Alex
94bc4d1eb6
* fix: route remote-device tool through Redis so scheduled runs reach the device
The remote-device tool worked interactively but timed out on every scheduled
run. DeviceBroker was an in-process, in-memory singleton, but scheduled runs
execute in the Celery worker — a different process from the gunicorn web tier
that holds the device's SSE session — so a worker-side dispatch never reached
the device and the tool always hit its deadline.
Make the broker Redis-backed so every hop crosses the process boundary:
- queued commands -> Redis list dev:cmd:{device_id}
- output chunks -> Redis stream dev:out:{invocation_id}
- invocation metadata -> Redis hash dev:inv:{invocation_id}
- SSE upgrade tickets -> Redis key dev🎫{device_id}
Per-connection SSE session state stays in the web process. Reuses the existing
get_redis_instance()/CACHE_REDIS_URL; no new infrastructure. Also makes the web
tier safe to scale past one worker.
Concurrency hardening (from adversarial review + real-Redis e2e):
- XADD the output/control chunk before flipping completed=1, and have
drain_output do a final non-blocking flush after observing completion, so a
reader can't see completion and stop before the control chunk lands (this had
reintroduced the false "device did not respond (timed out)" under a race).
- _collect_result builds the result from drained chunks, checks the deadline
only after capturing a chunk, and falls back to the authoritative snapshot
(before cleanup) when no control chunk was observed.
- Audit outcome is written from locally-known fields so it survives the worker
racing to delete the invocation; a denied command now records a terminal
"denied" outcome instead of staying "dispatched".
- cmd-queue TTL raised to 900s (>= max drain deadline); dispatch-failure and
reaped-invocation cleanup; UTF-8 byte counts.
Tests: new tests/devices/{conftest (FakeRedis double), test_broker_cross_process,
test_broker_race, test_submit_output_audit}; drain/cleanup/ticket tests rewritten
for the Redis contract. The race tests fail against the pre-fix code. ruff clean;
device + tool-executor suites green.
* fix: log instead of silently passing on failed-dispatch cleanup
Addresses the code-quality lint on the best-effort hash delete in
dispatch_invocation's failure path: replace the bare `except: pass` with a
logger.debug carrying the invocation_id. No behavior change — cleanup stays
best-effort and still returns a failed Invocation.
DocsGPT 🦖
Private AI for agents, assistants and enterprise search
DocsGPT is an open-source AI platform for building intelligent agents and assistants. Features Agent Builder, deep research tools, document analysis (PDF, Office, web content, and audio), Multi-model support (choose your provider or run locally), and rich API connectivity for agents with actionable tools and integrations. Deploy anywhere with complete privacy control.
Key Features:
- 🗂️ Wide Format Support: Reads PDF, DOCX, CSV, XLSX, EPUB, MD, RST, HTML, MDX, JSON, PPTX, images, and audio files such as MP3, WAV, M4A, OGG, and WebM.
- 🎙️ Speech Workflows: Record voice input into chat, transcribe audio on the backend, and ingest meeting recordings or voice notes as searchable knowledge.
- 🌐 Web & Data Integration: Ingests from URLs, sitemaps, Reddit, GitHub and web crawlers.
- ✅ Reliable Answers: Get accurate, hallucination-free responses with source citations viewable in a clean UI.
- 🔑 Streamlined API Keys: Generate keys linked to your settings, documents, and models, simplifying chatbot and integration setup.
- 🔗 Actionable Tooling: Connect to APIs, tools, and other services to enable LLM actions.
- 🧩 Pre-built Integrations: Use readily available HTML/React chat widgets, search tools, Discord/Telegram bots, and more.
- 🔌 Flexible Deployment: Works with major LLMs (OpenAI, Google, Anthropic) and local models (Ollama, llama_cpp).
- 🏢 Secure & Scalable: Run privately and securely with Kubernetes support, designed for enterprise-grade reliability.
Roadmap
- Agent Workflow Builder with conditional nodes ( February 2026 )
- SharePoint & Confluence connectors ( March – April 2026 )
- Research mode ( March 2026 )
- Postgres migration for user data ( April 2026 )
- OpenTelemetry observability ( April 2026 )
- Bring Your Own Model (BYOM) ( April 2026 )
- Agent scheduling (RedBeat-backed) ( Q2 2026 )
You can find our full roadmap here. Please don't hesitate to contribute or create issues, it helps us improve DocsGPT!
Production Support / Help for Companies:
We're eager to provide personalized assistance when deploying your DocsGPT to a live environment.
Join the Lighthouse Program 🌟
Calling all developers and GenAI innovators! The DocsGPT Lighthouse Program connects technical leaders actively deploying or extending DocsGPT in real-world scenarios. Collaborate directly with our team to shape the roadmap, access priority support, and build enterprise-ready solutions with exclusive community insights.
QuickStart
Note
Make sure you have Docker installed
A more detailed Quickstart is available in our documentation
-
Clone the repository:
git clone https://github.com/arc53/DocsGPT.git cd DocsGPT
For macOS and Linux:
-
Run the setup script:
./setup.sh
For Windows:
-
Run the PowerShell setup script:
PowerShell -ExecutionPolicy Bypass -File .\setup.ps1
Either script will guide you through setting up DocsGPT. Five options available: using the public API, running locally, connecting to a local inference engine, using a cloud API provider, or build the docker image locally. Scripts will automatically configure your .env file and handle necessary downloads and installations based on your chosen option.
Navigate to http://localhost:5173/
To stop DocsGPT, open a terminal in the DocsGPT directory and run:
docker compose -f deployment/docker-compose.yaml down
(or use the specific docker compose down command shown after running the setup script).
Note
For development environment setup instructions, please refer to the Development Environment Guide.
Contributing
Please refer to the CONTRIBUTING.md file for information about how to get involved. We welcome issues, questions, and pull requests.
Architecture
Project Structure
-
Application - Flask app (main application).
-
Extensions - Extensions, like react widget or discord bot.
-
Scripts - Miscellaneous scripts.
Code Of Conduct
We as members, contributors, and leaders, pledge to make participation in our community a harassment-free experience for everyone, regardless of age, body size, visible or invisible disability, ethnicity, sex characteristics, gender identity and expression, level of experience, education, socio-economic status, nationality, personal appearance, race, religion, or sexual identity and orientation. Please refer to the CODE_OF_CONDUCT.md file for more information about contributing.
Many Thanks To Our Contributors⚡
License
The source code license is MIT, as described in the LICENSE file.
This project is supported by:
