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Update app.py
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app.py
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@@ -3,7 +3,8 @@ import tempfile
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import logging
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from typing import List
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from langchain_community.document_loaders import PyPDFLoader
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from langchain_community.embeddings import HuggingFaceEmbeddings
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from langchain_community.vectorstores import FAISS
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from langchain_community.llms import HuggingFacePipeline
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from langchain.chains.summarize import load_summarize_chain
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@@ -18,7 +19,7 @@ logger = logging.getLogger(__name__)
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# Constants
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EMBEDDING_MODEL = 'sentence-transformers/all-MiniLM-L6-v2'
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DEFAULT_MODEL = "llava-v1.6-mistral-7b"
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@st.cache_resource
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def load_embeddings():
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@@ -50,7 +51,7 @@ def process_pdf(file) -> List[Document]:
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loader = PyPDFLoader(file_path=temp_file_path)
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pages = loader.load()
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text_splitter = RecursiveCharacterTextSplitter(chunk_size=
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documents = text_splitter.split_documents(pages)
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return documents
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except Exception as e:
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import logging
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from typing import List
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from langchain_community.document_loaders import PyPDFLoader
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#from langchain_community.embeddings import HuggingFaceEmbeddings
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from langchain_huggingface import HuggingFaceEmbeddings
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from langchain_community.vectorstores import FAISS
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from langchain_community.llms import HuggingFacePipeline
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from langchain.chains.summarize import load_summarize_chain
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# Constants
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EMBEDDING_MODEL = 'sentence-transformers/all-MiniLM-L6-v2'
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DEFAULT_MODEL = "llava-v1.6-mistral-7b-hf"
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@st.cache_resource
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def load_embeddings():
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loader = PyPDFLoader(file_path=temp_file_path)
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pages = loader.load()
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text_splitter = RecursiveCharacterTextSplitter(chunk_size=4000, chunk_overlap=200)
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documents = text_splitter.split_documents(pages)
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return documents
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except Exception as e:
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