NgddlmZmZmZmZmZddlZddlmZddl m Z ddl m Z m Z ddlmZddlmZdZd Zd Zd eed e ZGdde ZdS))AnyDictListMappingOptionalN)CallbackManagerForLLMRun)LLM)get_from_dict_or_envpre_init) ConfigDict)enforce_stop_tokensz### Instruction:z ### Response:ziBelow is an instruction that describes a task. Write a response that appropriately completes the request.z7{intro} {instruction_key} {instruction} {response_key} z {instruction})introinstruction_key instruction response_keyc VeZdZUdZdZeed< dZeed< dZ e e ed< dZ e ed < dZe eed <ed Zed edefdZedeeeffdZedefdZdedefdZ ddede eede edededef dZdS)MosaicMLa2MosaicML LLM service. To use, you should have the environment variable ``MOSAICML_API_TOKEN`` set with your API token, or pass it as a named parameter to the constructor. Example: .. code-block:: python from langchain_community.llms import MosaicML endpoint_url = ( "https://models.hosted-on.mosaicml.hosting/mpt-7b-instruct/v1/predict" ) mosaic_llm = MosaicML( endpoint_url=endpoint_url, mosaicml_api_token="my-api-key" ) zDhttps://models.hosted-on.mosaicml.hosting/mpt-7b-instruct/v1/predict endpoint_urlFinject_instruction_formatN model_kwargsg? retry_sleepmosaicml_api_tokenforbid)extravaluesreturnc2t|dd}||d<|S)z?Validate that api key and python package exists in environment.rMOSAICML_API_TOKEN)r )clsrrs ]/var/www/html/ai-engine/env/lib/python3.11/site-packages/langchain_community/llms/mosaicml.pyvalidate_environmentzMosaicML.validate_environmentBs/2 (*>  (:#$ c2|jpi}id|jid|iS)zGet the identifying parameters.rr)rr)self _model_kwargss r _identifying_paramszMosaicML._identifying_paramsKs8)/R  t01 }-  r"cdS)zReturn type of llm.mosaic)r$s r _llm_typezMosaicML._llm_typeTs xr"promptcJ|jrt|}|S)zTransform prompt.)r)rPROMPT_FOR_GENERATION_FORMATformat)r$r+s r _transform_promptzMosaicML._transform_promptYs1  ) 188"9F r"stop run_manageris_retrykwargsc &|jpi}||}d|gi}|||||jdd} t j|j||} n.#tjj$r} td| d} ~ wwxYw | j dkrP|s7ddl } | |j ||||d Std | j| } t#| t$r`gd } | D]}|| vr | |}n)td d| d| t#|t(r |d}n|}ntd| ||r|t-|d}n6#tjj$r} td| d| jd} ~ wwxYw|t1||}|S)azCall out to a MosaicML LLM inference endpoint. Args: prompt: The prompt to pass into the model. stop: Optional list of stop words to use when generating. Returns: The string generated by the model. Example: .. code-block:: python response = mosaic_llm.invoke("Tell me a joke.") inputszapplication/json) Authorizationz Content-Type)headersjsonz$Error raised by inference endpoint: NirT)r2z>Error raised by inference API: rate limit exceeded. Response: )dataoutputoutputszNo valid key (z, z) in response: zUnexpected response type: zError raised by inference API: z . Response: )rr/updaterrequestspostr exceptionsRequestException ValueError status_codetimesleepr_calltextr8 isinstancedictjoinlist startswithlenJSONDecodeErrorr )r$r+r0r1r2r3r%payloadr7responseerCparsed_response output_keyskey output_itemrFs r rEzMosaicML._callas,)/R ''//fX&}%%%v!% 79.    I}T%6gVVVHH"3 I I IGAGGHH H I+ #s**PKKKJJt/000::fdK$:OOO '}'' 'mmooO/400 Q;;; &Co--&5c&: .%.;)?)?..+..k400'&q>DD&DD !Oo!O!OPPPv&& +CKKMM*"2   Q!QQ(-QQ    &tT22D s8A77B" BB"&AG *CG G<G77G<)NNF)__name__ __module__ __qualname____doc__rstr__annotations__rboolrrrHrfloatrr model_configr rr!propertyrrr&r*r/rrrEr)r"r rrs( O#&+t+++C#'L(4.'''1KE(, ,,,:L$4X WS#X%6   X 3X%):> ZZZtCy!Z67 Z  Z  Z ZZZZZZr"r)typingrrrrrr=langchain_core.callbacksr#langchain_core.language_models.llmsr langchain_core.utilsr r pydanticr langchain_community.llms.utilsr INSTRUCTION_KEY RESPONSE_KEY INTRO_BLURBr.r-rr)r"r rhs55555555555555======333333????????>>>>>>$ A   F #   ^^^^^s^^^^^r"