Floke
4568623e77
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.
35 lines
1.1 KiB
Python
35 lines
1.1 KiB
Python
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import requests
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import os
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def test_export_endpoint():
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# The app runs on port 8000 inside the container.
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# The root_path is /ce, so the full URL is http://localhost:8000/ce/api/companies/export
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url = "http://localhost:8000/ce/api/companies/export"
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print(f"--- Testing Export Endpoint: GET {url} ---")
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try:
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response = requests.get(url)
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response.raise_for_status() # Will raise an exception for 4xx/5xx errors
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# Print the first few hundred characters to verify content
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print("\n--- Response Headers ---")
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print(response.headers)
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print("\n--- CSV Output (first 500 chars) ---")
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print(response.text[:500])
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# A simple check
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if "Metric Value" in response.text and "Source URL" in response.text:
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print("\n[SUCCESS] New columns found in export.")
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else:
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print("\n[FAILURE] New columns seem to be missing from the export.")
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except requests.exceptions.RequestException as e:
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print(f"\n[FAILURE] Could not connect to the endpoint: {e}")
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if __name__ == "__main__":
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test_export_endpoint()
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