Floke
adafab61ae
This commit resolves all outstanding issues with the AI Insights feature.
- Corrects the transcript formatting logic in to properly handle the database JSON structure, ensuring the AI receives the correct context.
- Fixes the Gemini API client by using the correct model name ('gemini-2.0-flash') and the proper client initialization.
- Updates to securely pass the API key as an environment variable to the container.
- Cleans up the codebase by removing temporary debugging endpoints.
- Adds script for programmatic updates.
- Updates documentation with troubleshooting insights from the implementation process.
49 lines
1.7 KiB
Python
49 lines
1.7 KiB
Python
from sqlalchemy import create_engine
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from sqlalchemy.orm import sessionmaker
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from backend.database import Industry
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from backend.services.classification import ClassificationService
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import logging
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# Setup DB connection directly to the file
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# Note: We need to use the absolute path that works inside the container or relative if running locally
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# Assuming we run this via 'docker exec' or locally if paths align.
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# For safety, I'll use the path from config but typically inside container it's /app/...
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DB_URL = "sqlite:////app/companies_v3_fixed_2.db"
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engine = create_engine(DB_URL)
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SessionLocal = sessionmaker(bind=engine)
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db = SessionLocal()
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def test_logic():
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print("--- DEBUGGING STANDARDIZATION LOGIC ---")
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industry_name = "Healthcare - Hospital"
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industry = db.query(Industry).filter(Industry.name == industry_name).first()
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if not industry:
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print(f"ERROR: Industry '{industry_name}' not found!")
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return
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print(f"Industry: {industry.name}")
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print(f"Search Term: {industry.scraper_search_term}")
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print(f"Standardization Logic (Raw DB Value): '{industry.standardization_logic}'")
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if not industry.standardization_logic:
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print("CRITICAL: Standardization logic is empty/null! That explains the null result.")
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return
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# Initialize Service to test the exact method
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service = ClassificationService()
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test_value = 352.0
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print(f"\nTesting calculation with value: {test_value}")
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try:
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result = service._parse_standardization_logic(industry.standardization_logic, test_value)
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print(f"Result: {result}")
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except Exception as e:
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print(f"Exception during parsing: {e}")
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if __name__ == "__main__":
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test_logic()
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