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Update app.py
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app.py
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@@ -83,6 +83,13 @@ Settings.embed_model = HuggingFaceEmbedding(model_name="sentence-transformers/al
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vector_store = ChromaVectorStore(chroma_collection=collection)
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index = VectorStoreIndex.from_vector_store(vector_store, embed_model=Settings.embed_model)
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query_engine = index.as_query_engine()
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def rag(input_text, file):
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if (file):
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# documents = []
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@@ -107,30 +114,24 @@ def rag(input_text, file):
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query_engine = index.as_query_engine()
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return query_engine.query(input_text)
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with gr.Column(scale=1):
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out = gr.Textbox(label="Odgovor:", lines=6)
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sub = gr.Button("Pokreni")
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u.upload(upload_file, u, file_out)
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sub.click(rag, inp, out)
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iface.launch()
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vector_store = ChromaVectorStore(chroma_collection=collection)
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index = VectorStoreIndex.from_vector_store(vector_store, embed_model=Settings.embed_model)
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query_engine = index.as_query_engine()
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def upload_file(filepath):
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documents = SimpleDirectoryReader(filepath).load_data()
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index = VectorStoreIndex.from_documents(documents)
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query_engine = index.as_query_engine()
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return filepath
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def rag(input_text, file):
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if (file):
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# documents = []
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query_engine = index.as_query_engine()
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return query_engine.query(input_text)
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iface = gr.Interface(fn=rag, inputs=[gr.Textbox(label="Pitanje:", lines=6), gr.File()],
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outputs=[gr.Textbox(label="Odgovor:", lines=6)],
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title="Kako Vam mogu pomoći?",
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description= "UChat"
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)
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#with gr.Blocks() as iface:
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# gr.Markdown("Uchat")
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# file_out = gr.File()
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# with gr.Row():
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# with gr.Column(scale=1):
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# inp = gr.Textbox(label="Pitanje:", lines=6)
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# u = gr.UploadButton("Upload a file", file_count="single")
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# with gr.Column(scale=1):
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# out = gr.Textbox(label="Odgovor:", lines=6)
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# sub = gr.Button("Pokreni")
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#
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# u.upload(upload_file, u, file_out)
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# sub.click(rag, inp, out)
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iface.launch()
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