Comparison
rag_api vs vault-ai
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 vault-ai if vault-ai is a tool that gives long-term memory capabilities to ChatGPT by integrating Pinecone Vector Database with an easy-to-use React frontend for uploading various types of files into the system.
Markdown twin · rag_api alternatives · vault-ai alternatives
GraphCanon updated 3d
vs
Trust & integrity
| Signal | rag_api | vault-ai |
|---|---|---|
| Maintenance | Very active (6d since push) As of 4d · github_public_v1 | Dormant (410d since push) As of 3d · github_public_v1 |
| Provenance | Not a fork · Personal account As of 4d · github_public_v1 | Not a fork · Personal account As of 3d · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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
- vault-ai
- Enhances ChatGPT with long-term memory using Pinecone Vector Database and React frontend for custom knowledge base uploads.
Stars
- rag_api
- 885
- vault-ai
- 3.4k
Forks
- rag_api
- 387
- vault-ai
- 296
Open issues
- rag_api
- 44
- vault-ai
- 50
Language
- rag_api
- Python
- vault-ai
- JavaScript
Adopt for
- rag_api
- Key Insights for Using rag_api as an ID-based RAG FastAPI Tool with Langchain and PostgreSQL/pgvector Integration
- vault-ai
- vault-ai is a tool that gives long-term memory capabilities to ChatGPT by integrating Pinecone Vector Database with an easy-to-use React frontend for uploading various types of files into the system.
Persona
- rag_api
- -
- vault-ai
- -
Runtime
- rag_api
- -
- vault-ai
- -
License
- rag_api
- MIT
- vault-ai
- MIT
Last pushed
- rag_api
- Aug 15, 2026
- vault-ai
- Jul 8, 2025
Categories
- rag_api
- Data & Retrieval, Vector Databases
- vault-ai
- Data & Retrieval, Vector Databases
Trust and health
Maintenance
- rag_api
- Very active (96%)
- vault-ai
- Dormant (18%)
Days since push
- rag_api
- 6d
- vault-ai
- 410d
Open issues (now)
- rag_api
- 44
- vault-ai
- 50
Stars delta
- rag_api
- +19 (30d)
- vault-ai
- 0 (30d)
Open issues delta
- rag_api
- -3 (30d)
- vault-ai
- 0 (30d)
Full report
- rag_api
- Trust report
- vault-ai
- Trust report
Choose rag_api if…
- rag_api is primarily Python; vault-ai is JavaScript.
- Tags unique to rag_api: api, api-rest, 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 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 vault-ai if…
- vault-ai is primarily JavaScript; rag_api is Python.
- Tags unique to vault-ai: ai, artificial-intelligence, chatgpt, generative.
- When you need a custom knowledge base that can be queried using a generative AI model, such as extending ChatGPT with historical context from uploaded documents in formats like PDFs or txt.
When NOT to use vault-ai
- When your requirements do not include uploading custom content for the AI to learn from, as vault-ai focuses on integrating a knowledge base with ChatGPT.
- If you prefer using other vector search databases such as Qdrant instead of Pinecone, as vault-ai is specifically designed around Pinecone.
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 Aug 21, 2026
- GitHub forks (danny-avila/rag_api) · observed Aug 21, 2026
- Last push (danny-avila/rag_api) · observed Aug 15, 2026
- License file (MIT) · observed Aug 21, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (pashpashpash/vault-ai) · observed Aug 23, 2026
- GitHub forks (pashpashpash/vault-ai) · observed Aug 23, 2026
- Last push (pashpashpash/vault-ai) · observed Jul 8, 2025
- License file (MIT) · observed Aug 23, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: rag_api 885 · vault-ai 3.4k (synced Aug 21, 2026).
Common questions
- What is the difference between rag_api and vault-ai?
- rag_api: ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector. vault-ai: Enhances ChatGPT with long-term memory using Pinecone Vector Database and React frontend for custom knowledge base uploads.. See the comparison table for live GitHub stats and shared categories.
- When should I choose rag_api over vault-ai?
- Choose rag_api over vault-ai when rag_api is primarily Python; vault-ai is JavaScript; Tags unique to rag_api: api, api-rest, 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 vault-ai over rag_api?
- Choose vault-ai over rag_api when vault-ai is primarily JavaScript; rag_api is Python; Tags unique to vault-ai: ai, artificial-intelligence, chatgpt, generative; When you need a custom knowledge base that can be queried using a generative AI model, such as extending ChatGPT with historical context from uploaded documents in formats like PDFs or txt.
- 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 vault-ai?
- When your requirements do not include uploading custom content for the AI to learn from, as vault-ai focuses on integrating a knowledge base with ChatGPT. If you prefer using other vector search databases such as Qdrant instead of Pinecone, as vault-ai is specifically designed around Pinecone.
- Is rag_api or vault-ai more popular on GitHub?
- vault-ai has more GitHub stars (3,387 vs 885). Stars measure visibility, not whether either tool fits your constraints.
- Are rag_api and vault-ai open source?
- Yes - both are open-source projects on GitHub (rag_api: MIT, vault-ai: MIT).
- Where can I find alternatives to rag_api or vault-ai?
- GraphCanon lists graph-backed alternatives at rag_api alternatives and vault-ai alternatives (rag_api markdown twin, vault-ai 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 vault-ai?
- rag_api: Very active. vault-ai: 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 vault-ai?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: rag_api trust report; vault-ai trust report.