Python function that uses the Google Drive API to search for files, ingests the raw data from those files into Pandas dataframes, and then analyzes the data using OpenAI's API for natural language processing

OpenAISearchGoogleDrive.py

import os
import pickle
import pandas as pd
from googleapiclient.discovery import build
from google_auth_oauthlib.flow import InstalledAppFlow
from google.auth.transport.requests import Request
import openai

# Google Drive API settings
SCOPES_DRIVE = ['https://www.googleapis.com/auth/drive.readonly']

# OpenAI API key
OPENAI_API_KEY = 'YOUR_OPENAI_API_KEY'

def authenticate_google_drive():
    creds = None
    if os.path.exists('token_drive.pickle'):
        with open('token_drive.pickle', 'rb') as token:
            creds = pickle.load(token)
    if not creds or not creds.valid:
        if creds and creds.expired and creds.refresh_token:
            creds.refresh(Request())
        else:
            flow = InstalledAppFlow.from_client_secrets_file(
                'credentials_drive.json', SCOPES_DRIVE)
            creds = flow.run_local_server(port=0)
        with open('token_drive.pickle', 'wb') as token:
            pickle.dump(creds, token)
    return creds

def search_and_analyze_files(query):
    creds = authenticate_google_drive()
    drive_service = build('drive', 'v3', credentials=creds)
    
    try:
        results = drive_service.files().list(
            q=query,
            fields="nextPageToken, files(id, name)").execute()
        files = results.get('files', [])
        
        if not files:
            print('No files found.')
            return
        
        openai.api_key = OPENAI_API_KEY
        
        for file in files:
            print(f"Processing {file['name']} ({file['id']})")
            download_url = f"https://drive.google.com/uc?id={file['id']}"
            df = pd.read_csv(download_url)  # Adjust for your file type
            
            # Analyze data using OpenAI
            data_analysis_prompt = f"Analyze the data in the file {file['name']}."
            response = openai.Completion.create(
                engine="davinci", prompt=data_analysis_prompt, max_tokens=100
            )
            analysis_result = response.choices[0].text
            
            print("Data Analysis:")
            print(analysis_result)
            
            # You can further process or visualize the DataFrame and analysis result as needed
            print(df.head())  # Print the first few rows of the DataFrame
            
    except Exception as e:
        print(f'An error occurred: {e}')

if __name__ == '__main__':
    search_query = "Your search query here"  # Replace with your search query
    search_and_analyze_files(search_query)