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PromptBoost v0.1.1+
PromptBoost is the Python/FastAPI app and product line for local prompt compilation, evaluation logging, and matrix-based prompt checks.
It reads PromptGarage examples read-only, accepts raw prompts, selects
task/harness/model rules, generates deterministic boosted prompts, runs a local
no-new-facts check, and stores boost runs in promptboost.db. The app also
includes a Matrix Lab UI/API and an optional agentic LLM prepass that safely
falls back to deterministic PromptBoost when the LLM is unavailable or unsafe.
The repository root TypeScript code is a separate portable V2 library and
experiment line. Its public entry point is ../src/index.ts; this Python app
remains the product-facing web/API implementation.
Run
uv run uvicorn promptboost.main:app --reload --port 8000
Open http://127.0.0.1:8000.
Routes
GET /β main PromptBoost web form.GET /matrix-labβ Matrix Lab UI for comparing deterministic and full-cell prompt evaluations.GET /healthβ local health check.POST /boostβ deterministic PromptBoost pipeline.POST /boost/agenticβ optional LLM prepass plus deterministic fallback.POST /api/matrix/deterministicβ deterministic matrix evaluation endpoint.POST /api/matrix/full-cellβ full-cell matrix evaluation endpoint.GET /api/runsβ stored boost-run history frompromptboost.db.GET /api/promptgarage/samplesβ read-only PromptGarage sample access.
Agentic mode
The deterministic /boost route remains the default. The optional
/boost/agentic route runs an OpenAI-compatible LLM prepass first, validates
the JSON task draft, then falls back to deterministic PromptBoost if the LLM is
unavailable or adds suspected new facts.
export PROMPTBOOST_LLM_API_KEY=...
export PROMPTBOOST_LLM_BASE_URL=https://api.openai.com/v1
export PROMPTBOOST_LLM_MODEL=gpt-5.4-mini
Test
uv run pytest
Notes
- PromptGarage is read with SQLite immutable/read-only connections.
- Paid LLM APIs are only called when agentic mode is explicitly configured and requested.
- The no-new-facts check is conservative and deterministic; it is a warning gate, not a semantic proof system.