Update app.py

app.py

@@ -1,178 +1,130 @@
 import gradio as gr
-import fitz  # PyMuPDF
 import requests
 import os
+import arxiv
+import io
+from pypdf import PdfReader
 
 # -----------------------------
-# CONFIG
+# LLM ENGINE (Grok-4)
 # -----------------------------
-XAI_API_KEY = os.getenv("XAI_API_KEY")
-XAI_URL = "https://api.x.ai/v1/chat/completions"
+API_KEY = os.getenv("XAI_API_KEY")
+API_URL = "https://api.x.ai/v1/chat/completions"
 
-
-# -----------------------------
-# PDF TEXT EXTRACTION
-# -----------------------------
-def extract_text(file):
-    try:
-        doc = fitz.open(file.name)
-        text = ""
-        for page in doc:
-            text += page.get_text()
-        return text[:20000]
-    except Exception as e:
-        return f"Error reading PDF: {str(e)}"
-
-
-# -----------------------------
-# GROK CALL
-# -----------------------------
 def call_grok(prompt):
-    headers = {
-        "Authorization": f"Bearer {XAI_API_KEY}",
-        "Content-Type": "application/json"
-    }
-
-    data = {
+    headers = {"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"}
+    payload = {
         "model": "grok-4-1-fast-non-reasoning",
         "messages": [
-            {"role": "system", "content": "You are an expert AI research analyst."},
+            {"role": "system", "content": "You are an expert polymath, research scientist, and critic. Use LaTeX for math ($...$ or $$...$$). Be dense, technical, and objective."},
             {"role": "user", "content": prompt}
         ],
-        "temperature": 0.7
+        "temperature": 0.15 
     }
-
     try:
-        response = requests.post(XAI_URL, headers=headers, json=data, timeout=60)
-        result = response.json()
-        return result["choices"][0]["message"]["content"]
+        response = requests.post(API_URL, headers=headers, json=payload, timeout=60)
+        return response.json()["choices"][0]["message"]["content"]
     except Exception as e:
-        return f"API Error: {str(e)} | {response.text if 'response' in locals() else ''}"
-
+        return f"LLM Error: {str(e)}"
 
 # -----------------------------
-# MAIN ANALYSIS PIPELINE
+# THE ENGINE ROOM
 # -----------------------------
-def analyze_paper(file):
-    if file is None:
-        return ["❌ Please upload a PDF."]
-
-    text = extract_text(file)
-
-    prompt = f"""
-Analyze this research paper and return a structured explanation.
-
-FORMAT STRICTLY as sections with clear headings:
-
-# 🧠 Core Idea
-# ❓ Research Question
-# 🏗 Problem It Solves
-# ⚙️ Methodology
-# 📊 Data & Experiments
-# 🧮 Math Explained Simply
-# 📈 Key Results
-# 💡 Key Insights
-# ⚠️ Limitations
-# 🧠 AI Critique
-# 👨‍🔬 About the Authors
-# 🔗 Related Concepts
-# 🧾 Summary
-
-Rules:
-- Explain clearly and deeply
-- Simplify math intuitively
-- Be insightful, not generic
-- No fluff
-
-Paper:
-{text}
-"""
-
-    result = call_grok(prompt)
-
-    # Split into sections by headings
-    sections = [s.strip() for s in result.split("\n#") if s.strip()]
-    sections = [("#" + s) if not s.startswith("#") else s for s in sections]
-
-    return sections
-
-
-# -----------------------------
-# DEEP EXPLAIN (PER SECTION)
-# -----------------------------
-def explain_section(section):
-    if not section:
-        return ""
-
-    prompt = f"""
-Explain this section of a research paper in more depth.
-
-- Make it easier to understand
-- Add intuition
-- Give examples if possible
-
-Section:
-{section}
-"""
-    return call_grok(prompt)
-
-
-# -----------------------------
-# BUILD UI
-# -----------------------------
-with gr.Blocks(title="arXivForMe") as app:
-
-    gr.Markdown("# 📄 arXivForMe")
-    gr.Markdown("Understand any research paper from arXiv in minutes")
-
-    file_input = gr.File(label="Upload PDF", file_types=[".pdf"])
-    analyze_btn = gr.Button("🚀 Analyze Paper")
-
-    sections_state = gr.State([])
-
-    section_dropdown = gr.Dropdown(label="Sections", choices=[])
-    section_output = gr.Markdown()
-
-    explain_btn = gr.Button("🧠 Explain Deeper")
-    deep_output = gr.Markdown()
-
-    # -----------------------------
-    # EVENTS
-    # -----------------------------
-
-    def update_dropdown(sections):
-        return gr.update(choices=[f"Section {i}" for i in range(len(sections))])
-
-    def show_section(sections, idx):
-        if idx is None:
-            return ""
-        return sections[int(idx.split()[-1])]
-
-    analyze_btn.click(
-        analyze_paper,
-        inputs=file_input,
-        outputs=sections_state
-    ).then(
-        update_dropdown,
-        inputs=sections_state,
-        outputs=section_dropdown
-    )
-
-    section_dropdown.change(
-        show_section,
-        inputs=[sections_state, section_dropdown],
-        outputs=section_output
-    )
-
-    explain_btn.click(
-        explain_section,
-        inputs=section_output,
-        outputs=deep_output
-    )
-
+def analyze_full_paper(url):
+    try:
+        # 1. Fetch Metadata
+        paper_id = url.split('/')[-1].split('v')[0]
+        search = arxiv.Search(id_list=[paper_id])
+        paper = next(search.results())
+        
+        # 2. Extract PDF Text (Targeting the first 10 pages for depth)
+        resp = requests.get(paper.pdf_url)
+        reader = PdfReader(io.BytesIO(resp.content))
+        content = "".join([page.extract_text() for page in reader.pages[:10]])
+
+        # 3. Master Prompt
+        prompt = f"""
+        PAPER: {paper.title}
+        AUTHORS: {', '.join([a.name for a in paper.authors])}
+        CONTENT: {content[:15000]}
+
+        Provide an exhaustive breakdown using these EXACT markers:
+        [SUMMARY] - High-level TL;DR.
+        [PROBLEM] - The specific research gap.
+        [IDEAS] - The core conceptual innovations.
+        [THEORY] - The formal mathematical framework (Use LaTeX).
+        [ALGO] - The implementation logic or pseudocode.
+        [FINDINGS] - Data, benchmarks, and results.
+        [AUTHORS] - Evaluation of the authors' expertise and potential institutional bias.
+        [VERDICT] - Brutal honest critique: What's good, what's bad, and is it overhyped?
+        """
+        
+        raw_resp = call_grok(prompt)
+        
+        # 4. Parse into Tabs
+        markers = ["[SUMMARY]", "[PROBLEM]", "[IDEAS]", "[THEORY]", "[ALGO]", "[FINDINGS]", "[AUTHORS]", "[VERDICT]"]
+        data = {m: "Section not generated." for m in markers}
+        current = None
+        for line in raw_resp.split('\n'):
+            if line.strip() in markers:
+                current = line.strip()
+                data[current] = ""
+            elif current:
+                data[current] += line + "\n"
+
+        return [paper.title] + [data[m] for m in markers]
+    
+    except Exception as e:
+        return [f"Error: {str(e)}"] + [""] * 8
 
 # -----------------------------
-# LAUNCH
+# THE DASHBOARD UI
 # -----------------------------
-if __name__ == "__main__":
-    app.launch()
+with gr.Blocks(theme=gr.themes.Default(primary_hue="orange", secondary_hue="slate"), title="arXivForMe Ultra") as demo:
+    gr.Markdown("# 🧬 arXivForMe: The Full Intelligence Suite")
+    gr.Markdown("*Deep-dive analysis of any arXiv paper: Theory, Math, and Critical Review.*")
+    
+    with gr.Row():
+        url_input = gr.Textbox(label="arXiv URL", placeholder="https://arxiv.org/abs/2401.xxxxx", scale=4)
+        run_btn = gr.Button("RUN FULL ANALYSIS", variant="primary", scale=1)
+
+    paper_head = gr.HTML("<h2 style='text-align: center;'>Submit a paper to begin extraction</h2>")
+
+    with gr.Tabs():
+        with gr.Tab("📋 Executive Summary"):
+            with gr.Row():
+                with gr.Column():
+                    gr.Markdown("### TL;DR")
+                    out_sum = gr.Markdown()
+                with gr.Column():
+                    gr.Markdown("### The Research Problem")
+                    out_prob = gr.Markdown()
+
+        with gr.Tab("💡 Main Ideas"):
+            out_idea = gr.Markdown()
+
+        with gr.Tab("📐 Math & Theory"):
+            gr.Markdown("### Mathematical Framework")
+            out_theo = gr.Markdown()
+
+        with gr.Tab("💻 Algorithm"):
+            gr.Markdown("### Logic & Implementation")
+            out_algo = gr.Markdown()
+
+        with gr.Tab("📊 Findings"):
+            gr.Markdown("### Results & Benchmarks")
+            out_find = gr.Markdown()
+
+        with gr.Tab("👤 Author Analysis"):
+            gr.Markdown("### Reputation & Context")
+            out_auth = gr.Markdown()
+
+        with gr.Tab("⚖️ AI Opinion"):
+            gr.Markdown("### The Brutal Verdict")
+            out_verd = gr.Markdown()
+
+    output_list = [paper_head, out_sum, out_prob, out_idea, out_theo, out_algo, out_find, out_auth, out_verd]
+    
+    run_btn.click(fn=analyze_full_paper, inputs=url_input, outputs=output_list)
+
+demo.launch()