19 Commits

Author SHA1 Message Date
9bab6a0c2d Sisyphus agent recreated in LangChain to figure out how it works and how to use it 2026-04-15 12:47:38 -06:00
ff3419a714 Merge branch 'tree-sitter-tools' into 'develop' 2026-04-09 14:48:22 -06:00
a5899da4fb feat: Automatic runtime customization using shebangs 2026-04-09 14:16:02 -06:00
dedcef8ac5 test: Updated client stream tests to use the thread_rng from rand 2026-04-09 13:53:52 -06:00
d658f1d2fe build: Pulled additional features for rand dependency 2026-04-09 13:45:08 -06:00
6b4a45874f fix: TypeScript function args were being passed as objects rather than direct parameters 2026-04-09 13:32:16 -06:00
7839e1dbd9 build: upgraded dependencies to latest 2026-04-09 13:28:19 -06:00
78c3932f36 docs: Updated docs to talk about the new TypeScript-based tool support 2026-04-09 13:19:15 -06:00
11334149b0 feat: Created a demo TypeScript tool and a get_current_weather function in TypeScript 2026-04-09 13:18:41 -06:00
4caa035528 feat: Updated the Python demo tool to show all possible parameter types and variations 2026-04-09 13:18:18 -06:00
f30e81af08 fix: Added in forgotten wrapper scripts for TypeScript tools 2026-04-09 13:17:53 -06:00
4c75655f58 feat: Added TypeScript tool support using the refactored common ScriptedLanguage trait 2026-04-09 13:17:28 -06:00
f865892c28 refactor: Extracted common Python parser logic into a common.rs module 2026-04-09 13:16:35 -06:00
ebeb9c9b7d refactor: python tools now use tree-sitter queries instead of AST 2026-04-09 10:20:49 -06:00
ab2b927fcb fix: don't shadow variables in binary path handling for Windows 2026-04-09 07:53:18 -06:00
7e5ff2ba1f build: Upgraded crossterm and reedline dependencies 2026-04-08 14:54:53 -06:00
ed59051f3d fix: Tool call improvements for Windows systems 2026-04-08 12:49:43 -06:00
github-actions[bot]
e98bf56a2b chore: bump Cargo.toml to 0.3.0 2026-04-02 20:17:47 +00:00
github-actions[bot]
fb510b1a4f bump: version 0.2.0 → 0.3.0 [skip ci] 2026-04-02 20:17:45 +00:00
40 changed files with 4923 additions and 1304 deletions
+71
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@@ -1,3 +1,74 @@
## v0.3.0 (2026-04-02)
### Feat
- Added `todo__clear` function to the todo system and updated REPL commands to have a .clear todo as well for significant changes in agent direction
- Added available tools to prompts for sisyphus and code-reviewer agent families
- Added available tools to coder prompt
- Improved token efficiency when delegating from sisyphus -> coder
- modified sisyphus agents to use the new ddg-search MCP server for web searches instead of built-in model searches
- Added support for specifying a custom response to multiple-choice prompts when nothing suits the user's needs
- Supported theming in the inquire prompts in the REPL
- Added the duckduckgo-search MCP server for searching the web (in addition to the built-in tools for web searches)
- Support for Gemini OAuth
- Support authenticating or refreshing OAuth for supported clients from within the REPL
- Allow first-runs to select OAuth for supported providers
- Support OAuth authentication flows for Claude
- Improved MCP server spinup and spindown when switching contexts or settings in the REPL: Modify existing config rather than stopping all servers always and re-initializing if unnecessary
- Allow the explore agent to run search queries for understanding docs or API specs
- Allow the oracle to perform web searches for deeper research
- Added web search support to the main sisyphus agent to answer user queries
- Created a CodeRabbit-style code-reviewer agent
- Added configuration option in agents to indicate the timeout for user input before proceeding (defaults to 5 minutes)
- Added support for sub-agents to escalate user interaction requests from any depth to the parent agents for user interactions
- built-in user interaction tools to remove the need for the list/confirm/etc prompts in prompt tools and to enhance user interactions in Loki
- Experimental update to sisyphus to use the new parallel agent spawning system
- Added an agent configuration property that allows auto-injecting sub-agent spawning instructions (when using the built-in sub-agent spawning system)
- Auto-dispatch support of sub-agents and support for the teammate pattern between subagents
- Full passive task queue integration for parallelization of subagents
- Implemented initial scaffolding for built-in sub-agent spawning tool call operations
- Initial models for agent parallelization
- Added interactive prompting between the LLM and the user in Sisyphus using the built-in Bash utils scripts
### Fix
- Clarified user text input interaction
- recursion bug with similarly named Bash search functions in the explore agent
- updated the error for unauthenticated oauth to include the REPL .authenticated command
- Corrected a bug in the coder agent that wasn't outputting a summary of the changes made, so the parent Sisyphus agent has no idea if the agent worked or not
- Claude code system prompt injected into claude requests to make them valid once again
- Do not inject tools when models don't support them; detect this conflict before API calls happen
- The REPL .authenticate command works from within sessions, agents, and roles with pre-configured models
- Implemented the path normalization fix for the oracle and explore agents
- Updated the atlassian MCP server endpoint to account for future deprecation
- Fixed a bug in the coder agent that was causing the agent to create absolute paths from the current directory
- the updated regex for secrets injection broke MCP server secrets interpolation because the regex greedily matched on new lines, replacing too much content. This fix just ignores commented out lines in YAML files by skipping commented out lines.
- Don't try to inject secrets into commented-out lines in the config
- Removed top_p parameter from some agents so they can work across model providers
- Improved sub-agent stdout and stderr output for users to follow
- Inject agent variables into environment variables for global tool calls when invoked from agents to modify global tool behavior
- Removed the unnecessary execute_commands tool from the oracle agent
- Added auto_confirm to the coder agent so sub-agent spawning doesn't freeze
- Fixed a bug in the new supervisor and todo built-ins that was causing errors with OpenAI models
- Added condition to sisyphus to always output a summary to clearly indicate completion
- Updated the sisyphus prompt to explicitly tell it to delegate to the coder agent when it wants to write any code at all except for trivial changes
- Added back in the auto_confirm variable into sisyphus
- Removed the now unnecessary is_stale_response that was breaking auto-continuing with parallel agents
- Bypassed enabled_tools for user interaction tools so if function calling is enabled at all, the LLM has access to the user interaction tools when in REPL mode
- When parallel agents run, only write to stdout from the parent and only display the parent's throbber
- Forgot to implement support for failing a task and keep all dependents blocked
- Clean up orphaned sub-agents when the parent agent
- Fixed the bash prompt utils so that they correctly show output when being run by a tool invocation
- Forgot to automatically add the bidirectional communication back up to parent agents from sub-agents (i.e. need to be able to check inbox and send messages)
- Agent delegation tools were not being passed into the {{__tools__}} placeholder so agents weren't delegating to subagents
### Refactor
- Made the oauth module more generic so it can support loopback OAuth (not just manual)
- Changed the default session name for Sisyphus to temp (to require users to explicitly name sessions they wish to save)
- Updated the sisyphus agent to use the built-in user interaction tools instead of custom bash-based tools
- Cleaned up some left-over implementation stubs
## v0.2.0 (2026-02-14)
### Feat
Generated
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+10 -7
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@@ -1,6 +1,6 @@
[package]
name = "loki-ai"
version = "0.2.0"
version = "0.3.0"
edition = "2024"
authors = ["Alex Clarke <alex.j.tusa@gmail.com>"]
description = "An all-in-one, batteries included LLM CLI Tool"
@@ -18,10 +18,11 @@ anyhow = "1.0.69"
bytes = "1.4.0"
clap = { version = "4.5.40", features = ["cargo", "derive", "wrap_help"] }
dirs = "6.0.0"
dunce = "1.0.5"
futures-util = "0.3.29"
inquire = "0.9.4"
is-terminal = "0.4.9"
reedline = "0.40.0"
reedline = "0.46.0"
serde = { version = "1.0.152", features = ["derive"] }
serde_json = { version = "1.0.93", features = ["preserve_order"] }
serde_yaml = "0.9.17"
@@ -37,7 +38,7 @@ tokio-graceful = "0.2.2"
tokio-stream = { version = "0.1.15", default-features = false, features = [
"sync",
] }
crossterm = "0.28.1"
crossterm = "0.29.0"
chrono = "0.4.23"
bincode = { version = "2.0.0", features = [
"serde",
@@ -90,14 +91,16 @@ strum_macros = "0.27.2"
indoc = "2.0.6"
rmcp = { version = "0.16.0", features = ["client", "transport-child-process"] }
num_cpus = "1.17.0"
rustpython-parser = "0.4.0"
rustpython-ast = "0.4.0"
tree-sitter = "0.26.8"
tree-sitter-language = "0.1"
tree-sitter-python = "0.25.0"
tree-sitter-typescript = "0.23"
colored = "3.0.0"
clap_complete = { version = "4.5.58", features = ["unstable-dynamic"] }
gman = "0.3.0"
gman = "0.4.1"
clap_complete_nushell = "4.5.9"
open = "5"
rand = "0.9.0"
rand = { version = "0.10.0", features = ["default"] }
url = "2.5.8"
[dependencies.reqwest]
+1
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@@ -28,6 +28,7 @@ Coming from [AIChat](https://github.com/sigoden/aichat)? Follow the [migration g
* [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 TypeScript Tools](./docs/function-calling/CUSTOM-TOOLS.md#custom-typescript-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.
+7 -1
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@@ -50,7 +50,13 @@ def parse_raw_data(data):
def parse_argv():
agent_func = sys.argv[1]
agent_data = sys.argv[2]
tool_data_file = os.environ.get("LLM_TOOL_DATA_FILE")
if tool_data_file and os.path.isfile(tool_data_file):
with open(tool_data_file, "r", encoding="utf-8") as f:
agent_data = f.read()
else:
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)
+5 -2
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@@ -14,7 +14,11 @@ main() {
parse_argv() {
agent_func="$1"
agent_data="$2"
if [[ -n "$LLM_TOOL_DATA_FILE" ]] && [[ -f "$LLM_TOOL_DATA_FILE" ]]; then
agent_data="$(cat "$LLM_TOOL_DATA_FILE")"
else
agent_data="$2"
fi
if [[ -z "$agent_data" ]] || [[ -z "$agent_func" ]]; then
die "usage: ./{agent_name}.sh <agent-func> <agent-data>"
fi
@@ -57,7 +61,6 @@ run() {
if [[ "$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'
+189
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@@ -0,0 +1,189 @@
#!/usr/bin/env tsx
// Usage: ./{agent_name}.ts <agent-func> <agent-data>
import { readFileSync, writeFileSync, existsSync } from "fs";
import { join } from "path";
import { pathToFileURL } from "url";
async function main(): Promise<void> {
const { agentFunc, rawData } = parseArgv();
const agentData = parseRawData(rawData);
const configDir = "{config_dir}";
setupEnv(configDir, agentFunc);
const agentToolsPath = join(configDir, "agents", "{agent_name}", "tools.ts");
await run(agentToolsPath, agentFunc, agentData);
}
function parseRawData(data: string): Record<string, unknown> {
if (!data) {
throw new Error("No JSON data");
}
try {
return JSON.parse(data);
} catch {
throw new Error("Invalid JSON data");
}
}
function parseArgv(): { agentFunc: string; rawData: string } {
const agentFunc = process.argv[2];
const toolDataFile = process.env["LLM_TOOL_DATA_FILE"];
let agentData: string;
if (toolDataFile && existsSync(toolDataFile)) {
agentData = readFileSync(toolDataFile, "utf-8");
} else {
agentData = process.argv[3];
}
if (!agentFunc || !agentData) {
process.stderr.write("Usage: ./{agent_name}.ts <agent-func> <agent-data>\n");
process.exit(1);
}
return { agentFunc, rawData: agentData };
}
function setupEnv(configDir: string, agentFunc: string): void {
loadEnv(join(configDir, ".env"));
process.env["LLM_ROOT_DIR"] = configDir;
process.env["LLM_AGENT_NAME"] = "{agent_name}";
process.env["LLM_AGENT_FUNC"] = agentFunc;
process.env["LLM_AGENT_ROOT_DIR"] = join(configDir, "agents", "{agent_name}");
process.env["LLM_AGENT_CACHE_DIR"] = join(configDir, "cache", "{agent_name}");
}
function loadEnv(filePath: string): void {
let lines: string[];
try {
lines = readFileSync(filePath, "utf-8").split("\n");
} catch {
return;
}
for (const raw of lines) {
const line = raw.trim();
if (line.startsWith("#") || !line) {
continue;
}
const eqIdx = line.indexOf("=");
if (eqIdx === -1) {
continue;
}
const key = line.slice(0, eqIdx).trim();
if (key in process.env) {
continue;
}
let value = line.slice(eqIdx + 1).trim();
if (
(value.startsWith('"') && value.endsWith('"')) ||
(value.startsWith("'") && value.endsWith("'"))
) {
value = value.slice(1, -1);
}
process.env[key] = value;
}
}
function extractParamNames(fn: Function): string[] {
const src = fn.toString();
const match = src.match(/^(?:async\s+)?function\s*\w*\s*\(([^)]*)\)/);
if (!match) {
return [];
}
return match[1]
.split(",")
.map((p) => p.trim().replace(/[:=?].*/s, "").trim())
.filter(Boolean);
}
function spreadArgs(
fn: Function,
data: Record<string, unknown>,
): unknown[] {
const names = extractParamNames(fn);
if (names.length === 0) {
return [];
}
return names.map((name) => data[name]);
}
async function run(
agentPath: string,
agentFunc: string,
agentData: Record<string, unknown>,
): Promise<void> {
const mod = await import(pathToFileURL(agentPath).href);
if (typeof mod[agentFunc] !== "function") {
throw new Error(`No module function '${agentFunc}' at '${agentPath}'`);
}
const fn = mod[agentFunc] as Function;
const args = spreadArgs(fn, agentData);
const value = await fn(...args);
returnToLlm(value);
dumpResult(`{agent_name}:${agentFunc}`);
}
function returnToLlm(value: unknown): void {
if (value === null || value === undefined) {
return;
}
const output = process.env["LLM_OUTPUT"];
const write = (s: string) => {
if (output) {
writeFileSync(output, s, "utf-8");
} else {
process.stdout.write(s);
}
};
if (typeof value === "string" || typeof value === "number" || typeof value === "boolean") {
write(String(value));
} else if (typeof value === "object") {
write(JSON.stringify(value, null, 2));
}
}
function dumpResult(name: string): void {
const dumpResults = process.env["LLM_DUMP_RESULTS"];
const llmOutput = process.env["LLM_OUTPUT"];
if (!dumpResults || !llmOutput || !process.stdout.isTTY) {
return;
}
try {
const pattern = new RegExp(`\\b(${dumpResults})\\b`);
if (!pattern.test(name)) {
return;
}
} catch {
return;
}
let data: string;
try {
data = readFileSync(llmOutput, "utf-8");
} catch {
return;
}
process.stdout.write(
`\x1b[2m----------------------\n${data}\n----------------------\x1b[0m\n`,
);
}
main().catch((err) => {
process.stderr.write(`${err}\n`);
process.exit(1);
});
+5
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@@ -49,6 +49,11 @@ def parse_raw_data(data):
def parse_argv():
tool_data_file = os.environ.get("LLM_TOOL_DATA_FILE")
if tool_data_file and os.path.isfile(tool_data_file):
with open(tool_data_file, "r", encoding="utf-8") as f:
return f.read()
argv = sys.argv[:] + [None] * max(0, 2 - len(sys.argv))
tool_data = argv[1]
+5 -2
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@@ -13,7 +13,11 @@ main() {
}
parse_argv() {
tool_data="$1"
if [[ -n "$LLM_TOOL_DATA_FILE" ]] && [[ -f "$LLM_TOOL_DATA_FILE" ]]; then
tool_data="$(cat "$LLM_TOOL_DATA_FILE")"
else
tool_data="$1"
fi
if [[ -z "$tool_data" ]]; then
die "usage: ./{function_name}.sh <tool-data>"
fi
@@ -54,7 +58,6 @@ run() {
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'
+184
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@@ -0,0 +1,184 @@
#!/usr/bin/env tsx
// Usage: ./{function_name}.ts <tool-data>
import { readFileSync, writeFileSync, existsSync } from "fs";
import { join } from "path";
import { pathToFileURL } from "url";
async function main(): Promise<void> {
const rawData = parseArgv();
const toolData = parseRawData(rawData);
const rootDir = "{root_dir}";
setupEnv(rootDir);
const toolPath = "{tool_path}.ts";
await run(toolPath, "run", toolData);
}
function parseRawData(data: string): Record<string, unknown> {
if (!data) {
throw new Error("No JSON data");
}
try {
return JSON.parse(data);
} catch {
throw new Error("Invalid JSON data");
}
}
function parseArgv(): string {
const toolDataFile = process.env["LLM_TOOL_DATA_FILE"];
if (toolDataFile && existsSync(toolDataFile)) {
return readFileSync(toolDataFile, "utf-8");
}
const toolData = process.argv[2];
if (!toolData) {
process.stderr.write("Usage: ./{function_name}.ts <tool-data>\n");
process.exit(1);
}
return toolData;
}
function setupEnv(rootDir: string): void {
loadEnv(join(rootDir, ".env"));
process.env["LLM_ROOT_DIR"] = rootDir;
process.env["LLM_TOOL_NAME"] = "{function_name}";
process.env["LLM_TOOL_CACHE_DIR"] = join(rootDir, "cache", "{function_name}");
}
function loadEnv(filePath: string): void {
let lines: string[];
try {
lines = readFileSync(filePath, "utf-8").split("\n");
} catch {
return;
}
for (const raw of lines) {
const line = raw.trim();
if (line.startsWith("#") || !line) {
continue;
}
const eqIdx = line.indexOf("=");
if (eqIdx === -1) {
continue;
}
const key = line.slice(0, eqIdx).trim();
if (key in process.env) {
continue;
}
let value = line.slice(eqIdx + 1).trim();
if (
(value.startsWith('"') && value.endsWith('"')) ||
(value.startsWith("'") && value.endsWith("'"))
) {
value = value.slice(1, -1);
}
process.env[key] = value;
}
}
function extractParamNames(fn: Function): string[] {
const src = fn.toString();
const match = src.match(/^(?:async\s+)?function\s*\w*\s*\(([^)]*)\)/);
if (!match) {
return [];
}
return match[1]
.split(",")
.map((p) => p.trim().replace(/[:=?].*/s, "").trim())
.filter(Boolean);
}
function spreadArgs(
fn: Function,
data: Record<string, unknown>,
): unknown[] {
const names = extractParamNames(fn);
if (names.length === 0) {
return [];
}
return names.map((name) => data[name]);
}
async function run(
toolPath: string,
toolFunc: string,
toolData: Record<string, unknown>,
): Promise<void> {
const mod = await import(pathToFileURL(toolPath).href);
if (typeof mod[toolFunc] !== "function") {
throw new Error(`No module function '${toolFunc}' at '${toolPath}'`);
}
const fn = mod[toolFunc] as Function;
const args = spreadArgs(fn, toolData);
const value = await fn(...args);
returnToLlm(value);
dumpResult("{function_name}");
}
function returnToLlm(value: unknown): void {
if (value === null || value === undefined) {
return;
}
const output = process.env["LLM_OUTPUT"];
const write = (s: string) => {
if (output) {
writeFileSync(output, s, "utf-8");
} else {
process.stdout.write(s);
}
};
if (typeof value === "string" || typeof value === "number" || typeof value === "boolean") {
write(String(value));
} else if (typeof value === "object") {
write(JSON.stringify(value, null, 2));
}
}
function dumpResult(name: string): void {
const dumpResults = process.env["LLM_DUMP_RESULTS"];
const llmOutput = process.env["LLM_OUTPUT"];
if (!dumpResults || !llmOutput || !process.stdout.isTTY) {
return;
}
try {
const pattern = new RegExp(`\\b(${dumpResults})\\b`);
if (!pattern.test(name)) {
return;
}
} catch {
return;
}
let data: string;
try {
data = readFileSync(llmOutput, "utf-8");
} catch {
return;
}
process.stdout.write(
`\x1b[2m----------------------\n${data}\n----------------------\x1b[0m\n`,
);
}
main().catch((err) => {
process.stderr.write(`${err}\n`);
process.exit(1);
});
+23 -10
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@@ -1,6 +1,7 @@
import os
from typing import List, Literal, Optional
def run(
string: str,
string_enum: Literal["foo", "bar"],
@@ -9,26 +10,38 @@ def run(
number: float,
array: List[str],
string_optional: Optional[str] = None,
integer_with_default: int = 42,
boolean_with_default: bool = True,
number_with_default: float = 3.14,
string_with_default: str = "hello",
array_optional: Optional[List[str]] = None,
):
"""Demonstrates how to create a tool using Python and how to use comments.
"""Demonstrates all supported Python parameter types and variations.
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
string: A required string property
string_enum: A required string property constrained to specific values
boolean: A required boolean property
integer: A required integer property
number: A required number (float) property
array: A required string array property
string_optional: An optional string property (Optional[str] with None default)
integer_with_default: An optional integer with a non-None default value
boolean_with_default: An optional boolean with a default value
number_with_default: An optional number with a default value
string_with_default: An optional string with a default value
array_optional: 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}
string_optional: {string_optional}
integer_with_default: {integer_with_default}
boolean_with_default: {boolean_with_default}
number_with_default: {number_with_default}
string_with_default: {string_with_default}
array_optional: {array_optional}"""
for key, value in os.environ.items():
+53
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@@ -0,0 +1,53 @@
/**
* Demonstrates all supported TypeScript parameter types and variations.
*
* @param string - A required string property
* @param string_enum - A required string property constrained to specific values
* @param boolean - A required boolean property
* @param number - A required number property
* @param array_bracket - A required string array using bracket syntax
* @param array_generic - A required string array using generic syntax
* @param string_optional - An optional string using the question mark syntax
* @param string_nullable - An optional string using the union-with-null syntax
* @param number_with_default - An optional number with a default value
* @param boolean_with_default - An optional boolean with a default value
* @param string_with_default - An optional string with a default value
* @param array_optional - An optional string array using the question mark syntax
*/
export function run(
string: string,
string_enum: "foo" | "bar",
boolean: boolean,
number: number,
array_bracket: string[],
array_generic: Array<string>,
string_optional?: string,
string_nullable: string | null = null,
number_with_default: number = 42,
boolean_with_default: boolean = true,
string_with_default: string = "hello",
array_optional?: string[],
): string {
const parts = [
`string: ${string}`,
`string_enum: ${string_enum}`,
`boolean: ${boolean}`,
`number: ${number}`,
`array_bracket: ${JSON.stringify(array_bracket)}`,
`array_generic: ${JSON.stringify(array_generic)}`,
`string_optional: ${string_optional}`,
`string_nullable: ${string_nullable}`,
`number_with_default: ${number_with_default}`,
`boolean_with_default: ${boolean_with_default}`,
`string_with_default: ${string_with_default}`,
`array_optional: ${JSON.stringify(array_optional)}`,
];
for (const [key, value] of Object.entries(process.env)) {
if (key.startsWith("LLM_")) {
parts.push(`${key}: ${value}`);
}
}
return parts.join("\n");
}
@@ -0,0 +1,24 @@
#!/usr/bin/env tsx
import { appendFileSync, mkdirSync } from "fs";
import { dirname } from "path";
/**
* Get the current weather in a given location
* @param location - The city and optionally the state or country (e.g., "London", "San Francisco, CA").
*/
export async function run(location: string): string {
const encoded = encodeURIComponent(location);
const url = `https://wttr.in/${encoded}?format=4`;
const resp = await fetch(url);
const data = await resp.text();
const dest = process.env["LLM_OUTPUT"] ?? "/dev/stdout";
if (dest !== "-" && dest !== "/dev/stdout") {
mkdirSync(dirname(dest), { recursive: true });
appendFileSync(dest, data, "utf-8");
}
return data;
}
+2
View File
@@ -46,6 +46,7 @@ enabled_tools: null # Which tools to enable by default. (e.g. 'fs,w
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
# - demo_ts.ts
- execute_command.sh
# - execute_py_code.py
# - execute_sql_code.sh
@@ -61,6 +62,7 @@ visible_tools: # Which tools are visible to be compiled (and a
# - fs_write.sh
- get_current_time.sh
# - get_current_weather.py
# - get_current_weather.ts
- get_current_weather.sh
- query_jira_issues.sh
# - search_arxiv.sh
+62 -9
View File
@@ -33,6 +33,7 @@ If you're looking for more example agents, refer to the [built-in agents](../ass
- [.env File Support](#env-file-support)
- [Python-Based Agent Tools](#python-based-agent-tools)
- [Bash-Based Agent Tools](#bash-based-agent-tools)
- [TypeScript-Based Agent Tools](#typescript-based-agent-tools)
- [5. Conversation Starters](#5-conversation-starters)
- [6. Todo System & Auto-Continuation](#6-todo-system--auto-continuation)
- [7. Sub-Agent Spawning System](#7-sub-agent-spawning-system)
@@ -62,10 +63,12 @@ Agent configurations often have the following directory structure:
├── tools.sh
or
├── tools.py
or
├── tools.ts
```
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`).
tool definitions (`agents/my-agent/tools.sh`, `tools.py`, or `tools.ts`).
To see a full example configuration file, refer to the [example agent config file](../config.agent.example.yaml).
@@ -114,10 +117,10 @@ isolated environment, so in order for an agent to use a tool or MCP server that
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
And if you don't define a `agents/my-agent/tools.sh`, `agents/my-agent/tools.py`, or `agents/my-agent/tools.ts`, 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
You'll notice there are 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).
@@ -205,7 +208,7 @@ variables:
### 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`.
in your `agents/my-agent/tools.py`, `agents/my-agent/tools.sh`, or `agents/my-agent/tools.ts`.
**Example: Instructions for a JSON-reader agent that specializes on each JSON input it receives**
`agents/json-reader/tools.py`:
@@ -306,8 +309,8 @@ 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.
For more information on how to create custom tools for your agent and the structure of the `agent/my-agent/tools.sh`,
`agent/my-agent/tools.py`, or `agent/my-agent/tools.ts` 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
@@ -337,10 +340,11 @@ defining a single function that gets executed at runtime (e.g. `main` for bash t
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 can only utilize one of: a bash-based `<loki-config-dir>/agents/my-agent/tools.sh`, a Python-based
`<loki-config-dir>/agents/my-agent/tools.py`, or a TypeScript-based `<loki-config-dir>/agents/my-agent/tools.ts`.
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
tools file. **Any scripts *not* named `tools.{py,sh,ts}` 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:
@@ -428,6 +432,55 @@ 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).
### TypeScript-Based Agent Tools
TypeScript-based agent tools work exactly the same as TypeScript global tools. Instead of a single `run` function,
you define as many exported functions as you like. Non-exported functions are private helpers and are invisible to the
LLM.
**Example:**
`agents/my-agent/tools.ts`
```typescript
/**
* Get your IP information
*/
export async function get_ip_info(): Promise<string> {
const resp = await fetch("https://httpbin.org/ip");
return await resp.text();
}
/**
* Find your public IP address using AWS
*/
export async function get_ip_address_from_aws(): Promise<string> {
const resp = await fetch("https://checkip.amazonaws.com");
return await resp.text();
}
// Non-exported helper — invisible to the LLM
function formatResponse(data: string): string {
return data.trim();
}
```
Loki automatically compiles each exported function as a separate tool for the LLM to call. Just make sure you
follow the same JSDoc and parameter conventions as you would when creating custom TypeScript tools.
TypeScript agent tools also support dynamic instructions via an exported `_instructions()` function:
```typescript
import { readFileSync } from "fs";
/**
* Generates instructions for the agent dynamically
*/
export function _instructions(): string {
const schema = readFileSync("schema.json", "utf-8");
return `You are an AI agent that works with the following schema:\n${schema}`;
}
```
For more information on how to build tools in TypeScript, refer to the [custom TypeScript tools documentation](function-calling/CUSTOM-TOOLS.md#custom-typescript-based-tools).
## 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.
+4 -3
View File
@@ -107,6 +107,7 @@ The following variables can be used to change the log level of Loki or the locat
can also pass the `--disable-log-colors` flag as well.
## Miscellaneous Variables
| Environment Variable | Description | Default Value |
|----------------------|--------------------------------------------------------------------------------------------------|---------------|
| `AUTO_CONFIRM` | Bypass all `guard_*` checks in the bash prompt helpers; useful for agent composition and routing | |
| Environment Variable | Description | Default Value |
|----------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------|
| `AUTO_CONFIRM` | Bypass all `guard_*` checks in the bash prompt helpers; useful for agent composition and routing | |
| `LLM_TOOL_DATA_FILE` | Set automatically by Loki on Windows. Points to a temporary file containing the JSON tool call data. <br>Tool scripts (`run-tool.sh`, `run-agent.sh`, etc.) read from this file instead of command-line args <br>to avoid JSON escaping issues when data passes through `cmd.exe` → bash. **Not intended to be set by users.** | |
+174 -11
View File
@@ -10,6 +10,8 @@ into your Loki setup. This document provides a guide on how to create and use cu
- [Environment Variables](#environment-variables)
- [Custom Bash-Based Tools](#custom-bash-based-tools)
- [Custom Python-Based Tools](#custom-python-based-tools)
- [Custom TypeScript-Based Tools](#custom-typescript-based-tools)
- [Custom Runtime](#custom-runtime)
<!--toc:end-->
---
@@ -19,9 +21,10 @@ Loki supports custom tools written in the following programming languages:
* Python
* Bash
* TypeScript
## Creating a Custom Tool
All tools are created as scripts in either Python or Bash. They should be placed in the `functions/tools` directory.
All tools are created as scripts in either Python, Bash, or TypeScript. They should be placed in the `functions/tools` directory.
The location of the `functions` directory varies between systems, so you can use the following command to locate
your `functions` directory:
@@ -81,6 +84,7 @@ Loki and demonstrates how to create a Python-based tool:
import os
from typing import List, Literal, Optional
def run(
string: str,
string_enum: Literal["foo", "bar"],
@@ -89,26 +93,38 @@ def run(
number: float,
array: List[str],
string_optional: Optional[str] = None,
integer_with_default: int = 42,
boolean_with_default: bool = True,
number_with_default: float = 3.14,
string_with_default: str = "hello",
array_optional: Optional[List[str]] = None,
):
"""Demonstrates how to create a tool using Python and how to use comments.
"""Demonstrates all supported Python parameter types and variations.
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
string: A required string property
string_enum: A required string property constrained to specific values
boolean: A required boolean property
integer: A required integer property
number: A required number (float) property
array: A required string array property
string_optional: An optional string property (Optional[str] with None default)
integer_with_default: An optional integer with a non-None default value
boolean_with_default: An optional boolean with a default value
number_with_default: An optional number with a default value
string_with_default: An optional string with a default value
array_optional: 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}
string_optional: {string_optional}
integer_with_default: {integer_with_default}
boolean_with_default: {boolean_with_default}
number_with_default: {number_with_default}
string_with_default: {string_with_default}
array_optional: {array_optional}"""
for key, value in os.environ.items():
@@ -117,3 +133,150 @@ array_optional: {array_optional}"""
return output
```
### Custom TypeScript-Based Tools
Loki supports tools written in TypeScript. TypeScript tools require [Node.js](https://nodejs.org/) and
[tsx](https://tsx.is/) (`npx tsx` is used as the default runtime).
Each TypeScript-based tool must follow a specific structure in order for Loki to properly compile and execute it:
* The tool must be a TypeScript file with a `.ts` file extension.
* The tool must have an `export function run(...)` that serves as the entry point for the tool.
* Non-exported functions are ignored by the compiler and can be used as private helpers.
* The `run` function must accept flat parameters that define the inputs for the tool.
* Always use type annotations to specify the data type of each parameter.
* Use `param?: type` or `type | null` to indicate optional parameters.
* Use `param: type = value` for parameters with default values.
* The `run` function must return a `string` (or `Promise<string>` for async functions).
* For TypeScript, the return value is automatically written to the `LLM_OUTPUT` environment variable, so there's
no need to explicitly write to the environment variable within the function.
* The function must have a JSDoc comment that describes the tool and its parameters.
* Each parameter should be documented using `@param name - description` tags.
* These descriptions are passed to the LLM as the tool description, letting the LLM know what the tool does and
how to use it.
* Async functions (`export async function run(...)`) are fully supported and handled transparently.
**Supported Parameter Types:**
| TypeScript Type | JSON Schema | Notes |
|-------------------|--------------------------------------------------|-----------------------------|
| `string` | `{"type": "string"}` | Required string |
| `number` | `{"type": "number"}` | Required number |
| `boolean` | `{"type": "boolean"}` | Required boolean |
| `string[]` | `{"type": "array", "items": {"type": "string"}}` | Array (bracket syntax) |
| `Array<string>` | `{"type": "array", "items": {"type": "string"}}` | Array (generic syntax) |
| `"foo" \| "bar"` | `{"type": "string", "enum": ["foo", "bar"]}` | String enum (literal union) |
| `param?: string` | `{"type": "string"}` (not required) | Optional via question mark |
| `string \| null` | `{"type": "string"}` (not required) | Optional via null union |
| `param = "value"` | `{"type": "string"}` (not required) | Optional via default value |
**Unsupported Patterns (will produce a compile error):**
* Rest parameters (`...args: string[]`)
* Destructured object parameters (`{ a, b }: { a: string, b: string }`)
* Arrow functions (`const run = (x: string) => ...`)
* Function expressions (`const run = function(x: string) { ... }`)
Only `export function` declarations are recognized. Non-exported functions are invisible to the compiler.
Below is the [`demo_ts.ts`](../../assets/functions/tools/demo_ts.ts) tool definition that comes pre-packaged with
Loki and demonstrates how to create a TypeScript-based tool:
```typescript
/**
* Demonstrates all supported TypeScript parameter types and variations.
*
* @param string - A required string property
* @param string_enum - A required string property constrained to specific values
* @param boolean - A required boolean property
* @param number - A required number property
* @param array_bracket - A required string array using bracket syntax
* @param array_generic - A required string array using generic syntax
* @param string_optional - An optional string using the question mark syntax
* @param string_nullable - An optional string using the union-with-null syntax
* @param number_with_default - An optional number with a default value
* @param boolean_with_default - An optional boolean with a default value
* @param string_with_default - An optional string with a default value
* @param array_optional - An optional string array using the question mark syntax
*/
export function run(
string: string,
string_enum: "foo" | "bar",
boolean: boolean,
number: number,
array_bracket: string[],
array_generic: Array<string>,
string_optional?: string,
string_nullable: string | null = null,
number_with_default: number = 42,
boolean_with_default: boolean = true,
string_with_default: string = "hello",
array_optional?: string[],
): string {
const parts = [
`string: ${string}`,
`string_enum: ${string_enum}`,
`boolean: ${boolean}`,
`number: ${number}`,
`array_bracket: ${JSON.stringify(array_bracket)}`,
`array_generic: ${JSON.stringify(array_generic)}`,
`string_optional: ${string_optional}`,
`string_nullable: ${string_nullable}`,
`number_with_default: ${number_with_default}`,
`boolean_with_default: ${boolean_with_default}`,
`string_with_default: ${string_with_default}`,
`array_optional: ${JSON.stringify(array_optional)}`,
];
for (const [key, value] of Object.entries(process.env)) {
if (key.startsWith("LLM_")) {
parts.push(`${key}: ${value}`);
}
}
return parts.join("\n");
}
```
## Custom Runtime
By default, Loki uses the following runtimes to execute tools:
| Language | Default Runtime | Requirement |
|------------|-----------------|--------------------------------|
| Python | `python` | Python 3 on `$PATH` |
| TypeScript | `npx tsx` | Node.js + tsx (`npm i -g tsx`) |
| Bash | `bash` | Bash on `$PATH` |
You can override the runtime for Python and TypeScript tools using a **shebang line** (`#!`) at the top of your
script. Loki reads the first line of each tool file; if it starts with `#!`, the specified interpreter is used instead
of the default.
**Examples:**
```python
#!/usr/bin/env python3.11
# This Python tool will be executed with python3.11 instead of the default `python`
def run(name: str):
"""Greet someone.
Args:
name: The name to greet
"""
return f"Hello, {name}!"
```
```typescript
#!/usr/bin/env bun
// This TypeScript tool will be executed with Bun instead of the default `npx tsx`
/**
* Greet someone.
* @param name - The name to greet
*/
export function run(name: string): string {
return `Hello, ${name}!`;
}
```
This is useful for pinning a specific Python version, using an alternative TypeScript runtime like
[Bun](https://bun.sh/) or [Deno](https://deno.com/), or working with virtual environments.
+2
View File
@@ -32,6 +32,7 @@ be enabled/disabled can be found in the [Configuration](#configuration) section
|-------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------|
| [`demo_py.py`](../../assets/functions/tools/demo_py.py) | Demonstrates how to create a tool using Python and how to use comments. | 🔴 |
| [`demo_sh.sh`](../../assets/functions/tools/demo_sh.sh) | Demonstrate how to create a tool using Bash and how to use comment tags. | 🔴 |
| [`demo_ts.ts`](../../assets/functions/tools/demo_ts.ts) | Demonstrates how to create a tool using TypeScript and how to use JSDoc comments. | 🔴 |
| [`execute_command.sh`](../../assets/functions/tools/execute_command.sh) | Execute the shell command. | 🟢 |
| [`execute_py_code.py`](../../assets/functions/tools/execute_py_code.py) | Execute the given Python code. | 🔴 |
| [`execute_sql_code.sh`](../../assets/functions/tools/execute_sql_code.sh) | Execute SQL code. | 🔴 |
@@ -49,6 +50,7 @@ be enabled/disabled can be found in the [Configuration](#configuration) section
| [`get_current_time.sh`](../../assets/functions/tools/get_current_time.sh) | Get the current time. | 🟢 |
| [`get_current_weather.py`](../../assets/functions/tools/get_current_weather.py) | Get the current weather in a given location (Python implementation) | 🔴 |
| [`get_current_weather.sh`](../../assets/functions/tools/get_current_weather.sh) | Get the current weather in a given location. | 🟢 |
| [`get_current_weather.ts`](../../assets/functions/tools/get_current_weather.ts) | Get the current weather in a given location (TypeScript implementation) | 🔴 |
| [`query_jira_issues.sh`](../../assets/functions/tools/query_jira_issues.sh) | Query for jira issues using a Jira Query Language (JQL) query. | 🟢 |
| [`search_arxiv.sh`](../../assets/functions/tools/search_arxiv.sh) | Search arXiv using the given search query and return the top papers. | 🔴 |
| [`search_wikipedia.sh`](../../assets/functions/tools/search_wikipedia.sh) | Search Wikipedia using the given search query. <br>Use it to get detailed information about a public figure, interpretation of a <br>complex scientific concept or in-depth connectivity of a significant historical <br>event, etc. | 🔴 |
+416
View File
@@ -0,0 +1,416 @@
# Sisyphus in LangChain/LangGraph
A faithful recreation of [Loki's Sisyphus agent](../../assets/agents/sisyphus/) using [LangGraph](https://docs.langchain.com/langgraph/) — LangChain's framework for stateful, multi-agent workflows.
This project exists to help you understand LangChain/LangGraph by mapping every concept to its Loki equivalent.
## Architecture Overview
```
┌─────────────────────────────────────────────────────────────┐
│ SUPERVISOR NODE │
│ Intent classification → Routing decision → Command(goto=) │
│ │
│ Loki equivalent: sisyphus/config.yaml │
│ (agent__spawn → Command, agent__collect → graph edge) │
└──────────┬──────────────┬──────────────┬────────────────────┘
│ │ │
▼ ▼ ▼
┌────────────┐ ┌────────────┐ ┌────────────┐
│ EXPLORE │ │ ORACLE │ │ CODER │
│ (research) │ │ (advise) │ │ (build) │
│ │ │ │ │ │
│ read-only │ │ read-only │ │ read+write │
│ tools │ │ tools │ │ tools │
└─────┬──────┘ └─────┬──────┘ └─────┬──────┘
│ │ │
└──────────────┼──────────────┘
back to supervisor
```
## Concept Map: Loki → LangGraph
This is the key reference. Every row maps a Loki concept to its LangGraph equivalent.
### Core Architecture
| Loki Concept | LangGraph Equivalent | Where in Code |
|---|---|---|
| Agent config (config.yaml) | Node function + system prompt | `agents/explore.py`, etc. |
| Agent instructions | System prompt string | `EXPLORE_SYSTEM_PROMPT`, etc. |
| Agent tools (tools.sh) | `@tool`-decorated Python functions | `tools/filesystem.py`, `tools/project.py` |
| Agent session (chat loop) | Graph state + message list | `state.py``SisyphusState.messages` |
| `agent__spawn --agent X` | `Command(goto="X")` | `agents/supervisor.py` |
| `agent__collect --id` | Graph edge (implicit — workers return to supervisor) | `graph.py``add_edge("explore", "supervisor")` |
| `agent__check` (non-blocking) | Not needed (graph handles scheduling) | — |
| `agent__cancel` | Not needed (graph handles lifecycle) | — |
| `can_spawn_agents: true` | Node has routing logic (supervisor) | `agents/supervisor.py` |
| `max_concurrent_agents: 4` | `Send()` API for parallel fan-out | See [Parallel Execution](#parallel-execution) |
| `max_agent_depth: 3` | `recursion_limit` in config | `cli.py``recursion_limit: 50` |
| `summarization_threshold` | Manual truncation in supervisor | `supervisor.py``_summarize_outputs()` |
### Tool System
| Loki Concept | LangGraph Equivalent | Notes |
|---|---|---|
| `tools.sh` with `@cmd` annotations | `@tool` decorator | Loki compiles bash annotations to JSON schema; LangChain generates schema from the Python function signature + docstring |
| `@option --pattern!` (required arg) | Function parameter without default | `def search_content(pattern: str)` |
| `@option --lines` (optional arg) | Parameter with default | `def read_file(path: str, limit: int = 200)` |
| `@env LLM_OUTPUT=/dev/stdout` | Return value | LangChain tools return strings; Loki tools write to `$LLM_OUTPUT` |
| `@describe` | Docstring | The tool's docstring becomes the description the LLM sees |
| Global tools (`fs_read.sh`, etc.) | Shared tool imports | Both agents import from `tools/filesystem.py` |
| Agent-specific tools | Per-node tool binding | `llm.bind_tools(EXPLORE_TOOLS)` vs `llm.bind_tools(CODER_TOOLS)` |
| `.shared/utils.sh` | `tools/project.py` | Shared project detection utilities |
| `detect_project()` heuristic | `detect_project()` in Python | Same logic: check Cargo.toml → go.mod → package.json → etc. |
| LLM fallback for unknown projects | (omitted) | The agents themselves can reason about unknown project types |
### State & Memory
| Loki Concept | LangGraph Equivalent | Notes |
|---|---|---|
| Agent session (conversation history) | `SisyphusState.messages` | `Annotated[list, add_messages]` — the reducer appends instead of replacing |
| `agent_session: temp` | `MemorySaver` checkpointer | Loki's temp sessions are ephemeral; MemorySaver is in-memory (lost on restart) |
| Per-agent isolation | Per-node system prompt + tools | In Loki agents have separate sessions; in LangGraph they share messages but have different system prompts |
| `{{project_dir}}` variable | `SisyphusState.project_dir` | Loki interpolates variables into prompts; LangGraph stores them in state |
| `{{__tools__}}` injection | `llm.bind_tools()` | Loki injects tool descriptions into the prompt; LangChain attaches them to the API call |
### Orchestration
| Loki Concept | LangGraph Equivalent | Notes |
|---|---|---|
| Intent classification table | `RoutingDecision` structured output | Loki does this in free text; LangGraph forces typed JSON |
| Oracle triggers ("How should I...") | Supervisor prompt + structured output | Same trigger phrases, enforced via system prompt |
| Coder delegation format | Supervisor builds HumanMessage | The structured prompt (Goal/Reference Files/Conventions/Constraints) |
| `agent__spawn` (parallel) | `Send()` API | Dynamic fan-out to multiple nodes |
| Todo system (`todo__init`, etc.) | `SisyphusState.todos` | State field with a merge reducer |
| `auto_continue: true` | Supervisor loop (iteration counter) | Supervisor re-routes until FINISH or max iterations |
| `max_auto_continues: 25` | `MAX_ITERATIONS = 15` | Safety valve to prevent infinite loops |
| `user__ask` / `user__confirm` | `interrupt()` API | Pauses graph, surfaces question to caller, resumes with answer |
| Escalation (child → parent → user) | `interrupt()` in any node | Any node can pause; the caller handles the interaction |
### Execution Model
| Loki Concept | LangGraph Equivalent | Notes |
|---|---|---|
| `loki --agent sisyphus` | `python -m sisyphus_langchain.cli` | CLI entry point |
| REPL mode | `cli.py``repl()` | Interactive loop with thread persistence |
| One-shot mode | `cli.py``run_query()` | Single query, print result, exit |
| Streaming output | `graph.stream()` | LangGraph supports per-node streaming |
| `inject_spawn_instructions` | (always on) | System prompts are always included |
| `inject_todo_instructions` | (always on) | Todo instructions could be added to prompts |
## How the Execution Flow Works
### 1. User sends a message
```python
graph.invoke({"messages": [HumanMessage("Add a health check endpoint")]})
```
### 2. Supervisor classifies intent
The supervisor LLM reads the message and produces a `RoutingDecision`:
```json
{
"intent": "implementation",
"next_agent": "explore",
"delegation_notes": "Find existing API endpoint patterns, route structure, and health check conventions"
}
```
### 3. Supervisor routes via Command
```python
return Command(goto="explore", update={"intent": "implementation", "iteration_count": 1})
```
### 4. Explore agent runs
- Receives the full message history (including the user's request)
- Calls read-only tools (search_content, search_files, read_file)
- Returns findings in messages
### 5. Control returns to supervisor
The graph edge `explore → supervisor` fires automatically.
### 6. Supervisor reviews and routes again
Now it has explore's findings. It routes to coder with context:
```json
{
"intent": "implementation",
"next_agent": "coder",
"delegation_notes": "Implement health check endpoint following patterns found in src/routes/"
}
```
### 7. Coder implements
- Reads explore's findings from the message history
- Writes files via `write_file` tool
- Runs `verify_build` to check compilation
### 8. Supervisor verifies and finishes
```json
{
"intent": "implementation",
"next_agent": "FINISH",
"delegation_notes": "Added /health endpoint in src/routes/health.py. Build passes."
}
```
## Key Differences from Loki
### What LangGraph does better
1. **Declarative graph** — The topology is visible and debuggable. Loki's orchestration is emergent from the LLM's tool calls.
2. **Typed state**`SisyphusState` is a TypedDict with reducers. Loki's state is implicit in the conversation.
3. **Checkpointing** — Built-in persistence. Loki manages sessions manually.
4. **Time-travel debugging** — Inspect any checkpoint. Loki has no equivalent.
5. **Structured routing**`RoutingDecision` forces valid JSON. Loki relies on the LLM calling the right tool.
### What Loki does better
1. **True parallelism**`agent__spawn` runs multiple agents concurrently in separate threads. This LangGraph implementation is sequential (see [Parallel Execution](#parallel-execution) for how to add it).
2. **Agent isolation** — Each Loki agent has its own session, tools, and config. LangGraph nodes share state.
3. **Teammate messaging** — Loki agents can send messages to siblings. LangGraph nodes communicate only through shared state.
4. **Dynamic tool compilation** — Loki compiles bash/python/typescript tools at startup. LangChain tools are statically defined.
5. **Escalation protocol** — Loki's child-to-parent escalation is sophisticated. LangGraph's `interrupt()` is simpler but less structured.
6. **Task queues with dependencies** — Loki's `agent__task_create` supports dependency DAGs. LangGraph's routing is simpler (hub-and-spoke).
## Running It
### Prerequisites
```bash
# Python 3.11+
python --version
# Set your API key
export OPENAI_API_KEY="sk-..."
```
### Install
```bash
cd examples/langchain-sisyphus
# With pip
pip install -e .
# Or with uv (recommended)
uv pip install -e .
```
### Usage
```bash
# Interactive REPL (like `loki --agent sisyphus`)
sisyphus
# One-shot query
sisyphus "Find all TODO comments in the codebase"
# With custom models (cost optimization)
sisyphus --explore-model gpt-4o-mini --coder-model gpt-4o "Add input validation to the API"
# Programmatic usage
python -c "
from sisyphus_langchain import build_graph
from langchain_core.messages import HumanMessage
graph = build_graph()
result = graph.invoke({
'messages': [HumanMessage('What patterns does this codebase use?')],
'intent': 'ambiguous',
'next_agent': '',
'iteration_count': 0,
'todos': [],
'agent_outputs': {},
'final_output': '',
'project_dir': '.',
}, config={'configurable': {'thread_id': 'demo'}, 'recursion_limit': 50})
print(result['final_output'])
"
```
### Using Anthropic Models
Replace `ChatOpenAI` with `ChatAnthropic` in the agent factories:
```python
from langchain_anthropic import ChatAnthropic
# In agents/oracle.py:
llm = ChatAnthropic(model="claude-sonnet-4-20250514", temperature=0.2).bind_tools(ORACLE_TOOLS)
```
## Deployment
### Option 1: Standalone Script (Simplest)
Just run the CLI directly. No infrastructure needed.
```bash
sisyphus "Add a health check endpoint"
```
### Option 2: FastAPI Server
```python
# server.py
from fastapi import FastAPI
from langserve import add_routes
from sisyphus_langchain import build_graph
app = FastAPI(title="Sisyphus API")
graph = build_graph()
add_routes(app, graph, path="/agent")
# Run: uvicorn server:app --host 0.0.0.0 --port 8000
# Call: POST http://localhost:8000/agent/invoke
```
### Option 3: LangGraph Platform (Production)
Create a `langgraph.json` at the project root:
```json
{
"graphs": {
"sisyphus": "./sisyphus_langchain/graph.py:build_graph"
},
"dependencies": ["./sisyphus_langchain"],
"env": ".env"
}
```
Then deploy:
```bash
pip install langgraph-cli
langgraph deploy
```
This gives you:
- Durable checkpointing (PostgreSQL)
- Background runs
- Streaming API
- Zero-downtime deployments
- Built-in observability
### Option 4: Docker
```dockerfile
FROM python:3.12-slim
WORKDIR /app
COPY . .
RUN pip install -e .
CMD ["sisyphus"]
```
```bash
docker build -t sisyphus .
docker run -it -e OPENAI_API_KEY=$OPENAI_API_KEY sisyphus
```
## Parallel Execution
This implementation routes sequentially for simplicity. To add Loki-style parallel agent execution, use LangGraph's `Send()` API:
```python
from langgraph.types import Send
def supervisor_node(state):
# Fan out to multiple explore agents in parallel
# (like Loki's agent__spawn called multiple times)
return [
Send("explore", {
**state,
"messages": state["messages"] + [
HumanMessage("Find existing API endpoint patterns")
],
}),
Send("explore", {
**state,
"messages": state["messages"] + [
HumanMessage("Find data models and database patterns")
],
}),
]
```
This is equivalent to Loki's pattern of spawning multiple explore agents:
```
agent__spawn --agent explore --prompt "Find API patterns"
agent__spawn --agent explore --prompt "Find database patterns"
agent__collect --id <id1>
agent__collect --id <id2>
```
## Adding Human-in-the-Loop
To replicate Loki's `user__ask` / `user__confirm` tools, use LangGraph's `interrupt()`:
```python
from langgraph.types import interrupt
def supervisor_node(state):
# Pause and ask the user (like Loki's user__ask)
answer = interrupt({
"question": "How should we structure the authentication?",
"options": [
"JWT with httpOnly cookies (Recommended)",
"Session-based with Redis",
"OAuth2 with external provider",
],
})
# `answer` contains the user's selection when the graph resumes
```
## Project Structure
```
examples/langchain-sisyphus/
├── pyproject.toml # Dependencies & build config
├── README.md # This file
└── sisyphus_langchain/
├── __init__.py # Package entry point
├── cli.py # CLI (REPL + one-shot mode)
├── graph.py # Graph assembly (wires nodes + edges)
├── state.py # Shared state schema (TypedDict)
├── agents/
│ ├── __init__.py
│ ├── supervisor.py # Sisyphus orchestrator (intent → routing)
│ ├── explore.py # Read-only codebase researcher
│ ├── oracle.py # Architecture/debugging advisor
│ └── coder.py # Implementation worker
└── tools/
├── __init__.py
├── filesystem.py # File read/write/search/glob tools
└── project.py # Project detection, build, test tools
```
### File-to-Loki Mapping
| This Project | Loki Equivalent |
|---|---|
| `state.py` | Session context + todo state (implicit in Loki) |
| `graph.py` | `src/supervisor/mod.rs` (runtime orchestration) |
| `cli.py` | `src/main.rs` (CLI entry point) |
| `agents/supervisor.py` | `assets/agents/sisyphus/config.yaml` |
| `agents/explore.py` | `assets/agents/explore/config.yaml` + `tools.sh` |
| `agents/oracle.py` | `assets/agents/oracle/config.yaml` + `tools.sh` |
| `agents/coder.py` | `assets/agents/coder/config.yaml` + `tools.sh` |
| `tools/filesystem.py` | `assets/functions/tools/fs_*.sh` |
| `tools/project.py` | `assets/agents/.shared/utils.sh` + `sisyphus/tools.sh` |
## Further Reading
- [LangGraph Documentation](https://docs.langchain.com/langgraph/)
- [LangGraph Multi-Agent Tutorial](https://docs.langchain.com/langgraph/how-tos/multi-agent-systems)
- [Loki Agents Documentation](../../docs/AGENTS.md)
- [Loki Sisyphus README](../../assets/agents/sisyphus/README.md)
- [LangGraph Supervisor Library](https://github.com/langchain-ai/langgraph-supervisor-py)
@@ -0,0 +1,29 @@
[project]
name = "sisyphus-langchain"
version = "0.1.0"
description = "Loki's Sisyphus multi-agent orchestrator recreated in LangChain/LangGraph"
readme = "README.md"
requires-python = ">=3.11"
dependencies = [
"langgraph>=0.3.0",
"langchain>=0.3.0",
"langchain-openai>=0.3.0",
"langchain-anthropic>=0.3.0",
"langchain-core>=0.3.0",
]
[project.optional-dependencies]
dev = [
"pytest>=8.0",
"ruff>=0.8.0",
]
server = [
"langgraph-api>=0.1.0",
]
[project.scripts]
sisyphus = "sisyphus_langchain.cli:main"
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
@@ -0,0 +1,5 @@
"""Sisyphus multi-agent orchestrator — a LangGraph recreation of Loki's Sisyphus agent."""
from sisyphus_langchain.graph import build_graph
__all__ = ["build_graph"]
@@ -0,0 +1 @@
"""Agent node definitions for the Sisyphus orchestrator."""
@@ -0,0 +1,145 @@
"""
Coder agent node — the implementation worker.
Loki equivalent: assets/agents/coder/config.yaml + tools.sh
In Loki, the coder is the ONLY agent that modifies files. It:
- Receives a structured prompt from sisyphus with code patterns to follow
- Writes files via the write_file tool (never pastes code in chat)
- Verifies builds after every change
- Signals CODER_COMPLETE or CODER_FAILED
In LangGraph, coder is a node with write-capable tools (read_file, write_file,
search_content, execute_command, verify_build). The supervisor formats a
structured delegation prompt (Goal / Reference Files / Code Patterns /
Conventions / Constraints) and routes to this node.
Key Loki→LangGraph mapping:
- Loki's "Coder Delegation Format" → the supervisor builds this as a
HumanMessage before routing to the coder node.
- Loki's auto_continue (up to 15) → the supervisor can re-route to coder
if verification fails, up to iteration_count limits.
- Loki's todo system for multi-file changes → the coder updates
state["todos"] as it completes each file.
"""
from __future__ import annotations
from langchain_core.messages import SystemMessage
from langchain_openai import ChatOpenAI
from sisyphus_langchain.state import SisyphusState
from sisyphus_langchain.tools.filesystem import (
read_file,
search_content,
search_files,
write_file,
)
from sisyphus_langchain.tools.project import (
execute_command,
run_tests,
verify_build,
)
# ---------------------------------------------------------------------------
# System prompt — faithfully mirrors coder/config.yaml
# ---------------------------------------------------------------------------
CODER_SYSTEM_PROMPT = """\
You are a senior engineer. You write code that works on the first try.
## Your Mission
Given an implementation task:
1. Check for context provided in the conversation (patterns, conventions, reference files).
2. Fill gaps only — read files NOT already covered in context.
3. Write the code using the write_file tool (NEVER output code in chat).
4. Verify it compiles/builds using verify_build.
5. Provide a summary of what you implemented.
## Using Provided Context (IMPORTANT)
Your prompt often contains prior findings from the explore agent: file paths,
code patterns, and conventions.
**If context is provided:**
1. Use it as your primary reference. Don't re-read files already summarized.
2. Follow the code patterns shown — snippets in context ARE the style guide.
3. Read referenced files ONLY IF you need more detail (full signatures, imports).
4. If context includes a "Conventions" section, follow it exactly.
**If context is NOT provided or is too vague:**
Fall back to self-exploration: search for similar files, read 1-2 examples,
match their style.
## Writing Code
CRITICAL: Write code using the write_file tool. NEVER paste code in chat.
## Pattern Matching
Before writing ANY file:
1. Find a similar existing file.
2. Match its style: imports, naming, structure.
3. Follow the same patterns exactly.
## Verification
After writing files:
1. Run verify_build to check compilation.
2. If it fails, fix the error (minimal change).
3. Don't move on until build passes.
## Rules
1. Write code via tools — never output code to chat.
2. Follow patterns — read existing files first.
3. Verify builds — don't finish without checking.
4. Minimal fixes — if build fails, fix precisely.
5. No refactoring — only implement what's asked.
"""
# Full tool set — coder gets write access and command execution
CODER_TOOLS = [
read_file,
write_file,
search_content,
search_files,
execute_command,
verify_build,
run_tests,
]
def create_coder_node(model_name: str = "gpt-4o", temperature: float = 0.1):
"""
Factory that returns a coder node function.
Coder needs a capable model because it writes production code. In Loki,
coder uses the same model as the parent by default.
Args:
model_name: Model identifier.
temperature: LLM temperature (Loki coder uses 0.1 for consistency).
"""
llm = ChatOpenAI(model=model_name, temperature=temperature).bind_tools(CODER_TOOLS)
def coder_node(state: SisyphusState) -> dict:
"""
LangGraph node: run the coder agent.
Reads conversation history (including the supervisor's structured
delegation prompt), invokes the LLM with write-capable tools,
and returns the result.
"""
response = llm.invoke(
[SystemMessage(content=CODER_SYSTEM_PROMPT)] + state["messages"]
)
return {
"messages": [response],
"agent_outputs": {
**state.get("agent_outputs", {}),
"coder": response.content,
},
}
return coder_node
@@ -0,0 +1,110 @@
"""
Explore agent node — the read-only codebase researcher.
Loki equivalent: assets/agents/explore/config.yaml + tools.sh
In Loki, the explore agent is spawned via `agent__spawn --agent explore --prompt "..."`
and runs as an isolated subprocess with its own session. It ends with
"EXPLORE_COMPLETE" so the parent knows it's finished.
In LangGraph, the explore agent is a *node* in the graph. The supervisor routes
to it via `Command(goto="explore")`. It reads the latest message (the supervisor's
delegation prompt), calls the LLM with read-only tools, and writes its findings
back to the shared message list. The graph edge then returns control to the
supervisor.
Key differences from Loki:
- No isolated session — shares the graph's message list (but has its own
system prompt and tool set, just like Loki's per-agent config).
- No "EXPLORE_COMPLETE" sentinel — the graph edge handles control flow.
- No output summarization — LangGraph's state handles context management.
"""
from __future__ import annotations
from langchain_core.messages import SystemMessage
from langchain_openai import ChatOpenAI
from sisyphus_langchain.state import SisyphusState
from sisyphus_langchain.tools.filesystem import (
list_directory,
read_file,
search_content,
search_files,
)
# ---------------------------------------------------------------------------
# System prompt — faithfully mirrors explore/config.yaml
# ---------------------------------------------------------------------------
EXPLORE_SYSTEM_PROMPT = """\
You are a codebase explorer. Your job: Search, find, report. Nothing else.
## Your Mission
Given a search task, you:
1. Search for relevant files and patterns
2. Read key files to understand structure
3. Report findings concisely
## Strategy
1. **Find first, read second** — Never read a file without knowing why.
2. **Use search_content to locate** — find exactly where things are defined.
3. **Use search_files to discover** — find files by name pattern.
4. **Read targeted sections** — use offset and limit to read only relevant lines.
5. **Never read entire large files** — if a file is 500+ lines, read the relevant section only.
## Output Format
Always end your response with a structured findings summary:
FINDINGS:
- [Key finding 1]
- [Key finding 2]
- Relevant files: [list of paths]
## Rules
1. Be fast — don't read every file, read representative ones.
2. Be focused — answer the specific question asked.
3. Be concise — report findings, not your process.
4. Never modify files — you are read-only.
5. Limit reads — max 5 file reads per exploration.
"""
# Read-only tools — mirrors explore's tool set (no write_file, no execute_command)
EXPLORE_TOOLS = [read_file, search_content, search_files, list_directory]
def create_explore_node(model_name: str = "gpt-4o-mini", temperature: float = 0.1):
"""
Factory that returns an explore node function bound to a specific model.
In Loki, the model is set per-agent in config.yaml. Here we parameterize it
so you can use a cheap model for exploration (cost optimization).
Args:
model_name: OpenAI model identifier.
temperature: LLM temperature (Loki explore uses 0.1).
"""
llm = ChatOpenAI(model=model_name, temperature=temperature).bind_tools(EXPLORE_TOOLS)
def explore_node(state: SisyphusState) -> dict:
"""
LangGraph node: run the explore agent.
Reads the conversation history, applies the explore system prompt,
invokes the LLM with read-only tools, and returns the response.
"""
response = llm.invoke(
[SystemMessage(content=EXPLORE_SYSTEM_PROMPT)] + state["messages"]
)
return {
"messages": [response],
"agent_outputs": {
**state.get("agent_outputs", {}),
"explore": response.content,
},
}
return explore_node
@@ -0,0 +1,124 @@
"""
Oracle agent node — the high-IQ architecture and debugging advisor.
Loki equivalent: assets/agents/oracle/config.yaml + tools.sh
In Loki, the oracle is a READ-ONLY advisor spawned for:
- Architecture decisions and multi-system tradeoffs
- Complex debugging (after 2+ failed fix attempts)
- Code/design review
- Risk assessment
It uses temperature 0.2 (slightly higher than explore/coder for more creative
reasoning) and ends with "ORACLE_COMPLETE".
In LangGraph, oracle is a node that receives the full message history, reasons
about the problem, and writes structured advice back. It has read-only tools
only — it never modifies files.
Key Loki→LangGraph mapping:
- Loki oracle triggers (the "MUST spawn oracle when..." rules in sisyphus)
become routing conditions in the supervisor node.
- Oracle's structured output format (Analysis/Recommendation/Reasoning/Risks)
is enforced via the system prompt, same as in Loki.
"""
from __future__ import annotations
from langchain_core.messages import SystemMessage
from langchain_openai import ChatOpenAI
from sisyphus_langchain.state import SisyphusState
from sisyphus_langchain.tools.filesystem import (
list_directory,
read_file,
search_content,
search_files,
)
# ---------------------------------------------------------------------------
# System prompt — faithfully mirrors oracle/config.yaml
# ---------------------------------------------------------------------------
ORACLE_SYSTEM_PROMPT = """\
You are Oracle — a senior architect and debugger consulted for complex decisions.
## Your Role
You are READ-ONLY. You analyze, advise, and recommend. You do NOT implement.
## When You're Consulted
1. **Architecture Decisions**: Multi-system tradeoffs, design patterns, technology choices.
2. **Complex Debugging**: After 2+ failed fix attempts, deep analysis needed.
3. **Code Review**: Evaluating proposed designs or implementations.
4. **Risk Assessment**: Security, performance, or reliability concerns.
## Your Process
1. **Understand**: Read relevant code, understand the full context.
2. **Analyze**: Consider multiple angles and tradeoffs.
3. **Recommend**: Provide clear, actionable advice.
4. **Justify**: Explain your reasoning.
## Output Format
Structure your response as:
## Analysis
[Your understanding of the situation]
## Recommendation
[Clear, specific advice]
## Reasoning
[Why this is the right approach]
## Risks/Considerations
[What to watch out for]
## Rules
1. Never modify files — you advise, others implement.
2. Be thorough — read all relevant context before advising.
3. Be specific — general advice isn't helpful.
4. Consider tradeoffs — there are rarely perfect solutions.
5. Stay focused — answer the specific question asked.
"""
# Read-only tools — same set as explore (oracle never writes)
ORACLE_TOOLS = [read_file, search_content, search_files, list_directory]
def create_oracle_node(model_name: str = "gpt-4o", temperature: float = 0.2):
"""
Factory that returns an oracle node function.
Oracle uses a more expensive model than explore because it needs deeper
reasoning. In Loki, the model is inherited from the global config unless
overridden in oracle/config.yaml.
Args:
model_name: Model identifier (use a strong reasoning model).
temperature: LLM temperature (Loki oracle uses 0.2).
"""
llm = ChatOpenAI(model=model_name, temperature=temperature).bind_tools(ORACLE_TOOLS)
def oracle_node(state: SisyphusState) -> dict:
"""
LangGraph node: run the oracle agent.
Reads conversation history, applies the oracle system prompt,
invokes the LLM, and returns structured advice.
"""
response = llm.invoke(
[SystemMessage(content=ORACLE_SYSTEM_PROMPT)] + state["messages"]
)
return {
"messages": [response],
"agent_outputs": {
**state.get("agent_outputs", {}),
"oracle": response.content,
},
}
return oracle_node
@@ -0,0 +1,227 @@
"""
Sisyphus supervisor node — the orchestrator that classifies intent and routes.
Loki equivalent: assets/agents/sisyphus/config.yaml
This is the brain of the system. In Loki, Sisyphus is the top-level agent that:
1. Classifies every incoming request (trivial / exploration / implementation /
architecture / ambiguous)
2. Routes to the appropriate sub-agent (explore, coder, oracle)
3. Manages the todo list for multi-step tasks
4. Verifies results and decides when the task is complete
In LangGraph, the supervisor is a node that returns `Command(goto="agent_name")`
to route control. This replaces Loki's `agent__spawn` + `agent__collect` pattern
with a declarative graph edge.
Key Loki→LangGraph mapping:
- agent__spawn --agent explore → Command(goto="explore")
- agent__spawn --agent coder → Command(goto="coder")
- agent__spawn --agent oracle → Command(goto="oracle")
- agent__check / agent__collect → (implicit: graph edges return to supervisor)
- todo__init / todo__add → state["todos"] updates
- user__ask / user__confirm → interrupt() for human-in-the-loop
Parallel execution note:
Loki can spawn multiple explore agents in parallel. In LangGraph, you'd use
the Send() API for dynamic fan-out. For simplicity, this implementation uses
sequential routing. See the README for how to add parallel fan-out.
"""
from __future__ import annotations
from typing import Literal
from langchain_core.messages import SystemMessage
from langchain_openai import ChatOpenAI
from langgraph.types import Command
from pydantic import BaseModel, Field
from sisyphus_langchain.state import SisyphusState
# ---------------------------------------------------------------------------
# Maximum iterations before forcing completion (safety valve)
# Mirrors Loki's max_auto_continues: 25
# ---------------------------------------------------------------------------
MAX_ITERATIONS = 15
# ---------------------------------------------------------------------------
# Structured output schema for the supervisor's routing decision.
#
# In Loki, the supervisor is an LLM that produces free-text and calls tools
# like agent__spawn. In LangGraph, we use structured output to force the
# LLM into a typed routing decision — more reliable than parsing free text.
# ---------------------------------------------------------------------------
class RoutingDecision(BaseModel):
"""The supervisor's decision about what to do next."""
intent: Literal["trivial", "exploration", "implementation", "architecture", "ambiguous"] = Field(
description="Classified intent of the user's request."
)
next_agent: Literal["explore", "oracle", "coder", "FINISH"] = Field(
description=(
"Which agent to route to. 'explore' for research/discovery, "
"'oracle' for architecture/design/debugging advice, "
"'coder' for implementation, 'FINISH' if the task is complete."
)
)
delegation_notes: str = Field(
description=(
"Brief instructions for the target agent: what to look for (explore), "
"what to analyze (oracle), or what to implement (coder). "
"For FINISH, summarize what was accomplished."
)
)
# ---------------------------------------------------------------------------
# Supervisor system prompt — faithfully mirrors sisyphus/config.yaml
# ---------------------------------------------------------------------------
SUPERVISOR_SYSTEM_PROMPT = """\
You are Sisyphus — an orchestrator that drives coding tasks to completion.
Your job: Classify → Delegate → Verify → Complete.
## Intent Classification (BEFORE every action)
| Type | Signal | Action |
|-----------------|-----------------------------------------------------|----------------------|
| trivial | Single file, known location, typo fix | Route to FINISH |
| exploration | "Find X", "Where is Y", "List all Z" | Route to explore |
| implementation | "Add feature", "Fix bug", "Write code" | Route to coder |
| architecture | See oracle triggers below | Route to oracle |
| ambiguous | Unclear scope, multiple interpretations | Route to FINISH with a clarifying question |
## Oracle Triggers (MUST route to oracle when you see these)
Route to oracle ANY time the user asks about:
- "How should I..." / "What's the best way to..." — design/approach questions
- "Why does X keep..." / "What's wrong with..." — complex debugging
- "Should I use X or Y?" — technology or pattern choices
- "How should this be structured?" — architecture
- "Review this" / "What do you think of..." — code/design review
- Tradeoff questions, multi-component questions, vague/open-ended questions
## Agent Specializations
| Agent | Use For |
|---------|-----------------------------------------------|
| explore | Find patterns, understand code, search |
| coder | Write/edit files, implement features |
| oracle | Architecture decisions, complex debugging |
## Workflow Patterns
### Implementation task: explore → coder
1. Route to explore to find existing patterns and conventions.
2. Review explore findings.
3. Route to coder with a structured prompt including the explore findings.
4. Verify the coder's output (check for CODER_COMPLETE or CODER_FAILED).
### Architecture question: explore + oracle
1. Route to explore to find relevant code.
2. Route to oracle with the explore findings for analysis.
### Simple question: oracle directly
For pure design/architecture questions, route to oracle directly.
## Rules
1. Always classify before acting.
2. You are a coordinator, not an implementer.
3. Route to oracle for ANY design/architecture question.
4. When routing to coder, include code patterns from explore findings.
5. Route to FINISH when the task is fully addressed.
## Current State
Iteration: {iteration_count}/{max_iterations}
Previous agent outputs: {agent_outputs}
"""
def create_supervisor_node(model_name: str = "gpt-4o", temperature: float = 0.1):
"""
Factory that returns a supervisor node function.
The supervisor uses a capable model for accurate routing.
Args:
model_name: Model identifier.
temperature: LLM temperature (low for consistent routing).
"""
llm = ChatOpenAI(model=model_name, temperature=temperature).with_structured_output(
RoutingDecision
)
def supervisor_node(
state: SisyphusState,
) -> Command[Literal["explore", "oracle", "coder", "__end__"]]:
"""
LangGraph node: the Sisyphus supervisor.
Classifies the user's intent, decides which agent to route to,
and returns a Command that directs graph execution.
"""
iteration = state.get("iteration_count", 0)
# Safety valve — prevent infinite loops
if iteration >= MAX_ITERATIONS:
return Command(
goto="__end__",
update={
"final_output": "Reached maximum iterations. Here's what was accomplished:\n"
+ "\n".join(
f"- {k}: {v[:200]}" for k, v in state.get("agent_outputs", {}).items()
),
},
)
# Format the system prompt with current state
prompt = SUPERVISOR_SYSTEM_PROMPT.format(
iteration_count=iteration,
max_iterations=MAX_ITERATIONS,
agent_outputs=_summarize_outputs(state.get("agent_outputs", {})),
)
# Invoke the LLM to get a structured routing decision
decision: RoutingDecision = llm.invoke(
[SystemMessage(content=prompt)] + state["messages"]
)
# Route to FINISH
if decision.next_agent == "FINISH":
return Command(
goto="__end__",
update={
"intent": decision.intent,
"next_agent": "FINISH",
"final_output": decision.delegation_notes,
},
)
# Route to a worker agent
return Command(
goto=decision.next_agent,
update={
"intent": decision.intent,
"next_agent": decision.next_agent,
"iteration_count": iteration + 1,
},
)
return supervisor_node
def _summarize_outputs(outputs: dict[str, str]) -> str:
"""Summarize agent outputs for the supervisor's context window."""
if not outputs:
return "(none yet)"
parts = []
for agent, output in outputs.items():
# Truncate long outputs to keep supervisor context manageable
# This mirrors Loki's summarization_threshold behavior
if len(output) > 2000:
output = output[:2000] + "... (truncated)"
parts.append(f"[{agent}]: {output}")
return "\n\n".join(parts)
@@ -0,0 +1,155 @@
"""
CLI entry point for the Sisyphus LangChain agent.
This mirrors Loki's `loki --agent sisyphus` entry point.
In Loki:
loki --agent sisyphus
# Starts a REPL with the sisyphus agent loaded
In this LangChain version:
python -m sisyphus_langchain.cli
# or: sisyphus (if installed via pip)
Usage:
# Interactive REPL mode
sisyphus
# One-shot query
sisyphus "Add a health check endpoint to the API"
# With custom models
sisyphus --supervisor-model gpt-4o --explore-model gpt-4o-mini "Find auth patterns"
Environment variables:
OPENAI_API_KEY — Required for OpenAI models
ANTHROPIC_API_KEY — Required if using Anthropic models
"""
from __future__ import annotations
import argparse
import sys
import uuid
from langchain_core.messages import HumanMessage
from sisyphus_langchain.graph import build_graph
def run_query(graph, query: str, thread_id: str) -> str:
"""
Run a single query through the Sisyphus graph.
Args:
graph: Compiled LangGraph.
query: User's natural language request.
thread_id: Session identifier for checkpointing.
Returns:
The final output string.
"""
result = graph.invoke(
{
"messages": [HumanMessage(content=query)],
"intent": "ambiguous",
"next_agent": "",
"iteration_count": 0,
"todos": [],
"agent_outputs": {},
"final_output": "",
"project_dir": ".",
},
config={
"configurable": {"thread_id": thread_id},
"recursion_limit": 50,
},
)
return result.get("final_output", "(no output)")
def repl(graph, thread_id: str) -> None:
"""
Interactive REPL loop — mirrors Loki's REPL mode.
Maintains conversation across turns via the thread_id (checkpointer).
"""
print("Sisyphus (LangChain) — type 'quit' to exit")
print("=" * 50)
while True:
try:
query = input("\n> ").strip()
except (EOFError, KeyboardInterrupt):
print("\nBye.")
break
if not query:
continue
if query.lower() in ("quit", "exit", "q"):
print("Bye.")
break
try:
output = run_query(graph, query, thread_id)
print(f"\n{output}")
except Exception as e:
print(f"\nError: {e}")
def main() -> None:
"""CLI entry point."""
parser = argparse.ArgumentParser(
description="Sisyphus — multi-agent coding orchestrator (LangChain edition)"
)
parser.add_argument(
"query",
nargs="?",
help="One-shot query (omit for REPL mode)",
)
parser.add_argument(
"--supervisor-model",
default="gpt-4o",
help="Model for the supervisor (default: gpt-4o)",
)
parser.add_argument(
"--explore-model",
default="gpt-4o-mini",
help="Model for the explore agent (default: gpt-4o-mini)",
)
parser.add_argument(
"--oracle-model",
default="gpt-4o",
help="Model for the oracle agent (default: gpt-4o)",
)
parser.add_argument(
"--coder-model",
default="gpt-4o",
help="Model for the coder agent (default: gpt-4o)",
)
parser.add_argument(
"--thread-id",
default=None,
help="Session thread ID for persistence (auto-generated if omitted)",
)
args = parser.parse_args()
graph = build_graph(
supervisor_model=args.supervisor_model,
explore_model=args.explore_model,
oracle_model=args.oracle_model,
coder_model=args.coder_model,
)
thread_id = args.thread_id or f"sisyphus-{uuid.uuid4().hex[:8]}"
if args.query:
output = run_query(graph, args.query, thread_id)
print(output)
else:
repl(graph, thread_id)
if __name__ == "__main__":
main()
@@ -0,0 +1,115 @@
"""
Graph assembly — wires together the supervisor and worker nodes.
This is the LangGraph equivalent of Loki's runtime agent execution engine
(src/supervisor/mod.rs + src/config/request_context.rs).
In Loki, the runtime:
1. Loads the agent config (config.yaml)
2. Compiles tools (tools.sh → binary)
3. Starts a chat loop: user → LLM → tool calls → LLM → ...
4. For orchestrators with can_spawn_agents: true, the supervisor module
manages child agent lifecycle (spawn, check, collect, cancel).
In LangGraph, all of this is declarative:
1. Define nodes (supervisor, explore, oracle, coder)
2. Define edges (workers always return to supervisor)
3. Compile the graph (with optional checkpointer for persistence)
4. Invoke with initial state
The graph topology:
┌─────────────────────────────────────────────┐
│ SUPERVISOR │
│ (classifies intent, routes to workers) │
└─────┬──────────┬──────────┬─────────────────┘
│ │ │
▼ ▼ ▼
┌────────┐ ┌────────┐ ┌────────┐
│EXPLORE │ │ ORACLE │ │ CODER │
│(search)│ │(advise)│ │(build) │
└───┬────┘ └───┬────┘ └───┬────┘
│ │ │
└──────────┼──────────┘
(back to supervisor)
Every worker returns to the supervisor. The supervisor decides what to do next:
route to another worker, or end the graph.
"""
from __future__ import annotations
from langgraph.checkpoint.memory import MemorySaver
from langgraph.graph import END, START, StateGraph
from sisyphus_langchain.agents.coder import create_coder_node
from sisyphus_langchain.agents.explore import create_explore_node
from sisyphus_langchain.agents.oracle import create_oracle_node
from sisyphus_langchain.agents.supervisor import create_supervisor_node
from sisyphus_langchain.state import SisyphusState
def build_graph(
*,
supervisor_model: str = "gpt-4o",
explore_model: str = "gpt-4o-mini",
oracle_model: str = "gpt-4o",
coder_model: str = "gpt-4o",
use_checkpointer: bool = True,
):
"""
Build and compile the Sisyphus LangGraph.
This is the main entry point for creating the agent system. It wires
together all nodes and edges, optionally adds a checkpointer for
persistence, and returns a compiled graph ready to invoke.
Args:
supervisor_model: Model for the routing supervisor.
explore_model: Model for the explore agent (can be cheaper).
oracle_model: Model for the oracle agent (should be strong).
coder_model: Model for the coder agent.
use_checkpointer: Whether to add MemorySaver for session persistence.
Returns:
A compiled LangGraph ready to .invoke() or .stream().
Model cost optimization (mirrors Loki's per-agent model config):
- supervisor: expensive (accurate routing is critical)
- explore: cheap (just searching, not reasoning deeply)
- oracle: expensive (deep reasoning, architecture advice)
- coder: expensive (writing correct code matters)
"""
# Create the graph builder with our typed state
builder = StateGraph(SisyphusState)
# ── Register nodes ─────────────────────────────────────────────────
# Each node is a function that takes state and returns state updates.
# This mirrors Loki's agent registration (agents are discovered by
# their config.yaml in the agents/ directory).
builder.add_node("supervisor", create_supervisor_node(supervisor_model))
builder.add_node("explore", create_explore_node(explore_model))
builder.add_node("oracle", create_oracle_node(oracle_model))
builder.add_node("coder", create_coder_node(coder_model))
# ── Define edges ───────────────────────────────────────────────────
# Entry point: every invocation starts at the supervisor
builder.add_edge(START, "supervisor")
# Workers always return to supervisor (the hub-and-spoke pattern).
# In Loki, this is implicit: agent__collect returns output to the parent,
# and the parent (sisyphus) decides what to do next.
builder.add_edge("explore", "supervisor")
builder.add_edge("oracle", "supervisor")
builder.add_edge("coder", "supervisor")
# The supervisor node itself uses Command(goto=...) to route,
# so we don't need add_conditional_edges — the Command API
# handles dynamic routing internally.
# ── Compile ────────────────────────────────────────────────────────
checkpointer = MemorySaver() if use_checkpointer else None
graph = builder.compile(checkpointer=checkpointer)
return graph
@@ -0,0 +1,100 @@
"""
Shared state schema for the Sisyphus orchestrator graph.
In LangGraph, state is the single source of truth that flows through every node.
This is analogous to Loki's per-agent session context, but unified into one typed
dictionary that the entire graph shares.
Loki Concept Mapping:
- Loki session context → SisyphusState (TypedDict)
- Loki todo__init / todo__add → SisyphusState.todos list
- Loki agent__spawn outputs → SisyphusState.agent_outputs dict
- Loki intent classification → SisyphusState.intent field
"""
from __future__ import annotations
from dataclasses import dataclass, field
from typing import Annotated, Literal
from langchain_core.messages import BaseMessage
from langgraph.graph.message import add_messages
from typing_extensions import TypedDict
# ---------------------------------------------------------------------------
# Intent types — mirrors Loki's Sisyphus classification table
# ---------------------------------------------------------------------------
IntentType = Literal[
"trivial", # Single file, known location, typo fix → handle yourself
"exploration", # "Find X", "Where is Y" → spawn explore
"implementation", # "Add feature", "Fix bug" → spawn coder
"architecture", # Design questions, oracle triggers → spawn oracle
"ambiguous", # Unclear scope → ask user
]
# ---------------------------------------------------------------------------
# Todo item — mirrors Loki's built-in todo system
# ---------------------------------------------------------------------------
@dataclass
class TodoItem:
"""A single task in the orchestrator's todo list."""
id: int
task: str
done: bool = False
def _merge_todos(existing: list[TodoItem], new: list[TodoItem]) -> list[TodoItem]:
"""
Reducer for the todos field.
LangGraph requires a reducer for any state field that can be written by
multiple nodes. This merges by id: if a todo with the same id already
exists, the incoming version wins (allows marking done).
"""
by_id = {t.id: t for t in existing}
for t in new:
by_id[t.id] = t
return list(by_id.values())
# ---------------------------------------------------------------------------
# Core graph state
# ---------------------------------------------------------------------------
class SisyphusState(TypedDict):
"""
The shared state that flows through every node in the Sisyphus graph.
Annotated fields use *reducers* — functions that merge concurrent writes.
Without reducers, parallel node outputs would overwrite each other.
"""
# Conversation history — the `add_messages` reducer appends new messages
# instead of replacing the list. This is critical: every node adds its
# response here, and downstream nodes see the full history.
#
# Loki equivalent: each agent's chat session accumulates messages the same
# way, but messages are scoped per-agent. In LangGraph the shared message
# list IS the inter-agent communication channel.
messages: Annotated[list[BaseMessage], add_messages]
# Classified intent for the current request
intent: IntentType
# Which agent the supervisor routed to last
next_agent: str
# Iteration counter — safety valve analogous to Loki's max_auto_continues
iteration_count: int
# Todo list for multi-step tracking (mirrors Loki's todo__* tools)
todos: Annotated[list[TodoItem], _merge_todos]
# Accumulated outputs from sub-agent nodes, keyed by agent name.
# The supervisor reads these to decide what to do next.
agent_outputs: dict[str, str]
# Final synthesized answer to return to the user
final_output: str
# The working directory / project path (mirrors Loki's project_dir variable)
project_dir: str
@@ -0,0 +1 @@
"""Tool definitions for Sisyphus agents."""
@@ -0,0 +1,175 @@
"""
Filesystem tools for Sisyphus agents.
These are the LangChain equivalents of Loki's global tools:
- fs_read.sh → read_file
- fs_grep.sh → search_content
- fs_glob.sh → search_files
- fs_ls.sh → list_directory
- fs_write.sh → write_file
- fs_patch.sh → (omitted — write_file covers full rewrites)
Loki Concept Mapping:
Loki tools are bash scripts with @cmd annotations that Loki's compiler
turns into function-calling declarations. In LangChain, we use the @tool
decorator which serves the same purpose: it generates the JSON schema
that the LLM sees, and wraps the Python function for execution.
"""
from __future__ import annotations
import fnmatch
import os
import re
import subprocess
from langchain_core.tools import tool
@tool
def read_file(path: str, offset: int = 1, limit: int = 200) -> str:
"""Read a file's contents with optional line range.
Args:
path: Path to the file (absolute or relative to cwd).
offset: 1-based line number to start from.
limit: Maximum number of lines to return.
"""
path = os.path.expanduser(path)
if not os.path.isfile(path):
return f"Error: file not found: {path}"
try:
with open(path, "r", encoding="utf-8", errors="replace") as f:
lines = f.readlines()
except Exception as e:
return f"Error reading {path}: {e}"
total = len(lines)
start = max(0, offset - 1)
end = min(total, start + limit)
selected = lines[start:end]
result = f"File: {path} (lines {start + 1}-{end} of {total})\n\n"
for i, line in enumerate(selected, start=start + 1):
result += f"{i}: {line}"
if end < total:
result += f"\n... truncated ({total} total lines)"
return result
@tool
def write_file(path: str, content: str) -> str:
"""Write complete contents to a file, creating parent directories as needed.
Args:
path: Path for the file.
content: Complete file contents to write.
"""
path = os.path.expanduser(path)
os.makedirs(os.path.dirname(path) or ".", exist_ok=True)
try:
with open(path, "w", encoding="utf-8") as f:
f.write(content)
return f"Wrote: {path}"
except Exception as e:
return f"Error writing {path}: {e}"
@tool
def search_content(pattern: str, directory: str = ".", file_type: str = "") -> str:
"""Search for a text/regex pattern in files under a directory.
Args:
pattern: Text or regex pattern to search for.
directory: Root directory to search in.
file_type: Optional file extension filter (e.g. "py", "rs").
"""
directory = os.path.expanduser(directory)
cmd = ["grep", "-rn"]
if file_type:
cmd += [f"--include=*.{file_type}"]
cmd += [pattern, directory]
try:
result = subprocess.run(cmd, capture_output=True, text=True, timeout=30)
lines = result.stdout.strip().splitlines()
except Exception as e:
return f"Error: {e}"
# Filter noise
noise = {"/.git/", "/node_modules/", "/target/", "/dist/", "/__pycache__/"}
filtered = [l for l in lines if not any(n in l for n in noise)][:30]
if not filtered:
return "No matches found."
return "\n".join(filtered)
@tool
def search_files(pattern: str, directory: str = ".") -> str:
"""Find files matching a glob pattern.
Args:
pattern: Glob pattern (e.g. '*.py', 'config*', '*test*').
directory: Directory to search in.
"""
directory = os.path.expanduser(directory)
noise = {".git", "node_modules", "target", "dist", "__pycache__"}
matches: list[str] = []
for root, dirs, files in os.walk(directory):
dirs[:] = [d for d in dirs if d not in noise]
for name in files:
if fnmatch.fnmatch(name, pattern):
matches.append(os.path.join(root, name))
if len(matches) >= 25:
break
if len(matches) >= 25:
break
if not matches:
return "No files found."
return "\n".join(matches)
@tool
def list_directory(path: str = ".", max_depth: int = 3) -> str:
"""List directory tree structure.
Args:
path: Directory to list.
max_depth: Maximum depth to recurse.
"""
path = os.path.expanduser(path)
if not os.path.isdir(path):
return f"Error: not a directory: {path}"
noise = {".git", "node_modules", "target", "dist", "__pycache__", ".venv", "venv"}
lines: list[str] = []
def _walk(dir_path: str, prefix: str, depth: int) -> None:
if depth > max_depth:
return
try:
entries = sorted(os.listdir(dir_path))
except PermissionError:
return
dirs = [e for e in entries if os.path.isdir(os.path.join(dir_path, e)) and e not in noise]
files = [e for e in entries if os.path.isfile(os.path.join(dir_path, e))]
for f in files[:20]:
lines.append(f"{prefix}{f}")
if len(files) > 20:
lines.append(f"{prefix}... ({len(files) - 20} more files)")
for d in dirs:
lines.append(f"{prefix}{d}/")
_walk(os.path.join(dir_path, d), prefix + " ", depth + 1)
lines.append(f"{os.path.basename(path) or path}/")
_walk(path, " ", 1)
return "\n".join(lines[:200])
@@ -0,0 +1,142 @@
"""
Project detection and build/test tools.
These mirror Loki's .shared/utils.sh detect_project() heuristic and the
sisyphus/coder tools.sh run_build / run_tests / verify_build commands.
Loki Concept Mapping:
Loki uses a heuristic cascade: check for Cargo.toml → go.mod → package.json
etc., then falls back to an LLM call for unknown projects. We replicate the
heuristic portion here. The LLM fallback is omitted since the agents
themselves can reason about unknown project types.
"""
from __future__ import annotations
import json
import os
import subprocess
from langchain_core.tools import tool
# ---------------------------------------------------------------------------
# Project detection (mirrors _detect_heuristic in utils.sh)
# ---------------------------------------------------------------------------
_HEURISTICS: list[tuple[str, dict[str, str]]] = [
("Cargo.toml", {"type": "rust", "build": "cargo build", "test": "cargo test", "check": "cargo check"}),
("go.mod", {"type": "go", "build": "go build ./...", "test": "go test ./...", "check": "go vet ./..."}),
("package.json", {"type": "nodejs", "build": "npm run build", "test": "npm test", "check": "npm run lint"}),
("pyproject.toml", {"type": "python", "build": "", "test": "pytest", "check": "ruff check ."}),
("pom.xml", {"type": "java", "build": "mvn compile", "test": "mvn test", "check": "mvn verify"}),
("Makefile", {"type": "make", "build": "make build", "test": "make test", "check": "make lint"}),
]
def detect_project(directory: str) -> dict[str, str]:
"""Detect project type and return build/test commands."""
for marker, info in _HEURISTICS:
if os.path.exists(os.path.join(directory, marker)):
return info
return {"type": "unknown", "build": "", "test": "", "check": ""}
@tool
def get_project_info(directory: str = ".") -> str:
"""Detect the project type and show structure overview.
Args:
directory: Project root directory.
"""
directory = os.path.expanduser(directory)
info = detect_project(directory)
result = f"Project: {os.path.abspath(directory)}\n"
result += f"Type: {info['type']}\n"
result += f"Build: {info['build'] or '(none)'}\n"
result += f"Test: {info['test'] or '(none)'}\n"
result += f"Check: {info['check'] or '(none)'}\n"
return result
def _run_project_command(directory: str, command_key: str) -> str:
"""Run a detected project command (build/test/check)."""
directory = os.path.expanduser(directory)
info = detect_project(directory)
cmd = info.get(command_key, "")
if not cmd:
return f"No {command_key} command detected for this project."
try:
result = subprocess.run(
cmd,
shell=True,
capture_output=True,
text=True,
cwd=directory,
timeout=300,
)
output = result.stdout + result.stderr
status = "SUCCESS" if result.returncode == 0 else f"FAILED (exit {result.returncode})"
return f"Running: {cmd}\n\n{output}\n\n{command_key.upper()}: {status}"
except subprocess.TimeoutExpired:
return f"{command_key.upper()}: TIMEOUT after 300s"
except Exception as e:
return f"{command_key.upper()}: ERROR — {e}"
@tool
def run_build(directory: str = ".") -> str:
"""Run the project's build command.
Args:
directory: Project root directory.
"""
return _run_project_command(directory, "build")
@tool
def run_tests(directory: str = ".") -> str:
"""Run the project's test suite.
Args:
directory: Project root directory.
"""
return _run_project_command(directory, "test")
@tool
def verify_build(directory: str = ".") -> str:
"""Run the project's check/lint command to verify correctness.
Args:
directory: Project root directory.
"""
return _run_project_command(directory, "check")
@tool
def execute_command(command: str, directory: str = ".") -> str:
"""Execute a shell command and return its output.
Args:
command: Shell command to execute.
directory: Working directory.
"""
directory = os.path.expanduser(directory)
try:
result = subprocess.run(
command,
shell=True,
capture_output=True,
text=True,
cwd=directory,
timeout=120,
)
output = (result.stdout + result.stderr).strip()
if result.returncode != 0:
return f"Command failed (exit {result.returncode}):\n{output}"
return output or "(no output)"
except subprocess.TimeoutExpired:
return "Command timed out after 120s."
except Exception as e:
return f"Error: {e}"
+3 -4
View File
@@ -342,7 +342,7 @@ mod tests {
use bytes::Bytes;
use futures_util::stream;
use rand::Rng;
use rand::random_range;
use serde_json::json;
#[test]
@@ -392,10 +392,9 @@ mod tests {
}
fn split_chunks(text: &str) -> Vec<Vec<u8>> {
let mut rng = rand::rng();
let len = text.len();
let cut1 = rng.random_range(1..len - 1);
let cut2 = rng.random_range(cut1 + 1..len);
let cut1 = random_range(1..len - 1);
let cut2 = random_range(cut1 + 1..len);
let chunk1 = text.as_bytes()[..cut1].to_vec();
let chunk2 = text.as_bytes()[cut1..cut2].to_vec();
let chunk3 = text.as_bytes()[cut2..].to_vec();
+1 -1
View File
@@ -584,7 +584,7 @@ impl Config {
}
pub fn agent_functions_file(name: &str) -> Result<PathBuf> {
let allowed = ["tools.sh", "tools.py", "tools.js"];
let allowed = ["tools.sh", "tools.py", "tools.ts", "tools.js"];
for entry in read_dir(Self::agent_data_dir(name))? {
let entry = entry?;
+145 -48
View File
@@ -12,7 +12,7 @@ use crate::mcp::{
MCP_DESCRIBE_META_FUNCTION_NAME_PREFIX, MCP_INVOKE_META_FUNCTION_NAME_PREFIX,
MCP_SEARCH_META_FUNCTION_NAME_PREFIX,
};
use crate::parsers::{bash, python};
use crate::parsers::{bash, python, typescript};
use anyhow::{Context, Result, anyhow, bail};
use indexmap::IndexMap;
use indoc::formatdoc;
@@ -53,6 +53,7 @@ enum BinaryType<'a> {
enum Language {
Bash,
Python,
TypeScript,
Unsupported,
}
@@ -61,6 +62,7 @@ impl From<&String> for Language {
match s.to_lowercase().as_str() {
"sh" => Language::Bash,
"py" => Language::Python,
"ts" => Language::TypeScript,
_ => Language::Unsupported,
}
}
@@ -72,6 +74,7 @@ impl Language {
match self {
Language::Bash => "bash",
Language::Python => "python",
Language::TypeScript => "npx tsx",
Language::Unsupported => "sh",
}
}
@@ -80,11 +83,32 @@ impl Language {
match self {
Language::Bash => "sh",
Language::Python => "py",
Language::TypeScript => "ts",
_ => "sh",
}
}
}
fn extract_shebang_runtime(path: &Path) -> Option<String> {
let file = File::open(path).ok()?;
let reader = io::BufReader::new(file);
let first_line = io::BufRead::lines(reader).next()?.ok()?;
let shebang = first_line.strip_prefix("#!")?;
let cmd = shebang.trim();
if cmd.is_empty() {
return None;
}
if let Some(after_env) = cmd.strip_prefix("/usr/bin/env ") {
let runtime = after_env.trim();
if runtime.is_empty() {
return None;
}
Some(runtime.to_string())
} else {
Some(cmd.to_string())
}
}
pub async fn eval_tool_calls(
config: &GlobalConfig,
mut calls: Vec<ToolCall>,
@@ -473,6 +497,11 @@ impl Functions {
file_name,
tools_file_path.parent(),
),
Language::TypeScript => typescript::generate_typescript_declarations(
tool_file,
file_name,
tools_file_path.parent(),
),
Language::Unsupported => {
bail!("Unsupported tool file extension: {}", language.as_ref())
}
@@ -513,7 +542,14 @@ impl Functions {
bail!("Unsupported tool file extension: {}", language.as_ref());
}
Self::build_binaries(binary_name, language, BinaryType::Tool(agent_name))?;
let tool_path = Config::global_tools_dir().join(tool);
let custom_runtime = extract_shebang_runtime(&tool_path);
Self::build_binaries(
binary_name,
language,
BinaryType::Tool(agent_name),
custom_runtime.as_deref(),
)?;
}
Ok(())
@@ -554,8 +590,9 @@ impl Functions {
}
fn build_agent_tool_binaries(name: &str) -> Result<()> {
let tools_file = Config::agent_functions_file(name)?;
let language = Language::from(
&Config::agent_functions_file(name)?
&tools_file
.extension()
.and_then(OsStr::to_str)
.map(|s| s.to_lowercase())
@@ -568,7 +605,8 @@ impl Functions {
bail!("Unsupported tool file extension: {}", language.as_ref());
}
Self::build_binaries(name, language, BinaryType::Agent)
let custom_runtime = extract_shebang_runtime(&tools_file);
Self::build_binaries(name, language, BinaryType::Agent, custom_runtime.as_deref())
}
#[cfg(windows)]
@@ -576,6 +614,7 @@ impl Functions {
binary_name: &str,
language: Language,
binary_type: BinaryType,
custom_runtime: Option<&str>,
) -> Result<()> {
use native::runtime;
let (binary_file, binary_script_file) = match binary_type {
@@ -613,6 +652,7 @@ impl Functions {
)
})?;
let content_template = unsafe { std::str::from_utf8_unchecked(&embedded_file.data) };
let to_script_path = |p: &str| -> String { p.replace('\\', "/") };
let content = match binary_type {
BinaryType::Tool(None) => {
let root_dir = Config::functions_dir();
@@ -622,8 +662,8 @@ impl Functions {
);
content_template
.replace("{function_name}", binary_name)
.replace("{root_dir}", &root_dir.to_string_lossy())
.replace("{tool_path}", &tool_path)
.replace("{root_dir}", &to_script_path(&root_dir.to_string_lossy()))
.replace("{tool_path}", &to_script_path(&tool_path))
}
BinaryType::Tool(Some(agent_name)) => {
let root_dir = Config::agent_data_dir(agent_name);
@@ -633,16 +673,19 @@ impl Functions {
);
content_template
.replace("{function_name}", binary_name)
.replace("{root_dir}", &root_dir.to_string_lossy())
.replace("{tool_path}", &tool_path)
.replace("{root_dir}", &to_script_path(&root_dir.to_string_lossy()))
.replace("{tool_path}", &to_script_path(&tool_path))
}
BinaryType::Agent => content_template
.replace("{agent_name}", binary_name)
.replace("{config_dir}", &Config::config_dir().to_string_lossy()),
.replace(
"{config_dir}",
&to_script_path(&Config::config_dir().to_string_lossy()),
),
}
.replace(
"{prompt_utils_file}",
&Config::bash_prompt_utils_file().to_string_lossy(),
&to_script_path(&Config::bash_prompt_utils_file().to_string_lossy()),
);
if binary_script_file.exists() {
fs::remove_file(&binary_script_file)?;
@@ -656,40 +699,48 @@ impl Functions {
binary_file.display()
);
let run = match language {
Language::Bash => {
let shell = runtime::bash_path().ok_or_else(|| anyhow!("Shell not found"))?;
format!("{shell} --noprofile --norc")
let run = if let Some(rt) = custom_runtime {
rt.to_string()
} else {
match language {
Language::Bash => {
let shell = runtime::bash_path().ok_or_else(|| anyhow!("Shell not found"))?;
format!("{shell} --noprofile --norc")
}
Language::Python if Path::new(".venv").exists() => {
let executable_path = env::current_dir()?
.join(".venv")
.join("Scripts")
.join("activate.bat");
let canonicalized_path = dunce::canonicalize(&executable_path)?;
format!(
"call \"{}\" && {}",
canonicalized_path.to_string_lossy(),
language.to_cmd()
)
}
Language::Python => {
let executable_path = which::which("python")
.or_else(|_| which::which("python3"))
.map_err(|_| anyhow!("Python executable not found in PATH"))?;
let canonicalized_path = dunce::canonicalize(&executable_path)?;
canonicalized_path.to_string_lossy().into_owned()
}
Language::TypeScript => {
let npx_path = which::which("npx").map_err(|_| {
anyhow!("npx executable not found in PATH (required for TypeScript tools)")
})?;
let canonicalized_path = dunce::canonicalize(&npx_path)?;
format!("{} tsx", canonicalized_path.to_string_lossy())
}
_ => bail!("Unsupported language: {}", language.as_ref()),
}
Language::Python if Path::new(".venv").exists() => {
let executable_path = env::current_dir()?
.join(".venv")
.join("Scripts")
.join("activate.bat");
let canonicalized_path = fs::canonicalize(&executable_path)?;
format!(
"call \"{}\" && {}",
canonicalized_path.to_string_lossy(),
language.to_cmd()
)
}
Language::Python => {
let executable_path = which::which("python")
.or_else(|_| which::which("python3"))
.map_err(|_| anyhow!("Python executable not found in PATH"))?;
let canonicalized_path = fs::canonicalize(&executable_path)?;
canonicalized_path.to_string_lossy().into_owned()
}
_ => bail!("Unsupported language: {}", language.as_ref()),
};
let bin_dir = binary_file
.parent()
.expect("Failed to get parent directory of binary file")
.canonicalize()?
.to_string_lossy()
.into_owned();
let wrapper_binary = binary_script_file
.canonicalize()?
.expect("Failed to get parent directory of binary file");
let canonical_bin_dir = dunce::canonicalize(bin_dir)?.to_string_lossy().into_owned();
let wrapper_binary = dunce::canonicalize(&binary_script_file)?
.to_string_lossy()
.into_owned();
let content = formatdoc!(
@@ -697,7 +748,7 @@ impl Functions {
@echo off
setlocal
set "bin_dir={bin_dir}"
set "bin_dir={canonical_bin_dir}"
{run} "{wrapper_binary}" %*"#,
);
@@ -713,6 +764,7 @@ impl Functions {
binary_name: &str,
language: Language,
binary_type: BinaryType,
custom_runtime: Option<&str>,
) -> Result<()> {
use std::os::unix::prelude::PermissionsExt;
@@ -741,7 +793,7 @@ impl Functions {
)
})?;
let content_template = unsafe { std::str::from_utf8_unchecked(&embedded_file.data) };
let content = match binary_type {
let mut content = match binary_type {
BinaryType::Tool(None) => {
let root_dir = Config::functions_dir();
let tool_path = format!(
@@ -772,13 +824,44 @@ impl Functions {
"{prompt_utils_file}",
&Config::bash_prompt_utils_file().to_string_lossy(),
);
if binary_file.exists() {
fs::remove_file(&binary_file)?;
}
let mut file = File::create(&binary_file)?;
file.write_all(content.as_bytes())?;
fs::set_permissions(&binary_file, fs::Permissions::from_mode(0o755))?;
if let Some(rt) = custom_runtime
&& let Some(newline_pos) = content.find('\n')
{
content = format!("#!/usr/bin/env {rt}{}", &content[newline_pos..]);
}
if language == Language::TypeScript {
let bin_dir = binary_file
.parent()
.expect("Failed to get parent directory of binary file");
let script_file = bin_dir.join(format!("run-{binary_name}.ts"));
if script_file.exists() {
fs::remove_file(&script_file)?;
}
let mut sf = File::create(&script_file)?;
sf.write_all(content.as_bytes())?;
fs::set_permissions(&script_file, fs::Permissions::from_mode(0o755))?;
let ts_runtime = custom_runtime.unwrap_or("tsx");
let wrapper = format!(
"#!/bin/sh\nexec {ts_runtime} \"{}\" \"$@\"\n",
script_file.display()
);
if binary_file.exists() {
fs::remove_file(&binary_file)?;
}
let mut wf = File::create(&binary_file)?;
wf.write_all(wrapper.as_bytes())?;
fs::set_permissions(&binary_file, fs::Permissions::from_mode(0o755))?;
} else {
if binary_file.exists() {
fs::remove_file(&binary_file)?;
}
let mut file = File::create(&binary_file)?;
file.write_all(content.as_bytes())?;
fs::set_permissions(&binary_file, fs::Permissions::from_mode(0o755))?;
}
Ok(())
}
@@ -1117,6 +1200,20 @@ pub fn run_llm_function(
#[cfg(windows)]
let cmd_name = polyfill_cmd_name(&cmd_name, &bin_dirs);
#[cfg(windows)]
let cmd_args = {
let mut args = cmd_args;
if let Some(json_data) = args.pop() {
let tool_data_file = temp_file("-tool-data-", ".json");
fs::write(&tool_data_file, &json_data)?;
envs.insert(
"LLM_TOOL_DATA_FILE".into(),
tool_data_file.display().to_string(),
);
}
args
};
envs.insert("CLICOLOR_FORCE".into(), "1".into());
envs.insert("FORCE_COLOR".into(), "1".into());
+236
View File
@@ -0,0 +1,236 @@
use crate::function::{FunctionDeclaration, JsonSchema};
use anyhow::{Context, Result, anyhow, bail};
use indexmap::IndexMap;
use serde_json::Value;
use tree_sitter::Node;
#[derive(Debug)]
pub(crate) struct Param {
pub name: String,
pub ty_hint: String,
pub required: bool,
pub default: Option<Value>,
pub doc_type: Option<String>,
pub doc_desc: Option<String>,
}
pub(crate) trait ScriptedLanguage {
fn ts_language(&self) -> tree_sitter::Language;
fn lang_name(&self) -> &str;
fn find_functions<'a>(&self, root: Node<'a>, src: &str) -> Vec<(Node<'a>, Node<'a>)>;
fn function_name<'a>(&self, func_node: Node<'a>, src: &'a str) -> Result<&'a str>;
fn extract_description(
&self,
wrapper_node: Node<'_>,
func_node: Node<'_>,
src: &str,
) -> Option<String>;
fn extract_params(
&self,
func_node: Node<'_>,
src: &str,
description: &str,
) -> Result<Vec<Param>>;
}
pub(crate) fn build_param(
name: &str,
mut ty: String,
mut required: bool,
default: Option<Value>,
) -> Param {
if ty.ends_with('?') {
ty.pop();
required = false;
}
Param {
name: name.to_string(),
ty_hint: ty,
required,
default,
doc_type: None,
doc_desc: None,
}
}
pub(crate) fn build_parameters_schema(params: &[Param], _description: &str) -> JsonSchema {
let mut props: IndexMap<String, JsonSchema> = IndexMap::new();
let mut req: Vec<String> = Vec::new();
for p in params {
let name = p.name.replace('-', "_");
let mut schema = JsonSchema::default();
let ty = if !p.ty_hint.is_empty() {
p.ty_hint.as_str()
} else if let Some(t) = &p.doc_type {
t.as_str()
} else {
"str"
};
if let Some(d) = &p.doc_desc
&& !d.is_empty()
{
schema.description = Some(d.clone());
}
apply_type_to_schema(ty, &mut schema);
if p.default.is_none() && p.required {
req.push(name.clone());
}
props.insert(name, schema);
}
JsonSchema {
type_value: Some("object".into()),
description: None,
properties: Some(props),
items: None,
any_of: None,
enum_value: None,
default: None,
required: if req.is_empty() { None } else { Some(req) },
}
}
pub(crate) fn apply_type_to_schema(ty: &str, s: &mut JsonSchema) {
let t = ty.trim_end_matches('?');
if let Some(rest) = t.strip_prefix("list[") {
s.type_value = Some("array".into());
let inner = rest.trim_end_matches(']');
let mut item = JsonSchema::default();
apply_type_to_schema(inner, &mut item);
if item.type_value.is_none() {
item.type_value = Some("string".into());
}
s.items = Some(Box::new(item));
return;
}
if let Some(rest) = t.strip_prefix("literal:") {
s.type_value = Some("string".into());
let vals = rest
.split('|')
.map(|x| x.trim().trim_matches('"').trim_matches('\'').to_string())
.collect::<Vec<_>>();
if !vals.is_empty() {
s.enum_value = Some(vals);
}
return;
}
s.type_value = Some(
match t {
"bool" => "boolean",
"int" => "integer",
"float" => "number",
"str" | "any" | "" => "string",
_ => "string",
}
.into(),
);
}
pub(crate) fn underscore(s: &str) -> String {
s.chars()
.map(|c| {
if c.is_ascii_alphanumeric() {
c.to_ascii_lowercase()
} else {
'_'
}
})
.collect::<String>()
.split('_')
.filter(|t| !t.is_empty())
.collect::<Vec<_>>()
.join("_")
}
pub(crate) fn node_text<'a>(node: Node<'_>, src: &'a str) -> Result<&'a str> {
node.utf8_text(src.as_bytes())
.map_err(|err| anyhow!("invalid utf-8 in source: {err}"))
}
pub(crate) fn named_child(node: Node<'_>, index: usize) -> Option<Node<'_>> {
let mut cursor = node.walk();
node.named_children(&mut cursor).nth(index)
}
pub(crate) fn generate_declarations<L: ScriptedLanguage>(
lang: &L,
src: &str,
file_name: &str,
is_tool: bool,
) -> Result<Vec<FunctionDeclaration>> {
let mut parser = tree_sitter::Parser::new();
let language = lang.ts_language();
parser.set_language(&language).with_context(|| {
format!(
"failed to initialize {} tree-sitter parser",
lang.lang_name()
)
})?;
let tree = parser
.parse(src.as_bytes(), None)
.ok_or_else(|| anyhow!("failed to parse {}: {file_name}", lang.lang_name()))?;
if tree.root_node().has_error() {
bail!(
"failed to parse {}: syntax error in {file_name}",
lang.lang_name()
);
}
let mut out = Vec::new();
for (wrapper, func) in lang.find_functions(tree.root_node(), src) {
let func_name = lang.function_name(func, src)?;
if func_name.starts_with('_') && func_name != "_instructions" {
continue;
}
if is_tool && func_name != "run" {
continue;
}
let description = lang
.extract_description(wrapper, func, src)
.unwrap_or_default();
let params = lang
.extract_params(func, src, &description)
.with_context(|| format!("in function '{func_name}' in {file_name}"))?;
let schema = build_parameters_schema(&params, &description);
let name = if is_tool && func_name == "run" {
underscore(file_name)
} else {
underscore(func_name)
};
let desc_trim = description.trim().to_string();
if desc_trim.is_empty() {
bail!("Missing or empty description on function: {func_name}");
}
out.push(FunctionDeclaration {
name,
description: desc_trim,
parameters: schema,
agent: !is_tool,
});
}
Ok(out)
}
+2
View File
@@ -1,2 +1,4 @@
pub(crate) mod bash;
pub(crate) mod common;
pub(crate) mod python;
pub(crate) mod typescript;
+680 -334
View File
File diff suppressed because it is too large Load Diff
+789
View File
@@ -0,0 +1,789 @@
use crate::function::FunctionDeclaration;
use crate::parsers::common::{self, Param, ScriptedLanguage};
use anyhow::{Context, Result, anyhow, bail};
use indexmap::IndexMap;
use serde_json::Value;
use std::fs::File;
use std::io::Read;
use std::path::Path;
use tree_sitter::Node;
pub(crate) struct TypeScriptLanguage;
impl ScriptedLanguage for TypeScriptLanguage {
fn ts_language(&self) -> tree_sitter::Language {
tree_sitter_typescript::LANGUAGE_TYPESCRIPT.into()
}
fn lang_name(&self) -> &str {
"typescript"
}
fn find_functions<'a>(&self, root: Node<'a>, _src: &str) -> Vec<(Node<'a>, Node<'a>)> {
let mut cursor = root.walk();
root.named_children(&mut cursor)
.filter_map(|stmt| match stmt.kind() {
"export_statement" => unwrap_exported_function(stmt).map(|fd| (stmt, fd)),
_ => None,
})
.collect()
}
fn function_name<'a>(&self, func_node: Node<'a>, src: &'a str) -> Result<&'a str> {
let name_node = func_node
.child_by_field_name("name")
.ok_or_else(|| anyhow!("function_declaration missing name"))?;
common::node_text(name_node, src)
}
fn extract_description(
&self,
wrapper_node: Node<'_>,
func_node: Node<'_>,
src: &str,
) -> Option<String> {
let text = jsdoc_text(wrapper_node, func_node, src)?;
let lines = clean_jsdoc_lines(text);
let mut description = Vec::new();
for line in lines {
if line.starts_with('@') {
break;
}
description.push(line);
}
let description = description.join("\n").trim().to_string();
(!description.is_empty()).then_some(description)
}
fn extract_params(
&self,
func_node: Node<'_>,
src: &str,
_description: &str,
) -> Result<Vec<Param>> {
let parameters = func_node
.child_by_field_name("parameters")
.ok_or_else(|| anyhow!("function_declaration missing parameters"))?;
let mut out = Vec::new();
let mut cursor = parameters.walk();
for param in parameters.named_children(&mut cursor) {
match param.kind() {
"required_parameter" | "optional_parameter" => {
let name = parameter_name(param, src)?;
let ty = get_arg_type(param.child_by_field_name("type"), src)?;
let required = param.kind() == "required_parameter"
&& param.child_by_field_name("value").is_none();
let default = param.child_by_field_name("value").map(|_| Value::Null);
out.push(common::build_param(name, ty, required, default));
}
"rest_parameter" => {
let line = param.start_position().row + 1;
bail!("line {line}: rest parameters (...) are not supported in tool functions")
}
"object_pattern" => {
let line = param.start_position().row + 1;
bail!(
"line {line}: destructured object parameters (e.g. '{{ a, b }}: {{ a: string }}') \
are not supported in tool functions. Use flat parameters instead (e.g. 'a: string, b: string')."
)
}
other => {
let line = param.start_position().row + 1;
bail!("line {line}: unsupported parameter type: {other}")
}
}
}
let wrapper = match func_node.parent() {
Some(parent) if parent.kind() == "export_statement" => parent,
_ => func_node,
};
if let Some(doc) = jsdoc_text(wrapper, func_node, src) {
let meta = parse_jsdoc_params(doc);
for p in &mut out {
if let Some(desc) = meta.get(&p.name)
&& !desc.is_empty()
{
p.doc_desc = Some(desc.clone());
}
}
}
Ok(out)
}
}
pub fn generate_typescript_declarations(
mut tool_file: File,
file_name: &str,
parent: Option<&Path>,
) -> Result<Vec<FunctionDeclaration>> {
let mut src = String::new();
tool_file
.read_to_string(&mut src)
.with_context(|| format!("Failed to load script at '{tool_file:?}'"))?;
let is_tool = parent
.and_then(|p| p.file_name())
.is_some_and(|n| n == "tools");
common::generate_declarations(&TypeScriptLanguage, &src, file_name, is_tool)
}
fn unwrap_exported_function(node: Node<'_>) -> Option<Node<'_>> {
node.child_by_field_name("declaration")
.filter(|child| child.kind() == "function_declaration")
.or_else(|| {
let mut cursor = node.walk();
node.named_children(&mut cursor)
.find(|child| child.kind() == "function_declaration")
})
}
fn jsdoc_text<'a>(wrapper_node: Node<'_>, func_node: Node<'_>, src: &'a str) -> Option<&'a str> {
wrapper_node
.prev_named_sibling()
.or_else(|| func_node.prev_named_sibling())
.filter(|node| node.kind() == "comment")
.and_then(|node| common::node_text(node, src).ok())
.filter(|text| text.trim_start().starts_with("/**"))
}
fn clean_jsdoc_lines(doc: &str) -> Vec<String> {
let trimmed = doc.trim();
let inner = trimmed
.strip_prefix("/**")
.unwrap_or(trimmed)
.strip_suffix("*/")
.unwrap_or(trimmed);
inner
.lines()
.map(|line| {
let line = line.trim();
let line = line.strip_prefix('*').unwrap_or(line).trim_start();
line.to_string()
})
.collect()
}
fn parse_jsdoc_params(doc: &str) -> IndexMap<String, String> {
let mut out = IndexMap::new();
for line in clean_jsdoc_lines(doc) {
let Some(rest) = line.strip_prefix("@param") else {
continue;
};
let mut rest = rest.trim();
if rest.starts_with('{')
&& let Some(end) = rest.find('}')
{
rest = rest[end + 1..].trim_start();
}
if rest.is_empty() {
continue;
}
let name_end = rest.find(char::is_whitespace).unwrap_or(rest.len());
let mut name = rest[..name_end].trim();
if let Some(stripped) = name.strip_suffix('?') {
name = stripped;
}
if name.is_empty() {
continue;
}
let mut desc = rest[name_end..].trim();
if let Some(stripped) = desc.strip_prefix('-') {
desc = stripped.trim_start();
}
out.insert(name.to_string(), desc.to_string());
}
out
}
fn parameter_name<'a>(node: Node<'_>, src: &'a str) -> Result<&'a str> {
if let Some(name) = node.child_by_field_name("name") {
return match name.kind() {
"identifier" => common::node_text(name, src),
"rest_pattern" => {
let line = node.start_position().row + 1;
bail!("line {line}: rest parameters (...) are not supported in tool functions")
}
"object_pattern" | "array_pattern" => {
let line = node.start_position().row + 1;
bail!(
"line {line}: destructured parameters are not supported in tool functions. \
Use flat parameters instead (e.g. 'a: string, b: string')."
)
}
other => {
let line = node.start_position().row + 1;
bail!("line {line}: unsupported parameter type: {other}")
}
};
}
let pattern = node
.child_by_field_name("pattern")
.ok_or_else(|| anyhow!("parameter missing pattern"))?;
match pattern.kind() {
"identifier" => common::node_text(pattern, src),
"rest_pattern" => {
let line = node.start_position().row + 1;
bail!("line {line}: rest parameters (...) are not supported in tool functions")
}
"object_pattern" | "array_pattern" => {
let line = node.start_position().row + 1;
bail!(
"line {line}: destructured parameters are not supported in tool functions. \
Use flat parameters instead (e.g. 'a: string, b: string')."
)
}
other => {
let line = node.start_position().row + 1;
bail!("line {line}: unsupported parameter type: {other}")
}
}
}
fn get_arg_type(annotation: Option<Node<'_>>, src: &str) -> Result<String> {
let Some(annotation) = annotation else {
return Ok(String::new());
};
match annotation.kind() {
"type_annotation" | "type" => get_arg_type(common::named_child(annotation, 0), src),
"predefined_type" => Ok(match common::node_text(annotation, src)? {
"string" => "str",
"number" => "float",
"boolean" => "bool",
"any" | "unknown" | "void" | "undefined" => "any",
_ => "any",
}
.to_string()),
"type_identifier" | "nested_type_identifier" => Ok("any".to_string()),
"generic_type" => {
let name = annotation
.child_by_field_name("name")
.ok_or_else(|| anyhow!("generic_type missing name"))?;
let type_name = common::node_text(name, src)?;
let type_args = annotation
.child_by_field_name("type_arguments")
.ok_or_else(|| anyhow!("generic_type missing type arguments"))?;
let inner = common::named_child(type_args, 0)
.ok_or_else(|| anyhow!("generic_type missing inner type"))?;
match type_name {
"Array" => Ok(format!("list[{}]", get_arg_type(Some(inner), src)?)),
_ => Ok("any".to_string()),
}
}
"array_type" => {
let inner = common::named_child(annotation, 0)
.ok_or_else(|| anyhow!("array_type missing inner type"))?;
Ok(format!("list[{}]", get_arg_type(Some(inner), src)?))
}
"union_type" => resolve_union_type(annotation, src),
"literal_type" => resolve_literal_type(annotation, src),
"parenthesized_type" => get_arg_type(common::named_child(annotation, 0), src),
_ => Ok("any".to_string()),
}
}
fn resolve_union_type(annotation: Node<'_>, src: &str) -> Result<String> {
let members = flatten_union_members(annotation);
let has_null = members.iter().any(|member| is_nullish_type(*member, src));
let mut literal_values = Vec::new();
let mut all_string_literals = true;
for member in &members {
match string_literal_member(*member, src) {
Some(value) => literal_values.push(value),
None => {
all_string_literals = false;
break;
}
}
}
if all_string_literals && !literal_values.is_empty() {
return Ok(format!("literal:{}", literal_values.join("|")));
}
let mut first_non_null = None;
for member in members {
if is_nullish_type(member, src) {
continue;
}
first_non_null = Some(get_arg_type(Some(member), src)?);
break;
}
let mut ty = first_non_null.unwrap_or_else(|| "any".to_string());
if has_null && !ty.ends_with('?') {
ty.push('?');
}
Ok(ty)
}
fn flatten_union_members(node: Node<'_>) -> Vec<Node<'_>> {
let node = if node.kind() == "type" {
match common::named_child(node, 0) {
Some(inner) => inner,
None => return vec![],
}
} else {
node
};
if node.kind() != "union_type" {
return vec![node];
}
let mut cursor = node.walk();
let mut out = Vec::new();
for child in node.named_children(&mut cursor) {
out.extend(flatten_union_members(child));
}
out
}
fn resolve_literal_type(annotation: Node<'_>, src: &str) -> Result<String> {
let inner = common::named_child(annotation, 0)
.ok_or_else(|| anyhow!("literal_type missing inner literal"))?;
match inner.kind() {
"string" | "number" | "true" | "false" | "unary_expression" => {
Ok(format!("literal:{}", common::node_text(inner, src)?.trim()))
}
"null" | "undefined" => Ok("any".to_string()),
_ => Ok("any".to_string()),
}
}
fn string_literal_member(node: Node<'_>, src: &str) -> Option<String> {
let node = if node.kind() == "type" {
common::named_child(node, 0)?
} else {
node
};
if node.kind() != "literal_type" {
return None;
}
let inner = common::named_child(node, 0)?;
if inner.kind() != "string" {
return None;
}
Some(common::node_text(inner, src).ok()?.to_string())
}
fn is_nullish_type(node: Node<'_>, src: &str) -> bool {
let node = if node.kind() == "type" {
match common::named_child(node, 0) {
Some(inner) => inner,
None => return false,
}
} else {
node
};
match node.kind() {
"literal_type" => common::named_child(node, 0)
.is_some_and(|inner| matches!(inner.kind(), "null" | "undefined")),
"predefined_type" => common::node_text(node, src)
.map(|text| matches!(text, "undefined" | "void"))
.unwrap_or(false),
_ => false,
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::function::JsonSchema;
use std::fs;
use std::time::{SystemTime, UNIX_EPOCH};
fn parse_ts_source(
source: &str,
file_name: &str,
parent: &Path,
) -> Result<Vec<FunctionDeclaration>> {
let unique = SystemTime::now()
.duration_since(UNIX_EPOCH)
.expect("time")
.as_nanos();
let path = std::env::temp_dir().join(format!("loki_ts_parser_{file_name}_{unique}.ts"));
fs::write(&path, source).expect("write");
let file = File::open(&path).expect("open");
let result = generate_typescript_declarations(file, file_name, Some(parent));
let _ = fs::remove_file(&path);
result
}
fn properties(schema: &JsonSchema) -> &IndexMap<String, JsonSchema> {
schema
.properties
.as_ref()
.expect("missing schema properties")
}
fn property<'a>(schema: &'a JsonSchema, name: &str) -> &'a JsonSchema {
properties(schema)
.get(name)
.unwrap_or_else(|| panic!("missing property: {name}"))
}
#[test]
fn test_ts_tool_demo() {
let source = r#"
/**
* Demonstrates how to create a tool using TypeScript.
*
* @param query - The search query string
* @param format - Output format
* @param count - Maximum results to return
* @param verbose - Enable verbose output
* @param tags - List of tags to filter by
* @param language - Optional language filter
* @param extra_tags - Optional extra tags
*/
export function run(
query: string,
format: "json" | "csv" | "xml",
count: number,
verbose: boolean,
tags: string[],
language?: string,
extra_tags?: Array<string>,
): string {
return "result";
}
"#;
let declarations = parse_ts_source(source, "demo_ts", Path::new("tools")).unwrap();
assert_eq!(declarations.len(), 1);
let decl = &declarations[0];
assert_eq!(decl.name, "demo_ts");
assert!(!decl.agent);
let params = &decl.parameters;
assert_eq!(params.type_value.as_deref(), Some("object"));
assert_eq!(
params.required.as_ref().unwrap(),
&vec![
"query".to_string(),
"format".to_string(),
"count".to_string(),
"verbose".to_string(),
"tags".to_string(),
]
);
assert_eq!(
property(params, "query").type_value.as_deref(),
Some("string")
);
let format = property(params, "format");
assert_eq!(format.type_value.as_deref(), Some("string"));
assert_eq!(
format.enum_value.as_ref().unwrap(),
&vec!["json".to_string(), "csv".to_string(), "xml".to_string()]
);
assert_eq!(
property(params, "count").type_value.as_deref(),
Some("number")
);
assert_eq!(
property(params, "verbose").type_value.as_deref(),
Some("boolean")
);
let tags = property(params, "tags");
assert_eq!(tags.type_value.as_deref(), Some("array"));
assert_eq!(
tags.items.as_ref().unwrap().type_value.as_deref(),
Some("string")
);
let language = property(params, "language");
assert_eq!(language.type_value.as_deref(), Some("string"));
assert!(
!params
.required
.as_ref()
.unwrap()
.contains(&"language".to_string())
);
let extra_tags = property(params, "extra_tags");
assert_eq!(extra_tags.type_value.as_deref(), Some("array"));
assert_eq!(
extra_tags.items.as_ref().unwrap().type_value.as_deref(),
Some("string")
);
assert!(
!params
.required
.as_ref()
.unwrap()
.contains(&"extra_tags".to_string())
);
}
#[test]
fn test_ts_tool_simple() {
let source = r#"
/**
* Execute the given code.
*
* @param code - The code to execute
*/
export function run(code: string): string {
return eval(code);
}
"#;
let declarations = parse_ts_source(source, "execute_code", Path::new("tools")).unwrap();
assert_eq!(declarations.len(), 1);
let decl = &declarations[0];
assert_eq!(decl.name, "execute_code");
assert!(!decl.agent);
let params = &decl.parameters;
assert_eq!(params.required.as_ref().unwrap(), &vec!["code".to_string()]);
assert_eq!(
property(params, "code").type_value.as_deref(),
Some("string")
);
}
#[test]
fn test_ts_agent_tools() {
let source = r#"
/** Get user info by ID */
export function get_user(id: string): string {
return "";
}
/** List all users */
export function list_users(): string {
return "";
}
"#;
let declarations = parse_ts_source(source, "tools", Path::new("demo")).unwrap();
assert_eq!(declarations.len(), 2);
assert_eq!(declarations[0].name, "get_user");
assert_eq!(declarations[1].name, "list_users");
assert!(declarations[0].agent);
assert!(declarations[1].agent);
}
#[test]
fn test_ts_reject_rest_params() {
let source = r#"
/**
* Has rest params
*/
export function run(...args: string[]): string {
return "";
}
"#;
let err = parse_ts_source(source, "rest_params", Path::new("tools")).unwrap_err();
let msg = format!("{err:#}");
assert!(msg.contains("rest parameters"));
assert!(msg.contains("in function 'run'"));
}
#[test]
fn test_ts_missing_jsdoc() {
let source = r#"
export function run(x: string): string {
return x;
}
"#;
let err = parse_ts_source(source, "missing_jsdoc", Path::new("tools")).unwrap_err();
assert!(
err.to_string()
.contains("Missing or empty description on function: run")
);
}
#[test]
fn test_ts_syntax_error() {
let source = "export function run(: broken";
let err = parse_ts_source(source, "syntax_error", Path::new("tools")).unwrap_err();
assert!(err.to_string().contains("failed to parse typescript"));
}
#[test]
fn test_ts_underscore_skipped() {
let source = r#"
/** Private helper */
function _helper(): void {}
/** Public function */
export function do_stuff(): string {
return "";
}
"#;
let declarations = parse_ts_source(source, "tools", Path::new("demo")).unwrap();
assert_eq!(declarations.len(), 1);
assert_eq!(declarations[0].name, "do_stuff");
assert!(declarations[0].agent);
}
#[test]
fn test_ts_non_exported_helpers_skipped() {
let source = r#"
#!/usr/bin/env tsx
import { appendFileSync } from 'fs';
/**
* Get the current weather in a given location
* @param location - The city
*/
export function get_current_weather(location: string): string {
return fetchSync("https://example.com/" + location);
}
function fetchSync(url: string): string {
return "sunny";
}
"#;
let declarations = parse_ts_source(source, "tools", Path::new("demo")).unwrap();
assert_eq!(declarations.len(), 1);
assert_eq!(declarations[0].name, "get_current_weather");
}
#[test]
fn test_ts_instructions_not_skipped() {
let source = r#"
/** Help text for the agent */
export function _instructions(): string {
return "";
}
"#;
let declarations = parse_ts_source(source, "tools", Path::new("demo")).unwrap();
assert_eq!(declarations.len(), 1);
assert_eq!(declarations[0].name, "instructions");
assert!(declarations[0].agent);
}
#[test]
fn test_ts_optional_with_null_union() {
let source = r#"
/**
* Fetch data with optional filter
*
* @param url - The URL to fetch
* @param filter - Optional filter string
*/
export function run(url: string, filter: string | null): string {
return "";
}
"#;
let declarations = parse_ts_source(source, "fetch_data", Path::new("tools")).unwrap();
let params = &declarations[0].parameters;
assert!(
params
.required
.as_ref()
.unwrap()
.contains(&"url".to_string())
);
assert!(
!params
.required
.as_ref()
.unwrap()
.contains(&"filter".to_string())
);
assert_eq!(
property(params, "filter").type_value.as_deref(),
Some("string")
);
}
#[test]
fn test_ts_optional_with_default() {
let source = r#"
/**
* Search with limit
*
* @param query - Search query
* @param limit - Max results
*/
export function run(query: string, limit: number = 10): string {
return "";
}
"#;
let declarations =
parse_ts_source(source, "search_with_limit", Path::new("tools")).unwrap();
let params = &declarations[0].parameters;
assert!(
params
.required
.as_ref()
.unwrap()
.contains(&"query".to_string())
);
assert!(
!params
.required
.as_ref()
.unwrap()
.contains(&"limit".to_string())
);
assert_eq!(
property(params, "limit").type_value.as_deref(),
Some("number")
);
}
#[test]
fn test_ts_shebang_parses() {
let source = r#"#!/usr/bin/env tsx
/**
* Get weather
* @param location - The city
*/
export function run(location: string): string {
return location;
}
"#;
let result = parse_ts_source(source, "get_weather", Path::new("tools"));
eprintln!("shebang parse result: {result:?}");
assert!(result.is_ok(), "shebang should not cause parse failure");
let declarations = result.unwrap();
assert_eq!(declarations.len(), 1);
assert_eq!(declarations[0].name, "get_weather");
}
}
+2
View File
@@ -111,12 +111,14 @@ fn create_suggestion(value: &str, description: &str, span: Span) -> Suggestion {
Some(description.to_string())
};
Suggestion {
display_override: None,
value: value.to_string(),
description,
style: None,
extra: None,
span,
append_whitespace: false,
match_indices: None,
}
}