tj#ddlZddlZddlZddlZddlZddlZddlmZmZm Z m Z m Z ddl Z ddl mZddlmZddlmZmZddlmZddlmZmZmZejeZdZd ZGd d eZdS) N)AnyDictListMappingOptional)CallbackManagerForLLMRun)LLM)get_from_dict_or_envpre_init) get_fields) ConfigDictFieldmodel_validator c PeZdZUdZdZeed<dZeed<dZeed<dZ eed<dZ eed<dZ eed<gZ e eed <dZeed <dZeed < ee Zeeefed < dZeed<dZeed<dZeeed<edZededeeefdefdZededefdZe de!eeffdZ"e defdZ#d%dZ$d%dZ%defdZ&e defdZ' d&d ed!ee(d"ee)d#edef d$Z*dS)'BeamaBeam API for gpt2 large language model. To use, you should have the ``beam-sdk`` python package installed, and the environment variable ``BEAM_CLIENT_ID`` set with your client id and ``BEAM_CLIENT_SECRET`` set with your client secret. Information on how to get this is available here: https://docs.beam.cloud/account/api-keys. The wrapper can then be called as follows, where the name, cpu, memory, gpu, python version, and python packages can be updated accordingly. Once deployed, the instance can be called. Example: .. code-block:: python llm = Beam(model_name="gpt2", name="langchain-gpt2", cpu=8, memory="32Gi", gpu="A10G", python_version="python3.8", python_packages=[ "diffusers[torch]>=0.10", "transformers", "torch", "pillow", "accelerate", "safetensors", "xformers",], max_length=50) llm._deploy() call_result = llm._call(input) model_namenamecpumemorygpupython_versionpython_packages max_lengthurl)default_factory model_kwargsbeam_client_idbeam_client_secretNapp_idforbid)extrabefore)modevaluesreturnc\dt|D}|di}t|D]U}||vrO||vrt d|dt |d|d||||<V||d<|S)z>Build extra kwargs from additional params that were passed in.ch|] }|j S)alias).0fields [/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/langchain_community/llms/beam.py z#Beam.build_extra..Ts#V#V#VEEK#V#V#VrzFound z supplied twice.zJ was transferred to model_kwargs. Please confirm that z is what you intended.)r r'getlist ValueErrorloggerwarningpop)clsr'all_required_field_namesr$ field_names r/ build_extrazBeam.build_extraPs$W#VZ__=S=S=U=U#V#V#V  >2..v,, ; ;J!999&&$%Jj%J%J%JKKK#NN)3NNN%+JJz$:$:j!!&~ r1c^t|dd}t|dd}||d<||d<|S)z?Validate that api key and python package exists in environment.r BEAM_CLIENT_IDr!BEAM_CLIENT_SECRET)r )r8r'r r!s r/validate_environmentzBeam.validate_environmentcsT. $&6  2 (*>  $2 '9#$ r1c t|j|j|j|j|j|j|j|j|jd S)zGet the identifying parameters. rrrrrrrrrrAselfs r/_identifying_paramszBeam._identifying_paramspsC/I8k8"1#3/ -   r1cdS)zReturn type of llm.beamr+rBs r/ _llm_typezBeam._llm_types vr1c tjd}d}t|d5}|||j|j|j|j|j |j ddddS#1swxYwYdS)zBCreates a Python file which will contain your Beam app definition.a import beam # The environment your code will run on app = beam.App( name="{name}", cpu={cpu}, memory="{memory}", gpu="{gpu}", python_version="{python_version}", python_packages={python_packages}, ) app.Trigger.RestAPI( inputs={{"prompt": beam.Types.String(), "max_length": beam.Types.String()}}, outputs={{"text": beam.Types.String()}}, handler="run.py:beam_langchain", ) zapp.pyw)rrrrrrN) textwrapdedentopenwriteformatrrrrrrrCscript script_namefiles r/ app_creationzBeam.app_creations   . +s # # t JJ ;#'#6$($8                      sA BBBctjd}d}t|d5}|||jddddS#1swxYwYdS)z5Creates a Python file which will be deployed on beam.a  import os import transformers from transformers import GPT2LMHeadModel, GPT2Tokenizer model_name = "{model_name}" def beam_langchain(**inputs): prompt = inputs["prompt"] length = inputs["max_length"] tokenizer = GPT2Tokenizer.from_pretrained(model_name) model = GPT2LMHeadModel.from_pretrained(model_name) encodedPrompt = tokenizer.encode(prompt, return_tensors='pt') outputs = model.generate(encodedPrompt, max_length=int(length), do_sample=True, pad_token_id=tokenizer.eos_token_id) output = tokenizer.decode(outputs[0], skip_special_tokens=True) print(output) # noqa: T201 return {{"text": output}} zrun.pyrI)rN)rJrKrLrMrNrrOs r/ run_creationzBeam.run_creations   2 +s # # Bt JJv}}}@@ A A A B B B B B B B B B B B B B B B B B Bs/A##A'*A'c ddl}|jdkrtn#t$rtdwxYw||t jdddd}|jdkr|j}t || d}|D]r}| d r[| d d |_ | d d |_|j cSst!d|t!d|j) Call to Beam.rNrzCould not import beam python package. Please install it with `curl https://raw.githubusercontent.com/slai-labs/get-beam/main/get-beam.sh -sSfL | sh`.zbeam deploy app.pyT)shellcapture_outputtext z. i Send requests to: https://apps.beam.cloud//:z\Failed to retrieve the appID from the deployment output. Deployment output: zDeployment failed. Error: )rF__path__ ImportErrorrSrU subprocessrun returncodestdoutr5infosplit startswithr"striprr4stderr)rCrFprocessoutputlineslines r/_deployz Beam._deploys  KKK}""!!#   :    . 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