chappie-backend

name	chappie-backend
description	Backend development for CHAPPiE. Use when working on FastAPI APIs, vLLM brain, Cerebras integration, training daemon, or backend_wrapper.py.

CHAPPiE Backend Development

Stack

• API: FastAPI (port 8010), CORS wildcard
• Brain: vLLM (local), Cerebras (cloud fallback)
• Database: ChromaDB for episodic memory
• Training: daemon_manager subprocess pattern

Key Files

File	Role
api/main.py	App entry, routers, root JSON endpoint
api/routers/*.py	chat, system, memory, runtime, training, context
api/schemas.py	Pydantic models
web_infrastructure/backend_wrapper.py	Main CHAPPiE backend class
brain/vllm_brain.py	vLLM OpenAI-compatible client
brain/base_brain.py	Abstract base + GenerationConfig
Chappies_Trainingspartner/daemon_manager.py	Subprocess daemon control

Generation Pipeline (Two-Step)

1. Step 1: Intent analysis via Cerebras (fast model: llama-3.1-8b)
2. Step 2: Response generation via vLLM (Qwen3.5-4B)
3. Post-processing: Cerebras GPT-OSS-120B formats CoT + Answer

Post-Processing (_format_via_cerebras)

• Method in backend_wrapper.py (~line 602)
• Sends raw CHAPPiE output to Cerebras for formatting
• Returns <cot> + <antwort> tagged blocks
• NEVER changes content — only formatting

Testing Without vLLM

import sys
from unittest.mock import MagicMock
# Mock all brain dependencies before import
sys.modules["ollama"] = MagicMock()
sys.modules["cerebras"] = MagicMock()
sys.modules["chromadb"] = MagicMock()
# Then import from brain.vllm_brain directly

Key Rules

• repetition_penalty muss via extra_body, nicht direkt als Keyword
• enable_thinking=True für Qwen3.5 Modelle (in _prepare_extra_body)
• Reasoning-Loop-Detektor: _detect_reasoning_loop() in vllm_brain.py
• Alle Settings über config.config.settings → update_from_ui() persistiert