a f2@sddlmZddlZddlmZmZmZmZmZm Z ddl m Z ddl Z ddl Z ddlmZddlmZmZmZmZmZddlmZmZmZdd lmZdd lmZmZdd lm Z m!Z!dd l"m#Z#m$Z$dd l%m&Z&ddl'm(Z(ddl)m*Z*ddl+m,Z,ddl-m.Z.ddl/m0Z0ddl1m2Z2ddl3m4Z4ddl5m6Z6ddgZ7GdddeZ8GdddeZ9GdddZ:GdddZ;GdddZdS)') annotationsN)DictListUnionIterableOptionaloverload)Literal)_legacy_response) NOT_GIVENBodyQueryHeadersNotGiven) required_argsmaybe_transformasync_maybe_transform)cached_property)SyncAPIResourceAsyncAPIResource)to_streamed_response_wrapper"async_to_streamed_response_wrapper)Stream AsyncStream)completion_create_params)make_request_options) ChatModel)ChatCompletion)ChatCompletionChunk)ChatCompletionToolParam)ChatCompletionMessageParam) ChatCompletionStreamOptionsParam)#ChatCompletionToolChoiceOptionParam CompletionsAsyncCompletionsc@s2eZdZeddddZeddddZeeeeeeeeeeeeeeeeeeeeeeddded d d d d ddddddd ddddddd dddd ddddddd d!d"Zeeeeeeeeeeeeeeeeeeeeeddded#d d d$d d ddddddd dddddd dddd dddddd%d&d'd"Zeeeeeeeeeeeeeeeeeeeeeddded#d d d(d d ddddddd dddddd dddd dddddd)d&d*d"Ze d+d,ggd-eeeeeeeeeeeeeeeeeeeeeddded d d d d ddddddd ddddd.dd dddd dddddd)d d/d"ZdS)0r$CompletionsWithRawResponsereturncCst|SN)r&selfr,Z/var/www/ai-form-bot/venv/lib/python3.9/site-packages/openai/resources/chat/completions.pywith_raw_response%szCompletions.with_raw_response CompletionsWithStreamingResponsecCst|Sr))r/r*r,r,r-with_streaming_response)sz#Completions.with_streaming_responseNfrequency_penalty function_call functions logit_biaslogprobs max_tokensnparallel_tool_callspresence_penaltyresponse_formatseed service_tierstopstreamstream_options temperature tool_choicetools top_logprobstop_puser extra_headers extra_query extra_bodytimeout$Iterable[ChatCompletionMessageParam]Union[str, ChatModel]Optional[float] | NotGiven0completion_create_params.FunctionCall | NotGiven6Iterable[completion_create_params.Function] | NotGiven#Optional[Dict[str, int]] | NotGivenOptional[bool] | NotGivenOptional[int] | NotGivenbool | NotGiven2completion_create_params.ResponseFormat | NotGiven/Optional[Literal['auto', 'default']] | NotGiven*Union[Optional[str], List[str]] | NotGiven#Optional[Literal[False]] | NotGiven5Optional[ChatCompletionStreamOptionsParam] | NotGiven.ChatCompletionToolChoiceOptionParam | NotGiven,Iterable[ChatCompletionToolParam] | NotGivenstr | NotGivenHeaders | None Query | None Body | None'float | httpx.Timeout | None | NotGivenrmessagesmodelr2r3r4r5r6r7r8r9r:r;r<r=r>r?r@rArBrCrDrErFrGrHrIrJr(cCsdSa$ Creates a model response for the given chat conversation. Args: messages: A list of messages comprising the conversation so far. [Example Python code](https://cookbook.openai.com/examples/how_to_format_inputs_to_chatgpt_models). model: ID of the model to use. See the [model endpoint compatibility](https://platform.openai.com/docs/models/model-endpoint-compatibility) table for details on which models work with the Chat API. frequency_penalty: Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim. [See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation/parameter-details) function_call: Deprecated in favor of `tool_choice`. Controls which (if any) function is called by the model. `none` means the model will not call a function and instead generates a message. `auto` means the model can pick between generating a message or calling a function. Specifying a particular function via `{"name": "my_function"}` forces the model to call that function. `none` is the default when no functions are present. `auto` is the default if functions are present. functions: Deprecated in favor of `tools`. A list of functions the model may generate JSON inputs for. logit_bias: Modify the likelihood of specified tokens appearing in the completion. Accepts a JSON object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token. logprobs: Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the `content` of `message`. max_tokens: The maximum number of [tokens](/tokenizer) that can be generated in the chat completion. The total length of input tokens and generated tokens is limited by the model's context length. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens. n: How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep `n` as `1` to minimize costs. parallel_tool_calls: Whether to enable [parallel function calling](https://platform.openai.com/docs/guides/function-calling/parallel-function-calling) during tool use. presence_penalty: Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics. [See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation/parameter-details) response_format: An object specifying the format that the model must output. Compatible with [GPT-4o](https://platform.openai.com/docs/models/gpt-4o), [GPT-4o mini](https://platform.openai.com/docs/models/gpt-4o-mini), [GPT-4 Turbo](https://platform.openai.com/docs/models/gpt-4-and-gpt-4-turbo) and all GPT-3.5 Turbo models newer than `gpt-3.5-turbo-1106`. Setting to `{ "type": "json_schema", "json_schema": {...} }` enables Structured Outputs which guarantees the model will match your supplied JSON schema. Learn more in the [Structured Outputs guide](https://platform.openai.com/docs/guides/structured-outputs). Setting to `{ "type": "json_object" }` enables JSON mode, which guarantees the message the model generates is valid JSON. **Important:** when using JSON mode, you **must** also instruct the model to produce JSON yourself via a system or user message. Without this, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly "stuck" request. Also note that the message content may be partially cut off if `finish_reason="length"`, which indicates the generation exceeded `max_tokens` or the conversation exceeded the max context length. seed: This feature is in Beta. If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same `seed` and parameters should return the same result. Determinism is not guaranteed, and you should refer to the `system_fingerprint` response parameter to monitor changes in the backend. service_tier: Specifies the latency tier to use for processing the request. This parameter is relevant for customers subscribed to the scale tier service: - If set to 'auto', the system will utilize scale tier credits until they are exhausted. - If set to 'default', the request will be processed using the default service tier with a lower uptime SLA and no latency guarentee. - When not set, the default behavior is 'auto'. When this parameter is set, the response body will include the `service_tier` utilized. stop: Up to 4 sequences where the API will stop generating further tokens. stream: If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) as they become available, with the stream terminated by a `data: [DONE]` message. [Example Python code](https://cookbook.openai.com/examples/how_to_stream_completions). stream_options: Options for streaming response. Only set this when you set `stream: true`. temperature: What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. We generally recommend altering this or `top_p` but not both. tool_choice: Controls which (if any) tool is called by the model. `none` means the model will not call any tool and instead generates a message. `auto` means the model can pick between generating a message or calling one or more tools. `required` means the model must call one or more tools. Specifying a particular tool via `{"type": "function", "function": {"name": "my_function"}}` forces the model to call that tool. `none` is the default when no tools are present. `auto` is the default if tools are present. tools: A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for. A max of 128 functions are supported. top_logprobs: An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability. `logprobs` must be set to `true` if this parameter is used. top_p: An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or `temperature` but not both. user: A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices/end-user-ids). 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 Nr,r+rarbr2r3r4r5r6r7r8r9r:r;r<r=r>r?r@rArBrCrDrErFrGrHrIrJr,r,r-create-sCzCompletions.creater2r3r4r5r6r7r8r9r:r;r<r=r>r@rArBrCrDrErFrGrHrIrJ Literal[True]zStream[ChatCompletionChunk]rarbr?r2r3r4r5r6r7r8r9r:r;r<r=r>r@rArBrCrDrErFrGrHrIrJr(cCsdSa$ Creates a model response for the given chat conversation. Args: messages: A list of messages comprising the conversation so far. [Example Python code](https://cookbook.openai.com/examples/how_to_format_inputs_to_chatgpt_models). model: ID of the model to use. See the [model endpoint compatibility](https://platform.openai.com/docs/models/model-endpoint-compatibility) table for details on which models work with the Chat API. stream: If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) as they become available, with the stream terminated by a `data: [DONE]` message. [Example Python code](https://cookbook.openai.com/examples/how_to_stream_completions). frequency_penalty: Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim. [See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation/parameter-details) function_call: Deprecated in favor of `tool_choice`. Controls which (if any) function is called by the model. `none` means the model will not call a function and instead generates a message. `auto` means the model can pick between generating a message or calling a function. Specifying a particular function via `{"name": "my_function"}` forces the model to call that function. `none` is the default when no functions are present. `auto` is the default if functions are present. functions: Deprecated in favor of `tools`. A list of functions the model may generate JSON inputs for. logit_bias: Modify the likelihood of specified tokens appearing in the completion. Accepts a JSON object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token. logprobs: Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the `content` of `message`. max_tokens: The maximum number of [tokens](/tokenizer) that can be generated in the chat completion. The total length of input tokens and generated tokens is limited by the model's context length. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens. n: How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep `n` as `1` to minimize costs. parallel_tool_calls: Whether to enable [parallel function calling](https://platform.openai.com/docs/guides/function-calling/parallel-function-calling) during tool use. presence_penalty: Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics. [See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation/parameter-details) response_format: An object specifying the format that the model must output. Compatible with [GPT-4o](https://platform.openai.com/docs/models/gpt-4o), [GPT-4o mini](https://platform.openai.com/docs/models/gpt-4o-mini), [GPT-4 Turbo](https://platform.openai.com/docs/models/gpt-4-and-gpt-4-turbo) and all GPT-3.5 Turbo models newer than `gpt-3.5-turbo-1106`. Setting to `{ "type": "json_schema", "json_schema": {...} }` enables Structured Outputs which guarantees the model will match your supplied JSON schema. Learn more in the [Structured Outputs guide](https://platform.openai.com/docs/guides/structured-outputs). Setting to `{ "type": "json_object" }` enables JSON mode, which guarantees the message the model generates is valid JSON. **Important:** when using JSON mode, you **must** also instruct the model to produce JSON yourself via a system or user message. Without this, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly "stuck" request. Also note that the message content may be partially cut off if `finish_reason="length"`, which indicates the generation exceeded `max_tokens` or the conversation exceeded the max context length. seed: This feature is in Beta. If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same `seed` and parameters should return the same result. Determinism is not guaranteed, and you should refer to the `system_fingerprint` response parameter to monitor changes in the backend. service_tier: Specifies the latency tier to use for processing the request. This parameter is relevant for customers subscribed to the scale tier service: - If set to 'auto', the system will utilize scale tier credits until they are exhausted. - If set to 'default', the request will be processed using the default service tier with a lower uptime SLA and no latency guarentee. - When not set, the default behavior is 'auto'. When this parameter is set, the response body will include the `service_tier` utilized. stop: Up to 4 sequences where the API will stop generating further tokens. stream_options: Options for streaming response. Only set this when you set `stream: true`. temperature: What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. We generally recommend altering this or `top_p` but not both. tool_choice: Controls which (if any) tool is called by the model. `none` means the model will not call any tool and instead generates a message. `auto` means the model can pick between generating a message or calling one or more tools. `required` means the model must call one or more tools. Specifying a particular tool via `{"type": "function", "function": {"name": "my_function"}}` forces the model to call that tool. `none` is the default when no tools are present. `auto` is the default if tools are present. tools: A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for. A max of 128 functions are supported. top_logprobs: An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability. `logprobs` must be set to `true` if this parameter is used. top_p: An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or `temperature` but not both. user: A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices/end-user-ids). 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 Nr,r+rarbr?r2r3r4r5r6r7r8r9r:r;r<r=r>r@rArBrCrDrErFrGrHrIrJr,r,r-resCboolz,ChatCompletion | Stream[ChatCompletionChunk]cCsdSrir,rjr,r,r-resCrarbrarbr?3Optional[Literal[False]] | Literal[True] | NotGivencCsjt| |jdt||||||||| | | | | ||||||||||dtjt||||dt|p^dttdSNz/chat/completions)rarbr2r3r4r5r6r7r8r9r:r;r<r=r>r?r@rArBrCrDrErF)rGrHrIrJF)bodyoptionsZcast_tor?Z stream_cls) validate_response_format_postrrCompletionCreateParamsrrrrrdr,r,r-reysJ"ݩ __name__ __module__ __qualname__rr.r0rr rerr,r,r,r-r$$sJDJDJDc@s2eZdZeddddZeddddZeeeeeeeeeeeeeeeeeeeeeeddded d d d d ddddddd ddddddd dddd ddddddd d!d"Zeeeeeeeeeeeeeeeeeeeeeddded#d d d$d d ddddddd dddddd dddd dddddd%d&d'd"Zeeeeeeeeeeeeeeeeeeeeeddded#d d d(d d ddddddd dddddd dddd dddddd)d&d*d"Ze d+d,ggd-eeeeeeeeeeeeeeeeeeeeeddded d d d d ddddddd ddddd.dd dddd dddddd)d d/d"ZdS)0r%AsyncCompletionsWithRawResponser'cCst|Sr))rxr*r,r,r-r.sz"AsyncCompletions.with_raw_response%AsyncCompletionsWithStreamingResponsecCst|Sr))ryr*r,r,r-r0sz(AsyncCompletions.with_streaming_responseNr1rKrLrMrNrOrPrQrRrSrTrUrVrWrXrYrZr[r\r]r^r_rr`csdSrcr,rdr,r,r-resCzAsyncCompletions.createrfrgz AsyncStream[ChatCompletionChunk]rhcsdSrir,rjr,r,r-resCrkz1ChatCompletion | AsyncStream[ChatCompletionChunk]csdSrir,rjr,r,r-reTsCrarbrlrmcsvt| |jdt||||||||| | | | | ||||||||||dtjIdHt||||dt|pddttdIdHSrn) rqrrrrrsrrrrrdr,r,r-resJ"rtr,r,r,r-r%sJDJDJDc@seZdZdddddZdS)r&r$None completionsr(cCs||_t|j|_dSr)) _completionsr Zto_raw_response_wrapperrer+r|r,r,r-__init__csz#CompletionsWithRawResponse.__init__Nrurvrwrr,r,r,r-r&bsr&c@seZdZdddddZdS)rxr%rzr{cCs||_t|j|_dSr))r}r Zasync_to_raw_response_wrapperrer~r,r,r-rlsz(AsyncCompletionsWithRawResponse.__init__Nrr,r,r,r-rxksrxc@seZdZdddddZdS)r/r$rzr{cCs||_t|j|_dSr))r}rrer~r,r,r-rusz)CompletionsWithStreamingResponse.__init__Nrr,r,r,r-r/tsr/c@seZdZdddddZdS)ryr%rzr{cCs||_t|j|_dSr))r}rrer~r,r,r-r~sz.AsyncCompletionsWithStreamingResponse.__init__Nrr,r,r,r-ry}sryobjectrz)r;r(cCs"t|rt|tjrtddS)NzzYou tried to pass a `BaseModel` class to `chat.completions.create()`; You must use `beta.chat.completions.parse()` instead)inspectisclass issubclasspydanticZ BaseModel TypeError)r;r,r,r-rqsrq)? __future__rrtypingrrrrrrtyping_extensionsr Zhttpxrr _typesr r rrrZ_utilsrrr_compatrZ _resourcerr _responserrZ _streamingrrZ types.chatrZ _base_clientrZtypes.chat_modelrZtypes.chat.chat_completionrZ types.chat.chat_completion_chunkrZ%types.chat.chat_completion_tool_paramr Z(types.chat.chat_completion_message_paramr!Z/types.chat.chat_completion_stream_options_paramr"Z3types.chat.chat_completion_tool_choice_option_paramr#__all__r$r%r&rxr/ryrqr,r,r,r-sN              $$