Update app.py

app.py

@@ -8,14 +8,14 @@ from sklearn.metrics.pairwise import cosine_similarity
 import time
 import os
 
-# Set cache directory explicitly (optional, as Dockerfile ENV should handle this)
+# Set cache directory
 os.environ["HF_HOME"] = "/app/cache"
 os.environ["TRANSFORMERS_CACHE"] = "/app/cache"
 
 app = FastAPI()
 
-# Load datasets (updated path to match Dockerfile)
-DATA_DIR = "/app/data/"  # Changed from "data/" to "/app/data/"
+# Load datasets
+DATA_DIR = "/app/data/"
 job_df = pd.read_csv(os.path.join(DATA_DIR, "Updated_Job_Posting_Dataset.csv"), encoding="latin1")
 course_df = pd.read_csv(os.path.join(DATA_DIR, "coursera_course_dataset_v2_no_null.csv"))
 coding_df = pd.read_csv(os.path.join(DATA_DIR, "Software Questions.csv"), encoding="latin1")
@@ -88,19 +88,27 @@ def recommend_jobs(skills):
 def read_root():
     return {"message": "Skill Assessment API"}
 
+# New endpoint to provide challenges
+@app.get("/challenges")
+def get_user_challenges(skills: List[str]):
+    if not skills:
+        raise HTTPException(status_code=400, detail="Skills list cannot be empty")
+    challenges = get_coding_challenges(skills)
+    # Return only questions (exclude solutions for the user)
+    return {
+        "challenges": {skill: [challenge["question"] for challenge in challenge_list] for skill, challenge_list in challenges.items()}
+    }
+
 @app.post("/assess")
 def assess_skills(user_input: UserInput):
-    # Extract user data from request
     user_name = user_input.name
     user_skills = user_input.skills
 
     if not user_skills:
         raise HTTPException(status_code=400, detail="Skills list cannot be empty")
 
-    # Fetch coding challenges based on provided skills
     challenges = get_coding_challenges(user_skills)
     
-    # Evaluate skills
     user_scores = {}
     for skill, challenge_list in challenges.items():
         if not challenge_list:
@@ -111,7 +119,6 @@ def assess_skills(user_input: UserInput):
         num_questions = len(challenge_list)
         
         if user_input.answers and skill in user_input.answers:
-            # Use provided answers
             for challenge in challenge_list:
                 question = challenge["question"]
                 if question in user_input.answers[skill]:
@@ -121,18 +128,15 @@ def assess_skills(user_input: UserInput):
                     score = evaluate_coding_with_time(user_code, correct_code, start_time)
                     total_score += score
                 else:
-                    total_score += 0  # No answer provided for this question
+                    total_score += 0
         else:
-            # No answers provided; assign default score (50% per question)
             total_score = 50 * num_questions
         
         user_scores[skill] = round(total_score / num_questions, 2)
 
-    # Proficiency levels
     proficiency_levels = {skill: get_proficiency_level(score) for skill, score in user_scores.items()}
     weak_skills = [skill for skill, level in proficiency_levels.items() if level in ["Beginner", "Intermediate"]]
 
-    # Recommendations
     courses = recommend_courses(weak_skills)
     jobs = recommend_jobs(user_skills)