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Create app.py

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  1. app.py +26 -0
app.py ADDED
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+ import gradio as gr
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+ import duckdb
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+ from langchain_community.embeddings import HuggingFaceEmbeddings
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+ from langchain_community.vectorstores import DuckDB
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+
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+ conn = duckdb.connect('your_database.duckdb')
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+
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+ embedding_function = HuggingFaceEmbeddings()
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+ vector_store = DuckDB(conn, embedding_function)
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+
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+ # Define a data structure for user data
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+ class User:
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+ def __init__(self, phone: str, features: str):
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+ self.phone = phone
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+ self.features = features
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+ def create(self):
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+ vector_store.add_texts([f'#features\n{self.features}\n\n#phone\n{self.phone}')
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+ def search(self):
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+ return vector_store.similarity_search(self.features, k=1)
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+
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+ def greet(name):
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+ return "Hello " + name + "!!"
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+
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+ demo = gr.Interface(fn=greet, inputs=["textbox", "button"], outputs="text")
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+ # demo.launch()
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+ demo.launch(share=True, auth=("username", "password"))