tool_calls

[CONVEX A(public/messages:create)] [Request ID: 7ffca58ab010e094] Server Error
Uncaught AI_APICallError: An assistant message with 'tool_calls' must be followed by tool messages responding to each 'tool_call_id'. The following tool_call_ids did not have response messages: call_GYArlXZG4Pn4dSe8RNk3ICov

[CONVEX A(public/messages:create)] [Request ID: 7ffca58ab010e094] Server Error
Uncaught AI_APICallError: An assistant message with 'tool_calls' must be followed by tool messages responding to each 'tool_call_id'. The following tool_call_ids did not have response messages: call_GYArlXZG4Pn4dSe8RNk3ICov

await supportAgent.generateText(
        ctx,
        { threadId: args.threadId },
        {
          prompt: args.propt,
          tools: {
            searchTool: search,
          },
        },
      );

await supportAgent.generateText(
        ctx,
        { threadId: args.threadId },
        {
          prompt: args.propt,
          tools: {
            searchTool: search,
          },
        },
      );

export const search = createTool({
  description:
    "Search the knowledge base for relevant information to help answer user questions",
  args: z.object({
    query: z.string().describe("The search query to find relevant information"),
  }),
  handler: async (ctx, args) => {
    const conversation = await ctx.runQuery(
      internal.system.conversations.getByThreadId,
      { threadId: ctx.threadId },
    );

    const searchResault = await rag.search(ctx, {
      namespace: conversation.organizationId,
      query: args.query,
      limit: 5,
    });

    const contextText = `Found results in ${searchResault.entries
      .map((e) => e.title || null)
      .filter((t) => t !== null)
      .join(", ")}. Here is the context:\n\n${searchResault.text}`;

    const response = await generateText({
      messages: [
        {
          role: "system",
          content: SEARCH_INTERPRETER_PROMPT,
        },
        {
          role: "user",
          content: `User asked:"${args.query}"\n\nSearch results:${contextText}`,
        },
      ],
      model: openai.chat("gpt-4o-mini"),
    });
    await supportAgent.saveMessage(ctx, {
      threadId: ctx.threadId,
      message: { role: "assistant", content: response.text },
    });
    console.log("Search tool response:", response);
    return response.text;
  },
});

export const search = createTool({
  description:
    "Search the knowledge base for relevant information to help answer user questions",
  args: z.object({
    query: z.string().describe("The search query to find relevant information"),
  }),
  handler: async (ctx, args) => {
    const conversation = await ctx.runQuery(
      internal.system.conversations.getByThreadId,
      { threadId: ctx.threadId },
    );

    const searchResault = await rag.search(ctx, {
      namespace: conversation.organizationId,
      query: args.query,
      limit: 5,
    });

    const contextText = `Found results in ${searchResault.entries
      .map((e) => e.title || null)
      .filter((t) => t !== null)
      .join(", ")}. Here is the context:\n\n${searchResault.text}`;

    const response = await generateText({
      messages: [
        {
          role: "system",
          content: SEARCH_INTERPRETER_PROMPT,
        },
        {
          role: "user",
          content: `User asked:"${args.query}"\n\nSearch results:${contextText}`,
        },
      ],
      model: openai.chat("gpt-4o-mini"),
    });
    await supportAgent.saveMessage(ctx, {
      threadId: ctx.threadId,
      message: { role: "assistant", content: response.text },
    });
    console.log("Search tool response:", response);
    return response.text;
  },
});