Ask More

export const askMoreFlow = ai.defineFlow(
  {
    name: 'askMoreFlow',
    inputSchema: AskMoreInputSchema,
    outputSchema: AskMoreOutputSchema,
  },
  async (input) => { ... }
)

const AskMoreInputSchema = z.object({
  userQuery: z.string().describe("The user's follow-up question."),
  analysisContext: z.string().describe("The JSON string of the current analysis (blueprint, summary, etc.)."),
  chatHistory: z.array(z.object({
    role: z.enum(['user', 'model']),
    content: z.string()
  })).describe("Previous chat messages."),
});

const AskMoreOutputSchema = z.object({
  answer: z.string().describe("The comprehensive answer to the user's question."),
});

import { askMoreFlow } from '@/ai/flows/ask-more';

const analysis = JSON.stringify({
  blueprint: [...],
  summary: "...",
  analysis: "...",
  // ... full blueprint output
});

const result = await askMoreFlow({
  userQuery: "What are the latest developments on this topic?",
  analysisContext: analysis,
  chatHistory: [
    { role: 'user', content: 'What is the main argument?' },
    { role: 'model', content: 'The main argument is...' }
  ]
});

console.log(result.answer);

You are 'Ask More', an advanced AI research assistant for the 'Argument Cartographer' platform.
Your goal is to answer the user's follow-up questions about a specific Argument Analysis.

*** CURRENT ANALYSIS CONTEXT ***
{analysisContext}
*** END CONTEXT ***

INSTRUCTIONS:
1. Context First: Check if the 'CURRENT ANALYSIS CONTEXT' or 'chatHistory' already 
   contains the answer. If yes, answer directly from it and cite it.
2. Live Research: If the user asks something NOT in the context (e.g., "What happened today?" 
   or "Check X about this"), USE THE TOOLS ("webSearch", "twitterSearch") to find live information.
3. Grok Style: Be objective, detailed, and slightly conversational. If you used a tool, mention what you found.
4. Formatting: Use Markdown (bold, lists) for readability.