jf"xddlZddlmZmZmZddlmZmZddlm Z ddl m Z m Z Gdde Z Gdd e Zy) N)AnyListOptional)AsyncCallbackManagerForLLMRunCallbackManagerForLLMRun) LLMResult)OpenAI OpenAIChatc eZdZUdZeeeed<dZee ed<e de fdZ d deedeeed ee d e def fd Z d deedeeed eed e def fd ZxZS)PromptLayerOpenAIaSPromptLayer OpenAI large language models. To use, you should have the ``openai`` and ``promptlayer`` python package installed, and the environment variable ``OPENAI_API_KEY`` and ``PROMPTLAYER_API_KEY`` set with your openAI API key and promptlayer key respectively. All parameters that can be passed to the OpenAI LLM can also be passed here. The PromptLayerOpenAI LLM adds two optional parameters: ``pl_tags``: List of strings to tag the request with. ``return_pl_id``: If True, the PromptLayer request ID will be returned in the ``generation_info`` field of the ``Generation`` object. Example: .. code-block:: python from langchain_community.llms import PromptLayerOpenAI openai = PromptLayerOpenAI(model_name="gpt-3.5-turbo-instruct") pl_tagsF return_pl_idreturncy)NF)clss u/var/www/html/Fitness-lenito-AI-main/venv/lib/python3.12/site-packages/langchain_community/llms/promptlayer_openai.pyis_lc_serializablez$PromptLayerOpenAI.is_lc_serializable(spromptsstop run_managerkwargsc ddlm}m}tjj j }t ||||}tjj j } tt|D]} || } |j| d} | j|jd} i|j|}|dd| g||j| || ||j }|js|| j t#| j t$si| _|| j d<|S)FCall OpenAI generate and then call PromptLayer API to log the request.r get_api_keypromptlayer_api_requesttext llm_outputzlangchain.PromptLayerOpenAI langchainr pl_request_idpromptlayer.utilsrrdatetimenow timestampsuper _generaterangelen generationsr r!_identifying_paramsr rgeneration_info isinstancedictselfrrrrrrrequest_start_timegenerated_responsesrequest_end_timeiprompt generationrespparamsr$ __class__s rr+zPromptLayerOpenAI._generate,s9 K%..224>>@#g/{K#,,002<<>s7|$AQZF,88;A>J"1<<D<00;F;F3- "  !.. M  --5Z..>24J.>K **?;3%4#"rc Kddlm}m}tjj j }t ||||d{}tjj j } tt|D]} || } |j| d} | j|jd} i|j|}|dd| g||j| || ||j d{}|js| j t#| j t$si| _|| j d<|S7 7Tw)Nrrpromptlayer_api_request_asyncrz!langchain.PromptLayerOpenAI.asyncr"r#r$r&rr@r'r(r)r* _agenerater,r-r.r r!r/r rr0r1r2r4rrrrrr@r5r6r7r8r9r:r;r<r$r=s rrBzPromptLayerOpenAI._agenerateUsQ Q%..224>>@$)G$6wk$RR#,,002<<>s7|$AQZF,88;A>J"1<<D<00;F;F"?3 "  !.. # M  --5Z..>24J.>K **?;3%4#"9S ,A E E B6EEEAEENN)__name__ __module__ __qualname____doc__rrstr__annotations__rbool classmethodrrrrr+rrB __classcell__r=s@rr r s.d3i  #(L(4.(4 %):> '#c'#tCy!'#67 '#  '#  '#X%)?C &#c&#tCy!&#;< &#  &#  &#&#rr c eZdZUdZeeeed<dZee ed< d deedeeedee de d e f fd Z d deedeeedeede d e f fd ZxZS) PromptLayerOpenAIChataZPromptLayer OpenAI large language models. To use, you should have the ``openai`` and ``promptlayer`` python package installed, and the environment variable ``OPENAI_API_KEY`` and ``PROMPTLAYER_API_KEY`` set with your openAI API key and promptlayer key respectively. All parameters that can be passed to the OpenAIChat LLM can also be passed here. The PromptLayerOpenAIChat adds two optional parameters: ``pl_tags``: List of strings to tag the request with. ``return_pl_id``: If True, the PromptLayer request ID will be returned in the ``generation_info`` field of the ``Generation`` object. Example: .. code-block:: python from langchain_community.llms import PromptLayerOpenAIChat openaichat = PromptLayerOpenAIChat(model_name="gpt-3.5-turbo") r Frrrrrrc ddlm}m}tjj j }t ||||}tjj j } tt|D]} || } |j| d} | j|jd} i|j|}|dd| g||j| || ||j }|js|| j t#| j t$si| _|| j d<|S)rrrrzlangchain.PromptLayerOpenAIChatr"r#r$r%r3s rr+zPromptLayerOpenAIChat._generates9 K%..224>>@#g/{K#,,002<<>s7|$AQZF,88;A>J"1<<D<00;F;F31 "  !.. M  --5Z..>24J.>K **?;3%4#"rc Kddlm}m}tjj j }t ||||d{}tjj j } tt|D]} || } |j| d} | j|jd} i|j|}|dd| g||j| || ||j d{}|js| j t#| j t$si| _|| j d<|S7 7Tw)Nrr?rz%langchain.PromptLayerOpenAIChat.asyncr"r#r$rArCs rrBz PromptLayerOpenAIChat._ageneratesQ Q%..224>>@$)G$6wk$RR#,,002<<>s7|$AQZF,88;A>J"1<<D<00;F;F"?7 "  !.. # M  --5Z..>24J.>K **?;3%4#"9S rDrE)rFrGrHrIrrrJrKrrLrrrr+rrBrNrOs@rrQrQ~s.d3i  #(L(4.( %):> '#c'#tCy!'#67 '#  '#  '#X%)?C &#c&#tCy!&#;< &#  &#  &#&#rrQ)r'typingrrrlangchain_core.callbacksrrlangchain_core.outputsrlangchain_community.llms.openair r r rQrrrrXs8&&->n#n#bj#Jj#r