智能客服

import os
from openai import OpenAI

client = OpenAI(base_url="https://www.tutujin.com/v1", api_key=os.environ["TUTUJIN_API_KEY"])

SYSTEM = (
    "You are the support assistant of an online store. Answer only from the reference material. "
    "If the material does not cover the question, or it is about a refund dispute, legal or medical matters, "
    "reply with the single word HANDOFF so a human agent takes over."
)


def classify(message):
    """Cheap intent check before the main model: order, product, complaint or other."""
    resp = client.chat.completions.create(
        model="gemini-2.5-flash-lite",
        messages=[
            {"role": "system", "content": "Classify the message as order, product, complaint or other. Reply with the label only."},
            {"role": "user", "content": message},
        ],
        max_tokens=5,
        temperature=0,
    )
    return resp.choices[0].message.content.strip().lower()


def reply_stream(message, references, history):
    messages = [{"role": "system", "content": SYSTEM + "\n\nReference material:\n" + references}]
    messages += history[-6:]  # keep only the last few turns
    messages.append({"role": "user", "content": message})
    stream = client.chat.completions.create(
        model="qwen3.5-plus",
        messages=messages,
        stream=True,
        temperature=0.3,
    )
    for chunk in stream:
        if chunk.choices and chunk.choices[0].delta.content:
            yield chunk.choices[0].delta.content


message = "When will my order ship?"
if classify(message) == "complaint":
    print("-> human agent")
else:
    # references: top matches from your knowledge base, embedded with text-embedding-3-small
    references = "In-stock orders ship within 48 hours of payment. Pre-orders ship on the date shown on the product page."
    reply = ""
    for piece in reply_stream(message, references, history=[]):
        reply += piece
        print(piece, end="", flush=True)
    if "HANDOFF" in reply:
        print("\n-> human agent")