git-metadata-extractor

API and CLI

Main entrypoints

• API app: src/api.py
• Repository analysis orchestrator: src/analysis/repositories.py
• User analysis orchestrator: src/analysis/user.py
• Organization analysis orchestrator: src/analysis/organization.py

Active API endpoints

• GET /v1/repository/gimie/json-ld/{full_path:path}: GIMIE-only JSON-LD extraction.
• GET /v1/repository/llm/json/{full_path:path}: repository Pydantic output.
• GET /v1/repository/llm/json-ld/{full_path:path}: repository JSON-LD output.
• GET /v1/user/llm/json/{full_path:path}: user profile analysis.
• GET /v1/org/llm/json/{full_path:path}: organization analysis.
• Cache management endpoints under /v1/cache/*.

Common query flags:

• force_refresh=true: bypass cache.
• enrich_orgs=true: run organization enrichment.
• enrich_users=true: run user enrichment (repository/user routes).

Response shape

All analysis endpoints return APIOutput (src/data_models/api.py):

• link
• type (repository, user, organization)
• parsedTimestamp
• output (model object or JSON-LD dict)
• stats (APIStats token usage, duration, GitHub rate-limit headers)

Endpoint-to-pipeline map

flowchart LR
    A[/repository/llm/*] --> R[Repository.run_analysis]
    B[/user/llm/json/*] --> U[User.run_analysis]
    C[/org/llm/json/*] --> O[Organization.run_analysis]

    R --> RA[Atomic repository pipeline + optional enrichments]
    U --> UA[GitHub parse + user/org enrich + linked entities + EPFL]
    O --> OA[Atomic organization pipeline]

Run the API

just serve-dev

Smoke tests

just api-test-gimie
just api-test-extract
just api-test-extract-refresh

CLI status and alternatives

• just extract ... currently calls src/main.py, which still imports legacy core.* modules.
• Use API endpoints for full extraction flows.
• Use scripts/convert_json_jsonld.py for JSON <-> JSON-LD conversion workflows.

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