Spaces:
Sleeping
Sleeping
File size: 4,086 Bytes
1f8582e |
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 89 90 91 |
from flask import Flask, request, jsonify
import os
import requests
from student_recommendation_system import StudentRecommendationSystem, setup_json_directory
app = Flask(__name__)
json_dir = setup_json_directory()
recommendation_system = StudentRecommendationSystem(json_dir)
FORWARD_URL = "http://54.242.19.19:3000/api/report/send-report/"
GRADES_API_BASE_URL = "http://54.242.19.19:3000/api/grades/report/"
@app.route('/recommend/<int:student_id>', methods=['POST'])
def recommend(student_id):
try:
grades_api_url = f"{GRADES_API_BASE_URL}{student_id}"
try:
grades_response = requests.get(grades_api_url, timeout=10)
grades_response.raise_for_status()
grades_data_raw = grades_response.json()
except requests.exceptions.RequestException as e:
return jsonify({"error": f"Failed to fetch grades data: {str(e)}"}), 500
except ValueError as e:
return jsonify({"error": "Invalid JSON response from grades API"}), 500
if "grades_data" not in grades_data_raw:
return jsonify({"error": "No 'grades_data' found in external API response"}), 400
email = grades_data_raw.get("email")
if not email:
return jsonify({"error": "No 'email' found in external API response"}), 400
try:
grades_data = {subject: float(score) for subject, score in grades_data_raw["grades_data"].items()}
except (ValueError, TypeError) as e:
return jsonify({"error": f"Invalid grades data format: {str(e)}"}), 400
results = recommendation_system.process_student_data(grades_data=grades_data)
strengths = results["strengths"]
top_recs = results["top_recommendations"]
clean_recs = [
{k: v for k, v in rec.items() if k not in ("raw_score", "refined_score")}
for rec in top_recs
]
response_payload = {
"email": email,
"studentName": "Ahmed Hassan",
"academic_strengths": strengths,
"top_recommendations": clean_recs
}
model_path = os.path.join(json_dir, "ai_model.pkl")
recommendation_system.save_ai_model(model_path)
try:
requests.post(FORWARD_URL, json=response_payload, timeout=10)
except requests.exceptions.RequestException as e:
print(f"Warning: Failed to forward data to report API: {str(e)}")
return jsonify(response_payload), 200
except Exception as e:
return jsonify({"error": f"Internal server error: {str(e)}"}), 500
@app.route('/recommend', methods=['POST'])
def recommend_post():
data = request.get_json(silent=True)
if not data or "grades_data" not in data:
return jsonify({"error": "No 'grades_data' provided in JSON payload."}), 400
try:
grades_data = {subject: float(score) for subject, score in data["grades_data"].items()}
results = recommendation_system.process_student_data(grades_data=grades_data)
strengths = results["strengths"]
top_recs = results["top_recommendations"]
clean_recs = [
{k: v for k, v in rec.items() if k not in ("raw_score", "refined_score")}
for rec in top_recs
]
response_payload = {
"academic_strengths": strengths,
"top_recommendations": clean_recs
}
model_path = os.path.join(json_dir, "ai_model.pkl")
recommendation_system.save_ai_model(model_path)
try:
requests.post(FORWARD_URL, json=response_payload, timeout=10)
except requests.exceptions.RequestException as e:
print(f"Warning: Failed to forward data to report API: {str(e)}")
return jsonify(response_payload), 200
except Exception as e:
return jsonify({"error": str(e)}), 500
if __name__ == '__main__':
port = int(os.environ.get("PORT", 7860))
app.run(host="0.0.0.0", port=port, debug=False) |