{"data":{"slug":"geeks-of-data-knowledge-gpt","name":"knowledge-gpt","tagline":"Extract knowledge from all information sources using GPT and other language models. Index and conduct Q&A sessions with information sources.","github_url":"https://github.com/geeks-of-data/knowledge-gpt","owner":"geeks-of-data","repo":"knowledge-gpt","owner_avatar_url":"https://avatars.githubusercontent.com/u/126761095?v=4","primary_language":"Python","stars":292,"forks":52,"topics":["context","embedding","embedding-vectors","gpt","gpt3-turbo","gpt4","huggingface","huggingface-transformers","information-extraction","language-model","llama","llm","natural-language-processing","openai","python","question-answering","scraper","sentence-embeddings","sentence-similarity","vector-search"],"archived":false,"github_pushed_at":"2023-04-25T06:55:08+00:00","maintenance_label":"Dormant","stars_delta_30d":1,"url":"https://www.graphcanon.com/tools/geeks-of-data-knowledge-gpt","markdown_url":"https://www.graphcanon.com/tools/geeks-of-data-knowledge-gpt.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/geeks-of-data-knowledge-gpt","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=geeks-of-data-knowledge-gpt","description":"Extract knowledge from all information sources using gpt and other language models. Index and make Q&A session with information sources.","homepage_url":"https://pypi.org/project/knowledgegpt/","license":"MIT","open_issues":8,"watchers":5,"ai_summary":"A Python-based toolkit for indexing and creating question-and-answer sessions with various information sources, leveraging language models like GPT and transformers.","readme_excerpt":"# Installation\n\n1. PyPI installation, run in terminal:  `pip install knowledgegpt`\n\n2. Or you can use the latest version from the repository: `pip install -r requirements.txt` and then `pip install .`\n\n3. Download needed language model for parsing: `python3 -m spacy download en_core_web_sm`\n\n---\n\n## Docker Usage\n\n```bash\ndocker build -t knowledgegptimage .\ndocker run -p 8888:8888 knowledgegptimage\n```","github_created_at":"2023-03-11T23:15:30+00:00","created_at":"2026-07-11T11:36:51.451997+00:00","updated_at":"2026-09-20T06:27:27.793108+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":"evaluation-observability","name":"Evaluation & Observability","url":"https://www.graphcanon.com/categories/evaluation-observability","markdown_url":"https://www.graphcanon.com/categories/evaluation-observability.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/evaluation-observability"},{"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":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"context","name":"context"},{"slug":"embedding-vectors","name":"embedding-vectors"},{"slug":"gpt","name":"gpt"},{"slug":"huggingface-transformers","name":"huggingface-transformers"},{"slug":"information-extraction","name":"information-extraction"},{"slug":"language-model","name":"language-model"},{"slug":"natural-language-processing","name":"natural language processing"},{"slug":"question-answering","name":"question-answering"}],"trust":{"provenance":{"is_fork":false,"github_id":612770423,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-20T06:27:25.447Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":1243,"last_release_at":"2023-03-17T13:16:12Z","stars_delta_30d":1,"open_issues_delta_30d":0},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:36:52.881Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-20T06:27:26.510Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-09-20T06:27:26.510Z","managed_saas":false},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-09-20T06:27:26.510Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-09-20T06:27:26.510Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-09-20T06:27:26.510Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When you need a flexible, model-agnostic approach for Q&A over diverse data sources","If you are leveraging Hugging Face models along with OpenAI's offerings"],"when_not_to_use":["Avoid if strictly needing real-time response performance without indexing capabilities","Not recommended if focusing solely on visual or multimedia content extraction"],"source":"enrich:decision_facts","observed_at":"2026-07-12T12:38:11.558Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"knowledge-gpt: Python toolkit for indexing and Q&A sessions with info sources using GPT & transformers."}]}}