mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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[Doc] add chat_template_kwagrs and update params docs (#3103)
* add chat_template_kwagrs and update params docs * add chat_template_kwagrs and update params docs * update enable_thinking * pre-commit * update test case --------- Co-authored-by: Jiang-Jia-Jun <163579578+Jiang-Jia-Jun@users.noreply.github.com>
This commit is contained in:
LiqinruiG
@@ -43,7 +43,7 @@ curl -X POST "http://0.0.0.0:8192/v1/chat/completions" \
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{"type": "text", "text": "Which era does the cultural relic in the picture belong to"}
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]}
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],
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"enable_thinking": true,
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"chat_template_kwargs":{"enable_thinking": true},
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"reasoning_max_tokens": 1024
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}'
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```
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@@ -70,7 +70,7 @@ chat_response = client.chat.completions.create(
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model="vl",
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stream=True,
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extra_body={
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"enable_thinking": True,
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"chat_template_kwargs":{"enable_thinking": True},
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"reasoning_max_tokens": 1024
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}
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)
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@@ -113,7 +113,7 @@ curl -X POST "http://0.0.0.0:8180/v1/chat/completions" \
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{"type": "text", "text": "From which era does the artifact in the image originate?"}
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]}
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],
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"enable_thinking": false
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"chat_template_kwargs":{"enable_thinking": false}
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}'
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```
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@@ -74,7 +74,7 @@ curl -X POST "http://0.0.0.0:8180/v1/chat/completions" \
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{"type": "text", "text": "What era does this artifact belong to?"}
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]}
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],
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"enable_thinking": false
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"chat_template_kwargs":{"enable_thinking": false}
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}'
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```
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@@ -21,9 +21,10 @@ python -m fastdeploy.entrypoints.openai.api_server \
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For more usage methods of the command line during service deployment, refer to [Parameter Descriptions](../parameters.md).
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## Sending User Requests
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## Chat Completion API
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FastDeploy provides a Chat Completion API that is compatible with the OpenAI protocol, allowing user requests to be sent directly using OpenAI's request method.
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The FastDeploy interface is compatible with the OpenAI protocol, allowing user requests to be sent directly using OpenAI's request method.
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### Sending User Requests
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Here is an example of sending a user request using the curl command:
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@@ -73,53 +74,169 @@ print('\n')
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For a description of the OpenAI protocol, refer to the document [OpenAI Chat Completion API](https://platform.openai.com/docs/api-reference/chat/create).
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## Parameter Differences
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### Request Parameter Differences
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The differences in request parameters between FastDeploy and the OpenAI protocol are as follows. Other request parameters will be ignored:
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### Compatible OpenAI Parameters
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```python
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messages: Union[List[Any], List[int]]
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# List of input messages, which can be text messages (`List[Any]`, typically `List[dict]`) or token ID lists (`List[int]`).
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- `prompt` (supported only in the `v1/completions` interface)
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- `messages` (supported only in the `v1/chat/completions` interface)
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- `logprobs`: Optional[bool] = False (supported only in the `v1/chat/completions` interface)
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- `top_logprobs`: Optional[int] = None (supported only in the `v1/chat/completions` interface. An integer between 0 and 20,logprobs must be set to true if this parameter is used)
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- `frequency_penalty`: Optional[float] = 0.0
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- `max_tokens`: Optional[int] = 16
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- `presence_penalty`: Optional[float] = 0.0
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- `stream`: Optional[bool] = False
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- `stream_options`: Optional[StreamOptions] = None
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- `temperature`: Optional[float] = None
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- `top_p`: Optional[float] = None
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- `extra_body`: Optional[dict] = None (supported only in `v1/chat/completions` for configuring additional parameters, e.g., `extra_body={"enable_thinking": True}`)
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- `min_tokens`: Optional[int] = 1 (minimum number of tokens generated)
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- `reasoning_max_tokens`: Optional[int] = None (maximum number of tokens for reasoning content, defaults to the same as `max_tokens`)
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- `enable_thinking`: Optional[bool] = True (whether to enable reasoning for models that support deep thinking)
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- `repetition_penalty`: Optional[float] = None (coefficient for directly penalizing repeated token generation (>1 penalizes repetition, <1 encourages repetition))
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- `return_token_ids`: Optional[bool] = False: (whether to return token ids as a list)
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- `include_stop_str_in_output`: Optional[bool] = False: (whether to include the stop strings in output text. Defaults to False.)
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tools: Optional[List[ChatCompletionToolsParam]] = None
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# List of tool call configurations, used for enabling function calling (Function Calling) or tool usage (e.g., ReAct framework).
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> Note: For multimodal models, since the reasoning chain is enabled by default, resulting in overly long outputs, `max_tokens` can be set to the model's maximum output length or the default value can be used.
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model: Optional[str] = "default"
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# Specifies the model name or version to use, defaulting to `"default"` (which may point to the base model).
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### Return Field Differences
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frequency_penalty: Optional[float] = None
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# Frequency penalty coefficient, reducing the probability of generating the same token repeatedly (`>1.0` suppresses repetition, `<1.0` encourages repetition, default `None` disables).
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The additional return fields added by FastDeploy are as follows:
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logprobs: Optional[bool] = False
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# Whether to return the log probabilities of each generated token, used for debugging or analysis.
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- `arrival_time`: Returns the cumulative time taken for all tokens
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- `reasoning_content`: The returned result of the reasoning chain
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- `prompt_token_ids`: The token id list of the prompt
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- `completion_token_ids`: The token id list of the completion
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top_logprobs: Optional[int] = 0
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# Returns the top `top_logprobs` tokens and their log probabilities for each generated position (default `0` means no return).
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max_tokens: Optional[int] = Field(
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default=None,
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deprecated="max_tokens is deprecated in favor of the max_completion_tokens field",
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)
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# Deprecated: Maximum number of tokens to generate (recommended to use `max_completion_tokens` instead).
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max_completion_tokens: Optional[int] = None
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# Maximum number of tokens to generate (recommended alternative to `max_tokens`), no default limit (restricted by the model's context window).
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presence_penalty: Optional[float] = None
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# Presence penalty coefficient, reducing the probability of generating new topics (unseen topics) (`>1.0` suppresses new topics, `<1.0` encourages new topics, default `None` disables).
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stream: Optional[bool] = False
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# Whether to enable streaming output (return results token by token), default `False` (returns complete results at once).
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stream_options: Optional[StreamOptions] = None
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# Additional configurations for streaming output (such as chunk size, timeout, etc.), refer to the specific definition of `StreamOptions`.
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temperature: Optional[float] = None
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# Temperature coefficient, controlling generation randomness (`0.0` for deterministic generation, `>1.0` for more randomness, default `None` uses model default).
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top_p: Optional[float] = None
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# Nucleus sampling threshold, only retaining tokens whose cumulative probability exceeds `top_p` (default `None` disables).
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response_format: Optional[AnyResponseFormat] = None
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# Specifies the output format (such as JSON, XML, etc.), requires passing a predefined format configuration object.
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user: Optional[str] = None
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# User identifier, used for tracking or distinguishing requests from different users (default `None` does not pass).
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metadata: Optional[dict] = None
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# Additional metadata, used for passing custom information (such as request ID, debug markers, etc.).
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```
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### Additional Parameters Added by FastDeploy
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> Note:
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When sending requests using curl, the following parameters can be used directly;
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When sending requests using openai.Client, these parameters need to be placed in the `extra_body` parameter, e.g. `extra_body={"chat_template_kwargs": {"enable_thinking":True}, "include_stop_str_in_output": True}`.
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The following sampling parameters are supported.
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```python
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top_k: Optional[int] = None
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# Limits the consideration to the top K tokens with the highest probability at each generation step, used to control randomness (default None means no limit).
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min_p: Optional[float] = None
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# Nucleus sampling threshold, only retaining tokens whose cumulative probability exceeds min_p (default None means disabled).
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min_tokens: Optional[int] = None
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# Forces a minimum number of tokens to be generated, avoiding premature truncation (default None means no limit).
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include_stop_str_in_output: Optional[bool] = False
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# Whether to include the stop string content in the output (default False, meaning output is truncated when a stop string is encountered).
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bad_words: Optional[List[str]] = None
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# List of forbidden words (e.g., sensitive words) that the model should avoid generating (default None means no restriction).
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repetition_penalty: Optional[float] = None
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# Repetition penalty coefficient, reducing the probability of repeating already generated tokens (`>1.0` suppresses repetition, `<1.0` encourages repetition, default None means disabled).
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```
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The following extra parameters are supported:
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```python
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chat_template_kwargs: Optional[dict] = None
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# Additional parameters passed to the chat template, used for customizing dialogue formats (default None).
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reasoning_max_tokens: Optional[int] = None
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# Maximum number of tokens to generate during reasoning (e.g., CoT, chain of thought) (default None means using global max_tokens).
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structural_tag: Optional[str] = None
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# Structural tag, used to mark specific structures of generated content (such as JSON, XML, etc., default None).
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guided_json: Optional[Union[str, dict, BaseModel]] = None
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# Guides the generation of content conforming to JSON structure, can be a JSON string, dictionary, or Pydantic model (default None).
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guided_regex: Optional[str] = None
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# Guides the generation of content conforming to regular expression rules (default None means no restriction).
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guided_choice: Optional[List[str]] = None
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# Guides the generation of content selected from a specified candidate list (default None means no restriction).
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guided_grammar: Optional[str] = None
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# Guides the generation of content conforming to grammar rules (such as BNF) (default None means no restriction).
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return_token_ids: Optional[bool] = None
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# Whether to return the token IDs of the generation results instead of text (default None means return text).
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prompt_token_ids: Optional[List[int]] = None
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# Directly passes the token ID list of the prompt, skipping the text encoding step (default None means using text input).
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max_streaming_response_tokens: Optional[int] = None
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# Maximum number of tokens returned at a time during streaming output (default None means no limit).
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disable_chat_template: Optional[bool] = False
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# Whether to disable chat template rendering, using raw input directly (default False means template is enabled).
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```
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### Differences in Return Fields
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Additional return fields added by FastDeploy:
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- `arrival_time`: Cumulative time consumed for all tokens
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- `reasoning_content`: Return results of the chain of thought
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- `prompt_token_ids`: List of token IDs for the input sequence
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- `completion_token_ids`: List of token IDs for the output sequence
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Overview of return parameters:
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```python
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ChatCompletionResponse:
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id: str
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object: str = "chat.completion"
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created: int = Field(default_factory=lambda: int(time.time()))
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model: str
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choices: List[ChatCompletionResponseChoice]
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usage: UsageInfo
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ChatCompletionResponseChoice:
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index: int
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message: ChatMessage
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logprobs: Optional[LogProbs] = None
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finish_reason: Optional[Literal["stop", "length", "tool_calls", "recover_stop"]]
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ChatMessage:
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role: str
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content: str
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reasoning_content: Optional[str] = None
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prompt_token_ids: Optional[List[int]] = None
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completion_token_ids: Optional[List[int]] = None
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# Fields returned for streaming responses
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ChatCompletionStreamResponse:
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id: str
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object: str = "chat.completion.chunk"
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created: int = Field(default_factory=lambda: int(time.time()))
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model: str
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choices: List[ChatCompletionResponseStreamChoice]
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usage: Optional[UsageInfo] = None
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ChatCompletionResponseStreamChoice:
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index: int
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delta: DeltaMessage
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finish_reason: Optional[Literal["stop", "length"]] = None
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logprobs: Optional[LogProbs] = None
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finish_reason: Optional[Literal["stop", "length", "tool_calls"]] = None
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arrival_time: Optional[float] = None
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DeltaMessage:
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role: Optional[str] = None
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@@ -128,3 +245,156 @@ DeltaMessage:
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completion_token_ids: Optional[List[int]] = None
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reasoning_content: Optional[str] = None
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```
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## Completion API
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The Completion API interface is mainly used for continuation scenarios, suitable for users who have customized context input and expect the model to only output continuation content; the inference process does not add other `prompt` concatenations.
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### Sending User Requests
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Here is an example of sending a user request using the curl command:
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```bash
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curl -X POST "http://0.0.0.0:8188/v1/completions" \
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-H "Content-Type: application/json" \
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-d '{
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"prompt": "以下是一篇关于深圳文心公园的500字游记和赏析："
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}'
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```
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Here is an example of sending a user request using a Python script:
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```python
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import openai
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host = "0.0.0.0"
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port = "8170"
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client = openai.Client(base_url=f"http://{host}:{port}/v1", api_key="null")
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response = client.completions.create(
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model="default",
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prompt="以下是一篇关于深圳文心公园的500字游记和赏析：",
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stream=False,
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)
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print(response.choices[0].text)
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```
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For an explanation of the OpenAI protocol, refer to the [OpenAI Completion API](https://platform.openai.com/docs/api-reference/completions/create)。
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### Compatible OpenAI Parameters
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```python
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model: Optional[str] = "default"
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# Specifies the model name or version to use, defaulting to `"default"` (which may point to the base model).
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prompt: Union[List[int], List[List[int]], str, List[str]]
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# Input prompt, supporting multiple formats:
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# - `str`: Plain text prompt (e.g., `"Hello, how are you?"`).
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# - `List[str]`: Multiple text segments (e.g., `["User:", "Hello!", "Assistant:", "Hi!"]`).
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# - `List[int]`: Directly passes a list of token IDs (e.g., `[123, 456]`).
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# - `List[List[int]]`: List of multiple token ID lists (e.g., `[[123], [456, 789]]`).
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best_of: Optional[int] = None
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# Generates `best_of` candidate results and returns the highest-scoring one (requires `n=1`).
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frequency_penalty: Optional[float] = None
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# Frequency penalty coefficient, reducing the probability of generating the same token repeatedly (`>1.0` suppresses repetition, `<1.0` encourages repetition).
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logprobs: Optional[int] = None
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# Returns the log probabilities of each generated token, can specify the number of candidates to return.
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max_tokens: Optional[int] = None
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# Maximum number of tokens to generate (including input and output), no default limit (restricted by the model's context window).
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presence_penalty: Optional[float] = None
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# Presence penalty coefficient, reducing the probability of generating new topics (unseen topics) (`>1.0` suppresses new topics, `<1.0` encourages new topics).
|
||||
```
|
||||
|
||||
### Additional Parameters Added by FastDeploy
|
||||
|
||||
> Note:
|
||||
When sending requests using curl, the following parameters can be used directly;
|
||||
When sending requests using openai.Client, these parameters need to be placed in the `extra_body` parameter, e.g. `extra_body={"chat_template_kwargs": {"enable_thinking":True}, "include_stop_str_in_output": True}`.
|
||||
|
||||
The following sampling parameters are supported.
|
||||
```python
|
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top_k: Optional[int] = None
|
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# Limits the consideration to the top K tokens with the highest probability at each generation step, used to control randomness (default None means no limit).
|
||||
|
||||
min_p: Optional[float] = None
|
||||
# Nucleus sampling threshold, only retaining tokens whose cumulative probability exceeds min_p (default None means disabled).
|
||||
|
||||
min_tokens: Optional[int] = None
|
||||
# Forces a minimum number of tokens to be generated, avoiding premature truncation (default None means no limit).
|
||||
|
||||
include_stop_str_in_output: Optional[bool] = False
|
||||
# Whether to include the stop string content in the output (default False, meaning output is truncated when a stop string is encountered).
|
||||
|
||||
bad_words: Optional[List[str]] = None
|
||||
# List of forbidden words (e.g., sensitive words) that the model should avoid generating (default None means no restriction).
|
||||
|
||||
repetition_penalty: Optional[float] = None
|
||||
# Repetition penalty coefficient, reducing the probability of repeating already generated tokens (`>1.0` suppresses repetition, `<1.0` encourages repetition, default None means disabled).
|
||||
```
|
||||
|
||||
The following extra parameters are supported:
|
||||
```python
|
||||
guided_json: Optional[Union[str, dict, BaseModel]] = None
|
||||
# Guides the generation of content conforming to JSON structure, can be a JSON string, dictionary, or Pydantic model (default None).
|
||||
|
||||
guided_regex: Optional[str] = None
|
||||
# Guides the generation of content conforming to regular expression rules (default None means no restriction).
|
||||
|
||||
guided_choice: Optional[List[str]] = None
|
||||
# Guides the generation of content selected from a specified candidate list (default None means no restriction).
|
||||
|
||||
guided_grammar: Optional[str] = None
|
||||
# Guides the generation of content conforming to grammar rules (such as BNF) (default None means no restriction).
|
||||
|
||||
return_token_ids: Optional[bool] = None
|
||||
# Whether to return the token IDs of the generation results instead of text (default None means return text).
|
||||
|
||||
prompt_token_ids: Optional[List[int]] = None
|
||||
# Directly passes the token ID list of the prompt, skipping the text encoding step (default None means using text input).
|
||||
|
||||
max_streaming_response_tokens: Optional[int] = None
|
||||
# Maximum number of tokens returned at a time during streaming output (default None means no limit).
|
||||
```
|
||||
|
||||
### Overview of Return Parameters
|
||||
|
||||
```python
|
||||
|
||||
CompletionResponse:
|
||||
id: str
|
||||
object: str = "text_completion"
|
||||
created: int = Field(default_factory=lambda: int(time.time()))
|
||||
model: str
|
||||
choices: List[CompletionResponseChoice]
|
||||
usage: UsageInfo
|
||||
CompletionResponseChoice:
|
||||
index: int
|
||||
text: str
|
||||
prompt_token_ids: Optional[List[int]] = None
|
||||
completion_token_ids: Optional[List[int]] = None
|
||||
arrival_time: Optional[float] = None
|
||||
logprobs: Optional[int] = None
|
||||
reasoning_content: Optional[str] = None
|
||||
finish_reason: Optional[Literal["stop", "length", "tool_calls"]]
|
||||
|
||||
# Fields returned for streaming responses
|
||||
CompletionStreamResponse：
|
||||
id: str
|
||||
object: str = "text_completion"
|
||||
created: int = Field(default_factory=lambda: int(time.time()))
|
||||
model: str
|
||||
choices: List[CompletionResponseStreamChoice]
|
||||
usage: Optional[UsageInfo] = None
|
||||
CompletionResponseStreamChoice:
|
||||
index: int
|
||||
text: str
|
||||
arrival_time: float = None
|
||||
prompt_token_ids: Optional[List[int]] = None
|
||||
completion_token_ids: Optional[List[int]] = None
|
||||
logprobs: Optional[float] = None
|
||||
reasoning_content: Optional[str] = None
|
||||
finish_reason: Optional[Literal["stop", "length", "tool_calls"]] = None
|
||||
|
||||
```
|
||||
|
||||
@@ -43,7 +43,7 @@ curl -X POST "http://0.0.0.0:8192/v1/chat/completions" \
|
||||
{"type": "text", "text": "图中的文物属于哪个年代"}
|
||||
]}
|
||||
],
|
||||
"enable_thinking": true,
|
||||
"chat_template_kwargs":{"enable_thinking": true},
|
||||
"reasoning_max_tokens": 1024
|
||||
}'
|
||||
|
||||
@@ -71,7 +71,7 @@ chat_response = client.chat.completions.create(
|
||||
model="vl",
|
||||
stream=True,
|
||||
extra_body={
|
||||
"enable_thinking": True,
|
||||
"chat_template_kwargs":{"enable_thinking": True},
|
||||
"reasoning_max_tokens": 1024
|
||||
}
|
||||
)
|
||||
|
||||
@@ -110,7 +110,7 @@ curl -X POST "http://0.0.0.0:8180/v1/chat/completions" \
|
||||
{"type": "text", "text": "图中的文物属于哪个年代"}
|
||||
]}
|
||||
],
|
||||
"enable_thinking": false
|
||||
"chat_template_kwargs":{"enable_thinking": false}
|
||||
}'
|
||||
```
|
||||
|
||||
|
||||
@@ -73,7 +73,7 @@ curl -X POST "http://0.0.0.0:8180/v1/chat/completions" \
|
||||
{"type": "text", "text": "图中的文物属于哪个年代"}
|
||||
]}
|
||||
],
|
||||
"enable_thinking": false
|
||||
"chat_template_kwargs":{"enable_thinking": false}
|
||||
}'
|
||||
```
|
||||
|
||||
|
||||
@@ -21,9 +21,10 @@ python -m fastdeploy.entrypoints.openai.api_server \
|
||||
|
||||
服务部署时的命令行更多使用方式参考[参数说明](../parameters.md)。
|
||||
|
||||
## 发送用户请求
|
||||
## Chat Completion API
|
||||
FastDeploy 接口兼容 OpenAI 的 Chat Completion API，用户可以通过 OpenAI 协议发送用户请求。
|
||||
|
||||
FastDeploy 接口兼容 OpenAI 协议，可以直接使用 OpenAI 的请求方式发送用户请求。
|
||||
### 发送用户请求
|
||||
|
||||
使用 curl 命令发送用户请求示例如下：
|
||||
|
||||
@@ -71,32 +72,124 @@ for chunk in response:
|
||||
print('\n')
|
||||
```
|
||||
|
||||
关于 OpenAI 协议的说明可参考文档 [OpenAI Chat Compeltion API](https://platform.openai.com/docs/api-reference/chat/create)。
|
||||
关于 OpenAI 协议的说明可参考文档 [OpenAI Chat Completion API](https://platform.openai.com/docs/api-reference/chat/create)。
|
||||
|
||||
## 参数差异
|
||||
### 请求参数差异
|
||||
FastDeploy 与 OpenAI 协议的请求参数差异如下，其余请求参数会被忽略：
|
||||
- `prompt` (仅支持 `v1/completions` 接口)
|
||||
- `messages` (仅支持 `v1/chat/completions` 接口)
|
||||
- `logprobs`: Optional[bool] = False (仅支持 `v1/chat/completions` 接口)
|
||||
- `top_logprobs`: Optional[int] = None (仅支持 `v1/chat/completions` 接口。如果使用这个参数必须设置logprobs为True，取值大于等于0小于20)
|
||||
- `frequency_penalty`: Optional[float] = 0.0
|
||||
- `max_tokens`: Optional[int] = 16
|
||||
- `presence_penalty`: Optional[float] = 0.0
|
||||
- `stream`: Optional[bool] = False
|
||||
- `stream_options`: Optional[StreamOptions] = None
|
||||
- `temperature`: Optional[float] = None
|
||||
- `top_p`: Optional[float] = None
|
||||
- `extra_body`: Optional[dict] = None (仅在 v1/chat/compeltions 中支持，用于配置额外参数, 如 `extra_body={"enable_thinking": True}`)
|
||||
- `min_tokens`: Optional[int] = 1 最小生成的Token个数
|
||||
- `reasoning_max_tokens`: Optional[int] = None 思考内容最大Token数，默认与max_tokens一致
|
||||
- `enable_thinking`: Optional[bool] = True 支持深度思考的模型是否打开思考
|
||||
- `repetition_penalty`: Optional[float] = None: 直接对重复生成的token进行惩罚的系数（>1时惩罚重复，<1时鼓励重复）
|
||||
- `return_token_ids`: Optional[bool] = False: 是否返回 token id 列表
|
||||
- `include_stop_str_in_output`: Optional[bool] = False: 是否返回结束符
|
||||
- `top_k`: Optional[bool] = None: TopK-TopP采样参数，参考[采样说明](../features/sampling.md)
|
||||
### 兼容OpenAI 参数
|
||||
```python
|
||||
messages: Union[List[Any], List[int]]
|
||||
# 输入消息列表，可以是文本消息（`List[Any]`，通常为 `List[dict]`）或 token ID 列表（`List[int]`）。
|
||||
|
||||
> 注: 若为多模态模型 由于思考链默认打开导致输出过长，max tokens 可以设置为模型最长输出，或使用默认值。
|
||||
tools: Optional[List[ChatCompletionToolsParam]] = None
|
||||
# 工具调用配置列表，用于启用函数调用（Function Calling）或工具使用（如 ReAct 框架）。
|
||||
|
||||
model: Optional[str] = "default"
|
||||
# 指定使用的模型名称或版本，默认值为 `"default"`（可能指向基础模型）。
|
||||
|
||||
frequency_penalty: Optional[float] = None
|
||||
# 频率惩罚系数，降低重复生成相同 token 的概率（`>1.0` 抑制重复，`<1.0` 鼓励重复，默认 `None` 禁用）。
|
||||
|
||||
logprobs: Optional[bool] = False
|
||||
# 是否返回每个生成 token 的对数概率（log probabilities），用于调试或分析。
|
||||
|
||||
top_logprobs: Optional[int] = 0
|
||||
# 返回每个生成位置概率最高的 `top_logprobs` 个 token 及其对数概率（默认 `0` 表示不返回）。
|
||||
|
||||
max_tokens: Optional[int] = Field(
|
||||
default=None,
|
||||
deprecated="max_tokens is deprecated in favor of the max_completion_tokens field",
|
||||
)
|
||||
# 已弃用：生成的最大 token 数（建议改用 `max_completion_tokens`）。
|
||||
|
||||
max_completion_tokens: Optional[int] = None
|
||||
# 生成的最大 token 数（推荐替代 `max_tokens`），默认无限制（受模型上下文窗口限制）。
|
||||
|
||||
presence_penalty: Optional[float] = None
|
||||
# 存在惩罚系数，降低新主题（未出现过的话题）的生成概率（`>1.0` 抑制新话题，`<1.0` 鼓励新话题，默认 `None` 禁用）。
|
||||
|
||||
stream: Optional[bool] = False
|
||||
# 是否启用流式输出（逐 token 返回结果），默认 `False`（一次性返回完整结果）。
|
||||
|
||||
stream_options: Optional[StreamOptions] = None
|
||||
# 流式输出的额外配置（如分块大小、超时等），需参考 `StreamOptions` 的具体定义。
|
||||
|
||||
temperature: Optional[float] = None
|
||||
# 温度系数，控制生成随机性（`0.0` 确定性生成，`>1.0` 更随机，默认 `None` 使用模型默认值）。
|
||||
|
||||
top_p: Optional[float] = None
|
||||
# 核采样（nucleus sampling）阈值，只保留概率累计超过 `top_p` 的 token（默认 `None` 禁用）。
|
||||
|
||||
response_format: Optional[AnyResponseFormat] = None
|
||||
# 指定输出格式（如 JSON、XML 等），需传入预定义的格式配置对象。
|
||||
|
||||
user: Optional[str] = None
|
||||
# 用户标识符，用于跟踪或区分不同用户的请求（默认 `None` 不传递）。
|
||||
|
||||
metadata: Optional[dict] = None
|
||||
# 附加元数据，用于传递自定义信息（如请求 ID、调试标记等）。
|
||||
|
||||
```
|
||||
|
||||
### FastDeploy 增加额外参数
|
||||
|
||||
> 注：
|
||||
使用 curl 命令发送请求时， 可以直接使用以下参数；
|
||||
使用openai.Client 发送请求时，需要使用将以下参数放入 `extra_body` 参数中， 如：`extra_body={"chat_template_kwargs": {"enable_thinking":True}, "include_stop_str_in_output": True}`。
|
||||
|
||||
额外采样参数的支持如下：
|
||||
```python
|
||||
top_k: Optional[int] = None
|
||||
# 限制每一步生成时只考虑概率最高的 K 个 token，用于控制随机性（默认 None 表示不限制）。
|
||||
|
||||
min_p: Optional[float] = None
|
||||
# 核采样（nucleus sampling）阈值，只保留概率累计超过 min_p 的 token（默认 None 表示禁用）。
|
||||
|
||||
min_tokens: Optional[int] = None
|
||||
# 强制生成的最小 token 数，避免过早截断（默认 None 表示不限制）。
|
||||
|
||||
include_stop_str_in_output: Optional[bool] = False
|
||||
# 是否在输出中包含停止符（stop string）的内容（默认 False，即遇到停止符时截断输出）。
|
||||
|
||||
bad_words: Optional[List[str]] = None
|
||||
# 禁止生成的词汇列表（例如敏感词），模型会避免输出这些词（默认 None 表示不限制）。
|
||||
|
||||
repetition_penalty: Optional[float] = None
|
||||
# 重复惩罚系数，降低已生成 token 的重复概率（>1.0 抑制重复，<1.0 鼓励重复，默认 None 表示禁用）。
|
||||
```
|
||||
其他参数的支持如下：
|
||||
```python
|
||||
chat_template_kwargs: Optional[dict] = None
|
||||
# 传递给聊天模板（chat template）的额外参数，用于自定义对话格式（默认 None）。
|
||||
|
||||
reasoning_max_tokens: Optional[int] = None
|
||||
# 推理（如 CoT, 思维链）过程中生成的最大 token 数（默认 None 表示使用全局 max_tokens）。
|
||||
|
||||
structural_tag: Optional[str] = None
|
||||
# 结构化标签，用于标记生成内容的特定结构（如 JSON、XML 等，默认 None）。
|
||||
|
||||
guided_json: Optional[Union[str, dict, BaseModel]] = None
|
||||
# 引导生成符合 JSON 结构的内容，可以是 JSON 字符串、字典或 Pydantic 模型（默认 None）。
|
||||
|
||||
guided_regex: Optional[str] = None
|
||||
# 引导生成符合正则表达式规则的内容（默认 None 表示不限制）。
|
||||
|
||||
guided_choice: Optional[List[str]] = None
|
||||
# 引导生成内容从指定的候选列表中选择（默认 None 表示不限制）。
|
||||
|
||||
guided_grammar: Optional[str] = None
|
||||
# 引导生成符合语法规则（如 BNF）的内容（默认 None 表示不限制）。
|
||||
|
||||
return_token_ids: Optional[bool] = None
|
||||
# 是否返回生成结果的 token ID 而非文本（默认 None 表示返回文本）。
|
||||
|
||||
prompt_token_ids: Optional[List[int]] = None
|
||||
# 直接传入 prompt 的 token ID 列表，跳过文本编码步骤（默认 None 表示使用文本输入）。
|
||||
|
||||
max_streaming_response_tokens: Optional[int] = None
|
||||
# 流式输出时每次返回的最大 token 数（默认 None 表示不限制）。
|
||||
|
||||
disable_chat_template: Optional[bool] = False
|
||||
# 是否禁用聊天模板渲染，直接使用原始输入（默认 False 表示启用模板）。
|
||||
```
|
||||
|
||||
### 返回字段差异
|
||||
|
||||
@@ -110,16 +203,39 @@ FastDeploy 增加的返回字段如下：
|
||||
返回参数总览：
|
||||
|
||||
```python
|
||||
|
||||
ChatCompletionResponse:
|
||||
id: str
|
||||
object: str = "chat.completion"
|
||||
created: int = Field(default_factory=lambda: int(time.time()))
|
||||
model: str
|
||||
choices: List[ChatCompletionResponseChoice]
|
||||
usage: UsageInfo
|
||||
ChatCompletionResponseChoice:
|
||||
index: int
|
||||
message: ChatMessage
|
||||
logprobs: Optional[LogProbs] = None
|
||||
finish_reason: Optional[Literal["stop", "length", "tool_calls", "recover_stop"]]
|
||||
ChatMessage:
|
||||
role: str
|
||||
content: str
|
||||
reasoning_content: Optional[str] = None
|
||||
prompt_token_ids: Optional[List[int]] = None
|
||||
completion_token_ids: Optional[List[int]] = None
|
||||
|
||||
# 返回流式响应的字段
|
||||
ChatCompletionStreamResponse:
|
||||
id: str
|
||||
object: str = "chat.completion.chunk"
|
||||
created: int = Field(default_factory=lambda: int(time.time()))
|
||||
model: str
|
||||
choices: List[ChatCompletionResponseStreamChoice]
|
||||
usage: Optional[UsageInfo] = None
|
||||
ChatCompletionResponseStreamChoice:
|
||||
index: int
|
||||
delta: DeltaMessage
|
||||
finish_reason: Optional[Literal["stop", "length"]] = None
|
||||
logprobs: Optional[LogProbs] = None
|
||||
finish_reason: Optional[Literal["stop", "length", "tool_calls"]] = None
|
||||
arrival_time: Optional[float] = None
|
||||
DeltaMessage:
|
||||
role: Optional[str] = None
|
||||
@@ -128,3 +244,155 @@ DeltaMessage:
|
||||
completion_token_ids: Optional[List[int]] = None
|
||||
reasoning_content: Optional[str] = None
|
||||
```
|
||||
|
||||
## Completion API
|
||||
Completion API 接口主要用于续聊场景, 适应于用户自定义好上下文输入, 并希望模型仅输出续写内容的场景; 推理过程不会增加其他 `prompt`拼接。：
|
||||
|
||||
### 发送用户请求
|
||||
|
||||
使用 curl 命令发送用户请求示例如下：
|
||||
|
||||
```bash
|
||||
curl -X POST "http://0.0.0.0:8188/v1/completions" \
|
||||
-H "Content-Type: application/json" \
|
||||
-d '{
|
||||
"prompt": "以下是一篇关于深圳文心公园的500字游记和赏析："
|
||||
}'
|
||||
```
|
||||
|
||||
使用 Python 脚本发送用户请求示例如下：
|
||||
|
||||
```python
|
||||
import openai
|
||||
host = "0.0.0.0"
|
||||
port = "8170"
|
||||
client = openai.Client(base_url=f"http://{host}:{port}/v1", api_key="null")
|
||||
|
||||
response = client.completions.create(
|
||||
model="default",
|
||||
prompt="以下是一篇关于深圳文心公园的500字游记和赏析：",
|
||||
stream=False,
|
||||
)
|
||||
print(response.choices[0].text)
|
||||
```
|
||||
|
||||
关于 OpenAI 协议的说明可参考文档 [OpenAI Completion API](https://platform.openai.com/docs/api-reference/completions/create)。
|
||||
|
||||
### 兼容OpenAI 参数
|
||||
```python
|
||||
model: Optional[str] = "default"
|
||||
# 指定使用的模型名称或版本，默认值为 `"default"`（可能指向基础模型）。
|
||||
|
||||
prompt: Union[List[int], List[List[int]], str, List[str]]
|
||||
# 输入提示，支持多种格式：
|
||||
# - `str`: 纯文本提示（如 `"Hello, how are you?"`）。
|
||||
# - `List[str]`: 多段文本（如 `["User:", "Hello!", "Assistant:", "Hi!"]`）。
|
||||
# - `List[int]`: 直接传入 token ID 列表（如 `[123, 456]`）。
|
||||
# - `List[List[int]]`: 多段 token ID 列表（如 `[[123], [456, 789]]`）。
|
||||
|
||||
best_of: Optional[int] = None
|
||||
# 生成 `best_of` 个候选结果，然后返回其中评分最高的一个（需配合 `n=1` 使用）。
|
||||
|
||||
frequency_penalty: Optional[float] = None
|
||||
# 频率惩罚系数，降低重复生成相同 token 的概率（`>1.0` 抑制重复，`<1.0` 鼓励重复）。
|
||||
|
||||
logprobs: Optional[int] = None
|
||||
# 返回每个生成 token 的对数概率（log probabilities），可指定返回的候选数量。
|
||||
|
||||
max_tokens: Optional[int] = None
|
||||
# 生成的最大 token 数（包括输入和输出），默认无限制（受模型上下文窗口限制）。
|
||||
|
||||
presence_penalty: Optional[float] = None
|
||||
# 存在惩罚系数，降低新主题（未出现过的话题）的生成概率（`>1.0` 抑制新话题，`<1.0` 鼓励新话题）。
|
||||
```
|
||||
|
||||
### FastDeploy 增加额外参数
|
||||
|
||||
> 注：
|
||||
使用 curl 命令发送请求时， 可以直接使用以下参数；
|
||||
使用openai.Client 发送请求时，需要使用将以下参数放入 `extra_body` 参数中， 如：`extra_body={"chat_template_kwargs": {"enable_thinking":True}, "include_stop_str_in_output": True}`。
|
||||
|
||||
额外采样参数的支持如下：
|
||||
```python
|
||||
top_k: Optional[int] = None
|
||||
# 限制每一步生成时只考虑概率最高的 K 个 token，用于控制随机性（默认 None 表示不限制）。
|
||||
|
||||
min_p: Optional[float] = None
|
||||
# 核采样（nucleus sampling）阈值，只保留概率累计超过 min_p 的 token（默认 None 表示禁用）。
|
||||
|
||||
min_tokens: Optional[int] = None
|
||||
# 强制生成的最小 token 数，避免过早截断（默认 None 表示不限制）。
|
||||
|
||||
include_stop_str_in_output: Optional[bool] = False
|
||||
# 是否在输出中包含停止符（stop string）的内容（默认 False，即遇到停止符时截断输出）。
|
||||
|
||||
bad_words: Optional[List[str]] = None
|
||||
# 禁止生成的词汇列表（例如敏感词），模型会避免输出这些词（默认 None 表示不限制）。
|
||||
|
||||
repetition_penalty: Optional[float] = None
|
||||
# 重复惩罚系数，降低已生成 token 的重复概率（>1.0 抑制重复，<1.0 鼓励重复，默认 None 表示禁用）。
|
||||
```
|
||||
其他参数的支持如下：
|
||||
```python
|
||||
guided_json: Optional[Union[str, dict, BaseModel]] = None
|
||||
# 引导生成符合 JSON 结构的内容，可以是 JSON 字符串、字典或 Pydantic 模型（默认 None）。
|
||||
|
||||
guided_regex: Optional[str] = None
|
||||
# 引导生成符合正则表达式规则的内容（默认 None 表示不限制）。
|
||||
|
||||
guided_choice: Optional[List[str]] = None
|
||||
# 引导生成内容从指定的候选列表中选择（默认 None 表示不限制）。
|
||||
|
||||
guided_grammar: Optional[str] = None
|
||||
# 引导生成符合语法规则（如 BNF）的内容（默认 None 表示不限制）。
|
||||
|
||||
return_token_ids: Optional[bool] = None
|
||||
# 是否返回生成结果的 token ID 而非文本（默认 None 表示返回文本）。
|
||||
|
||||
prompt_token_ids: Optional[List[int]] = None
|
||||
# 直接传入 prompt 的 token ID 列表，跳过文本编码步骤（默认 None 表示使用文本输入）。
|
||||
|
||||
max_streaming_response_tokens: Optional[int] = None
|
||||
# 流式输出时每次返回的最大 token 数（默认 None 表示不限制）。
|
||||
```
|
||||
|
||||
### 返回参数总览
|
||||
|
||||
```python
|
||||
|
||||
CompletionResponse:
|
||||
id: str
|
||||
object: str = "text_completion"
|
||||
created: int = Field(default_factory=lambda: int(time.time()))
|
||||
model: str
|
||||
choices: List[CompletionResponseChoice]
|
||||
usage: UsageInfo
|
||||
CompletionResponseChoice:
|
||||
index: int
|
||||
text: str
|
||||
prompt_token_ids: Optional[List[int]] = None
|
||||
completion_token_ids: Optional[List[int]] = None
|
||||
arrival_time: Optional[float] = None
|
||||
logprobs: Optional[int] = None
|
||||
reasoning_content: Optional[str] = None
|
||||
finish_reason: Optional[Literal["stop", "length", "tool_calls"]]
|
||||
|
||||
# 返回流式响应的字段
|
||||
CompletionStreamResponse：
|
||||
id: str
|
||||
object: str = "text_completion"
|
||||
created: int = Field(default_factory=lambda: int(time.time()))
|
||||
model: str
|
||||
choices: List[CompletionResponseStreamChoice]
|
||||
usage: Optional[UsageInfo] = None
|
||||
CompletionResponseStreamChoice:
|
||||
index: int
|
||||
text: str
|
||||
arrival_time: float = None
|
||||
prompt_token_ids: Optional[List[int]] = None
|
||||
completion_token_ids: Optional[List[int]] = None
|
||||
logprobs: Optional[float] = None
|
||||
reasoning_content: Optional[str] = None
|
||||
finish_reason: Optional[Literal["stop", "length", "tool_calls"]] = None
|
||||
|
||||
```
|
||||
|
||||
@@ -343,28 +343,29 @@ class CompletionRequest(BaseModel):
|
||||
suffix: Optional[dict] = None
|
||||
temperature: Optional[float] = None
|
||||
top_p: Optional[float] = None
|
||||
top_k: Optional[int] = None
|
||||
min_p: Optional[float] = None
|
||||
include_stop_str_in_output: Optional[bool] = False
|
||||
user: Optional[str] = None
|
||||
|
||||
# doc: begin-completion-sampling-params
|
||||
top_k: Optional[int] = None
|
||||
min_p: Optional[float] = None
|
||||
repetition_penalty: Optional[float] = None
|
||||
stop_token_ids: Optional[List[int]] = Field(default_factory=list)
|
||||
min_tokens: Optional[int] = None
|
||||
return_token_ids: Optional[bool] = None
|
||||
max_streaming_response_tokens: Optional[int] = None
|
||||
prompt_token_ids: Optional[List[int]] = None
|
||||
include_stop_str_in_output: Optional[bool] = False
|
||||
bad_words: Optional[List[str]] = None
|
||||
# doc: end-completion-sampling-params
|
||||
|
||||
# doc: start-completion-extra-params
|
||||
response_format: Optional[AnyResponseFormat] = None
|
||||
guided_json: Optional[Union[str, dict, BaseModel]] = None
|
||||
guided_regex: Optional[str] = None
|
||||
guided_choice: Optional[list[str]] = None
|
||||
guided_grammar: Optional[str] = None
|
||||
|
||||
# doc: begin-completion-sampling-params
|
||||
repetition_penalty: Optional[float] = None
|
||||
stop_token_ids: Optional[List[int]] = Field(default_factory=list)
|
||||
|
||||
# doc: end-completion-sampling-params
|
||||
max_streaming_response_tokens: Optional[int] = None
|
||||
return_token_ids: Optional[bool] = None
|
||||
prompt_token_ids: Optional[List[int]] = None
|
||||
# doc: end-completion-extra-params
|
||||
|
||||
def to_dict_for_infer(self, request_id=None, prompt=None):
|
||||
"""
|
||||
@@ -477,33 +478,34 @@ class ChatCompletionRequest(BaseModel):
|
||||
stream_options: Optional[StreamOptions] = None
|
||||
temperature: Optional[float] = None
|
||||
top_p: Optional[float] = None
|
||||
top_k: Optional[int] = None
|
||||
min_p: Optional[float] = None
|
||||
user: Optional[str] = None
|
||||
metadata: Optional[dict] = None
|
||||
response_format: Optional[AnyResponseFormat] = None
|
||||
|
||||
return_token_ids: Optional[bool] = None
|
||||
prompt_token_ids: Optional[List[int]] = None
|
||||
disable_chat_template: Optional[bool] = False
|
||||
# doc: begin-chat-completion-sampling-params
|
||||
top_k: Optional[int] = None
|
||||
min_p: Optional[float] = None
|
||||
min_tokens: Optional[int] = None
|
||||
enable_thinking: Optional[bool] = None
|
||||
reasoning_max_tokens: Optional[int] = None
|
||||
max_streaming_response_tokens: Optional[int] = None
|
||||
include_stop_str_in_output: Optional[bool] = False
|
||||
bad_words: Optional[List[str]] = None
|
||||
repetition_penalty: Optional[float] = None
|
||||
stop_token_ids: Optional[List[int]] = Field(default_factory=list)
|
||||
# doc: end-chat-completion-sampling-params
|
||||
|
||||
response_format: Optional[AnyResponseFormat] = None
|
||||
# doc: start-completion-extra-params
|
||||
chat_template_kwargs: Optional[dict] = None
|
||||
reasoning_max_tokens: Optional[int] = None
|
||||
structural_tag: Optional[str] = None
|
||||
guided_json: Optional[Union[str, dict, BaseModel]] = None
|
||||
guided_regex: Optional[str] = None
|
||||
guided_choice: Optional[list[str]] = None
|
||||
guided_grammar: Optional[str] = None
|
||||
structural_tag: Optional[str] = None
|
||||
|
||||
# doc: begin-chat-completion-sampling-params
|
||||
repetition_penalty: Optional[float] = None
|
||||
stop_token_ids: Optional[List[int]] = Field(default_factory=list)
|
||||
|
||||
# doc: end-chat-completion-sampling-params
|
||||
return_token_ids: Optional[bool] = None
|
||||
prompt_token_ids: Optional[List[int]] = None
|
||||
max_streaming_response_tokens: Optional[int] = None
|
||||
disable_chat_template: Optional[bool] = False
|
||||
# doc: end-chat-completion-extra-params
|
||||
|
||||
def to_dict_for_infer(self, request_id=None):
|
||||
"""
|
||||
|
||||
@@ -129,11 +129,11 @@ class OpenAIServingChat:
|
||||
if request.max_streaming_response_tokens is not None
|
||||
else (request.metadata or {}).get("max_streaming_response_tokens", 1)
|
||||
) # dierctly passed & passed in metadata
|
||||
enable_thinking = (
|
||||
request.enable_thinking
|
||||
if request.enable_thinking is not None
|
||||
else (request.metadata or {}).get("enable_thinking")
|
||||
)
|
||||
|
||||
enable_thinking = request.chat_template_kwargs.get("enable_thinking") if request.chat_template_kwargs else None
|
||||
if enable_thinking is None:
|
||||
enable_thinking = request.metadata.get("enable_thinking") if request.metadata else None
|
||||
|
||||
include_stop_str_in_output = request.include_stop_str_in_output
|
||||
|
||||
stream_options = request.stream_options
|
||||
@@ -330,11 +330,10 @@ class OpenAIServingChat:
|
||||
"""
|
||||
created_time = int(time.time())
|
||||
final_res = None
|
||||
enable_thinking = (
|
||||
request.enable_thinking
|
||||
if request.enable_thinking is not None
|
||||
else (request.metadata or {}).get("enable_thinking")
|
||||
)
|
||||
enable_thinking = request.chat_template_kwargs.get("enable_thinking") if request.chat_template_kwargs else None
|
||||
if enable_thinking is None:
|
||||
enable_thinking = request.metadata.get("enable_thinking") if request.metadata else None
|
||||
|
||||
include_stop_str_in_output = request.include_stop_str_in_output
|
||||
|
||||
try:
|
||||
|
||||
@@ -493,7 +493,7 @@ def test_chat_with_thinking(openai_client, capsys):
|
||||
temperature=1,
|
||||
stream=False,
|
||||
max_tokens=10,
|
||||
extra_body={"enable_thinking": True},
|
||||
extra_body={"chat_template_kwargs": {"enable_thinking": True}},
|
||||
)
|
||||
assert response.choices[0].message.reasoning_content is not None
|
||||
|
||||
@@ -504,7 +504,7 @@ def test_chat_with_thinking(openai_client, capsys):
|
||||
temperature=1,
|
||||
stream=False,
|
||||
max_tokens=10,
|
||||
extra_body={"enable_thinking": False},
|
||||
extra_body={"chat_template_kwargs": {"enable_thinking": False}},
|
||||
)
|
||||
assert response.choices[0].message.reasoning_content is None
|
||||
|
||||
@@ -514,7 +514,11 @@ def test_chat_with_thinking(openai_client, capsys):
|
||||
model="default",
|
||||
messages=[{"role": "user", "content": "Explain gravity in a way that a five-year-old child can understand."}],
|
||||
temperature=1,
|
||||
extra_body={"enable_thinking": True, "reasoning_max_tokens": reasoning_max_tokens, "return_token_ids": True},
|
||||
extra_body={
|
||||
"chat_template_kwargs": {"enable_thinking": True},
|
||||
"reasoning_max_tokens": reasoning_max_tokens,
|
||||
"return_token_ids": True,
|
||||
},
|
||||
stream=True,
|
||||
max_tokens=10,
|
||||
)
|
||||
|
||||
Reference in New Issue
Block a user