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app.py
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@@ -8,24 +8,17 @@ from transformers import AutoTokenizer
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bshtml_dir_loader = DirectoryLoader('./data/', loader_cls=BSHTMLLoader)
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data = bshtml_dir_loader.load()
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print("loading documents")
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bloomz_tokenizer = AutoTokenizer.from_pretrained("bigscience/bloomz-1b7")
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print("add tokenizer")
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text_splitter = CharacterTextSplitter.from_huggingface_tokenizer(bloomz_tokenizer,
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chunk_size=100,
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chunk_overlap=0,
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separator="\n")
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print("Add text spliters")
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documents = text_splitter.split_documents(data)
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print("Getting HF embeddings")
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embeddings = HuggingFaceEmbeddings()
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llm = HuggingFacePipeline.from_model_id(
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@@ -33,24 +26,17 @@ llm = HuggingFacePipeline.from_model_id(
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task="text-generation",
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model_kwargs={"temperature" : 0, "max_length" : 500})
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print("Adding LLM hugginFacePipeline with bigscience bloomz")
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vectordb = Chroma.from_documents(documents=documents, embedding=embeddings)
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print("Getting vectors")
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doc_retriever = vectordb.as_retriever()
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print("Creating Retreiver")
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shakespeare_qa = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=doc_retriever)
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print("Add shakespeare qa")
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def query(query):
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shakespeare_qa.run(query)
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iface = gr.Interface(fn=query, inputs="text", outputs="text")
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iface.launch()
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bshtml_dir_loader = DirectoryLoader('./data/', loader_cls=BSHTMLLoader)
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data = bshtml_dir_loader.load()
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bloomz_tokenizer = AutoTokenizer.from_pretrained("bigscience/bloomz-1b7")
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text_splitter = CharacterTextSplitter.from_huggingface_tokenizer(bloomz_tokenizer,
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chunk_size=100,
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chunk_overlap=0,
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separator="\n")
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documents = text_splitter.split_documents(data)
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embeddings = HuggingFaceEmbeddings()
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llm = HuggingFacePipeline.from_model_id(
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task="text-generation",
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model_kwargs={"temperature" : 0, "max_length" : 500})
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vectordb = Chroma.from_documents(documents=documents, embedding=embeddings)
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doc_retriever = vectordb.as_retriever()
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shakespeare_qa = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=doc_retriever)
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def query(query):
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shakespeare_qa.run(query)
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iface = gr.Interface(fn=query, inputs="text", outputs="text")
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iface.launch()
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