Ng:ddlZddlZddlmZmZmZmZmZmZm Z ddl m Z ddl m Z ddlmZddlmZmZmZddlmZmZmZddlmZmZejeZe d d d Gd deZdS)N)AnyDictIteratorListMappingOptionalUnion) deprecated)CallbackManagerForLLMRun)BaseLLM) GenerationGenerationChunk LLMResult)convert_to_secret_strget_from_dict_or_envpre_init) ConfigDict SecretStrz0.0.18z1.0zlangchain_ibm.WatsonxLLM)sinceremovalalternative_importc eZdZUdZdZeed< 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<edZedefdZede eeffdZ!e"de de fdZ#ede$eeffdZ%edefdZ&e' d,de e(e eefde eeffdZ)d,de e(ede eeffd Z*de(ede+fd!Z,d"e eefde-fd#Z. d-d$ede e(ed%e e/d&edef d'Z0 d.d(e(ede e(ed%e e/d)e ed&ede+f d*Z1 d-d$ede e(ed%e e/d&ede2e-f d+Z3dS)/ WatsonxLLMa- IBM watsonx.ai large language models. To use, you should have ``ibm_watsonx_ai`` python package installed, and the environment variable ``WATSONX_APIKEY`` set with your API key, or pass it as a named parameter to the constructor. Example: .. code-block:: python from ibm_watsonx_ai.metanames import GenTextParamsMetaNames parameters = { GenTextParamsMetaNames.DECODING_METHOD: "sample", GenTextParamsMetaNames.MAX_NEW_TOKENS: 100, GenTextParamsMetaNames.MIN_NEW_TOKENS: 1, GenTextParamsMetaNames.TEMPERATURE: 0.5, GenTextParamsMetaNames.TOP_K: 50, GenTextParamsMetaNames.TOP_P: 1, } from langchain_community.llms import WatsonxLLM watsonx_llm = WatsonxLLM( model_id="google/flan-ul2", url="https://us-south.ml.cloud.ibm.com", apikey="*****", project_id="*****", params=parameters, ) model_id deployment_id project_idspace_idNurlapikeytokenpasswordusername instance_idversionparamsverifyF streaming watsonx_modelforbid)extrareturncdS)NF)clss _/var/www/html/ai-engine/env/lib/python3.11/site-packages/langchain_community/llms/watsonxllm.pyis_lc_serializablezWatsonxLLM.is_lc_serializablefsucdddddddS)N WATSONX_URLWATSONX_APIKEY WATSONX_TOKENWATSONX_PASSWORDWATSONX_USERNAMEWATSONX_INSTANCE_ID)rr r!r"r#r$r.selfs r0 lc_secretszWatsonxLLM.lc_secretsjs%!&$**0    r2valuesc tt|dd|d<d|ddvr#tt|dd|d<nq|dsIdtjvr;|d s3d tjvr%|dsdtjvrt d |dsdtjvr"tt|dd|d<n|d sd tjvrCtt|d d |d <tt|d d |d <nX|dsdtjvrBtt|dd|d<tt|d d |d <|drdtjvr!tt|dd|d< ddlm}|dr|dnd|dr|dnd|dr|dnd|d r|d nd|d r|d nd|dr|dnd|dr|dndd}d| D}||d|d||d|d|d|d}||d<n#t$rtdwxYw|S)zCValidate that credentials and python package exists in environment.rr4z cloud.ibm.comrr r5r!r6r"r7zDid 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.r#r8r$r9r)ModelInferenceNr%)rr r!r"r#r$r%ci|] \}}||| SNr.).0keyvalues r0 z3WatsonxLLM.validate_environment..s*...)sEEDUUDUDUDUr2rrr&rrr')rr credentialsr&rrr'r)zdCould not import ibm_watsonx_ai python package. Please install it with `pip install ibm_watsonx_ai`.) rrgetget_secret_valueosenviron ValueError ibm_watsonx_ai.foundation_modelsr?items ImportError)r/r=r?rFcredentials_without_none_valuer)s r0validate_environmentzWatsonxLLM.validate_environmentus.  > >  u  fjj33DDFF F F4$VX7GHH  F8   7O! #2:55z*6&bj88x(9$BJ66 - Orz$A$A"7(/JJ##w # '9RZ'G'G%:(=OPP&&z"&;(=OPP&&z""! %5%C%C#8(;KLL$$x &;(=OPP&&z"-( ,A,S,S(=(@UVV))}%1  G G G G G G->-@-@... *+N +$_5:h'!,/ +h'M'4F? # #   G    s !EL99McD|j|j|j|j|jdS)zGet the identifying parameters.rrr&rrrRr:s r0_identifying_paramszWatsonxLLM._identifying_paramss- !/k/    r2cdS)zReturn type of llm.zIBM watsonx.air.r:s r0 _llm_typezWatsonxLLM._llm_types  r2responsec|dddSd}d}dtdtttfdtfd}|D]C}|d}|r*||d|dz }||d |dz }D||dS) Nr)generated_token_countinput_token_countrCresultr,c2||dpdS)Nr)rG)rCrZs r0get_count_valuez8WatsonxLLM._extract_token_usage..get_count_values::c1%%* *r2resultsrYrX)strrrintrG)rVrYrXr\resr]s r0_extract_token_usagezWatsonxLLM._extract_token_usages  -.QGG G ! + +d38n + + + + +  Cggi((G !__5H'RS*%U%UU!%+WQZ**% &;!2   r2stopc8|jr i|jni}|||d<|S)Nstop_sequences)r&)r;rbr&s r0_get_chat_paramszWatsonxLLM._get_chat_paramss.48K!GDKR  '+F# $ r2cdg}|D]v}|d}|r]|dd}t|ddd|i}||gw||}||j|jd}t ||S) z2Create the LLMResult from the choices and prompts.r]r stop_reasongenerated_text finish_reasontextgeneration_info) token_usagerr generations llm_output)rGr appendrarrr) r;rVror`r]rigenfinal_token_usagerps r0_create_llm_resultzWatsonxLLM._create_llm_result s  * *Cggi((G * ' } = =   (899%4m$D""C5))) 55h??, !/  [ZHHHHr2stream_responsec |dstdSt|dddt|dddd|j|jd  S) z0Convert a stream response to a generation chunk.r]rrkrrhrgN)rr)rirprj)rdictrGrr)r;rus r0$_stream_response_to_generation_chunkz/WatsonxLLM._stream_response_to_generation_chunks y) ,"+++ + +A./?@ -i8;?? tTT $ %)%7    r2prompt run_managerkwargsc V|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") )promptsrbr{rr.) _generaterork)r;rzrbr{r|rZs r0_callzWatsonxLLM._call1sJ&  H4[  DJ  !!$Q',,r2r~streamc ||}||n|j}|rt|dkrtd|t d}|j|df||d|} | D] } || }|| z } |Jt |jtr-|j d } t|gg| St|gg S|j || } | | S) aCall the IBM watsonx.ai inference endpoint which then generate the response. Args: prompts: List of strings (prompts) to pass into the model. stop: Optional list of stop words to use when generating. run_manager: Optional callback manager. Returns: The full LLMResult output. Example: .. code-block:: python response = watsonx_llm.generate(["What is a molecule"]) rbNz6WatsonxLLM currently only supports single prompt, got rrwr)rbr{rprn)ro)rzr&)rer(lenrKr_stream isinstancerlrxpoprr)generatert) r;r~rbr{rr|r& should_stream generation stream_iterchunkrprVs r0rzWatsonxLLM._generateIs`(&&D&11"("4$.  57||a VWVV)b111J&$, !%;BHK% ( (%!&JJ%'JJ)))*4d;; T'7;;LII  zl^ SSSS:,888 8)22'&2QQH**844 4r2c+K||}|j|d|D]9}||}|r||j||V:dS)a4Call the IBM watsonx.ai inference endpoint which then streams the response. Args: prompt: The prompt to pass into the model. stop: Optional list of stop words to use when generating. run_manager: Optional callback manager. Returns: The iterator which yields generation chunks. Example: .. code-block:: python response = watsonx_llm.stream("What is a molecule") for chunk in response: print(chunk, end='') # noqa: T201 rT)rz raw_responser&)rN)rer)generate_text_streamryon_llm_new_tokenrk)r;rzrbr{r|r& stream_resprs r0rzWatsonxLLM._streamvs*&&D&11-BBVC    K==kJJE F,,UZu,EEEKKKK  r2rA)NN)NNN)4__name__ __module__ __qualname____doc__rr^__annotations__rrrrrrr r!r"r#r$r%r&rxr'r boolr(r)rr model_config classmethodr1propertyrr<rrPrrSrU staticmethodrrarerrtrryr rrrrr.r2r0rrs>HcM3(J*Hc(#C) ###1"&FHY &&&4!%E8I %%%3$(Hhy!(((6$(Hhy!(((6'+K)$+++9#'GXi '''5!FHTN!!!;!FE#t) !!!0 It1M3:L4[ DcN   X c$c4cccXcJ WS#X%6   X  3   X 37  4S#X/0 c3h   \ 2Xd3i%8DcN I4:I)IIII( c3h      *%):> ---tCy!-67 -  - ----6%):>!% +5+5c+5tCy!+567 +5  +5  +5 +5+5+5+5`%):> tCy!67    / " r2r)loggingrItypingrrrrrrr langchain_core._api.deprecationr langchain_core.callbacksr #langchain_core.language_models.llmsr langchain_core.outputsr rrlangchain_core.utilsrrrpydanticrr getLoggerrloggerrr.r2r0rsO FFFFFFFFFFFFFFFFFF666666======777777IIIIIIIIIIVVVVVVVVVV********  8 $ $  E6PAAAAAAAAAAr2