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openai
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openai
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dashscope
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dashscope
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langchain
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langchain-deepseek
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langchain-community
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llama-index
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llama-index-core
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llama-index-llms-dashscope
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llama-index-indices-managed-dashscope
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15
test/langchain/compatible/deepseek.py
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15
test/langchain/compatible/deepseek.py
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from langchain_openai import ChatOpenAI
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from langchain_deepseek import ChatDeepSeek
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import os
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chatLLM = ChatDeepSeek(
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api_key=os.getenv("DASHSCOPE_API_KEY"),
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base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",
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model="deepseek-chat", # 此处以qwen-plus为例,您可按需更换模型名称。模型列表:https://help.aliyun.com/zh/model-studio/getting-started/models
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# other params...
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)
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messages = [
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": "你是谁?"}]
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response = chatLLM.invoke(messages)
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print(response.model_dump_json())
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15
test/langchain/qwen.py
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test/langchain/qwen.py
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import getpass
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import os
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if not os.environ.get("DEEPSEEK_API_KEY"):
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os.environ["DEEPSEEK_API_KEY"] = os.environ['DASHSCOPE_API_KEY']
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from langchain.chat_models import init_chat_model
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model = init_chat_model("qwen-max", model_provider="deepseek")
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messages = [
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": "你是谁?"}]
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response = model.invoke(messages)
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print(response.model_dump_json())
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52
test/llamaindex/test_20250826_1.ipynb
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52
test/llamaindex/test_20250826_1.ipynb
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{
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"cells": [
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{
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"metadata": {},
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"cell_type": "raw",
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"source": [
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"from llama_index.llms.dashscope import DashScope\n",
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"from llama_index.llms.openai import OpenAI\n",
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"\n",
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"llm = DashScope(model_name=\"qwen-max\") # 设置检索引擎生成回答时调用的大模型。"
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],
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"id": "a5d3b9e1d4e6588f"
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},
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{
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"cell_type": "code",
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"id": "initial_id",
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"metadata": {
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"collapsed": true,
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"jupyter": {
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"is_executing": true
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}
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},
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"source": [
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"response = llm.complete(\"William Shakespeare is \")\n",
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"print(response)"
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],
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"outputs": [],
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"execution_count": null
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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41
test/llamaindex/test_20250826_1.py
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41
test/llamaindex/test_20250826_1.py
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from llama_index.core.base.llms.types import ChatMessage
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from llama_index.llms.dashscope import DashScope
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import asyncio
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llm = DashScope(model_name="qwen-max") # 设置检索引擎生成回答时调用的大模型。
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def test1():
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response = llm.complete("William Shakespeare is ")
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print(response)
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async def test2():
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response = await llm.acomplete("William Shakespeare is ")
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print(response)
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def test3():
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response = llm.stream_complete("William Shakespeare is ")
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for chunk in response:
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print(chunk)
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def test4():
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handle = llm.stream_complete("William Shakespeare is ")
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for token in handle:
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print(token.delta, end="", flush=True)
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def test5():
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messages = [
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ChatMessage(role="system", content="You are a helpful assistant."),
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ChatMessage(role="user", content="Tell me a joke."),
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]
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chat_response = llm.chat(messages)
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print(chat_response)
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if __name__ == '__main__':
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# test1()
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# asyncio.run(test2())
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# test3()
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# test4()
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test5()
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44
test/llamaindex/test_20250826_2.ipynb
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44
test/llamaindex/test_20250826_2.ipynb
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{
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"cells": [
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{
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"metadata": {},
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"cell_type": "raw",
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"source": "print(\"hello\")",
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"id": "a5d3b9e1d4e6588f"
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},
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{
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"cell_type": "code",
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"id": "initial_id",
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"metadata": {
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"collapsed": true,
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"jupyter": {
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"is_executing": true
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}
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},
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"source": "",
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"outputs": [],
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"execution_count": null
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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