--- title: "graphrag-rs vs Langchain-Chatchat" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/automataia-graphrag-rs-vs-chatchat-space-langchain-chatchat" tools: ["automataia-graphrag-rs", "chatchat-space-langchain-chatchat"] --- # graphrag-rs vs Langchain-Chatchat *GraphCanon updated Sep 20, 2026* ## Verdict Pick graphrag-rs if graphRAG-rs creates knowledge graphs from documents, enables natural language querying with customizable entity extraction and local LLM support, written in Rust; pick Langchain-Chatchat if langchain-Chatchat is a local knowledge-based application that integrates RAG and Agent functionalities using Langchain and various language models like ChatGLM, Qwen, and Llama. [graphrag-rs](https://automataia.github.io/graphrag-rs/) reports 527 GitHub stars, 50 forks, and 0 open issues, last pushed Jun 2, 2026. [Langchain-Chatchat](https://github.com/chatchat-space/Langchain-Chatchat) has 39k stars, 6.3k forks, and 26 open issues, last pushed Nov 10, 2025. Figures are from public GitHub metadata via [graphrag-rs's repository](https://github.com/automataIA/graphrag-rs) and [Langchain-Chatchat's repository](https://github.com/chatchat-space/Langchain-Chatchat). | | [graphrag-rs](/tools/automataia-graphrag-rs.md) | [Langchain-Chatchat](/tools/chatchat-space-langchain-chatchat.md) | | --- | --- | --- | | Tagline | GraphRAG-rs implements Graph-based Retrieval Augmented Generation for knowledge graph creation and natural language querying with entity extraction and LLM integration. | Local knowledge-based LLM RAG and Agent app with Langchain | | Stars | 527 | 38,644 | | Forks | 50 | 6,265 | | Open issues | 0 | 26 | | Language | Rust | Python | | Adopt for | GraphRAG-rs creates knowledge graphs from documents, enables natural language querying with customizable entity extraction and local LLM support, written in Rust. | Langchain-Chatchat is a local knowledge-based application that integrates RAG and Agent functionalities using Langchain and various language models like ChatGLM, Qwen, and Llama. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Data & Retrieval, LLM Frameworks | AI Agents, Data & Retrieval, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [graphrag-rs](/tools/automataia-graphrag-rs.md) | [Langchain-Chatchat](/tools/chatchat-space-langchain-chatchat.md) | | --- | --- | --- | | Days since push | 109d | 311d | | Open issues (now) | 0 | 26 | | Stars delta | +5 (30d) | +122 (30d) | | Open issues delta | 0 (30d) | +1 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/automataia-graphrag-rs/trust.md) | [trust report](/tools/chatchat-space-langchain-chatchat/trust.md) | ## Decision facts: graphrag-rs - **Adopt for:** GraphRAG-rs creates knowledge graphs from documents, enables natural language querying with customizable entity extraction and local LLM support, written in Rust. ## Decision facts: Langchain-Chatchat - **Adopt for:** Langchain-Chatchat is a local knowledge-based application that integrates RAG and Agent functionalities using Langchain and various language models like ChatGLM, Qwen, and Llama. ## Choose when ### Choose graphrag-rs if… - graphrag-rs is primarily Rust; Langchain-Chatchat is Python. - License: graphrag-rs is MIT, Langchain-Chatchat is Apache-2.0. - Tags unique to graphrag-rs: ai, embeddings, entity-extraction, graphrag. - Need Rust-based implementation for integration into existing Rust projects ### Choose Langchain-Chatchat if… - Langchain-Chatchat is primarily Python; graphrag-rs is Rust. - License: Langchain-Chatchat is Apache-2.0, graphrag-rs is MIT. - Tags unique to Langchain-Chatchat: chatbot, chatchat, chatglm, chatgpt. - Also covers AI Agents. - When you need a local deployment of a knowledge-based application that supports multiple language models including ChatGLM, Qwen, and Llama. ## When NOT to use graphrag-rs - Seeking solutions that offer cloud-hosted machine learning services directly - Projects that demand Python libraries due to ecosystem dependencies ## When NOT to use Langchain-Chatchat - If you are looking for a cloud-based solution that does not require local deployment and management. - When your project specifically requires a different set of language models that are not supported by Langchain-Chatchat, such as models that are not listed in its documentation. - If your use case does not benefit from the integration of RAG and Agent functionalities, and you are looking for a simpler chatbot solution. - When you need a solution that is tightly integrated with a specific cloud provider's services, as Langchain-Chatchat is designed for local deployment and may not offer the same level of integration. ## Common questions ### What is the difference between graphrag-rs and Langchain-Chatchat? graphrag-rs: GraphRAG-rs implements Graph-based Retrieval Augmented Generation for knowledge graph creation and natural language querying with entity extraction and LLM integration.. Langchain-Chatchat: Local knowledge-based LLM RAG and Agent app with Langchain. See the comparison table for live GitHub stats and shared categories. ### When should I choose graphrag-rs over Langchain-Chatchat? Choose graphrag-rs over Langchain-Chatchat when graphrag-rs is primarily Rust; Langchain-Chatchat is Python; License: graphrag-rs is MIT, Langchain-Chatchat is Apache-2.0; Tags unique to graphrag-rs: ai, embeddings, entity-extraction, graphrag; Need Rust-based implementation for integration into existing Rust projects. ### When should I choose Langchain-Chatchat over graphrag-rs? Choose Langchain-Chatchat over graphrag-rs when Langchain-Chatchat is primarily Python; graphrag-rs is Rust; License: Langchain-Chatchat is Apache-2.0, graphrag-rs is MIT; Tags unique to Langchain-Chatchat: chatbot, chatchat, chatglm, chatgpt; Also covers AI Agents; When you need a local deployment of a knowledge-based application that supports multiple language models including ChatGLM, Qwen, and Llama. ### When should I avoid graphrag-rs? Seeking solutions that offer cloud-hosted machine learning services directly Projects that demand Python libraries due to ecosystem dependencies ### When should I avoid Langchain-Chatchat? If you are looking for a cloud-based solution that does not require local deployment and management. When your project specifically requires a different set of language models that are not supported by Langchain-Chatchat, such as models that are not listed in its documentation. If your use case does not benefit from the integration of RAG and Agent functionalities, and you are looking for a simpler chatbot solution. When you need a solution that is tightly integrated with a specific cloud provider's services, as Langchain-Chatchat is designed for local deployment and may not offer the same level of integration. ### Is graphrag-rs or Langchain-Chatchat more popular on GitHub? Langchain-Chatchat has more GitHub stars (38,644 vs 527). Stars measure visibility, not whether either tool fits your constraints. ### Are graphrag-rs and Langchain-Chatchat open source? Yes - both are open-source projects on GitHub (graphrag-rs: MIT, Langchain-Chatchat: Apache-2.0). ### Where can I find alternatives to graphrag-rs or Langchain-Chatchat? GraphCanon lists graph-backed alternatives at [graphrag-rs alternatives](/tools/automataia-graphrag-rs/alternatives) and [Langchain-Chatchat alternatives](/tools/chatchat-space-langchain-chatchat/alternatives) ([graphrag-rs markdown twin](/tools/automataia-graphrag-rs/alternatives.md), [Langchain-Chatchat markdown twin](/tools/chatchat-space-langchain-chatchat/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/automataia-graphrag-rs-vs-chatchat-space-langchain-chatchat.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, graphrag-rs or Langchain-Chatchat? graphrag-rs: Slowing. Langchain-Chatchat: Slowing. 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 graphrag-rs and Langchain-Chatchat? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [graphrag-rs trust report](/tools/automataia-graphrag-rs/trust); [Langchain-Chatchat trust report](/tools/chatchat-space-langchain-chatchat/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=automataia-graphrag-rs`](/api/graphcanon/graph?tool=automataia-graphrag-rs) - 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/_