Building a Production Chatbot

Production Chatbot Architecture

# FastAPI chatbot with Redis session history
from fastapi import FastAPI
from pydantic import BaseModel
import anthropic, redis, json

app    = FastAPI()
client = anthropic.Anthropic()
r      = redis.Redis(decode_responses=True)

class ChatRequest(BaseModel):
    session_id: str
    message: str

@app.post('/chat')
async def chat(req: ChatRequest):
    # Load history
    key     = 'chat:' + req.session_id
    history = json.loads(r.get(key) or '[]')

    # Add user message
    history.append({'role':'user','content':req.message})
    if len(history) > 20:
        history = history[-20:]  # sliding window

    # Call LLM
    response = client.messages.create(
        model='claude-opus-4-5', max_tokens=500,
        system='You are a helpful customer support agent for EzyCoders.',
        messages=history
    )
    reply = response.content[0].text

    # Persist updated history
    history.append({'role':'assistant','content':reply})
    r.setex(key, 3600, json.dumps(history))  # 1hr TTL

    return {'reply': reply, 'session_id': req.session_id}