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Update app.py
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app.py
CHANGED
@@ -2,7 +2,7 @@ import gradio as gr
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from huggingface_hub import InferenceClient
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from langchain_community.document_loaders import PyPDFLoader
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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from langchain_community.vectorstores import FAISS
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from sentence_transformers import SentenceTransformer
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from langchain.chains import RetrievalQA
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from langchain_community.llms import HuggingFaceHub
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@@ -20,7 +20,7 @@ embeddings = SentenceTransformer("sentence-transformers/all-mpnet-base-v2")
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texts = [doc.page_content for doc in texts] # Get the text content from the documents
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embeddings = embeddings.encode(texts) # Get the embeddings for the texts
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vector_store = FAISS.
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# Initialize the HuggingFaceHub LLM
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llm = HuggingFaceHub(repo_id="HuggingFaceH4/zephyr-7b-beta", model_kwargs={"temperature": None, "top_p": None})
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from huggingface_hub import InferenceClient
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from langchain_community.document_loaders import PyPDFLoader
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from langchain.text_splitter import RecursiveCharacterTextSplitter
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from langchain_community.vectorstores.faiss import FAISS
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from sentence_transformers import SentenceTransformer
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from langchain.chains import RetrievalQA
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from langchain_community.llms import HuggingFaceHub
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texts = [doc.page_content for doc in texts] # Get the text content from the documents
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embeddings = embeddings.encode(texts) # Get the embeddings for the texts
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vector_store = FAISS.from_texts(texts, embeddings)
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# Initialize the HuggingFaceHub LLM
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llm = HuggingFaceHub(repo_id="HuggingFaceH4/zephyr-7b-beta", model_kwargs={"temperature": None, "top_p": None})
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