--- title: "contextcheck vs filco" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/addepto-contextcheck-vs-zorazrw-filco" tools: ["addepto-contextcheck", "zorazrw-filco"] --- # contextcheck vs filco *GraphCanon updated Sep 30, 2026* ## Verdict Pick contextcheck if contextcheck is a MIT-licensed framework for testing large language models, retrieval-augmented generation systems, and chatbots. It is configurable via YAML and can be integrated into CI pipelines for automated testing; pick filco if filco is a Python-based project that focuses on dialog generation, fact verification, and question answering using models like Flan-T5 and LLaMA2, with Dense Passage. [contextcheck](https://addepto.com/) reports 97 GitHub stars, 11 forks, and 1 open issues, last pushed Dec 11, 2024. [filco](https://arxiv.org/pdf/2311.08377.pdf) has 199 stars, 20 forks, and 2 open issues, last pushed Apr 6, 2024. Figures are from public GitHub metadata via [contextcheck's repository](https://github.com/Addepto/contextcheck) and [filco's repository](https://github.com/zorazrw/filco). | | [contextcheck](/tools/addepto-contextcheck.md) | [filco](/tools/zorazrw-filco.md) | | --- | --- | --- | | Tagline | Framework for LLMs, RAGs, Chatbots testing | Learning to Filter Context for Retrieval-Augmented Generation | | Stars | 97 | 199 | | Forks | 11 | 20 | | Open issues | 1 | 2 | | Language | Python | Python | | Adopt for | Contextcheck is a MIT-licensed framework for testing large language models, retrieval-augmented generation systems, and chatbots. It is configurable via YAML and can be integrated into CI pipelines for automated testing. | Filco is a Python-based project that focuses on dialog generation, fact verification, and question answering using models like Flan-T5 and LLaMA2, with Dense Passage Retriever for retrieving relevant Wikipedia passages. | | Persona | - | - | | Runtime | - | - | | License | MIT-licensed, allowing for free use, modification, and distribution. | CC-BY-SA-4.0 | | Categories | Evaluation & Observability | Data & Retrieval, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [contextcheck](/tools/addepto-contextcheck.md) | [filco](/tools/zorazrw-filco.md) | | --- | --- | --- | | Days since push | 635d | 894d | | Open issues (now) | 1 | 2 | | Owner type | Organization | User | | Full report | [trust report](/tools/addepto-contextcheck/trust.md) | [trust report](/tools/zorazrw-filco/trust.md) | ## Decision facts: contextcheck - **Requirements:** Requires Python environment.; Supports integration with CI pipelines. - **Adopt for:** Contextcheck is a MIT-licensed framework for testing large language models, retrieval-augmented generation systems, and chatbots. It is configurable via YAML and can be integrated into CI pipelines for automated testing. - **License detail:** MIT-licensed, allowing for free use, modification, and distribution. ## Decision facts: filco - **Adopt for:** Filco is a Python-based project that focuses on dialog generation, fact verification, and question answering using models like Flan-T5 and LLaMA2, with Dense Passage Retriever for retrieving relevant Wikipedia passages. ## Choose when ### Choose contextcheck if… - License: contextcheck is MIT, filco is CC-BY-SA-4.0. - Requirements: Requires Python environment.; Supports integration with CI pipelines.. - Tags unique to contextcheck: ai-chat, ai-testing, ai-testing-tool, chatbot-framework. - Also covers Evaluation & Observability. - When you need a framework that is specifically designed for testing large language models, retrieval-augmented generation systems, and chatbots. ### Choose filco if… - License: filco is CC-BY-SA-4.0, contextcheck is MIT. - Tags unique to filco: dialog-generation, fact-verification, flan-t5, llama2. - Also covers Data & Retrieval, Model Training. - When you need to generate dialogues that require fact verification and question answering capabilities, leveraging models like Flan-T5 and LLaMA2. ## When NOT to use contextcheck - If your testing requirements do not align with the specific focus on large language models, retrieval-augmented generation systems, and chatbots. - If you prefer a testing tool that does not require YAML configuration or CI pipeline integration. ## When NOT to use filco - If your project does not require the use of Flan-T5 or LLaMA2 models for dialog generation, fact verification, or question answering. - When you do not need to retrieve relevant Wikipedia passages using Dense Passage Retriever. - If your project does not involve the use of preprocessed datasets with top-5 retrieved passages from Wikipedia. ## Common questions ### What is the difference between contextcheck and filco? contextcheck: Framework for LLMs, RAGs, Chatbots testing. filco: Learning to Filter Context for Retrieval-Augmented Generation. See the comparison table for live GitHub stats and shared categories. ### When should I choose contextcheck over filco? Choose contextcheck over filco when License: contextcheck is MIT, filco is CC-BY-SA-4.0; Requirements: Requires Python environment.; Supports integration with CI pipelines.; Tags unique to contextcheck: ai-chat, ai-testing, ai-testing-tool, chatbot-framework; Also covers Evaluation & Observability; When you need a framework that is specifically designed for testing large language models, retrieval-augmented generation systems, and chatbots. ### When should I choose filco over contextcheck? Choose filco over contextcheck when License: filco is CC-BY-SA-4.0, contextcheck is MIT; Tags unique to filco: dialog-generation, fact-verification, flan-t5, llama2; Also covers Data & Retrieval, Model Training; When you need to generate dialogues that require fact verification and question answering capabilities, leveraging models like Flan-T5 and LLaMA2. ### When should I avoid contextcheck? If your testing requirements do not align with the specific focus on large language models, retrieval-augmented generation systems, and chatbots. If you prefer a testing tool that does not require YAML configuration or CI pipeline integration. ### When should I avoid filco? If your project does not require the use of Flan-T5 or LLaMA2 models for dialog generation, fact verification, or question answering. When you do not need to retrieve relevant Wikipedia passages using Dense Passage Retriever. If your project does not involve the use of preprocessed datasets with top-5 retrieved passages from Wikipedia. ### Is contextcheck or filco more popular on GitHub? filco has more GitHub stars (199 vs 97). Stars measure visibility, not whether either tool fits your constraints. ### Are contextcheck and filco open source? Yes - both are open-source projects on GitHub (contextcheck: MIT, filco: CC-BY-SA-4.0). ### Where can I find alternatives to contextcheck or filco? GraphCanon lists graph-backed alternatives at [contextcheck alternatives](/tools/addepto-contextcheck/alternatives) and [filco alternatives](/tools/zorazrw-filco/alternatives) ([contextcheck markdown twin](/tools/addepto-contextcheck/alternatives.md), [filco markdown twin](/tools/zorazrw-filco/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/addepto-contextcheck-vs-zorazrw-filco.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, contextcheck or filco? contextcheck: Dormant. filco: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for contextcheck and filco? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [contextcheck trust report](/tools/addepto-contextcheck/trust); [filco trust report](/tools/zorazrw-filco/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=addepto-contextcheck`](/api/graphcanon/graph?tool=addepto-contextcheck) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_