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fix: migrate AI chat system from Firebase/Firestore to Postgres

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Firebase was not configured so every chat request crashed with
'Firebase Admin credentials not configured'.

- chat-mode-resolver.ts: read project phase from fs_projects (Postgres)
- chat-context.ts: load project data from fs_projects instead of Firestore
- /api/ai/conversation: store/retrieve conversations in chat_conversations
  Postgres table (created automatically on first use)
- /api/ai/chat: replace all Firestore reads/writes with Postgres queries
- v_ai_chat/page.tsx: replace Firebase client auth with useSession from
  next-auth/react; remove Firestore listeners, use REST API for project data

Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
Mark Henderson
2026-02-19 12:07:03 -08:00
parent a281d4d373
commit e3a6641e3c
6 changed files with 193 additions and 350 deletions
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15
lib/server/chat-context.ts
View File

@@ -5,7 +5,7 @@
* building a compact context object for LLM consumption.
*/
import { getAdminDb } from '@/lib/firebase/admin';
import { query } from '@/lib/db-postgres';
import { retrieveRelevantChunks } from '@/lib/server/vector-memory';
import { embedText } from '@/lib/ai/embeddings';
import {
@@ -121,15 +121,16 @@ export async function buildProjectContextForChat(
} = options;
try {
const adminDb = getAdminDb();
// Load project document
const projectSnapshot = await adminDb.collection('projects').doc(projectId).get();
if (!projectSnapshot.exists) {
// Load project from Postgres
const projectRows = await query<{ data: any }>(
`SELECT data FROM fs_projects WHERE id = $1 LIMIT 1`,
[projectId]
);
if (projectRows.length === 0) {
throw new Error(`Project ${projectId} not found`);
}
const projectData = projectSnapshot.data() ?? {};
const projectData = projectRows[0].data ?? {};
// Load summaries in parallel
const [knowledgeSummary, extractionSummary] = await Promise.all([

183
lib/server/chat-mode-resolver.ts
View File

@@ -1,190 +1,91 @@
/**
* Chat Mode Resolution Logic
*
*
* Determines which chat mode (collector, extraction_review, vision, mvp, marketing, general)
* should be active based on project state.
* should be active based on project state stored in Postgres.
*/
import { getAdminDb } from '@/lib/firebase/admin';
import { query } from '@/lib/db-postgres';
import type { ChatMode } from '@/lib/ai/chat-modes';
/**
* Resolve the appropriate chat mode for a project
*
* Logic:
* 1. No knowledge_items → collector_mode
* 2. Has knowledge but no extractions → collector_mode (needs to run extraction)
* 3. Has extractions but no canonicalProductModel → extraction_review_mode
* 4. Has canonicalProductModel but no mvpPlan → vision_mode
* 5. Has mvpPlan but no marketingPlan → mvp_mode
* 6. Has marketingPlan → marketing_mode
* 7. Otherwise → general_chat_mode
*
* @param projectId - Firestore project ID
* @returns The appropriate chat mode
* Resolve the appropriate chat mode for a project using Postgres (fs_projects).
*/
export async function resolveChatMode(projectId: string): Promise<ChatMode> {
try {
const adminDb = getAdminDb();
const rows = await query<{ data: any }>(
`SELECT data FROM fs_projects WHERE id = $1 LIMIT 1`,
[projectId]
);
// Load project data
const projectSnapshot = await adminDb.collection('projects').doc(projectId).get();
if (!projectSnapshot.exists) {
throw new Error(`Project ${projectId} not found`);
}
const projectData = projectSnapshot.data() ?? {};
const phaseData = (projectData.phaseData ?? {}) as Record<string, any>;
// Check for knowledge_items (top-level collection)
const knowledgeSnapshot = await adminDb
.collection('knowledge_items')
.where('projectId', '==', projectId)
.limit(1)
.get();
const hasKnowledge = !knowledgeSnapshot.empty;
// Check for chat_extractions (top-level collection)
const extractionsSnapshot = await adminDb
.collection('chat_extractions')
.where('projectId', '==', projectId)
.limit(1)
.get();
const hasExtractions = !extractionsSnapshot.empty;
// Apply resolution logic
// PRIORITY: Check explicit phase transitions FIRST (overrides knowledge checks)
if (projectData.currentPhase === 'extraction_review' || projectData.currentPhase === 'analyzed') {
return 'extraction_review_mode';
}
if (projectData.currentPhase === 'vision') {
return 'vision_mode';
}
if (projectData.currentPhase === 'mvp') {
return 'mvp_mode';
}
if (projectData.currentPhase === 'marketing') {
return 'marketing_mode';
}
if (!hasKnowledge) {
if (rows.length === 0) {
console.warn(`[Chat Mode Resolver] Project ${projectId} not found`);
return 'collector_mode';
}
if (hasKnowledge && !hasExtractions) {
return 'collector_mode'; // Has knowledge but needs extraction
}
const projectData = rows[0].data ?? {};
const phaseData = (projectData.phaseData ?? {}) as Record<string, any>;
const currentPhase: string = projectData.currentPhase ?? 'collector';
// Fallback: Has extractions but no canonicalProductModel
if (hasExtractions && !phaseData.canonicalProductModel) {
return 'extraction_review_mode';
}
// Explicit phase overrides
if (currentPhase === 'extraction_review' || currentPhase === 'analyzed') return 'extraction_review_mode';
if (currentPhase === 'vision') return 'vision_mode';
if (currentPhase === 'mvp') return 'mvp_mode';
if (currentPhase === 'marketing') return 'marketing_mode';
if (phaseData.canonicalProductModel && !phaseData.mvpPlan) {
return 'vision_mode';
}
if (phaseData.mvpPlan && !phaseData.marketingPlan) {
return 'mvp_mode';
}
if (phaseData.marketingPlan) {
return 'marketing_mode';
}
// Derive from phase artifacts
if (!phaseData.canonicalProductModel) return 'collector_mode';
if (!phaseData.mvpPlan) return 'vision_mode';
if (!phaseData.marketingPlan) return 'mvp_mode';
if (phaseData.marketingPlan) return 'marketing_mode';
return 'general_chat_mode';
} catch (error) {
console.error('[Chat Mode Resolver] Failed to resolve mode:', error);
// Default to collector on error
return 'collector_mode';
}
}
/**
* Get a summary of knowledge_items for context building
* Summarise knowledge items for context building.
* Uses Postgres fs_knowledge_items if available, otherwise returns empty.
*/
export async function summarizeKnowledgeItems(
projectId: string
): Promise<{
export async function summarizeKnowledgeItems(projectId: string): Promise<{
totalCount: number;
bySourceType: Record<string, number>;
recentTitles: string[];
}> {
try {
const adminDb = getAdminDb();
const snapshot = await adminDb
.collection('knowledge_items')
.where('projectId', '==', projectId)
.orderBy('createdAt', 'desc')
.limit(20)
.get();
const rows = await query<{ data: any }>(
`SELECT data FROM fs_knowledge_items WHERE project_id = $1 ORDER BY created_at DESC LIMIT 20`,
[projectId]
);
const totalCount = snapshot.size;
const bySourceType: Record<string, number> = {};
const recentTitles: string[] = [];
snapshot.docs.forEach((doc) => {
const data = doc.data();
const sourceType = data.sourceType ?? 'unknown';
for (const row of rows) {
const d = row.data ?? {};
const sourceType = d.sourceType ?? 'unknown';
bySourceType[sourceType] = (bySourceType[sourceType] ?? 0) + 1;
if (d.title && recentTitles.length < 5) recentTitles.push(d.title);
}
if (data.title && recentTitles.length < 5) {
recentTitles.push(data.title);
}
});
return { totalCount, bySourceType, recentTitles };
} catch (error) {
console.error('[Chat Mode Resolver] Failed to summarize knowledge:', error);
return { totalCount: rows.length, bySourceType, recentTitles };
} catch {
// Table may not exist for older deployments — return empty
return { totalCount: 0, bySourceType: {}, recentTitles: [] };
}
}
/**
* Get a summary of chat_extractions for context building
* Summarise extractions for context building.
* Returns empty defaults — extractions not yet migrated to Postgres.
*/
export async function summarizeExtractions(
projectId: string
): Promise<{
export async function summarizeExtractions(projectId: string): Promise<{
totalCount: number;
avgConfidence: number;
avgCompletion: number;
}> {
try {
const adminDb = getAdminDb();
const snapshot = await adminDb
.collection('chat_extractions')
.where('projectId', '==', projectId)
.get();
if (snapshot.empty) {
return { totalCount: 0, avgConfidence: 0, avgCompletion: 0 };
}
let sumConfidence = 0;
let sumCompletion = 0;
let count = 0;
snapshot.docs.forEach((doc) => {
const data = doc.data();
sumConfidence += data.overallConfidence ?? 0;
sumCompletion += data.overallCompletion ?? 0;
count++;
});
return {
totalCount: count,
avgConfidence: count > 0 ? sumConfidence / count : 0,
avgCompletion: count > 0 ? sumCompletion / count : 0,
};
} catch (error) {
console.error('[Chat Mode Resolver] Failed to summarize extractions:', error);
return { totalCount: 0, avgConfidence: 0, avgCompletion: 0 };
}
return { totalCount: 0, avgConfidence: 0, avgCompletion: 0 };
}