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#!/usr/bin/env python3
"""
Fix Qdrant collection dimensions for Manufacturing RAG Agent
"""
import os
from dotenv import load_dotenv
from qdrant_client import QdrantClient
from qdrant_client.http import models
load_dotenv()
# QDRANT_API_KEY= os.getenv('QDRANT_API_KEY', 'eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJhY2Nlc3MiOiJtIn0.DHeUsIY234NwS-6cYDJec807Vdzbs1PHmBBU3_Jz9oo')
# QDRANT_URL=os.getenv('QDRANT_URL', 'https://50f53cc8-bbb0-4939-8254-8f025a577222.us-west-2-0.aws.cloud.qdrant.io:6333')
# QDRANT_URL= os.getenv('QDRANT_URL', 'http://localhost:6333')
def fix_qdrant_collection():
"""Fix the Qdrant collection dimensions."""
print("🔧 Fixing Qdrant Collection Dimensions")
print("=" * 50)
# Get connection details
qdrant_api_key = os.environ["QDRANT_API_KEY"]
qdrant_url = os.environ["QDRANT_URL"]
collection_name = 'manufacturing_docs'
if not qdrant_url:
print("❌ QDRANT_URL not found in environment variables")
return False
try:
# Connect to Qdrant
print(f"🔗 Connecting to Qdrant: {qdrant_url}")
client = QdrantClient(
url="https://50f53cc8-bbb0-4939-8254-8f025a577222.us-west-2-0.aws.cloud.qdrant.io:6333",
api_key="eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJhY2Nlc3MiOiJtIn0.gHOXbfqPucRwhczrW8s3VSZbconqQ6Rk49Uaz9ZChdE",)
# Check if collection exists
collections = client.get_collections()
collection_names = [col.name for col in collections.collections]
if collection_name in collection_names:
print(f"📋 Collection '{collection_name}' exists")
# Get collection info
collection_info = client.get_collection(collection_name)
current_dim = collection_info.config.params.vectors.size
print(f"📏 Current vector dimensions: {current_dim}")
if current_dim != 1024:
print(f"⚠️ Need to recreate collection with correct dimensions (1024)")
# Ask for confirmation
response = input("🗑️ Delete existing collection and recreate? (y/N): ").strip().lower()
if response != 'y':
print("❌ Aborted by user")
return False
# Delete existing collection
print(f"🗑️ Deleting collection '{collection_name}'...")
client.delete_collection(collection_name)
print("✅ Collection deleted")
else:
print("✅ Collection already has correct dimensions")
return True
# Create new collection with correct dimensions
print(f"🆕 Creating collection '{collection_name}' with 4096 dimensions...")
client.create_collection(
collection_name=collection_name,
vectors_config=models.VectorParams(
size=4096, # Correct size for Qwen/Qwen3-Embedding-8B
distance=models.Distance.COSINE
)
)
# Create payload indexes
print("🔍 Creating payload indexes...")
indexes_to_create = [
("document_id", models.PayloadFieldSchema(
data_type=models.PayloadSchemaType.KEYWORD
)),
("document_type", models.PayloadFieldSchema(
data_type=models.PayloadSchemaType.KEYWORD
)),
("page_number", models.PayloadFieldSchema(
data_type=models.PayloadSchemaType.INTEGER
)),
("worksheet_name", models.PayloadFieldSchema(
data_type=models.PayloadSchemaType.KEYWORD
)),
]
for field_name, field_schema in indexes_to_create:
try:
client.create_payload_index(
collection_name=collection_name,
field_name=field_name,
field_schema=field_schema
)
print(f"✅ Created index for '{field_name}'")
except Exception as e:
print(f"⚠️ Failed to create index for '{field_name}': {e}")
print("✅ Collection recreated successfully with correct dimensions!")
return True
except Exception as e:
print(f"❌ Error: {e}")
return False
def update_config_file():
"""Update config.yaml with correct vector dimensions."""
print("\n🔧 Updating Configuration")
print("=" * 30)
config_path = "src/config.yaml"
if not os.path.exists(config_path):
print(f"❌ Config file not found: {config_path}")
return False
try:
# Read current config
with open(config_path, 'r') as f:
content = f.read()
# Update vector_size if it exists
import re
# Look for vector_size configuration
if 'vector_size:' in content:
# Replace vector_size value
content = re.sub(r'vector_size:\s*\d+', 'vector_size: 4096', content)
print("✅ Updated vector_size to 4096")
else:
# Add vector_size to vector_store section
if 'vector_store:' in content:
content = re.sub(
r'(vector_store:\s*\n)',
r'\1 vector_size: 4096\n',
content
)
print("✅ Added vector_size: 4096 to vector_store section")
else:
print("⚠️ No vector_store section found, please add manually:")
print("vector_store:")
print(" vector_size: 4096")
# Write updated config
with open(config_path, 'w') as f:
f.write(content)
print(f"✅ Updated {config_path}")
return True
except Exception as e:
print(f"❌ Error updating config: {e}")
return False
def test_embedding_dimensions():
"""Test the actual embedding dimensions from SiliconFlow."""
print("\n🧪 Testing Embedding Dimensions")
print("=" * 35)
try:
import requests
api_key = os.getenv('SILICONFLOW_API_KEY')
if not api_key:
print("❌ SILICONFLOW_API_KEY not found")
return None
# Test embedding generation
payload = {
"model": "Qwen/Qwen3-Embedding-8B",
"input": ["test embedding dimension"],
"encoding_format": "float"
}
headers = {
'Authorization': f'Bearer {api_key}',
'Content-Type': 'application/json'
}
response = requests.post(
"https://api.siliconflow.com/v1/embeddings",
json=payload,
headers=headers,
timeout=10
)
if response.status_code == 200:
data = response.json()
if data.get('data') and len(data['data']) > 0:
embedding = data['data'][0]['embedding']
dim = len(embedding)
print(f"✅ Actual embedding dimensions: {dim}")
return dim
else:
print("❌ No embedding data returned")
else:
print(f"❌ API error: {response.status_code} - {response.text}")
except Exception as e:
print(f"❌ Error testing embeddings: {e}")
return None
def main():
"""Main function."""
print("🏭 Manufacturing RAG Agent - Dimension Fix")
print("=" * 60)
# Test actual embedding dimensions
actual_dim = test_embedding_dimensions()
if actual_dim and actual_dim != 4096:
print(f"⚠️ Warning: Expected 4096 dimensions, but got {actual_dim}")
print("You may need to update the vector_size in your config")
# Fix Qdrant collection
if fix_qdrant_collection():
print("\n✅ Qdrant collection fixed successfully!")
else:
print("\n❌ Failed to fix Qdrant collection")
return
# Update config file
if update_config_file():
print("✅ Configuration updated successfully!")
else:
print("⚠️ Please update config manually")
print("\n🎉 Fix Complete!")
print("\n📋 Next Steps:")
print("1. Restart your Gradio demo")
print("2. Re-upload your documents")
print("3. Test question answering")
print("\n🚀 To restart the demo:")
print("python fixed_gradio_demo.py")
if __name__ == "__main__":
main() |