OYhfddlmZddlmZmZmZmZmZmZddl m Z ddl Z ddl m Z ddlmZmZmZmZmZddlmZmZmZdd lmZdd lmZmZdd lmZmZdd l m!Z!m"Z"dd l#m$Z$ddl%m&Z&ddl'm(Z(ddl)m*Z*ddl+m,Z,ddl-m.Z.ddl/m0Z0ddl1m2Z2ddl3m4Z4ddgZ5GddeZ6GddeZ7GddZ8GddZ9GddZ:Gd d!Z;y)") annotations)DictListUnionIterableOptionaloverload)LiteralN)_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 CompletionsAsyncCompletionsceZdZed dZeddZeeeeeeeeeeeeeeeeeeeeeddded ddZeeeeeeeeeeeeeeeeeeeeddded dd Zeeeeeeeeeeeeeeeeeeeeddded dd Ze ddggd eeeeeeeeeeeeeeeeeeeeddded dd Zy)r%ct|SN)CompletionsWithRawResponseselfs `/var/www/feuerwehr-webapp/venv/lib/python3.12/site-packages/openai/resources/chat/completions.pywith_raw_responsezCompletions.with_raw_response%s )$//ct|Sr)) CompletionsWithStreamingResponser+s r-with_streaming_responsez#Completions.with_streaming_response)s /55r/Nfrequency_penalty function_call functions logit_biaslogprobs max_tokensnparallel_tool_callspresence_penaltyresponse_formatseedstopstreamstream_options temperature tool_choicetools top_logprobstop_puser extra_headers extra_query extra_bodytimeoutmessagesmodelcya 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-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_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. 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,rLrMr4r5r6r7r8r9r:r;r<r=r>r?r@rArBrCrDrErFrGrHrIrJrKs r-createzCompletions.create-\ r/r4r5r6r7r8r9r:r;r<r=r>r?rArBrCrDrErFrGrHrIrJrKcya 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-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_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. 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 NrPr,rLrMr@r4r5r6r7r8r9r:r;r<r=r>r?rArBrCrDrErFrGrHrIrJrKs r-rRzCompletions.createrSr/cyrVrPrWs r-rRzCompletions.createrSr/rLrMr@c |jdtid|d|d|d|d|d|d|d |d | d | d | d | d| d|d|d|d||||||dtjt ||||t |xsdt tSNz/chat/completionsrLrMr4r5r6r7r8r9r:r;r<r=r>r?r@rArB)rCrDrErFrG)rHrIrJrKF)bodyoptionscast_tor@ stream_cls)_postrrCompletionCreateParamsrrrr rQs r-rRzCompletions.create=sBBzz  U():$]     !* !**+>'(8&DDf %n!"";#$$/"$0" -0)??36)+Q[el#?U12E# # r/)returnr*)rbr16rL$Iterable[ChatCompletionMessageParam]rMUnion[str, ChatModel]r4Optional[float] | NotGivenr50completion_create_params.FunctionCall | NotGivenr66Iterable[completion_create_params.Function] | NotGivenr7#Optional[Dict[str, int]] | NotGivenr8Optional[bool] | NotGivenr9Optional[int] | NotGivenr:rkr;bool | NotGivenr<rfr=2completion_create_params.ResponseFormat | NotGivenr>rkr?*Union[Optional[str], List[str]] | NotGivenr@z#Optional[Literal[False]] | NotGivenrA5Optional[ChatCompletionStreamOptionsParam] | NotGivenrBrfrC.ChatCompletionToolChoiceOptionParam | NotGivenrD,Iterable[ChatCompletionToolParam] | NotGivenrErkrFrfrGstr | NotGivenrHHeaders | NonerI Query | NonerJ Body | NonerK'float | httpx.Timeout | None | NotGivenrbr)6rLrdrMrer@ Literal[True]r4rfr5rgr6rhr7rir8rjr9rkr:rkr;rlr<rfr=rmr>rkr?rnrArorBrfrCrprDrqrErkrFrfrGrrrHrsrIrtrJrurKrvrbzStream[ChatCompletionChunk])6rLrdrMrer@boolr4rfr5rgr6rhr7rir8rjr9rkr:rkr;rlr<rfr=rmr>rkr?rnrArorBrfrCrprDrqrErkrFrfrGrrrHrsrIrtrJrurKrvrb,ChatCompletion | Stream[ChatCompletionChunk])6rLrdrMrer4rfr5rgr6rhr7rir8rjr9rkr:rkr;rlr<rfr=rmr>rkr?rnr@3Optional[Literal[False]] | Literal[True] | NotGivenrArorBrfrCrprDrqrErkrFrfrGrrrHrsrIrtrJrurKrvrbry __name__ __module__ __qualname__rr.r2r r rRrrPr/r-r%r%$sx0066 9BJSLU:C.7/8&//87@NW)2;D6?PY2;FO>G1:,5()-$("&;D=m 7m % m 6 m H m Jm 8m ,m -m  $m -m 5m Lm 'm 9!m "4#m $N%m &0'm (D)m *<+m ,/-m .*/m 01m 6&7m 8"9m : ;m <9=m > ?m m ^9BJSLU:C.7/8&//87@NW)2;DPY2;FO>G1:,5()-$("&;D=m 7m % m  m 6 m Hm Jm 8m ,m -m  $m -m 5m Lm '!m "9#m $N%m &0'm (D)m *<+m ,/-m .*/m 01m 6&7m 8"9m : ;m <9=m > %?m m ^9BJSLU:C.7/8&//87@NW)2;DPY2;FO>G1:,5()-$("&;D=m 7m % m  m 6 m Hm Jm 8m ,m -m  $m -m 5m Lm '!m "9#m $N%m &0'm (D)m *<+m ,/-m .*/m 01m 6&7m 8"9m : ;m <9=m > 6?m m ^J(*IJ 9BJSLU:C.7/8&//87@NW)2;DFOPY2;FO>G1:,5()-$("&;D=C 7C % C 6 C H C JC 8C ,C -C  $C -C 5C LC 'C 9!C "D#C $N%C &0'C (D)C *<+C ,/-C .*/C 01C 6&7C 8"9C : ;C <9=C > 6?C KC r/ceZdZed dZeddZeeeeeeeeeeeeeeeeeeeeeddded ddZeeeeeeeeeeeeeeeeeeeeddded dd Zeeeeeeeeeeeeeeeeeeeeddded dd Ze ddggd eeeeeeeeeeeeeeeeeeeeddded dd Zy)r&ct|Sr))AsyncCompletionsWithRawResponser+s r-r.z"AsyncCompletions.with_raw_responses .t44r/ct|Sr))%AsyncCompletionsWithStreamingResponser+s r-r2z(AsyncCompletions.with_streaming_responses 4T::r/Nr3rLrMc KywrOrPrQs r-rRzAsyncCompletions.create \ rTc KywrVrPrWs r-rRzAsyncCompletions.create=rrc KywrVrPrWs r-rRzAsyncCompletions.createrrrYc FK|jdtid|d|d|d|d|d|d|d |d | d | d | d | d| d|d|d|d||||||dtjd{t ||||t |xsdt td{S757wr[)r`rrrarrrr rQs r-rRzAsyncCompletions.creates[BZZ ,U():$]     !* !**+>'(8&DDf %n!"";#$$/"$0" -0)??36)+Q[el#?U"#67E # # # # s$A%B!'B (0B!BB!B!)rbr)rbrrc)6rLrdrMrer@rwr4rfr5rgr6rhr7rir8rjr9rkr:rkr;rlr<rfr=rmr>rkr?rnrArorBrfrCrprDrqrErkrFrfrGrrrHrsrIrtrJrurKrvrbz AsyncStream[ChatCompletionChunk])6rLrdrMrer@rxr4rfr5rgr6rhr7rir8rjr9rkr:rkr;rlr<rfr=rmr>rkr?rnrArorBrfrCrprDrqrErkrFrfrGrrrHrsrIrtrJrurKrvrb1ChatCompletion | AsyncStream[ChatCompletionChunk])6rLrdrMrer4rfr5rgr6rhr7rir8rjr9rkr:rkr;rlr<rfr=rmr>rkr?rnr@rzrArorBrfrCrprDrqrErkrFrfrGrrrHrsrIrtrJrurKrvrbrr{rPr/r-r&r&sx55;; 9BJSLU:C.7/8&//87@NW)2;D6?PY2;FO>G1:,5()-$("&;D=m 7m % m 6 m H m Jm 8m ,m -m  $m -m 5m Lm 'm 9!m "4#m $N%m &0'm (D)m *<+m ,/-m .*/m 01m 6&7m 8"9m : ;m <9=m > ?m m ^9BJSLU:C.7/8&//87@NW)2;DPY2;FO>G1:,5()-$("&;D=m 7m % m  m 6 m Hm Jm 8m ,m -m  $m -m 5m Lm '!m "9#m $N%m &0'm (D)m *<+m ,/-m .*/m 01m 6&7m 8"9m : ;m <9=m > *?m m ^9BJSLU:C.7/8&//87@NW)2;DPY2;FO>G1:,5()-$("&;D=m 7m % m  m 6 m Hm Jm 8m ,m -m  $m -m 5m Lm '!m "9#m $N%m &0'm (D)m *<+m ,/-m .*/m 01m 6&7m 8"9m : ;m <9=m > ;?m m ^J(*IJ 9BJSLU:C.7/8&//87@NW)2;DFOPY2;FO>G1:,5()-$("&;D=C 7C % C 6 C H C JC 8C ,C -C  $C -C 5C LC 'C 9!C "D#C $N%C &0'C (D)C *<+C ,/-C .*/C 01C 6&7C 8"9C : ;C <9=C > ;?C KC r/ceZdZddZy)r*cZ||_tj|j|_yr)) _completionsr to_raw_response_wrapperrRr, completionss r-__init__z#CompletionsWithRawResponse.__init__s%'&>>     r/Nrr%rbNoner|r}r~rrPr/r-r*r* r/r*ceZdZddZy)rcZ||_tj|j|_yr))rr async_to_raw_response_wrapperrRrs r-rz(AsyncCompletionsWithRawResponse.__init__s%'&DD     r/Nrr&rbrrrPr/r-rrrr/rceZdZddZy)r1cF||_t|j|_yr))rrrRrs r-rz)CompletionsWithStreamingResponse.__init__s'2     r/NrrrPr/r-r1r1rr/r1ceZdZddZy)rcF||_t|j|_yr))rrrRrs r-rz.AsyncCompletionsWithStreamingResponse.__init__s'8     r/NrrrPr/r-rrrr/r)< __future__rtypingrrrrrr typing_extensionsr httpxr _typesr rrrr_utilsrrr_compatr _resourcerr _responserr _streamingrr types.chatr _base_clientrtypes.chat_modelrtypes.chat.chat_completionr types.chat.chat_completion_chunkr %types.chat.chat_completion_tool_paramr!(types.chat.chat_completion_message_paramr"/types.chat.chat_completion_stream_options_paramr#3types.chat.chat_completion_tool_choice_option_paramr$__all__r%r&r*rr1rrPr/r-rs#BB% ?? ':Y-2*8CLR_f , -]  /]  @]  ']  @        r/