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Question

So I’m using langchain js for my front-end application ( i know I shouldn’t do that but I use azure oauth so I’m fine), My application is in react and whenevever I try using langchain agents in the front-end it always throws error.

I found a guy with a similar issue -> LangChain simple llm.predict in Angular returns empty result

but he is not using agents

Example Code

export const GPTmodel = (model, temp) => {
  return new ChatOpenAI({
        model,
        temperature,
        configuration: {
            baseURL: LLM_GATEWAY_BASE_URL,
            dangerouslyAllowBrowser: true,
            defaultHeaders: {
              blabla
            },
        },
        azureOpenAIBasePath: `ourpath`,
        azureOpenAIApiDeploymentName: model,
        azureOpenAIApiVersion: '2024-02-01',
        azureOpenAIApiKey: 'fake-key-we-use-auth',

}


export const ProcessMiningTutor = async () => {
    const llm = GPTmodel(GPTModel.GPT4, 0);

    const promptTemplate = SystemMessagePromptTemplate.fromTemplate(`
    answer the user question in a funny and rap like way.
    The user question is: {input}
    also what is the value of foo?
    `);

    const prompt = ChatPromptTemplate.fromMessages([
        [ 'system', 'You are a helpful assistant.' ],
        promptTemplate,
        new MessagesPlaceholder('agent_scratchpad'),
    ]);
    const tools = [
        new DynamicTool({
            name: 'FOO',
            description: 'call this to get the value of foo.',
            // eslint-disable-next-line @typescript-eslint/require-await
            func: async () => 'baz',
        }),
    ];

    const agent = await createOpenAIFunctionsAgent({
        llm,
        prompt,
        tools,
    });

    return new AgentExecutor({
        agent,
        tools,
        verbose: true,
    }).withConfig({ runName: 'Agent' });
};



then when I call it 


 const {
        isLoading, error,
    } = useQuery(
        {
            // eslint-disable-next-line @stylistic/max-len
            queryKey: [ 'agentResponse', currentQuestion?.id, currentQuestion, currentQuestion?.agent, currentQuestion?.question, askedQuestions ],
            queryFn: async () => {
                if (!currentQuestion) {
                    return;
                }
                console.log(currentQuestion);
                // I have multiple agents so just think I'm giving the agent from above
                const agentName = currentQuestion.agent;
                const agentCreator = agentRegistry[agentName];
                const executor = (await agentCreator()) as AgentExecutor;

               // this thing ALWAYS fails. 
                const result = executor.streamEvents({ input: currentQuestion.question }, { version: 'v1' });

                for await (const event of result) {
                    const eventType = event.event;
                    if (eventType === 'on_chain_start') {
                        // Was assigned when creating the agent with `.withConfig({"runName": "Agent"})` above
                        if (event.name === 'Agent') {
                            console.log('n-----');
                            console.log(
                                `Starting agent: ${event.name} with input: ${JSON.stringify(
                                    event.data.input,
                                )}`,
                            );
                        }
                    } else if (eventType === 'on_chain_end') {
                        // Was assigned when creating the agent with `.withConfig({"runName": "Agent"})` above
                        if (event.name === 'Agent') {
                            console.log('n-----');
                            console.log(`Finished agent: ${event.name}n`);
                            console.log(`Agent output was: ${event.data.output}`);
                            console.log('n-----');
                        }
                    } else if (eventType === 'on_llm_stream') {
                        const content = event.data?.chunk?.message?.content;
                        // Empty content in the context of OpenAI means
                        // that the model is asking for a tool to be invoked via function call.
                        // So we only print non-empty content
                        if (content !== undefined && content !== '') {
                            console.log(`| ${content}`);
                        }
                    } else if (eventType === 'on_tool_start') {
                        console.log('n-----');
                        console.log(
                            `Starting tool: ${event.name} with inputs: ${event.data.input}`,
                        );
                    } else if (eventType === 'on_tool_end') {
                        console.log('n-----');
                        console.log(`Finished tool: ${event.name}n`);
                        console.log(`Tool output was: ${event.data.output}`);
                        console.log('n-----');
                    }
                }

Description

I’m trying to use langchain to create an agent with openai functions/tools.
My application is living fully in the front-end. React.

In my network tab I can see the response of the llm is SUCCESSFUL I CAN SEE THE CONTENT but

@tanstack_react-query.js?v=77745d11:2942 Uncaught TypeError: Cannot read properties of undefined (reading 'content')
    at OpenAIFunctionsAgentOutputParser._baseMessageToString (chunk-NSISG4FD.js?v=77745d11:32:27)
    at OpenAIFunctionsAgentOutputParser._callWithConfig (chunk-NSISG4FD.js?v=77745d11:54:22)
    at OpenAIFunctionsAgentOutputParser._callWithConfig (chunk-2YXJZ3EI.js?v=77745d11:12447:28)
    at async OpenAIFunctionsAgentOutputParser._streamIterator (chunk-2YXJZ3EI.js?v=77745d11:12392:5)
    at async OpenAIFunctionsAgentOutputParser.transform (chunk-2YXJZ3EI.js?v=77745d11:12612:5)
    at async _RunnableSequence._streamIterator (chunk-2YXJZ3EI.js?v=77745d11:13336:24)

then after using verbose: true on the agent ->

 Entering LLM run with input: {
  "messages": [
    [
      {
        "lc": 1,
        "type": "constructor",
        "id": [
          "langchain_core",
          "messages",
          "SystemMessage"
        ],
        "kwargs": {
          "content": "You are a helpful assistant.",
          "additional_kwargs": {},
          "response_metadata": {}
        }
      },
      {
        "lc": 1,
        "type": "constructor",
        "id": [
          "langchain_core",
          "messages",
          "SystemMessage"
        ],
        "kwargs": {
          "content": "n    answer the user question in a funny and rap like way.
    The user question is: what the dawg doing?
    also what is the value of foo?  ",
          "additional_kwargs": {},
          "response_metadata": {}
        }
      }
    ]
  ]
}
chunk-2YXJZ3EI.js?v=77745d11:5262 [llm/end] [1:chain:Agent > 2:chain:OpenAIFunctionsAgent > 7:llm:ChatOpenAI] [1.28s] Exiting LLM run with output: {
  "generations": [
    [
      null
    ]
  ]
}
chunk-2YXJZ3EI.js?v=77745d11:5225 [chain/start] [1:chain:Agent > 2:chain:OpenAIFunctionsAgent > 8:parser:OpenAIFunctionsAgentOutputParser] Entering Chain run with input: {}
chunk-2YXJZ3EI.js?v=77745d11:5243 [chain/error] [1:chain:Agent > 2:chain:OpenAIFunctionsAgent > 8:parser:OpenAIFunctionsAgentOutputParser] [0ms] Chain run errored with error: "Cannot read properties of undefined (reading 'content')nnTypeError: Cannot read properties of undefined (reading 'content')n    at OpenAIFunctionsAgentOutputParser._baseMessageToString (http://localhost:9000/node_modules/.vite/deps/chunk-NSISG4FD.js?v=77745d11:32:27)n    at OpenAIFunctionsAgentOutputParser._callWithConfig (http://localhost:9000/node_modules/.vite/deps/chunk-NSISG4FD.js?v=77745d11:54:22)n    at OpenAIFunctionsAgentOutputParser._callWithConfig (http://localhost:9000/node_modules/.vite/deps/chunk-2YXJZ3EI.js?v=77745d11:12447:28)n    at async OpenAIFunctionsAgentOutputParser._streamIterator (http://localhost:9000/node_modules/.vite/deps/chunk-2YXJZ3EI.js?v=77745d11:12392:5)n    at async OpenAIFunctionsAgentOutputParser.transform (http://localhost:9000/node_modules/.vite/deps/chunk-2YXJZ3EI.js?v=77745d11:12612:5)n    at async _RunnableSequence._streamIterator (http://localhost:9000/node_modules/.vite/deps/chunk-2YXJZ3EI.js?v=77745d11:13336:24)"

But i can see the network tab
that the responce is there -_-

System Info

“@langchain/core”: “^0.2.31”,
“@langchain/openai”: “^0.2.10”,
“langchain”: “^0.3.0”,

platform macos
node version -> Node.js v20.12.2.
npm version 10.8.2

I tried making a custom output parser didnt work.

Thiết kế website giá rẻ

Danh mục

when using langchain agent in front-end it always returns error – Exiting LLM run with output: { “generations”: [ [ null ] ] }

Description

System Info