Create app.py

app.py

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+import streamlit as st
+from langchain_google_genai import ChatGoogleGenerativeAI
+from datetime import datetime
+
+st.title("Job Interview Preparation Bot")
+
+# Function to generate interview questions
+def generate_questions(role, topic, difficulty, num_questions):
+    prompt = (
+        f"Generate {num_questions} {difficulty} interview questions for a {role} role "
+        f"focused on {topic}."
+    )
+    llm = ChatGoogleGenerativeAI(model='gemini-pro', google_api_key=st.secrets["GOOGLE_API_KEY"])
+    answers = llm.invoke(prompt)
+    return answers.content if answers else "No questions generated."
+
+# Function to analyze responses and give feedback
+def analyze_responses(response):
+    prompt = (
+        f"Provide constructive feedback on the following interview response:\n\n{response}"
+    )
+    llm = ChatGoogleGenerativeAI(model='gemini-pro', google_api_key=st.secrets["GOOGLE_API_KEY"])
+    feedback = llm.invoke(prompt)
+    return feedback.content if feedback else "No feedback available."
+
+# Function to provide general and specific interview tips
+def provide_tips(role=None):
+    prompt = "Share general interview tips."
+    if role:
+        prompt += f" Provide specific tips for a {role} role."
+    llm = ChatGoogleGenerativeAI(model='gemini-pro', google_api_key=st.secrets["GOOGLE_API_KEY"])
+    tips = llm.invoke(prompt)
+    return tips.content if tips else "No tips available."
+
+# Interface for generating questions
+with st.form('question_form'):
+    role = st.selectbox('Select Role', ['Software Developer', 'Data Analyst', 'Marketing Manager'])
+    topic = st.selectbox('Select Topic', ['Behavioral', 'Technical', 'Situational'])
+    difficulty = st.selectbox('Select Difficulty Level', ['Easy', 'Medium', 'Hard'])
+    num_questions = st.slider('Number of Questions', 1, 10, 5)
+    question_submitted = st.form_submit_button('Generate Questions')
+
+    if question_submitted:
+        questions = generate_questions(role, topic, difficulty, num_questions)
+        st.info(questions)
+
+# Interface for feedback on responses
+with st.form('feedback_form'):
+    response = st.text_area('Type your interview response')
+    feedback_submitted = st.form_submit_button('Get Feedback')
+
+    if feedback_submitted and response:
+        feedback = analyze_responses(response)
+        st.info(feedback)
+
+# Interface for interview tips
+with st.form('tips_form'):
+    role_for_tips = st.selectbox('Select Role for Tips', ['', 'Software Developer', 'Data Analyst', 'Marketing Manager'])
+    tips_submitted = st.form_submit_button('Get Tips')
+
+    if tips_submitted:
+        tips = provide_tips(role_for_tips if role_for_tips else None)
+        st.info(tips)
+
+# Example mock interview scheduling (this is a placeholder for now)
+st.sidebar.header("Mock Interview Scheduler")
+st.sidebar.write("Schedule a mock interview with the bot.")
+mock_date = st.sidebar.date_input("Select Date", datetime.now())
+mock_time = st.sidebar.time_input("Select Time", datetime.now().time())
+st.sidebar.button("Schedule Interview", on_click=lambda: st.sidebar.write("Interview scheduled!"))
+
+# Placeholder for engagement metrics and resource recommendations
+st.sidebar.header("Engagement Metrics and Resources")
+st.sidebar.write("Track your progress over time and connect with resources.")