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Enhance video generation logging and testing:
- Add detailed logging for video job processing in api_server.py - Implement synchronous and asynchronous video generation tests in test_endpoints.py - Introduce a debug response analyzer for inspecting JSON structures - Create comprehensive debug test for async video generation - Enable debug logging configuration for troubleshooting
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‎.github/workflows/publish.yml‎

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name: Publish metaai-sdk to PyPI
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on:
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push:
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tags:
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- "v*"
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permissions:
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contents: read
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id-token: write
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jobs:
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publish:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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with:
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fetch-depth: 0
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- uses: actions/setup-python@v5
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with:
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python-version: "3.11"
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- name: Build
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run: |
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pip install build setuptools_scm
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python -m build
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- name: Publish to PyPI
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uses: pypa/gh-action-pypi-publish@release/v1

‎.github/workflows/python-publish.yml‎

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‎analyze_debug_responses.py‎

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"""
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Analyze debug response files to understand the raw JSON structure.
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This helps us see EXACTLY what Meta AI is returning.
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"""
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import json
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import os
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import re
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from pathlib import Path
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DEBUG_DIR = Path("debug_responses")
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def analyze_response_file(filepath):
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"""Analyze a single debug response file."""
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print(f"\n{'='*80}")
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print(f"FILE: {filepath.name}")
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print(f"{'='*80}")
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try:
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with open(filepath, 'r', encoding='utf-8') as f:
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content = f.read()
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# Try to parse as JSON
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try:
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data = json.loads(content)
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print(f"✓ Valid JSON ({len(content)} characters)")
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# Look for video-related keys
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video_keys = []
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def find_video_keys(obj, path=""):
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if isinstance(obj, dict):
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for key, value in obj.items():
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current_path = f"{path}.{key}" if path else key
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if 'video' in key.lower() or 'url' in key.lower():
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video_keys.append((current_path, type(value).__name__, str(value)[:100]))
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find_video_keys(value, current_path)
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elif isinstance(obj, list):
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for idx, item in enumerate(obj):
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find_video_keys(item, f"{path}[{idx}]")
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find_video_keys(data)
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if video_keys:
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print(f"\nFound {len(video_keys)} video-related keys:")
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for path, vtype, sample in video_keys:
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print(f" • {path} ({vtype})")
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if vtype == 'str' and ('http' in sample or '.mp4' in sample):
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print(f" URL: {sample}")
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# Look for URLs in the raw text
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urls = re.findall(r'https?://[^\s\'"]+\.mp4[^\s\'"]*', content)
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if urls:
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print(f"\nFound {len(urls)} .mp4 URLs via regex:")
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for idx, url in enumerate(urls[:5], 1): # Show first 5
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print(f" {idx}. {url[:80]}...")
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# Look for video identifiers
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video_ids = re.findall(r'/v/[a-zA-Z0-9_-]+|/t6/[a-zA-Z0-9_-]+', content)
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if video_ids:
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print(f"\nFound {len(video_ids)} video identifier paths:")
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for vid_id in set(video_ids[:5]):
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print(f" • {vid_id}")
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except json.JSONDecodeError as e:
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print(f"✗ Invalid JSON: {e}")
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print(f"\nFirst 500 characters:")
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print(content[:500])
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except Exception as e:
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print(f"✗ Error reading file: {e}")
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def main():
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print("\n" + "="*80)
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print("DEBUG RESPONSE ANALYZER")
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print("="*80)
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if not DEBUG_DIR.exists():
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print(f"\n✗ Directory not found: {DEBUG_DIR}")
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return
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response_files = sorted(DEBUG_DIR.glob("response_*.txt"))
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if not response_files:
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print(f"\n✗ No response files found in {DEBUG_DIR}")
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return
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print(f"\nFound {len(response_files)} debug response files")
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for filepath in response_files:
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analyze_response_file(filepath)
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print("\n" + "="*80)
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print("ANALYSIS COMPLETE")
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print("="*80)
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print("\nThis shows the EXACT structure of Meta AI responses.")
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print("Use this to understand what fields contain video URLs.\n")
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if __name__ == "__main__":
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main()

‎debug_async_video_test.py‎

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"""
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Comprehensive debug test for async video generation with full tracing.
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This script will show EXACTLY what's happening at each step.
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"""
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import requests
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import json
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import time
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import logging
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# Enable detailed logging
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logging.basicConfig(
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level=logging.DEBUG,
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format='%(asctime)s - [%(levelname)s] %(message)s',
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)
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logger = logging.getLogger(__name__)
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API_URL = "http://localhost:8000"
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IMAGE_PATH = r"C:\Users\spike\Downloads\meta-ai-api-main\ChatGPT Image Jan 14, 2026, 06_59_02 PM.png"
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def test_async_video_generation():
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"""Test async video generation with comprehensive debugging."""
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print("\n" + "=" * 80)
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print("COMPREHENSIVE DEBUG TEST - ASYNC VIDEO GENERATION")
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print("=" * 80)
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# Step 1: Upload image
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logger.info("STEP 1: Uploading image...")
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with open(IMAGE_PATH, 'rb') as f:
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upload_response = requests.post(f"{API_URL}/upload", files={'file': f})
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if upload_response.status_code != 200:
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logger.error(f"Upload failed: {upload_response.text}")
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return
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upload_result = upload_response.json()
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media_id = upload_result['media_id']
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file_size = upload_result['file_size']
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mime_type = upload_result['mime_type']
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logger.info(f"✓ Upload successful")
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logger.info(f" Media ID: {media_id}")
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logger.info(f" File Size: {file_size}")
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logger.info(f" MIME Type: {mime_type}")
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# Step 2: Submit async video job
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logger.info("\nSTEP 2: Submitting async video job...")
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payload = {
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"prompt": "generate a video with cinematic zoom effect",
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"media_ids": [media_id],
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"attachment_metadata": {
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"file_size": file_size,
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"mime_type": mime_type
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},
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"wait_before_poll": 10,
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"max_attempts": 30,
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"wait_seconds": 5,
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"verbose": False
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}
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logger.debug(f"Payload: {json.dumps(payload, indent=2)}")
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job_response = requests.post(
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f"{API_URL}/video/async",
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headers={"Content-Type": "application/json"},
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data=json.dumps(payload)
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)
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if job_response.status_code != 200:
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logger.error(f"Job submission failed: {job_response.text}")
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return
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job_result = job_response.json()
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job_id = job_result['job_id']
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initial_status = job_result['status']
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logger.info(f"✓ Job submitted")
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logger.info(f" Job ID: {job_id}")
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logger.info(f" Initial Status: {initial_status}")
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# Step 3: Poll job status
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logger.info("\nSTEP 3: Polling job status...")
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max_polls = 20
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poll_interval = 3
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for poll_num in range(1, max_polls + 1):
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time.sleep(poll_interval)
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logger.info(f"\n--- POLL #{poll_num}/{max_polls} ---")
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status_response = requests.get(f"{API_URL}/video/jobs/{job_id}")
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if status_response.status_code != 200:
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logger.error(f"Failed to get job status: {status_response.text}")
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break
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job_status = status_response.json()
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current_status = job_status['status']
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logger.info(f"Status: {current_status}")
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logger.info(f"Created: {job_status['created_at']}")
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logger.info(f"Updated: {job_status['updated_at']}")
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if current_status == 'succeeded':
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logger.info("\n✓✓✓ JOB SUCCEEDED ✓✓✓")
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result = job_status.get('result', {})
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logger.info("\nResult Details:")
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logger.info(f" Success Flag: {result.get('success')}")
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logger.info(f" Conversation ID: {result.get('conversation_id')}")
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logger.info(f" Prompt: {result.get('prompt')}")
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logger.info(f" Timestamp: {result.get('timestamp')}")
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video_urls = result.get('video_urls', [])
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logger.info(f"\n Video URLs Count: {len(video_urls)}")
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if video_urls:
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for idx, url in enumerate(video_urls, 1):
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logger.info(f"\n VIDEO {idx}:")
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logger.info(f" Full URL: {url}")
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logger.info(f" Length: {len(url)} characters")
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logger.info(f" Has .mp4: {'.mp4' in url}")
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logger.info(f" Has fbcdn: {'fbcdn' in url}")
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logger.info(f" Has /v/: {'/v/' in url}")
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logger.info(f" Has /t6/: {'/t6/' in url}")
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else:
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logger.warning("\n ⚠ NO VIDEO URLs FOUND!")
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logger.warning(" This means URL extraction failed even though generation succeeded")
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logger.debug(f"\nFull Job Status JSON:\n{json.dumps(job_status, indent=2)}")
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break
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elif current_status == 'failed':
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logger.error("\n✗✗✗ JOB FAILED ✗✗✗")
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error = job_status.get('error', 'Unknown error')
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logger.error(f"Error: {error}")
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logger.debug(f"\nFull Job Status JSON:\n{json.dumps(job_status, indent=2)}")
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break
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elif current_status in ['pending', 'running']:
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logger.info(f"⏳ Job still {current_status}... waiting {poll_interval}s")
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else:
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logger.warning(f"Unknown status: {current_status}")
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else:
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logger.warning(f"\n⚠ Reached max polls ({max_polls}). Job may still be processing.")
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logger.info(f"Check manually: GET {API_URL}/video/jobs/{job_id}")
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print("\n" + "=" * 80)
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print("DEBUG TEST COMPLETE")
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print("=" * 80)
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print("\nCheck meta_ai_debug.log for server-side logs")
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print()
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if __name__ == "__main__":
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try:
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test_async_video_generation()
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except KeyboardInterrupt:
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logger.info("\n\nTest interrupted by user")
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except Exception as e:
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logger.error(f"\n\nTest failed with exception: {e}", exc_info=True)

‎enable_debug_logging.py‎

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"""
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Enable comprehensive debug logging for Meta AI API troubleshooting.
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Run this before starting the server to see detailed logs.
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"""
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import logging
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import sys
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# Configure root logger
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logging.basicConfig(
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level=logging.DEBUG,
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
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handlers=[
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logging.StreamHandler(sys.stdout),
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logging.FileHandler('meta_ai_debug.log', mode='w')
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]
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)
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# Set specific loggers to DEBUG
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logging.getLogger('metaai_api').setLevel(logging.DEBUG)
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logging.getLogger('metaai_api.video_generation').setLevel(logging.DEBUG)
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logging.getLogger('metaai_api.api_server').setLevel(logging.DEBUG)
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logging.getLogger('uvicorn').setLevel(logging.INFO)
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print("=" * 70)
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print("DEBUG LOGGING ENABLED")
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print("=" * 70)
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print("Log output:")
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print(" - Console: stdout (colored)")
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print(" - File: meta_ai_debug.log")
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print("=" * 70)
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print()

‎pyproject.toml‎

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[build-system]
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requires = ["setuptools>=61", "wheel"]
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requires = ["setuptools>=61", "setuptools_scm"]
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build-backend = "setuptools.build_meta"
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[project]
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name = "metaai-sdk"
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version = "2.2.1"
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dynamic = ["version"]
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description = "Feature-rich Python SDK for Meta AI - Chat, Image & Video Generation powered by Llama 3"
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authors = [{name = "Ashiq Hussain Mir", email = "imseldrith@gmail.com"}]
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readme = "README.md"
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"pytest",
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"black",
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"flake8",
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]
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]
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[tool.setuptools_scm]
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version_scheme = "release"
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local_scheme = "no-local-version"

‎setup.cfg‎

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