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import openai, os |
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openai.api_key = "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" |
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from llama_index.core import SimpleDirectoryReader |
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documents = SimpleDirectoryReader( |
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input_files = ["./HFNWAY.pdf"] |
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).load_data() |
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from llama_index.core.schema import Document |
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document = Document(text = "\n\n".join([doc.text for doc in documents])) |
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from llama_index.core import VectorStoreIndex |
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from llama_index.core import ServiceContext |
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from llama_index.llms.openai import OpenAI |
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llm = OpenAI(model= "gpt-3.5-turbo", temperature=0.2) |
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service_context = ServiceContext.from_defaults( |
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llm = llm, embed_model = "local:BAAI/bge-small-en-v1.5" |
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) |
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index = VectorStoreIndex.from_documents([document], service_context=service_context) |
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query_engine = index.as_query_engine() |
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import gradio as gr |
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def chat_interface(message, history): |
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response = str(query_engine.query(message)) |
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history.append([message, response]) |
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return response |
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history = [] |
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interface = gr.ChatInterface(chat_interface, examples = ["Who is DAAJI?", "What is Heartfulness way of meditation all about?"] , title = "HFN BOT") |
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interface.launch() |
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