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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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conn = duckdb.connect('your_database.duckdb') |
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embedding_function = HuggingFaceEmbeddings() |
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vector_store = DuckDB(conn, embedding_function) |
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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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def greet(name): |
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return "Hello " + name + "!!" |
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demo = gr.Interface(fn=greet, inputs=["textbox", "button"], outputs="text") |
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demo.launch(share=True, auth=("username", "password")) |