o Zh:@sddlZddlZddlmZmZmZmZmZmZm Z ddl m Z ddl m Z ddlmZddlmZmZmZddlmZmZmZddlmZmZeeZe d d d d Gd ddeZdS)N)AnyDictIteratorListMappingOptionalUnion) deprecated)CallbackManagerForLLMRun)BaseLLM) GenerationGenerationChunk LLMResult)convert_to_secret_strget_from_dict_or_envpre_init) ConfigDict SecretStrz0.0.18z1.0zlangchain_ibm.WatsonxLLM)ZsinceZremovalZalternative_importc @seZdZUdZdZeed< dZeed< dZeed< dZ eed< dZ e e ed< dZ e e ed < dZe e ed < dZe e ed < dZe e ed < dZe e ed < dZe e ed< dZe eed< dZeeefed< dZeed< dZeed<eddZedefddZede eeffddZ!e"de de fddZ#ede$eeffddZ%edefd d!Z&e' d8d"e e(e eefde eeffd#d$Z)d8d%e e(ede eeffd&d'Z*d"e(ede+fd(d)Z,d*e eefde-fd+d,Z.  d9d-ed%e e(ed.e e/d/edef d0d1Z0   d:d2e(ed%e e(ed.e e/d3e ed/ede+f d4d5Z1  d9d-ed%e e(ed.e e/d/ede2e-f d6d7Z3dS); WatsonxLLMa- IBM watsonx.ai large language models. To use, you should have ``ibm_watsonx_ai`` python package installed, and the environment variable ``WATSONX_APIKEY`` set with your API key, or pass it as a named parameter to the constructor. Example: .. code-block:: python from ibm_watsonx_ai.metanames import GenTextParamsMetaNames parameters = { GenTextParamsMetaNames.DECODING_METHOD: "sample", GenTextParamsMetaNames.MAX_NEW_TOKENS: 100, GenTextParamsMetaNames.MIN_NEW_TOKENS: 1, GenTextParamsMetaNames.TEMPERATURE: 0.5, GenTextParamsMetaNames.TOP_K: 50, GenTextParamsMetaNames.TOP_P: 1, } from langchain_community.llms import WatsonxLLM watsonx_llm = WatsonxLLM( model_id="google/flan-ul2", url="https://us-south.ml.cloud.ibm.com", apikey="*****", project_id="*****", params=parameters, ) model_id deployment_id project_idspace_idNurlapikeytokenpasswordusername instance_idversionparamsverifyF streaming watsonx_modelZforbid)extrareturncCdS)NF)clsr(r(Z/var/www/html/lang_env/lib/python3.10/site-packages/langchain_community/llms/watsonxllm.pyis_lc_serializablefszWatsonxLLM.is_lc_serializablecCsdddddddS)N WATSONX_URLWATSONX_APIKEY WATSONX_TOKENWATSONX_PASSWORDWATSONX_USERNAMEWATSONX_INSTANCE_ID)rrrrrrr(selfr(r(r* lc_secretsjszWatsonxLLM.lc_secretsvaluesc CsTtt|dd|d<d|ddvrtt|dd|d<n|ds>dtjvr>|d s>d tjvr>|ds>dtjvr>td |dsGdtjvrRtt|dd|d<n;|d s[d tjvrptt|d d |d <tt|d d |d <n|dsydtjvrtt|dd|d<tt|d d |d <|drdtjvrtt|dd|d<z}ddlm}|dr|dnd|dr|dnd|dr|dnd|d r|d nd|d r|d nd|dr|dnd|dr|dndd}dd| D}||d|d||d|d|d|dd}||d<W|St y)t dw) zCValidate that credentials and python package exists in environment.rr,z cloud.ibm.comrrr-rr.rr/zDid not find 'token', 'password' or 'apikey', please add an environment variable `WATSONX_TOKEN`, 'WATSONX_PASSWORD' or 'WATSONX_APIKEY' which contains it, or pass 'token', 'password' or 'apikey' as a named parameter.rr0rr1r)ModelInferenceNr )rrrrrrr cSsi|] \}}|dur||qSNr().0keyvaluer(r(r* sz3WatsonxLLM.validate_environment..rrr!rrr")rr credentialsr!rrr"r$zdCould not import ibm_watsonx_ai python package. Please install it with `pip install ibm_watsonx_ai`.) rrgetZget_secret_valueosenviron ValueErrorZ ibm_watsonx_ai.foundation_modelsr6items ImportError)r)r5r6r<Zcredentials_without_none_valuer$r(r(r*validate_environmentus                zWatsonxLLM.validate_environmentcCs|j|j|j|j|jdS)zGet the identifying parameters.rrr!rrrDr2r(r(r*_identifying_paramss zWatsonxLLM._identifying_paramscCr')zReturn type of llm.zIBM watsonx.air(r2r(r(r* _llm_typeszWatsonxLLM._llm_typeresponsecCs~|dur dddSd}d}dtdtttfdtfdd}|D]}|d}|r9||d |d7}||d |d7}q||dS) Nr)generated_token_countinput_token_countr9resultr&cSs||dpdS)Nr)r=)r9rJr(r(r*get_count_valuesz8WatsonxLLM._extract_token_usage..get_count_valueresultsrIrH)strrrintr=)rGrIrHrKresrLr(r(r*_extract_token_usages   zWatsonxLLM._extract_token_usagestopcCs(|jri|jni}|dur||d<|S)NZstop_sequences)r!)r3rQr!r(r(r*_get_chat_paramsszWatsonxLLM._get_chat_paramsc Csvg}|D]#}|d}|r'|dd}t|ddd|id}||gq||}||j|jd}t||dS) z2Create the LLMResult from the choices and prompts.rLr stop_reasongenerated_text finish_reasontextgeneration_info)Z token_usagerr generations llm_output)r=r appendrPrrr) r3rGrZrOrLrUgenZfinal_token_usager[r(r(r*_create_llm_result s"     zWatsonxLLM._create_llm_resultstream_responsecCsL|ds tddSt|dddt|dddd|j|jdd d S) z0Convert a stream response to a generation chunk.rLrrWrrTrSN)rr)rUr[rV)r dictr=rr)r3r_r(r(r*$_stream_response_to_generation_chunks z/WatsonxLLM._stream_response_to_generation_chunkprompt run_managerkwargscKs*|jd|g||d|}|jddjS)aCall the IBM watsonx.ai inference endpoint. Args: prompt: The prompt to pass into the model. stop: Optional list of stop words to use when generating. run_manager: Optional callback manager. Returns: The string generated by the model. Example: .. code-block:: python response = watsonx_llm.invoke("What is a molecule") )promptsrQrdrNr() _generaterZrW)r3rcrQrdrerJr(r(r*_call1s zWatsonxLLM._callrfstreamc Ks|j|d}|dur |n|j}|rbt|dkrtd|tdd}|j|df||d|} | D] } |dur<| }q3|| 7}q3|dusGJt|jtr[|j d } t |gg| d St |ggd S|j j ||d } | | S) aCall the IBM watsonx.ai inference endpoint which then generate the response. Args: prompts: List of strings (prompts) to pass into the model. stop: Optional list of stop words to use when generating. run_manager: Optional callback manager. Returns: The full LLMResult output. Example: .. code-block:: python response = watsonx_llm.generate(["What is a molecule"]) rQNz6WatsonxLLM currently only supports single prompt, got rr`r)rQrdr[rY)rZ)rcr!)rRr#lenr@r _stream isinstancerXrapoprr$generater^) r3rfrQrdrirer!Z should_streamZ generationZ stream_iterchunkr[rGr(r(r*rgIs4        zWatsonxLLM._generatecksN|j|d}|jj|d|dD]}||}|r!|j|j|d|VqdS)a4Call the IBM watsonx.ai inference endpoint which then streams the response. Args: prompt: The prompt to pass into the model. stop: Optional list of stop words to use when generating. run_manager: Optional callback manager. Returns: The iterator which yields generation chunks. Example: .. code-block:: python response = watsonx_llm.stream("What is a molecule") for chunk in response: print(chunk, end='') # noqa: T201 rjT)rcZ raw_responser!)rqN)rRr$Zgenerate_text_streamrbZon_llm_new_tokenrW)r3rcrQrdrer!Z stream_resprqr(r(r*rmvs  zWatsonxLLM._streamr7)NN)NNN)4__name__ __module__ __qualname____doc__rrM__annotations__rrrrrrrrrrrr r!rar"rboolr#r$rrZ model_config classmethodr+propertyrr4rrCrrErF staticmethodrrPrRrr^r rbr rhrgrrmr(r(r(r*rs        e   $      0 r)loggingr>typingrrrrrrrZlangchain_core._api.deprecationr Zlangchain_core.callbacksr Z#langchain_core.language_models.llmsr Zlangchain_core.outputsr r rZlangchain_core.utilsrrrZpydanticrr getLoggerrrloggerrr(r(r(r*s$