brung back memory

Author: izadoesdev

apps/api/src/ai/agents.ts

@@ -1,6 +1,12 @@
 import { Agent } from "@ai-sdk-tools/agents";
 import type { AppContext } from "./config/context";
 
+import {
+	extendedMemoryConfig,
+	maxMemoryConfig,
+	minimalMemoryConfig,
+	standardMemoryConfig,
+} from "./config/memory";
 import { models } from "./config/models";
 import { buildAnalyticsInstructions } from "./prompts/analytics";
 import { buildReflectionInstructions } from "./prompts/reflection";
@@ -66,6 +72,7 @@ export function createAnalyticsAgent(
 		temperature: 0.3,
 		instructions: buildAnalyticsInstructions,
 		tools,
+		memory: standardMemoryConfig,
 		modelSettings: {
 			failureMode: {
 				maxAttempts: 2,
@@ -94,14 +101,17 @@ export const createReflectionAgent = (
 		standard: {
 			model: models.advanced,
 			maxTurns: 15,
+			memory: extendedMemoryConfig, // 30 messages for Sonnet
 		},
 		haiku: {
 			model: models.analytics,
 			maxTurns: 15,
+			memory: standardMemoryConfig, // 20 messages for Haiku
 		},
 		max: {
 			model: models.advanced,
 			maxTurns: 20,
+			memory: maxMemoryConfig, // 40 messages for deep investigations
 		},
 	}[variant];
 
@@ -139,6 +149,7 @@ export function createTriageAgent(
 		model: models.triage,
 		temperature: 0.1,
 		instructions: buildTriageInstructions,
+		memory: minimalMemoryConfig,
 		modelSettings: {
 			toolChoice: {
 				type: "tool",

apps/api/src/ai/config/memory.ts

@@ -0,0 +1,52 @@
+import { RedisProvider } from "@ai-sdk-tools/memory/redis";
+import { redis } from "@databuddy/redis";
+import type { RedisClientType } from "redis";
+
+/**
+ * Shared memory provider for all agents.
+ * Uses Redis for persistent conversation history.
+ */
+export const memoryProvider = new RedisProvider(
+	redis as unknown as RedisClientType
+);
+
+/**
+ * Memory configurations for different agent types.
+ * Higher-capability models get more memory to support complex, multi-step reasoning.
+ */
+
+/** Minimal memory for simple routing (triage) */
+export const minimalMemoryConfig = {
+	provider: memoryProvider,
+	history: {
+		enabled: true,
+		limit: 10, // ~5 turns - just enough for context
+	},
+} as const;
+
+/** Standard memory for typical analytical queries */
+export const standardMemoryConfig = {
+	provider: memoryProvider,
+	history: {
+		enabled: true,
+		limit: 20, // ~10 turns - good for most conversations
+	},
+} as const;
+
+/** Extended memory for complex multi-step investigations */
+export const extendedMemoryConfig = {
+	provider: memoryProvider,
+	history: {
+		enabled: true,
+		limit: 30, // ~15 turns - deep analysis sessions
+	},
+} as const;
+
+/** Maximum memory for advanced reasoning with Sonnet */
+export const maxMemoryConfig = {
+	provider: memoryProvider,
+	history: {
+		enabled: true,
+		limit: 40, // ~20 turns - complex multi-step workflows
+	},
+} as const;

apps/api/src/ai/config/models.ts

@@ -17,12 +17,15 @@ export const openrouter = createOpenRouter({
  * Centralized here for easy switching and environment-based overrides.
  */
 
+// const overrideModel = 'z-ai/glm-4.6'
+const overrideModel = null;
+
 const modelNames = {
-	triage: "anthropic/claude-haiku-4.5",
-	analytics: "anthropic/claude-haiku-4.5",
+	triage: overrideModel || "anthropic/claude-haiku-4.5",
+	analytics: overrideModel || "anthropic/claude-haiku-4.5",
 	// triage: "z-ai/glm-4.6",
 	// analytics: "z-ai/glm-4.6",
-	advanced: "anthropic/claude-sonnet-4.5",
+	advanced: overrideModel || "anthropic/claude-sonnet-4.5",
 	// advanced: "z-ai/glm-4.6",
 	perplexity: "perplexity/sonar-pro",
 } as const;

apps/api/src/ai/prompts/analytics.ts

@@ -7,6 +7,14 @@ import { COMMON_AGENT_RULES } from "./shared";
  * Analytics-specific rules for data analysis and presentation.
  */
 const ANALYTICS_RULES = `<agent-specific-rules>
+**CRITICAL DATA INTEGRITY RULES:**
+- NEVER make up, invent, fabricate, or hallucinate any analytics data
+- NEVER provide fake numbers, metrics, page views, visitor counts, or any analytics without calling tools first
+- NEVER respond to questions like "what's my top page", "how many visitors", "traffic data" without calling the appropriate tool
+- If a user asks about ANY analytics data, you MUST call get_top_pages, execute_query_builder, or execute_sql_query BEFORE responding
+- Only use real data returned from tool calls - never use example data, placeholder numbers, or made-up metrics
+- If you don't have tool results, you MUST call the tool first - never guess or estimate
+
 **Data Analysis:**
 - Lead with key metrics and insights
 - Always include time context (e.g., "in the last 7 days", "yesterday vs last week")
@@ -20,7 +28,6 @@ const ANALYTICS_RULES = `<agent-specific-rules>
 - Use execute_query_builder for pre-built analytics queries (PREFERRED - use this for common queries like traffic, sessions, pages, devices, geo, errors, performance, etc.)
 - Use execute_sql_query ONLY for custom SQL queries that aren't covered by query builders
 - Use competitor_analysis for real-time competitor insights, market trends, and industry analysis with citations
-- Use memory tools (search_memory, add_memory) to remember user preferences and past analysis patterns
 - Use funnels tools when users ask about funnels, conversion paths, or user journeys:
   - list_funnels: List all funnels for a website (use when user asks "show me my funnels", "what funnels do I have", etc.)
   - get_funnel_by_id: Get details of a specific funnel by ID
@@ -54,15 +61,15 @@ const ANALYTICS_RULES = `<agent-specific-rules>
  * Builds the instruction prompt for the analytics agent.
  */
 export function buildAnalyticsInstructions(ctx: AppContext): string {
-	return `You are Databunny, an analytics assistant for ${ctx.websiteDomain}. Your goal is to analyze website traffic, user behavior, and performance metrics.
-
-<background-data>
-${formatContextForLLM(ctx)}
-</background-data>
+  return `You are Databunny, an analytics assistant for ${ctx.websiteDomain}. Your goal is to analyze website traffic, user behavior, and performance metrics.
 
 ${COMMON_AGENT_RULES}
 
 ${ANALYTICS_RULES}
 
+<background-data>
+${formatContextForLLM(ctx)}
+</background-data>
+
 ${CLICKHOUSE_SCHEMA_DOCS}`;
 }

apps/api/src/ai/prompts/reflection.ts

@@ -13,6 +13,8 @@ analytics: Website traffic analysis, page views, visitors, performance metrics,
  * Reflection and orchestration rules.
  */
 const REFLECTION_RULES = `<reflection-rules>
+**CRITICAL: NEVER make up, invent, or fabricate analytics data. Always hand off to analytics agent to get real data first.**
+
 Your primary role is to reflect on responses and orchestrate multi-step investigations:
 
 1. **Response Analysis**: When you receive a response from another agent or tool:
@@ -24,6 +26,7 @@ Your primary role is to reflect on responses and orchestrate multi-step investig
    - If the response is complete and clear → Explain it to the user in a helpful, synthesized way
    - If more data is needed → Hand off to the analytics agent with specific instructions
    - If the response needs clarification → Ask follow-up questions or request specific data
+   - NEVER provide analytics data without handing off to analytics agent first
 
 3. **Multi-Step Workflows**: For complex questions, break them down:
    - First, gather initial data (e.g., "check for errors")
@@ -47,6 +50,7 @@ Your primary role is to reflect on responses and orchestrate multi-step investig
    - Ask clarifying questions when the request is ambiguous
    - Proactively suggest related insights worth investigating
    - CRITICAL: Never respond before tool calls complete. Always wait for actual tool results before generating your response
+   - CRITICAL: Never make up analytics data - always hand off to analytics agent to get real data
 </reflection-rules>`;
 
 /**
@@ -98,19 +102,19 @@ User: "Create a funnel for signup" or "I want to track the checkout process"
  * Builds the instruction prompt for the reflection agent.
  */
 export function buildReflectionInstructions(ctx: AppContext): string {
-	return `You are Databunny, an analytics assistant for ${ctx.websiteDomain}. Your job is to review responses, determine what to do next, and either explain findings to users or coordinate deeper investigations when needed.
+   return `You are Databunny, an analytics assistant for ${ctx.websiteDomain}. Your job is to review responses, determine what to do next, and either explain findings to users or coordinate deeper investigations when needed.
 
-<background-data>
-${formatContextForLLM(ctx)}
-</background-data>
+${COMMON_AGENT_RULES}
 
 ${AGENT_CAPABILITIES}
 
 ${REFLECTION_RULES}
 
 ${WORKFLOW_EXAMPLES}
 
-${COMMON_AGENT_RULES}
+<background-data>
+${formatContextForLLM(ctx)}
+</background-data>
 
 <important-notes>
 - You are the orchestrator - use other agents to gather data, then synthesize and explain
@@ -120,5 +124,6 @@ ${COMMON_AGENT_RULES}
 - If a response is incomplete or unclear, investigate further before responding to the user
 - Consider the business context and primary goal when framing insights
 - Be data-driven but acknowledge limitations (small samples, short time periods, data gaps)
+- NEVER make up analytics data - always hand off to analytics agent to get real data first
 </important-notes>`;
 }

apps/api/src/ai/prompts/shared.ts

@@ -5,8 +5,11 @@
 export const COMMON_AGENT_RULES = `<behavior_rules>
 - Call tools immediately without explanatory text
 - CRITICAL: NEVER generate a response before tool calls complete. Always wait for tool results before responding to the user
+- CRITICAL: NEVER make up, invent, or fabricate data. NEVER provide fake numbers, metrics, or analytics. If you don't have real data from tools, you MUST call the appropriate tool first
+- CRITICAL: If a user asks about analytics data (page views, visitors, traffic, etc.), you MUST call the appropriate tool (get_top_pages, execute_query_builder, execute_sql_query) BEFORE responding. Never respond with made-up data
 - If you need data to answer a question, call the tool first, then respond based on the actual results
 - Do not speculate or guess what tool results will be - wait for actual data
+- Do not provide example data or placeholder responses - only use real data from tool calls
 - Use parallel tool calls when possible
 - Provide specific numbers and actionable insights
 - Lead with the most important information first

apps/api/src/ai/prompts/triage.ts

@@ -1,5 +1,6 @@
 import type { AppContext } from "../config/context";
 import { formatContextForLLM } from "../config/context";
+import { COMMON_AGENT_RULES } from "./shared";
 
 /**
  * Single-model capabilities.
@@ -25,6 +26,8 @@ const ROUTING_RULES = `<routing-rules>
 export function buildTriageInstructions(ctx: AppContext): string {
 	return `You are Databunny, an analytics assistant for ${ctx.websiteDomain}. Handle analytics requests directly.
 
+${COMMON_AGENT_RULES}
+
 <background-data>
 ${formatContextForLLM(ctx)}
 

apps/api/src/routes/agent.ts

@@ -53,7 +53,6 @@ function toUIMessage(msg: IncomingMessage): UIMessage {
 		};
 	}
 
-	// Extract text from content or text field
 	const text = msg.content ?? msg.text ?? "";
 
 	return {