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Exception is thrown with large `max_tokens`.

Fresh3 days ago
Mar 14, 20260 views
Confidence Score47%
47%

Problem

Hello, I am trying to use a model with `max_tokens=64000`. However, an exception gets thrown, saying that, with a large `max_tokens`, streaming is strongly recommended. In particular, from where the exception is thrown and from the text of the exception it seems like this should be a warning instead? In my use case, I do not need streaming, and I am fine with not using it, even if the expected time to get a completion is long. Thank you in advance!

Error Output

exception gets thrown, saying that, with a large `max_tokens`, streaming is strongly recommended. In particular, from [where the exception is thrown](https://github.com/anthropics/anthropic-sdk-python/blob/main

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1 Fix

Canonical Fix
Unverified Fix
New Fix โ€“ Awaiting Verification

Adjust max_tokens and Implement Streaming for Large Requests

Medium Risk

The exception is thrown because the model's API is designed to recommend streaming for large `max_tokens` values (like 64000) to handle the response efficiently and avoid timeouts. Without streaming, the request may take too long to process, leading to performance issues or failures.

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  1. 1

    Reduce max_tokens Value

    Consider reducing the `max_tokens` value to a more manageable size (e.g., 4096 or 8192) to avoid the need for streaming. This will allow the model to process the request without throwing an exception.

    python
    max_tokens = 4096
  2. 2

    Implement Streaming

    If you require the full response and cannot reduce `max_tokens`, implement streaming in your API call. This will allow the model to send partial responses as they are generated, which can handle larger token counts more effectively.

    python
    response = client.completions.create(model='claude', prompt='your prompt', max_tokens=64000, stream=True)
  3. 3

    Handle Streaming Responses

    Ensure your code can handle streamed responses correctly. This may involve iterating over the response chunks and concatenating them to form the complete output.

    python
    for chunk in response:
        print(chunk['choices'][0]['text'], end='')
  4. 4

    Test the Implementation

    Run your application with the adjusted `max_tokens` or streaming implementation to ensure that it works without throwing exceptions and that the output is as expected.

    python
    assert 'expected output' in output

Validation

Confirm the fix by running the application with both the reduced `max_tokens` and the streaming implementation. Ensure that no exceptions are thrown and that the output is generated correctly.

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Environment

Submitted by

AC

Alex Chen

2450 rep

Tags

claudeanthropicllmapi