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app.py

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+
+import streamlit as st
+from groq import Groq
+import re
+from fpdf import FPDF
+import datetime
+import os
+
+# ── Page Config ───────────────────────────────────
+st.set_page_config(
+    page_title = "InterviewGen AI",
+    page_icon  = "🎯",
+    layout     = "wide"
+)
+
+# ── Custom CSS ────────────────────────────────────
+st.markdown("""
+<style>
+    .main-header {
+        font-size: 2.8rem;
+        font-weight: 900;
+        background: linear-gradient(90deg, #667eea, #764ba2);
+        -webkit-background-clip: text;
+        -webkit-text-fill-color: transparent;
+        text-align: center;
+        padding: 1rem 0;
+    }
+    .question-card {
+        background: #f8f9fa;
+        border-left: 5px solid #667eea;
+        padding: 1.2rem;
+        margin: 0.8rem 0;
+        border-radius: 10px;
+        box-shadow: 0 2px 4px rgba(0,0,0,0.1);
+    }
+    .answer-card {
+        background: linear-gradient(135deg, #e8f4f8, #f0fff4);
+        border-left: 5px solid #2ecc71;
+        padding: 1.2rem;
+        margin: 0.8rem 0;
+        border-radius: 10px;
+    }
+    .score-card {
+        background: linear-gradient(135deg, #fff3cd, #ffeaa7);
+        border-left: 5px solid #f39c12;
+        padding: 1.2rem;
+        margin: 0.8rem 0;
+        border-radius: 10px;
+    }
+    .metric-card {
+        background: linear-gradient(135deg, #667eea, #764ba2);
+        color: white;
+        padding: 1rem;
+        border-radius: 10px;
+        text-align: center;
+    }
+</style>
+""", unsafe_allow_html=True)
+
+# ── Groq Client ───────────────────────────────────
+GROQ_API_KEY = os.environ.get("GROQ_API_KEY", "")
+client       = Groq(api_key=GROQ_API_KEY)
+
+# ── Helper Functions ──────────────────────────────
+def generate_questions(role, difficulty, q_type, num, job_desc=""):
+    job_context = f"Job Description: {job_desc[:500]}" if job_desc else ""
+    prompt = f"""You are a senior technical interviewer at a top tech company.
+{job_context}
+Generate exactly {num} {difficulty} level {q_type} interview questions for a {role}.
+Format EXACTLY like this:
+Q1: [question]
+A1: [detailed answer]
+
+Q2: [question]
+A2: [detailed answer]
+
+Only output questions and answers. Nothing else."""
+
+    response = client.chat.completions.create(
+        model       = "llama-3.3-70b-versatile",
+        messages    = [{"role": "user", "content": prompt}],
+        temperature = 0.7,
+        max_tokens  = 2000
+    )
+    return response.choices[0].message.content
+
+def evaluate_answer(question, user_answer, correct_answer):
+    prompt = f"""You are a technical interviewer evaluating a candidate answer.
+Question: {question}
+Candidate Answer: {user_answer}
+Expected Answer: {correct_answer}
+
+Evaluate the candidate answer and provide:
+1. Score: X/10
+2. Strengths: what they got right
+3. Improvements: what they missed
+4. Verdict: Pass/Fail
+
+Be concise and professional."""
+
+    response = client.chat.completions.create(
+        model       = "llama-3.3-70b-versatile",
+        messages    = [{"role": "user", "content": prompt}],
+        temperature = 0.3,
+        max_tokens  = 500
+    )
+    return response.choices[0].message.content
+
+def parse_questions(text):
+    qa_pairs = []
+    blocks   = re.split(r"Q\d+:", text)
+    blocks   = [b.strip() for b in blocks if b.strip()]
+    for block in blocks:
+        if re.search(r"A\d+:", block):
+            parts    = re.split(r"A\d+:", block, maxsplit=1)
+            question = parts[0].strip()
+            answer   = parts[1].strip() if len(parts) > 1 else "N/A"
+        else:
+            question = block.strip()
+            answer   = "N/A"
+        qa_pairs.append({"question": question, "answer": answer})
+    return qa_pairs
+
+# ── Session State Init ────────────────────────────
+if "history"         not in st.session_state: st.session_state.history         = []
+if "total_generated" not in st.session_state: st.session_state.total_generated = 0
+if "parsed_qa"       not in st.session_state: st.session_state.parsed_qa       = []
+if "mock_index"      not in st.session_state: st.session_state.mock_index      = 0
+if "mock_scores"     not in st.session_state: st.session_state.mock_scores     = []
+if "mock_active"     not in st.session_state: st.session_state.mock_active     = False
+
+# ── Header ────────────────────────────────────────
+st.markdown("<p class=\'main-header\'>🎯 InterviewGen AI</p>", unsafe_allow_html=True)
+st.markdown("<p style=\'text-align:center;color:gray;font-size:1.1rem;\'>Professional Interview Preparation Powered by LLaMA-3.3 & Groq</p>", unsafe_allow_html=True)
+st.divider()
+
+# ── Top Metrics ───────────────────────────────────
+col1, col2, col3, col4 = st.columns(4)
+with col1: st.metric("Questions Generated", st.session_state.total_generated)
+with col2: st.metric("Sessions",            len(st.session_state.history))
+with col3: st.metric("Mock Interviews",     len(st.session_state.mock_scores))
+with col4:
+    avg = sum(st.session_state.mock_scores) / len(st.session_state.mock_scores) if st.session_state.mock_scores else 0
+    st.metric("Avg Mock Score", f"{avg:.1f}/10")
+
+st.divider()
+
+# ── Sidebar ───────────────────────────────────────
+with st.sidebar:
+    st.markdown("## Settings")
+
+    role = st.selectbox(
+        "Select Role",
+        ["Python Developer", "Data Scientist",
+         "Software Engineer", "ML Engineer",
+         "DevOps Engineer", "Full Stack Developer",
+         "Data Analyst", "Backend Developer",
+         "Frontend Developer", "AI Engineer"]
+    )
+    difficulty = st.select_slider(
+        "Difficulty Level",
+        options=["Junior", "Mid-Level", "Senior"]
+    )
+    num_questions = st.slider(
+        "Number of Questions",
+        min_value=1, max_value=10, value=5
+    )
+    show_answers = st.toggle("Show Answers", value=True)
+
+    st.divider()
+    st.markdown("### Paste Job Description (Optional)")
+    job_desc = st.text_area(
+        "Job Description",
+        placeholder="Paste job description here for targeted questions...",
+        height=150
+    )
+
+# ── Tabs ──────────────────────────────────────────
+tab1, tab2, tab3 = st.tabs([
+    "📋 Generate Questions",
+    "🎯 Mock Interview Mode",
+    "📚 History"
+])
+
+# ════════════════════════════════════════════════
+# TAB 1 — Generate Questions
+# ════════════════════════════════════════════════
+with tab1:
+    q_type = st.radio(
+        "Question Type",
+        ["Technical", "Behavioral", "Mixed"],
+        horizontal=True
+    )
+
+    generate_btn = st.button(
+        "🚀 Generate Interview Questions",
+        use_container_width=True
+    )
+
+    if generate_btn:
+        with st.spinner("LLaMA-3.3 is generating questions..."):
+            raw    = generate_questions(role, difficulty, q_type, num_questions, job_desc)
+            parsed = parse_questions(raw)
+            st.session_state.parsed_qa = parsed
+
+        st.markdown(f"### {role} | {difficulty} | {q_type}")
+        st.divider()
+
+        questions = []
+        answers   = []
+
+        for i, qa in enumerate(parsed):
+            q = qa["question"]
+            a = qa["answer"]
+            questions.append(q)
+            answers.append(a)
+
+            st.info(f"**Q{i+1}.** {q}")
+            if show_answers:
+                st.success(f"**Answer:** {a}")
+            st.write("")
+
+        st.session_state.total_generated += len(parsed)
+        st.session_state.history.append({
+            "time"      : datetime.datetime.now().strftime("%H:%M:%S"),
+            "role"      : role,
+            "difficulty": difficulty,
+            "type"      : q_type,
+            "questions" : questions,
+            "answers"   : answers
+        })
+
+        # ── PDF Export ────────────────────────────
+        try:
+            pdf = FPDF()
+            pdf.add_page()
+            pdf.set_font("Arial", "B", 14)
+            pdf.cell(190, 10, f"Interview Questions - {role}", ln=True, align="C")
+            pdf.set_font("Arial", "", 9)
+            pdf.cell(190, 8, f"Type: {q_type} | Difficulty: {difficulty}", ln=True, align="C")
+            pdf.ln(4)
+            for i, (q, a) in enumerate(zip(questions, answers)):
+                q_c = q.encode("latin-1", "replace").decode("latin-1")
+                a_c = a.encode("latin-1", "replace").decode("latin-1")
+                pdf.set_font("Arial", "B", 10)
+                pdf.multi_cell(190, 7, f"Q{i+1}. {q_c}")
+                if show_answers:
+                    pdf.set_font("Arial", "", 9)
+                    pdf.multi_cell(190, 6, f"Answer: {a_c}")
+                pdf.ln(2)
+            pdf_path = "/tmp/interview_questions.pdf"
+            pdf.output(pdf_path)
+            with open(pdf_path, "rb") as f:
+                st.download_button(
+                    label     = "📥 Download as PDF",
+                    data      = f,
+                    file_name = f"interview_{role.replace(' ','_')}.pdf",
+                    mime      = "application/pdf"
+                )
+        except Exception as e:
+            st.warning(f"PDF error: {e}")
+
+# ═══════════════════════════════════��════════════
+# TAB 2 — Mock Interview Mode
+# ════════════════════════════════════════════════
+with tab2:
+    st.markdown("### 🎯 Mock Interview Mode")
+    st.markdown("Answer questions one by one — AI will evaluate your answers!")
+    st.divider()
+
+    if not st.session_state.parsed_qa:
+        st.info("First generate questions in Tab 1, then come back here!")
+    else:
+        total_q = len(st.session_state.parsed_qa)
+        idx     = st.session_state.mock_index
+
+        if idx < total_q:
+            current_qa = st.session_state.parsed_qa[idx]
+
+            st.markdown(f"**Question {idx+1} of {total_q}**")
+            st.progress((idx) / total_q)
+
+            st.markdown(f"""
+            <div class="question-card">
+                <strong>Q{idx+1}. {current_qa["question"]}</strong>
+            </div>
+            """, unsafe_allow_html=True)
+
+            user_answer = st.text_area(
+                "Your Answer",
+                placeholder="Type your answer here...",
+                height=150,
+                key=f"answer_{idx}"
+            )
+
+            col1, col2 = st.columns(2)
+            with col1:
+                submit_btn = st.button("Submit Answer", use_container_width=True)
+            with col2:
+                skip_btn = st.button("Skip Question", use_container_width=True)
+
+            if submit_btn and user_answer:
+                with st.spinner("AI is evaluating your answer..."):
+                    evaluation = evaluate_answer(
+                        current_qa["question"],
+                        user_answer,
+                        current_qa["answer"]
+                    )
+
+                st.markdown(f"""
+                <div class="score-card">
+                    <strong>AI Evaluation:</strong><br>{evaluation}
+                </div>
+                """, unsafe_allow_html=True)
+
+                # Extract score
+                score_match = re.search(r"(\d+)/10", evaluation)
+                if score_match:
+                    score = int(score_match.group(1))
+                    st.session_state.mock_scores.append(score)
+
+                st.session_state.mock_index += 1
+                st.rerun()
+
+            if skip_btn:
+                st.session_state.mock_index += 1
+                st.rerun()
+
+        else:
+            st.success("Mock Interview Complete!")
+            if st.session_state.mock_scores:
+                avg = sum(st.session_state.mock_scores) / len(st.session_state.mock_scores)
+                st.markdown(f"### Your Final Score: {avg:.1f}/10")
+                if avg >= 8:
+                    st.balloons()
+                    st.success("Excellent! You are ready for the interview!")
+                elif avg >= 6:
+                    st.warning("Good performance! A little more practice needed.")
+                else:
+                    st.error("Keep practicing! Review the answers carefully.")
+
+            if st.button("Restart Mock Interview"):
+                st.session_state.mock_index  = 0
+                st.session_state.mock_scores = []
+                st.rerun()
+
+# ════════════════════════════════════════════════
+# TAB 3 — History
+# ════════════════════════════════════════════════
+with tab3:
+    st.markdown("### Question History")
+    if not st.session_state.history:
+        st.info("No history yet! Generate some questions first.")
+    else:
+        for session in reversed(st.session_state.history):
+            with st.expander(f"{session['time']} - {session['role']} | {session['difficulty']} | {session['type']}"):
+                for i, (q, a) in enumerate(zip(session["questions"], session["answers"])):
+                    st.markdown(f"**Q{i+1}.** {q}")
+                    if show_answers:
+                        st.markdown(f"*A: {a[:200]}...*")
+                    st.write("")