Comparison
rag_api vs autoflow
Verdict
Pick rag_api if key Insights for Using rag_api as an ID-based RAG FastAPI Tool with Langchain and PostgreSQL/pgvector Integration; 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.
Markdown twin · rag_api alternatives · autoflow alternatives
GraphCanon updated Sep 20, 2026
10views this month
vs
Trust & integrity
| Signal | rag_api | autoflow |
|---|---|---|
| Maintenance | Steady (35d since push) As of Sep 20, 2026 · github_public_v1 | Slowing (145d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- rag_api
- ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector
- autoflow
- Graph RAG based conversational knowledge base tool using TiDB Serverless Vector Storage
Stars
- rag_api
- 901
- autoflow
- 3.0k
Forks
- rag_api
- 404
- autoflow
- 193
Open issues
- rag_api
- 45
- autoflow
- 74
Language
- rag_api
- Python
- autoflow
- TypeScript
Adopt for
- rag_api
- Key Insights for Using rag_api as an ID-based RAG FastAPI Tool with Langchain and PostgreSQL/pgvector Integration
- autoflow
- pingcap/autoflow leverages Graph RAG technology and TiDB Serverless Vector Storage, making it a specialized choice for building conversational knowledge bases in TypeScript.
Persona
- rag_api
- -
- autoflow
- -
Runtime
- rag_api
- -
- autoflow
- -
License
- rag_api
- MIT
- autoflow
- Apache-2.0
Last pushed
- rag_api
- Aug 15, 2026
- autoflow
- Apr 27, 2026
Categories
- rag_api
- Data & Retrieval, Vector Databases
- autoflow
- Data & Retrieval, Vector Databases
Trust and health
Maintenance
- rag_api
- Steady (60%)
- autoflow
- Slowing (36%)
Days since push
- rag_api
- 35d
- autoflow
- 145d
Open issues (now)
- rag_api
- 45
- autoflow
- 74
Stars delta
- rag_api
- +35 (30d)
- autoflow
- +18 (30d)
Open issues delta
- rag_api
- -2 (30d)
- autoflow
- -1 (30d)
Owner type
- rag_api
- User
- autoflow
- Organization
Full report
- rag_api
- Trust report
- autoflow
- Trust report
Choose rag_api if…
- rag_api is primarily Python; autoflow is TypeScript.
- License: rag_api is MIT, autoflow is Apache-2.0.
- Tags unique to rag_api: api, api-rest, embeddings, fastapi.
- When you need rapid integration of REST API services for Retrieval-Augmented Generation (RAG) with robust vector storage.
When NOT to use rag_api
- Avoid using if your project cannot leverage PostgreSQL/pgvector due to license or compatibility constraints.
- Not recommended for scenarios where high-level orchestration of multiple APIs and services is necessary without a direct need for FastAPI's simplicity.
Choose autoflow if…
- autoflow is primarily TypeScript; rag_api is Python.
- License: autoflow is Apache-2.0, rag_api is MIT.
- Tags unique to autoflow: chatbot, cot, graphrag, knowledge-graph.
- - 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 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
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (danny-avila/rag_api) · observed Sep 20, 2026
- GitHub forks (danny-avila/rag_api) · observed Sep 20, 2026
- Last push (danny-avila/rag_api) · observed Aug 15, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (pingcap/autoflow) · observed Sep 20, 2026
- GitHub forks (pingcap/autoflow) · observed Sep 20, 2026
- Last push (pingcap/autoflow) · observed Apr 27, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: rag_api 901 · autoflow 3.0k (synced Sep 20, 2026).
Common questions
- What is the difference between rag_api and autoflow?
- rag_api: ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector. 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 rag_api over autoflow?
- Choose rag_api over autoflow when rag_api is primarily Python; autoflow is TypeScript; License: rag_api is MIT, autoflow is Apache-2.0; Tags unique to rag_api: api, api-rest, embeddings, fastapi; When you need rapid integration of REST API services for Retrieval-Augmented Generation (RAG) with robust vector storage.
- When should I choose autoflow over rag_api?
- Choose autoflow over rag_api when autoflow is primarily TypeScript; rag_api is Python; License: autoflow is Apache-2.0, rag_api is MIT; Tags unique to autoflow: chatbot, cot, graphrag, knowledge-graph; - 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 rag_api?
- Avoid using if your project cannot leverage PostgreSQL/pgvector due to license or compatibility constraints. Not recommended for scenarios where high-level orchestration of multiple APIs and services is necessary without a direct need for FastAPI's simplicity.
- 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 rag_api or autoflow more popular on GitHub?
- autoflow has more GitHub stars (2,974 vs 901). Stars measure visibility, not whether either tool fits your constraints.
- Are rag_api and autoflow open source?
- Yes - both are open-source projects on GitHub (rag_api: MIT, autoflow: Apache-2.0).
- Where can I find alternatives to rag_api or autoflow?
- GraphCanon lists graph-backed alternatives at rag_api alternatives and autoflow alternatives (rag_api markdown twin, autoflow markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, rag_api or autoflow?
- rag_api: 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 rag_api and autoflow?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: rag_api trust report; autoflow trust report.