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Update app.py
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app.py
CHANGED
@@ -112,12 +112,14 @@ for f in os.listdir("multiple_docs"):
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splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=10)
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docs = splitter.split_documents(docs)
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#
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embedding_model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
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#
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vectorstore = Chroma
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vectorstore.persist()
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# Load the Hugging Face model for text generation
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@@ -172,3 +174,4 @@ demo.launch(debug=True)
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splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=10)
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docs = splitter.split_documents(docs)
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# Extract the content from documents and create embeddings
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embedding_model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
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texts = [doc.page_content for doc in docs]
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embeddings = embedding_model.encode(texts)
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# Create a Chroma vector store and add documents and their embeddings
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vectorstore = Chroma(persist_directory="./data")
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vectorstore.add_texts(texts, embeddings)
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vectorstore.persist()
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# Load the Hugging Face model for text generation
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