mirror of
https://github.com/tiennm99/DocsGPT.git
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Alex
574f96341e
The backend import package is now docsgpt, the name it will carry on PyPI; application was far too generic to install into anyone's site-packages. git mv plus a mechanical rewrite of every import, dotted string and path reference: 734 Python files, the compose files, Dockerfile, workflows, docs, setup scripts, devcontainer, k8s manifests, vscode config, pytest and coverage config, .gitignore. Behaviour is unchanged. Kept for one release: - A top-level application package whose meta-path finder resolves application.x.y to the already-imported docsgpt.x.y object, so old imports and entry points (celery -A application.app.celery, uvicorn application.asgi:asgi_app) keep working with a FutureWarning. - Celery registers every application.* task name as an alias of its docsgpt.* task on start-up, so messages queued by the previous release still run. The redbeat key prefix moves to redbeat:docsgpt:v2: so schedule entries the previous release wrote are left unread instead of firing twice. The backend image builds from the repository root (docker build -f docsgpt/Dockerfile .) so it can ship the alias package; a root .dockerignore allow-lists docsgpt/ and application/ and keeps caches, local data, .env files, the sample index files and the Dockerfile out. Compose and the image workflows point at the new context.
71 lines
2.0 KiB
Python
71 lines
2.0 KiB
Python
from docsgpt.agents.tools.base import Tool
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THINK_TOOL_ID = "think"
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THINK_TOOL_ENTRY = {
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"name": "think",
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"actions": [
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{
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"name": "reason",
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"description": (
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"Use this tool to think through your reasoning step by step "
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"before deciding on your next action. Always reason before "
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"searching or answering."
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),
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"active": True,
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"parameters": {
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"properties": {
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"reasoning": {
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"type": "string",
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"description": "Your step-by-step reasoning and analysis",
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"filled_by_llm": True,
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"required": True,
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}
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}
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},
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}
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],
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}
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class ThinkTool(Tool):
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"""Pseudo-tool that captures chain-of-thought reasoning.
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Returns a short acknowledgment so the LLM can continue.
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The reasoning content is captured in tool_call data for transparency.
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"""
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internal = True
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def __init__(self, config=None):
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pass
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def execute_action(self, action_name: str, **kwargs):
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return "Continue."
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def get_actions_metadata(self):
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return [
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{
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"name": "reason",
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"description": (
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"Use this tool to think through a complex step — analyze "
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"tool results, weigh options, or plan multi-step work — "
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"before taking your next action."
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),
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"parameters": {
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"properties": {
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"reasoning": {
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"type": "string",
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"description": "Your step-by-step reasoning and analysis",
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"filled_by_llm": True,
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"required": True,
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}
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}
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},
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}
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]
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def get_config_requirements(self):
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return {}
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