Add docker-compose setup

.env.example

@@ -0,0 +1,21 @@
+POSTGRES_USER=appuser
+POSTGRES_PASSWORD=secret
+POSTGRES_DB=appdb
+POSTGRES_HOST=postgres
+POSTGRES_PORT=5432
+
+DATABASE_URL=postgresql+asyncpg://appuser:secret@postgres:5432/appdb
+SYNC_DATABASE_URL=postgresql://appuser:secret@postgres:5432/appdb
+
+REDIS_URL=redis://redis:6379/0
+
+GAPGPT_API_KEY=
+OPENAI_API_KEY=
+
+TELEGRAM_BOT_TOKEN=
+
+RESUME_PATH=/data/resume.txt
+
+BACKEND_PORT=8000
+FRONTEND_PORT=3000
+TELBOT_PORT=8080

.gitignore

@@ -1,2 +1,3 @@
 .env
-extracted_for_ai.text
+__pycache__/
+

docker-compose.yml

@@ -0,0 +1,62 @@
+version: '3.8'
+services:
+  postgres:
+    image: postgres:15-alpine
+    env_file: .env
+    volumes:
+      - db_data:/var/lib/postgresql/data
+
+  pgbouncer:
+    image: edoburu/pgbouncer:latest
+    volumes:
+      - ./services/pgbouncer/pgbouncer.ini:/etc/pgbouncer/pgbouncer.ini
+      - ./services/pgbouncer/userlist.txt:/etc/pgbouncer/userlist.txt
+    env_file: .env
+    depends_on:
+      - postgres
+
+  redis:
+    image: redis:7-alpine
+    command: ["redis-server","--maxmemory","256mb","--maxmemory-policy","allkeys-lru"]
+
+  backend:
+    build: ./services/backend
+    env_file: .env
+    ports:
+      - "${BACKEND_PORT}:8000"
+    depends_on:
+      - pgbouncer
+      - redis
+
+  rq-worker:
+    build: ./services/backend
+    env_file: .env
+    entrypoint: ["rq","worker","--url","${REDIS_URL}","default"]
+    depends_on:
+      - backend
+      - redis
+
+  frontend:
+    build: ./services/frontend
+    env_file: .env
+    ports:
+      - "${FRONTEND_PORT}:3000"
+    depends_on:
+      - backend
+
+  telbot:
+    build: ./services/telbot
+    env_file: .env
+    depends_on:
+      - postgres
+    command: ["python","bot.py"]
+
+  resume-pipeline:
+    build: ./services/resume_pipeline
+    env_file: .env
+    volumes:
+      - ./data:/data
+    command: ["python","run_pipeline.py"]
+
+volumes:
+  db_data:

requirements.txt

@@ -11,3 +11,6 @@ langchain_openai
 sqlalchemy
 tenacity
 matplotlib
+psycopg2-binary
+requests
+beautifulsoup4

services/backend/Dockerfile

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+FROM python:3.11-slim AS builder
+WORKDIR /app
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+FROM python:3.11-slim
+WORKDIR /app
+COPY --from=builder /usr/local/lib/python3.11/site-packages /usr/local/lib/python3.11/site-packages
+COPY . .
+CMD ["uvicorn","main:app","--host","0.0.0.0","--port","8000"]

services/backend/db.py

@@ -0,0 +1,11 @@
+import os
+from sqlalchemy.ext.asyncio import create_async_engine, AsyncSession
+from sqlalchemy.orm import sessionmaker
+
+DATABASE_URL = os.getenv("DATABASE_URL")
+engine = create_async_engine(DATABASE_URL, echo=False)
+AsyncSessionLocal = sessionmaker(engine, class_=AsyncSession, expire_on_commit=False)
+
+async def get_db():
+    async with AsyncSessionLocal() as session:
+        yield session

services/backend/main.py

@@ -0,0 +1,11 @@
+from fastapi import FastAPI, Depends
+from sqlalchemy import select
+from .db import get_db
+from .models import Item
+
+app = FastAPI()
+
+@app.get("/items")
+async def list_items(db=Depends(get_db)):
+    result = await db.execute(select(Item))
+    return result.scalars().all()

services/backend/models.py

@@ -0,0 +1,11 @@
+from sqlalchemy.orm import declarative_base
+from sqlalchemy import Column, Integer, String, Text
+
+Base = declarative_base()
+
+class Item(Base):
+    __tablename__ = "items"
+    id = Column(Integer, primary_key=True)
+    name = Column(String(100))
+    description = Column(Text)
+    status = Column(String(20))

services/backend/requirements.txt

@@ -0,0 +1,7 @@
+fastapi
+uvicorn[standard]
+asyncpg
+sqlalchemy
+psycopg2-binary
+redis
+rq

services/backend/rq_worker.py

@@ -0,0 +1,11 @@
+import os
+from rq import Worker, Queue, Connection
+import redis
+
+redis_url = os.getenv("REDIS_URL")
+conn = redis.from_url(redis_url)
+
+if __name__ == "__main__":
+    with Connection(conn):
+        worker = Worker(["default"])
+        worker.work()

services/frontend/Dockerfile

@@ -0,0 +1,9 @@
+FROM node:18-alpine AS builder
+WORKDIR /app
+COPY package.json yarn.lock ./
+RUN yarn install
+COPY . .
+RUN yarn build
+
+FROM nginx:alpine
+COPY --from=builder /app/build /usr/share/nginx/html

services/frontend/package.json

@@ -0,0 +1,11 @@
+{
+  "name": "frontend",
+  "version": "1.0.0",
+  "dependencies": {
+    "react": "^18.0.0",
+    "react-dom": "^18.0.0"
+  },
+  "scripts": {
+    "build": "echo building frontend"
+  }
+}

services/frontend/src/components/ItemsTable.jsx

@@ -0,0 +1,3 @@
+export default function ItemsTable() {
+  return null;
+}

services/frontend/src/index.jsx

@@ -0,0 +1 @@
+console.log('frontend placeholder');

services/frontend/yarn.lock

@@ -0,0 +1 @@
+# lockfile

services/pgbouncer/pgbouncer.ini

@@ -0,0 +1,6 @@
+[databases]
+appdb = host=postgres port=5432 dbname=appdb user=appuser password=secret
+
+[pgbouncer]
+listen_port = 6432
+listen_addr = 0.0.0.0

services/pgbouncer/userlist.txt

@@ -0,0 +1 @@
+"appuser" "secret"

services/postgres/init.sql

@@ -0,0 +1,13 @@
+-- optional schema
+CREATE TABLE IF NOT EXISTS jobs (
+    id SERIAL PRIMARY KEY,
+    url TEXT,
+    page_html TEXT,
+    requirements TEXT
+);
+CREATE TABLE IF NOT EXISTS items (
+    id SERIAL PRIMARY KEY,
+    name TEXT,
+    description TEXT,
+    status TEXT
+);

services/resume_pipeline/Dockerfile

@@ -0,0 +1,6 @@
+FROM python:3.11-slim
+WORKDIR /app
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+COPY . .
+CMD ["python","run_pipeline.py"]

services/resume_pipeline/database.py

@@ -0,0 +1,35 @@
+import os
+from contextlib import contextmanager
+import psycopg2
+from psycopg2.pool import SimpleConnectionPool
+
+DATABASE_URL = os.getenv("DATABASE_URL")
+
+if not DATABASE_URL:
+    raise RuntimeError("DATABASE_URL environment variable is required")
+
+pool = SimpleConnectionPool(minconn=1, maxconn=5, dsn=DATABASE_URL)
+
+@contextmanager
+def get_conn():
+    conn = pool.getconn()
+    try:
+        yield conn
+    finally:
+        pool.putconn(conn)
+
+def fetch_job_urls(limit=10):
+    """Return a list of (id, url) tuples from the jobs table."""
+    query = "SELECT id, url FROM jobs WHERE url IS NOT NULL LIMIT %s"
+    with get_conn() as conn:
+        with conn.cursor() as cur:
+            cur.execute(query, (limit,))
+            return cur.fetchall()
+
+def store_job_page(job_id, html, requirements_text):
+    """Store downloaded HTML and extracted requirements for a job."""
+    query = "UPDATE jobs SET page_html=%s, requirements=%s WHERE id=%s"
+    with get_conn() as conn:
+        with conn.cursor() as cur:
+            cur.execute(query, (html, requirements_text, job_id))
+            conn.commit()

services/resume_pipeline/requirements.txt

@@ -0,0 +1,4 @@
+psycopg2-binary
+requests
+beautifulsoup4
+openai

services/resume_pipeline/resume_generator.py

@@ -0,0 +1,17 @@
+import os
+import openai
+
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+PROMPT = (
+    "You are a helpful assistant that rewrites a resume to match a job description." 
+    "Return the improved resume in plain text."
+)
+
+def generate_resume(resume_text: str, job_requirements: str) -> str:
+    messages = [
+        {"role": "system", "content": PROMPT},
+        {"role": "user", "content": f"Resume:\n{resume_text}\n\nJob requirements:\n{job_requirements}"},
+    ]
+    resp = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=messages)
+    return resp.choices[0].message.content.strip()

services/resume_pipeline/resume_parser.py

@@ -0,0 +1,8 @@
+from pathlib import Path
+
+def load_resume(path: str) -> str:
+    """Load resume text from a file."""
+    p = Path(path)
+    if not p.exists():
+        raise FileNotFoundError(path)
+    return p.read_text()

services/resume_pipeline/run_pipeline.py

@@ -0,0 +1,25 @@
+import os
+from database import fetch_job_urls, store_job_page
+from scraper import download_job_page, parse_requirements
+from resume_parser import load_resume
+from resume_generator import generate_resume
+
+RESUME_PATH = os.getenv("RESUME_PATH", "resume.txt")
+
+
+def main():
+    resume_text = load_resume(RESUME_PATH)
+    jobs = fetch_job_urls(limit=1)
+    for job_id, url in jobs:
+        html = download_job_page(url)
+        reqs = parse_requirements(html)
+        new_resume = generate_resume(resume_text, reqs)
+        store_job_page(job_id, html, reqs)
+        out_file = f"resume_{job_id}.txt"
+        with open(out_file, "w") as f:
+            f.write(new_resume)
+        print(f"Generated resume for job {job_id} -> {out_file}")
+
+
+if __name__ == "__main__":
+    main()

services/resume_pipeline/scraper.py

@@ -0,0 +1,26 @@
+import requests
+from bs4 import BeautifulSoup
+from typing import Tuple
+
+HEADERS = {"User-Agent": "Mozilla/5.0"}
+
+def download_job_page(url: str) -> str:
+    resp = requests.get(url, headers=HEADERS, timeout=10)
+    resp.raise_for_status()
+    return resp.text
+
+def parse_requirements(html: str) -> str:
+    soup = BeautifulSoup(html, "html.parser")
+    # Simple heuristic: extract bullet lists under sections containing 'requirement'
+    sections = soup.find_all(text=lambda t: t and 'require' in t.lower())
+    if not sections:
+        return ""
+    # Gather sibling lists or paragraphs
+    requirements = []
+    for s in sections:
+        parent = s.parent
+        ul = parent.find_next("ul")
+        if ul:
+            items = [li.get_text(" ", strip=True) for li in ul.find_all("li")]
+            requirements.extend(items)
+    return "\n".join(requirements)

services/telbot/Dockerfile

@@ -0,0 +1,6 @@
+FROM python:3.11-slim
+WORKDIR /app
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+COPY . .
+CMD ["python","bot.py"]

services/telbot/requirements.txt

@@ -0,0 +1,16 @@
+python-telegram-bot==13.7
+pandas
+numpy
+plotly
+python-dotenv
+openai
+langchain
+langchain_community
+langchain_experimental
+langchain_openai
+sqlalchemy
+tenacity
+matplotlib
+psycopg2-binary
+requests
+beautifulsoup4