+#hgLdZddlmZddlmZmZmZmZmZm Z m Z m Z m Z m Z ddlmZmZddlmZddlmZddlmZmZmZmZmZmZddlmZmZmZdd l m!Z!dd l"m#Z#dd l$m%Z%dd l&m'Z'dd l(m)Z)ddl*m+Z+ddl,m-Z-dZ.eGddZ/eGddZ0dedefdZ1de0defdZ2dede3fdZ4dede3fdZ5dede3fdZ6dede3fdZ7Gdd eZ8y!)"zHugging Face Chat Wrapper.) dataclass) AnyCallableDictListLiteralOptionalSequenceTypeUnioncast)AsyncCallbackManagerForLLMRunCallbackManagerForLLMRun)LanguageModelInput) BaseChatModel) AIMessage BaseMessage ChatMessage HumanMessage SystemMessage ToolMessage)ChatGeneration ChatResult LLMResult)Runnable)BaseTool)convert_to_openai_tool)model_validator)Self)HuggingFaceEndpoint)HuggingFacePipelinez4You are a helpful, respectful, and honest assistant.c,eZdZUdZeeed<eed<y) TGI_RESPONSEz'Response from the TextGenInference API.choicesusageN)__name__ __module__ __qualname____doc__rr__annotations__rj/var/www/html/sandstorm/venv/lib/python3.12/site-packages/langchain_huggingface/chat_models/huggingface.pyr#r#,s1 #Y Kr,r#c6eZdZUdZeed<eed<eeed<y) TGI_MESSAGEz,Message to send to the TextGenInference API.rolecontent tool_callsN)r&r'r(r)strr*rrr+r,r-r/r/4s6 I LT r,r/messagereturnc6t|tr!t|j|jSt|t rtd|jSt|t rNd|jvr.|jdDcgc]}d|dd|dddi}}nd}d|j|d St|trtd |jSt|trd |j|jd Std |cc}w)Nr0r1userr2functionname arguments)r:r; assistant)r0r1r2systemtool)r0r1r:zGot unknown type ) isinstancerdictr0r1rradditional_kwargsrrr: ValueError)r4tcr2s r- _convert_message_to_chat_messagerD=s';'w?? G\ *99 GY ' 744 4"33LA  ":v 6%' ^K%@!JJ$  G] +7??;; G[ )LL  ,WI6773sD_messagecF|j}|dk(s Jd|tt|j}|d}i}|jx}rLd|ddvr=t|ddj d}|j dd}||ddd<||d <t|| S) Nr<z%Expected role to be 'assistant', got r;rr9'"r2)r1rA)r0r r3r1r2popreplacer)rEr0r1rAr2functions_stringcorrected_functionss r-"_convert_TGI_message_to_LC_messagerNbs ==D ; N"Gv NN 3(()G (((z( *Q- 3 3":a=#<#@#@#MN "2":":3"D 5HJqM* %k 2*4,' W8I JJr,llmcF ddlm}t||S#t$rYywxYw)Nr)HuggingFaceHubF)(langchain_community.llms.huggingface_hubrQr? ImportError)rOrQs r-_is_huggingface_hubrTts- #~..    cF ddlm}t||S#t$rYywxYw)Nr)HuggingFaceTextGenInferenceF)7langchain_community.llms.huggingface_text_gen_inferencerWr?rS)rOrWs r-!_is_huggingface_textgen_inferencerYs. #:;; rUc"t|tSN)r?r rOs r-_is_huggingface_endpointr] c. //r,c"t|tSr[)r?r!r\s r-_is_huggingface_pipeliner`r^r,c eZdZUdZeed< eeZeed<dZ eed<dZ e e ed<deffd Z ed d efd Zded efdZ d"deede ee de eded ef dZ d"deede ee de eded ef dZdeed e fdZded efdZeded efdZd#dZ ddde!e"e#e efe$e%e&fde e"ee e'de(fded e)e*efffdZ+deede ee d ee#eeffd Z,e-d e fd!Z.xZ/S)$ChatHuggingFaceuHugging Face LLM's as ChatModels. Works with `HuggingFaceTextGenInference`, `HuggingFaceEndpoint`, `HuggingFaceHub`, and `HuggingFacePipeline` LLMs. Upon instantiating this class, the model_id is resolved from the url provided to the LLM, and the appropriate tokenizer is loaded from the HuggingFace Hub. Setup: Install ``langchain-huggingface`` and ensure your Hugging Face token is saved. .. code-block:: bash pip install langchain-huggingface .. code-block:: python from huggingface_hub import login login() # You will be prompted for your HF key, which will then be saved locally Key init args — completion params: llm: `HuggingFaceTextGenInference`, `HuggingFaceEndpoint`, `HuggingFaceHub`, or 'HuggingFacePipeline' LLM to be used. Key init args — client params: custom_get_token_ids: Optional[Callable[[str], List[int]]] Optional encoder to use for counting tokens. metadata: Optional[Dict[str, Any]] Metadata to add to the run trace. tags: Optional[List[str]] Tags to add to the run trace. tokenizer: Any verbose: bool Whether to print out response text. See full list of supported init args and their descriptions in the params section. Instantiate: .. code-block:: python from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace llm = HuggingFaceEndpoint( repo_id="microsoft/Phi-3-mini-4k-instruct", task="text-generation", max_new_tokens=512, do_sample=False, repetition_penalty=1.03, ) chat = ChatHuggingFace(llm=llm, verbose=True) Invoke: .. code-block:: python messages = [ ("system", "You are a helpful translator. Translate the user sentence to French."), ("human", "I love programming."), ] chat(...).invoke(messages) .. code-block:: python AIMessage(content='Je ai une passion pour le programme. In French, we use "ai" for masculine subjects and "a" for feminine subjects. Since "programming" is gender-neutral in English, we will go with the masculine "programme". Confirmation: "J'aime le programme." is more commonly used. The sentence above is technically accurate, but less commonly used in spoken French as "ai" is used less frequently in everyday speech.', response_metadata={'token_usage': ChatCompletionOutputUsage (completion_tokens=100, prompt_tokens=55, total_tokens=155), 'model': '', 'finish_reason': 'length'}, id='run-874c24b7-0272-4c99-b259-5d6d7facbc56-0') Stream: .. code-block:: python for chunk in chat.stream(messages): print(chunk) .. code-block:: python content='Je ai une passion pour le programme. In French, we use "ai" for masculine subjects and "a" for feminine subjects. Since "programming" is gender-neutral in English, we will go with the masculine "programme". Confirmation: "J'aime le programme." is more commonly used. The sentence above is technically accurate, but less commonly used in spoken French as "ai" is used less frequently in everyday speech.' response_metadata={'token_usage': ChatCompletionOutputUsage (completion_tokens=100, prompt_tokens=55, total_tokens=155), 'model': '', 'finish_reason': 'length'} id='run-7d7b1967-9612-4f9a-911a-b2b5ca85046a-0' Async: .. code-block:: python await chat.ainvoke(messages) .. code-block:: python AIMessage(content='Je déaime le programming. Littérale : Je (j'aime) déaime (le) programming. Note: "Programming" in French is "programmation". But here, I used "programming" instead of "programmation" because the user said "I love programming" instead of "I love programming (in French)", which would be "J'aime la programmation". By translating the sentence literally, I preserved the original meaning of the user's sentence.', id='run-fd850318-e299-4735-b4c6-3496dc930b1d-0') Tool calling: .. code-block:: python from pydantic import BaseModel, Field class GetWeather(BaseModel): '''Get the current weather in a given location''' location: str = Field(..., description="The city and state, e.g. San Francisco, CA") class GetPopulation(BaseModel): '''Get the current population in a given location''' location: str = Field(..., description="The city and state, e.g. San Francisco, CA") chat_with_tools = chat.bind_tools([GetWeather, GetPopulation]) ai_msg = chat_with_tools.invoke("Which city is hotter today and which is bigger: LA or NY?") ai_msg.tool_calls .. code-block:: python [{'name': 'GetPopulation', 'args': {'location': 'Los Angeles, CA'}, 'id': '0'}] Response metadata .. code-block:: python ai_msg = chat.invoke(messages) ai_msg.response_metadata .. code-block:: python {'token_usage': ChatCompletionOutputUsage(completion_tokens=100, prompt_tokens=8, total_tokens=108), 'model': '', 'finish_reason': 'length'} rOr1system_messageN tokenizermodel_idkwargsc t|di|ddlm}|j |j !|j |j|_y|j |_y)Nr) AutoTokenizerr+)super__init__ transformersri_resolve_model_idrefrom_pretrainedrf)selfrgri __class__s r-rkzChatHuggingFace.__init__<sY "6".  ~~%  ) )$-- 8  r,after)moder5ct|js`t|jsKt|js6t |js!t dt |j|S)NzyExpected llm to be one of HuggingFaceTextGenInference, HuggingFaceEndpoint, HuggingFaceHub, HuggingFacePipeline received )rTrOrYr]r` TypeErrortyperos r- validate_llmzChatHuggingFace.validate_llmIs`$DHH-5dhh?,TXX6,TXX6 N+-   r,responsec g}|jdj}tt|jdjd|i}|j ||j }|jj}||d}t||S)Nr finish_reasonr4generation_info) token_usagemodel generations llm_output) r$rzrrNr4appendr%rOinference_server_urlr)rorxrrzgenr} model_objectrs r-_create_chat_resultz#ChatHuggingFace._create_chat_resultXs  ((+99 6x7G7G7J7R7RS,m<  3nn xx44 %0<H kjIIr,messagesstop run_managerc t|jrK|j||}|jjjdd|i|}|j |St |jrK|j||}|jjjdd|i|}|j |S|j|}|jjd|g||d|}|j|SNr)promptsrrr+) rYrO_create_message_dictsclientchatrr]chat_completion_to_chat_prompt _generate_to_chat_result rorrrrg message_dictsanswer llm_input llm_results r-rzChatHuggingFace._generatees -TXX 6 66xFM)TXX__))K=KFKF++F3 3 %dhh / 66xFM4TXX__44VmVvVF++F3 3,,X6I+++" $KKQJ'' 3 3r,cxKt|jrS|j||}|jjjdd|i|d{}|j |S|j |}|jjd|g||d|d{}|j|S7`7wr) rYrOr async_clientrrr _ageneraterrs r-rzChatHuggingFace._agenerate{s -TXX 6 66xFM54880055W}WPVWWF++F3 3,,X6I2txx22 " $K KQ J'' 3 3Xs%AB:B6A B: B8!B:8B:c|s tdt|dts td|Dcgc]}|j|}}|jj |ddScc}w)zHConvert a list of messages into a prompt format expected by wrapped LLM.z+At least one HumanMessage must be provided!z$Last message must be a HumanMessage!FT)tokenizeadd_generation_prompt)rBr?r_to_chatml_formatreapply_chat_template)rormmessages_dictss r-rzChatHuggingFace._to_chat_promptst JK K(2, 5CD D=EF$003FF~~11 U$2  GsA(r4ct|trd}n=t|trd}n*t|trd}nt dt |||j dS)z+Convert LangChain message to ChatML format.r=r<r8zUnknown message type: r7)r?rrrrBrur1)ror4r0s r-rz!ChatHuggingFace._to_chatml_formatsW g} -D  +D  .D5d7m_EF F99r,rcg}|jdD]>}tt|j|j}|j |@t ||jS)Nrrcr{r)rrrtextr|rrr)rchat_generationsgchat_generations r-rzChatHuggingFace._to_chat_resultsj''* 5A,!!&&11CTCTO  # #O 4  5 (Z5J5J  r,cFddlm}t|js,t |jdr2|jj r|jj |_yt|jr|jj}nGt|jr|jj |_y|jj}|d}|D]#}|j|k(s|j|_%|j std|dy)z8Resolve the model_id from the LLM's inference_server_urlr)list_inference_endpointsrepo_idN*zIFailed to resolve model_id:Could not find model id for inference server: zBMake sure that your Hugging Face token has access to the endpoint.)huggingface_hubrrTrOhasattrrrfrYrr` endpoint_urlurl repositoryrB)rorravailable_endpointsendpoints r-rmz!ChatHuggingFace._resolve_model_ids = txx ( DHHi (TXX-=-= HH,,DM  .txx 8*.((*G*GL %dhh / HH--DM 8800L6s;+ 4H|||+ ( 3 3  4}}AAMTU r,) tool_choicetoolsrautononec |Dcgc] }t|}}||rt|dk7rtdt|dt|tr |dvrkdd|id}nct|t r|d}nMt|t r/|ddd|ddk7r)td |d |dddd td |||d <t| dd|i|Scc}w)a*Bind tool-like objects to this chat model. Assumes model is compatible with OpenAI tool-calling API. Args: tools: A list of tool definitions to bind to this chat model. Supports any tool definition handled by :meth:`langchain_core.utils.function_calling.convert_to_openai_tool`. tool_choice: Which tool to require the model to call. Must be the name of the single provided function or "auto" to automatically determine which function to call (if any), or a dict of the form: {"type": "function", "function": {"name": <>}}. **kwargs: Any additional parameters to pass to the :class:`~langchain.runnable.Runnable` constructor. zKWhen specifying `tool_choice`, you must provide exactly one tool. Received z tools.rr9r:)rur9rz Tool choice z/ was specified, but the only provided tool was .zEUnrecognized tool_choice type. Expected str, bool or dict. Received: rrr+) rlenrBr?r3boolr@rjbind)rorrrgr>formatted_toolsrps r- bind_toolszChatHuggingFace.bind_toolssE0EJJD1$7JJ  "{?#q( &&)/&:%;7D+s+&66 *%+[$9#KK.-a0 K.#A&z26:":.v67%&{m4-- 4{#4tCy!467 4  4  42%)?C 4{#4tCy!4;< 4  4  4$ {#   " : : :  I  *    BRV 6=d38ndHhFGH6=eD#w~/F$LMN 6=  6= $k1 2 6=p[)19$s)1D d38n  *3**r,rbN)9r) dataclassesrtypingrrrrrr r r r r langchain_core.callbacks.managerrrlangchain_core.language_modelsr*langchain_core.language_models.chat_modelsrlangchain_core.messagesrrrrrrlangchain_core.outputsrrrlangchain_core.runnablesrlangchain_core.toolsr%langchain_core.utils.function_callingrpydanticrtyping_extensionsr/langchain_huggingface.llms.huggingface_endpointr /langchain_huggingface.llms.huggingface_pipeliner!rr#r/rDrNrrTrYr]r`rbr+r,r-rs !   >DIH-)H$"OOR    "8 "8 "8JKKK$ S T  3 4 0#0$00#0$0C*mC*r,