{
    "messages": [
        {
            "role": "system",
            "content": "Assistant is a large language model trained by OpenAI.\n\nAssistant is designed to be able to assist with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics. As a language model, Assistant is able to generate human-like text based on the input it receives, allowing it to engage in natural-sounding conversations and provide responses that are coherent and relevant to the topic at hand.\n\nAssistant is constantly learning and improving, and its capabilities are constantly evolving. It is able to process and understand large amounts of text, and can use this knowledge to provide accurate and informative responses to a wide range of questions. Additionally, Assistant is able to generate its own text based on the input it receives, allowing it to engage in discussions and provide explanations and descriptions on a wide range of topics.\n\nOverall, Assistant is a powerful system that can help with a wide range of tasks and provide valuable insights and information on a wide range of topics. Whether you need help with a specific question or just want to have a conversation about a particular topic, Assistant is here to assist. However, above all else, all responses must adhere to the format of RESPONSE FORMAT INSTRUCTIONS."
        },
        {
            "role": "user",
            "content": "TOOLS\n------\nAssistant can ask the user to use tools to look up information that may be helpful in answering the users original question. The tools the human can use are:\n\ninfo-tool: Useful for situations where you need to retrieve content through one or more URLs from https://info.bilibili.co/. Input should be a comma-separated list in the format of \"one or more valid URLs with the domain https://info.bilibili.co/pages/viewpage.action, where the URL should include the pageId parameter\", followed by \"the information you need to summarize, or to obtain a summary\".\n\nRESPONSE FORMAT INSTRUCTIONS\n----------------------------\n\nOutput a JSON markdown code snippet containing a valid JSON object in one of two formats:\n\n**Option 1:**\nUse this if you want the human to use a tool.\nMarkdown code snippet formatted in the following schema:\n\n```json\n{\n    \"action\": string, // The action to take. Must be one of [info-tool]\n    \"action_input\": string // The input to the action. May be a stringified object.\n}\n```\n\n**Option #2:**\nUse this if you want to respond directly and conversationally to the human. Markdown code snippet formatted in the following schema:\n\n```json\n{\n    \"action\": \"Final Answer\",\n    \"action_input\": string // You should put what you want to return to use here and make sure to use valid json newline characters.\n}\n```\n\nFor both options, remember to always include the surrounding markdown code snippet delimiters (begin with \"```json\" and end with \"```\")!\n\n\nUSER'S INPUT\n--------------------\nHere is the user's input (remember to respond with a markdown code snippet of a json blob with a single action, and NOTHING else):\n\nhttps://info.bilibili.co/pages/viewpage.action?pageId=849684529\n這篇文章講了什么"
        }
    ]
}

// POST /chat/completions
{
  ...
  "tools": [
      {
        "type": "function",
        "function": {
          "name": "info-tool",
          "description": "打開一個或多個帶有pageId的xxxx網(wǎng)站，完成用戶需求",
          "parameters": {
            "type": "object",
            "properties": {
              "pageId": {
                "type": "number",
                "description": "請?zhí)顚懢W(wǎng)址里的pageId,多個用逗號隔開"
              },
              "task": {
                "type": "string",
                "description": "描述需求"
              }
            },
            "required": [
              "pageId",
              "task"
            ],
            "additionalProperties": false,
            "$schema": "http://json-schema.org/draft-07/schema#"
          }
        }
      },
      ...更多其他工具
  ],
  ...
}

// API Response
{
    ...
    "tool_calls": [
        {
            "index": 0,
            "id": "info-tool:0",
            "type": "function",
            "function": {
            "name": "info-tool",
            "arguments": "{\n    \"task\": \"獲取頁面內(nèi)容\",\n    \"pageId\": 845030990\n}"
            }
        }
    ]
    ...
}

import { AgentExecutor } from 'langchain/agents'
 
// 將工具的配置信息轉(zhuǎn)為model接口里tools的結(jié)構(gòu)化字段
// 由于對齊了接口規(guī)范,所以可以直接使用formatToOpenAITool函數(shù)
const modelWithTools = model.bind({
    tools: [...tools.map((tool: any) => formatToOpenAITool(tool))]
})
 
// 按順序組合
const runnableAgent = RunnableSequence.from([
    // 包含了用戶的指令,和將模型消息里的tool_calls format后得到的ToolMessage,和上下文聊天記錄
    // 以上這些都會輸入給prompt
    {
        [inputKey]: (i: { input: string; steps: AgentStep[] }) => i.input,
        agent_scratchpad: (i: { input: string; steps: ToolsAgentStep[] }) => formatToolAgentSteps(i.steps),
        [memoryKey]: async (_: { input: string; steps: AgentStep[] }) => {
            const messages = (await memory.getChatMessages(flowObj?.sessionId, true, chatHistory)) as BaseMessage[]
            return messages ?? []
        }
    },
    prompt,
    modelWithTools,
    new OpenAIToolsAgentOutputParser()
])
 
const executor = AgentExecutor.fromAgentAndTools({
    agent: runnableAgent,
    tools,
    returnIntermediateSteps: true,
    maxIterations: 5
})
 
executor.invoke({input: '明天是幾月幾號?'})
 
// tool_calls示例
{
    "tool_calls": [
      {
        "index": 0,
        "id": "GetDate:0",
        "type": "function",
        "function": {
          "name": "GetDate",
          "arguments": "{\n    \"task\": \"獲取明天的日期\"\n}"
        }
      }
    ]
}