Open HR

yanfr-lab-open-hr/.env.example

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+HRFLOW_API_KEY=your_api_key_here
+HRFLOW_USER_EMAIL=your_email_here
+HRFLOW_SOURCE_KEY=your_source_key_here
+HRFLOW_BOARD_KEY=your_board_key_here

yanfr-lab-open-hr/README.md

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+# Open HR avec HrFlow.ai
+
+> Intelligent candidate sourcing with auto-generated questionnaires and HrFlow.ai-powered scoring.
+
+## What it does
+
+Open HR is an AI sourcing agent built for recruiters. Given a job title and requirements, it:
+
+1. **Auto-generates a weighted questionnaire** from the job description (skills, experience, education, stability)
+2. **Indexes the job** via HrFlow.ai Job Indexing API
+3. **Scores all candidates** in the source using HrFlow.ai Scoring API with a custom algorithm key
+4. **Combines AI scores with questionnaire weights** to produce precise decimal rankings
+5. **Allows refinement** via natural language feedback loop
+
+## HrFlow.ai APIs used
+
+- `POST /v1/job/indexing` — Index job description to enable scoring
+- `GET /v1/profiles/scoring` — Score all profiles against the job using algorithm key
+- `GET /v1/profiles/searching` — Fallback profile search
+- `POST /v1/profile/indexing` — Index candidate profiles
+
+## How to run
+
+### Prerequisites
+
+- Python 3.11+
+
+### Setup
+
+```bash
+# Install dependencies
+pip install -r requirements.txt
+
+# Copy environment variables
+cp .env.example .env
+# Fill in your HrFlow API keys in .env
+
+# Start the app
+uvicorn web_app_fr_v2:app --host 0.0.0.0 --port 8002
+```
+
+### Environment variables
+
+| Variable | Required | Description |
+|----------|----------|-------------|
+| `HRFLOW_API_KEY` | Yes | HrFlow.ai API secret key |
+| `HRFLOW_USER_EMAIL` | Yes | HrFlow.ai account email |
+| `HRFLOW_SOURCE_KEY` | Yes | HrFlow.ai source key |
+| `HRFLOW_BOARD_KEY` | Yes | HrFlow.ai board key |
+
+## Screenshots
+
+![Preview](./assets/preview.png)
+
+## Team
+
+- **Yan** — Full-stack development & HrFlow.ai integration
+- **Leo** — HrFlow.ai API integration & scoring algorithm
+- **Aike** — Development & HrFlow.ai integration

yanfr-lab-open-hr/app.json

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+{
+  "$schema": "../../schemas/app.schema.json",
+  "name": "Open HR avec HrFlow.ai",
+  "description": "AI agent that auto-generates a weighted questionnaire from any job description, scores and ranks candidates using HrFlow.ai Scoring API, and refines results through a natural language feedback loop.",
+  "credentials": {
+    "source_keys": ["c1039b004a836e42427b9c89309ad99cf9b6a73c"],
+    "board_keys": ["c99d70c3a062c2f99ca78fce23b89fb4f53119ef"],
+    "algorithm_key": "b1ebac4c62fa96e06206f4433b95ae69674891ff"
+  },
+  "settings": {
+    "team_name": "yanfr-lab",
+    "theme_color": "#83D9DC",
+    "custom_filters": [],
+    "filters": []
+  }
+}

yanfr-lab-open-hr/database.py

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+import sqlite3
+import json
+from datetime import datetime
+
+DB_NAME = "sourcing.db"
+
+def init_db():
+    conn = sqlite3.connect(DB_NAME)
+    cursor = conn.cursor()
+    cursor.execute('''
+        CREATE TABLE IF NOT EXISTS searches (
+            id INTEGER PRIMARY KEY AUTOINCREMENT,
+            query TEXT,
+            created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
+        )
+    ''')
+    cursor.execute('''
+        CREATE TABLE IF NOT EXISTS candidates (
+            id INTEGER PRIMARY KEY AUTOINCREMENT,
+            search_id INTEGER,
+            name TEXT,
+            headline TEXT,
+            location TEXT,
+            profile_url TEXT,
+            source_platform TEXT,
+            hrflow_profile_key TEXT,
+            score REAL,
+            rank INTEGER,
+            raw_json TEXT,
+            created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
+            FOREIGN KEY(search_id) REFERENCES searches(id)
+        )
+    ''')
+    conn.commit()
+    conn.close()
+
+def save_search(query: str) -> int:
+    conn = sqlite3.connect(DB_NAME)
+    cursor = conn.cursor()
+    cursor.execute("INSERT INTO searches (query) VALUES (?)", (query,))
+    search_id = cursor.lastrowid
+    conn.commit()
+    conn.close()
+    return search_id
+
+def save_candidate(search_id: int, candidate: dict):
+    conn = sqlite3.connect(DB_NAME)
+    cursor = conn.cursor()
+    cursor.execute('''
+        INSERT INTO candidates (search_id, name, headline, location, profile_url, 
+                               source_platform, hrflow_profile_key, score, rank, raw_json)
+        VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+    ''', (
+        search_id, candidate['name'], candidate.get('headline'), candidate.get('location'),
+        candidate['profile_url'], candidate.get('source_platform', 'github'),
+        candidate.get('hrflow_profile_key'), candidate.get('score', 0),
+        candidate.get('rank'), json.dumps(candidate)
+    ))
+    conn.commit()
+    conn.close()
+
+def get_recent_searches(limit=20):
+    conn = sqlite3.connect(DB_NAME)
+    conn.row_factory = sqlite3.Row
+    cursor = conn.cursor()
+    cursor.execute('''
+        SELECT s.*, (SELECT COUNT(*) FROM candidates WHERE search_id = s.id) as candidate_count 
+        FROM searches s ORDER BY created_at DESC LIMIT ?
+    ''', (limit,))
+    rows = [dict(row) for row in cursor.fetchall()]
+    conn.close()
+    return rows
+
+init_db()