j%dZddlmZmZmZmZmZmZmZm Z m Z m Z ddl m Z mZddlmZddlmZddlmZmZmZmZmZddlmZmZmZmZddlmZdd l m!Z!dd l"m#Z#dd l$m%Z%d Z&Gd deZ'y)zMLX Chat Wrapper.) AnyCallableDictIteratorListLiteralOptionalSequenceTypeUnion)AsyncCallbackManagerForLLMRunCallbackManagerForLLMRun)LanguageModelInput) BaseChatModel) AIMessageAIMessageChunk BaseMessage HumanMessage SystemMessage)ChatGenerationChatGenerationChunk ChatResult LLMResult)Runnable)BaseTool)convert_to_openai_tool) MLXPipelinez4You are a helpful, respectful, and honest assistant.c eZdZUdZeed<eeZeed<dZ e ed<de ffd Z dd e e d ee ed eede d ef d Z dd e e d ee ed eede d ef dZ dd e e dedeed efdZde d efdZeded efdZed efdZ dd e e d ee ed eede d eef dZ ddde!e"e#ee fe$e%e&fdee"eee'defde d e(e)e fffdZ*xZ+S)ChatMLXaMLX chat models. Works with `MLXPipeline` LLM. To use, you should have the ``mlx-lm`` python package installed. Example: .. code-block:: python from langchain_community.chat_models import chatMLX from langchain_community.llms import MLXPipeline llm = MLXPipeline.from_model_id( model_id="mlx-community/quantized-gemma-2b-it", ) chat = chatMLX(llm=llm) llmcontentsystem_messageN tokenizerkwargsc Zt|di||jj|_y)N)super__init__r r$)selfr% __class__s m/var/www/html/Fitness-lenito-AI-main/venv/lib/python3.12/site-packages/langchain_community/chat_models/mlx.pyr)zChatMLX.__init__Ds$ "6"++messagesstop run_managerreturnc |j|}|jjd|g||d|}|j|SN)promptsr/r0r')_to_chat_promptr _generate_to_chat_resultr*r.r/r0r% llm_input llm_results r,r6zChatMLX._generateHsS((2 'TXX'' Kd  GM ##J//r-cK|j|}|jjd|g||d|d{}|j|S7wr3)r5r _agenerater7r8s r,r<zChatMLX._agenerateUsa((2 .488.. Kd  GM  ##J// s6AAAtokenizereturn_tensorsc|s tdt|dts td|Dcgc]}|j|}}|jj ||d|Scc}w)zHConvert a list of messages into a prompt format expected by wrapped LLM.z+At least one HumanMessage must be provided!z$Last message must be a HumanMessage!T)r=add_generation_promptr>) ValueError isinstancer_to_chatml_formatr$apply_chat_template)r*r.r=r>mmessages_dictss r,r5zChatMLX._to_chat_promptbszJK K(2, 5CD D=EFX$003XF~~11 "&) 2  GsA)messagect|trd}n=t|trd}n*t|trd}nt dt |||j dS)z+Convert LangChain message to ChatML format.system assistantuserzUnknown message type: )roler")rCrrrrBtyper")r*rHrMs r,rDzChatMLX._to_chatml_formatwsW g} -D  +D  .D5d7m_EF F99r-r:cg}|jdD]>}tt|j|j}|j |@t ||jS)Nrr!)rHgeneration_info) generations llm_output)rQrrtextrPappendrrR)r:chat_generationsgchat_generations r,r7zChatMLX._to_chat_resultse''*A,!!&&11CTCTO  # #O 4 + (Z5J5J  r-cy)Nzmlx-chat-wrapperr')r*s r, _llm_typezChatMLX._llm_types!r-c+$Kddlm}ddlm} ddlm}ddlm}m}ddlm}|jd|jjxsi} | jdd} | jdd } | jd d} | jd d} | jd d }| jdd}| jdd}|j|dd}|j|d}|jj}|| xsd|||}|d| | }t|||jj ||t#| D]\\}}}d}t%|t&s*|jj)|j+}n|jj)|}|r/t-t/|}|r|j1|||||k(s|||vsyy#t$r tdwxYww)Nr) generate_step)make_logits_processors make_samplerzTCould not import mlx_lm python package. Please install it with `pip install mlx_lm`. model_kwargstempg max_tokensdrepetition_penaltyrepetition_context_sizetop_pg?min_pmin_tokens_to_keepTnp)r=r>)samplerlogits_processorsr!)rH)chunk)mlx.corecore mlx_lm.utilsr[mlx_lm.sample_utilsr\r] ImportErrorgetr pipeline_kwargsr5arrayr$ eos_token_idzipmodelrangerCintdecodeitemrron_llm_new_token)r*r.r/r0r%mxr[r\r]r^r_max_new_tokensrbrcrdrerfr9 prompt_tokensrtrirjtokenprobnrSrks r,_streamzChatMLX._streams .  ! P 2zz.$((2J2JKQr "&&vs3*..|SA.:.>.> $/ 2>1A1A %t2 $''5#''5"."2"23G"K((DQU(V 1. ~~22 t{sE5:LM2 $&= !$ "3   . !! MUD1#'DeS)~~,,UZZ\:~~,,U3+N44PQ00U0C  $)9ddl3! = ?  s( HG8G H/H4H8H  H) 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. rgzKWhen specifying `tool_choice`, you must provide exactly one tool. Received z tools.rfunctionname)rNrrz Tool choice z/ was specified, but the only provided tool was .zEUnrecognized tool_choice type. Expected str, bool or dict. Received: rrr') rlenrBrCstrbooldictr(bind)r*rrr%toolformatted_toolsr+s r, bind_toolszChatMLX.bind_toolssF0EJJED1$7EJ  "{?#q( &&)/&:%;7D+s+&66 *%+[$9#KK.-a0 K.#A&z26:":.v67%&{m4-- 0{# 0tCy! 067 0  0  0 %)?C 0{# 0tCy! 0;< 0  0  0 (,  {#  !   * : : :  I  *    "3"" %):> F{#FtCy!F67 F  F % & FXRV 6=d38ndHhFGH6=eD#w~/F$LMN 6=  6= $k1 2 6=6=r-rN)(rtypingrrrrrrr r r r langchain_core.callbacks.managerr rlangchain_core.language_modelsr*langchain_core.language_models.chat_modelsrlangchain_core.messagesrrrrrlangchain_core.outputsrrrrlangchain_core.runnablesrlangchain_core.toolsr%langchain_core.utils.function_callingr%langchain_community.llms.mlx_pipelinerrrr'r-r,rsZ   >D .)H=Ri=mi=r-