Portkey supports managing files in two ways:
  1. Provider Files: Uploading and managing files directly to any provider using the unified signature
  2. Portkey Files: Uploading files to Portkey and using them for batching/fine-tuning requests with any provider

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1. Provider Files

Upload and manage files directly to providers (OpenAI, Bedrock, etc.) using Portkey’s unified API signature. This approach is useful when you need provider-specific file features or want to manage files directly on the provider’s platform.

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Supported Providers

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Quick Example

curl -X POST https://api.portkey.ai/v1/files \
  -H "Authorization: Bearer $PORTKEY_API_KEY" \
  -H "x-portkey-provider: openai" \
  -F "purpose=fine-tune" \
  -F "file=@training_data.jsonl"

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2. Portkey Files

Upload files to Portkey and reuse them for batching inference with any provider and fine-tuning with supported providers. This approach is ideal for:
  • Testing your data with different foundation models
  • Performing A/B testing across multiple providers
  • Batch inference with provider-agnostic file management
  • Reusing the same file across multiple batch jobs

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File Requirements

  • Format: JSONL files where each line contains a single request payload

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Uploading Files

curl -X POST https://api.portkey.ai/v1/files \
  -H "Authorization: Bearer $PORTKEY_API_KEY" \
  -F "purpose=batch" \
  -F "file=@batch_data.jsonl"

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Listing Files

curl -X GET https://api.portkey.ai/v1/files \
  -H "Authorization: Bearer $PORTKEY_API_KEY"

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Get File Details

curl -X GET https://api.portkey.ai/v1/files/{file_id} \
  -H "Authorization: Bearer $PORTKEY_API_KEY"

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Get File Content

curl -X GET https://api.portkey.ai/v1/files/{file_id}/content \
  -H "Authorization: Bearer $PORTKEY_API_KEY"

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File Format Examples

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Batch Inference JSONL Format

Each line should be a valid JSON object representing a single request: 
{"custom_id": "request-1", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "gpt-3.5-turbo-0125", "messages": [{"role": "system", "content": "You are a helpful assistant."},{"role": "user", "content": "Hello world!"}],"max_tokens": 1000}}
{"custom_id": "request-2", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "gpt-3.5-turbo-0125", "messages": [{"role": "system", "content": "You are an unhelpful assistant."},{"role": "user", "content": "Hello world!"}],"max_tokens": 1000}}

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Fine-tuning JSONL Format

For fine-tuning, each line should contain training examples: 
{"messages": [{"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": "Hello"}, {"role": "assistant", "content": "Hi! How can I help you today?"}]}
{"messages": [{"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": "What's 2+2?"}, {"role": "assistant", "content": "2+2 equals 4."}]}

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Security & Best Practices

  • Encryption: Files are encrypted at rest using AES-256
  • Access Control: File access is gated by workspace permissions
  • Provider Upload: Portkey uploads files to providers using least-privilege credentials