Spaces:
Sleeping
Sleeping
File size: 7,905 Bytes
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SIMPLE FIX - UPDATE YOUR SPACE (Takes 2 Minutes)
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PROBLEM: Still getting timeout errors even with token set
CAUSE: Code is still using local models (setdefault doesn't force override)
SOLUTION: Replace with direct assignment to force HF API mode
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STEP 1: Open Your Space
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1. Go to your HuggingFace Space
2. Click "Files" tab
3. Click "app.py" to edit
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STEP 2: Find and Replace Lines 140-170
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FIND THIS (around line 140-170):
# Set defaults for HuggingFace Spaces (can be overridden with Spaces Variables)
os.environ.setdefault("USE_HF_API", "False")
os.environ.setdefault("USE_LMSTUDIO", "False")
os.environ.setdefault("DEBUG_MODE", os.getenv("DEBUG_MODE", "False"))
os.environ.setdefault("LLM_BACKEND", "local")
os.environ.setdefault("LLM_TIMEOUT", "120")
os.environ.setdefault("MAX_TOKENS_PER_REQUEST", "1500")
os.environ.setdefault("LLM_TEMPERATURE", "0.7")
print("✅ Configuration loaded for HuggingFace Spaces")
# Auto-detect HuggingFace Spaces and force HF API (...)
# ... (about 20 more lines of auto-detection code)
REPLACE WITH THIS (copy exactly):
# FORCE HF API for HuggingFace Spaces deployment
# Local models timeout on free tier - always use HF API when deployed
print("🚀 Forcing HF API mode for HuggingFace Spaces deployment...")
os.environ["USE_HF_API"] = "True"
os.environ["USE_LMSTUDIO"] = "False"
os.environ["LLM_BACKEND"] = "hf_api"
os.environ["DEBUG_MODE"] = os.getenv("DEBUG_MODE", "False")
os.environ["LLM_TIMEOUT"] = "180" # 3 minutes
os.environ["MAX_TOKENS_PER_REQUEST"] = "1500"
os.environ["LLM_TEMPERATURE"] = "0.7"
# Check if HF token is set (required for HF API)
hf_token = os.getenv("HUGGINGFACE_TOKEN", "")
if not hf_token:
print("="*70)
print("⚠️ ERROR: HUGGINGFACE_TOKEN not set!")
print(" This is REQUIRED for HF API mode to work.")
print(" Add it in Space Settings → Repository Secrets")
print(" Get token from: https://huggingface.co/settings/tokens")
print("="*70)
else:
print("✅ HuggingFace token detected")
print("✅ Configuration loaded for HuggingFace Spaces")
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STEP 3: Save and Commit
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1. Click "Commit changes to main"
2. Wait ~2 minutes for Space to restart
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STEP 4: Verify It Worked
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After restart, check the Logs tab. You should see:
🚀 Forcing HF API mode for HuggingFace Spaces deployment...
✅ HuggingFace token detected
✅ Configuration loaded for HuggingFace Spaces
🚀 TranscriptorAI Enterprise - LLM Backend: hf_api
🔧 USE_HF_API: True
When processing a file, you should see:
INFO: Calling HF API: microsoft/Phi-3-mini-4k-instruct
(NOT "Generating with local model")
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KEY DIFFERENCE: setdefault vs direct assignment
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OLD (doesn't work):
os.environ.setdefault("USE_HF_API", "False") ← Won't override existing value
NEW (works):
os.environ["USE_HF_API"] = "True" ← Always sets it to True
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IF STILL NOT WORKING
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Add this as the FIRST LINE in the analyze() function (around line 178):
def analyze(files, file_type, user_comments, role_hint, debug_mode, interviewee_type,
enable_pii_redaction, redaction_level, progress=gr.Progress()):
"""..."""
# FORCE HF API MODE - add this as first line
os.environ["USE_HF_API"] = "True"
os.environ["LLM_BACKEND"] = "hf_api"
print("🚀🚀🚀 FORCED HF API IN ANALYZE FUNCTION")
# ... rest of function ...
This ensures it's set RIGHT before processing starts.
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CHECKLIST
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□ Token added to Space Settings → Repository Secrets
□ Replaced lines 140-170 in app.py with new code
□ Committed changes
□ Space restarted
□ Logs show "USE_HF_API: True"
□ Logs show "Calling HF API" (not "local model")
□ Processing completes without timeout
□ Quality Score > 0.00
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IF ALL CHECKED: YOUR SPACE IS FIXED! 🎉
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