asepharyanaandClaude Opus 5 (Nous Research)
30828a5534
The chatbot already had an agentic tool loop (get_server_stats, get_top_channels, get_recent_activity, get_top_flagged), but processMessage still baked a serverInsights snapshot into the system prompt and told the model to "answer from that data". That defeats the tools: the model answered from a stale snapshot instead of living numbers, and the guild/channel scope the frontend sends was never forwarded to the tools. Changes (services/backend/src/modules/chatbot): - Remove getServerInsights() + ServerInsights (dead after this change). - buildSystemPrompt(): drop the hardcoded stats block; instruct the model it has NO memorized server numbers and MUST call a tool for any server-data question, answering only from tool results. - processMessage(): stop fetching insights; pass the request guildId/channelId scope through to callLLM. - callLLM(): accept scope; auto-fill empty guildId/channelId on tool calls from the request scope so the model never has to guess IDs and tools always query the right server. Behavior: answers now come from live DB data via tools, scoped to the server the user is chatting in. tsc + biome + 36 backend tests green. Co-Authored-By: Claude Opus 5 (Nous Research)
82 lines
2.2 KiB
TypeScript
82 lines
2.2 KiB
TypeScript
import { and, desc, eq, type SQL, sql } from "drizzle-orm";
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import { getDatabase } from "../../shared/database/index.js";
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import { pgChatbotMessagesTable, pgMessagesTable } from "../../shared/index.js";
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import { createChildLogger } from "../../shared/logger/index.js";
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const logger = createChildLogger("chatbot.repository");
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export interface ChatbotContext {
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messageCount?: number;
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activeParticipants?: number;
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lastActivity?: string;
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topicsDiscussed?: string[];
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guildId?: string;
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channelId?: string;
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}
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export interface SaveConversationInput {
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userId: string;
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userMessage: string;
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botResponse: string;
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context?: ChatbotContext;
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timestamp: Date;
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}
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export interface ChatbotHistoryRow {
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id: string;
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user_id: string;
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user_message: string;
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bot_response: string;
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context: ChatbotContext | null;
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created_at: string;
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}
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export class ChatbotRepository {
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async saveConversation(input: SaveConversationInput): Promise<void> {
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const db = getDatabase();
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await db.insert(pgChatbotMessagesTable).values({
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user_id: input.userId,
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user_message: input.userMessage,
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bot_response: input.botResponse,
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context: (input.context ?? {}) as Record<string, unknown>,
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created_at: input.timestamp,
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});
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logger.debug({ userId: input.userId }, "Conversation saved");
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}
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async getChatHistory(
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userId: string,
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limit: number,
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): Promise<ChatbotHistoryRow[]> {
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const db = getDatabase();
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const rows = await db
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.select()
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.from(pgChatbotMessagesTable)
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.where(eq(pgChatbotMessagesTable.user_id, userId))
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.orderBy(desc(pgChatbotMessagesTable.created_at))
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.limit(limit);
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logger.debug({ userId, count: rows.length }, "Chat history fetched");
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return rows.reverse() as unknown as ChatbotHistoryRow[];
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}
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async clearChatHistory(userId: string): Promise<void> {
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const db = getDatabase();
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const deleted = await db
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.delete(pgChatbotMessagesTable)
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.where(eq(pgChatbotMessagesTable.user_id, userId))
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.returning({ id: pgChatbotMessagesTable.id });
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logger.info(
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{ userId, deletedRows: deleted.length },
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"Chat history cleared",
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);
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}
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}
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export const chatbotRepository = new ChatbotRepository();
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