such as using LangSmith for fine-tuning, AI decision-making with LangSmith, deploying LLMs with LangSmith, and more. It also includes information on LangChain Hub and upcoming webinars. LangChain is a platform for debugging, testing, evaluating, and monitoring LLM applications."    }    ```        > Finished chain.    The LangChain blog features posts on topics such as using LangSmith for fine-tuning, AI decision-making with LangSmith, deploying LLMs with LangSmith, and more. It also includes information on LangChain Hub and upcoming webinars. LangChain is a platform for debugging, testing, evaluating, and monitoring LLM applications.Use off the shelf agent‚Äãllm = ChatOpenAI(temperature=0) # Also works well with Anthropic modelsagent_chain = initialize_agent(tools, llm, agent=AgentType.STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION, verbose=True)response = await agent_chain.ainvoke({"input": "Browse to blog.langchain.dev and summarize the text, please."})print(response['output'])            > Entering new AgentExecutor chain...    Action:    ```    {      "action": "navigate_browser",      "action_input": {        "url": "https://blog.langchain.dev"      }    }    ```    Observation: Navigating to https://blog.langchain.dev returned status code 200    Thought:I have successfully navigated to the blog.langchain.dev website. Now I need to extract the text from the webpage to summarize it.    Action:    ```    {      "action": "extract_text",      "action_input": {}    }    ```    Observation: LangChain LangChain Home GitHub Docs By LangChain Release Notes Write with Us Sign in Subscribe The official LangChain blog. Subscribe now Login Featured Posts Announcing LangChain Hub Using LangSmith to Support Fine-tuning Announcing LangSmith, a unified platform for debugging, testing, evaluating, and monitoring your LLM applications Sep 20 Peering Into the Soul of AI Decision-Making with LangSmith 10 min read Sep 20 LangChain + Docugami Webinar: Lessons from Deploying LLMs with
The structured tool chat agent is capable of using multi-input tools.
The structured tool chat agent is capable of using multi-input tools. ->: such as using LangSmith for fine-tuning, AI decision-making with LangSmith, deploying LLMs with LangSmith, and more. It also includes information on LangChain Hub and upcoming webinars. LangChain is a platform for debugging, testing, evaluating, and monitoring LLM applications."    }    ```        > Finished chain.    The LangChain blog features posts on topics such as using LangSmith for fine-tuning, AI decision-making with LangSmith, deploying LLMs with LangSmith, and more. It also includes information on LangChain Hub and upcoming webinars. LangChain is a platform for debugging, testing, evaluating, and monitoring LLM applications.Use off the shelf agent‚Äãllm = ChatOpenAI(temperature=0) # Also works well with Anthropic modelsagent_chain = initialize_agent(tools, llm, agent=AgentType.STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION, verbose=True)response = await agent_chain.ainvoke({"input": "Browse to blog.langchain.dev and summarize the text, please."})print(response['output'])            > Entering new AgentExecutor chain...    Action:    ```    {      "action": "navigate_browser",      "action_input": {        "url": "https://blog.langchain.dev"      }    }    ```    Observation: Navigating to https://blog.langchain.dev returned status code 200    Thought:I have successfully navigated to the blog.langchain.dev website. Now I need to extract the text from the webpage to summarize it.    Action:    ```    {      "action": "extract_text",      "action_input": {}    }    ```    Observation: LangChain LangChain Home GitHub Docs By LangChain Release Notes Write with Us Sign in Subscribe The official LangChain blog. Subscribe now Login Featured Posts Announcing LangChain Hub Using LangSmith to Support Fine-tuning Announcing LangSmith, a unified platform for debugging, testing, evaluating, and monitoring your LLM applications Sep 20 Peering Into the Soul of AI Decision-Making with LangSmith 10 min read Sep 20 LangChain + Docugami Webinar: Lessons from Deploying LLMs with