a bg}@sdddlmZddlmZmZmZmZmZddlm Z m Z ddl m Z ddl mZGddde ZdS) )partial)AnyDictListOptionalSequence)AsyncCallbackManagerForLLMRunCallbackManagerForLLMRun)LLM)pre_initc@seZdZUdZeed<eed<dZeeed<dZ eeed<dZ ee eefed<dZ eeed<e e eefd d d Ze ed d d Zee e dddZdeeeeeeeedddZdeeeeeeeedddZdS) CTransformersa_C Transformers LLM models. To use, you should have the ``ctransformers`` python package installed. See https://github.com/marella/ctransformers Example: .. code-block:: python from langchain_community.llms import CTransformers llm = CTransformers(model="/path/to/ggml-gpt-2.bin", model_type="gpt2") clientmodelN model_type model_fileconfiglib)returncCs|j|j|j|jdS)zGet the identifying parameters.rrrrrselfrt/var/www/html/cobodadashboardai.evdpl.com/venv/lib/python3.9/site-packages/langchain_community/llms/ctransformers.py_identifying_params-s z!CTransformers._identifying_paramscCsdS)zReturn type of llm. ctransformersrrrrr _llm_type7szCTransformers._llm_type)valuesrcCsjzddlm}Wnty*tdYn0|dp6i}|j|df|d|d|dd ||d <|S) z5Validate that ``ctransformers`` package is installed.r)AutoModelForCausalLMz\Could not import `ctransformers` package. Please install it with `pip install ctransformers`rrrrr)rrrr )rr ImportErrorZfrom_pretrained)clsrrrrrrvalidate_environment<s"    z"CTransformers.validate_environment)promptstop run_managerkwargsrcKsJg}|pt}|j||ddD]}|||j||jdq d|S)aVGenerate text from a prompt. Args: prompt: The prompt to generate text from. stop: A list of sequences to stop generation when encountered. Returns: The generated text. Example: .. code-block:: python response = llm.invoke("Tell me a joke.") Tr"streamverbose)r Zget_noop_managerr appendon_llm_new_tokenr(join)rr!r"r#r$textZ _run_managerchunkrrr_callQs   zCTransformers._callcsPd}|rt|j|jd}d}|j||ddD]}|rB||IdH||7}q,|S)aAsynchronous Call out to CTransformers generate method. Very helpful when streaming (like with websockets!) Args: prompt: The prompt to pass into the model. stop: A list of strings to stop generation when encountered. Returns: The string generated by the model. Example: .. code-block:: python response = llm.invoke("Once upon a time, ") Nr'r)Tr%)rr+r(r )rr!r"r#r$Z text_callbackr-tokenrrr_acallms zCTransformers._acall)NN)NN)__name__ __module__ __qualname____doc__r__annotations__strrrrrrrpropertyrrr r rr r/rrr1rrrrr s>      r N) functoolsrtypingrrrrrZlangchain_core.callbacksrr Z#langchain_core.language_models.llmsr Zlangchain_core.utilsr r rrrrs