CLOUDM0N
Repository intelligence

zylon-ai/private-gpt

GitHub

An open-source, API-first layer following the Claude spec that provides higher-level AI building blocks for local models.

CLOUDM0N decision
REVIEW BEFORE ADOPTION
Trust REVIEW · 70/100
Good fit if

Developers building private AI products who want to avoid creating backend primitives like RAG, file ingestion, and tools from scratch.

Watch out for

Does not run or serve models itself, requiring a separate OpenAI-compatible inference server.

Practical intelligence

What matters before you adopt it

Best for
Developers building private AI products who want to avoid creating backend primitives like RAG, file ingestion, and tools from scratch.
Teams seeking a local backend to power terminal-based AI coding assistants and office productivity integrations.
Application builders who need a standardized, Claude-compatible API instead of an out-of-the-box user-facing chat app.
Main trade-offs
Does not run or serve models itself, requiring a separate OpenAI-compatible inference server.
Lacks support for prompt caching and OAuth/organizations.
The included user interface is a testing demonstrator rather than a complete production-ready application.
Why it stands out
Powers Zylon's production-grade enterprise platform, ensuring a production-tested codebase.
Comes with built-in tools (web search, web fetch, code execution) and database/CSV querying out-of-the-box.
Natively integrates with developer tools like Claude Code, Claude Desktop, and Microsoft 365.
Trust & CVEs

Security evidence without the noise

Trust remains a decision signal; CVEs and scanner evidence explain what is driving the risk.

Security findings
3
CLOUDM0N scanner findings
Critical
0
High
0
Medium
3
Low
0
View trust evidence & security findings▼
Why this score
No trust rationale was stored for this scan.
CLOUDM0N findings
MEDIUM
Dynamic code execution pattern detected. 5 sample match(es) found.
MEDIUM
The project can spawn operating-system processes; review command construction and input handling. 5 sample match(es) found.
MEDIUM
Dockerfile does not end with an explicit non-root USER.
Architecture from code6 modules · 2 edges▼
Structural evidence

Modules and dependency edges extracted from repository code. This is code evidence, not README inference.

Code files
888
Modules
6
Dependency edges
2
Core modules
private_gpt
681 files
scripts
8 files
Dependency flow
scripts→private_gpt
Detected languages
Python
Detected frameworks
FastAPI
Architecture evidence details
flowchart TD
    %% private-gpt — high-level architecture (DRAFT, refine me)
    n0["private_gpt · 681 files"]
    n1["scripts · scripts · 8 files"]
    n2["tests · tests · 199 files"]
    n1 --> n0
    n2 --> n0
    class n1 infra
    class n2 test
    classDef infra fill:#b35c00,color:#ffffff,stroke:#8f4a00
    classDef test fill:#499894,color:#ffffff,stroke:#397975
Evidence, security & integrations▼
Integrations
Security notes
Still unknown
• Does not provide local system resource guidelines, operating system compatibility, or Python runtime requirements.
• Does not contain performance benchmarks, token processing speeds, or maximum document ingestion size limits.
Agent handoff
Use with any agent
JSON API
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