hack/tools/scripts/llm-key-hunter/results/_cache/content/aigclink_aigc-search.json

{"repo": "aigclink/aigc-search", "files": {"glm-4-long.py": {"09b5bce1964c33d18493052de3d484d1b2ade3c7": {"t": 1785674168.7260768, "n": 1197, "h": "d1b22d4fdb96bc0f", "c": "import requests\nimport uuid\nfrom zhipuai import ZhipuAI\nimport streamlit as st\n\n\napi_key = \"你的API-key\"\n\ndef run_v4_sync(input):\n    msg = [\n        {\n            \"role\": \"user\",\n            \"content\":input\n        }\n    ]\n    tool = \"web-search-pro\"\n    url = \"https://open.bigmodel.cn/api/paas/v4/tools\"\n    request_id = str(uuid.uuid4())\n    data = {\n        \"request_id\": request_id,\n        \"tool\": tool,\n        \"stream\": False,\n        \"messages\": msg\n    }\n\n    resp = requests.post(\n        url,\n        json=data,\n        headers={'Authorization': api_key},\n        timeout=300\n    )\n    return resp.content.decode()\n\n\n\ndef glmlong(m):\n    client = ZhipuAI(api_key=api_key) # 填写您自己的APIKey\n    x=run_v4_sync(m)\n    response = client.chat.completions.create(\n    model=\"glm-4-long\",  # 填写需要调用的模型编码\n    messages=[\n        {\"role\": \"system\", \"content\": \"你是一个搜索内容整合专家助手，你的任务是针对用户搜索内容提供1000字的概括总结，并且备注来源网址。\"},\n        {\"role\": \"user\", \"content\": x}\n            ],\n    stream=False,\n    )\n    return response.choices[0].message.content\n\nif __name__ == '__main__':\n    st.title(\"AIGCLINK：glm-4-long+websearch构建AI搜索最小用例\")\n    user_input = st.text_input(\"输入一些文本：\")\n    st.write(glmlong(user_input))"}}}}