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app.py
Browse files
app.py
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import gradio as gr
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from transformers import pipeline
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# Ładowanie modelu raz
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chatbot = pipeline("text-generation", model="radlab/polish-gpt2-small", max_new_tokens=80)
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# Historia rozmowy
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conversation_history = ""
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def respond(user_input, history):
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global conversation_history
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conversation_history += f"Użytkownik: {user_input}\nAI: "
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response = chatbot(conversation_history, do_sample=True, top_k=50, top_p=0.95, temperature=0.7)[0]["generated_text"]
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ai_response = response[len(conversation_history):].split("Użytkownik:")[0].strip()
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conversation_history += ai_response + "\n"
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return conversation_history, conversation_history
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def clear_history():
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global conversation_history
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conversation_history = ""
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return "", ""
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# UI
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with gr.Blocks() as demo:
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gr.Markdown("# 🤖 Polski Chatbot AI\nNapisz coś po polsku, a AI odpowie!")
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chatbox = gr.Textbox(label="Twoja wiadomość")
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history_box = gr.Textbox(label="📖 Historia rozmowy", lines=10)
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submit_btn = gr.Button("Wyślij")
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clear_btn = gr.Button("🧹 Wyczyść")
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submit_btn.click(fn=respond, inputs=[chatbox, history_box], outputs=[history_box, history_box])
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clear_btn.click(fn=clear_history, outputs=[history_box, history_box])
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demo.launch()
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