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.git
node_modules
packages/*/node_modules
packages/*/dist
packages/backend/.env.local
*.log
.vscode
.idea

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name: Recommender Build and Deploy (internal)
on:
push:
branches:
- main
workflow_dispatch: {}
env:
REGISTRY_HOST: git.ivanch.me
REGISTRY_USERNAME: ivanch
IMAGE: ${{ env.REGISTRY_HOST }}/ivanch/recommender
KUBE_CONFIG: ${{ secrets.KUBE_CONFIG }}
jobs:
build_recommender:
name: Build Recommender Image
runs-on: ubuntu-22.04
steps:
- name: Check out repository
uses: actions/checkout@v2
- name: Log in to Container Registry
run: |
echo "${{ secrets.REGISTRY_PASSWORD }}" \
| docker login "${{ env.REGISTRY_HOST }}" \
-u "${{ env.REGISTRY_USERNAME }}" \
--password-stdin
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Build and Push Multi-Arch Image
uses: docker/build-push-action@v6
with:
push: true
context: .
platforms: linux/amd64,linux/arm64
tags: |
${{ env.IMAGE }}:latest
deploy_recommender:
name: Deploy Recommender (internal)
runs-on: ubuntu-amd64
needs: build_recommender
steps:
- name: Check KUBE_CONFIG validity
run: |
if [ -z "${KUBE_CONFIG}" ] || [ "${KUBE_CONFIG}" = "" ] || [ "${KUBE_CONFIG// }" = "" ]; then
echo "KUBE_CONFIG is not set or is empty."
exit 1
fi
- name: Check out repository
uses: actions/checkout@v2
- name: Download and install dependencies
run: |
apt-get update -y
apt-get install -y curl
curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl"
install -m 0755 kubectl /usr/local/bin/kubectl
kubectl version --client
- name: Set up kubeconfig
run: |
cd deploy
echo "$KUBE_CONFIG" > kubeconfig.yaml
env:
KUBE_CONFIG: ${{ env.KUBE_CONFIG }}
- name: Check connection to cluster
run: |
cd deploy
kubectl --kubeconfig=kubeconfig.yaml cluster-info
- name: Apply Recommender deployment
run: |
cd deploy
kubectl --kubeconfig=kubeconfig.yaml apply -f recommender.yaml
- name: Rollout restart
run: |
cd deploy
kubectl --kubeconfig=kubeconfig.yaml rollout restart deployment recommender -n media

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# Dependencies
node_modules/
# Build outputs
dist/
dist-ssr/
# Environment secrets — use .env.local for real values, never commit secrets
.env.local
*.local
# Logs
*.log
npm-debug.log*
yarn-debug.log*
pnpm-debug.log*
# Editor
.vscode/*
!.vscode/extensions.json
.idea/
.DS_Store
.claude/
documents/
# OS
Thumbs.db

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# ─── Stage 1: Install all workspace dependencies ─────────────────────────────
FROM node:22-slim AS deps
WORKDIR /app
COPY package.json package-lock.json ./
COPY packages/backend/package.json ./packages/backend/package.json
COPY packages/frontend/package.json ./packages/frontend/package.json
RUN npm ci --ignore-scripts
# ─── Stage 2: Build the Preact frontend ──────────────────────────────────────
FROM deps AS build-frontend
COPY packages/frontend/ ./packages/frontend/
RUN npm run build -w frontend
# ─── Stage 3: Runtime image ───────────────────────────────────────────────────
FROM node:22-slim AS runtime
# Install Nginx
RUN apt-get update && apt-get install -y --no-install-recommends nginx \
&& rm -rf /var/lib/apt/lists/*
WORKDIR /app
# --- Backend ---
COPY --from=deps /app/node_modules ./node_modules
COPY --from=deps /app/packages/backend/node_modules ./packages/backend/node_modules
COPY packages/backend/ ./packages/backend/
# --- Frontend static files ---
COPY --from=build-frontend /app/packages/frontend/dist /usr/share/nginx/html
# --- Nginx config ---
COPY nginx.conf /etc/nginx/nginx.conf
# --- Entrypoint ---
COPY entrypoint.sh /entrypoint.sh
RUN chmod +x /entrypoint.sh
# DATABASE_URL and OPENAI_API_KEY must be set when running the container.
ENV PORT=3000
ENV DATABASE_URL=postgres://user:password@localhost:5432/recommender
ENV OPENAI_API_KEY=your-openai-api-key-here
EXPOSE 80
ENTRYPOINT ["/entrypoint.sh"]

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# Recommender
A pure TypeScript monolith AI agent application that will recommend TV shows based on a very customized user profile and input.
## Project Structure
- **packages/frontend**: Preact application powered by Vite and TypeScript.
- **packages/backend**: Fastify server utilizing Drizzle ORM and the official OpenAI SDK.
## Getting Started
1. **Install dependencies**:
```bash
npm install
```
2. **Configure Environment**:
Ensure `packages/backend/.env` exists with your database and AI settings.
3. **Run the application**:
```bash
npm run dev
```
This will concurrently start the frontend development server and the backend API.

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apiVersion: apps/v1
kind: Deployment
metadata:
name: recommender
namespace: media
spec:
replicas: 1
selector:
matchLabels:
app: recommender
template:
metadata:
labels:
app: recommender
spec:
containers:
- name: recommender
image: git.ivanch.me/ivanch/recommender:latest
imagePullPolicy: Always
ports:
- containerPort: 8080
env:
- name: OPENAI_API_KEY
valueFrom:
secretKeyRef:
name: recommender-secrets
key: OPENAI_API_KEY
- name: DATABASE_URL
valueFrom:
secretKeyRef:
name: recommender-secrets
key: DATABASE_URL
resources:
requests:
memory: "256Mi"
cpu: "500m"
limits:
memory: "512Mi"
cpu: "1"
---
apiVersion: v1
kind: Service
metadata:
name: recommender
namespace: media
spec:
selector:
app: recommender
ports:
- port: 80
targetPort: 8080
---
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: recommender
namespace: media
labels:
app.kubernetes.io/name: recommender
spec:
ingressClassName: nginx
rules:
- host: "recommender.haven"
http:
paths:
- path: "/"
pathType: Prefix
backend:
service:
name: recommender
port:
number: 80

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#!/bin/sh
set -e
# Start Nginx in the background
nginx &
# Start the Node.js backend
exec node /app/node_modules/.bin/tsx /app/packages/backend/src/index.ts

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events {}
http {
include /etc/nginx/mime.types;
default_type application/octet-stream;
server {
listen 80;
# Reverse-proxy /api/* -> Fastify backend (strips the /api prefix)
location /api/ {
proxy_pass http://127.0.0.1:3000/;
proxy_http_version 1.1;
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
}
# Serve Preact static build — SPA fallback to index.html
location / {
root /usr/share/nginx/html;
index index.html;
try_files $uri $uri/ /index.html;
}
}
}

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{
"name": "recommender",
"version": "1.0.0",
"description": "",
"main": "index.js",
"scripts": {
"test": "echo \"Error: no test specified\" && exit 1",
"dev": "concurrently -n \"backend,frontend\" -c \"bgBlue.bold,bgCyan.bold\" \"npm run dev -w backend\" \"npm run dev -w frontend\""
},
"keywords": [],
"author": "",
"license": "ISC",
"type": "commonjs",
"private": "true",
"workspaces": [
"packages/*"
],
"devDependencies": {
"concurrently": "^9.2.1"
}
}

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# Copy this file to .env.local and fill in the real values.
# .env.local is gitignored and will override these defaults.
# In production / Docker, supply these as environment variables.
DATABASE_URL=postgres://user:password@localhost:5432/recommender
OPENAI_API_KEY=your-openai-api-key-here

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import { defineConfig } from 'drizzle-kit';
import * as dotenv from 'dotenv';
dotenv.config();
export default defineConfig({
schema: './src/db/schema.ts',
out: './drizzle',
dialect: 'postgresql',
dbCredentials: {
url: process.env['DATABASE_URL'] ?? 'postgres://user:password@localhost:5432/recommender',
},
});

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{
"name": "backend",
"version": "1.0.0",
"description": "",
"main": "index.js",
"scripts": {
"test": "echo \"Error: no test specified\" && exit 1",
"dev": "tsx watch src/index.ts"
},
"keywords": [],
"author": "",
"license": "ISC",
"type": "module",
"dependencies": {
"dotenv": "^17.3.1",
"drizzle-orm": "^0.45.1",
"fastify": "^5.8.4",
"openai": "^6.32.0",
"postgres": "^3.4.8"
},
"devDependencies": {
"@types/node": "^24.12.0",
"drizzle-kit": "^0.31.10",
"tsx": "^4.21.0",
"typescript": "^5.9.3"
}
}

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import OpenAI from 'openai';
import * as dotenv from 'dotenv';
dotenv.config();
export const openai = new OpenAI({
apiKey: process.env.OPENAI_API_KEY,
});
export async function askAgent(prompt: string) {
try {
const response = await openai.chat.completions.create({
model: 'gpt-5.4',
service_tier: 'flex',
messages: [{ role: 'user', content: prompt }],
});
return response!.choices![0]!.message!.content;
} catch (err) {
console.error('Agent endpoint dummy error:', err instanceof Error ? err.message : err);
return 'Agent is in dummy mode or encountered an error.';
}
}

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import { openai } from '../agent.js';
import type { InterpreterOutput, RankingOutput, CuratorOutput } from '../types/agents.js';
export async function runCurator(
ranking: RankingOutput,
interpreter: InterpreterOutput,
): Promise<CuratorOutput[]> {
const allShows = [
...ranking.definitely_like.map((t) => ({ title: t, category: 'Definitely Like' as const })),
...ranking.might_like.map((t) => ({ title: t, category: 'Might Like' as const })),
...ranking.questionable.map((t) => ({ title: t, category: 'Questionable' as const })),
...ranking.will_not_like.map((t) => ({ title: t, category: 'Will Not Like' as const })),
];
if (allShows.length === 0) return [];
const showList = allShows
.map((s) => `- "${s.title}" (${s.category})`)
.join('\n');
const response = await openai.chat.completions.create({
model: 'gpt-5.4-mini',
temperature: 0.5,
service_tier: 'flex',
response_format: { type: 'json_object' },
messages: [
{
role: 'system',
content: `You are a TV show recommendation curator. For each show, write a concise 1-2 sentence explanation of why it was assigned to its category based on the user's preferences.
Your output MUST be valid JSON:
{
"shows": [
{
"title": string,
"explanation": string,
"category": "Definitely Like" | "Might Like" | "Questionable" | "Will Not Like"
}
]
}
Rules:
- Preserve the exact title and category as given
- Keep explanations concise (1-2 sentences max)
- Reference specific user preferences in the explanation
- Be honest — explain why "Questionable" or "Will Not Like" shows got that rating`,
},
{
role: 'user',
content: `User preferences summary:
Liked: ${JSON.stringify(interpreter.liked)}
Themes: ${JSON.stringify(interpreter.themes)}
Tone: ${JSON.stringify(interpreter.tone)}
Character preferences: ${JSON.stringify(interpreter.character_preferences)}
Avoid: ${JSON.stringify(interpreter.avoid)}
Shows to describe:
${showList}`,
},
],
});
const content = response.choices[0]?.message?.content ?? '{"shows":[]}';
const result = JSON.parse(content) as { shows: CuratorOutput[] };
return result.shows ?? [];
}

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import { openai } from '../agent.js';
import type { InterpreterOutput } from '../types/agents.js';
interface InterpreterInput {
main_prompt: string;
liked_shows: string;
disliked_shows: string;
themes: string;
feedback_context?: string;
}
export async function runInterpreter(input: InterpreterInput): Promise<InterpreterOutput> {
const feedbackSection = input.feedback_context
? `\n\nUser Feedback Context (incorporate into preferences):\n${input.feedback_context}`
: '';
const response = await openai.chat.completions.create({
model: 'gpt-5.4-mini',
temperature: 0.2,
service_tier: 'flex',
response_format: { type: 'json_object' },
messages: [
{
role: 'system',
content: `You are a TV show preference interpreter. Transform raw user input into structured, normalized preferences.
Your output MUST be valid JSON matching this schema:
{
"liked": string[], // shows the user likes
"disliked": string[], // shows the user dislikes
"themes": string[], // normalized themes (e.g. "spy" -> "espionage")
"character_preferences": string[], // character types they prefer
"tone": string[], // tone descriptors (e.g. "serious", "grounded", "dark")
"avoid": string[] // things to explicitly avoid
}
Rules:
- Extract implicit preferences from the main prompt
- Normalize terminology (e.g. "spy" → "espionage", "cop show" → "police procedural")
- Detect and resolve contradictions (prefer explicit over implicit)
- Do NOT assume anything not stated or clearly implied
- Be specific and concrete, not vague`,
},
{
role: 'user',
content: `Main prompt: ${input.main_prompt}
Liked shows: ${input.liked_shows || '(none)'}
Disliked shows: ${input.disliked_shows || '(none)'}
Themes and requirements: ${input.themes || '(none)'}${feedbackSection}`,
},
],
});
const content = response.choices[0]?.message?.content ?? '{}';
return JSON.parse(content) as InterpreterOutput;
}

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import { openai } from '../agent.js';
import type { InterpreterOutput, RetrievalOutput, RankingOutput } from '../types/agents.js';
export async function runRanking(
interpreter: InterpreterOutput,
retrieval: RetrievalOutput,
): Promise<RankingOutput> {
// Phase 1: Pre-filter — remove avoidance violations
const avoidList = interpreter.avoid.map((a) => a.toLowerCase());
const filtered = retrieval.candidates.filter((c) => {
const text = (c.title + ' ' + c.reason).toLowerCase();
return !avoidList.some((a) => text.includes(a));
});
// Phase 2: Chunked ranking — split into groups of ~15
const CHUNK_SIZE = 15;
const chunks: typeof filtered[] = [];
for (let i = 0; i < filtered.length; i += CHUNK_SIZE) {
chunks.push(filtered.slice(i, i + CHUNK_SIZE));
}
const allBuckets: RankingOutput = {
definitely_like: [],
might_like: [],
questionable: [],
will_not_like: [],
};
for (const chunk of chunks) {
const chunkTitles = chunk.map((c) => `- ${c.title}: ${c.reason}`).join('\n');
const response = await openai.chat.completions.create({
model: 'gpt-5.4',
temperature: 0.2,
service_tier: 'flex',
response_format: { type: 'json_object' },
messages: [
{
role: 'system',
content: `You are a TV show ranking critic. Assign each show to exactly one of four confidence buckets based on how well it matches the user's preferences.
Buckets:
- "definitely_like": Near-perfect match to all preferences
- "might_like": Strong match to most preferences
- "questionable": Partial alignment, some aspects don't match
- "will_not_like": Likely mismatch, conflicts with preferences or avoidance criteria
Your output MUST be valid JSON:
{
"definitely_like": string[],
"might_like": string[],
"questionable": string[],
"will_not_like": string[]
}
Every show in the input must appear in exactly one bucket. Use the title exactly as given.`,
},
{
role: 'user',
content: `User preferences:
Liked shows: ${JSON.stringify(interpreter.liked)}
Themes: ${JSON.stringify(interpreter.themes)}
Character preferences: ${JSON.stringify(interpreter.character_preferences)}
Tone: ${JSON.stringify(interpreter.tone)}
Avoid: ${JSON.stringify(interpreter.avoid)}
Rank these shows:
${chunkTitles}`,
},
],
});
const content = response.choices[0]?.message?.content ?? '{}';
const chunkResult = JSON.parse(content) as Partial<RankingOutput>;
allBuckets.definitely_like.push(...(chunkResult.definitely_like ?? []));
allBuckets.might_like.push(...(chunkResult.might_like ?? []));
allBuckets.questionable.push(...(chunkResult.questionable ?? []));
allBuckets.will_not_like.push(...(chunkResult.will_not_like ?? []));
}
return allBuckets;
}

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import { openai } from '../agent.js';
import type { InterpreterOutput, RetrievalOutput } from '../types/agents.js';
export async function runRetrieval(input: InterpreterOutput): Promise<RetrievalOutput> {
const response = await openai.chat.completions.create({
model: 'gpt-5.4',
temperature: 0.9,
service_tier: 'flex',
response_format: { type: 'json_object' },
messages: [
{
role: 'system',
content: `You are a TV show candidate generator. Your goal is to brainstorm a LARGE, DIVERSE pool of 6080 TV show candidates that match the user's structured preferences.
Your output MUST be valid JSON matching this schema:
{
"candidates": [
{ "title": string, "reason": string }
]
}
Rules:
- Include both well-known and obscure shows
- Prioritize RECALL over precision — it's better to include too many than too few
- Each "reason" should briefly explain why the show matches the preferences
- Avoid duplicates
- Include shows from different decades, countries, and networks
- Aim for 6080 candidates minimum`,
},
{
role: 'user',
content: `Structured preferences:
Liked shows: ${JSON.stringify(input.liked)}
Disliked shows: ${JSON.stringify(input.disliked)}
Themes: ${JSON.stringify(input.themes)}
Character preferences: ${JSON.stringify(input.character_preferences)}
Tone: ${JSON.stringify(input.tone)}
Avoid: ${JSON.stringify(input.avoid)}
Generate a large, diverse pool of TV show candidates.`,
},
],
});
const content = response.choices[0]?.message?.content ?? '{"candidates":[]}';
return JSON.parse(content) as RetrievalOutput;
}

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import { drizzle } from 'drizzle-orm/postgres-js';
import postgres from 'postgres';
import * as dotenv from 'dotenv';
dotenv.config();
const connectionString = process.env.DATABASE_URL || 'postgres://user:password@iris.haven:5432/recommender';
export const client = postgres(connectionString);
export const db = drizzle(client);

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export { db, client } from '../db.js';
export * as schema from './schema.js';

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import { pgTable, uuid, text, jsonb, timestamp, integer, uniqueIndex } from 'drizzle-orm/pg-core';
import type { CuratorOutput } from '../types/agents.js';
export const recommendations = pgTable('recommendations', {
id: uuid('id').defaultRandom().primaryKey(),
title: text('title').notNull(),
main_prompt: text('main_prompt').notNull(),
liked_shows: text('liked_shows').notNull().default(''),
disliked_shows: text('disliked_shows').notNull().default(''),
themes: text('themes').notNull().default(''),
recommendations: jsonb('recommendations').$type<CuratorOutput[]>(),
status: text('status').notNull().default('pending'),
created_at: timestamp('created_at').defaultNow().notNull(),
});
export const feedback = pgTable(
'feedback',
{
id: uuid('id').defaultRandom().primaryKey(),
tv_show_name: text('tv_show_name').notNull(),
stars: integer('stars').notNull(),
feedback: text('feedback').notNull().default(''),
created_at: timestamp('created_at').defaultNow().notNull(),
},
(table) => [uniqueIndex('feedback_tv_show_name_idx').on(table.tv_show_name)],
);

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import Fastify from 'fastify';
import * as dotenv from 'dotenv';
import recommendationsRoute from './routes/recommendations.js';
import feedbackRoute from './routes/feedback.js';
// Load .env first, then .env.local
// env vars set on the container take precedence over both files
dotenv.config();
dotenv.config({ path: '.env.local', override: true });
const fastify = Fastify({ logger: true });
// CORS — allow frontend dev server and production
fastify.addHook('onRequest', async (_req, reply) => {
reply.header('Access-Control-Allow-Origin', '*');
reply.header('Access-Control-Allow-Methods', 'GET,POST,OPTIONS');
reply.header('Access-Control-Allow-Headers', 'Content-Type');
});
fastify.options('*', async (_req, reply) => {
return reply.send();
});
// Body parsing is included in Fastify by default for JSON
await fastify.register(recommendationsRoute);
await fastify.register(feedbackRoute);
const port = Number(process.env['PORT'] ?? 3000);
try {
await fastify.listen({ port, host: '0.0.0.0' });
console.log(`Backend listening on http://localhost:${port}`);
} catch (err) {
fastify.log.error(err);
process.exit(1);
}

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import { eq } from 'drizzle-orm';
import { db } from '../db.js';
import { recommendations } from '../db/schema.js';
import { runInterpreter } from '../agents/interpreter.js';
import { runRetrieval } from '../agents/retrieval.js';
import { runRanking } from '../agents/ranking.js';
import { runCurator } from '../agents/curator.js';
import type { CuratorOutput, SSEEvent } from '../types/agents.js';
type RecommendationRecord = typeof recommendations.$inferSelect;
function log(recId: string, msg: string, data?: unknown) {
const ts = new Date().toISOString();
if (data !== undefined) {
console.log(`[pipeline] [${ts}] [${recId}] ${msg}`, data);
} else {
console.log(`[pipeline] [${ts}] [${recId}] ${msg}`);
}
}
export async function runPipeline(
rec: RecommendationRecord,
sseWrite: (event: SSEEvent) => void,
feedbackContext?: string,
): Promise<CuratorOutput[]> {
let currentStage: SSEEvent['stage'] = 'interpreter';
const startTime = Date.now();
log(rec.id, `Starting pipeline for "${rec.title}"${feedbackContext ? ' (with feedback context)' : ''}`);
try {
// Set status to running
log(rec.id, 'Setting status → running');
await db
.update(recommendations)
.set({ status: 'running' })
.where(eq(recommendations.id, rec.id));
// --- Interpreter ---
currentStage = 'interpreter';
log(rec.id, 'Interpreter: start');
sseWrite({ stage: 'interpreter', status: 'start' });
const t0 = Date.now();
const interpreterOutput = await runInterpreter({
main_prompt: rec.main_prompt,
liked_shows: rec.liked_shows,
disliked_shows: rec.disliked_shows,
themes: rec.themes,
...(feedbackContext !== undefined ? { feedback_context: feedbackContext } : {}),
});
log(rec.id, `Interpreter: done (${Date.now() - t0}ms)`, {
liked: interpreterOutput.liked,
disliked: interpreterOutput.disliked,
themes: interpreterOutput.themes,
tone: interpreterOutput.tone,
avoid: interpreterOutput.avoid,
});
sseWrite({ stage: 'interpreter', status: 'done', data: interpreterOutput });
// --- Retrieval ---
currentStage = 'retrieval';
log(rec.id, 'Retrieval: start');
sseWrite({ stage: 'retrieval', status: 'start' });
const t1 = Date.now();
const retrievalOutput = await runRetrieval(interpreterOutput);
log(rec.id, `Retrieval: done (${Date.now() - t1}ms) — ${retrievalOutput.candidates.length} candidates`, {
titles: retrievalOutput.candidates.map((c) => c.title),
});
sseWrite({ stage: 'retrieval', status: 'done', data: retrievalOutput });
// --- Ranking ---
currentStage = 'ranking';
log(rec.id, 'Ranking: start');
sseWrite({ stage: 'ranking', status: 'start' });
const t2 = Date.now();
const rankingOutput = await runRanking(interpreterOutput, retrievalOutput);
log(rec.id, `Ranking: done (${Date.now() - t2}ms)`, {
definitely_like: rankingOutput.definitely_like.length,
might_like: rankingOutput.might_like.length,
questionable: rankingOutput.questionable.length,
will_not_like: rankingOutput.will_not_like.length,
});
sseWrite({ stage: 'ranking', status: 'done', data: rankingOutput });
// --- Curator ---
currentStage = 'curator';
log(rec.id, 'Curator: start');
sseWrite({ stage: 'curator', status: 'start' });
const t3 = Date.now();
const curatorOutput = await runCurator(rankingOutput, interpreterOutput);
log(rec.id, `Curator: done (${Date.now() - t3}ms) — ${curatorOutput.length} shows curated`);
sseWrite({ stage: 'curator', status: 'done', data: curatorOutput });
// Save results to DB
log(rec.id, 'Saving results to DB');
await db
.update(recommendations)
.set({ recommendations: curatorOutput, status: 'done' })
.where(eq(recommendations.id, rec.id));
sseWrite({ stage: 'complete', status: 'done' });
log(rec.id, `Pipeline complete (total: ${Date.now() - startTime}ms)`);
return curatorOutput;
} catch (err) {
const message = err instanceof Error ? err.message : String(err);
log(rec.id, `Pipeline error at stage "${currentStage}": ${message}`);
sseWrite({ stage: currentStage, status: 'error', data: { message } });
await db
.update(recommendations)
.set({ status: 'error' })
.where(eq(recommendations.id, rec.id));
return [];
}
}

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import type { FastifyInstance } from 'fastify';
import { eq } from 'drizzle-orm';
import { db } from '../db.js';
import { feedback } from '../db/schema.js';
export default async function feedbackRoute(fastify: FastifyInstance) {
// POST /feedback — upsert by tv_show_name
fastify.post('/feedback', async (request, reply) => {
const body = request.body as {
tv_show_name: string;
stars: number;
feedback?: string;
};
await db
.insert(feedback)
.values({
tv_show_name: body.tv_show_name,
stars: body.stars,
feedback: body.feedback ?? '',
})
.onConflictDoUpdate({
target: feedback.tv_show_name,
set: {
stars: body.stars,
feedback: body.feedback ?? '',
},
});
return reply.code(201).send({ ok: true });
});
// GET /feedback — return all feedback entries
fastify.get('/feedback', async (_request, reply) => {
const rows = await db.select().from(feedback);
return reply.send(rows);
});
}

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import type { FastifyInstance } from 'fastify';
import { eq, desc } from 'drizzle-orm';
import { db } from '../db.js';
import { recommendations, feedback } from '../db/schema.js';
import { runPipeline } from '../pipelines/recommendation.js';
import type { SSEEvent } from '../types/agents.js';
export default async function recommendationsRoute(fastify: FastifyInstance) {
// POST /recommendations — create record, return { id }
fastify.post('/recommendations', async (request, reply) => {
const body = request.body as {
main_prompt: string;
liked_shows?: string;
disliked_shows?: string;
themes?: string;
};
const title = (body.main_prompt ?? '')
.trim()
.split(/\s+/)
.slice(0, 5)
.join(' ');
const [rec] = await db
.insert(recommendations)
.values({
title: title || 'Untitled',
main_prompt: body.main_prompt ?? '',
liked_shows: body.liked_shows ?? '',
disliked_shows: body.disliked_shows ?? '',
themes: body.themes ?? '',
status: 'pending',
})
.returning({ id: recommendations.id });
return reply.code(201).send({ id: rec?.id });
});
// GET /recommendations — list all
fastify.get('/recommendations', async (_request, reply) => {
const rows = await db
.select({
id: recommendations.id,
title: recommendations.title,
status: recommendations.status,
created_at: recommendations.created_at,
})
.from(recommendations)
.orderBy(desc(recommendations.created_at));
return reply.send(rows);
});
// GET /recommendations/:id — full record
fastify.get('/recommendations/:id', async (request, reply) => {
const { id } = request.params as { id: string };
const [rec] = await db
.select()
.from(recommendations)
.where(eq(recommendations.id, id));
if (!rec) return reply.code(404).send({ error: 'Not found' });
return reply.send(rec);
});
// GET /recommendations/:id/stream — SSE pipeline stream
// Always fetches all current feedback and injects if present (supports rerank flow)
fastify.get('/recommendations/:id/stream', async (request, reply) => {
const { id } = request.params as { id: string };
const [rec] = await db
.select()
.from(recommendations)
.where(eq(recommendations.id, id));
if (!rec) return reply.code(404).send({ error: 'Not found' });
// Load all feedback to potentially inject as context
const feedbackRows = await db.select().from(feedback);
const feedbackContext =
feedbackRows.length > 0
? feedbackRows
.map(
(f) =>
`Show: "${f.tv_show_name}" — Rating: ${f.stars}/3 stars${f.feedback ? ` — Comment: ${f.feedback}` : ''}`,
)
.join('\n')
: undefined;
// Set SSE headers and hijack
reply.raw.setHeader('Content-Type', 'text/event-stream');
reply.raw.setHeader('Cache-Control', 'no-cache');
reply.raw.setHeader('Connection', 'keep-alive');
reply.raw.setHeader('Access-Control-Allow-Origin', '*');
reply.raw.flushHeaders();
reply.hijack();
const sseWrite = (event: SSEEvent) => {
reply.raw.write(`data: ${JSON.stringify(event)}\n\n`);
};
try {
await runPipeline(rec, sseWrite, feedbackContext);
} finally {
reply.raw.end();
}
});
// POST /recommendations/:id/rerank — reset status so client can re-open SSE stream
fastify.post('/recommendations/:id/rerank', async (request, reply) => {
const { id } = request.params as { id: string };
const [rec] = await db
.select({ id: recommendations.id })
.from(recommendations)
.where(eq(recommendations.id, id));
if (!rec) return reply.code(404).send({ error: 'Not found' });
await db
.update(recommendations)
.set({ status: 'pending' })
.where(eq(recommendations.id, id));
return reply.send({ ok: true });
});
}

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export interface InterpreterOutput {
liked: string[];
disliked: string[];
themes: string[];
character_preferences: string[];
tone: string[];
avoid: string[];
}
export interface RetrievalCandidate {
title: string;
reason: string;
}
export interface RetrievalOutput {
candidates: RetrievalCandidate[];
}
export interface RankingOutput {
definitely_like: string[];
might_like: string[];
questionable: string[];
will_not_like: string[];
}
export type CuratorCategory = 'Definitely Like' | 'Might Like' | 'Questionable' | 'Will Not Like';
export interface CuratorOutput {
title: string;
explanation: string;
category: CuratorCategory;
}
export type PipelineStage = 'interpreter' | 'retrieval' | 'ranking' | 'curator' | 'complete';
export type SSEStatus = 'start' | 'done' | 'error';
export interface SSEEvent {
stage: PipelineStage;
status: SSEStatus;
data?: unknown;
}

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{
// Visit https://aka.ms/tsconfig to read more about this file
"compilerOptions": {
// File Layout
// "rootDir": "./src",
// "outDir": "./dist",
// Environment Settings
// See also https://aka.ms/tsconfig/module
"module": "nodenext",
"target": "esnext",
"types": [],
// For nodejs:
// "lib": ["esnext"],
// "types": ["node"],
// and npm install -D @types/node
// Other Outputs
"sourceMap": true,
"declaration": true,
"declarationMap": true,
// Stricter Typechecking Options
"noUncheckedIndexedAccess": true,
"exactOptionalPropertyTypes": true,
// Style Options
// "noImplicitReturns": true,
// "noImplicitOverride": true,
// "noUnusedLocals": true,
// "noUnusedParameters": true,
// "noFallthroughCasesInSwitch": true,
// "noPropertyAccessFromIndexSignature": true,
// Recommended Options
"strict": true,
"jsx": "react-jsx",
"verbatimModuleSyntax": true,
"isolatedModules": true,
"noUncheckedSideEffectImports": true,
"moduleDetection": "force",
"skipLibCheck": true,
}
}

24
packages/frontend/.gitignore vendored Normal file
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@@ -0,0 +1,24 @@
# Logs
logs
*.log
npm-debug.log*
yarn-debug.log*
yarn-error.log*
pnpm-debug.log*
lerna-debug.log*
node_modules
dist
dist-ssr
*.local
# Editor directories and files
.vscode/*
!.vscode/extensions.json
.idea
.DS_Store
*.suo
*.ntvs*
*.njsproj
*.sln
*.sw?

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<!doctype html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<link rel="icon" type="image/svg+xml" href="/favicon.svg" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>frontend</title>
</head>
<body>
<div id="app"></div>
<script type="module" src="/src/main.tsx"></script>
</body>
</html>

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{
"name": "frontend",
"private": true,
"version": "0.0.0",
"type": "module",
"scripts": {
"dev": "vite",
"build": "tsc -b && vite build",
"preview": "vite preview"
},
"dependencies": {
"preact": "^10.29.0"
},
"devDependencies": {
"@preact/preset-vite": "^2.10.4",
"@types/node": "^24.12.0",
"typescript": "~5.9.3",
"vite": "^8.0.1"
}
}

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import type { Recommendation, RecommendationSummary, FeedbackEntry } from '../types/index.js';
const BASE = '/api';
async function request<T>(path: string, options?: RequestInit): Promise<T> {
const res = await fetch(`${BASE}${path}`, {
headers: { 'Content-Type': 'application/json' },
...options,
});
if (!res.ok) {
const text = await res.text();
throw new Error(`HTTP ${res.status}: ${text}`);
}
return res.json() as Promise<T>;
}
export function createRecommendation(body: {
main_prompt: string;
liked_shows: string;
disliked_shows: string;
themes: string;
}): Promise<{ id: string }> {
return request('/recommendations', {
method: 'POST',
body: JSON.stringify(body),
});
}
export function listRecommendations(): Promise<RecommendationSummary[]> {
return request('/recommendations');
}
export function getRecommendation(id: string): Promise<Recommendation> {
return request(`/recommendations/${id}`);
}
export function rerankRecommendation(id: string): Promise<{ ok: boolean }> {
return request(`/recommendations/${id}/rerank`, { method: 'POST' });
}
export function submitFeedback(body: {
tv_show_name: string;
stars: number;
feedback?: string;
}): Promise<{ ok: boolean }> {
return request('/feedback', {
method: 'POST',
body: JSON.stringify(body),
});
}
export function getFeedback(): Promise<FeedbackEntry[]> {
return request('/feedback');
}

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/* App-level styles are in index.css */

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import { Home } from './pages/Home.js';
export function App() {
return <Home />;
}

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import { useState } from 'preact/hooks';
interface NewRecommendationModalProps {
onClose: () => void;
onSubmit: (body: {
main_prompt: string;
liked_shows: string;
disliked_shows: string;
themes: string;
}) => Promise<void>;
}
export function NewRecommendationModal({ onClose, onSubmit }: NewRecommendationModalProps) {
const [mainPrompt, setMainPrompt] = useState('');
const [likedShows, setLikedShows] = useState('');
const [dislikedShows, setDislikedShows] = useState('');
const [themes, setThemes] = useState('');
const [loading, setLoading] = useState(false);
const handleSubmit = async (e: Event) => {
e.preventDefault();
if (!mainPrompt.trim()) return;
setLoading(true);
try {
await onSubmit({
main_prompt: mainPrompt.trim(),
liked_shows: likedShows.trim(),
disliked_shows: dislikedShows.trim(),
themes: themes.trim(),
});
onClose();
} finally {
setLoading(false);
}
};
const handleBackdropClick = (e: MouseEvent) => {
if ((e.target as HTMLElement).classList.contains('modal-backdrop')) {
onClose();
}
};
return (
<div class="modal-backdrop" onClick={handleBackdropClick}>
<div class="modal">
<div class="modal-header">
<h2>New Recommendation</h2>
<button class="modal-close" onClick={onClose} aria-label="Close">×</button>
</div>
<form class="modal-form" onSubmit={handleSubmit}>
<div class="form-group">
<label for="main-prompt">What are you looking for?</label>
<textarea
id="main-prompt"
class="form-textarea"
placeholder="Describe what you want to watch. Be as specific as you like — mood, themes, setting, what you've enjoyed before..."
value={mainPrompt}
onInput={(e) => setMainPrompt((e.target as HTMLTextAreaElement).value)}
rows={5}
required
/>
</div>
<div class="form-row">
<div class="form-group">
<label for="liked-shows">Shows you liked</label>
<input
id="liked-shows"
type="text"
class="form-input"
placeholder="e.g. Breaking Bad, The Wire"
value={likedShows}
onInput={(e) => setLikedShows((e.target as HTMLInputElement).value)}
/>
</div>
<div class="form-group">
<label for="disliked-shows">Shows you disliked</label>
<input
id="disliked-shows"
type="text"
class="form-input"
placeholder="e.g. Game of Thrones"
value={dislikedShows}
onInput={(e) => setDislikedShows((e.target as HTMLInputElement).value)}
/>
</div>
</div>
<div class="form-group">
<label for="themes">Themes and requirements</label>
<input
id="themes"
type="text"
class="form-input"
placeholder="e.g. dramatic setting, historical, sci-fi, etc."
value={themes}
onInput={(e) => setThemes((e.target as HTMLInputElement).value)}
/>
</div>
<div class="modal-actions">
<button type="button" class="btn-secondary" onClick={onClose} disabled={loading}>
Cancel
</button>
<button type="submit" class="btn-primary" disabled={loading || !mainPrompt.trim()}>
{loading ? 'Starting…' : 'Get Recommendations'}
</button>
</div>
</form>
</div>
</div>
);
}

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import type { StageMap, StageStatus } from '../types/index.js';
const STAGES: { key: keyof StageMap; label: string }[] = [
{ key: 'interpreter', label: 'Interpreting Preferences' },
{ key: 'retrieval', label: 'Generating Candidates' },
{ key: 'ranking', label: 'Ranking Shows' },
{ key: 'curator', label: 'Curating Results' },
];
interface PipelineProgressProps {
stages: StageMap;
}
function StageIcon({ status }: { status: StageStatus }) {
switch (status) {
case 'done':
return <span class="stage-icon stage-done"></span>;
case 'error':
return <span class="stage-icon stage-error"></span>;
case 'running':
return <span class="stage-icon stage-running spinner"></span>;
default:
return <span class="stage-icon stage-pending"></span>;
}
}
export function PipelineProgress({ stages }: PipelineProgressProps) {
return (
<div class="pipeline-progress">
<h3 class="pipeline-title">Generating Recommendations</h3>
<ul class="pipeline-steps">
{STAGES.map(({ key, label }) => (
<li key={key} class={`pipeline-step pipeline-step--${stages[key]}`}>
<StageIcon status={stages[key]} />
<span class="pipeline-step-label">{label}</span>
</li>
))}
</ul>
</div>
);
}

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import { useState } from 'preact/hooks';
import type { CuratorOutput, CuratorCategory } from '../types/index.js';
interface RecommendationCardProps {
show: CuratorOutput;
existingFeedback?: { stars: number; feedback: string };
onFeedback: (tv_show_name: string, stars: number, feedback: string) => Promise<void>;
}
const CATEGORY_COLORS: Record<CuratorCategory, string> = {
'Definitely Like': 'badge-green',
'Might Like': 'badge-blue',
'Questionable': 'badge-yellow',
'Will Not Like': 'badge-red',
};
export function RecommendationCard({ show, existingFeedback, onFeedback }: RecommendationCardProps) {
const [selectedStars, setSelectedStars] = useState(existingFeedback?.stars ?? 0);
const [comment, setComment] = useState(existingFeedback?.feedback ?? '');
const [showComment, setShowComment] = useState(false);
const [submitted, setSubmitted] = useState(!!existingFeedback);
const [saving, setSaving] = useState(false);
const handleStarClick = (stars: number) => {
setSelectedStars(stars);
setShowComment(true);
};
const handleSubmit = async () => {
if (!selectedStars) return;
setSaving(true);
try {
await onFeedback(show.title, selectedStars, comment);
setSubmitted(true);
setShowComment(false);
} finally {
setSaving(false);
}
};
return (
<div class="card">
<div class="card-header">
<span class={`badge ${CATEGORY_COLORS[show.category]}`}>{show.category}</span>
<h3 class="card-title">{show.title}</h3>
</div>
<p class="card-explanation">{show.explanation}</p>
<div class="card-feedback">
<div class="star-rating">
{[1, 2, 3].map((star) => (
<button
key={star}
class={`star-btn${selectedStars >= star ? ' star-active' : ''}`}
onClick={() => handleStarClick(star)}
aria-label={`Rate ${star} star${star > 1 ? 's' : ''}`}
>
{selectedStars >= star ? '★' : '☆'}
</button>
))}
{submitted && <span class="feedback-saved">Saved</span>}
</div>
{showComment && !submitted && (
<div class="comment-area">
<textarea
class="form-textarea comment-input"
placeholder="Optional comment…"
value={comment}
onInput={(e) => setComment((e.target as HTMLTextAreaElement).value)}
rows={2}
/>
<button
class="btn-primary btn-sm"
onClick={handleSubmit}
disabled={saving || !selectedStars}
>
{saving ? 'Saving…' : 'Save Feedback'}
</button>
</div>
)}
</div>
</div>
);
}

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import type { RecommendationSummary } from '../types/index.js';
interface SidebarProps {
list: RecommendationSummary[];
selectedId: string | null;
onSelect: (id: string) => void;
onNewClick: () => void;
}
function statusIcon(status: RecommendationSummary['status']): string {
switch (status) {
case 'done': return '✓';
case 'error': return '✗';
case 'running': return '⟳';
default: return '…';
}
}
function statusClass(status: RecommendationSummary['status']): string {
switch (status) {
case 'done': return 'status-done';
case 'error': return 'status-error';
case 'running': return 'status-running';
default: return 'status-pending';
}
}
export function Sidebar({ list, selectedId, onSelect, onNewClick }: SidebarProps) {
return (
<aside class="sidebar">
<div class="sidebar-header">
<span class="sidebar-title">Recommender</span>
</div>
<button class="btn-new" onClick={onNewClick}>
+ New Recommendation
</button>
<div class="sidebar-section-label">History</div>
<ul class="sidebar-list">
{list.length === 0 && (
<li class="sidebar-empty">No recommendations yet</li>
)}
{list.map((item) => (
<li
key={item.id}
class={`sidebar-item${selectedId === item.id ? ' selected' : ''}`}
onClick={() => onSelect(item.id)}
>
<span class={`sidebar-icon ${statusClass(item.status)}`}>
{statusIcon(item.status)}
</span>
<span class="sidebar-item-title">{item.title}</span>
</li>
))}
</ul>
</aside>
);
}

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import { useState, useEffect, useCallback } from 'preact/hooks';
import type { RecommendationSummary, FeedbackEntry } from '../types/index.js';
import {
listRecommendations,
createRecommendation,
rerankRecommendation,
submitFeedback,
getFeedback,
} from '../api/client.js';
export function useRecommendations() {
const [list, setList] = useState<RecommendationSummary[]>([]);
const [selectedId, setSelectedId] = useState<string | null>(null);
const [feedback, setFeedback] = useState<FeedbackEntry[]>([]);
const refreshList = useCallback(async () => {
const rows = await listRecommendations();
setList(rows);
}, []);
const refreshFeedback = useCallback(async () => {
const rows = await getFeedback();
setFeedback(rows);
}, []);
useEffect(() => {
void refreshList();
void refreshFeedback();
}, [refreshList, refreshFeedback]);
const createNew = useCallback(
async (body: {
main_prompt: string;
liked_shows: string;
disliked_shows: string;
themes: string;
}) => {
const { id } = await createRecommendation(body);
await refreshList();
setSelectedId(id);
return id;
},
[refreshList],
);
const rerank = useCallback(
async (id: string) => {
await rerankRecommendation(id);
// Update local list to show pending status
setList((prev) =>
prev.map((r) => (r.id === id ? { ...r, status: 'pending' as const } : r)),
);
},
[],
);
const handleSubmitFeedback = useCallback(
async (body: { tv_show_name: string; stars: number; feedback?: string }) => {
await submitFeedback(body);
await refreshFeedback();
},
[refreshFeedback],
);
const updateStatus = useCallback(
(id: string, status: RecommendationSummary['status']) => {
setList((prev) => prev.map((r) => (r.id === id ? { ...r, status } : r)));
},
[],
);
return {
list,
selectedId,
feedback,
setSelectedId,
createNew,
rerank,
submitFeedback: handleSubmitFeedback,
updateStatus,
refreshList,
};
}

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import { useEffect, useRef } from 'preact/hooks';
import type { SSEEvent } from '../types/index.js';
export function useSSE(
url: string | null,
onEvent: (event: SSEEvent) => void,
): { close: () => void } {
const esRef = useRef<EventSource | null>(null);
const onEventRef = useRef(onEvent);
onEventRef.current = onEvent;
useEffect(() => {
if (!url) return;
const es = new EventSource(url);
esRef.current = es;
es.onmessage = (e: MessageEvent) => {
try {
const event = JSON.parse(e.data as string) as SSEEvent;
onEventRef.current(event);
if (event.stage === 'complete' || event.status === 'error') {
es.close();
esRef.current = null;
}
} catch {
// ignore parse errors
}
};
es.onerror = () => {
es.close();
esRef.current = null;
};
return () => {
es.close();
esRef.current = null;
};
}, [url]);
return {
close: () => {
esRef.current?.close();
esRef.current = null;
},
};
}

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*, *::before, *::after {
box-sizing: border-box;
margin: 0;
padding: 0;
}
:root {
--bg: #0f1117;
--bg-surface: #1a1d27;
--bg-surface-2: #222535;
--bg-surface-3: #2a2e42;
--border: #2e3248;
--text: #e2e4ed;
--text-muted: #8a8fa8;
--text-dim: #5a5f77;
--accent: #6366f1;
--accent-hover: #4f52d9;
--accent-dim: rgba(99, 102, 241, 0.15);
--green: #22c55e;
--blue: #3b82f6;
--yellow: #eab308;
--red: #ef4444;
--radius: 8px;
--radius-sm: 4px;
--sidebar-width: 260px;
font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
font-size: 14px;
color: var(--text);
background: var(--bg);
-webkit-font-smoothing: antialiased;
}
html, body, #app {
height: 100%;
width: 100%;
overflow: hidden;
}
/* ── Layout ────────────────────────────────────────────── */
.layout {
display: flex;
height: 100vh;
overflow: hidden;
}
.main-content {
flex: 1;
overflow-y: auto;
padding: 32px;
}
/* ── Sidebar ────────────────────────────────────────────── */
.sidebar {
width: var(--sidebar-width);
background: var(--bg-surface);
border-right: 1px solid var(--border);
display: flex;
flex-direction: column;
overflow: hidden;
flex-shrink: 0;
}
.sidebar-header {
padding: 20px 16px 12px;
border-bottom: 1px solid var(--border);
}
.sidebar-title {
font-size: 16px;
font-weight: 700;
color: var(--text);
letter-spacing: -0.3px;
}
.btn-new {
margin: 12px;
padding: 10px 14px;
background: var(--accent);
color: #fff;
border: none;
border-radius: var(--radius);
font-size: 13px;
font-weight: 600;
cursor: pointer;
transition: background 0.15s;
text-align: left;
}
.btn-new:hover {
background: var(--accent-hover);
}
.sidebar-section-label {
padding: 8px 16px 4px;
font-size: 11px;
font-weight: 600;
letter-spacing: 0.06em;
text-transform: uppercase;
color: var(--text-dim);
}
.sidebar-list {
list-style: none;
overflow-y: auto;
flex: 1;
padding: 4px 8px 8px;
}
.sidebar-empty {
padding: 8px;
color: var(--text-dim);
font-size: 13px;
}
.sidebar-item {
display: flex;
align-items: center;
gap: 8px;
padding: 8px 10px;
border-radius: var(--radius-sm);
cursor: pointer;
color: var(--text-muted);
font-size: 13px;
transition: background 0.1s, color 0.1s;
user-select: none;
}
.sidebar-item:hover {
background: var(--bg-surface-2);
color: var(--text);
}
.sidebar-item.selected {
background: var(--accent-dim);
color: var(--text);
}
.sidebar-icon {
font-size: 12px;
width: 16px;
text-align: center;
flex-shrink: 0;
}
.status-done { color: var(--green); }
.status-error { color: var(--red); }
.status-running { color: var(--accent); }
.status-pending { color: var(--text-dim); }
.sidebar-item-title {
overflow: hidden;
text-overflow: ellipsis;
white-space: nowrap;
}
/* ── Main content areas ─────────────────────────────────── */
.empty-state {
display: flex;
flex-direction: column;
align-items: center;
justify-content: center;
height: 100%;
gap: 12px;
color: var(--text-muted);
text-align: center;
}
.empty-state h2 {
font-size: 24px;
font-weight: 700;
color: var(--text);
}
.content-area {
max-width: 860px;
margin: 0 auto;
}
.rec-title {
font-size: 20px;
font-weight: 700;
color: var(--text);
margin-bottom: 24px;
}
.error-state {
color: var(--text-muted);
}
.error-state h2 {
color: var(--red);
margin-bottom: 8px;
}
.error-state p {
margin-bottom: 16px;
}
/* ── Pipeline Progress ──────────────────────────────────── */
.pipeline-progress {
padding: 40px 0;
}
.pipeline-title {
font-size: 18px;
font-weight: 600;
color: var(--text);
margin-bottom: 24px;
}
.pipeline-steps {
list-style: none;
display: flex;
flex-direction: column;
gap: 12px;
}
.pipeline-step {
display: flex;
align-items: center;
gap: 12px;
padding: 12px 16px;
background: var(--bg-surface);
border: 1px solid var(--border);
border-radius: var(--radius);
font-size: 14px;
}
.pipeline-step--running {
border-color: var(--accent);
background: var(--accent-dim);
}
.pipeline-step--done {
border-color: rgba(34, 197, 94, 0.3);
background: rgba(34, 197, 94, 0.05);
}
.pipeline-step--error {
border-color: rgba(239, 68, 68, 0.3);
background: rgba(239, 68, 68, 0.05);
}
.stage-icon {
font-size: 16px;
width: 20px;
text-align: center;
}
.stage-done { color: var(--green); }
.stage-error { color: var(--red); }
.stage-running { color: var(--accent); }
.stage-pending { color: var(--text-dim); }
.spinner {
display: inline-block;
animation: spin 1s linear infinite;
}
@keyframes spin {
from { transform: rotate(0deg); }
to { transform: rotate(360deg); }
}
.pipeline-step-label {
font-weight: 500;
}
/* ── Cards ─────────────────────────────────────────────── */
.cards-grid {
display: flex;
flex-direction: column;
gap: 12px;
margin-bottom: 32px;
}
.card {
background: var(--bg-surface);
border: 1px solid var(--border);
border-radius: var(--radius);
padding: 16px;
transition: border-color 0.15s;
}
.card:hover {
border-color: var(--bg-surface-3);
}
.card-header {
display: flex;
align-items: center;
gap: 10px;
margin-bottom: 8px;
flex-wrap: wrap;
}
.badge {
font-size: 11px;
font-weight: 600;
padding: 2px 8px;
border-radius: 100px;
text-transform: uppercase;
letter-spacing: 0.04em;
flex-shrink: 0;
}
.badge-green { background: rgba(34,197,94,0.15); color: #4ade80; }
.badge-blue { background: rgba(59,130,246,0.15); color: #60a5fa; }
.badge-yellow{ background: rgba(234,179,8,0.15); color: #facc15; }
.badge-red { background: rgba(239,68,68,0.15); color: #f87171; }
.card-title {
font-size: 16px;
font-weight: 600;
color: var(--text);
}
.card-explanation {
font-size: 13px;
color: var(--text-muted);
line-height: 1.5;
margin-bottom: 12px;
}
.card-feedback {
border-top: 1px solid var(--border);
padding-top: 10px;
}
.star-rating {
display: flex;
align-items: center;
gap: 2px;
}
.star-btn {
background: none;
border: none;
cursor: pointer;
font-size: 18px;
color: var(--text-dim);
padding: 0 2px;
transition: color 0.1s, transform 0.1s;
}
.star-btn:hover,
.star-btn.star-active {
color: var(--yellow);
}
.star-btn:hover {
transform: scale(1.1);
}
.feedback-saved {
margin-left: 8px;
font-size: 12px;
color: var(--green);
font-weight: 500;
}
.comment-area {
margin-top: 8px;
display: flex;
flex-direction: column;
gap: 6px;
}
.comment-input {
font-size: 13px;
resize: vertical;
}
/* ── Rerank Button ──────────────────────────────────────── */
.rerank-section {
padding: 16px 0 32px;
display: flex;
justify-content: center;
}
.btn-rerank {
padding: 12px 28px;
background: var(--bg-surface-2);
color: var(--text);
border: 1px solid var(--border);
border-radius: var(--radius);
font-size: 14px;
font-weight: 600;
cursor: pointer;
transition: background 0.15s, border-color 0.15s;
}
.btn-rerank:hover:not(:disabled) {
background: var(--bg-surface-3);
border-color: var(--accent);
color: var(--accent);
}
.btn-rerank:disabled {
opacity: 0.4;
cursor: not-allowed;
}
/* ── Buttons ────────────────────────────────────────────── */
.btn-primary {
padding: 10px 20px;
background: var(--accent);
color: #fff;
border: none;
border-radius: var(--radius);
font-size: 14px;
font-weight: 600;
cursor: pointer;
transition: background 0.15s;
}
.btn-primary:hover:not(:disabled) {
background: var(--accent-hover);
}
.btn-primary:disabled {
opacity: 0.5;
cursor: not-allowed;
}
.btn-primary.btn-sm {
padding: 6px 14px;
font-size: 13px;
}
.btn-secondary {
padding: 10px 20px;
background: var(--bg-surface-2);
color: var(--text-muted);
border: 1px solid var(--border);
border-radius: var(--radius);
font-size: 14px;
font-weight: 500;
cursor: pointer;
transition: background 0.15s;
}
.btn-secondary:hover:not(:disabled) {
background: var(--bg-surface-3);
}
/* ── Modal ──────────────────────────────────────────────── */
.modal-backdrop {
position: fixed;
inset: 0;
background: rgba(0, 0, 0, 0.6);
display: flex;
align-items: center;
justify-content: center;
z-index: 100;
backdrop-filter: blur(2px);
}
.modal {
background: var(--bg-surface);
border: 1px solid var(--border);
border-radius: 12px;
width: 540px;
max-width: 96vw;
max-height: 90vh;
overflow-y: auto;
box-shadow: 0 20px 60px rgba(0, 0, 0, 0.5);
}
.modal-header {
display: flex;
align-items: center;
justify-content: space-between;
padding: 20px 20px 0;
}
.modal-header h2 {
font-size: 18px;
font-weight: 700;
}
.modal-close {
background: none;
border: none;
font-size: 22px;
color: var(--text-muted);
cursor: pointer;
line-height: 1;
padding: 0;
}
.modal-close:hover {
color: var(--text);
}
.modal-form {
padding: 20px;
display: flex;
flex-direction: column;
gap: 16px;
}
.form-group {
display: flex;
flex-direction: column;
gap: 6px;
flex: 1;
}
.form-group label {
font-size: 13px;
font-weight: 500;
color: var(--text-muted);
}
.form-row {
display: flex;
gap: 12px;
}
.form-input,
.form-textarea {
background: var(--bg-surface-2);
border: 1px solid var(--border);
border-radius: var(--radius-sm);
color: var(--text);
font-size: 14px;
padding: 10px 12px;
outline: none;
transition: border-color 0.15s;
font-family: inherit;
width: 100%;
}
.form-input:focus,
.form-textarea:focus {
border-color: var(--accent);
}
.form-textarea {
resize: vertical;
min-height: 80px;
}
.modal-actions {
display: flex;
justify-content: flex-end;
gap: 10px;
padding-top: 4px;
}

View File

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import { render } from 'preact'
import './index.css'
import { App } from './app.tsx'
render(<App />, document.getElementById('app')!)

View File

@@ -0,0 +1,192 @@
import { useState, useCallback, useEffect } from 'preact/hooks';
import { Sidebar } from '../components/Sidebar.js';
import { NewRecommendationModal } from '../components/NewRecommendationModal.js';
import { PipelineProgress } from '../components/PipelineProgress.js';
import { RecommendationCard } from '../components/RecommendationCard.js';
import { useRecommendations } from '../hooks/useRecommendations.js';
import { useSSE } from '../hooks/useSSE.js';
import { getRecommendation } from '../api/client.js';
import type { Recommendation, SSEEvent, StageMap, PipelineStage } from '../types/index.js';
const DEFAULT_STAGES: StageMap = {
interpreter: 'pending',
retrieval: 'pending',
ranking: 'pending',
curator: 'pending',
};
const STAGE_ORDER: (keyof StageMap)[] = ['interpreter', 'retrieval', 'ranking', 'curator'];
export function Home() {
const {
list,
selectedId,
feedback,
setSelectedId,
createNew,
rerank,
submitFeedback,
updateStatus,
refreshList,
} = useRecommendations();
const [showModal, setShowModal] = useState(false);
const [selectedRec, setSelectedRec] = useState<Recommendation | null>(null);
const [stages, setStages] = useState<StageMap>(DEFAULT_STAGES);
const [sseUrl, setSseUrl] = useState<string | null>(null);
// Load full recommendation when selected
useEffect(() => {
if (!selectedId) {
setSelectedRec(null);
return;
}
void getRecommendation(selectedId).then((rec) => {
setSelectedRec(rec);
// If already running or pending, open SSE
if (rec.status === 'running' || rec.status === 'pending') {
setStages(DEFAULT_STAGES);
setSseUrl(`/api/recommendations/${selectedId}/stream`);
}
});
}, [selectedId]);
const handleSSEEvent = useCallback(
(event: SSEEvent) => {
if (!selectedId) return;
if (event.stage !== 'complete') {
const stageKey = event.stage as keyof StageMap;
if (STAGE_ORDER.includes(stageKey)) {
setStages((prev) => ({
...prev,
[stageKey]: event.status === 'start' ? 'running' : event.status === 'done' ? 'done' : 'error',
}));
}
}
if (event.stage === 'complete' && event.status === 'done') {
setSseUrl(null);
updateStatus(selectedId, 'done');
// Reload full recommendation to get results
void getRecommendation(selectedId).then(setSelectedRec);
void refreshList();
}
if (event.status === 'error') {
setSseUrl(null);
updateStatus(selectedId, 'error');
const stageKey = event.stage as PipelineStage;
if (stageKey !== 'complete') {
setStages((prev) => ({ ...prev, [stageKey as keyof StageMap]: 'error' }));
}
}
},
[selectedId, updateStatus, refreshList],
);
useSSE(sseUrl, handleSSEEvent);
const handleSelect = (id: string) => {
setSseUrl(null);
setStages(DEFAULT_STAGES);
setSelectedId(id);
};
const handleCreateNew = async (body: {
main_prompt: string;
liked_shows: string;
disliked_shows: string;
themes: string;
}) => {
const id = await createNew(body);
setStages(DEFAULT_STAGES);
setSseUrl(`/api/recommendations/${id}/stream`);
};
const handleRerank = async () => {
if (!selectedId) return;
await rerank(selectedId);
setStages(DEFAULT_STAGES);
setSseUrl(`/api/recommendations/${selectedId}/stream`);
setSelectedRec((prev) => (prev ? { ...prev, status: 'pending' } : null));
};
const isRunning =
selectedRec?.status === 'running' || selectedRec?.status === 'pending' || !!sseUrl;
const feedbackMap = new Map(feedback.map((f) => [f.tv_show_name, f]));
return (
<div class="layout">
<Sidebar
list={list}
selectedId={selectedId}
onSelect={handleSelect}
onNewClick={() => setShowModal(true)}
/>
<main class="main-content">
{!selectedId && (
<div class="empty-state">
<h2>TV Show Recommender</h2>
<p>Click <strong>+ New Recommendation</strong> to get started.</p>
</div>
)}
{selectedId && isRunning && (
<div class="content-area">
<PipelineProgress stages={stages} />
</div>
)}
{selectedId && !isRunning && selectedRec?.status === 'done' && selectedRec.recommendations && (
<div class="content-area">
<h2 class="rec-title">{selectedRec.title}</h2>
<div class="cards-grid">
{selectedRec.recommendations.map((show) => (
<RecommendationCard
key={show.title}
show={show}
existingFeedback={feedbackMap.get(show.title)}
onFeedback={async (name, stars, comment) => {
await submitFeedback({ tv_show_name: name, stars, feedback: comment });
}}
/>
))}
</div>
<div class="rerank-section">
<button
class="btn-rerank"
onClick={handleRerank}
disabled={feedback.length === 0}
title={feedback.length === 0 ? 'Rate at least one show to enable re-ranking' : 'Re-rank based on your feedback'}
>
Re-rank with Feedback {feedback.length > 0 ? `(${feedback.length} rated)` : ''}
</button>
</div>
</div>
)}
{selectedId && !isRunning && selectedRec?.status === 'error' && (
<div class="content-area error-state">
<h2>Something went wrong</h2>
<p>The pipeline encountered an error. You can try again by clicking Re-rank.</p>
<button class="btn-primary" onClick={handleRerank}>
Try Again
</button>
</div>
)}
</main>
{showModal && (
<NewRecommendationModal
onClose={() => setShowModal(false)}
onSubmit={handleCreateNew}
/>
)}
</div>
);
}

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export type CuratorCategory = 'Definitely Like' | 'Might Like' | 'Questionable' | 'Will Not Like';
export interface CuratorOutput {
title: string;
explanation: string;
category: CuratorCategory;
}
export type RecommendationStatus = 'pending' | 'running' | 'done' | 'error';
export interface Recommendation {
id: string;
title: string;
main_prompt: string;
liked_shows: string;
disliked_shows: string;
themes: string;
recommendations: CuratorOutput[] | null;
status: RecommendationStatus;
created_at: string;
}
export interface RecommendationSummary {
id: string;
title: string;
status: RecommendationStatus;
created_at: string;
}
export interface FeedbackEntry {
id: string;
tv_show_name: string;
stars: number;
feedback: string;
created_at: string;
}
export type PipelineStage = 'interpreter' | 'retrieval' | 'ranking' | 'curator' | 'complete';
export type SSEStatus = 'start' | 'done' | 'error';
export interface SSEEvent {
stage: PipelineStage;
status: SSEStatus;
data?: unknown;
}
export type StageStatus = 'pending' | 'running' | 'done' | 'error';
export type StageMap = Record<Exclude<PipelineStage, 'complete'>, StageStatus>;

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@@ -0,0 +1,33 @@
{
"compilerOptions": {
"tsBuildInfoFile": "./node_modules/.tmp/tsconfig.app.tsbuildinfo",
"target": "ES2023",
"useDefineForClassFields": true,
"module": "ESNext",
"lib": ["ES2023", "DOM", "DOM.Iterable"],
"types": ["vite/client"],
"skipLibCheck": true,
"paths": {
"react": ["./node_modules/preact/compat/"],
"react-dom": ["./node_modules/preact/compat/"]
},
/* Bundler mode */
"moduleResolution": "bundler",
"allowImportingTsExtensions": true,
"verbatimModuleSyntax": true,
"moduleDetection": "force",
"noEmit": true,
"jsx": "react-jsx",
"jsxImportSource": "preact",
/* Linting */
"strict": true,
"noUnusedLocals": true,
"noUnusedParameters": true,
"erasableSyntaxOnly": true,
"noFallthroughCasesInSwitch": true,
"noUncheckedSideEffectImports": true
},
"include": ["src"]
}

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@@ -0,0 +1,7 @@
{
"files": [],
"references": [
{ "path": "./tsconfig.app.json" },
{ "path": "./tsconfig.node.json" }
]
}

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@@ -0,0 +1,26 @@
{
"compilerOptions": {
"tsBuildInfoFile": "./node_modules/.tmp/tsconfig.node.tsbuildinfo",
"target": "ES2023",
"lib": ["ES2023"],
"module": "ESNext",
"types": ["node"],
"skipLibCheck": true,
/* Bundler mode */
"moduleResolution": "bundler",
"allowImportingTsExtensions": true,
"verbatimModuleSyntax": true,
"moduleDetection": "force",
"noEmit": true,
/* Linting */
"strict": true,
"noUnusedLocals": true,
"noUnusedParameters": true,
"erasableSyntaxOnly": true,
"noFallthroughCasesInSwitch": true,
"noUncheckedSideEffectImports": true
},
"include": ["vite.config.ts"]
}

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@@ -0,0 +1,16 @@
import { defineConfig } from 'vite'
import preact from '@preact/preset-vite'
// https://vite.dev/config/
export default defineConfig({
plugins: [preact()],
server: {
proxy: {
'/api': {
target: 'http://localhost:3000',
rewrite: (path) => path.replace(/^\/api/, ''),
changeOrigin: true,
},
},
},
})