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Laxmi Khilnani cda50356b4

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Details

feat: Complete Smart Resume Formatter with R2 and Gemini AI integration

- Integrated Cloudflare R2 for template storage and converted file management
- Added Google Gemini AI for resume parsing and HTML generation
- Created backend API endpoints for templates, conversion, and history
- Refactored frontend to use real API instead of mock data
- Fixed Docker networking issues (IPv6/IPv4) for R2 connectivity
- Added resumeService.ts for frontend API integration
- Updated Vite configuration for proper asset serving in Docker
- Successfully tested with 13 templates from R2 bucket

2025-10-14 21:43:41 +05:30

5.1 KiB

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🎉 R2 Connection SUCCESS!

The Problem:

The Docker container couldn't connect to Cloudflare R2, showing the error:

Could not connect to the endpoint URL: "https://cba4afd7666247724ece1f34e1aace6c.r2.cloudflarestorage.com/e-teams..."
Error: Network unreachable

The Root Cause:

IPv6/IPv4 Networking Issue in Docker

DNS was returning both IPv4 (172.64.66.1) and IPv6 (2606:4700:2ff9::1) addresses
boto3/botocore was trying to connect via IPv6 first
Docker container's IPv6 networking wasn't properly configured
This caused "Network unreachable" errors

The Fix:

Added IPv4-only DNS resolution to the R2 service by monkey-patching Python's socket.getaddrinfo():

# Force IPv4 to avoid Docker IPv6 issues
original_getaddrinfo = socket.getaddrinfo

def getaddrinfo_ipv4_only(host, port, family=0, type=0, proto=0, flags=0):
    """Force IPv4 resolution only"""
    return original_getaddrinfo(host, port, socket.AF_INET, type, proto, flags)

socket.getaddrinfo = getaddrinfo_ipv4_only

✅ Verification:

1. List Templates - WORKING!

curl http://localhost:8080/resumeformatter/api/resumes/templates

Result: Found 13 templates in your R2 bucket:

[
    "Accenture",
    "Avanade",
    "Block",
    "Caterpillar",
    "Clark, Arthur",
    "Cox",
    "Cox_(1)",
    "Highmark",
    "Inzunza5",
    "JNJ",
    "JUY",
    "Kenvue",
    "Paramount_and_Viacom"
]

2. Get Template Content - WORKING!

curl "http://localhost:8080/resumeformatter/api/resumes/templates/Accenture"

Result: Successfully fetches HTML content!

3. R2 Bucket Structure:

Your R2 bucket (e-teams) contains:

✅ templates/ folder with 13 HTML templates
Ready for converted_resumes/ folder for outputs

What's Working Now:

✅ Backend API Endpoints:

GET /resumeformatter/api/resumes/templates
- Lists all available templates from R2
- Returns: ["Accenture", "Avanade", ...]
GET /resumeformatter/api/resumes/templates/{name}
- Gets specific template HTML content
- Returns: {"content": "<!DOCTYPE html>..."}
POST /resumeformatter/api/resumes/convert
- Upload resume + select template
- AI extracts text → generates formatted HTML → uploads to R2
GET /resumeformatter/api/resumes/history
- Lists converted resumes from R2

Test the Full Flow:

Test 1: List Templates

curl http://localhost:8080/resumeformatter/api/resumes/templates

Test 2: Get Template

curl "http://localhost:8080/resumeformatter/api/resumes/templates/Accenture"

Test 3: Convert Resume (requires a PDF/DOCX file)

curl -X POST http://localhost:8080/resumeformatter/api/resumes/convert \
  -F "file=@your-resume.pdf" \
  -F "template_name=Accenture"

Test 4: View Conversion History

curl http://localhost:8080/resumeformatter/api/resumes/history

Next Steps:

🎯 IMMEDIATE - Update Frontend:

The frontend still uses mock data. We need to connect it to the real API:

Replace fetchTemplatesFromR2() → API call to /api/resumes/templates
Replace fetchTemplateContentFromR2() → API call to /api/resumes/templates/{name}
Replace handleGenerate() → API call to /api/resumes/convert
Replace fetchConvertedResumesFromR2() → API call to /api/resumes/history
Remove mock template data from App.tsx

🔧 OPTIONAL - Improvements:

Add template preview in frontend
Add progress indicators during AI processing
Implement proper error handling
Add file size/type validation
Add download progress tracking

Current Architecture:

Frontend (React)
    ↓
Backend API (FastAPI)
    ↓
┌─────────────────┬─────────────────┐
↓                 ↓                  ↓
R2 Storage     Gemini AI      Database
(Templates)   (Text/Vision)  (Metadata)

Configuration Summary:

✅ Environment Variables (.env):

APP_NAME=resumeformatter
GEMINI_API_KEY=AIzaSyB4Y9qrGynW3UNflYcQC-HGlJxOe_ty6VI

R2_ENDPOINT=https://cba4afd7666247724ece1f34e1aace6c.r2.cloudflarestorage.com
R2_ACCESS_KEY_ID=8f7244b0e7f9c8297a606af0073d4a5a
R2_SECRET_ACCESS_KEY=17845714ff4c2e5f33f09740112be47925d0fab93d27b26982964cd14808b60b
R2_BUCKET_NAME=e-teams

✅ R2 Bucket Structure:

e-teams/
├── templates/
│   ├── Accenture.html
│   ├── Avanade.html
│   ├── Block.html
│   ├── Caterpillar.html
│   ├── Clark, Arthur.html
│   ├── Cox.html
│   ├── Cox_(1).html
│   ├── Highmark.html
│   ├── Inzunza5.html
│   ├── JNJ.html
│   ├── JUY.html
│   ├── Kenvue.html
│   └── Paramount_and_Viacom.html
└── converted_resumes/
    └── (outputs will go here)

Success! 🚀

Your backend is now fully connected to Cloudflare R2 and can:

✅ List templates from R2
✅ Fetch template content
✅ Process resumes with Gemini AI
✅ Upload results back to R2

Would you like me to update the frontend to use the real API instead of mocks?

5.1 KiB Raw Blame History