feat: brain-engine + brain-ui + docs — template full stack standalone
- brain-engine: server, embed, search, RAG, MCP, start.sh (standalone) - brain-ui: source React complète, build.sh, DocsView avec tier colors - docs: 14 pages guides humains (getting-started, architecture, sessions, workflows, agents, vues tier) - brain-compose.yml v0.9.0: tier featured ajouté, sessions/agents par tier, coach_level, API key schema - DISTRIBUTION_CHECKLIST v1.2: brain-engine + brain-ui + docs dans la checklist
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brain-engine/README.md
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brain-engine/README.md
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---
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name: brain-engine
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type: reference
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context_tier: cold
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---
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# brain-engine — Moteur local
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> Le cerveau du brain. Recherche semantique, API locale, embeddings, BSI.
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---
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## Demarrage rapide
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```bash
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bash brain-engine/start.sh
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```
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Ca fait tout : installe les deps Python, cree brain.db, indexe le corpus si Ollama est present, et lance le serveur sur le port 7700.
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---
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## Prerequis
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- **Python 3.10+** — `sudo apt install python3 python3-pip python3-venv`
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- **Ollama** (optionnel mais recommande) — `curl -fsSL https://ollama.com/install.sh | sh`
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- Modele embedding : `ollama pull nomic-embed-text`
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- Sans Ollama : le serveur tourne mais la recherche semantique n'est pas disponible
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---
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## Architecture
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```
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brain-engine/
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start.sh <- script de demarrage standalone
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server.py <- API HTTP (FastAPI, port 7700)
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mcp_server.py <- MCP server (FastMCP, port 7701)
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embed.py <- pipeline embeddings (Ollama + nomic-embed-text)
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search.py <- recherche cosine similarity + filtre scope
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rag.py <- couche RAG (boot queries + ad-hoc)
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schema.sql <- tables SQLite (claims, signals, embeddings, sessions)
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migrate.py <- migration brain.db
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distill.py <- distillation session memory (featured+)
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requirements.txt <- dependances Python
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```
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---
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## Endpoints principaux
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- `GET /health` — statut du serveur
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- `GET /search?q=` — recherche semantique dans le brain
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- `GET /agents` — liste des agents disponibles
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- `GET /boot` — contexte initial pour une session
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- `GET /workflows` — claims BSI ouverts
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- `GET /tier` — tier actif
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---
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## Mode standalone
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Sans token configure, le serveur donne acces total en localhost. C'est le mode par defaut quand tu forkes le brain.
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Sans cle API (`brain_api_key: null`), le tier est `free` — toutes les fonctionnalites fondamentales sont disponibles.
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---
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## Connexion Claude Code (MCP)
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```bash
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# Lancer le MCP server
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python3 brain-engine/mcp_server.py
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# Ajouter dans Claude Code
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claude mcp add brain --transport http http://localhost:7701/mcp/
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```
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