{"data":{"slug":"quivrhq-quivr","name":"quivr","tagline":"Opiniated RAG for integrating GenAI in your apps","github_url":"https://github.com/The-Vibe-Company/quivr","owner":"The-Vibe-Company","repo":"quivr","owner_avatar_url":"https://avatars.githubusercontent.com/u/252322352?v=4","primary_language":"Python","stars":39533,"forks":3731,"topics":["ai","api","chatbot","chatgpt","database","docker","framework","frontend","groq","html","javascript","llm","openai","postgresql","privacy","rag","react","security","typescript","vector"],"archived":false,"github_pushed_at":"2026-08-31T18:02:45+00:00","maintenance_label":"Active","stars_delta_30d":132,"url":"https://www.graphcanon.com/tools/quivrhq-quivr","markdown_url":"https://www.graphcanon.com/tools/quivrhq-quivr.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/quivrhq-quivr","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=quivrhq-quivr","description":"Opiniated RAG for integrating GenAI in your apps 🧠   Focus on your product rather than the RAG. Easy integration in existing products with customisation!  Any LLM: GPT4, Groq, Llama. Any Vectorstore: PGVector, Faiss. Any Files. Anyway you want.","homepage_url":"https://core.quivr.com","license":"Other","open_issues":34,"watchers":290,"ai_summary":"Quivr is a framework for integrating generative AI into applications with support for various LLMs and vectorstores, enabling easy customization and integration.","readme_excerpt":"## Getting Started 🚀\n\nYou can find everything on the [documentation](https://core.quivr.com/).\n\n---\n\n### 30 seconds Installation 💽\n\n\n- **Step 1**: Install the package\n\n  \n\n  ```bash\n  pip install quivr-core # Check that the installation worked\n  ```\n\n\n- **Step 2**: Create a RAG with 5 lines of code\n\n  ```python\n  import tempfile\n\n  from quivr_core import Brain\n\n  if __name__ == \"__main__\":\n      with tempfile.NamedTemporaryFile(mode=\"w\", suffix=\".txt\") as temp_file:\n          temp_file.write(\"Gold is a liquid of blue-like colour.\")\n          temp_file.flush()\n\n          brain = Brain.from_files(\n              name=\"test_brain\",\n              file_paths=[temp_file.name],\n          )\n\n          answer = brain.ask(\n              \"what is gold? asnwer in french\"\n          )\n          print(\"answer:\", answer)\n  ```\n\n---\n\n## License 📄\n\nThis project is licensed under the Apache 2.0 License - see the [LICENSE](LICENSE) file for details","github_created_at":"2023-05-12T23:53:30+00:00","created_at":"2026-07-07T17:31:35.291823+00:00","updated_at":"2026-09-20T04:32:30.884339+00:00","categories":[{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"},{"slug":"inference-serving","name":"Inference & Serving","url":"https://www.graphcanon.com/categories/inference-serving","markdown_url":"https://www.graphcanon.com/categories/inference-serving.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/inference-serving"},{"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"}],"tags":[{"slug":"ai","name":"ai"},{"slug":"api","name":"api"},{"slug":"chatbot","name":"chatbot"},{"slug":"database","name":"database"},{"slug":"docker","name":"docker"},{"slug":"framework","name":"framework"},{"slug":"frontend","name":"frontend"},{"slug":"llm","name":"llm"}],"trust":{"provenance":{"is_fork":false,"github_id":640079149,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-18T08:40:14.831Z","maintenance":{"label":"Active","score":82,"methodology":"github_public_v1","releases_90d":0,"days_since_push":17,"last_release_at":"2025-02-04T10:18:50Z","stars_delta_30d":132,"open_issues_delta_30d":-2},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-09-18T08:40:17.259Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-18T08:40:13.665Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-09-18T08:40:13.665Z"},"license_spdx":{"value":"Other","source":"github.license","observed_at":"2026-09-18T08:40:13.665Z"}},"decision_facts":{"hosting":null,"pricing":{"model":"freemium","summary":"The core framework is free to use under the Apache 2.0 License, but additional services or support might incur costs."},"requirements":{"notes":["Python environment is required.","Installation is straightforward with pip."],"min_ram_gb":2,"requires_docker":false},"constraints":{"min_ram_gb":2,"pricing_model":"freemium","requires_docker":false},"when_to_use":["When you need to integrate generative AI into your applications with support for multiple LLMs like GPT4, Groq, and Llama.","If you require flexibility in choosing vectorstores such as PGVector and Faiss for your application.","When customization and ease of integration are critical, and you want to focus on your product rather than the RAG (Retrieval-Augmented Generation) setup."],"when_not_to_use":["If you are looking for a framework that enforces a strict, non-customizable approach to integrating generative AI.","When your project requires a framework that supports only a specific set of LLMs or vectorstores, and you do not need the flexibility to switch between them.","If your application does not require the level of customization and flexibility that Quivr offers, and a more rigid framework would suffice."],"source":"enrich:decision_facts","observed_at":"2026-09-18T11:36:39.233Z"},"constraint_facets":{"min_ram_gb":2,"pricing_model":"freemium","requires_docker":false},"decision_summary":[{"label":"Pricing","value":"freemium - The core framework is free to use under the Apache 2.0 License, but additional services or support might incur costs."},{"label":"Requirements","value":"Min 2 GB RAM; Python environment is required.; Installation is straightforward with pip."},{"label":"Adopt for","value":"Quivr is a Python-based framework for integrating generative AI into applications, supporting various LLMs and vectorstores, with a focus on customization and ease of integration."},{"label":"License detail","value":"Quivr is licensed under the Apache 2.0 License."}]}}