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| """# Import the Packages""" | |
| import gradio | |
| from groq import Groq | |
| client = Groq( | |
| api_key="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", | |
| ) | |
| def initialize_messages(): | |
| return [{"role": "system", | |
| "content": """You are a highly experienced senior software engineer with over 10 years | |
| of hands-on expertise in full-stack development and machine learning. You are deeply | |
| familiar with scalable backend architecture, modern frontend frameworks, cloud-native | |
| technologies, DevOps practices, and deploying ML models in production. You write clean, | |
| maintainable code, follow industry best practices, and mentor junior developers. | |
| You think critically about trade-offs, prioritize performance, and have a practical | |
| mindset informed by real-world engineering challenges. When you respond, explain your | |
| thought process clearly, justify your design decisions, and always consider scalability, | |
| maintainability, and efficiency."""}] | |
| """#Assign it to a variable""" | |
| messages_prmt = initialize_messages() | |
| print(type(messages_prmt)) | |
| [{},{}] | |
| """#Define a function to connect with LLM""" | |
| def customLLMBot(user_input, history): | |
| global messages_prmt | |
| messages_prmt.append({"role": "user", "content": user_input}) | |
| response = client.chat.completions.create( | |
| messages=messages_prmt, | |
| model="llama3-8b-8192", | |
| ) | |
| print(response) | |
| LLM_reply = response.choices[0].message.content | |
| messages_prmt.append({"role": "assistant", "content": LLM_reply}) | |
| return LLM_reply | |
| iface = gradio.ChatInterface(customLLMBot, | |
| chatbot=gradio.Chatbot(height=400), | |
| textbox=gradio.Textbox(placeholder="Ask me a question related to software development",), | |
| title="Senior software developer", | |
| description="Chat bot for technical assistance", | |
| theme="soft", | |
| examples=["hi","What is ml", "how to learn full stack development"], | |
| submit_btn=True | |
| ) | |
| """#Call launch function to execute""" | |
| iface.launch(share=True) |