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Browse files- app.py +38 -0
- requirements.txt +2 -0
app.py
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import gradio as gr
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from llama_cpp import Llama
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# Load the Llama model
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llm = Llama.from_pretrained(
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repo_id="krishna195/second_guff",
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filename="unsloth.Q4_K_M.gguf",
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)
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# Define the chatbot function
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def chatbot_response(user_input):
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band_name = " from Curly Strings"
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formatted_input = f"{user_input} {band_name}" # Append automatically
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response = llm.create_chat_completion(
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messages=[
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{"role": "system", "content": "You are a chatbot for the Curly Strings band. Provide structured, concise, and clear responses."},
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{"role": "user", "content": formatted_input}
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],
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temperature=0.5,
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max_tokens=50,
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top_p=0.9,
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frequency_penalty=0.8,
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)
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return response["choices"][0]["message"]["content"].strip()
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# Create Gradio interface
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iface = gr.Interface(
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fn=chatbot_response,
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inputs=gr.Textbox(placeholder="Ask me about Curly Strings..."),
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outputs="text",
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title="Curly Strings Chatbot 🎵",
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description="Ask me about songs, albums, or anything related to Curly Strings!",
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)
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# Launch the Gradio app
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iface.launch()
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requirements.txt
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gradio
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llama-cpp-python
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