Job Application Assistant

A Job assistant built with CopilotKit (Next.js) on the frontend and DeepAgents (by LangChain) on the backend. Users upload their resume (PDF), the system extracts skills and context and DeepAgents orchestrate sub-agents & tools to search the web (via Tavily) for relevant job postings. Results stream back to the UI in real time and are rendered alongside the chat.

DeepAgents provides clean orchestration with sub-agents and tools, while CopilotKit (AG‑UI) handles real-time streaming and stateful UI updates. Refer to the official integration docs.

What This Demo Shows:

Resume upload + PDF parsing
Skill extraction from real resumes
DeepAgents orchestration with sub-agents and tools
Internet search via Tavily
Tool calls streamed to the UI using AG-UI

Here is the high-level flow:

[User uploads resume & submits job query]
        ↓
Next.js UI (ResumeUpload + CopilotChat)
        ↓
useCopilotReadable syncs resume + preferences
        ↓
POST /api/copilotkit (AG-UI protocol)
        ↓
FastAPI + DeepAgents (/copilotkit endpoint)
        ↓
Resume context + skills injected into agent
        ↓
DeepAgents orchestration
   ├─ internet_search (Tavily)
   ├─ job filtering & normalization
   └─ update_jobs_list (tool call)
        ↓
AG-UI streaming (SSE)
        ↓
CopilotKit runtime receives tool result
        ↓
Frontend captures tool output
        ↓
Jobs rendered in table + chat stay clean

Project Structure

.
├── src/                               ← Next.js frontend
│   ├── app/
│   │   ├── page.tsx
│   │   ├── layout.tsx                 ← CopilotKit provider
│   │   └── api/
│   │       ├── upload-resume/route.ts ← upload endpoint
│   │       └── copilotkit/route.ts    ← CopilotKit AG-UI runtime
│   ├── components/
│   │   ├── ChatPanel.tsx              ← Chat + tool capture
│   │   ├── ResumeUpload.tsx           ← PDF upload UI
│   │   ├── JobsResults.tsx            ← Jobs table renderer
│   │   └── LivePreviewPanel.tsx
│   └── lib/
│       ├── jobsParser.ts              ← Normalization helpers
│       └── types.ts                   ← Shared frontend types
│
├── agent/                             ← DeepAgents backend
│   ├── main.py                        ← FastAPI + AG-UI endpoint
│   ├── agent.py                       ← DeepAgents graph & tools
│   ├── pyproject.toml                 ← Python deps (uv)
│   └── uv.lock
│
├── package.json
├── next.config.ts
└── README.md

Environment Variables

You will need an OpenAI API Key and Tavily API Key.

Create the agent/.env and set your keys:

dotenv

OPENAI_API_KEY=sk-proj-...
TAVILY_API_KEY=tvly-dev-...
OPENAI_MODEL=gpt-4-turbo

Setup & Installation

1. Installation

Frontend (Next.js):

bash

npm install
# or
yarn install

Backend (Python, uv)

bash

cd agent
uv add
uv sync

The backend uses uv for dependency management. Install it if it's not already in your system: pip install uv.

2. Running locally

Start the backend:

bash

cd agent
uv run python main.py

Backend runs on http://localhost:8123.

Start the frontend (in a new terminal):

bash

npm run dev
# or
yarn dev

Navigate to http://localhost:3000 in your browser.

License

This project is licensed under the MIT License. See the LICENSE file for details.