Fixed Major Issues

Dockerfile

@@ -1,20 +1,13 @@
-# Use a modern, lightweight Python version
 FROM python:3.9-slim
 
-# Set the working directory in the container
 WORKDIR /app
 
-# Copy the requirements file first to leverage Docker cache
 COPY requirements.txt .
 
-# Install Python dependencies
 RUN pip install --no-cache-dir -r requirements.txt
 
-# Copy the rest of the application's code into the container
 COPY . .
 
-# Expose the port that Hugging Face expects
 EXPOSE 7860
 
-# Run the app using a production-ready server (Gunicorn)
 CMD ["gunicorn", "--bind", "0.0.0.0:7860", "app:app"]

Required Data/Resume.pdf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:285138a988bc48546637d36a93d903fd10ef68e62b0d38e7283173b03d8635cf
+size 52610

app.py

@@ -1,8 +1,13 @@
+# --- Set Cache Folders for Hugging Face Environment ---
+# THIS IS THE CRUCIAL FIX for the PermissionError. It must be at the top.
+import os
+os.environ["TRANSFORMERS_CACHE"] = "/tmp/transformers"
+os.environ["HF_HOME"] = "/tmp/huggingface"
+
 import json
 import re
 import logging
 import math
-import os
 import docx
 import fitz  # PyMuPDF
 from dotenv import load_dotenv
@@ -12,10 +17,6 @@ from sentence_transformers import SentenceTransformer, util
 from rapidfuzz import fuzz, process
 from urllib.parse import quote_plus
 
-# --- Set Cache Folders for Hugging Face Environment ---
-os.environ["TRANSFORMERS_CACHE"] = "/tmp/transformers"
-os.environ["HF_HOME"] = "/tmp/huggingface"
-
 # --- Load environment variables and configure Gemini API ---
 load_dotenv()
 GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
@@ -167,7 +168,6 @@ def get_recommendations(answers, courses):
     raw_recs = [course for _, course in top_courses]
     if not raw_recs: return "🤔 I couldn’t find a strong match. Would you like to try again?", []
 
-    # --- THIS IS THE MODIFIED PART ---
     response_html = "<div class='recommendation-container'><h4>🚀 Here are my top recommendations for you:</h4>"
     for i, (_, course_data) in enumerate(top_courses):
         course_name = course_data.get('course')
@@ -186,8 +186,7 @@ def get_recommendations(answers, courses):
         response_html += "</div>"
         
         response_html += "</div>"
-    # ------------------------------------
-
+    
     response_html += f"<div class='recommendation-card clickable-card compare-card' data-action='compare' data-value='compare'><p><b>⚖️ Compare Courses</b></p></div></div>"
     return response_html, raw_recs
 
@@ -220,7 +219,9 @@ def analyze_resume_and_suggest_jobs(resume_text):
     2. "overall_score": An integer score out of 100 for the resume's quality.
     3. "summary": A brief, encouraging 1-2 sentence summary of the resume.
     4. "job_titles": A list of 3-5 specific job titles the candidate is well-suited for based on their skills and experience.
+
     Do not add any text before or after the JSON object.
+
     Resume Text to analyze:
     ---
     {resume_text}