tower/apps/api/src/modules/ask-ai/ask-ai.service.ts

import { Injectable, Logger } from '@nestjs/common';
import { ConfigService } from '@nestjs/config';
import { PrismaService } from '../../prisma/prisma.service';
import { SearchService } from '../search/search.service';
import { callLLM } from '../../common/llm-client';

export interface Citation {
  messageId: string;
  snippet: string;
  senderName: string;
  sourceGroupName: string;
  approvedAt: number;
}

@Injectable()
export class AskAIService {
  private readonly logger = new Logger(AskAIService.name);

  constructor(
    private readonly prisma: PrismaService,
    private readonly search: SearchService,
    private readonly config: ConfigService,
  ) {}

  async ask(userId: string, tenantId: string, question: string) {
    // 1. Retrieve: pull the most relevant approved messages from the tenant's index.
    const { hits } = await this.search.search(tenantId, question, undefined, undefined, 1, 8);

    const citations: Citation[] = hits.map((h) => ({
      messageId: h.id,
      snippet: h.content.slice(0, 240),
      senderName: h.senderName || 'Unknown',
      sourceGroupName: h.sourceGroupName,
      approvedAt: h.approvedAt,
    }));

    // 2. Generate: ground the LLM in the retrieved snippets. Degrade gracefully
    //    if no AI key is configured or no context was found.
    const apiKey = this.config.get<string>('OPENROUTER_API_KEY');
    let answer: string;

    if (citations.length === 0) {
      answer = "I couldn't find anything in your community's messages about that yet. Try rephrasing, or ask an admin.";
    } else if (!apiKey) {
      answer = this.fallbackAnswer(citations);
    } else {
      try {
        answer = await callLLM(this.buildPrompt(question, citations), apiKey);
      } catch (err) {
        this.logger.warn({ err }, 'Ask AI LLM call failed — returning snippet fallback');
        answer = this.fallbackAnswer(citations);
      }
    }

    // 3. Log the query for history + future tuning.
    const record = await this.prisma.askAIQuery.create({
      data: { tenantId, userId, question, answer, citations: citations as unknown as object },
    });

    return {
      id: record.id,
      question,
      answer,
      citations,
      createdAt: record.createdAt.toISOString(),
    };
  }

  async history(userId: string, tenantId: string) {
    const queries = await this.prisma.askAIQuery.findMany({
      where: { userId, tenantId },
      orderBy: { createdAt: 'desc' },
      take: 20,
    });
    return queries.map((q) => ({
      id: q.id,
      question: q.question,
      answer: q.answer,
      citations: q.citations as unknown as Citation[],
      createdAt: q.createdAt.toISOString(),
    }));
  }

  private buildPrompt(question: string, citations: Citation[]): string {
    const context = citations
      .map((c, i) => `[${i + 1}] (${c.sourceGroupName}, by ${c.senderName}): ${c.snippet}`)
      .join('\n');
    return [
      'You are a helpful assistant for a community group. Answer the member\'s question',
      'using ONLY the message excerpts below. If the excerpts do not contain the answer,',
      'say you don\'t have that information. Cite sources inline as [1], [2], etc.',
      'Keep the answer concise and friendly.',
      '',
      'Message excerpts:',
      context,
      '',
      `Question: ${question}`,
      '',
      'Answer:',
    ].join('\n');
  }

  private fallbackAnswer(citations: Citation[]): string {
    const top = citations.slice(0, 3).map((c, i) => `[${i + 1}] ${c.snippet}`).join('\n\n');
    return `Here are the most relevant messages I found:\n\n${top}`;
  }
}