--- title: "openagent vs autoflow" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/haohao-end-openagent-vs-pingcap-autoflow" tools: ["haohao-end-openagent", "pingcap-autoflow"] --- # openagent vs autoflow *GraphCanon updated Aug 21, 2026* ## Verdict Pick openagent if openAgent integrates OpenAI and Dify, focusing on deep reasoning loops, visual workflows, RAG, and agent delegation in Python under MIT license; pick autoflow if pingcap/autoflow leverages Graph RAG technology and TiDB Serverless Vector Storage, making it a specialized choice for building conversational knowledge bases in TypeScript. [openagent](https://openllm.cloud) reports 792 GitHub stars, 80 forks, and 46 open issues, last pushed Jul 17, 2026. [autoflow](https://tidb.ai) has 3.0k stars, 194 forks, and 74 open issues, last pushed Apr 27, 2026. Figures are from public GitHub metadata via [openagent's repository](https://github.com/Haohao-end/openagent) and [autoflow's repository](https://github.com/pingcap/autoflow). | | [openagent](/tools/haohao-end-openagent.md) | [autoflow](/tools/pingcap-autoflow.md) | | --- | --- | --- | | Tagline | Harness architecture for rapidly building vertical AI agents | Graph RAG based conversational knowledge base tool using TiDB Serverless Vector Storage | | Stars | 792 | 2,971 | | Forks | 80 | 194 | | Open issues | 46 | 74 | | Language | Python | TypeScript | | Adopt for | OpenAgent integrates OpenAI and Dify, focusing on deep reasoning loops, visual workflows, RAG, and agent delegation in Python under MIT license. | pingcap/autoflow leverages Graph RAG technology and TiDB Serverless Vector Storage, making it a specialized choice for building conversational knowledge bases in TypeScript. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | AI Agents, Data & Retrieval, Vector Databases | Data & Retrieval, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [openagent](/tools/haohao-end-openagent.md) | [autoflow](/tools/pingcap-autoflow.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Slowing (36%) | | Days since push | 34d | 115d | | Open issues (now) | 46 | 74 | | Stars delta | +21 (30d) | +15 (30d) | | Open issues delta | +1 (30d) | -1 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/haohao-end-openagent/trust.md) | [trust report](/tools/pingcap-autoflow/trust.md) | ## Decision facts: openagent - **Adopt for:** OpenAgent integrates OpenAI and Dify, focusing on deep reasoning loops, visual workflows, RAG, and agent delegation in Python under MIT license. ## Decision facts: autoflow - **Adopt for:** pingcap/autoflow leverages Graph RAG technology and TiDB Serverless Vector Storage, making it a specialized choice for building conversational knowledge bases in TypeScript. ## Choose when ### Choose openagent if… - openagent is primarily Python; autoflow is TypeScript. - License: openagent is MIT, autoflow is Apache-2.0. - Tags unique to openagent: agent, ai, celery, deepagents. - Also covers AI Agents. - Need integration of OpenAI and Dify functionalities. ### Choose autoflow if… - autoflow is primarily TypeScript; openagent is Python. - License: autoflow is Apache-2.0, openagent is MIT. - Tags unique to autoflow: chatbot, cot, graphrag, knowledge-graph. - autoflow ships Docker support for self-hosted deployment. - - When you need to create a conversational interface that can leverage both graph-based data structures and retrieval-augmented generation techniques for context-aware responses. ## When NOT to use openagent - Projects requiring only basic AI functionality without deep reasoning loops or RAG. - Teams preferring non-Python environments for AI agent development. ## When NOT to use autoflow - - When your application does not require a conversational knowledge base or cannot benefit from retrieval-augmented generation (RAG) techniques. - - If you are aiming for broad compatibility across different SQL-based databases, as autoflow specifically integrates with TiDB and might offer less flexibility when compared to tools that support a ## Common questions ### What is the difference between openagent and autoflow? openagent: Harness architecture for rapidly building vertical AI agents. autoflow: Graph RAG based conversational knowledge base tool using TiDB Serverless Vector Storage. See the comparison table for live GitHub stats and shared categories. ### When should I choose openagent over autoflow? Choose openagent over autoflow when openagent is primarily Python; autoflow is TypeScript; License: openagent is MIT, autoflow is Apache-2.0; Tags unique to openagent: agent, ai, celery, deepagents; Also covers AI Agents; Need integration of OpenAI and Dify functionalities. ### When should I choose autoflow over openagent? Choose autoflow over openagent when autoflow is primarily TypeScript; openagent is Python; License: autoflow is Apache-2.0, openagent is MIT; Tags unique to autoflow: chatbot, cot, graphrag, knowledge-graph; autoflow ships Docker support for self-hosted deployment; - When you need to create a conversational interface that can leverage both graph-based data structures and retrieval-augmented generation techniques for context-aware responses. ### When should I avoid openagent? Projects requiring only basic AI functionality without deep reasoning loops or RAG. Teams preferring non-Python environments for AI agent development. ### When should I avoid autoflow? - When your application does not require a conversational knowledge base or cannot benefit from retrieval-augmented generation (RAG) techniques. - If you are aiming for broad compatibility across different SQL-based databases, as autoflow specifically integrates with TiDB and might offer less flexibility when compared to tools that support a ### Is openagent or autoflow more popular on GitHub? autoflow has more GitHub stars (2,971 vs 792). Stars measure visibility, not whether either tool fits your constraints. ### Are openagent and autoflow open source? Yes - both are open-source projects on GitHub (openagent: MIT, autoflow: Apache-2.0). ### Where can I find alternatives to openagent or autoflow? GraphCanon lists graph-backed alternatives at [openagent alternatives](/tools/haohao-end-openagent/alternatives) and [autoflow alternatives](/tools/pingcap-autoflow/alternatives) ([openagent markdown twin](/tools/haohao-end-openagent/alternatives.md), [autoflow markdown twin](/tools/pingcap-autoflow/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/haohao-end-openagent-vs-pingcap-autoflow.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, openagent or autoflow? openagent: Steady. autoflow: 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 openagent and autoflow? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [openagent trust report](/tools/haohao-end-openagent/trust); [autoflow trust report](/tools/pingcap-autoflow/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=haohao-end-openagent`](/api/graphcanon/graph?tool=haohao-end-openagent) - 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/_