Create app.py

app.py

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+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()