smart_ide/services/langextract-api

langextract-api

Local HTTP API on 127.0.0.1 wrapping google/langextract: structured extractions from unstructured text with optional character grounding.

Environment

Variable	Required	Description
LANGEXTRACT_SERVICE_TOKEN	no	If set, every request must send Authorization: Bearer <token>.
LANGEXTRACT_API_HOST	no	Bind address (default 127.0.0.1).
LANGEXTRACT_API_PORT	no	Port (default 37141).
LANGEXTRACT_API_KEY	no	Used by LangExtract for cloud models (e.g. Gemini) when the client does not pass api_key in the JSON body. See upstream docs.

Endpoints

• GET /health — liveness.
• POST /extract — run extraction. JSON body matches LangExtract extract() parameters where applicable: text, prompt_description, examples, model_id, optional model_url (Ollama), extraction_passes, max_workers, max_char_buffer, api_key, fence_output, use_schema_constraints.

Example examples item:

{
  "text": "ROMEO. But soft!",
  "extractions": [
    {
      "extraction_class": "character",
      "extraction_text": "ROMEO",
      "attributes": {}
    }
  ]
}

Run

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
export LANGEXTRACT_SERVICE_TOKEN='…'
uvicorn app.main:app --host "${LANGEXTRACT_API_HOST:-127.0.0.1}" --port "${LANGEXTRACT_API_PORT:-37141}"

For Ollama-backed models, set model_id to your tag (e.g. gemma2:2b), model_url to http://127.0.0.1:11434, and typically fence_output: false, use_schema_constraints: false per upstream README.

License

This wrapper is MIT. LangExtract is Apache-2.0 (see upstream repository).