7|hddlmZmZmZmZmZddlZddlmZddl m Z ddl m Z m Z ddlmZddlmZdZd Zd Zd j+eed e ZGdde Zy))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 eZdZUdZdZeed< dZeed< dZ e e ed< dZ e ed < dZe eed <ed Zed edefdZedeeeffdZedefdZdedefdZ ddede eede edededef dZy)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)extravaluesreturnc*t|dd}||d<|S)z?Validate that api key and python package exists in environment.rMOSAICML_API_TOKEN)r )clsrrs `/var/www/html/test/engine/venv/lib/python3.12/site-packages/langchain_community/llms/mosaicml.pyvalidate_environmentzMosaicML.validate_environmentBs*2 (*> (:#$ cJ|jxsi}id|jid|iS)zGet the identifying parameters.rr)rr)self _model_kwargss r _identifying_paramszMosaicML._identifying_paramsKs>))/R  t001 }-  r"cy)zReturn type of llm.mosaic)r$s r _llm_typezMosaicML._llm_typeTsr"promptcJ|jrtj|}|S)zTransform prompt.)r)rPROMPT_FOR_GENERATION_FORMATformat)r$r+s r _transform_promptzMosaicML._transform_promptYs*  ) )188"9F r"stop run_manageris_retrykwargsc |jxsi}|j|}d|gi}|j||j||jdd} t j |j ||} | jdk(rN|s4ddl } | j|j|j|||d Std | j| j!} t#| t$rOgd } | D] }|| vs| |}n!td dj'| d| t#|t(r|d}n|}ntd| |j+|r|t-|d}| t1||}|S#tjj$r} td| d} ~ wwxYw#tjj.$r } td| d| jd} ~ wwxYw)azCall out to a MosaicML LLM inference endpoint. Args: prompt: The prompt to pass into the model. stop: Optional list of stop words to use when generating. Returns: The string generated by the model. Example: .. code-block:: python response = mosaic_llm.invoke("Tell me a joke.") inputszapplication/json) Authorizationz Content-Type)headersjsonz$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$r+r0r1r2r3r%payloadr7responseerCparsed_response output_keyskey output_itemrFs r rEzMosaicML._callas),))/R ''/fX&}%v!% 7 78.   I}}T%6%6gVH+ ##s*JJt//0::fdK$:OO U}}o' 'mmoO/40; &Co-&5c&:  %(;)?(@A+,.k40&q>D&D #=o=N!OPPv&CKM*  &tT2D g""33 ICA3GH H IV""22 1!M(--Q  s?"F=AF9AF9A.F9F6#F11F69G6G11G6)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$4 WS#X%6  3%):> ZZtCy!Z67 Z  Z  Z Zr"r)typingrrrrrr=langchain_core.callbacksr#langchain_core.language_models.llmsr langchain_core.utilsr r pydanticr langchain_community.llms.utilsr INSTRUCTION_KEY RESPONSE_KEY INTRO_BLURBr.r-rr)r"r rhsg55=3?>$ A   F #   ^s^r"