{"role": "system", "content": "Output code only without comments or explanations."},
{"role": "user", "content": "async sleep in js"},
{"role": "assistant", "content": "```javascript\nasync function timeout(ms) {\n return new Promise(resolve => setTimeout(resolve, ms));\n}\n```"},
{"role": "user", "content": "python add two numbers"}
]
```
## Built-In Roles
Loki comes packaged with some useful built-in roles. These are also good examples if you're looking for more examples on
how to make your own roles, so be sure to check out the [built-in role definitions](../assets/roles) if you're looking
for more examples.
* `code`: Generates code (used by `loki -c`)
* `create-prompt`: Creates a prompt based on the user's input
* `create-title`: Creates 3-6 word titles based on the user's input
* `explain-shell`: Explains shell commands
* `functions`: Enable all globally-visible functions
* `github`: Interact with GitHub using natural language
* `mcp-servers`: Enables all MCP servers
* `repo-analyzer`: Ask questions about the code repository in the current working directory
* `shell`: Convert natural language into shell commands (used by `loki -e`)
* `slack`: Interact with Slack using natural language
## Temporary Roles
Loki also enables you to create temporary roles that will be discarded once you're finished with them. This is done via
the `.prompt/--prompt` command:
![prompt role](./images/roles/prompt-role.gif)
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# Sessions
By default, Loki does not send back all previous messages in a conversation to the model. This means that each time you
query a model, it's essentially a one-off. However, Loki does support chat-like conversations with LLMs via its
`sessions` mechanism.
Sessions in Loki enable the familiar conversational interactions with LLMs. This means you can reference previous
answers and ask follow-up questions and the model will know what you're referring to.
Sessions can be temporary, or can be saved so you can continue conversations at a later time.
Saved sessions are stored in the `sessions` subdirectory of the Loki configuration directory. The location of the
`sessions` directory varies by system, so you can use the following command to find the `sessions` directory if you need
it:
```shell
loki --info | grep 'sessions_dir' | awk '{print $2}'
```
## Usage
When you use a session in Loki, you can either persist it or discard it once you're done. Sessions you discard are then
just considered 'temporary' sessions.
![Persistent Session Example](./images/sessions/sessions-example.gif)
Sessions you persist and then load again later will inherit the same configuration as was used during the last usage of
that session. That is to say, if you had certain tools or MCP servers enabled when you were last in that session, they
will be available again when you continue that session.
## Configuration
Session behavior can be configured from the global Loki configuration file. The location of this file varies between
systems so you can use the following command to locate it on your system:
```shell
loki --info | grep 'config_file' | awk '{print $2}'
```
The following settings are available to customize the default behavior of sessions globally:
| Setting | Description |
|--------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| `save_session` | Controls the persistence of the session. <br><ul><li>If `true`, then any time you're in a session, changes will auto-save unless explicitly defined otherwise.</li> <li>If `false`, then any time you're in a session, changes will not auto-save unless explicitly specified otherwise.</li><li>If `null`, Loki will always prompt the user for what to do.</li></ul> |
| `compression_threshold` | Defines the token count threshold at which Loki will compress the session to save on the context length |
| `summarization_prompt` | This is the prompt that is used to compress the session up to a given point when compression is triggered |
| `summary_context_prompt` | This is the prompt that's used to add the summarized conversation generated by the `summarization_prompt` as context to the model |
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# Loki Shell Integrations
Loki supports the following integrations with a handful of shell environments to enhance user experience and streamline workflows.
## Tab Completions
### Dynamic
Dynamic tab completions are supported by Loki to assist users in quickly completing commands, options, and arguments.
You can enable it by using the corresponding command for your shell. To enable dynamic tab completions for every
shell session (i.e. persistently), add the corresponding command to your shell's configuration file as indicated:
```shell
# Bash
# (add to: `~/.bashrc`)
source <(COMPLETE=bash loki)
# Zsh
# (add to: `~/.zshrc`)
source <(COMPLETE=zsh loki)
# Fish
# (add to: `~/.config/fish/config.fish`)
source <(COMPLETE=fish loki | psub)
# Elvish
# (add to: `~/.elvish/rc.elv`)
eval (E:COMPLETE=elvish loki | slurp)
# PowerShell
# (add to: `$PROFILE`)
$env:COMPLETE = "powershell"
loki | Out-String | Invoke-Expression
```
At the time of writing, `nushell` is not yet fully supported for dynamic tab completions due to limitations
in the [`clap`](https://crates.io/crates/clap) crate. However, `nushell` support is being actively developed, and will
be added in a future release.
Progress on this feature can be tracked in the following issue: [Clap Issue #5840](https://github.com/clap-rs/clap/issues/5840).
### Static
Static tab completions (i.e. pre-generated completion scripts that are not context aware) can also be generated using the
`--completions` flag. You can enable static tab completions by using the corresponding commands for your shell. These commands
will enable them for every shell session (i.e. persistently):
```shell
# Bash
echo 'source <(loki --completions bash)' >> ~/.bashrc
# Zsh
echo 'source <(loki --completions zsh)' >> ~/.zshrc
# Fish
echo 'loki --completions fish | source' >> ~/.config/fish/config.fish
# Elvish
echo 'eval (loki --completions elvish | slurp)' >> ~/.elvish/rc.elv
# Nushell
[[ -d ~/.config/nushell/completions ]] || mkdir -p ~/.config/nushell/completions
loki --completions nushell | save -f ~/.config/nushell/completions/loki.nu
echo 'use ~/.config/nushell/completions/cli.nu *' >> ~/.config/nushell/config.nu
# PowerShell
Add-content $PROFILE "loki --completions powershell | Out-String | Invoke-Expression"
```
## Shell Assistant
Loki has an `-e,--execute` flag that allows users to run natural language commands directly from the CLI. It accepts
natural language input and translates it into executable shell commands.
![Shell Assistant Demo](./images/shell_integrations/assistant.gif)
## Intelligent Command Completions
Loki also provides shell scripts that bind `Alt-e` to `loki -e "<current command line>"`, allowing users to generate
commands from natural text directly without invoking the CLI.
For example:
```shell
$ find all typescript files with more than 100 lines<Alt-e>
# Gets replaced with
$ find . -name '*.ts' -type f -exec awk 'NR>100{exit 1}' {} \; -print
```
To use the CLI helper, add the content of the appropriate integration script for your shell to your shell configuration file:
* [Bash Integration](../scripts/shell-integration/integration.bash) (add to: `~/.bashrc`)
* [Zsh Integration](../scripts/shell-integration/integration.zsh) (add to: `~/.zshrc`)
* [Elvish Integration](../scripts/shell-integration/integration.elv) (add to: `~/.elvish/rc.elv`)
* [Fish Integration](../scripts/shell-integration/integration.fish) (add to: `~/.config/fish/config.fish`)
* [Nushell Integration](../scripts/shell-integration/integration.nu) (add to: `~/.config/nushell/config.nu`)
* [PowerShell Integration](../scripts/shell-integration/integration.ps1) (add to: `$PROFILE`)
## Explain Commands
In addition to the Shell Assistant, Loki has a built-in role that explains shell commands to you to decipher their
language. So if Loki generates a command that you're unsure of what it does, simply pass it to the `explain-shell` role:
![Explain Shell Role](./images/shell_integrations/explain-shell.png)
## Code Generation
Users can also directly generate code snippets from natural language prompts using the `-c,--code` flag.
![Code Generation Demo](./images/shell_integrations/code-generation.gif)
**Pro Tip:** Pipe the output of the code generation directly into `tee` to ensure the generated code is properly extracted
from any generated Markdown (i.e. remove any triple backticks).
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# Theming Loki
Loki supports customizing the theme via a `.tmTheme` file.
## Setup
To install a custom theme, download the `.tmTheme` file to the Loki configuration directory and name it `dark.tmTheme`
or `light.tmTheme`. The location of the Loki configuration directory varies between systems, so you can use the
following command to locate it on your system:
```shell
loki --info | grep 'config_dir' | awk '{print $2}'
```
## Themes
### 1337-Scheme
https://raw.githubusercontent.com/MarkMichos/1337-Scheme/ca6a329cfda8307449d405b70f8fab34b8fd23b5/1337.tmTheme
![1337-scheme](./images/themes/1337-scheme.png)
### Coldark
https://raw.githubusercontent.com/ArmandPhilippot/coldark-bat/e44750b2a9629dd12d8ed3ad9fd50c77232170b9/Coldark-Dark.tmTheme
![coldark](./images/themes/coldark.png)
### Dracula
https://raw.githubusercontent.com/dracula/sublime/c2de0acf5af67042393cf70de68013153c043656/Dracula.tmTheme
![dracula](./images/themes/dracula.png)
### GitHub
https://raw.githubusercontent.com/AlexanderEkdahl/github-sublime-theme/508740b2430c3c3a9e785fc93ee1d7c6f233af53/GitHub.tmTheme
![github](./images/themes/github.png)
### gruvbox
#### Dark
https://raw.githubusercontent.com/subnut/gruvbox-tmTheme/64c47250e54298b91e2cf8d401320009aba9f991/gruvbox-dark.tmTheme
![gruvbox-dark](./images/themes/gruvbox-dark.png)
#### Light
https://raw.githubusercontent.com/subnut/gruvbox-tmTheme/64c47250e54298b91e2cf8d401320009aba9f991/gruvbox-light.tmTheme
![gruvbox-light](./images/themes/gruvbox-light.png)
### OneHalf
#### Dark
https://raw.githubusercontent.com/sonph/onehalf/141c775ace6b71992305f144a8ab68e9a8ca4a25/sublimetext/OneHalfDark.tmTheme
![onehalf-dark](./images/themes/onehalf-dark.png)
#### Light
https://raw.githubusercontent.com/sonph/onehalf/141c775ace6b71992305f144a8ab68e9a8ca4a25/sublimetext/OneHalfLight.tmTheme
![onehalf-light](./images/themes/onehalf-light.png)
### Solarized
#### Dark
https://raw.githubusercontent.com/braver/Solarized/87e01090cggjf5fb821a234265b3138426ae84900e7/Solarized%20(dark).tmTheme
![solarized-dark](./images/themes/solarized-dark.png)
#### Light
https://raw.githubusercontent.com/braver/Solarized/87e01090cf5fb821a234265b3138426ae84900e7/Solarized%20(light).tmTheme
![solarized-light](./images/themes/solarized-light.png)
### Sublime Snazzy
https://raw.githubusercontent.com/greggb/sublime-snazzy/70343201f1d7539adbba3c79e2fe81c2559a0431/Sublime%20Snazzy.tmTheme
![sublime-snazzy](./images/themes/sublime-snazzy.png)
### TwoDark
https://raw.githubusercontent.com/erremauro/TwoDark/8e0f6fa5b59d196658a22288f519fd8320de4c87/TwoDark.tmTheme
![twodark](./images/themes/twodark.png)
### Visual Studio Dark+
https://raw.githubusercontent.com/vidann1/visual-studio-dark-plus/01ee1e8e0dc578f3b4e8c0dbb6aa0279b4a26a40/Visual%20Studio%20Dark%2B.tmTheme
![visual-studio-dark-plus](./images/themes/visual-studio-dark-plus.png)
### Zenburn
https://raw.githubusercontent.com/colinta/zenburn/86d4ee7a1f884851a1d21d66249687f527fced32/zenburn.tmTheme
![zenburn](./images/themes/zenburn.png)
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# The Loki Vault
The Loki vault lets users store sensitive secrets and credentials securely so that there's no plaintext secrets
anywhere in your configurations.
It's based on the [G-Man library](https://github.com/Dark-Alex-17/gman) (which also comes in a binary format) which
functions as a universal secret management tool.
![Vault Demo](./images/vault/vault-demo.gif)
## Quick Links
<!--toc:start-->
- [Usage](#usage)
- [CLI Usage](#cli-usage)
- [REPL Usage](#repl-usage)
- [Motivation](#motivation)
- [How it works](#how-it-works)
- [Supported Files](#supported-files)
- [Environment Variable Secret Injection in Agents](#environment-variable-secret-injection-in-agents)
<!--toc:end-->
---
## Usage
The Loki vault can be used in one of two ways: via the CLI or via the REPL for interactive usage.
### CLI Usage
The vault is utilized from the CLI with the following flags:
```bash
--add-secret <SECRET_NAME> Add a secret to the Loki vault
--get-secret <SECRET_NAME> Decrypt a secret from the Loki vault and print the plaintext
--update-secret <SECRET_NAME> Update an existing secret in the Loki vault
--delete-secret <SECRET_NAME> Delete a secret from the Loki vault
--list-secrets List all secrets stored in the Loki vault
```
(The above is also documented in `loki --help`)
Loki will guide you through manipulating your secrets to make usage easier.
### REPL Usage
The vault can be access from within the Loki REPL using the `.vault` commands:
![Loki Vault REPL](./images/vault/vault-repl.png)
![Loki Vault REPL Commands](./images/vault/vault-repl-commands.png)
The manipulation of your vault is guided in the same way as the CLI usage, ensuring ease of use.
## Motivation
Loki is intended to be highly configurable and adaptable to many different use cases. This means that users of Loki
should be able to share configurations for agents, tools, roles, etc. with other users or even entire teams.
My objective is to encourage this, and to make it so that users can easily version their configurations using version
control. Good VCS hygiene dictates that one *never* commits secrets or sensitive information to a repository.
Since a number of files and configurations in Loki may contain sensitive information, the vault exists to solve this problem.
Users can either share the vault password with a team, making it so a single configuration can be pulled from VCS and used
by said team. Alternatively, each user can maintain their own vault password and expect other users to replace secret values
with their user-specific secrets.
## How it works
When you first start Loki, if you don't already have a vault password file, it will prompt you to create one. This file
houses the password that is used to encrypt and decrypt secrets within Loki. This file exists so that you are not prompted
for a password every time Loki attempts to decrypt a secret.
When you encrypt a secret, it uses the local provider for `gman` to securely store those secrets in the Loki vault file.
This file is typically located at your Loki configuration directory under `vault.yml`. If you open this file, you'll see a
bunch of gibberish. This is because all secrets are encrypted using the password you provided, meaning only you can decrypt them.
Secrets are specified in Loki configurations using the same variable templating as the [Jinja templating engine](https://jinja.palletsprojects.com/en/stable/):
```
{{some_variable}}
```
So whenever you want Loki to use a secret from the vault, you simply specify the secret name in this format in the applicable
file.
**Example:**
Suppose my vault has a secret called `GITHUB_TOKEN` in it, and I want to use that in the MCP configuration. Then, I simply replace
the expected value in my `mcp.json` with the templated secret:
```json
{
"mcpServers": {
"atlassian": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://mcp.atlassian.com/v1/sse"]
},
"github": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"GITHUB_PERSONAL_ACCESS_TOKEN",
"ghcr.io/github/github-mcp-server"
],
"env": {
"GITHUB_PERSONAL_ACCESS_TOKEN": "{{GITHUB_TOKEN}}"
}
}
}
}
```
At runtime, Loki will detect the templated secret and replace it with the decrypted value from the vault before executing.
## Supported Files
At the time of writing, the following files support Loki secret injection:
| File Type | Description | Limitations |
|-------------------------|-----------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------|
| `config.yaml` | The main Loki configuration file | Cannot use secret injection on the `vault_password_file` field |
| `functions/mcp.json` | The MCP server configuration file | |
| `<agent>/tools.<py/sh>` | Tool files for agents | Specific configuration and only supported for Agents, not all global tools ([see below](#environment-variable-secret-injection-in-agents) |
Note that all paths are relative to the Loki configuration directory. The directory varies by system, so you can find yours by
running
```shell
loki --info | grep config_dir | awk '{print $2}'
```
## Environment Variable Secret Injection in Agents
Secrets from the Loki vault can be injected into agent `tools.sh/tools.py` as environment variables. This is done as
follows:
1. Ensure a secret named `MY_USERNAME` is in your Loki vault.
2. Set the name of the secret as the default value for a variable
`<agent>/config.yaml`
```yaml
name: Username
description: An AI agent that demonstrates agent capabilities
instructions: |
You are a AI agent designed to demonstrate agent capabilities.
variables:
- name: username
description: Your user name
# Configure the secret you want to inject using the same templating mentioned above; i.e. wrap the
# case-sensitive name in '{{}}'
default: '{{MY_USERNAME}}'
```
3. Reference the variable in your `<agent>/tools.<py/sh>` file using the familiar variable injection name; that is,
since the name of the variable is `username`, the environment variable that will be provided to the tool call will
be named `LLM_AGENT_VAR_USERNAME`
`tools.sh`
```bash
#!/usr/bin/env bash
# @env LLM_OUTPUT=/dev/stdout The output path
# @cmd Get my username
get_my_username() {
echo "$LLM_AGENT_VAR_USERNAME" >> "$LLM_OUTPUT"
}
```
For more information about variable usage within agents, refer to the [Variables section](./AGENTS.md#user-defined-variables) of the [Agents README](./AGENTS.md)
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# Model Clients
Loki supports a large number of model providers (referred to as `clients` since Loki is a client of these providers). In
order to use them, you must configure each one in the `clients` array in the global Loki configuration file.
The location of the global Loki configuration file varies between systems, so you can use the following command to
locate your configuration file:
```shell
loki --info | grep 'config_file' | awk '{print $2}'
```
## Quick Links
<!--toc:start-->
- [Supported Clients](#supported-clients)
- [Client Configuration](#client-configuration)
- [Extra Settings](#extra-settings)
<!--toc:end-->
---
## Supported Clients
Loki supports the following model client types:
* Azure AI Foundry
* AWS Bedrock
* Anthropic Claude
* Cohere
* Google Gemini
* OpenAI
* OpenAI-Compatible
* GCP Vertex AI
In addition to the settings detailed below, each client may have additional settings specific to the provider. Check the
[example global configuration file](../../config.example.yaml) to verify that your client has all the necessary fields
defined.
## Client Configuration
Each client in Loki has the same configuration settings available to them, with only special authentication fields added
for specific clients as necessary. They are each placed under the `clients` array in your global configuration file:
```yaml
clients:
- name: client1
# ... client configuration ...
- name: client2
# ... client configuration ...
```
### Metadata
The client metadata uniquely identifies the client in Loki so you can reference it across your configurations. The
available settings are listed below:
| Setting | Description |
|----------|-----------------------------------------------------------------------------------------------|
| `name` | The name of the client (e.g. `openai`, `gemini`, etc.) |
| `models` | See the [model settings](#model-settings) documentation below |
| `patch` | See the [client patch configuration](./PATCHES.md#client-configuration-patches) documentation |
| `extra` | See the [extra settings](#extra-settings) documentation below |
Be sure to also check provider-specific configurations for any extra fields that are added for authentication purposes.
### Model Settings
The `models` array lists the available models from the model client. Each one has the following settings:
| Setting | Required | Model Type | Description |
|-----------------------------|----------|-------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| `name` | * | `all` | The name of the model |
| `real_name` | | `all` | You can define model aliases via the `name` field. However, Loki still needs to know the real name <br>of the model so it can query it. For example: If you have `name: gpt-alias`, then you must <br>also define `real_name: gpt-oss:latest` |
| `type` | * | `all` | The type of model. Loki supports only 3 types of models: <ul><li>`chat`</li><li>`embedding`</li><li>`reranker`</li></ul> |
| `input_price` | | `all` | The cost in USD per 1M tokens for each input sequence; Loki will keep track of usage costs if this is defined |
| `output_price` | | `all` | The cost in USD per 1M tokens of the model output; Loki will keep track of usage costs if this is defined |
| `patch` | | `all` | See the [model-specific patch configuration](./PATCHES.md#model-specific-patches) documentation |
| `max_input_tokens` | | `all` | The maximum number of input tokens for the model |
| `max_output_tokens` | | `chat` | The maximum number of output tokens for the model |
| `require_max_tokens` | | `chat` | Whether to enforce the `max_output_tokens` constraint. |
| `supports_vision` | | `chat` | Indicates if the model supports multimodal queries that would require vision (i.e. image recognition) |
| `supports_function_calling` | | `chat` | Indicates if the model supports function calling |
| `no_stream` | | `chat` | Enable or disable streaming API responses |
| `no_system_message` | | `chat` | Controls whether the model supports system messages |
| `system_prompt_prefix` | | `chat` | An additional prefix prompt to add to all system prompts to ensure consistent behavior across all interactions |
| `max_tokens_per_chunk` | | `embedding` | The maximum chunk size supported by the embedding model |
| `default_chunk_size` | | `embedding` | The default chunk size to use with the given model |
| `max_batch_size` | | `embedding` | The maximum batch size that the given embedding model supports |
## Extra Settings
Loki also lets you customize some extra settings for interacting with APIs:
| Setting | Description |
|-------------------|-------------------------------------------------------|
| `proxy` | Set a proxy to use |
| `connect_timeout` | Set the timeout in seconds for connections to the API |
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# Request Patching in Loki
Loki provides two mechanisms for modifying API requests sent to LLM providers: **Model-Specific Patches** and
**Client Configuration Patches**. These allow you to customize request parameters, headers, and URLs to work around
provider quirks or add custom behavior.
## Quick Links
- [Model-Specific Patches](#model-specific-patches)
- [Client Configuration Patches](#client-configuration-patches)
- [Comparison](#comparison)
- [Common Use Cases](#common-use-cases)
- [Environment Variable Patches](#environment-variable-patches)
- [Tips](#tips)
- [Debugging Patches](#debugging-patches)
---
## Model-Specific Patches
### Overview
Model-specific patches are applied **unconditionally** to a single model. They are useful for handling model-specific
quirks or requirements.
### When to Use
- A specific model requires certain parameters to be set or removed
- A model needs different default values than other models from the same provider
- You need to add special configuration for one model only
### Structure
```yaml
models:
- name: model-name
type: chat
# ... other model properties ...
patch:
url: "https://custom-endpoint.com" # Optional: override the API endpoint
body: # Optional: modify request body
<parameter>: <value> # Add or modify parameters
<parameter>: null # Remove parameters (set to null)
headers: # Optional: modify request headers
<header-name>: <value> # Add or modify headers
<header-name>: null # Remove headers (set to null)
```
### Examples
#### Example 1: Removing Parameters
OpenAI's o1 models don't support `temperature`, `top_p`, or `max_tokens` parameters. The `patch` removes them:
```yaml
- name: o4-mini
type: chat
max_input_tokens: 200000
max_output_tokens: 100000
supports_function_calling: true
patch:
body:
max_tokens: null # Remove max_tokens from request
temperature: null # Remove temperature from request
top_p: null # Remove top_p from request
```
#### Example 2: Setting Required Parameters
Some models require specific parameters to be set:
```yaml
- name: o4-mini-high
type: chat
patch:
body:
reasoning_effort: high # Always set reasoning_effort to "high"
max_tokens: null
temperature: null
```
#### Example 3: Custom Endpoint
If a model needs a different API endpoint:
```yaml
- name: custom-model
type: chat
patch:
url: "https://special-endpoint.example.com/v1/chat"
```
#### Example 4: Adding Headers
Add authentication or custom headers:
```yaml
- name: special-model
type: chat
patch:
headers:
X-Custom-Header: "special-value"
X-API-Version: "2024-01"
```
### How It Works
1. When you use a model, Loki loads its configuration
2. If the model has a `patch` field, it's **always applied** to every request
3. The patch modifies the request URL, body, or headers before sending to the API
4. Parameters set to `null` are **removed** from the request
---
## Client Configuration Patches
### Overview
Client configuration patches allow you to apply customizations to **multiple models** based on
**regex pattern matching**. They're defined in your `config.yaml` file and can target specific API types (`chat`,
`embeddings`, or `rerank`).
### When to Use
- You want to apply the same settings to multiple models from a provider
- You need different configurations for different groups of models
- You want to override the default client model settings
- You need environment-specific customizations
### Structure
```yaml
clients:
- type: <client> # e.g., gemini, openai, claude
# ... client configuration ...
patch:
chat_completions: # For chat models
'<regex-pattern>': # Regex to match model names
url: "..." # Optional: override endpoint
body: # Optional: modify request body
<parameter>: <value>
headers: # Optional: modify headers
<header>: <value>
embeddings: # For embedding models
'<regex-pattern>':
# ... same structure ...
rerank: # For reranker models
'<regex-pattern>':
# ... same structure ...
```
### Pattern Matching
- Patterns are **regular expressions** that match against the model name
- Use `.*` to match all models
- Use specific patterns like `gpt-4.*` to match model families
- Use `model1|model2` to match multiple specific models
### Examples
#### Example 1: Disable Safety Filters for Gemini Models
Apply to all Gemini chat models:
```yaml
clients:
- type: gemini
api_key: "{{GEMINI_API_KEY}}"
patch:
chat_completions:
'.*': # Matches all Gemini models
body:
safetySettings:
- category: HARM_CATEGORY_HARASSMENT
threshold: BLOCK_NONE
- category: HARM_CATEGORY_HATE_SPEECH
threshold: BLOCK_NONE
- category: HARM_CATEGORY_SEXUALLY_EXPLICIT
threshold: BLOCK_NONE
- category: HARM_CATEGORY_DANGEROUS_CONTENT
threshold: BLOCK_NONE
```
#### Example 2: Apply Settings to Specific Model Family
Only apply to GPT-4 models (not GPT-3.5):
```yaml
clients:
- type: openai
api_key: "{{OPENAI_API_KEY}}"
patch:
chat_completions:
'gpt-4.*': # Matches gpt-4, gpt-4-turbo, gpt-4o, etc.
body:
frequency_penalty: 0.2
presence_penalty: 0.1
```
#### Example 3: Different Settings for Different Models
Apply different patches based on model name:
```yaml
clients:
- type: openai
api_key: "{{OPENAI_API_KEY}}"
patch:
chat_completions:
'gpt-4o': # Specific model
body:
temperature: 0.7
'gpt-3.5.*': # Model family
body:
temperature: 0.9
max_tokens: 2000
```
#### Example 4: Modify Embedding Requests
Apply to embedding models:
```yaml
clients:
- type: openai
api_key: "{{OPENAI_API_KEY}}"
patch:
embeddings:
'text-embedding-.*': # All text-embedding models
body:
dimensions: 1536
encoding_format: "float"
```
#### Example 5: Custom Headers for Specific Models
Add headers only for certain models:
```yaml
clients:
- type: openai-compatible
api_base: "https://api.example.com/v1"
patch:
chat_completions:
'custom-model-.*':
headers:
X-Custom-Auth: "bearer-token"
X-Model-Version: "latest"
```
#### Example 6: Override Endpoint for Specific Models
Use different endpoints for different model groups:
```yaml
clients:
- type: openai-compatible
api_base: "https://default-endpoint.com/v1"
patch:
chat_completions:
'premium-.*': # Premium models use different endpoint
url: "https://premium-endpoint.com/v1/chat/completions"
```
### How It Works
1. When making a request, Loki checks if the client has a `patch` configuration
2. It looks at the appropriate API type (`chat_completions`, `embeddings`, or `rerank`)
3. For each pattern in that section, it checks if the regex matches the model name
4. If a match is found, that patch is applied to the request
5. Only the **first matching pattern** is applied (patterns are processed in order)
---
## Comparison
| Feature | Model-Specific Patch | Client Configuration Patch |
|-----------------------|-----------------------|-------------------------------------|
| **Scope** | Single model only | Multiple models via regex |
| **Matching** | Exact model name | Regular expression pattern |
| **Application** | Always applied | Only if pattern matches |
| **API Type** | All APIs | Separate for chat/embeddings/rerank |
| **Override** | Cannot be overridden | Can override model patch |
| **Use Case** | Model-specific quirks | User preferences & customization |
| **Application Order** | Applied first | Applied second (can override) |
### Patch Application Order
When both patches are present, they're applied in this order:
1. **Model-Specific Patch**
2. **Client Configuration Patch**
This means client configuration patches can override model-specific patches if they modify the same parameters.
## Common Use Cases
### Removing Unsupported Parameters
Some models don't support standard parameters like `temperature` or `max_tokens`:
**Model Patch**:
```yaml
patch:
body:
temperature: null
max_tokens: null
```
### Adding Provider-Specific Parameters
Providers often have unique parameters:
**Client Patch**:
```yaml
patch:
chat_completions:
'.*':
body:
safetySettings: [...] # Gemini
thinking_budget: 10000 # DeepSeek
response_format: # OpenAI
type: json_object
```
### Changing Endpoints
Use custom or regional endpoints:
**Client Patch**:
```yaml
patch:
chat_completions:
'.*':
url: "https://eu-endpoint.example.com/v1/chat"
```
### Setting Default Values
Provide defaults for specific models or model families:
**Client Patch**:
```yaml
patch:
chat_completions:
'claude-3-.*':
body:
max_tokens: 4096
temperature: 0.7
```
### Custom Authentication
Add special authentication headers:
**Client Patch**:
```yaml
patch:
chat_completions:
'.*':
headers:
Authorization: "Bearer {{custom_token}}"
X-Organization-ID: "org-123"
```
## Environment Variable Patches
You can also apply patches via environment variables for temporary overrides:
```bash
export LLM_PATCH_OPENAI_CHAT_COMPLETIONS='{"gpt-4.*":{"body":{"temperature":0.5}}}'
```
This takes precedence over client configuration patches but not model-specific patches.
## Tips
1. **Use model patches** for permanent, model-specific requirements
2. **Use client patches** for personal preferences or environment-specific settings
3. **Test regex patterns** carefully
4. **Set to `null`** to remove parameters, don't just omit them
5. **Check each model provider's docs** for available parameters and their formats
6. **Be specific** with patterns to avoid unintended matches
7. **Remember order matters** - first matching pattern wins for client patches
8. **Patches merge** - both types can be applied, with client patches overriding model patches
## Debugging Patches
To see what request is actually being sent, enable debug logging:
```bash
export RUST_LOG=loki=debug
loki "your prompt here"
```
This will show the final request body after all patches are applied.
@@ -0,0 +1,275 @@
# Bash Prompt Helpers
When creating bash based tools, it's often helpful to prompt the user for input or confirmation.
Loki comes pre-packaged with a handful of prompt helpers for your bash-based tools. These helpers
can be used to prompt the user for various types of input, such as yes/no confirmations,
text input, and selections from a list.
The utility script is located at `functions/utils/prompt-utils.sh` within your Loki `functions` directory.
The Loki `functions` directory varies between machines, so you can find its location on your system by running the following command in your terminal:
```shell
loki --info | grep functions_dir | awk '{print $2}'
```
## Quick Links
<!--toc:start-->
- [Import The Prompt Utils Into Your Tools Script](#import-the-prompt-utils-into-your-tools-script)
- [Included Utility Functions](#included-utility-functions)
- [input](#input)
- [confirm](#confirm)
- [list](#list)
- [checkbox](#checkbox)
- [password](#password)
- [editor](#editor)
- [with_validate](#with_validate)
- [validate_present](#validate_present)
- [detect_os](#detect_os)
- [get_opener](#get_opener)
- [open_link](#open_link)
- [guard_operation](#guard_operation)
- [guard_path](#guard_path)
- [patch_file](#patch_file)
- [error](#error)
- [warn](#warn)
- [info](#info)
- [debug](#debug)
- [trace](#trace)
- [Colored Output](#colored-output)
<!--toc:end-->
---
## Import The Prompt Utils Into Your Tools Script
In order to use the bash prompt helpers in your bash scripts, you need to source the provided `prompt-utils.sh` script.
This script is pre-packaged with Loki and is located [here](../../assets/functions/utils/prompt-utils.sh).
When sourcing the file in your bash script, you use the `LLM_PROMPT_UTILS_FILE` environment variable that automatically
populates the `functions/utils/prompt-utils.sh` path for you.
Thus, to properly source and enable all the bash prompt helpers in your Bash tools, add the following prelude to your
scripts:
```bash
source "$LLM_PROMPT_UTILS_FILE"
```
## Included Utility Functions
Below are the built-in bash prompt helpers that can be used to enhance user interaction with your tool scripts.
### input
Prompt for text input
![Prompt Utils Input](../images/tools/prompt-utils-input.png)
**Example With Validation:**
```bash
text=$(with_validation 'input "Please enter something:"' validate_present)
```
**Example Without Validation:**
```bash
text=$(input "Please enter something:")
```
### confirm
Show a confirm dialog with options for yes/no
![Prompt Utils Confirm](../images/tools/prompt-utils-confirm.png)
**Example:**
```bash
confirmed=$(confirm "Do the thing?")
if [[ $confirmed == "0" ]]; then echo "No"; else echo "Yes"; fi
```
### list
Renders a text based list of options that can be selected by the user using up, down, and enter
keys that then returns the chosen option.
![Prompt Utils List](../images/tools/prompt-utils-list.png)
**Example:**
```bash
options=("one" "two" "three" "four")
choice=$(list "Select an item" "${options[@]}")
echo "Your choice: ${options[$choice]}"
```
### checkbox
Render a text based list of options, where multiple options can be selected by the user using down, up,
and enter keys that then returns the chosen options.
![Prompt Utils Checkbox](../images/tools/prompt-utils-checkbox.png)
**Example:**
```bash
options=("one" "two" "three" "four")
checked=$(checkbox "Select one or more items" "${options[@]}")
echo "Your choices: ${checked}"
```
### password
Show a password prompt displaying stars for each character typed.
![Prompt Utils Password](../images/tools/prompt-utils-password.png)
**Example With Validation:**
```bash
validate_password() {
if [[ ${#1} -lt 10 ]]; then
echo "Password must be at least 10 characters"
exit 1
fi
}
pass=$(with_validate 'password "Enter your password"' validate_password)
```
**Example Without Validation:**
```bash
pass="$(password "Enter your password:")"
```
### editor
Open the default editor (`$EDITOR`); if none is set, default back to `vi`
**Example:**
```bash
text=$(editor "Please enter something in the editor")
echo -e "You wrote:\n${text}"
```
### with_validate
Evaluate the given prompt command with validation. This prompts the user for input until the
validation functions returns 0.
![Prompt Utils With-validate](../images/tools/prompt-utils-with-validate.png)
**Example:**
```bash
# Using the built-in 'validate_present' validator
text=$(with_validate 'input "Please enter something and confirm with enter"' validate_present)
# Using a custom validator; e.g. for password
validate_password() {
if [[ ${#1} -lt 10 ]]; then
echo "Password needs to be at least 10 characters"
exit 1
fi
}
pass=$(with_validate 'password "Enter random password"' validate_password)
```
### validate_present
Validate that the prompt returned a value.
![Prompt Utils Validate-Present](../images/tools/prompt-utils-validate-present.png)
**Example:**
```bash
text=$(with_validate 'input "Please enter something and confirm with enter"' validate_present)
```
### detect_os
Detect the current OS.
Returns one of the following:
* `solaris`
* `macos`
* `linux`
* `bsd`
* `windows`
* `unknown`
**Example:**
```bash
detect_os
```
### get_opener
Determines the Os-specific file opening command (i.e. the command to open anything)
**Example:**
```bash
# Returns 'xdg-open'
get_opener
```
### open_link
Opens the given link in the default browser
**Example:**
```bash
open_link https://www.google.com
```
### guard_operation
Prompt for permission to run an operation
**Example:**
```bash
guard_operation "Execute SQL?"
_run_sql
```
### guard_path
Prompt for permission to perform path operations
**Example:***
```bash
guard_path "$target_path" "Remove '$target_path'?"
rm -rf "$target_path"
```
### patch_file
Patch a file and show a diff using the default diff viewer. Uses git diff syntax.
**Example:**
```bash
new_contents="$(patch_file "$path" file.patch)"
```
### error
Log an error
![Prompt Utils Error](../images/tools/prompt-utils-error.png)
### warn
Log a warning
![Prompt Utils Warning](../images/tools/prompt-utils-warning.png)
### info
Log info
![Prompt Utils Info](../images/tools/prompt-utils-info.png)
### debug
Log a debug message
![Prompt Utils Debug](../images/tools/prompt-utils-debug.png)
### trace
Log a trace message
![Prompt Utils Trace](../images/tools/prompt-utils-trace.png)
### Colored Output
The following commands allow users to output text in specific colors.
* `red`
* `green`
* `gold`
* `blue`
* `magenta`
* `cyan`
* `white`
**Example:**
```bash
red "This will be red"
yellow "This will be yellow"
```

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