{"data":{"slug":"zorazrw-filco","name":"filco","tagline":"[Preprint] Learning to Filter Context for Retrieval-Augmented Generaton","github_url":"https://github.com/zorazrw/filco","owner":"zorazrw","repo":"filco","owner_avatar_url":"https://avatars.githubusercontent.com/u/49503887?v=4","primary_language":"Python","stars":198,"forks":20,"topics":["dialog-generation","fact-verification","flan-t5","llama2","question-answering","retrieval-augmented-generation"],"archived":false,"github_pushed_at":"2024-04-06T18:57:53+00:00","maintenance_label":"Dormant","url":"https://www.graphcanon.com/tools/zorazrw-filco","markdown_url":"https://www.graphcanon.com/tools/zorazrw-filco.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/zorazrw-filco","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=zorazrw-filco","description":"[Preprint] Learning to Filter Context for Retrieval-Augmented Generaton","homepage_url":"https://arxiv.org/pdf/2311.08377.pdf","license":"CC-BY-SA-4.0","open_issues":2,"watchers":1,"ai_summary":"A tool for improving context filtering in retrieval-augmented generation tasks such as dialog-generation and question-answering.","readme_excerpt":"## Install\n\nInstall all required libraries by running\n\n```bash\npip install -r requirements.txt\n```\n\nRetrieve top relevant Wikipedia passages using [Dense Passage Retriever (DPR)](https://github.com/facebookresearch/DPR)\nand store into the `./datasets/${name}` directory. We also provide preprocessed datasets with top-5 retrieved passages [(here)](https://drive.google.com/file/d/13z_qrVOBlgu75IJBpX-1vMSCC6hC9yH4/view?usp=sharing).\nWe specify `${name}` for six datasets with ['nq', 'tqa', 'hotpotqa', 'fever', 'wow'] in following example commands.","github_created_at":"2023-11-14T21:18:30+00:00","created_at":"2026-07-11T23:07:28.194186+00:00","updated_at":"2026-08-01T18:00:11.365323+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":"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":"dialog-generation","name":"dialog-generation"},{"slug":"fact-verification","name":"fact-verification"},{"slug":"flan-t5","name":"flan-t5"},{"slug":"llama2","name":"llama2"},{"slug":"question-answering","name":"question-answering"},{"slug":"retrieval-augmented-generation","name":"retrieval-augmented-generation"}],"trust":{"provenance":{"is_fork":false,"github_id":718814616,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-01T18:00:10.631Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":846,"last_release_at":null},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":28,"high_count":5,"last_scan_at":"2026-07-11T23:07:37.333Z","medium_count":12,"scan_profile":"deps","critical_count":1}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-01T18:00:11.071Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-08-01T18:00:11.071Z"},"license_spdx":{"value":"CC-BY-SA-4.0","source":"github.license","observed_at":"2026-08-01T18:00:11.071Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When developing applications requiring accurate and relevant context extraction, such as refined conversational agents","For projects that benefit from preprocessed datasets with top-relevant passages for training"],"when_not_to_use":["If you need a general-purpose context generation tool without advanced passage retrieval capabilities","For tasks that do not depend on preexisting Wikipedia-based or similar text corpus retrieval mechanisms"],"source":"enrich:decision_facts","observed_at":"2026-07-12T13:45:55.416Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Filco enhances context filtering for retrieval-augmented generation tasks like dialog-generation and question-answering by integrating with Dense Passage Retriever for precise passage retrieval."}]}}