{"data":{"slug":"langroid-langroid","name":"langroid","tagline":"Harness LLMs with Multi-Agent Programming","github_url":"https://github.com/langroid/langroid","owner":"langroid","repo":"langroid","owner_avatar_url":"https://avatars.githubusercontent.com/u/130325191?v=4","primary_language":"Python","stars":4056,"forks":381,"topics":["agents","ai","chatgpt","function-calling","gpt","gpt-4","gpt4","information-retrieval","language-model","llama","llm","llm-agent","llm-framework","local-llm","multi-agent-systems","openai-api","rag","retrieval-augmented-generation"],"archived":false,"github_pushed_at":"2026-07-07T14:21:36+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/langroid-langroid","markdown_url":"https://www.graphcanon.com/tools/langroid-langroid.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/langroid-langroid","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=langroid-langroid","description":"Harness LLMs with Multi-Agent Programming","homepage_url":"https://langroid.github.io/langroid/","license":"MIT","open_issues":74,"watchers":29,"ai_summary":null,"readme_excerpt":"### Install `langroid`\nLangroid requires Python 3.11+. We recommend using a virtual environment.\nUse `pip` to install a bare-bones slim version of `langroid` (from PyPi) to your virtual \nenvironment:\n```bash\npip install langroid\n```\nThe core Langroid package lets you use OpenAI Embeddings models via their API. \nIf you instead want to use the `sentence-transformers` embedding models from HuggingFace, \ninstall Langroid like this: \n```bash\npip install \"langroid[hf-embeddings]\"\n```\nFor many practical scenarios, you may need additional optional dependencies:\n- To use various document-parsers, install langroid with the `doc-chat` extra:\n    ```bash\n    pip install \"langroid[doc-chat]\"\n    ```\n- For \"chat with databases\", use the `db` extra:\n    ```bash\n    pip install \"langroid[db]\"\n    ```\n- You can specify multiple extras by separating them with commas, e.g.:\n    ```bash\n    pip install \"langroid[doc-chat,db]\"\n    ```\n- To simply install _all_ optional dependencies, use the `all` extra (but note that this will result in longer load/startup times and a larger install size):\n    ```bash\n    pip install \"langroid[all]\"\n    ```\n<details>\n<summary><b>Optional Installs for using SQL Chat with a PostgreSQL DB </b></summary>\n\nIf you are using `SQLChatAgent` \n(e.g. the script [`examples/data-qa/sql-chat/sql_chat.py`](https://github.com/langroid/langroid/blob/main/examples/data-qa/sql-chat/sql_chat.py)),\nwith a postgres db, you will need to:\n\n- Install PostgreSQL dev libraries for your platform, e.g.\n  - `sudo apt-get install libpq-dev` on Ubuntu,\n  - `brew install postgresql` on Mac, etc.\n- Install langroid with the postgres extra, e.g. `pip install langroid[postgres]`\n  or `poetry add \"langroid[postgres]\"` or `poetry install -E postgres`,\n  (or the corresponding `uv` versions, e.g. `uv add \"langroid[postgres]\"`\n  or `uv pip install langroid[postgres]`).\n  If this gives you an error, try `pip install psycopg2-binary` in your virtualenv.\n</details>\n\n📝 If you get strange errors involving `mysqlclient`, try doing `pip uninstall mysqlclient` followed by `pip install mysqlclient`.\n\n---\n\n# 🐳 Docker Instructions\n\nWe provide a containerized version of the [`langroid-examples`](https://github.com/langroid/langroid-examples) \nrepository via this [Docker Image](https://hub.docker.com/r/langroid/langroid).\nAll you need to do is set up environment variables in the `.env` file.\nPlease follow these steps to setup the container:\n\n```bash","github_created_at":"2023-04-16T20:47:28+00:00","created_at":"2026-07-11T10:39:14.344516+00:00","updated_at":"2026-07-11T10:39:23.796269+00:00","categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"},{"slug":"vector-databases","name":"Vector Databases","url":"https://www.graphcanon.com/categories/vector-databases","markdown_url":"https://www.graphcanon.com/categories/vector-databases.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/vector-databases"}],"tags":[{"slug":"agents","name":"agents"},{"slug":"ai","name":"ai"},{"slug":"chatgpt","name":"chatgpt"},{"slug":"function-calling","name":"function-calling"},{"slug":"gpt","name":"gpt"},{"slug":"gpt-4","name":"gpt-4"},{"slug":"gpt4","name":"gpt4"},{"slug":"information-retrieval","name":"information-retrieval"}],"trust":{"provenance":{"is_fork":false,"github_id":628729877,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-11T10:39:14.997Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":12,"days_since_push":3,"last_release_at":"2026-07-07T14:21:29Z"},"security_summary":{"status":"findings","scanner":"mcp_manifest@v1","low_count":2,"high_count":0,"last_scan_at":"2026-07-11T10:39:15.831Z","medium_count":0,"scan_profile":"mcp_manifest","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-11T10:39:15.470Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-07-11T10:39:15.470Z","managed_saas":false},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-07-11T10:39:15.470Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-07-11T10:39:15.470Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-07-11T10:39:15.470Z"}}}}