9i9w ddlZddlZddlZddlZddlmZddlmZddl Z ddl m Z m Z m Z ddlmZddlmZmZmZmZdd lmZmZmZmZmZdd lmZmZdd lmZej@e!Z"erddl#Z#erdd l$m%Z%m&Z&dd lm'Z'ne(Z%da)e*e+e,e-e.e/dZ0eGddZ1ia2gdZ3d%dZ4dZ5d&dZ6d'dZ7dZ8dZ9GddZ:Gdde:Z;Gdde:Z<Gdd e:Z=Gd!d"e:Z>Gd#d$e%Z?y)(N) dataclass)Dict)HfFolderhf_hub_download list_spaces) AutoTokenizer)is_offline_modeis_openai_availableis_torch_availablelogging) TASK_MAPPINGTOOL_CONFIG_FILETool load_toolsupports_remote)CHAT_MESSAGE_PROMPTdownload_prompt)evaluate)StoppingCriteriaStoppingCriteriaList)AutoModelForCausalLMF)printrangefloatintboolstrc,eZdZUeed<eed<eed<y)PreTooltask descriptionrepo_idN)__name__ __module__ __qualname__r__annotations__c/var/www/html/backtest/airagagent/rag_env/lib/python3.12/site-packages/transformers/tools/agents.pyr!r!;s I Lr*r!)zimage-transformationz text-downloadz text-to-imagez text-to-videocrtrtjdiSt|}i}|D]v}|j}t |t d}t|d5}tj|}ddd|jdd}t|d | ||d <x|S#1swY8xYw) Nz;You are in offline mode, so remote tools are not available.)authorspace) repo_typezutf-8)encoding/r#r"r#r$name) r loggerinforidrropenjsonloadsplitr!) organizationspacestools space_infor$resolved_config_filereaderconfigr"s r+get_remote_toolsrCMs QR  -F Eg --.w8HT[\ & 9 'VYYv&F '}}S!"% 'Tvm?T^e ffVng L  ' 's B--B6 ctrytjd}|j}t }t j D]<\}}t||}|j}t||dt|j<>tsQtD]H}d}|j D]!\}} | j|k(s| t|<d}n|rrCritemsgetattrr#r!HUGGINGFACE_DEFAULT_TOOLSr4r "HUGGINGFACE_DEFAULT_TOOLS_FROM_HUBr" ValueError) main_module tools_module remote_tools task_nametool_class_name tool_classr#found tool_nametools r+_setup_default_toolsrW`s)).9K$$L#%L&2&8&8&:t" ?\?;  ,, 5<)Ydnr5s!*//2t  ; PIE#/#5#5#7  499 );?-i8 E    I;.M!NOO P"r*c,|tj}n|}|jD]g\}}||vs||vrt|tr|||<%|j |j n |j }|xr t|}t||||<i|S)Nremote) BASE_PYTHON_TOOLScopyrI isinstancerr$r"rr) codetoolboxrZ cached_toolsresolved_toolsr4rVtask_or_repo_id_remotes r+ resolve_toolsrds*//1%mmo N d t t~5  dD !#'N4 +/<<+?diiT\\OA!AG#,_W#MN4  N r*cddg}|jD]c\}}||vst|tr|j |jn |j}|d|d}|r|dz }|dz }|j |edj |dzS)Nz"from transformers import load_toolz = load_tool(""z , remote=True) )rIr]rr$r"appendjoin)r^r_rZ code_linesr4rVrblines r+get_tool_creation_coderns6;Jmmo  d t z$5 '+||';$))~o%6a8  O #D  $   99Z 4 ''r*cJ|jd}d}|t|krX||jjds6|dz }|t|kr#||jjds6dj |d|j }|t|k(r|dfS|dz }|}||jjds(|dz }||jjds(dj |||j }||fS)Nrir```r)r;lenlstrip startswithrkstrip)resultlinesidx explanation start_idxr^s r+clean_code_for_chatrzs LL E C E 5:#4#4#6#A#A%#H q E 5:#4#4#6#A#A%#H))E$3K(..0K c%jD  1HCICj!,,U3 qCj!,,U3 99U9S) * 0 0 2D  r*cd|}|jd\}}|j}|j}|jd}|ddvr|dd}|ddk(r|dd}dj|}||fS) NzI will use the following zAnswer:rir)rpz```pyz ```pythonrr2rp)r;rtrk)rurxr^rls r+clean_code_for_runr|s( 1F Y/K##%K ::t|ttfr|Dcic]}|j|}}nt|ts|j|i}|j!Dcic]\}}|t vs||}}}|jj#|t%|dkDrRdj'|j!D cgc] \} }d| d|c}} } t(j+d| d nHt%|dk(r:t|j-d }t(j+|d ||d |j/ycc}wcc}}wcc}} w) Nchat)moderunrri- : zSThe following tools have been replaced by the ones provided in `additional_tools`: .rz has been replaced by z# as provided in `additional_tools`.)rW __class__r%rchat_prompt_templaterun_prompt_templaterKr\_toolboxrlogr]listtupler4dictrIupdaterqrkr5warningkeysprepare_for_new_chat) selfrradditional_tools agent_nametr4rV replacementsnnamess r+__init__zAgent.__init__s^^,, $34H*[a$b!#23F Y^#_ 1668   '*T5M:7G#H!AFFAI#H #H 0$7$4$9$9;K#L 9I9O9O9Qw:4UY]vUvD$JwLw MM !1 2< 1$ \=O=O=Q"RTQRs"QC="RSjkpjqqrs\"a'L--/03$'=l4>P=QQtuv !!#$Ix#SsF=G!G0G returnc|jS)z-Get all tool currently available to the agent)rrs r+r_z Agent.toolboxs}}r*Fc dj|jjDcgc]\}}d|d|jc}}}|rP|j|j j d|}n |j}|tj d|z }|S|jj d|}|j d|}|Scc}}w)Nrirrz <>z<>z <>) rkr_rIr# chat_historyrreplacerr)rr" chat_moder4rVr#prompts r+ format_promptzAgent.format_promptsiiSWS_S_SeSeSg hZT42dV2d.>.>-?!@ hi   (22::?KX** )11*dC CF --55o{SF^^L$7F !isC c||_y)z Set the function use to stream results (which is `print` by default). Args: streamer (`callable`): The function to call when streaming results from the LLM. N)r)rstreamers r+ set_streamzAgent.set_streams r*) return_coderZc *|j|d}|j|ddg}||jzdz|_t |\}}|j d|||j d ||sw|j d t ||j||j |_|jj|t||j|jdSt||j| } | d|Sy) a Sends a new request to the agent in a chat. Will use the previous ones in its history. Args: task (`str`): The task to perform return_code (`bool`, *optional*, defaults to `False`): Whether to just return code and not evaluate it. remote (`bool`, *optional*, defaults to `False`): Whether or not to use remote tools (inference endpoints) instead of local ones. kwargs (additional keyword arguments, *optional*): Any keyword argument to send to the agent when evaluating the code. Example: ```py from transformers import HfAgent agent = HfAgent("https://api-inference.huggingface.co/models/bigcode/starcoder") agent.chat("Draw me a picture of rivers and lakes") agent.chat("Transform the picture so that there is a rock in there") ``` T)rzHuman:z=====stopri==Explanation from the agent== N" ==Code generated by the agent== ==Result==rZr`rY) r generate_onertrrzrrdr_r` chat_staterrrn rr"rrZkwargsrrurxr^ tool_codes r+rz Agent.chat s 0##DD#9""670C"D"V\\^3d:/7 T 3K=AB   HHs,##D)""6 ":.v6 T 3K=AB 8?@ HH% & -dDLL^b^o^o pD D$"3"36;;=I I.tT\\&QI[4&) )r*ctN)NotImplementedErrorrrrs r+rzAgent.generate_onecs!!r*cL|Dcgc]}|j||c}Scc}wr)rrpromptsrrs r+ generate_manyzAgent.generate_manygs#>EFF!!&$/FFFs!NNNF)r%r&r'__doc__rpropertyrrrr_rrrrrrrr)r*r+r~r~sc"$6c4i ).e(.T!(-U#*J"Gr*r~cFeZdZdZ dfd ZdZdZdZdZxZ S) OpenAiAgentu! Agent that uses the openai API to generate code. The openAI models are used in generation mode, so even for the `chat()` API, it's better to use models like `"text-davinci-003"` over the chat-GPT variant. Proper support for chat-GPT models will come in a next version. Args: model (`str`, *optional*, defaults to `"text-davinci-003"`): The name of the OpenAI model to use. api_key (`str`, *optional*): The API key to use. If unset, will look for the environment variable `"OPENAI_API_KEY"`. chat_prompt_template (`str`, *optional*): Pass along your own prompt if you want to override the default template for the `chat` method. Can be the actual prompt template or a repo ID (on the Hugging Face Hub). The prompt should be in a file named `chat_prompt_template.txt` in this repo in this case. run_prompt_template (`str`, *optional*): Pass along your own prompt if you want to override the default template for the `run` method. Can be the actual prompt template or a repo ID (on the Hugging Face Hub). The prompt should be in a file named `run_prompt_template.txt` in this repo in this case. additional_tools ([`Tool`], list of tools or dictionary with tool values, *optional*): Any additional tools to include on top of the default ones. If you pass along a tool with the same name as one of the default tools, that default tool will be overridden. Example: ```py from transformers import OpenAiAgent agent = OpenAiAgent(model="text-davinci-003", api_key=xxx) agent.run("Is the following `text` (in Spanish) positive or negative?", text="¡Este es un API muy agradable!") ``` cts td| tjj dd}| t d|t _||_t|)|||y)N?6v??? A)ztext-davinci-003NNNN r%r&r'rrrrrr __classcell__rs@r+rrls5#N!!   8< @ :@r*rcJeZdZdZ dfd ZdZdZdZdZxZ S)AzureOpenAiAgentu Agent that uses Azure OpenAI to generate code. See the [official documentation](https://learn.microsoft.com/en-us/azure/cognitive-services/openai/) to learn how to deploy an openAI model on Azure The openAI models are used in generation mode, so even for the `chat()` API, it's better to use models like `"text-davinci-003"` over the chat-GPT variant. Proper support for chat-GPT models will come in a next version. Args: deployment_id (`str`): The name of the deployed Azure openAI model to use. api_key (`str`, *optional*): The API key to use. If unset, will look for the environment variable `"AZURE_OPENAI_API_KEY"`. resource_name (`str`, *optional*): The name of your Azure OpenAI Resource. If unset, will look for the environment variable `"AZURE_OPENAI_RESOURCE_NAME"`. api_version (`str`, *optional*, default to `"2022-12-01"`): The API version to use for this agent. is_chat_mode (`bool`, *optional*): Whether you are using a completion model or a chat model (see note above, chat models won't be as efficient). Will default to `gpt` being in the `deployment_id` or not. chat_prompt_template (`str`, *optional*): Pass along your own prompt if you want to override the default template for the `chat` method. Can be the actual prompt template or a repo ID (on the Hugging Face Hub). The prompt should be in a file named `chat_prompt_template.txt` in this repo in this case. run_prompt_template (`str`, *optional*): Pass along your own prompt if you want to override the default template for the `run` method. Can be the actual prompt template or a repo ID (on the Hugging Face Hub). The prompt should be in a file named `run_prompt_template.txt` in this repo in this case. additional_tools ([`Tool`], list of tools or dictionary with tool values, *optional*): Any additional tools to include on top of the default ones. If you pass along a tool with the same name as one of the default tools, that default tool will be overridden. Example: ```py from transformers import AzureOpenAiAgent agent = AzureAiAgent(deployment_id="Davinci-003", api_key=xxx, resource_name=yyy) agent.run("Is the following `text` (in Spanish) positive or negative?", text="¡Este es un API muy agradable!") ``` c ts td||_dt_| t j jdd}| td|t_ | t j jdd}| tdd|dt_ |t_ |d |jv}||_ t |=||| y) NrazureAZURE_OPENAI_API_KEYzYou need an Azure openAI key to use `AzureOpenAIAgent`. If you have one, set it in your env with `os.environ['AZURE_OPENAI_API_KEY'] = xxx.AZURE_OPENAI_RESOURCE_NAMEzYou need a resource_name to use `AzureOpenAIAgent`. If you have one, set it in your env with `os.environ['AZURE_OPENAI_RESOURCE_NAME'] = xxx.zhttps://z.openai.azure.comrr)r r deployment_idrapi_typerrrrMrapi_base api_versionlower is_chat_modelrr) rrr resource_namerrrrrrs r+rzAzureOpenAiAgent.__init__s#$\] ]*! ?jjnn%;TBG ?=  %FN  JJNN+GNM  C  !)7HIFO(  !]%8%8%::M* !5 3-  r*c|jr |Dcgc]}|j||c}S|j||Scc}wrrrrrs r+rzAzureOpenAiAgent.generate_many,sB   DKL&D''5L L,,Wd; ;Ms?cj|jr|j||S|j|g|dS)Nrrrs r+rzAzureOpenAiAgent.generate_one2s8   &&vt4 4,,fXt?6v???r)NNz 2022-12-01NNNNrrs@r+rrs<-d ! , \< @ :@r*rc,eZdZdZ dfd ZdZxZS)HfAgentuc Agent that uses an inference endpoint to generate code. Args: url_endpoint (`str`): The name of the url endpoint to use. token (`str`, *optional*): The token to use as HTTP bearer authorization for remote files. If unset, will use the token generated when running `huggingface-cli login` (stored in `~/.huggingface`). chat_prompt_template (`str`, *optional*): Pass along your own prompt if you want to override the default template for the `chat` method. Can be the actual prompt template or a repo ID (on the Hugging Face Hub). The prompt should be in a file named `chat_prompt_template.txt` in this repo in this case. run_prompt_template (`str`, *optional*): Pass along your own prompt if you want to override the default template for the `run` method. Can be the actual prompt template or a repo ID (on the Hugging Face Hub). The prompt should be in a file named `run_prompt_template.txt` in this repo in this case. additional_tools ([`Tool`], list of tools or dictionary with tool values, *optional*): Any additional tools to include on top of the default ones. If you pass along a tool with the same name as one of the default tools, that default tool will be overridden. Example: ```py from transformers import HfAgent agent = HfAgent("https://api-inference.huggingface.co/models/bigcode/starcoder") agent.run("Is the following `text` (in Spanish) positive or negative?", text="¡Este es un API muy agradable!") ``` c||_|!dtj|_n4|j ds|j dr||_n d||_t ||||y)NzBearer BearerBasicr) url_endpointr get_tokentokenrsrr)rrrrrrrs r+rzHfAgent.__init__lsw) ="8:#7#7#9":;DJ   h '5+;+;G+DDJ"5'*DJ !5 3-  r*cd|ji}|dd|dd}tj|j||}|jdk(r;t j dtjd |j|S|jdk7r)td |jd |j|jd d }|D]$}|j|s|dt| cS|S)N AuthorizationrF)max_new_tokensreturn_full_textr)inputs parameters)r9headersiz=Getting rate-limited, waiting a tiny bit before trying again.rzError rrgenerated_text)rrequestspostr status_coder5r6timesleep _generate_onerMr9endswithrq)rrrrr responserustop_seqs r+rzHfAgent.generate_one|s"DJJ/-0eUYZ  ==!2!2Q   3 & KKW X JJqM%%f- -  ! !S (vh&:&:%;2hmmo=NOP P#$45 0Hx(.X// 0 r*)NNNN)r%r&r'rrrrrs@r+rrLs@os r*rcJeZdZdZdfd ZedZedZdZ xZ S) LocalAgenta Agent that uses a local model and tokenizer to generate code. Args: model ([`PreTrainedModel`]): The model to use for the agent. tokenizer ([`PreTrainedTokenizer`]): The tokenizer to use for the agent. chat_prompt_template (`str`, *optional*): Pass along your own prompt if you want to override the default template for the `chat` method. Can be the actual prompt template or a repo ID (on the Hugging Face Hub). The prompt should be in a file named `chat_prompt_template.txt` in this repo in this case. run_prompt_template (`str`, *optional*): Pass along your own prompt if you want to override the default template for the `run` method. Can be the actual prompt template or a repo ID (on the Hugging Face Hub). The prompt should be in a file named `run_prompt_template.txt` in this repo in this case. additional_tools ([`Tool`], list of tools or dictionary with tool values, *optional*): Any additional tools to include on top of the default ones. If you pass along a tool with the same name as one of the default tools, that default tool will be overridden. Example: ```py import torch from transformers import AutoModelForCausalLM, AutoTokenizer, LocalAgent checkpoint = "bigcode/starcoder" model = AutoModelForCausalLM.from_pretrained(checkpoint, device_map="auto", torch_dtype=torch.bfloat16) tokenizer = AutoTokenizer.from_pretrained(checkpoint) agent = LocalAgent(model, tokenizer) agent.run("Draw me a picture of rivers and lakes.") ``` cF||_||_t| |||y)Nr)r tokenizerrr)rrrrrrrs r+rzLocalAgent.__init__s, " !5 3-  r*c ltj|fi|}tj|fi|}|||S)a Convenience method to build a `LocalAgent` from a pretrained checkpoint. Args: pretrained_model_name_or_path (`str` or `os.PathLike`): The name of a repo on the Hub or a local path to a folder containing both model and tokenizer. kwargs (`Dict[str, Any]`, *optional*): Keyword arguments passed along to [`~PreTrainedModel.from_pretrained`]. Example: ```py import torch from transformers import LocalAgent agent = LocalAgent.from_pretrained("bigcode/starcoder", device_map="auto", torch_dtype=torch.bfloat16) agent.run("Draw me a picture of rivers and lakes.") ``` )rfrom_pretrainedr )clspretrained_model_name_or_pathrrrs r+rzLocalAgent.from_pretraineds?*%445R]V\]!112OZSYZ 5)$$r*ct|jdr0t|jjj dS|jj D]}|j cSy)N hf_device_mapr)hasattrrrr"valuesr device)rparams r+ _model_devicezLocalAgent._model_devicesY 4:: / 00779:1= =ZZ**, E<<  r*c|j|dj|j}|djd}t t ||jg}|j j|dd|}|jj|dj|d}|D]#}|j|s|dt| }%|S)Npt)return_tensors input_idsrr)r stopping_criteriar) rtor'shaperStopSequenceCriteriargeneratedecodetolistrrq) rrrencoded_inputssrc_lenr,outputsrurs r+rzLocalAgent.generate_onestDGGHZHZ[ -33A602FtT^^2\1]^**%% ; 'O`& &&wqz'8'8':78'DE 2Hx( 03x=.1 2 r*r) r%r&r'rr classmethodrrr'rrrs@r+rrs;!F %%0  r*rc"eZdZdZdZdefdZy)r/a6 This class can be used to stop generation whenever a sequence of tokens is encountered. Args: stop_sequences (`str` or `List[str]`): The sequence (or list of sequences) on which to stop execution. tokenizer: The tokenizer used to decode the model outputs. cFt|tr|g}||_||_yr)r]rstop_sequencesr)rr9rs r+rzStopSequenceCriteria.__init__s# nc *,-N,"r*rc |jj|jdtfd|jDS)Nrc3@K|]}j|ywr)r).0 stop_sequencedecoded_outputs r+ z0StopSequenceCriteria.__call__..scm>**=9cs)rr1r2anyr9)rr+scoresrr>s @r+__call__zStopSequenceCriteria.__call__s<..y/?/?/A!/DEctObObcccr*N)r%r&r'rrrrBr)r*r+r/r/s# dtdr*r/)zhuggingface-tools)FNr)@importlib.utilrGr9rr dataclassesrtypingrrhuggingface_hubrrr models.autor utilsr r r r baserrrrrrrrpython_interpreterr get_loggerr%r5r generationrrrobjectrFrrrrrrr[r!rKrLrCrWrdrnrzr|r~rrrrr/r)r*r+rNs/" !BB'UURR9(   H %C2         &"&">& ( $  eGeGP_@%_@D{@u{@|DeDNZZzd+dr*