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NickNYU
[bugfix]fix the cut-off issue due to LLM predict token limit(256 for openai python lib default), by setting temperature to 0 and set LLM predict method from compact-refine to refine
bd59653
| from abc import abstractmethod, ABC | |
| from langchain.base_language import BaseLanguageModel | |
| from langchain.embeddings.base import Embeddings as LCEmbeddings | |
| from langchain.embeddings.openai import OpenAIEmbeddings | |
| from langchain.llms import AzureOpenAI | |
| class BaseLangChainManager(ABC): | |
| def __init__(self) -> None: | |
| super().__init__() | |
| def get_embedding(self) -> LCEmbeddings: | |
| pass | |
| def get_llm(self) -> BaseLanguageModel: | |
| pass | |
| class LangChainAzureManager(BaseLangChainManager): | |
| def __init__(self) -> None: | |
| super().__init__() | |
| self.embedding = OpenAIEmbeddings(client=None, chunk_size=1) | |
| self.llm = AzureOpenAI( | |
| deployment_name="text-davinci-003", | |
| # model_name="text-davinci-003", | |
| model="text-davinci-003", | |
| client=None, | |
| # temperature set to 0.0(default 0.7) to get a certain answer from OpenAI, | |
| # as a wiki robot we won't want to get flexible answers | |
| temperature=0.0, | |
| # GPT-3 default is 4096, however, openai.py default is 256 | |
| max_tokens=2048, | |
| ) | |
| # Override | |
| def get_embedding(self) -> LCEmbeddings: | |
| return self.embedding | |
| # Override | |
| def get_llm(self) -> BaseLanguageModel: | |
| return self.llm | |
| class LangChainHuggingFaceManager(BaseLangChainManager): | |
| def __init__(self) -> None: | |
| super().__init__() | |
| from transformers import AutoTokenizer, AutoModel | |
| AutoTokenizer.from_pretrained("GanymedeNil/text2vec-large-chinese") | |
| AutoModel.from_pretrained("GanymedeNil/text2vec-large-chinese") | |
| self.embedding = OpenAIEmbeddings(client=None, chunk_size=1) | |
| self.llm = AzureOpenAI( | |
| deployment_name="text-davinci-003", | |
| # model_name="text-davinci-003", | |
| model="text-davinci-003", | |
| client=None, | |
| ) | |
| # Override | |
| def get_embedding(self) -> LCEmbeddings: | |
| return self.embedding | |
| # Override | |
| def get_llm(self) -> BaseLanguageModel: | |
| return self.llm | |