48 lines
1.4 KiB
Python
48 lines
1.4 KiB
Python
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import json
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from zhipuai import ZhipuAI
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import flask
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# client = ZhipuAI(api_key="73bdeed728677bc80efc6956478a2315.VerNWJMCwN9L5gTi") # 请填写您自己的APIKey
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# response = client.chat.completions.create(
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# model="glm-4", # 请填写您要调用的模型名称
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# messages=[
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# {"role": "user", "content": "你好"},
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# ],
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# )
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# print(response.choices[0].message)
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app = flask.Flask(__name__)
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@app.route("/chat", methods=['POST'])
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def app_chat():
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data = json.loads(flask.globals.request.get_data())
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# print(data)
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uid = data["user_id"]
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if not data["text"][-1] in ['?', '？', '.', '。', ',', '，', '!', '！']:
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data["text"] += "。"
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# 使用ZhipuAI库调用模型生成回复
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client = ZhipuAI(api_key="73bdeed728677bc80efc6956478a2315.VerNWJMCwN9L5gTi") # 请填写您自己的APIKey
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response = client.chat.completions.create(
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model="glm-4-flash", # 请填写您要调用的模型名称
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messages=[
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{"role": "user", "content": data["text"]},
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],
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)
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# 获取模型的回复
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resp = response.choices[0].message.content
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if resp:
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return json.dumps({"user_id": data["user_id"], "text": resp, "error": False, "error_msg": ""})
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else:
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return json.dumps({"user_id": data["user_id"], "text": "", "error": True, "error_msg": "模型未返回回复"})
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if __name__ == '__main__':
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app.run(host="0.0.0.0", port=11111)
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