AI chatbot development.
Production conversational AI, model-agnostic.

from anthropic import Anthropic
client = Anthropic()

def chat_turn(user_msg: str, history: list[dict]) -> dict:
    # 1. Intent classify with Haiku 4.5 (~$0.0001 / turn)
    intent = classify_intent(user_msg)

    # 2. RAG retrieve from pgvector (top-k 5, re-ranked)
    docs = retrieve(query=user_msg, k=5, rerank=True)

    # 3. Tool-aware generate — switch the reply model:
    response = client.messages.create(
        model="claude-sonnet-4.6",
        max_tokens=600,
        system=SYSTEM_PROMPT + format_docs(docs),
        tools=[zendesk_create_ticket, order_status_lookup],
        messages=history + [{"role": "user", "content": user_msg}],
    )

    # 4. Guardrail: confidence + PII + policy
    verdict = guardrail.check(response, intent=intent)
    if verdict.action == "escalate":
        return handoff_to_human(response, verdict)

    # 5. Log to Langfuse for nightly eval
    langfuse.log(trace_id, response, verdict, tokens=response.usage)
    return response