from huggingface_hub import InferenceClient from resume import data import markdowm as md import gradio as gr client = InferenceClient("HuggingFaceH4/zephyr-7b-beta") # Chatbot response function with integrated system message def respond( message, history: list[tuple[str, str]], max_tokens=1024, temperature=0.7, top_p=0.95, ): # System message defining assistant behavior system_message = { "role": "system", "content": f"Act and chat as SARATH to thw user question. SARATH is a professional fresher seeking a job abd pursuing Btech-4-1. your name is SARATH." f"Here is about SARATH:```{data}```. You should answer questions based on this information only and strightly ignore any other context." f"strictly prohibit the random respons or output and speak in English" } messages = [system_message] # Adding conversation history for val in history: if val[0]: messages.append({"role": "user", "content": val[0]}) if val[1]: messages.append({"role": "assistant", "content": val[1]}) # Adding the current user input messages.append({"role": "user", "content": message}) response = "" # Streaming the response from the API for message in client.chat_completion( messages, max_tokens=max_tokens, stream=True, temperature=temperature, top_p=top_p, ): token = message.choices[0].delta.content response += token yield response # Gradio interface with additional sliders for control with gr.Blocks(theme=gr.themes.Ocean(font=[gr.themes.GoogleFont("Roboto Mono")])) as main: gr.Markdown(md.title) with gr.Tabs(): with gr.TabItem("Resume"): gr.Markdown(data) with gr.TabItem("My2.0"): gr.ChatInterface(respond, chatbot=gr.Chatbot(height=500), examples=["Tell me about yourself sarath", 'Can you walk me through some of your recent projects and explain the role you played in each?', "What specific skills do you bring to the table that would benefit our company's AI/ML initiatives?", "How do you stay updated with the latest trends and advancements in AI and Machine Learning?" ], ) gr.Markdown(md.description) gr.Markdown(md.footer.format(github_logo_encoded, linkedin_logo_encoded, website_logo_encoded)) if __name__ == "__main__": main.launch(share=True)