fc2e4cd7d1
Add README.md with project description, quick-start instructions, and AGPL-3.0 license badge. Add .gitignore for Python, Node, and Docker artifacts. Include existing CLAUDE.md, spec, docker-compose.yml, and env.example.
65 lines
2.5 KiB
Markdown
65 lines
2.5 KiB
Markdown
# PromptLooper
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[](https://www.gnu.org/licenses/agpl-3.0)
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[]()
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> The one who loops prompts — a universal LLM pipeline tuning workbench.
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PromptLooper is a self-hosted tool for systematically optimizing LLM prompts, model selection, and inference parameters. It runs experiments across prompt x model x parameter combinations, caches every response, scores results against pluggable evaluation functions, and surfaces the best configurations through a real-time observability dashboard with human-in-the-loop steering.
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It ships as a single Docker container (SQLite mode) for zero-config quickstart, or a Docker Compose stack (Postgres + Redis) for production use. An MCP server enables any AI agent to drive PromptLooper programmatically — creating experiments, running sweeps, and reading results without human intervention.
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## Quick Start
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### Single Container (zero dependencies)
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```bash
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docker run -p 8400:8400 -v promptlooper-data:/data ghcr.io/xpltdco/promptlooper
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```
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Open `http://localhost:8400` — you'll be prompted to create an admin account on first boot.
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### Production (Docker Compose)
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```bash
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git clone git@git.xpltd.co:xpltdco/promptlooper.git
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cd promptlooper
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cp .env.example .env
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# Edit .env — set POSTGRES_PASSWORD and JWT_SECRET at minimum
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docker compose up -d
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```
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## Features
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- **Systematic experimentation** — grid, random, and guided sweeps across prompt x model x parameter space
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- **Response caching** — SHA-256 deduplication means re-runs cost zero tokens
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- **Pluggable scoring** — embedding similarity, format compliance, keyword presence, LLM-as-judge, human rating, custom webhooks
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- **Real-time dashboard** — live progress, leaderboard, side-by-side comparison, steering controls
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- **MCP server** — AI agents can create experiments, run sweeps, and export results programmatically
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- **Single-container mode** — SQLite + in-process queue when no external dependencies are configured
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## Development
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```bash
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# Start backing services
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docker compose up -d promptlooper-db promptlooper-redis
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# Backend
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cd backend && pip install -r requirements.txt
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alembic upgrade head
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uvicorn main:app --reload --host 0.0.0.0 --port 8000
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# Frontend (separate terminal)
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cd frontend && npm install && npm run dev
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```
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## Testing
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```bash
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cd backend && pytest
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cd frontend && npm test
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```
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## License
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[AGPL-3.0](https://www.gnu.org/licenses/agpl-3.0.html)
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