chaos
5d215e1649
- tools/scripts/llm-key-hunter: GitHub leak hunting pipeline (hunt_*, pivot miner, two-layer verify/content caches, per-provider verification) - usable_keys: verified key vault across 12 providers (deepseek, minimax, volcanoark, longcat, codingplan, zhipu free-tier, mimo, siliconflow, etc.) - .grok/skills/llm-key-hunter: operator skill for the hunt/verify/vault flow - NewAPI channel import scripts and CDP capture helpers - Result verdict buckets (excluding multi-GB blob caches and dedup dumps)
35 lines
1.2 KiB
Plaintext
35 lines
1.2 KiB
Plaintext
import os
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os.environ["ZHIPUAI_API_KEY"] = "53ca6a88a682be774f7c07ad856b5d42.5Hczmqc5Cz3d4WBM"
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os.environ["IFLYTEK_SPARK_APP_ID"] = "1a2c0e22"
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os.environ["IFLYTEK_SPARK_API_KEY"] = "91ac602cffda5c10bbb78fc314f8525d"
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os.environ["IFLYTEK_SPARK_API_SECRET"] = "ODYyMWEzMDViNGVjMWZjYWQyMmE5YWJi" # 这个key来自老师
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# 此处参考：https://www.xfyun.cn/doc/spark/Web.html
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os.environ["IFLYTEK_SPARK_API_URL"] = "wss://spark-api.xf-yun.com/v3.1/chat"
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os.environ["IFLYTEK_SPARK_llm_DOMAIN"] = "generalv3"
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from langchain_community.chat_models import ChatZhipuAI
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zhipuai_model = ChatZhipuAI(
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model="glm-4",
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# temperature=0.9,
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)
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from langchain_community.chat_models import ChatSparkLLM
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spark_chat_model = ChatSparkLLM()
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MyModel = spark_chat_model
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import streamlit as st
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text = st.text_area(label='输入问题，最大200字，ctrl+enter发送。'
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'(此问答以大语言模型api为基础,通过LangChain构建对话,streamlit搭建web界面)',
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value='你好......',
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height=5,
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max_chars=200,
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help='最大长度限制为200')
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st.write("正在思考：", text)
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response = MyModel.invoke(text)
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st.write('回答：', response.content)
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