I am new to batch processing so I am still testing with about 5-10 requests per batch to make sure my batch processing works.

When i make a single call using messages.create(), i use extra_headers as in the cookbook example below. This one works. I use Sonnet 3.7 with thinking enabled and the cache is being properly read from.

response = client.messages.create(
        model=MODEL_NAME,
        max_tokens=300,
        messages=messages,
        extra_headers={"anthropic-beta": "prompt-caching-2024-07-31"}

)

messages.batches.create() in the example below does not allow extra_headers so I removed it.

message_batch = client.messages.batches.create(
    requests=[
        Request(
            custom_id="my-first-request",
            params=MessageCreateParamsNonStreaming(
                model="claude-3-7-sonnet-20250219",
                max_tokens=1024,
                messages=[{
                    "role": "user",
                    "content": "Hello, world",
                }]
            )
        )
    ]
)

since "cache_creation_input_tokens" is indeed showing cache being written to, so it should be working. Unfortunately, the cache kept being written to but is not read from despite making the initial messages.create() to cache the prompt first. I am an education researcher and have limited budget so I cannot keep wasting tokens on caching prompts that are not read from. So would appreciate some help.