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b2efd24 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 | # ⚡ AI Recruitment Agent
A production-grade hybrid candidate matching pipeline using **Groq LLM**, **Pinecone vector DB**, and a **Gradio 4.16.0** UI.
## Architecture
```
CSV Input → Stage 1: Normalize (Groq)
→ Stage 2: Embed + Match (Pinecone + SentenceTransformers) → Top 20
→ Stage 3: Deterministic Rerank (Groq) → Top 10
→ Stage 4: LLM Deep Review (Groq) → Top 5
→ Stage 5: Final Synthesis (Groq) → Shortlist
```
## Setup
### 1. Install dependencies
```bash
pip install -r requirements.txt
```
### 2. Configure environment
```bash
cp .env.example .env
# Edit .env and fill in your API keys
```
### 3. Create Pinecone index
In your Pinecone console:
- Create an index named `recruitment-index` (or whatever you set in `PINECONE_INDEX`)
- Dimension: **1024** for `BAAI/bge-m3`, **768** for `bge-large-en`, **384** for `all-MiniLM-L6-v2`
- Metric: **cosine**
### 4. Run the Gradio UI
```bash
python gradio_app.py
```
Open http://localhost:7860 in your browser.
### 5. (Optional) Run the FastAPI backend
```bash
uvicorn main:app --host 0.0.0.0 --port 8000 --reload
```
API docs at http://localhost:8000/docs
## CSV Format
Your CSV should have these columns (exact names or common variants):
| Column | Variants |
|--------|----------|
| `name` | `full_name`, `candidate_name` |
| `email` | `email_address` |
| `skills` | `parsed_skills`, `technical_skills` |
| `experience` | `parsed_work_experience`, `years_of_experience` |
| `education` | `parsed_metadata_education` |
| `resume_text` | `parsed_summary`, `summary` |
## Key Environment Variables
| Variable | Description | Default |
|----------|-------------|---------|
| `GROQ_API_KEYS` | Comma-separated keys for rotation | — |
| `GROQ_MODEL` | Model name | `llama3-70b-8192` |
| `PINECONE_API_KEY` | Pinecone API key | — |
| `PINECONE_INDEX` | Index name | `recruitment-index` |
| `EMBEDDING_MODEL` | SentenceTransformer model | `BAAI/bge-m3` |
| `STAGE2_TOP_K` | Candidates retrieved by embeddings | `20` |
| `GRADIO_PORT` | UI port | `7860` |
| `GRADIO_SHARE` | Enable public share link | `False` |
## Pipeline Stages
| Stage | Method | Input | Output |
|-------|--------|-------|--------|
| 1. Normalize | Groq LLM | All candidates | Structured features |
| 2. Embed & Match | Pinecone + BAAI/bge-m3 | All candidates | Top 20 by similarity |
| 3. Rerank | Groq LLM (deterministic scoring) | Top 20 | Top 10 with scores |
| 4. Deep Review | Groq LLM | Top 5 | Verdicts + signals |
| 5. Final Synthesis | Groq LLM | Top 5 reviews | Final ranked shortlist |
|