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loki/config.example.yaml

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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 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
# 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}'
# ---- 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
# URL to sync model changes from
sync_models_url: https://raw.githubusercontent.com/Dark-Alex-17/loki/refs/heads/main/models.yaml
# ---- 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/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
compress_threshold: 4000 # Compress the session when the token count reaches or exceeds this threshold
summarize_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_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 ----
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
# 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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