o ZhX@sddlZddlZddlmZmZmZmZmZmZm Z ddl Z ddl m Z ddl mZddlmZddlmZmZddlmZdZejGd d d Zd eefd d Z  ddedededed eeeeeefff ddZGdddeZdS)N)AnyDictListMappingOptionalUnioncast)CallbackManagerForLLMRun)LLM)get_from_dict_or_env) ConfigDictmodel_validator)enforce_stop_tokens<c@s:eZdZUdZeed<eed<d ddZed dd ZdS) AviaryBackendzAviary backend. Attributes: backend_url: The URL for the Aviary backend. bearer: The bearer token for the Aviary backend. backend_urlbearerreturnNcCsd|ji|_dS)N Authorization)rheaderselfrV/var/www/html/lang_env/lib/python3.10/site-packages/langchain_community/llms/aviary.py __post_init__szAviaryBackend.__post_init__cCsTtd}|s Jdtdd}|rd|nd}||ds"dnd7}|||S)N AVIARY_URLzAVIARY_URL must be set AVIARY_TOKENzBearer /)osgetenvendswith)cls aviary_url aviary_tokenrrrrfrom_envs    zAviaryBackend.from_env)rN)rr) __name__ __module__ __qualname____doc__str__annotations__r classmethodr%rrrrrs  rrc Cs~t}|jd}tj||jtd}z|}Wntjy1}z t d|d|j |d}~wwt dd| D}|S)zList available modelsz-/routes)headerstimeoutError decoding JSON from . Text response: NcSs&g|]}d|vr|dddqS)--r)lstripreplace).0krrr 8s&zget_models..) rr%rrequestsgetrTIMEOUTjsonJSONDecodeError RuntimeErrortextsortedkeys)backend request_urlresponseresulterrr get_models,s"  rETrmodelpromptuse_prompt_formatversionc Cs~t}|j|ddd|d}tj||j||dtd}z|WStj y>}z t d|d|j |d}~ww) z#Get completions from Aviary models.rr1query)rGrH)r-r:r.r/r0N) rr%rr3r7postrr9r:r;r<r=)rFrGrHrIr@urlrBrDrrrget_completions=s$ rMc @seZdZUdZdZeed<dZeeed<dZ eeed<dZ e ed<dZ eeed <e d d Zed d ededefddZedeeeffddZedefddZ  ddedeeedeededef ddZdS)AviaryabAviary hosted models. Aviary is a backend for hosted models. You can find out more about aviary at http://github.com/ray-project/aviary To get a list of the models supported on an aviary, follow the instructions on the website to install the aviary CLI and then use: `aviary models` AVIARY_URL and AVIARY_TOKEN environment variables must be set. Attributes: model: The name of the model to use. Defaults to "amazon/LightGPT". aviary_url: The URL for the Aviary backend. Defaults to None. aviary_token: The bearer token for the Aviary backend. Defaults to None. use_prompt_format: If True, the prompt template for the model will be ignored. Defaults to True. version: API version to use for Aviary. Defaults to None. Example: .. code-block:: python from langchain_community.llms import Aviary os.environ["AVIARY_URL"] = "" os.environ["AVIARY_TOKEN"] = "" light = Aviary(model='amazon/LightGPT') output = light('How do you make fried rice?') zamazon/LightGPTrFNr#r$TrHrIZforbid)extrabefore)modevaluesrc Cst|dd}t|dd}|tjd<|tjd<zt}Wntjjy-}zt|d}~ww|d}|rE||vrEt|d|dd|S) z?Validate that api key and python package exists in environment.r#rr$rNrFz does not support model .) r renvironrEr7 exceptionsRequestException ValueErrorr8)r"rRr#r$Z aviary_modelsrDrFrrrvalidate_environments       zAviary.validate_environmentcCs|j|jdS)zGet the identifying parameters.)Z model_namer#)rFr#rrrr_identifying_paramsszAviary._identifying_paramscCsd|jddS)zReturn type of llm.zaviary-r-)rFr3rrrr _llm_typeszAviary._llm_typerGstop run_managerkwargscKsPd|ji}|jr |j|d<td|j|d|}tt|d}|r&t||}|S)a Call out to Aviary Args: prompt: The prompt to pass into the model. Returns: The string generated by the model. Example: .. code-block:: python response = aviary("Tell me a joke.") rHrI)rFrGZgenerated_textNr)rHrIrMrFrr*r)rrGr\r]r^outputr=rrr_calls   z Aviary._call)NN)r&r'r(r)rFr*r+r#rr$rHboolrIr Z model_configr r,rrrXpropertyrrYr[rr r`rrrrrNUs<    rN)Tr) dataclassesrtypingrrrrrrrr7Zlangchain_core.callbacksr Z#langchain_core.language_models.llmsr Zlangchain_core.utilsr Zpydanticr r Zlangchain_community.llms.utilsrr9 dataclassrr*rErafloatintrMrNrrrrs6$