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Browse files- README.md +25 -7
- app.py +47 -0
- requirements.txt +4 -0
README.md
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---
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title: My
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emoji:
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colorFrom:
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sdk: gradio
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sdk_version: 4.
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app_file: app.py
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pinned: false
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license: ecl-2.0
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---
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-
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---
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title: My-Llama3-Groq
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emoji: 🦙🤖
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colorFrom: blue
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colorTo: green
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sdk: gradio
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sdk_version: "4.12.0"
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app_file: app.py
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pinned: false
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---
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# My Chatbot
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My groq llama3 chatbot
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# This project
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This project uses Groq cloud API
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Llama3-70b-8192
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## More information
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Developed by Ramon Mayor Martins (2024)
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mail [email protected]
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hp https://rmayormartins.github.io/
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twitter @rmayormartins
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github https://github.com/rmayormartins
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## Special thanks
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Groq https://groq.com/
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app.py
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import os
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from groq import Groq
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import gradio as gr
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# Recupera a chave API da variável de ambiente
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api_key = os.getenv('GROQ_API_KEY')
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client = Groq(api_key=api_key)
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system_prompt = {
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"role": "system",
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"content": "You are a useful assistant. You reply with efficient answers."
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}
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async def chat_groq(message, history):
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messages = [system_prompt]
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for msg in history:
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messages.append({"role": "user", "content": str(msg[0])})
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messages.append({"role": "assistant", "content": str(msg[1])})
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messages.append({"role": "user", "content": str(message)})
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response_content = ''
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stream = client.chat.completions.create(
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model="llama3-70b-8192",
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messages=messages,
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max_tokens=1024,
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temperature=1.3,
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stream=True
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)
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for chunk in stream:
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content = chunk.choices[0].delta.content
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if content:
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response_content += chunk.choices[0].delta.content
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yield response_content
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with gr.Blocks(theme=gr.themes.Monochrome(), fill_height=True) as demo:
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gr.ChatInterface(chat_groq,
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clear_btn=None,
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undo_btn=None,
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retry_btn=None)
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demo.queue()
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demo.launch()
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requirements.txt
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groq
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gradio
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transformers
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torch
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