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import os
import json
import re
from typing import List, Dict, Any, Tuple
import gradio as gr
from groq import Groq
# -----------------------------
# Configuration
# -----------------------------
GROQ_API_KEY = os.environ.get("GROQ_API_KEY", "").strip()
client = Groq(api_key=GROQ_API_KEY)
LANG_OPTIONS = [
"English",
"Urdu",
"Mandarin Chinease",
"Hindi",
"Spanish",
"Standard Arabic",
"French",
"Bengali",
"Protaguese",
"Russian",
"Indonasion",
]
LEVEL_OPTIONS = ["Beginner", "Intermediate", "Advanced"]
# -----------------------------
# Helpers
# -----------------------------
def generate_with_groq(prompt: str) -> str:
"""
Call Groq chat completions with the specified model and return text content.
Includes basic error handling and a concise error message for the UI.
"""
if not GROQ_API_KEY:
return "❌ Missing GROQ_API_KEY. Please set it as a secret/environment variable."
try:
response = client.chat.completions.create(
model="llama-3.1-8b-instant",
messages=[{"role": "user", "content": prompt}],
temperature=0.7,
max_tokens=500,
)
return response.choices[0].message.content
except Exception as e:
return f"❌ API error: {e}"
def build_system_context(subject: str, topic: str, language: str, level: str) -> str:
return (
f"Subject: {subject}\n"
f"Topic: {topic}\n"
f"Language: {language}\n"
f"Student Level: {level}\n"
)
def prompt_explanation(subject: str, topic: str, language: str, level: str) -> str:
ctx = build_system_context(subject, topic, language, level)
return (
f"{ctx}\n"
"Task: Write a clear, friendly, step-by-step explanation of the topic."
" Use short paragraphs, numbered steps where helpful, and examples."
" Keep it concise but thorough. Reply in the specified language only."
)
def prompt_resources(subject: str, topic: str, language: str, level: str) -> str:
ctx = build_system_context(subject, topic, language, level)
return (
f"{ctx}\n"
"Task: Recommend at least 3 quality learning resources (mix of articles, videos, documentation). "
"Return as a markdown bulleted list. Each item must include a title, the type (Article/Video/Docs), "
"a one-line why it's useful, and a URL. Reply in the specified language only."
)
def prompt_roadmap(subject: str, topic: str, language: str, level: str) -> str:
ctx = build_system_context(subject, topic, language, level)
return (
f"{ctx}\n"
"Task: Produce a structured learning roadmap for this topic and level. "
"Organize into stages with bullet points, estimated effort, and key outcomes. "
"Add a short list of common mistakes to avoid. Reply in the specified language only."
)
def prompt_quiz(subject: str, topic: str, language: str, level: str) -> str:
ctx = build_system_context(subject, topic, language, level)
return (
f"{ctx}\n"
"Task: Create a short multiple-choice quiz with 3 to 5 questions. "
"Return STRICT JSON only with this schema:\n"
"{\n"
' "questions": [\n'
' {\n'
' "question": "string",\n'
' "options": ["A", "B", "C", "D"],\n'
' "answer_index": 0\n'
" }\n"
" ]\n"
"}\n"
"Requirements:\n"
"- options length 3-5\n"
"- answer_index is an integer index into the options array\n"
"- No additional commentary or code fences\n"
f"- Write the question text and options in {language}."
)
def parse_quiz_json(text: str) -> Dict[str, Any]:
"""
Extract and parse the JSON quiz from model output.
Tries to locate the first JSON-looking block if the response isn't pure JSON.
"""
# Try direct JSON first
try:
parsed = json.loads(text)
if "questions" in parsed:
return parsed
except Exception:
pass
# Fallback: regex to find JSON block
match = re.search(r"\{(?:[^{}]|(?R))*\}", text, re.DOTALL)
if match:
try:
parsed = json.loads(match.group(0))
if "questions" in parsed:
return parsed
except Exception:
pass
# Final fallback
return {"questions": []}
def normalize_quiz(quiz: Dict[str, Any]) -> List[Dict[str, Any]]:
"""
Ensure each question has required fields. Drop invalid ones.
"""
cleaned = []
for q in quiz.get("questions", []):
question = q.get("question")
options = q.get("options", [])
answer_index = q.get("answer_index")
if (
isinstance(question, str)
and isinstance(options, list)
and 3 <= len(options) <= 5
and isinstance(answer_index, int)
and 0 <= answer_index < len(options)
):
cleaned.append(
{
"question": question.strip(),
"options": [str(o).strip() for o in options],
"answer_index": answer_index,
}
)
return cleaned[:5] # at most 5
def evaluate_answers(
user_choices: List[int], quiz_data: List[Dict[str, Any]]
) -> Tuple[str, str]:
"""
Compute score and short feedback summary.
"""
correct = 0
details = []
for i, q in enumerate(quiz_data):
user_idx = user_choices[i] if i < len(user_choices) else None
ans_idx = q["answer_index"]
is_correct = (user_idx == ans_idx)
if is_correct:
correct += 1
# Build per-question line
chosen = (
f"{q['options'][user_idx]}"
if isinstance(user_idx, int) and 0 <= user_idx < len(q["options"])
else "No answer"
)
details.append(
f"Q{i+1}: {'✅ Correct' if is_correct else '❌ Incorrect'} | "
f"Your answer: {chosen} | Correct: {q['options'][ans_idx]}"
)
total = len(quiz_data)
score_text = f"Score: {correct} / {total}"
if total == 0:
return "No quiz generated yet.", ""
# Brief feedback
if correct == total and total > 0:
feedback = "Great job. You’ve mastered this set."
elif correct >= (total * 0.6):
feedback = "Good work. Review the missed questions and try again."
else:
feedback = "Keep practicing. Revisit the explanation and roadmap."
return score_text, feedback + "\n\n" + "\n".join(details)
# -----------------------------
# Gradio Callbacks
# -----------------------------
def on_generate_explanation(subject, topic, language, level):
prompt = prompt_explanation(subject, topic, language, level)
return generate_with_groq(prompt)
def on_generate_resources(subject, topic, language, level):
prompt = prompt_resources(subject, topic, language, level)
return generate_with_groq(prompt)
def on_generate_roadmap(subject, topic, language, level):
prompt = prompt_roadmap(subject, topic, language, level)
return generate_with_groq(prompt)
def on_generate_quiz(subject, topic, language, level):
raw = generate_with_groq(prompt_quiz(subject, topic, language, level))
quiz = normalize_quiz(parse_quiz_json(raw))
# Build updates for up to 5 radios and their labels
vis = [False] * 5
labels = [("Question", ["Option 1", "Option 2", "Option 3"])] * 5
for i, q in enumerate(quiz):
vis[i] = True
labels[i] = (f"Q{i+1}. {q['question']}", q["options"])
return (
quiz, # gr.State
gr.update(visible=vis[0], label=labels[0][0], choices=labels[0][1], value=None),
gr.update(visible=vis[1], label=labels[1][0], choices=labels[1][1], value=None),
gr.update(visible=vis[2], label=labels[2][0], choices=labels[2][1], value=None),
gr.update(visible=vis[3], label=labels[3][0], choices=labels[3][1], value=None),
gr.update(visible=vis[4], label=labels[4][0], choices=labels[4][1], value=None),
raw if not quiz else "Quiz generated. Select your answers below."
)
def on_display_results(
quiz_state,
a1, a2, a3, a4, a5
):
quiz = quiz_state or []
# Map selected option text back to index
selections = []
for i, q in enumerate(quiz):
# chosen label may be None
chosen = [a1, a2, a3, a4, a5][i]
if chosen is None:
selections.append(None)
continue
try:
idx = q["options"].index(chosen)
except ValueError:
idx = None
selections.append(idx)
score_text, feedback = evaluate_answers(selections, quiz)
return score_text, feedback
# -----------------------------
# UI
# -----------------------------
# Custom blue theme + card-like styling
CSS = """
:root {
--brand-blue: #1e40af; /* indigo-800 */
--brand-blue-600: #2563eb;
--card-bg: #f8fafc;
--border: #cbd5e1;
}
.gradio-container {max-width: 1200px !important}
#title h1 {color: var(--brand-blue); margin-bottom: 6px}
#subtitle {color:#334155; margin-top:0}
.card {
background: var(--card-bg);
border: 1px solid var(--border);
border-radius: 14px;
padding: 14px;
box-shadow: 0 2px 8px rgb(2 6 23 / 6%);
}
.btn-primary button {
background: var(--brand-blue-600) !important;
border-color: var(--brand-blue-600) !important;
color: white !important;
}
.section-title {
font-weight: 700; color: var(--brand-blue);
margin-bottom: 6px; font-size: 16px;
}
"""
with gr.Blocks(css=CSS, theme=gr.themes.Soft(primary_hue="blue")) as demo:
gr.Markdown("<div id='title'><h1>AI Study Tutor</h1><p id='subtitle'>Powered by Groq + Gradio</p></div>")
with gr.Row():
with gr.Column(scale=1):
with gr.Group(elem_classes="card"):
gr.Markdown("### Inputs")
subject = gr.Textbox(label="Subject", placeholder="e.g., Mathematics")
topic = gr.Textbox(label="Topic", placeholder="e.g., Derivatives of Trigonometric Functions")
language = gr.Dropdown(LANG_OPTIONS, value="English", label="Language")
level = gr.Radio(LEVEL_OPTIONS, value="Beginner", label="Level")
with gr.Column(scale=2):
# Explanation
with gr.Group(elem_classes="card"):
gr.Markdown("<div class='section-title'>Generate Explanation</div>")
btn_explain = gr.Button("Generate Explanation", elem_classes="btn-primary")
explanation = gr.Markdown(label="Explanation", value="")
# Resources
with gr.Group(elem_classes="card"):
gr.Markdown("<div class='section-title'>Generate Resources</div>")
btn_resources = gr.Button("Generate Resources", elem_classes="btn-primary")
resources = gr.Markdown(label="Resources", value="")
with gr.Row():
with gr.Column():
with gr.Group(elem_classes="card"):
gr.Markdown("<div class='section-title'>Generate Roadmap</div>")
btn_roadmap = gr.Button("Generate Roadmap", elem_classes="btn-primary")
roadmap = gr.Markdown(label="Roadmap", value="")
with gr.Row():
with gr.Column():
with gr.Group(elem_classes="card"):
gr.Markdown("<div class='section-title'>Generate Quiz</div>")
btn_quiz = gr.Button("Generate Quiz", elem_classes="btn-primary")
quiz_info = gr.Markdown("Click the button to create a quiz.")
# Quiz state and up to 5 radios
quiz_state = gr.State([])
q1 = gr.Radio(label="Question 1", choices=[], visible=False, interactive=True)
q2 = gr.Radio(label="Question 2", choices=[], visible=False, interactive=True)
q3 = gr.Radio(label="Question 3", choices=[], visible=False, interactive=True)
q4 = gr.Radio(label="Question 4", choices=[], visible=False, interactive=True)
q5 = gr.Radio(label="Question 5", choices=[], visible=False, interactive=True)
with gr.Row():
with gr.Column():
with gr.Group(elem_classes="card"):
gr.Markdown("<div class='section-title'>Display Results</div>")
btn_results = gr.Button("Evaluate Answers", elem_classes="btn-primary")
score = gr.Markdown("Score will appear here.")
feedback = gr.Markdown("Feedback will appear here.")
# Events
btn_explain.click(
fn=on_generate_explanation,
inputs=[subject, topic, language, level],
outputs=[explanation],
)
btn_resources.click(
fn=on_generate_resources,
inputs=[subject, topic, language, level],
outputs=[resources],
)
btn_roadmap.click(
fn=on_generate_roadmap,
inputs=[subject, topic, language, level],
outputs=[roadmap],
)
btn_quiz.click(
fn=on_generate_quiz,
inputs=[subject, topic, language, level],
outputs=[quiz_state, q1, q2, q3, q4, q5, quiz_info],
)
btn_results.click(
fn=on_display_results,
inputs=[quiz_state, q1, q2, q3, q4, q5],
outputs=[score, feedback],
)
if __name__ == "__main__":
demo.launch()
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