completions.cpython-312.pyc•17.9 kB
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� � y�a� [Legacy] Create a Text Completion.
The Text Completions API is a legacy API.
We recommend using the
[Messages API](https://docs.anthropic.com/claude/reference/messages_post) going
forward.
Future models and features will not be compatible with Text Completions. See our
[migration guide](https://docs.anthropic.com/claude/reference/migrating-from-text-completions-to-messages)
for guidance in migrating from Text Completions to Messages.
Args:
max_tokens_to_sample: The maximum number of tokens to generate before stopping.
Note that our models may stop _before_ reaching this maximum. This parameter
only specifies the absolute maximum number of tokens to generate.
model: The model that will complete your prompt.
See [models](https://docs.anthropic.com/claude/docs/models-overview) for
additional details and options.
prompt: The prompt that you want Claude to complete.
For proper response generation you will need to format your prompt using
alternating `
Human:` and `
Assistant:` conversational turns. For example:
```
"
Human: {userQuestion}
Assistant:"
```
See
[prompt validation](https://anthropic.readme.io/claude/reference/prompt-validation)
and our guide to
[prompt design](https://docs.anthropic.com/claude/docs/introduction-to-prompt-design)
for more details.
metadata: An object describing metadata about the request.
stop_sequences: Sequences that will cause the model to stop generating.
Our models stop on `"
Human:"`, and may include additional built-in stop
sequences in the future. By providing the stop_sequences parameter, you may
include additional strings that will cause the model to stop generating.
stream: Whether to incrementally stream the response using server-sent events.
See
[streaming](https://docs.anthropic.com/claude/reference/text-completions-streaming)
for details.
temperature: Amount of randomness injected into the response.
Defaults to `1.0`. Ranges from `0.0` to `1.0`. Use `temperature` closer to `0.0`
for analytical / multiple choice, and closer to `1.0` for creative and
generative tasks.
Note that even with `temperature` of `0.0`, the results will not be fully
deterministic.
top_k: Only sample from the top K options for each subsequent token.
Used to remove "long tail" low probability responses.
[Learn more technical details here](https://towardsdatascience.com/how-to-sample-from-language-models-682bceb97277).
Recommended for advanced use cases only. You usually only need to use
`temperature`.
top_p: Use nucleus sampling.
In nucleus sampling, we compute the cumulative distribution over all the options
for each subsequent token in decreasing probability order and cut it off once it
reaches a particular probability specified by `top_p`. You should either alter
`temperature` or `top_p`, but not both.
Recommended for advanced use cases only. You usually only need to use
`temperature`.
extra_headers: Send extra headers
extra_query: Add additional query parameters to the request
extra_body: Add additional JSON properties to the request
timeout: Override the client-level default timeout for this request, in seconds
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� � y�a� [Legacy] Create a Text Completion.
The Text Completions API is a legacy API.
We recommend using the
[Messages API](https://docs.anthropic.com/claude/reference/messages_post) going
forward.
Future models and features will not be compatible with Text Completions. See our
[migration guide](https://docs.anthropic.com/claude/reference/migrating-from-text-completions-to-messages)
for guidance in migrating from Text Completions to Messages.
Args:
max_tokens_to_sample: The maximum number of tokens to generate before stopping.
Note that our models may stop _before_ reaching this maximum. This parameter
only specifies the absolute maximum number of tokens to generate.
model: The model that will complete your prompt.
See [models](https://docs.anthropic.com/claude/docs/models-overview) for
additional details and options.
prompt: The prompt that you want Claude to complete.
For proper response generation you will need to format your prompt using
alternating `
Human:` and `
Assistant:` conversational turns. For example:
```
"
Human: {userQuestion}
Assistant:"
```
See
[prompt validation](https://anthropic.readme.io/claude/reference/prompt-validation)
and our guide to
[prompt design](https://docs.anthropic.com/claude/docs/introduction-to-prompt-design)
for more details.
stream: Whether to incrementally stream the response using server-sent events.
See
[streaming](https://docs.anthropic.com/claude/reference/text-completions-streaming)
for details.
metadata: An object describing metadata about the request.
stop_sequences: Sequences that will cause the model to stop generating.
Our models stop on `"
Human:"`, and may include additional built-in stop
sequences in the future. By providing the stop_sequences parameter, you may
include additional strings that will cause the model to stop generating.
temperature: Amount of randomness injected into the response.
Defaults to `1.0`. Ranges from `0.0` to `1.0`. Use `temperature` closer to `0.0`
for analytical / multiple choice, and closer to `1.0` for creative and
generative tasks.
Note that even with `temperature` of `0.0`, the results will not be fully
deterministic.
top_k: Only sample from the top K options for each subsequent token.
Used to remove "long tail" low probability responses.
[Learn more technical details here](https://towardsdatascience.com/how-to-sample-from-language-models-682bceb97277).
Recommended for advanced use cases only. You usually only need to use
`temperature`.
top_p: Use nucleus sampling.
In nucleus sampling, we compute the cumulative distribution over all the options
for each subsequent token in decreasing probability order and cut it off once it
reaches a particular probability specified by `top_p`. You should either alter
`temperature` or `top_p`, but not both.
Recommended for advanced use cases only. You usually only need to use
`temperature`.
extra_headers: Send extra headers
extra_query: Add additional query parameters to the request
extra_body: Add additional JSON properties to the request
timeout: Override the client-level default timeout for this request, in seconds
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