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Update app.py
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app.py
CHANGED
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@@ -2,23 +2,24 @@ import gradio as gr
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import os
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from groq import Groq
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#
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GROQ_API_KEY = os.getenv("Groq_API_Key")
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# Initialize Groq client
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client = Groq(api_key=GROQ_API_KEY)
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# System
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SYSTEM_PROMPT = (
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"You are a Construction Material Advisor Bot. Your job is to recommend the best construction materials "
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"for civil engineering projects based on environmental conditions, budget, load requirements, and durability. "
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"Be concise, informative, and explain
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)
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MODEL_NAME = "llama3-70b-8192"
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def get_material_advice(user_query: str) -> str:
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"""Return a material recommendation generated by the Groq LLM."""
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try:
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chat_completion = client.chat.completions.create(
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model=MODEL_NAME,
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@@ -29,15 +30,18 @@ def get_material_advice(user_query: str) -> str:
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temperature=0.7,
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max_tokens=500,
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)
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# Gradio
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demo = gr.Interface(
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fn=get_material_advice,
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inputs=gr.Textbox(lines=3, placeholder="Ask about construction materials..."),
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outputs=
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title="🧱 Construction Material Advisor Bot",
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description=(
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"Ask questions like 'What is the best material for a coastal bridge?' or "
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@@ -45,6 +49,5 @@ demo = gr.Interface(
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),
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)
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# Launch the app
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if __name__ == "__main__":
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demo.launch()
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import os
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from groq import Groq
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# Load API key securely from environment variable
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GROQ_API_KEY = os.getenv("Groq_API_Key")
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# Initialize Groq client using the SDK
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client = Groq(api_key=GROQ_API_KEY)
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# System instruction for the bot
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SYSTEM_PROMPT = (
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"You are a Construction Material Advisor Bot. Your job is to recommend the best construction materials "
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"for civil engineering projects based on environmental conditions, budget, load requirements, and durability. "
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"Be concise, informative, and explain pros and cons of the materials."
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)
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# Model name
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MODEL_NAME = "llama3-70b-8192"
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# Chat function using Groq SDK
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def get_material_advice(user_query: str) -> str:
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try:
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chat_completion = client.chat.completions.create(
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model=MODEL_NAME,
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temperature=0.7,
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max_tokens=500,
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)
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response = chat_completion.choices[0].message.content.strip()
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# Convert plain text response to Markdown for better formatting
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formatted_response = f"### 🧱 Material Recommendations\n\n{response}"
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return formatted_response
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except Exception as e:
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return f"Error: {str(e)}"
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# Gradio UI
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demo = gr.Interface(
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fn=get_material_advice,
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inputs=gr.Textbox(lines=3, placeholder="Ask about construction materials..."),
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outputs=gr.Markdown(),
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title="🧱 Construction Material Advisor Bot",
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description=(
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"Ask questions like 'What is the best material for a coastal bridge?' or "
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),
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)
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if __name__ == "__main__":
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demo.launch()
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