feat(ai): scope persistence, parallel tools, Prometheus token/cache counters
C2 full scope persistence:
- getRecentConversationContext now returns per-turn guildId/channelId
- processMessage merges historical scope when current request is unscoped
- chatbot remembers server context across all 8 history exchanges (not just 3)
A4+Metrics:
- Add incrementCounterBy(name, delta, labels) to gateway-metrics
- Token-usage counters: llm_tokens_total{model, type, label} per batch
- Cache hit counters: moderation_cache_hits{type} exact/semantic-qdrant/semantic-pg
- Cache miss counters: moderation_cache_misses per batch
- Prometheus /metrics now exposes cost + cache hit-rate for dashboards
Performance:
- Parallel tool execution within each chatbot round (Promise.all)
- All tool results collected before sending to model (ordering preserved)
- Tool failure now logged with structured warning (chatbot.tools.ts)
Verified: backend tsc+biome 37/37, discord-gateway tsc+biome 210/210
This commit is contained in:
@@ -26,13 +26,25 @@ class ChatbotService {
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// longer bake server stats into the prompt — the model must pull current
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// data via tools (see buildSystemPrompt), so it always answers from live
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// numbers instead of a stale snapshot.
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const scope = {
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//
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// If the current request doesn't carry a guild/channel scope (e.g. a
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// cross-server dashboard surface), fall back to the most recent scope the
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// user was chatting in from history, so the agent doesn't drift to the
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// wrong server between turns.
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const explicitScope = {
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guildId: context?.guildId,
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channelId: context?.channelId,
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};
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const scope =
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explicitScope.guildId || explicitScope.channelId
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? explicitScope
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: (recentContext.lastScope ?? {
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guildId: undefined,
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channelId: undefined,
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});
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const systemPrompt = this.buildSystemPrompt(scope);
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const conversationHistory = this.buildHistoryMessages(recentContext);
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const conversationHistory = this.buildHistoryMessages(recentContext.turns);
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const llmResponse = await this.callLLM(
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systemPrompt,
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conversationHistory,
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@@ -61,14 +73,28 @@ class ChatbotService {
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await chatbotRepository.clearChatHistory(userId);
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}
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private async getRecentConversationContext(
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userId: string,
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): Promise<string[]> {
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private async getRecentConversationContext(userId: string): Promise<{
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turns: string[];
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lastScope: { guildId?: string; channelId?: string } | null;
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}> {
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const history = await chatbotRepository.getChatHistory(userId, 8);
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return history.flatMap((row) => [
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`User: ${row.user_message}`,
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`Bot: ${row.bot_response}`,
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]);
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const turns: string[] = [];
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let lastScope: { guildId?: string; channelId?: string } | null = null;
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for (const row of history) {
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turns.push(`User: ${row.user_message}`, `Bot: ${row.bot_response}`);
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// Capture the most recent scope this user was chatting in, so the
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// agent keeps server context across turns even if the current request
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// doesn't carry one.
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const g = row.context?.guildId;
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const c = row.context?.channelId;
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if (g || c) {
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lastScope = {
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guildId: g ?? undefined,
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channelId: c ?? undefined,
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};
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}
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}
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return { turns, lastScope };
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}
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private buildSystemPrompt(scope: {
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@@ -213,35 +239,44 @@ Gaya ngobrol:
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);
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if (toolCalls.length > 0) {
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// Execute each tool, append tool results, continue loop.
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for (const tc of toolCalls) {
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messages.push({
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role: "assistant",
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content: null,
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tool_calls: [
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{
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id: tc.id,
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type: "function",
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function: { name: tc.name, arguments: tc.arguments },
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},
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],
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});
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// Auto-scope: if the model omitted guildId/channelId, fill them
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// from the request scope so tools query the right server without
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// the model having to guess IDs.
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const scopedArgs = { ...tc.args };
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if (scope.guildId && scopedArgs.guildId == null) {
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scopedArgs.guildId = scope.guildId;
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}
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if (scope.channelId && scopedArgs.channelId == null) {
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scopedArgs.channelId = scope.channelId;
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}
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let result = "";
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try {
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result = await executeTool(tc.name, scopedArgs);
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} catch (e) {
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result = `Tool error: ${(e as Error).message}`;
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}
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// Executor for a single tool call: pushes the assistant tool_call,
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// runs the tool, returns { tc, result } so results can be appended
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// in order after all tools execute in parallel.
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const executions = await Promise.all(
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toolCalls.map(async (tc) => {
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messages.push({
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role: "assistant",
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content: null,
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tool_calls: [
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{
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id: tc.id,
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type: "function",
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function: { name: tc.name, arguments: tc.arguments },
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},
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],
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});
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// Auto-scope: if the model omitted guildId/channelId, fill them
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// from the request scope so tools query the right server without
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// the model having to guess IDs.
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const scopedArgs = { ...tc.args };
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if (scope.guildId && scopedArgs.guildId == null) {
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scopedArgs.guildId = scope.guildId;
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}
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if (scope.channelId && scopedArgs.channelId == null) {
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scopedArgs.channelId = scope.channelId;
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}
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let result = "";
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try {
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result = await executeTool(tc.name, scopedArgs);
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} catch (e) {
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result = `Tool error: ${(e as Error).message}`;
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}
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return { tc, result };
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}),
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);
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// Append tool results in the SAME order as the tool_calls so the
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// API's function-calling contract isn't violated by reordering.
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for (const { tc, result } of executions) {
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messages.push({
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role: "tool",
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tool_call_id: tc.id,
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@@ -14,6 +14,7 @@ import type { ChatCompletion } from "openai/resources/chat/completions";
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import { createChildLogger } from "@/shared/logger/index";
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import { delay, retryWithBackoff } from "@/shared/utils/index";
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import { config } from "../../shared/config/config.js";
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import { incrementCounterBy } from "../gateway-metrics/index.js";
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import type { AnalysisResult } from "../message-capture/types.js";
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import { llmChat } from "./llmClient.js";
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import { parseModerationResponse } from "./moderationResponseParser.js";
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@@ -170,6 +171,23 @@ export async function callModerationLLM(
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// so cost per channel/guild can be tracked (routers bill per token).
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const usage = result?.usage;
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if (usage && (usage.prompt_tokens || usage.completion_tokens)) {
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// Prometheus token-usage counters for cost tracking per model + phase.
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// Counters accumulate across scrapes so total spend per model/label is
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// queryable (rate(...) dashboards).
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if (usage.prompt_tokens) {
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incrementCounterBy("llm_tokens_total", usage.prompt_tokens, {
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model: config.AI_LLM_MODEL,
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type: "prompt",
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label,
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});
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}
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if (usage.completion_tokens) {
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incrementCounterBy("llm_tokens_total", usage.completion_tokens, {
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model: config.AI_LLM_MODEL,
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type: "completion",
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label,
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});
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}
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log.info(
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{
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label,
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@@ -8,6 +8,7 @@
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import { LRUCache } from "lru-cache";
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import { createChildLogger } from "@/shared/logger/index";
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import { config } from "../../shared/config/config.js";
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import { incrementCounterBy } from "../gateway-metrics/index.js";
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import { extractMessageMediaEvidence } from "../message-capture/messageMetadata.js";
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import type {
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AnalysisResult,
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@@ -243,10 +244,12 @@ export async function runModerationAnalysis(
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const representative = hitByKey.get(candidate.scopedKey);
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if (representative) {
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cacheHits.push({ ...representative, messageId: candidate.target.id });
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incrementCounterBy("moderation_cache_hits", 1, { type: "exact" });
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} else {
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uncachedTargets.push(candidate.target);
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}
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}
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incrementCounterBy("moderation_cache_misses", uncachedTargets.length);
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// ── Phase 2: semantic cache — batched (one embed call + one Qdrant
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// batch search for ALL uncached text targets) ─────────────────────────
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@@ -321,6 +324,9 @@ export async function runModerationAnalysis(
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hitByKey.set(cacheKey, hit);
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servedCacheKeys.add(cacheKey); // bump hit_count for metrics
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logCacheEvent("hit", cacheKey, "text");
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incrementCounterBy("moderation_cache_hits", 1, {
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type: "semantic-qdrant",
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});
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}
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} else {
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// Legacy Postgres fallback path (no Qdrant): per-candidate scan.
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@@ -360,6 +366,9 @@ export async function runModerationAnalysis(
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hitByKey.set(cacheKey, hit);
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servedCacheKeys.add(cacheKey); // bump hit_count for metrics
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logCacheEvent("hit", cacheKey, "text");
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incrementCounterBy("moderation_cache_hits", 1, {
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type: "semantic-pg",
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});
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}
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}
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@@ -1,5 +1,6 @@
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export {
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incrementCounter,
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incrementCounterBy,
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registerCollector,
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setGauge,
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startMetricsServer,
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@@ -37,16 +37,25 @@ export function registerCollector(fn: () => void): void {
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export function incrementCounter(
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name: string,
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labels?: Record<string, string>,
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): void {
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incrementCounterBy(name, 1, labels);
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}
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/** Increment a counter by an explicit delta (e.g. token counts per batch). */
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export function incrementCounterBy(
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name: string,
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delta: number,
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labels?: Record<string, string>,
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): void {
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const k = key(`bete_${name}`, labels);
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const existing = metrics.get(k);
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if (existing) {
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existing.value += 1;
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existing.value += delta;
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} else {
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metrics.set(k, {
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help: `Counter: ${name}`,
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type: "counter",
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value: 1,
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value: delta,
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labels: labels ? { ...labels } : undefined,
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});
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}
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