{"data":{"slug":"nirdiamant-rag-techniques","name":"RAG_Techniques","tagline":"Showcases advanced Retrieval-Augmented Generation (RAG) techniques with detailed notebook tutorials.","github_url":"https://github.com/NirDiamant/RAG_Techniques","owner":"NirDiamant","repo":"RAG_Techniques","owner_avatar_url":"https://avatars.githubusercontent.com/u/28316913?v=4","primary_language":"Jupyter Notebook","stars":29525,"forks":3611,"topics":["agentic-rag","ai","embeddings","generative-ai","gpt","langchain","llama-index","llm","llms","machine-learning","nlp","openai","python","rag","retrieval-augmented-generation","semantic-search","tutorials","vector-database"],"archived":false,"github_pushed_at":"2026-09-15T12:51:09+00:00","maintenance_label":"Very active","stars_delta_30d":449,"url":"https://www.graphcanon.com/tools/nirdiamant-rag-techniques","markdown_url":"https://www.graphcanon.com/tools/nirdiamant-rag-techniques.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/nirdiamant-rag-techniques","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=nirdiamant-rag-techniques","description":"This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.","homepage_url":"https://diamant-ai.com","license":"Other","open_issues":5,"watchers":262,"ai_summary":"This repository provides detailed tutorials on various advanced Retrieval-Augmented Generation (RAG) techniques through Jupyter Notebook tutorials. It covers topics such as embeddings, semantic search, and integration with LLMs like GPT and LLaMA.","readme_excerpt":"## Getting Started\n\nTo begin implementing these advanced RAG techniques in your projects:\n\n1. Clone this repository:\n   ```\n   git clone https://github.com/NirDiamant/RAG_Techniques.git\n   ```\n2. Navigate to the technique you're interested in:\n   ```\n   cd all_rag_techniques/technique-name\n   ```\n3. Follow the detailed implementation guide in each technique's directory.\n\n---\n\n## License\n\nThis project is licensed under a custom non-commercial license - see the [LICENSE](LICENSE) file for details.\n\n---\n\n⭐️ If you find this repository helpful, please consider giving it a star!\n\n\n\nKeywords: RAG, Retrieval-Augmented Generation, NLP, AI, Machine Learning, Information Retrieval, Natural Language Processing, LLM, Embeddings, Semantic Search, PydanticAI, Agent Frameworks","github_created_at":"2024-07-13T16:08:36+00:00","created_at":"2026-07-07T17:32:17.970939+00:00","updated_at":"2026-09-20T04:28:51.291606+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":"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":"ai","name":"ai"},{"slug":"embeddings","name":"embeddings"},{"slug":"information-retrieval","name":"information retrieval"},{"slug":"llm","name":"llm"},{"slug":"machine-learning","name":"machine-learning"},{"slug":"natural-language-processing","name":"natural language processing"},{"slug":"nlp","name":"nlp"},{"slug":"rag","name":"rag"}],"trust":{"provenance":{"is_fork":false,"github_id":828268839,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-18T08:10:51.257Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":0,"days_since_push":2,"last_release_at":"2026-04-15T15:30:39Z","stars_delta_30d":449,"open_issues_delta_30d":-9},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-09-18T08:10:53.338Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-18T08:10:49.780Z"},"languages":{"value":["jupyter notebook"],"source":"github.language","observed_at":"2026-09-18T08:10:49.780Z"},"license_spdx":{"value":"Other","source":"github.license","observed_at":"2026-09-18T08:10:49.780Z"}},"decision_facts":{"hosting":null,"pricing":{"model":"freemium","summary":"Free to use for non-commercial purposes."},"requirements":{"notes":["Requires a Python environment and Jupyter Notebook for running the tutorials."],"min_ram_gb":8,"requires_docker":false},"constraints":{"min_ram_gb":8,"pricing_model":"freemium","requires_docker":false},"when_to_use":["When you need comprehensive tutorials on RAG techniques, including embeddings and semantic search, with practical examples in Jupyter Notebooks.","If your project requires integration with specific LLMs such as GPT and LLaMA, and you seek detailed guidance on how to implement these integrations."],"when_not_to_use":["If you are looking for a repository that focuses on a broader range of AI techniques beyond RAG, as RAG_Techniques is specialized in Retrieval-Augmented Generation.","If you require a repository that supports commercial use, as RAG_Techniques is licensed under a custom non-commercial license."],"source":"enrich:decision_facts","observed_at":"2026-09-18T12:04:29.317Z"},"constraint_facets":{"min_ram_gb":8,"pricing_model":"freemium","requires_docker":false},"decision_summary":[{"label":"Pricing","value":"freemium - Free to use for non-commercial purposes."},{"label":"Requirements","value":"Min 8 GB RAM; Requires a Python environment and Jupyter Notebook for running the tutorials."},{"label":"Adopt for","value":"RAG_Techniques offers detailed Jupyter Notebook tutorials on advanced Retrieval-Augmented Generation techniques, focusing on embeddings, semantic search, and integration with LLMs like GPT and LLaMA."},{"label":"License detail","value":"Licensed under a custom non-commercial license."}]}}