--- title: "rag_api vs ChatGLM-6B" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/danny-avila-rag-api-vs-zai-org-chatglm-6b" tools: ["danny-avila-rag-api", "zai-org-chatglm-6b"] --- # rag_api vs ChatGLM-6B *GraphCanon updated Jul 11, 2026* ## Verdict Pick rag_api when license: rag_api is MIT, ChatGLM-6B is Apache-2.0; pick ChatGLM-6B when license: ChatGLM-6B is Apache-2.0, rag_api is MIT. [rag_api](https://librechat.ai/) reports 863 GitHub stars, 376 forks, and 44 open issues, last pushed Jun 18, 2026. [ChatGLM-6B](https://github.com/zai-org/ChatGLM-6B) has 41k stars, 5.1k forks, and 609 open issues, last pushed Jun 27, 2024. Figures are from public GitHub metadata via [rag_api's repository](https://github.com/danny-avila/rag_api) and [ChatGLM-6B's repository](https://github.com/zai-org/ChatGLM-6B). | | [rag_api](/tools/danny-avila-rag-api.md) | [ChatGLM-6B](/tools/zai-org-chatglm-6b.md) | | --- | --- | --- | | Tagline | ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector | ChatGLM-6B: An Open Bilingual Dialogue Language Model | 开源双语对话语言模型 | | Stars | 863 | 41,035 | | Forks | 376 | 5,132 | | Open issues | 44 | 609 | | Language | Python | Python | | Adopt for | Key Insights for Using rag_api as an ID-based RAG FastAPI Tool with Langchain and PostgreSQL/pgvector Integration | - | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Data & Retrieval, Vector Databases | LLM Frameworks, Data & Retrieval, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [rag_api](/tools/danny-avila-rag-api.md) | [ChatGLM-6B](/tools/zai-org-chatglm-6b.md) | | --- | --- | --- | | Maintenance | Active (82%) | Dormant (18%) | | Days since push | 22d | 744d | | Open issues (now) | 44 | 609 | | Owner type | User | Organization | | Security scan | No lockfile | 75 low (75 low) | | Full report | [trust report](/tools/danny-avila-rag-api/trust.md) | [trust report](/tools/zai-org-chatglm-6b/trust.md) | ## Decision facts: rag_api - **Adopt for:** Key Insights for Using rag_api as an ID-based RAG FastAPI Tool with Langchain and PostgreSQL/pgvector Integration ## Choose when ### Choose rag_api if… - License: rag_api is MIT, ChatGLM-6B is Apache-2.0. - Tags unique to rag_api: postgresql, psql, embeddings, fastapi. - rag_api ships Docker support for self-hosted deployment. - When you need rapid integration of REST API services for Retrieval-Augmented Generation (RAG) with robust vector storage. ### Choose ChatGLM-6B if… - License: ChatGLM-6B is Apache-2.0, rag_api is MIT. - Tags unique to ChatGLM-6B: python. - Also covers LLM Frameworks. ## 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. ## When NOT to use ChatGLM-6B - Last GitHub push was 745 days ago (dormant maintenance, Jun 27, 2024). Validate activity before betting a new project on ChatGLM-6B. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## Common questions ### What is the difference between rag_api and ChatGLM-6B? rag_api: ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector. ChatGLM-6B: ChatGLM-6B: An Open Bilingual Dialogue Language Model | 开源双语对话语言模型. See the comparison table for live GitHub stats and shared categories. ### When should I choose rag_api over ChatGLM-6B? Choose rag_api over ChatGLM-6B when License: rag_api is MIT, ChatGLM-6B is Apache-2.0; Tags unique to rag_api: postgresql, psql, embeddings, fastapi; rag_api ships Docker support for self-hosted deployment; When you need rapid integration of REST API services for Retrieval-Augmented Generation (RAG) with robust vector storage. ### When should I choose ChatGLM-6B over rag_api? Choose ChatGLM-6B over rag_api when License: ChatGLM-6B is Apache-2.0, rag_api is MIT; Tags unique to ChatGLM-6B: python; Also covers LLM Frameworks. ### 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 ChatGLM-6B? Last GitHub push was 745 days ago (dormant maintenance, Jun 27, 2024). Validate activity before betting a new project on ChatGLM-6B. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is rag_api or ChatGLM-6B more popular on GitHub? ChatGLM-6B has more GitHub stars (41,035 vs 863). Stars measure visibility, not whether either tool fits your constraints. ### Are rag_api and ChatGLM-6B open source? Yes - both are open-source projects on GitHub (rag_api: MIT, ChatGLM-6B: Apache-2.0). ### Where can I find alternatives to rag_api or ChatGLM-6B? GraphCanon lists graph-backed alternatives at [rag_api alternatives](/tools/danny-avila-rag-api/alternatives) and [ChatGLM-6B alternatives](/tools/zai-org-chatglm-6b/alternatives) ([rag_api markdown twin](/tools/danny-avila-rag-api/alternatives.md), [ChatGLM-6B markdown twin](/tools/zai-org-chatglm-6b/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/danny-avila-rag-api-vs-zai-org-chatglm-6b.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, rag_api or ChatGLM-6B? rag_api: Active. ChatGLM-6B: 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 rag_api and ChatGLM-6B? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [rag_api trust report](/tools/danny-avila-rag-api/trust); [ChatGLM-6B trust report](/tools/zai-org-chatglm-6b/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=danny-avila-rag-api`](/api/graphcanon/graph?tool=danny-avila-rag-api) - 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/_