🚀 Math Research AI

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+.DS_Store
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+

README.md

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+---
+title: MathResearchIA
+emoji: 💬
+colorFrom: yellow
+colorTo: purple
+sdk: gradio
+sdk_version: 5.23.3
+app_file: app.py
+pinned: false
+license: mit
+---
+
+# 📚 MathResearchIA
+
+**MathResearchIA** makes learning mathematics easier by making key concepts accessible to everyone through clear and simplified explanations.  
+This project provides a user-friendly interface to explore **mathematical concepts** (e.g., *Fourier transform*, *Lie group*, *Lebesgue integral*, etc.) using summaries generated from Wikipedia articles.
+
+---
+
+## ✨ Key Features
+
+- 🔍 **Smart filtering**: detects whether the topic is mathematical (via an autonomous AI agent).
+- 📖 **Wikipedia search**: retrieves the full article related to the concept.
+- 🧠 **AI-generated summary**: provides a clear and simplified explanation (powered by Gemini Flash).
+- 🌐 **Source included**: each response includes a link to the corresponding Wikipedia article.
+- ❌ **Explicit rejection**: if the topic is not mathematical, the query is rejected with a helpful message.
+
+---
+
+## 🚀 How It Works
+
+1. Enter a **mathematical concept** (e.g., "Fourier transform").
+2. The autonomous AI agent checks whether it's a math-related topic.
+3. If valid:
+   - The Wikipedia article is retrieved.
+   - A simplified summary is generated.
+   - The source is displayed.
+4. Otherwise, the query is rejected with a message inviting you to correct or rephrase.
+
+---
+
+## 🧪 Tech Stack
+
+- Python
+- Gradio (web interface)
+- `wikipedia-api` (for article retrieval)
+- Gemini Flash (AI summarization)
+- Autonomous agent (intelligent filtering)
+
+---
+
+## 📌 Project Purpose
+
+This project explores the use of **autonomous agents** in focused AI applications, while also democratizing mathematics through clear, pedagogical, and reliable explanations.
+
+---
+
+## 🙌 Contributions
+
+Suggestions, ideas, and feedback are welcome! Feel free to fork the project, open a pull request, or contact me by [email](mailto:amessaoudi.am@gmail.com).
+
+---
+
+## 🔒 Note
+
+**MathResearchIA** handles **mathematical concepts only**. If your input is rejected, check for typos or try rephrasing it for better detection.
+
+---
+
+✨ *A personal project by Adel Messaoudi – at the intersection of mathematics, pedagogy, and artificial intelligence.*

app.py

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+import gradio as gr
+from filter_agent import filter_math_query
+from wiki_scraper import get_wikipedia_article
+
+def math_explainer(topic):
+    """First checks if the topic is mathematical, corrects spelling, then fetches the full Wikipedia article and summarizes it."""
+
+    # 🔍 Step 1: Check if topic is math-related + Spelling correction
+    filter_result, corrected_topic = filter_math_query(topic)
+
+    if "❌" in filter_result:  # If the query is rejected
+        return filter_result  # Return the error message
+
+    # 📑 Step 2: Retrieve full Wikipedia article and summarize it
+    return get_wikipedia_article(corrected_topic)
+
+iface = gr.Interface(
+    fn=math_explainer,
+    inputs="text",
+    outputs="text",
+    title="Math Research AI",
+    description="🚀 Math Research AI makes learning mathematics easier by making key concepts accessible to everyone through clear and simplified explanations.\n\nThis math-specialized AI agent analyzes your query, automatically corrects spelling errors, retrieves a Wikipedia article, and generates a simplified and understandable summary."
+)
+
+if __name__ == "__main__":
+    iface.launch()

filter_agent.py

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+import os
+import requests
+
+API_KEY = os.getenv("API_KEY_GEMINI")
+GEMINI_URL = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key={API_KEY}"
+
+def filter_math_query(query):
+    """Checks if the query is related to a mathematical topic and corrects spelling mistakes using a single API call."""
+
+    if not API_KEY:
+        return "⚠️ Error: Missing API key. Please configure API_KEY_GEMINI.", None
+
+    headers = {"Content-Type": "application/json"}
+
+    prompt = (
+        f"Analyze the following query and perform two tasks:\n"
+        f"1️⃣ Check whether it strictly relates to mathematics.\n"
+        f"   - Reply only with 'MATH' if it's a valid math-related topic.\n"
+        f"   - Reply with 'NON MATH' if it's not a mathematical subject.\n"
+        f"2️⃣ If the query is mathematical, correct any spelling mistakes.\n"
+        f"   - Respond in the format 'MATH\nCorrection: [Corrected query]'.\n"
+        f"   - If the query is not mathematical, do not provide a correction.\n\n"
+        f"Query: {query}"
+    )
+
+    data = {
+        "contents": [
+            {
+                "parts": [
+                    {"text": prompt}
+                ]
+            }
+        ]
+    }
+
+    try:
+        response = requests.post(GEMINI_URL, headers=headers, json=data)
+        response_json = response.json()
+        result = response_json["candidates"][0]["content"]["parts"][0]["text"].strip()
+
+        if result.startswith("MATH"):
+            corrected_query = query  # Default to the original query
+            if "Correction:" in result:
+                corrected_query = result.split("Correction:")[1].strip()
+
+            return "✅ Query accepted as mathematical.", corrected_query
+
+        elif "NON MATH" in result:
+            return "❌ Query rejected. This is not a mathematical topic.", None
+
+        else:
+            return f"⚠️ Error: Unexpected response from Gemini ({result})", None
+
+    except Exception as e:
+        return f"⚠️ Gemini API Error: {e}", None

requirements.txt

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+wikipedia-api
+gradio
+requests

wiki_scraper.py

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+import wikipediaapi
+import os
+import requests
+
+API_KEY = os.getenv("API_KEY_GEMINI")
+GEMINI_URL = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key={API_KEY}"
+
+def generate_summary(text):
+    """Generates a simplified summary of the text using the Gemini Flash API."""
+
+    if not API_KEY:
+        return "⚠️ Error: Missing API key. Please configure API_KEY_GEMINI."
+
+    headers = {"Content-Type": "application/json"}
+
+    text = text[:4000]  # ✅ Send only the first 4000 characters
+
+    prompt = (
+        f"Here is an article extracted from Wikipedia:\n\n{text}\n\n"
+        "Generate a simplified summary that is easy to understand even for someone without an advanced background in mathematics. "
+        "Use an educational tone and rephrase complex concepts in simple terms. "
+        "The summary should be concise (5 to 7 sentences) and focus on the essential points."
+    )
+
+    data = {
+        "contents": [
+            {
+                "parts": [
+                    {"text": prompt}
+                ]
+            }
+        ]
+    }
+
+    try:
+        response = requests.post(GEMINI_URL, headers=headers, json=data)
+        response_json = response.json()
+
+        if "candidates" not in response_json:
+            return "⚠️ Gemini API Error: Unexpected response. No text was returned."
+
+        result = response_json["candidates"][0]["content"]["parts"][0]["text"]
+        return result
+
+    except Exception as e:
+        return f"⚠️ Gemini API Error: {e}"
+
+def get_wikipedia_article(topic):
+    """Fetches the full Wikipedia article and reformulates it with Gemini 2.0 Flash."""
+    user_agent = "MathResearchAI/1.0 (https://huggingface.co/spaces/AdelMessaoudi-13/MathResearchIA)"
+
+    wiki = wikipediaapi.Wikipedia(language="en", user_agent=user_agent)
+    page = wiki.page(topic)
+
+    if not page.exists():
+        return f"⚠️ No article found for '{topic}'."
+
+    raw_text = page.text  # 🔍 Retrieve the full article
+
+    summary = generate_summary(raw_text)  # 🔍 Summarize with Gemini
+
+    wikipedia_url = page.fullurl  # 🔗 Include Wikipedia source
+    summary_with_source = f"{summary}\n\n🔗 **Wikipedia Source**: {wikipedia_url}"
+
+    return summary_with_source