output = AgentAction(tool="dummy", tool_input=result, log=result)# 名字要等与前面的”dummy“ else: output = AgentFinish(...)# 名字要等与前面的”dummy“ return output 就是这么简单 需要注意的是,tools的返回结果会再次返回llm确定是否触发AgentFinish,当然也可以用max_iteration和max_time在AgentExecu...
在langchain agent中,如何控制工具调用的顺序 在medium的这篇文章中,作者详细介绍了langchain 是如何调用tools的,感兴趣的可以直接参考这篇文章(medium的这篇文章是收费的,可以直接参考代码:https://github.com/sagaruprety/tutorial_langchain_agents/blob/main/langchain_documents_qa_serp_tools.ipynb) 我感兴趣的...
AgentGPT 通过https://agentgpt.reworkd.ai/：决定将此任务视为合成数据生成器，这不是我们询问的内容...
def create_agent(prompt, llm_with_tools): runnable_agent = ( { "input": lambda x: x["input"], "agent_scratchpad": lambda x: format_to_openai_tool_messages( x["intermediate_steps"] ), } | prompt | llm_with_tools | OpenAIToolsAgentOutputParser() ) return AgentExecutor(agent=runnable...
Checked other resources I added a very descriptive title to this issue. I searched the LangChain documentation with the integrated search. I used the GitHub search to find a similar question and didn't find it. I am sure that this is a b...
agent=initialize_agent(tools,llm,agent="zero-shot-react-description",verbose=True) agent.run("In what year was the film Departed with Leopnardo Dicaprio released? What is this year raised to the 0.43 power?") Memory¶ Add state to Chains and Agents. ...
> Entering new AgentExecutor chain... I should search for LangChain to see what it is Action: tavily_search_results_json Action Input: "LangChain"[{'url': 'https://towardsdatascience.com/getting-started-with-langchain-a-beginners-guide-to-building-llm-powered-applications-95fc8898732c', ...
得到的只是模板结果,之后还需要chain去具体执行 by integrating LLM with this template。 fromlangchain.promptsimport(ChatPromptTemplate,SystemMessagePromptTemplate,AIMessagePromptTemplate,HumanMessagePromptTemplate, )system_template="You are a professional translator that translates {src_lang} to {dst_lang}."...
The AI agent often struggles when it needs to perform mathematical and symbolic reasoning to produce a response. By integrating Azure Container Apps dynamic sessions with LangChain, you give the agent a code interpreter to use to perform specialized tasks. In this tutorial, you learn how to run...
model, and then pass the output through an (optional) output parser.\nNext steps\u200b\nWe've touched on how to build an application with LangChain, how to trace it with LangSmith, and how to serve it with LangServe.\n"}]I shouldreadthe LangChain tutorial to learnmoreabout Lang...