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Migrate Flask backend
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# Calling OpenAI Batch steps
Guide to OpenAI batch api --> https://platform.openai.com/docs/guides/batch
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## Step 1: Prepare Batch File (prepare_batch.py)
1. Prepare a .jsonl file containing your batch requests. Each line represents a single API request.
2. Usage: Run the script to process all files in the specified directory and generate the batch file.
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## Step 2: Upload Batch File (upload_batch_file.py)
1. Upload the prepared batch file to OpenAI using the Files API.
2. The script uploads batch_input.jsonl and returns the file ID.
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## Step 3: Create Batch (create_batch.py)
1. Create a batch job using the uploaded file's ID. Add the file ID obtained from running upload_batch_file.py to create_batch.py.
2. Returns a batch ID.
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## Step 4: Check Batch Status (check_batch_status.py)
1. Use the batch iD from create_batch.py to check the status of the batch job to monitor progress.
Possible statuses:
1. validating: Validating the input file.
2. in_progress: Batch is running.
3. completed: Batch is finished and results are ready.
4. failed: Validation failed.
5. expired: Batch did not complete within the window.
2. Retrieves the output_file_ID if completed.
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## Step 5: Retrieve Results (retrieve_results.py)
1. Download the results using the output_file_id retrieved from the batch status.
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## Helper scripts
1. Cancel Batch (cancel_batch.py)
1. Cancel an ongoing batch if required. Changes batch status to cancelling and eventually cancelled.
2. List Batches (list_batches.py)
1. View all batches created, including their status and metadata.
## Consolidated script that combines all the functionalities (Except helpers)
1. batch_processing.py