| from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer | |
| import gradio as gr | |
| model_name = "TinyLlama/TinyLlama-1.1B-Chat-v1.0" | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = AutoModelForCausalLM.from_pretrained(model_name) | |
| text_generator = pipeline("text-generation", model=model, tokenizer=tokenizer) | |
| def interview_chatbot(user_input, task): | |
| """ | |
| Handles interview-specific chatbot tasks. | |
| Parameters: | |
| - user_input: str, the input text from the user. | |
| - task: str, the type of task (e.g., "Behavioral Question", "Technical Question", "General Advice"). | |
| Returns: | |
| - str: The generated response. | |
| """ | |
| if task == "Behavioral Question": | |
| prompt = f"You are an interview coach. Provide a strong response to the following behavioral question:\n{user_input}\nSuggested Response:" | |
| elif task == "Technical Question": | |
| prompt = f"You are a technical interview expert. Answer the following technical question clearly and concisely:\nQuestion: {user_input}\nAnswer:" | |
| elif task == "General Advice": | |
| prompt = f"You are an interview expert. Provide advice for the following situation:\n{user_input}\nAdvice:" | |
| else: | |
| return "Invalid task selected." | |
| response = text_generator( | |
| prompt, | |
| max_length=200, | |
| num_return_sequences=1, | |
| pad_token_id=tokenizer.eos_token_id, | |
| temperature=0.7, | |
| top_p=0.9 | |
| )[0]["generated_text"] | |
| return response[len(prompt):].strip() | |
| def gradio_interface(user_input, task): | |
| """ | |
| Interface function for Gradio integration. | |
| """ | |
| if not user_input.strip(): | |
| return "Please enter some input." | |
| return interview_chatbot(user_input, task) | |
| with gr.Blocks(theme=gr.themes.Monochrome()) as interview_chat_ui: | |
| gr.Markdown( | |
| """ | |
| # 🌟 Interview Preparation Chatbot | |
| Welcome to your personal interview preparation assistant! This chatbot can help you tackle: | |
| - **Behavioral Questions**: Practice with confidence. | |
| - **Technical Questions**: Get clear and concise explanations. | |
| - **General Advice**: Learn how to ace your interviews. | |
| """, | |
| elem_id="main_header", | |
| ) | |
| with gr.Row(): | |
| with gr.Column(): | |
| gr.Markdown( | |
| """### 🎯 Enter your query and select the task type:""", | |
| elem_id="sub_header", | |
| ) | |
| user_input = gr.Textbox( | |
| lines=5, | |
| placeholder="Enter your question or situation here...", | |
| label="Your Input", | |
| elem_id="input_box", | |
| ) | |
| task = gr.Radio( | |
| ["Behavioral Question", "Technical Question", "General Advice"], | |
| label="Select Task", | |
| elem_id="task_selector", | |
| ) | |
| submit_button = gr.Button("✨ Get Response", elem_id="submit_button") | |
| with gr.Column(): | |
| gr.Markdown( | |
| """### 💡 Chatbot Response:""", | |
| elem_id="response_header", | |
| ) | |
| output = gr.Textbox( | |
| lines=10, | |
| label="Response", | |
| interactive=False, | |
| elem_id="output_box", | |
| ) | |
| submit_button.click(gradio_interface, inputs=[user_input, task], outputs=output) | |
| clear_button = gr.Button("🧹 Clear All", elem_id="clear_button") | |
| clear_button.click(lambda: ("", ""), None, [user_input, output]) | |
| gr.Markdown( | |
| """ | |
| --- | |
| **Tip**: Practice regularly to build confidence and improve your interview skills! 🚀 | |
| """, | |
| elem_id="footer_text", | |
| ) | |
| interview_chat_ui.launch() |