wehub-resource-sync
131 lines
4.2 KiB
Python
131 lines
4.2 KiB
Python
"""Example usage of the Google Drive backend for Ragas.
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This example shows how to:
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1. Set up authentication for Google Drive
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2. Create a dataset with Google Drive backend
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3. Store and retrieve data from Google Sheets
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Prerequisites:
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1. Install Google Drive dependencies:
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pip install "ragas[gdrive]"
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2. Set up Google Drive API credentials:
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- Go to Google Cloud Console
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- Enable Google Drive API and Google Sheets API
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- Create credentials (OAuth or Service Account)
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- Download the JSON file
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3. Set up authentication - choose one:
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Option A: Environment variables
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Option B: Pass paths directly to backend
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For detailed setup instructions, see the documentation.
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"""
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from pydantic import BaseModel
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from ragas.dataset import Dataset
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# Example data model
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class EvaluationRecord(BaseModel):
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question: str
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answer: str
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context: str
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score: float
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feedback: str
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def example_usage():
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"""Example of using the Google Drive backend."""
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# REQUIRED: Replace with your actual Google Drive folder ID
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# This should be the ID from the Google Drive folder URL:
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# https://drive.google.com/drive/folders/YOUR_FOLDER_ID_HERE
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folder_id = "folder_id_here"
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# Option A: Set up with environment variables
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# os.environ["GDRIVE_CREDENTIALS_PATH"] = "path/to/credentials.json"
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# dataset = Dataset(
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# name="evaluation_results",
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# backend="gdrive",
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# data_model=EvaluationRecord, # This is required when using Pydantic models
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# folder_id=folder_id
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# )
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# Option B: Pass credentials directly
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dataset = Dataset(
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name="evaluation_results",
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backend="gdrive",
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data_model=EvaluationRecord, # This is required when using Pydantic models
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folder_id=folder_id,
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credentials_path="credentials.json", # For OAuth
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# service_account_path="path/to/service_account.json", # Alternative: Service Account
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token_path="token.json", # Where OAuth token will be saved
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)
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# Create some sample data
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sample_data = [
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EvaluationRecord(
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question="What is the capital of France?",
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answer="Paris",
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context="France is a country in Western Europe.",
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score=0.95,
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feedback="Correct answer",
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),
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EvaluationRecord(
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question="What is 2 + 2?",
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answer="Four", # Changed from "4" to avoid Google Sheets auto-conversion to number
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context="Basic arithmetic question.",
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score=1.0,
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feedback="Perfect answer",
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),
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EvaluationRecord(
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question="Who wrote Romeo and Juliet?",
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answer="William Shakespeare",
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context="Romeo and Juliet is a famous play.",
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score=1.0,
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feedback="Correct author",
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),
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]
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# Add data to the dataset
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for record in sample_data:
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dataset.append(record)
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# Save to Google Drive
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dataset.save()
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print(f"Saved {len(dataset)} records to Google Drive")
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# Load data back
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dataset.reload()
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print(f"Loaded {len(dataset)} records from Google Drive")
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# Access individual records
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for i, record in enumerate(dataset):
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print(
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f"Record {i + 1}: {record['question'] if isinstance(record, dict) else record.question} -> {record['answer'] if isinstance(record, dict) else record.answer} (Score: {record['score'] if isinstance(record, dict) else record.score})"
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)
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# List all datasets in the backend
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available_datasets = dataset.backend.list_datasets()
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print(f"Available datasets: {available_datasets}")
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return dataset
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if __name__ == "__main__":
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try:
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dataset = example_usage()
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print("\nGoogle Drive backend example completed successfully!")
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print(
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"\nYour data is now stored in Google Sheets within your specified folder."
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)
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except Exception as e:
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print(f"Error: {e}")
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print("\nMake sure to:")
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print("1. Install required dependencies: pip install 'ragas[gdrive]'")
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print("2. Set up Google Drive API credentials")
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print("3. Update the folder_id and credential paths in this example")
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print("4. Ensure the Google Drive folder is accessible to your credentials")
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