Upload app.py

app.py

@@ -0,0 +1,264 @@
+import os
+from typing import Any
+
+from dotenv import load_dotenv
+import gradio as gr
+import requests
+
+
+load_dotenv()
+
+BACKEND_URL = os.getenv("BACKEND_URL", "").rstrip("/")
+EXAMPLE_QUESTION = "soil erosion vaneko ke ho"
+EXAMPLE_CONTEXT = (
+    "Soil erosion is the removal of topsoil by wind, water, or other natural forces. "
+    "It can make farmland less fertile and can be reduced by planting trees and grass."
+)
+
+
+def ask_tutor(question: str, textbook_context: str) -> tuple[str, str, str]:
+    question = question.strip()
+    textbook_context = textbook_context.strip()
+
+    if not question:
+        return (
+            "Please type a student question.",
+            "कृपया विद्यार्थीको प्रश्न लेख्नुहोस्।",
+            "1. Add a question first.\n2. Then try again.\n3. Use a textbook topic.",
+        )
+
+    if BACKEND_URL:
+        backend_result = ask_backend(question)
+
+        if backend_result:
+            return backend_result
+
+    return mock_response(question=question, textbook_context=textbook_context)
+
+
+def ask_backend(question: str) -> tuple[str, str, str] | None:
+    try:
+        response = requests.post(
+            f"{BACKEND_URL}/ask",
+            json={
+                "question": question,
+                "student_id": "hf-space-demo",
+                "language_support": "English and Nepali",
+            },
+            timeout=60,
+        )
+        response.raise_for_status()
+        data = response.json()
+    except requests.RequestException:
+        return None
+    except ValueError:
+        return None
+
+    return format_backend_response(data)
+
+
+def format_backend_response(data: dict[str, Any]) -> tuple[str, str, str]:
+    quiz_questions = data.get("quiz_questions", [])
+    english_answer = data.get("answer_english", "No English answer returned.")
+    normalized_question = str(data.get("normalized_question") or "").strip()
+
+    if normalized_question:
+        english_answer = f"Interpreted question: {normalized_question}\n\n{english_answer}"
+
+    return (
+        english_answer,
+        data.get("answer_nepali", "नेपाली उत्तर प्राप्त भएन।"),
+        format_quiz(quiz_questions),
+    )
+
+
+def mock_response(question: str, textbook_context: str) -> tuple[str, str, str]:
+    context = textbook_context or EXAMPLE_CONTEXT
+    simple_context = truncate(context, max_length=450)
+    normalized_question = normalize_question_mock(question)
+
+    english = (
+        f"Interpreted question: {normalized_question}\n\n"
+        "Mock demo answer: I am using the textbook context only. "
+        f"A simple explanation is: {simple_context}"
+    )
+    nepali = (
+        "मक डेमो उत्तर: म पाठ्यपुस्तकको सन्दर्भ मात्र प्रयोग गर्दैछु। "
+        "यो विषयलाई सरल रूपमा बुझ्दा, माटोको माथिल्लो उपयोगी भाग हावा वा पानीले "
+        "बगाएर लैजान सक्छ। यस्तो हुँदा खेतीका लागि माटो कमजोर हुन सक्छ।"
+    )
+    quiz = format_quiz(
+        [
+            "What is the main idea from the explanation?",
+            "Can you give one simple example?",
+            "Can you explain it in your own words?",
+        ]
+    )
+
+    return english, nepali, quiz
+
+
+def normalize_question_mock(question: str) -> str:
+    text = question.lower()
+
+    if "soil erosion" in text or ("mato" in text and "katan" in text):
+        return "What is soil erosion?"
+
+    if "photosynthesis" in text or ("prakash" in text and "sansleshan" in text):
+        return "What is photosynthesis?"
+
+    if "fraction" in text or "bhinn" in text:
+        return "What is a fraction?"
+
+    if "oxygen" in text or "aksijan" in text:
+        return "What is oxygen?"
+
+    mixed_topic = extract_mixed_language_topic(text)
+
+    if mixed_topic:
+        return f"What is {mixed_topic}?"
+
+    return question
+
+
+def extract_mixed_language_topic(text: str) -> str:
+    markers = [
+        " vaneko ",
+        " bhaneko ",
+        " vanya ",
+        " bhanya ",
+        " vanne ",
+        " bhanne ",
+    ]
+
+    if not any(marker in f" {text} " for marker in markers):
+        return ""
+
+    topic = f" {text} "
+    removable_phrases = [
+        " vaneko ",
+        " bhaneko ",
+        " vanya ",
+        " bhanya ",
+        " vanne ",
+        " bhanne ",
+        " ke ho ",
+        " k ho ",
+        " kya ho ",
+        " vana ",
+        " bhana ",
+        " ho ",
+        " ? ",
+    ]
+
+    for phrase in removable_phrases:
+        topic = topic.replace(phrase, " ")
+
+    topic = " ".join(topic.split()).strip(" ?.,")
+
+    if not topic or len(topic) > 80:
+        return ""
+
+    return topic
+
+
+def format_quiz(quiz_questions: list[Any]) -> str:
+    questions = [
+        str(question).strip()
+        for question in quiz_questions
+        if str(question).strip()
+    ]
+
+    if not questions:
+        questions = [
+            "What did you learn from the explanation?",
+            "Can you give one example?",
+            "Can you explain it to a friend?",
+        ]
+
+    return "\n".join(
+        f"{index}. {question}"
+        for index, question in enumerate(questions[:3], start=1)
+    )
+
+
+def truncate(text: str, max_length: int) -> str:
+    if len(text) <= max_length:
+        return text
+
+    return f"{text[: max_length - 3]}..."
+
+
+with gr.Blocks(title="Pathshala AI", theme=gr.themes.Soft()) as demo:
+    gr.Markdown(
+        """
+        # Pathshala AI
+        Bilingual AI tutor for rural primary students in Nepal. Try English, Nepali,
+        or romanized Nepali questions like `soil erosion vaneko ke ho`.
+        """
+    )
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            question_input = gr.Textbox(
+                label="Student question",
+                placeholder=EXAMPLE_QUESTION,
+                value=EXAMPLE_QUESTION,
+                lines=2,
+            )
+            context_input = gr.Textbox(
+                label="Optional textbook context",
+                placeholder="Paste a short textbook paragraph here.",
+                value=EXAMPLE_CONTEXT,
+                lines=5,
+            )
+            ask_button = gr.Button("Ask Tutor", variant="primary")
+
+        with gr.Column(scale=1):
+            english_output = gr.Textbox(
+                label="English explanation",
+                lines=6,
+            )
+            nepali_output = gr.Textbox(
+                label="Nepali explanation",
+                lines=6,
+            )
+            quiz_output = gr.Textbox(
+                label="3 quiz questions",
+                lines=5,
+            )
+
+    gr.Examples(
+        examples=[
+            [EXAMPLE_QUESTION, EXAMPLE_CONTEXT],
+            [
+                "What is a fraction?",
+                (
+                    "A fraction shows a part of a whole. The top number tells how many "
+                    "parts we have. The bottom number tells how many equal parts the "
+                    "whole is divided into."
+                ),
+            ],
+            [
+                "photosynthesis vaneko ke ho vana",
+                (
+                    "Photosynthesis is the process by which green plants use sunlight, "
+                    "water, and carbon dioxide to make food."
+                ),
+            ],
+        ],
+        inputs=[question_input, context_input],
+        outputs=[english_output, nepali_output, quiz_output],
+        fn=ask_tutor,
+        cache_examples=False,
+    )
+
+    ask_button.click(
+        fn=ask_tutor,
+        inputs=[question_input, context_input],
+        outputs=[english_output, nepali_output, quiz_output],
+    )
+
+
+if __name__ == "__main__":
+    demo.launch()