dhSSKJrJrJrJrJr SSKrSSKJr SSK J r SSK J r J r SSKJr SSKJr SrS rS rS R+\\S \S 9r"SS\ 5rg))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 &\rSrSr%SrSr\\S'Sr\ \S'Sr \ \ \S'S r \\S 'Sr\ \\S '\"S S 9r\S\S\4Sj5r\S\\\44Sj5r\S\4Sj5rS\S\4SjrSS\S\ \\S\ \S\ S\S\4 SjjrSrg)MosaicMLaMosaicML 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([USS5nX!S'U$)z?Validate that api key and python package exists in environment.rMOSAICML_API_TOKEN)r )clsrrs Y/var/www/html/shao/venv/lib/python3.13/site-packages/langchain_community/llms/mosaicml.pyvalidate_environmentMosaicML.validate_environmentBs(2 (*> (:#$ cTUR=(d 0n0SUR0ESU0E$)zGet the identifying parameters.rr)rr)self _model_kwargss r!_identifying_paramsMosaicML._identifying_paramsKs>))/R  t001 }-  r$cg)zReturn type of llm.mosaic)r&s r! _llm_typeMosaicML._llm_typeTsr$promptcNUR(a[RUS9nU$)zTransform prompt.)r)rPROMPT_FOR_GENERATION_FORMATformat)r&r/s r!_transform_promptMosaicML._transform_promptYs*  ) )188"9F r$stop run_manageris_retrykwargsc "UR=(d 0nURU5nSU/0nURU5 URU5 URSS.n[R "UR XS9n U RS:XaOU(d0SSK n U RUR5 URXUS S 9$[S U R35eU R!5n [#U [$5(aV/S Qn U HnX;dM Xn O" [S SR'U 5SU 35e[#U[(5(aUSnOUnO[SU 35eUR+U5(aU[-U5SnUb [1UU5nU$![RRan [SU 35eSn A ff=f![RR.a n [SU SU R35eSn A ff=f)a2Call 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$Error raised by inference endpoint: NirT)r7z>Error raised by inference API: rate limit exceeded. Response: )dataoutputoutputszNo valid key (z, z) in response: zUnexpected response type: zError raised by inference API: z . Response: )rr3updaterrequestspostr exceptionsRequestException ValueError status_codetimesleepr_calltextr= isinstancedictjoinlist startswithlenJSONDecodeErrorr )r&r/r5r6r7r8r'payloadr<responseerHparsed_response output_keyskey output_itemrKs r!rJMosaicML._callas%,))/R ''/fX&}%v!% 7 78.   I}}T%6%6VH+ ##s*JJt//0::fK$:OO U}}o' 'mmoO/400; &C-&5&: ' %(;)?(@A+,.k400&q>D&D #=o=N!OPPv&&CKM*  &tT2D g""33 ICA3GH H IV""22 1!M(--Q  s?F?AGA GA8GG :GG H.H  Hr,)NNF)__name__ __module__ __qualname____firstlineno____doc__rstr__annotations__rboolrrrMrfloatrr model_configr rr"propertyrrr(r-r3rrrJ__static_attributes__r,r$r!rrs@( O#&+t+C#'L(4.'1KE(, ,L$4 WS#X%6  3%):> ZZtCy!Z67 Z  Z  Z ZZr$r)typingrrrrrrBlangchain_core.callbacksr#langchain_core.language_models.llmsr langchain_core.utilsr r pydanticr langchain_community.llms.utilsr INSTRUCTION_KEY RESPONSE_KEY INTRO_BLURBr2r1rr,r$r!rpsg55=3?>$ A   F #   ^s^r$