OpenAIFunctionsAgentOutputParser: LangChain处理OpenAI函数输出的输出解析。 agent = … | … | … |: Langchain表达式语言接口,它允许您通过提供一个简单的界面,使用Unix管道符号|来构建复杂的酷炫代理,结合了模型和提示等构建模块。 AgentExecutor: LangChain框架,充当代理的运行时。它负责执行代理的决策过程、调用...
Thank you for reaching out and providing a detailed description of your issue. Yes, streaming is supported in the OpenAIFunctionsAgent in the LangChain framework. The 'TypeError: 'async_generator' object is not subscriptable' error you're encountering is likely due to trying to access the result...
agent.run("whats my name") The agent has responded with the name fetched from the memory so the memory is running successfully with the agent: That’s all for now. Conclusion To add the memory to the OpenAI functions agent in LangChain, install the modules to get the dependencies for imp...
from langchain.tools import ShellTool, format_tool_to_openai_function tools = [ShellTool()] functions = [format_tool_to_openai_function(t) for t in tools] message = model.predict_messages([HumanMessage(content='count how many lines in a.txt?')], functions=functions) print(message.addition...
如果有了解Langchain的朋友会发现,这不就是agent的功能吗?是的,OPENAI将这个功能“抄“到了自己的API接口服务中。让整个流程更加丝滑合理,符合逻辑。具体的差距后面会讲。下面我们先了解一下functions的参数。 functions具体参数介绍 functions 是 ChatCompletion API 中的可选参数,可用于提供函数规范。这样做的目的是...
I was able to fix this by passing the system message explicitly to the cls.create_prompt()-function in the OpenAI functions agent class. Inlangchain\agents\openai_functions_agent\base.pyi modified these lines: line 244: # check if system_message in kwargs and pass it to create_prompt if...
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在深入探讨 Azure OpenAI 与 LangChain 结合的应用时,我们经常提到 Agent 代理这个概念,但并未在基础篇中给出具体的示例。今天,我们将通过一个实战案例,来详细解读 Agent 的功能与用法。Agent 代理在任务执行中的角色是关键的。Chain 是链条任务,它提供了一个固定的执行流程。然而,在面对复杂且动态...
Step 6: Creating the Agent Once the tools are configured, simply build the agent using the OPENAI_FUNCTIONS type after configuring the llm using the ChatOpenAI() method: from langchain.agentsimportAgentType from langchain.agentsimportinitialize_agent ...
Langchain:特别是LCEL,这是用于构建大型语言模型(LLM)应用的编排框架。 OpenAI:提供我们需要的大型语言模型(LLM)。 FAISS-cpu:用作向量存储解决方案。 数据源:我们使用ArxivLoader来检索arXiv上发表文章的元数据。 4 代码实现 安装所需的依赖项: !pip install -qU langchain langchain_openai langgraph arxiv du...