initial commit

.dockerignore

@@ -0,0 +1,9 @@
+node_modules
+dist
+.git
+.env.local
+.DS_Store
+__pycache__
+*.pyc
+backend/__pycache__
+backend/*.pyc

.gitignore

@@ -0,0 +1,25 @@
+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+lerna-debug.log*
+
+node_modules
+dist
+dist-ssr
+*.local
+
+# Editor directories and files
+.vscode/*
+!.vscode/extensions.json
+.idea
+.DS_Store
+*.suo
+*.ntvs*
+*.njsproj
+*.sln
+*.sw?
+.claude/*

App.tsx

@@ -0,0 +1,438 @@
+import React, { useState, useCallback, useEffect } from 'react';
+import { Classification, DocumentFile, Innovation, MeetingDoc } from './types';
+import { backendService } from './services/backendService';
+import FilterBar from './components/FilterBar';
+import DocFilterBar from './components/DocFilterBar';
+import StatsDashboard from './components/StatsDashboard';
+import FileContentCard from './components/FileContentCard';
+import InnovationCard from './components/InnovationCard';
+import { LayoutDashboard, FileText, Settings, Play, CheckCircle2, CircleDashed } from 'lucide-react';
+import { useLiveQuery } from 'dexie-react-hooks';
+
+const App: React.FC = () => {
+  // Application State
+  const [files, setFiles] = useState<DocumentFile[]>([]);
+  const [innovations, setInnovations] = useState<Innovation[]>([]);
+
+  const [isFetchingDocs, setIsFetchingDocs] = useState(false);
+  const [isProcessing, setIsProcessing] = useState(false);
+
+  // Progress tracking
+  const [processedCount, setProcessedCount] = useState(0);
+  const [currentProcessingFile, setCurrentProcessingFile] = useState<string>("");
+
+  const [currentView, setCurrentView] = useState<'list' | 'dashboard'>('list');
+
+  // New state for raw docs from API
+  const [rawDocs, setRawDocs] = useState<MeetingDoc[]>([]);
+
+  // Pattern state
+  const [patterns, setPatterns] = useState<any[]>([]);
+  const [selectedPatternId, setSelectedPatternId] = useState<number | null>(null);
+  const [isAnalyzing, setIsAnalyzing] = useState(false);
+
+  // Metadata state for Backend
+  const [selectedWG, setSelectedWG] = useState<string>("");
+  const [selectedMeeting, setSelectedMeeting] = useState<string>("");
+
+  useEffect(() => {
+    const fetchPatterns = async () => {
+      const data = await backendService.getPatterns();
+      setPatterns(data);
+      if (data.length > 0) {
+        setSelectedPatternId(data[0].pattern_id);
+      }
+    };
+    fetchPatterns();
+  }, []);
+
+
+  const handleFetchDocuments = useCallback(async (wg: string, meeting: string) => {
+    setIsFetchingDocs(true);
+    setFiles([]);
+    setInnovations([]);
+    setRawDocs([]);
+    setProcessedCount(0);
+    setSelectedWG(wg);
+    setSelectedMeeting(meeting);
+
+    try {
+      const response = await fetch('https://organizedprogrammers-docxtract.hf.space/docs/get_meeting_docs', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({ "working_group": wg, "meeting": meeting, "custom_url": null })
+      });
+
+      if (response.ok) {
+        const data = await response.json();
+        if (data.data && Array.isArray(data.data)) {
+          setRawDocs(data.data);
+        }
+      } else {
+        console.error("Failed to fetch docs");
+      }
+    } catch (error) {
+      console.error("Error fetching docs:", error);
+    } finally {
+      setIsFetchingDocs(false);
+    }
+  }, []);
+
+  const handleFilterChange = useCallback((filteredDocs: MeetingDoc[]) => {
+    // Convert MeetingDoc to DocumentFile
+    const newFiles: DocumentFile[] = filteredDocs.map((doc, index) => ({
+      id: doc.TDoc || `doc-${index}`,
+      filename: doc.TDoc ? `${doc.TDoc}.zip` : `Document ${index}`,
+      size: 'Unknown', // API doesn't provide size
+      type: doc.Type,
+      uploaded: false,
+      status: doc["TDoc Status"],
+      agendaItem: doc["Agenda item description"],
+      url: doc.URL
+    }));
+
+    setFiles(newFiles);
+    setProcessedCount(0);
+    setInnovations([]);
+  }, []);
+
+  // Logic: Backend Processing Engine (Phase 2 - SQLite)
+  const handleExtractInnovations = async () => {
+    if (files.length === 0) return;
+    setIsProcessing(true);
+    setProcessedCount(0);
+    setInnovations([]);
+
+    // Sequential Processing Logic
+    for (let i = 0; i < files.length; i++) {
+      const file = files[i];
+      setCurrentProcessingFile(file.filename);
+
+      // Process individually via Backend
+      const result = await backendService.processDocument(file, selectedWG, selectedMeeting);
+
+      if (result) {
+        setInnovations(prev => [...prev, result]);
+      }
+
+      setProcessedCount(prev => prev + 1);
+    }
+
+    setIsProcessing(false);
+    setCurrentProcessingFile("");
+  };
+
+  const handleClassify = async (id: string, classification: Classification) => {
+    // Find the innovation by ID or result_id (since InnovationCard passes result_id)
+    const numId = Number(id);
+    const targetInv = innovations.find(i => i.id === id || (!isNaN(numId) && i.result_id === numId));
+
+    if (!targetInv) return;
+
+    // 1. Update Local State
+    setInnovations(prev => prev.map(inv =>
+      inv.id === targetInv.id ? { ...inv, classification } : inv
+    ));
+
+    // 2. Persist to Backend if we have a result_id
+    if (targetInv.result_id) {
+      await backendService.saveClassification(targetInv.result_id, classification);
+    }
+  };
+
+  const handleFileUpload = (e: React.ChangeEvent<HTMLInputElement>) => {
+    const file = e.target.files?.[0];
+    if (file && file.type === 'text/plain') {
+      const reader = new FileReader();
+      reader.onload = (event) => {
+        const text = event.target?.result as string;
+        const newInnovation: Innovation = {
+          id: `uploaded-${Date.now()}`,
+          file_name: file.name,
+          answer: text,
+          classification: Classification.UNCLASSIFIED
+        };
+        setInnovations(prev => [...prev, newInnovation]);
+      };
+      reader.readAsText(file);
+    } else {
+      alert("Please upload a .txt file");
+    }
+  };
+
+  const handleAnalyze = async () => {
+    if (!selectedPatternId) {
+      alert("Please select a pattern");
+      return;
+    }
+
+    if (innovations.length === 0) {
+      alert("No documents to analyze.");
+      return;
+    }
+
+    setIsAnalyzing(true);
+
+    try {
+      const updatedInnovations = [...innovations];
+
+      for (let i = 0; i < updatedInnovations.length; i++) {
+        const inv = updatedInnovations[i];
+        let result: string | null = null;
+        let resultId: number | undefined;
+
+        // If it's an uploaded file (id starts with uploaded-), pass text content
+        if (inv.id.startsWith('uploaded-')) {
+          const res = await backendService.analyzeContent(selectedPatternId, undefined, inv.answer);
+          if (res) {
+            updatedInnovations[i] = {
+              ...inv,
+              analysis_result: res.content,
+              result_id: res.result_id,
+              methodology: res.methodology,
+              context: res.context,
+              problem: res.problem,
+              pattern_name: res.pattern_name
+            };
+          }
+        } else {
+          // It's a processed doc, pass the ID
+          const res = await backendService.analyzeContent(selectedPatternId, inv.id);
+          if (res) {
+            updatedInnovations[i] = {
+              ...inv,
+              analysis_result: res.content,
+              result_id: res.result_id,
+              methodology: res.methodology,
+              context: res.context,
+              problem: res.problem,
+              pattern_name: res.pattern_name
+            };
+          }
+        }
+      }
+
+      setInnovations(updatedInnovations);
+    } catch (error) {
+      console.error("Error during analysis:", error);
+    } finally {
+      setIsAnalyzing(false);
+    }
+  };
+
+  const pendingInnovations = innovations.filter(i => i.classification !== Classification.DELETE);
+  const progressPercent = files.length > 0 ? (processedCount / files.length) * 100 : 0;
+
+  return (
+    <div className="min-h-screen bg-slate-50 font-sans text-slate-900">
+
+      {/* 1. Header */}
+      <header className="bg-slate-900 text-white shadow-md sticky top-0 z-50">
+        <div className="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
+          <div className="flex justify-between h-16 items-center">
+            <div className="flex items-center">
+              <div className="bg-blue-500 p-1.5 rounded mr-3">
+                <FileText className="h-5 w-5 text-white" />
+              </div>
+              <div>
+                <h1 className="text-lg font-bold tracking-tight">3GPP Innovation Extractor</h1>
+                <p className="text-xs text-slate-400">SQLite Backend Powered</p>
+              </div>
+            </div>
+            <nav className="flex space-x-4">
+              <button
+                onClick={() => setCurrentView('list')}
+                className={`px-3 py-2 rounded-md text-sm font-medium transition-colors ${currentView === 'list' ? 'bg-slate-800 text-white' : 'text-slate-300 hover:text-white hover:bg-slate-800'}`}
+              >
+                Extraction
+              </button>
+              <button
+                onClick={() => setCurrentView('dashboard')}
+                className={`px-3 py-2 rounded-md text-sm font-medium transition-colors ${currentView === 'dashboard' ? 'bg-slate-800 text-white' : 'text-slate-300 hover:text-white hover:bg-slate-800'}`}
+              >
+                Analytics
+              </button>
+            </nav>
+          </div>
+        </div>
+      </header>
+
+      <main className="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-8">
+
+        {/* View: Extraction List */}
+        <div className={currentView === 'list' ? 'animate-fade-in' : 'hidden'}>
+          <FilterBar onFetch={handleFetchDocuments} isFetching={isFetchingDocs} />
+
+          {rawDocs.length > 0 && (
+            <DocFilterBar docs={rawDocs} onFilterChange={handleFilterChange} />
+          )}
+
+          <div className="grid grid-cols-1 lg:grid-cols-12 gap-8">
+
+            {/* Left Column: Files & Status */}
+            <div className="lg:col-span-4 space-y-6">
+
+              {/* File Stats Card */}
+              <div className="bg-white rounded-lg shadow-sm border border-slate-200 p-5">
+                <div className="flex items-center justify-between mb-4">
+                  <h2 className="font-semibold text-slate-800">Documents</h2>
+                  <span className="text-xs font-mono bg-slate-100 px-2 py-1 rounded text-slate-600">
+                    {files.length} Files
+                  </span>
+                </div>
+
+                {files.length === 0 ? (
+                  <div className="text-center py-8 text-slate-400 text-sm border-2 border-dashed border-slate-100 rounded-lg">
+                    No documents selected
+                  </div>
+                ) : (
+                  <div className="mb-4">
+                    <div className="flex justify-between text-xs text-slate-500 mb-1">
+                      <span>Processing Progress</span>
+                      <span>{processedCount} / {files.length}</span>
+                    </div>
+                    <div className="h-2 w-full bg-slate-100 rounded-full overflow-hidden">
+                      <div className="h-full bg-blue-500 transition-all duration-300" style={{ width: `${progressPercent}%` }}></div>
+                    </div>
+                    {isProcessing && (
+                      <p className="text-xs text-blue-500 mt-2 animate-pulse">
+                        Processing: {currentProcessingFile}
+                      </p>
+                    )}
+                  </div>
+                )}
+
+                <div className="mt-4">
+                  <button
+                    onClick={handleExtractInnovations}
+                    disabled={files.length === 0 || isProcessing}
+                    className="w-full bg-slate-900 hover:bg-slate-800 text-white font-medium py-3 rounded-lg shadow-md transition-all disabled:opacity-50 disabled:cursor-not-allowed flex items-center justify-center"
+                  >
+                    {isProcessing ? (
+                      <><CircleDashed className="w-4 h-4 mr-2 animate-spin" /> Processing...</>
+                    ) : (
+                      <><Play className="w-4 h-4 mr-2 fill-current" /> Start Extraction</>
+                    )}
+                  </button>
+                </div>
+              </div>
+
+              {/* Pattern Analysis Card */}
+              <div className="bg-white rounded-lg shadow-sm border border-slate-200 p-5">
+                <h2 className="font-semibold text-slate-800 mb-4">Pattern Analysis</h2>
+
+                <div className="space-y-4">
+                  <div>
+                    <label className="block text-xs font-medium text-slate-500 mb-1">Select Pattern</label>
+                    <select
+                      className="w-full bg-slate-50 border border-slate-200 rounded-md px-3 py-2 text-sm focus:outline-none focus:ring-2 focus:ring-blue-500"
+                      value={selectedPatternId || ''}
+                      onChange={(e) => setSelectedPatternId(Number(e.target.value))}
+                    >
+                      {patterns.map(p => (
+                        <option key={p.pattern_id} value={p.pattern_id}>{p.pattern_name}</option>
+                      ))}
+                    </select>
+                  </div>
+
+                  <div>
+                    <label className="block text-xs font-medium text-slate-500 mb-1">Upload .txt File (Optional)</label>
+                    <input
+                      type="file"
+                      accept=".txt"
+                      onChange={handleFileUpload}
+                      className="w-full text-xs text-slate-500 file:mr-4 file:py-2 file:px-4 file:rounded-full file:border-0 file:text-xs file:font-semibold file:bg-blue-50 file:text-blue-700 hover:file:bg-blue-100"
+                    />
+                    {/* Upload status is now handled in the main list */}
+                  </div>
+
+                  <button
+                    onClick={handleAnalyze}
+                    disabled={isAnalyzing || innovations.length === 0}
+                    className="w-full bg-blue-600 hover:bg-blue-700 text-white font-medium py-2 rounded-lg shadow-sm transition-all disabled:opacity-50 flex items-center justify-center text-sm"
+                  >
+                    {isAnalyzing ? (
+                      <><CircleDashed className="w-4 h-4 mr-2 animate-spin" /> Analyzing...</>
+                    ) : (
+                      <><Play className="w-4 h-4 mr-2 fill-current" /> Analyse</>
+                    )}
+                  </button>
+                </div>
+              </div>
+            </div>
+
+            {/* Right Column: Results */}
+            <div className="lg:col-span-8">
+              <div className="flex items-center justify-between mb-4">
+                <h2 className="text-xl font-bold text-slate-800">Files content refined</h2>
+                {innovations.length > 0 && (
+                  <span className="text-sm text-slate-500">
+                    Showing {pendingInnovations.length} potential items
+                  </span>
+                )}
+              </div>
+
+              {innovations.length === 0 ? (
+                <div className="bg-white rounded-xl border border-dashed border-slate-300 p-12 text-center">
+                  <div className="mx-auto bg-slate-50 w-16 h-16 rounded-full flex items-center justify-center mb-4">
+                    <Settings className="w-8 h-8 text-slate-400" />
+                  </div>
+                  <h3 className="text-lg font-medium text-slate-900">Ready to Process</h3>
+                  <p className="text-slate-500 max-w-sm mx-auto mt-2">
+                    Load documents and start the extraction engine. The Data will be mocked and stored in your local SQLite database.
+                  </p>
+                </div>
+              ) : (
+                <div className="space-y-4">
+                  {pendingInnovations.map(inv => (
+                    <div key={inv.id}>
+                      <FileContentCard
+                        innovation={inv}
+                        onClassify={handleClassify}
+                      />
+                      {inv.analysis_result && (
+                        <div className="ml-8 mt-2">
+                          <InnovationCard
+                            innovation={{
+                              id: inv.result_id || 0,
+                              file_name: inv.file_name,
+                              content: inv.analysis_result || "",
+                              classification: inv.classification,
+                              methodology: inv.methodology || "N/A",
+                              context: inv.context || "N/A",
+                              problem: inv.problem || "N/A",
+                            }}
+                            onClassify={handleClassify}
+                          />
+                        </div>
+                      )}
+                    </div>
+                  ))}
+                  {pendingInnovations.length === 0 && innovations.length > 0 && (
+                    <div className="text-center py-10 text-slate-500">
+                      All items have been deleted. Check the Analytics tab for stats.
+                    </div>
+                  )}
+                </div>
+              )}
+            </div>
+          </div>
+        </div>
+
+
+        {/* View: Analytics Dashboard */}
+        <div className={currentView === 'dashboard' ? 'animate-fade-in' : 'hidden'}>
+          <div className="flex items-center justify-between mb-6">
+            <h2 className="text-2xl font-bold text-slate-900">Classification Analytics</h2>
+          </div>
+
+          <StatsDashboard innovations={[]} isVisible={currentView === 'dashboard'} />
+
+        </div>
+
+      </main>
+    </div>
+  );
+};
+
+export default App;

Dockerfile

@@ -0,0 +1,39 @@
+# Stage 1: Build Frontend
+FROM node:20-alpine as build
+WORKDIR /app
+COPY package.json package-lock.json ./
+# Install dependencies
+RUN npm install
+# Copy source code
+COPY . .
+# Build
+RUN npm run build
+
+# Stage 2: Run Backend
+FROM python:3.10-slim
+
+WORKDIR /app
+
+# Install system dependencies
+# RUN apt-get update && apt-get install -y gcc
+
+# Install Python dependencies
+COPY backend/requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy Backend Code
+# We copy contents of backend/ directly to /app so main.py is at /app/main.py
+COPY backend /app
+
+# Copy Built Frontend from Stage 1 to /app/static
+COPY --from=build /app/dist /app/static
+
+# Create cache directory for Hugging Face (optional, but good for permissions)
+RUN mkdir -p /app/cache
+ENV HF_HOME=/app/cache
+
+# Expose port (HF Spaces uses 7860)
+EXPOSE 7860
+
+# Run Application
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]

README.md

@@ -1,11 +1,80 @@
----
-title: 3GPP Innovation Extractor
-emoji: 🏢
-colorFrom: yellow
-colorTo: gray
-sdk: docker
-pinned: false
-short_description: Extract and generate context - problem description from 3GPP
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+<div align="center">
+<img width="1200" height="475" alt="GHBanner" src="https://github.com/user-attachments/assets/0aa67016-6eaf-458a-adb2-6e31a0763ed6" />
+</div>
+
+# Run and deploy your AI Studio app
+
+This contains everything you need to run your app locally.
+
+View your app in AI Studio: https://ai.studio/apps/drive/1O8Eus7hM_SgPBOyiJCLEArY0Jz76f6bF
+
+## Run Locally
+
+**Prerequisites:**  Node.js
+
+
+1. Install dependencies:
+   `npm install`
+2. Set the `GEMINI_API_KEY` in [.env.local](.env.local) to your Gemini API key
+3. Run the app:
+   `npm run dev`
+
+
+Workflow Overview
+
+```mermaid
+flowchart TD
+    subgraph S1 [Phase 1: Data Ingestion]
+        A[User Selects Working Group] -->|SA1-6, RAN1-2| B[Fetch Meetings via POST]
+        B --> C[User Selects Meeting]
+        C --> D[Filter Docs by Metadata]
+        D --> E[Extract Raw Text]
+    end
+
+    subgraph S2 [Phase 2: Refinement & Caching]
+        E --> F{Text in Cache?}
+        F -- Yes --> G[Retrieve Cached Refinement]
+        F -- No --> H[LLM Processing]
+        H --> I[Task: Dense Chunking & 'What's New']
+        I --> J[Store in Dataset]
+        J --> G
+    end
+
+    subgraph S3 [Phase 3: Pattern Analysis]
+        G --> K[User Selects Pattern/Prompt]
+        K --> L{Result in Cache?}
+        L -- Yes --> M[Retrieve Analysis]
+        L -- No --> N[Execute Pattern]
+        N --> O[Multi-Model Verification]
+        O --> P[Store Result]
+    end
+
+    S1 --> S2 --> S3
+```
+
+### Detailed Process Specification
+
+#### Phase 1: Data Ingestion & Extraction
+The user navigates a strict hierarchy to isolate relevant source text.
+1.  **Working Group Selection:** User selects one group from the allowlist: `['SA1', 'SA2', 'SA3', 'SA4', 'SA5', 'SA6', 'RAN1', 'RAN2']`.
+2.  **Meeting Retrieval:** System executes a `POST` request to the endpoint using the selected Working Group to retrieve the meeting list.
+3.  **Document Filtering:** User selects a meeting, then filters the resulting file list using available metadata.
+4.  **Text Extraction:** System extracts raw content from the filtered files into a text list.
+
+#### Phase 2: Content Refinement (with Caching)
+Raw text is processed into high-value summaries to reduce noise.
+*   **Cache Check:** Before processing, check the dataset for existing `(text_hash, refined_output)` pairs to prevent duplicate processing.
+*   **LLM Processing:** If not cached, pass text to the selected LLM (default provided, user-changeable).
+*   **Prompt Objective:**
+    1.  Create information-dense chunks (minimize near-duplicates).
+    2.  Generate a "What's New" paragraph wrapped in `SUGGESTION START` and `SUGGESTION END` tags.
+*   **Storage:** Save the input text and the LLM output to the dataset.
+
+#### Phase 3: Pattern Analysis & Verification
+Refined text is analyzed using specific user-defined patterns.
+*   **Pattern Selection:** User applies a specific prompt/pattern to the refined documents.
+*   **Cache Check:** Check the results database for existing `(document_id, pattern_id)` results.
+*   **Execution & Verification:**
+    *   Run the selected pattern against the documents.
+    *   **Verifier Mode:** Optionally execute the same input across multiple models simultaneously to compare results and ensure accuracy.
+*   **Storage:** Save the final analysis in the database to prevent future re-computation.

backend/.env

@@ -0,0 +1,2 @@
+GEMINI_API_KEY=AIzaSyC9XHvWz4gxQAJoUyuiK07EaZct53dHtgE
+GROQ_API_KEY=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

backend/data_service.py

@@ -0,0 +1,326 @@
+
+import os
+import pandas as pd
+from datasets import load_dataset, Dataset, DatasetDict
+from huggingface_hub import login
+import logging
+from typing import List, Optional, Dict, Any
+
+from dotenv import load_dotenv
+
+logger = logging.getLogger(__name__)
+
+# Load envs
+load_dotenv()
+load_dotenv("../.env.local")
+
+class DataService:
+    def __init__(self):
+        self.hf_token = os.getenv("HF_TOKEN")
+        self.dataset_name = os.getenv("HF_DATASET_NAME")
+        
+        if not self.hf_token or not self.dataset_name:
+            logger.error("HF_TOKEN or HF_DATASET_NAME not set via environment variables.")
+            # We might want to raise an error here or handle it gracefully if running locally without HF
+            # For now, we'll log error.
+            
+        if self.hf_token:
+            login(token=self.hf_token)
+
+        self.configs = ["files", "refined", "patterns", "results"]
+        self.data: Dict[str, pd.DataFrame] = {}
+        
+        self._load_data()
+
+    def _load_data(self):
+        """Loads data from HF Hub for each config. Initializes empty if not found."""
+        for config in self.configs:
+            try:
+                # trust_remote_code=True is sometimes needed, but for simple datasets usually not.
+                # using split="train" by default as load_dataset returns a DatasetDict if split not specified
+                ds = load_dataset(self.dataset_name, config, split="train")
+                self.data[config] = ds.to_pandas()
+                logger.info(f"Loaded config '{config}' with {len(self.data[config])} rows.")
+            except Exception as e:
+                logger.warning(f"Could not load config '{config}' from HF: {e}. Initializing empty.")
+                self.data[config] = pd.DataFrame()
+
+    def _save(self, config_name: str):
+        """Pushes the specific config DataFrame to HF Hub."""
+        if not self.hf_token or not self.dataset_name:
+            logger.warning("Skipping save to HF: Credentials missing.")
+            return
+
+        try:
+            df = self.data[config_name]
+            # Convert DataFrame to Dataset
+            ds = Dataset.from_pandas(df)
+            # Push to hub
+            # We need to preserve the columns.
+            ds.push_to_hub(self.dataset_name, config_name=config_name, token=self.hf_token)
+            logger.info(f"Saved config '{config_name}' to HF Hub.")
+        except Exception as e:
+            logger.error(f"Failed to save config '{config_name}': {e}")
+
+    # --- Schema Helpers ---
+    # These ensure we have the right columns even if empty
+
+    def _ensure_columns(self, config, columns):
+        if self.data[config].empty:
+            self.data[config] = pd.DataFrame(columns=columns)
+        else:
+            # Add missing columns if any
+            for col in columns:
+                if col not in self.data[config].columns:
+                    self.data[config][col] = None
+
+    # --- File Operations ---
+
+    def get_all_files(self) -> List[Dict[str, Any]]:
+        if self.data["files"].empty:
+            return []
+        return self.data["files"].to_dict(orient="records")
+
+    def get_file_content(self, file_id: str) -> Optional[str]:
+        df = self.data["files"]
+        if df.empty: return None
+        row = df[df["file_id"] == file_id]
+        if not row.empty:
+            return row.iloc[0]["content"]
+        return None
+
+    def add_file(self, file_data: Dict[str, Any]):
+        self._ensure_columns("files", ["file_id", "working_group", "meeting", "type", "status", "agenda_item", "content", "filename", "timestamp"])
+        df = self.data["files"]
+        
+        # Check if exists
+        if not df.empty and file_id in df["file_id"].values:
+             # Update? Or Skip? The original code did INSERT, so it might fail on duplicate PK usually?
+             # SQLite: INSERT INTO file ... (if PK integrity error, it fails).
+             # We will overwrite if exists for simplicity or skip.
+             # Let's overwrite.
+             file_id = file_data["file_id"]
+             df = df[df["file_id"] != file_id]
+        
+        # Add new row
+        new_row = pd.DataFrame([file_data])
+        self.data["files"] = pd.concat([df, new_row], ignore_index=True)
+        self._save("files")
+
+    # --- Refined Operations ---
+
+    def get_refined_output(self, file_id: str) -> Optional[str]:
+        df = self.data["refined"]
+        if df.empty: return None
+        row = df[df["file_id"] == file_id]
+        if not row.empty:
+            return row.iloc[0]["refined_output"]
+        return None
+
+    def add_refined(self, file_id: str, refined_output: str) -> int:
+        self._ensure_columns("refined", ["refined_id", "refined_output", "file_id"])
+        df = self.data["refined"]
+        
+        # Generate ID
+        next_id = 1
+        if not df.empty:
+            # check max. If refined_id is not numeric (e.g. None), handle it.
+            # Assuming it is numeric as per SQLite schema
+            max_id = pd.to_numeric(df["refined_id"]).max()
+            if not pd.isna(max_id):
+                next_id = int(max_id) + 1
+        
+        new_row = pd.DataFrame([{
+            "refined_id": next_id,
+            "refined_output": refined_output,
+            "file_id": file_id
+        }])
+        
+        self.data["refined"] = pd.concat([df, new_row], ignore_index=True)
+        self._save("refined")
+        return next_id
+    
+    def get_refined_by_file_id(self, file_id: str):
+        df = self.data["refined"]
+        if df.empty: return None
+        row = df[df["file_id"] == file_id]
+        if not row.empty:
+            return row.iloc[0].to_dict()
+        return None
+
+    # --- Pattern Operations ---
+
+    def get_patterns(self) -> List[Dict[str, Any]]:
+        if self.data["patterns"].empty:
+            return []
+        return self.data["patterns"].to_dict(orient="records")
+    
+    def get_pattern(self, pattern_id: int):
+        df = self.data["patterns"]
+        if df.empty: return None
+        row = df[df["pattern_id"] == pattern_id]
+        if not row.empty:
+            return row.iloc[0].to_dict()
+        return None
+
+    def add_pattern(self, pattern_name: str, prompt: str) -> int:
+        self._ensure_columns("patterns", ["pattern_id", "pattern_name", "prompt"])
+        df = self.data["patterns"]
+        
+        next_id = 1
+        if not df.empty:
+            max_id = pd.to_numeric(df["pattern_id"]).max()
+            if not pd.isna(max_id):
+                next_id = int(max_id) + 1
+        
+        new_row = pd.DataFrame([{
+            "pattern_id": next_id,
+            "pattern_name": pattern_name,
+            "prompt": prompt
+        }])
+        self.data["patterns"] = pd.concat([df, new_row], ignore_index=True)
+        self._save("patterns")
+        return next_id
+
+    def update_pattern(self, pattern_id: int, pattern_name: str, prompt: str):
+        df = self.data["patterns"]
+        if df.empty: return False
+        
+        # Check if exists
+        if pattern_id not in df["pattern_id"].values:
+            return False
+            
+        # Update
+        self.data["patterns"].loc[df["pattern_id"] == pattern_id, ["pattern_name", "prompt"]] = [pattern_name, prompt]
+        self._save("patterns")
+        return True
+
+    # --- Result Operations ---
+
+    def get_existing_result(self, file_id: str):
+        """
+        Equivalent to:
+        SELECT ... FROM result r JOIN refined ref ... WHERE refined.file_id = ?
+        """
+        # First get refined_id for file_id
+        ref_row = self.get_refined_by_file_id(file_id)
+        file_df = self.data["files"]
+        file_name = "Unknown File"
+        if not file_df.empty:
+            f_row = file_df[file_df["file_id"] == file_id]
+            if not f_row.empty:
+                file_name = f_row.iloc[0]["filename"]
+
+        if not ref_row:
+            return None, None, file_name
+        
+        refined_id = ref_row["refined_id"]
+        
+        # Search in results
+        res_df = self.data["results"]
+        if res_df.empty:
+             return None, refined_id, file_name
+        
+        # Filter where refined_id matches
+        # Note: result has refined_id
+        match = res_df[res_df["refined_id"] == refined_id]
+        
+        if match.empty:
+             return None, refined_id, file_name
+             
+        # Use the LAST result if multiple? Original SQL used simple join, usually implies 1-to-1 or fetchone
+        # We'll take the first one or last one.
+        result_row = match.iloc[-1].to_dict() # latest
+        
+        # Need pattern name
+        pat_df = self.data["patterns"]
+        pattern_name = "Unknown"
+        if not pat_df.empty and "pattern_id" in result_row:
+             pat_match = pat_df[pat_df["pattern_id"] == result_row["pattern_id"]]
+             if not pat_match.empty:
+                 pattern_name = pat_match.iloc[0]["pattern_name"]
+        
+        result_row["pattern_name"] = pattern_name
+        # normalize keys to match what main.py expects (content vs result_content)
+        # Main.py expects 'content' key for result_content
+        result_row["content"] = result_row.get("result_content")
+        
+        return result_row, refined_id, file_name
+
+    def add_result(self, pattern_id: int, refined_id: int, result_content: str, methodology: str, context: str, problem: str, classification: str = "UNCLASSIFIED") -> int:
+        self._ensure_columns("results", ["result_id", "pattern_id", "refined_id", "result_content", "methodology", "context", "problem", "classification"])
+        df = self.data["results"]
+        
+        next_id = 1
+        if not df.empty:
+             max_id = pd.to_numeric(df["result_id"]).max()
+             if not pd.isna(max_id):
+                 next_id = int(max_id) + 1
+        
+        new_row = pd.DataFrame([{
+            "result_id": next_id,
+            "pattern_id": pattern_id,
+            "refined_id": refined_id,
+            "result_content": result_content,
+            "methodology": methodology,
+            "context": context,
+            "problem": problem,
+            "classification": classification
+        }])
+        
+        self.data["results"] = pd.concat([df, new_row], ignore_index=True)
+        self._save("results")
+        return next_id
+
+    def update_classification(self, result_id: int, classification: str):
+        df = self.data["results"]
+        if df.empty: raise Exception("No results found")
+        
+        if result_id not in df["result_id"].values:
+             return False
+        
+        self.data["results"].loc[df["result_id"] == result_id, "classification"] = classification
+        self._save("results")
+        return True
+
+    def get_all_results_joined(self):
+        """
+        Joins results, refined, file, pattern
+        """
+        if self.data["results"].empty:
+            return []
+            
+        res_df = self.data["results"].copy()
+        
+        # Join Patterns
+        pat_df = self.data["patterns"]
+        if not pat_df.empty:
+            res_df = res_df.merge(pat_df[["pattern_id", "pattern_name"]], on="pattern_id", how="left")
+            
+        # Join Refined
+        ref_df = self.data["refined"]
+        if not ref_df.empty:
+            res_df = res_df.merge(ref_df[["refined_id", "file_id"]], on="refined_id", how="left")
+            
+        # Join File
+        def_file = self.data["files"]
+        if not def_file.empty:
+            res_df = res_df.merge(def_file[["file_id", "filename"]], on="file_id", how="left")
+            
+        # Select/Rename for output
+        # Mappings based on API: id, file_name, content, classification, pattern_name, etc.
+        out = []
+        for _, row in res_df.iterrows():
+            out.append({
+                "id": row.get("result_id"),
+                "file_name": row.get("filename"),
+                "content": row.get("result_content"),
+                "classification": row.get("classification"),
+                "pattern_name": row.get("pattern_name"),
+                "methodology": row.get("methodology"),
+                "context": row.get("context"),
+                "problem": row.get("problem")
+            })
+        # sort desc by id
+        out.sort(key=lambda x: x["id"] or 0, reverse=True)
+        return out

backend/main.py

@@ -0,0 +1,378 @@
+
+from datetime import datetime
+from fastapi import FastAPI, HTTPException, BackgroundTasks
+from fastapi.staticfiles import StaticFiles
+from fastapi.responses import FileResponse
+from pydantic import BaseModel
+from fastapi.middleware.cors import CORSMiddleware
+from google import genai
+from dotenv import load_dotenv
+import os
+import json
+import logging
+import re
+import mistune
+import requests
+from data_service import DataService
+
+# Load envs
+load_dotenv()
+load_dotenv("../.env.local")
+
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
+
+# Configure Logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+app = FastAPI(title="3GPP Innovation Backend")
+
+# Initialize DataService
+data_service = DataService()
+
+# CORS Setup
+origins = [
+    "http://localhost:5173",
+    "http://localhost:3000",
+    "*"
+]
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=origins,
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+
+def ask_gemini(prompt, content):
+    MAX_LEN = 10000
+
+    if len(prompt) + len(content) <= MAX_LEN:
+        client = genai.Client(api_key=GEMINI_API_KEY)
+        response = client.models.generate_content(
+            model="gemma-3-27b-it",
+            contents=prompt + "\n\n" + content
+        )
+        return response.text
+
+    chunk = content[:MAX_LEN - len(prompt)]
+    rest = content[MAX_LEN - len(prompt):]
+
+    first_answer = ask_gemini(prompt, chunk)
+    #remaining_answer = ask_gemini(prompt, rest)
+
+    return first_answer #+ "\n\n" + remaining_answer
+
+PROCESS_PROMPT = """
+Task : 
+Using the text provided, 
+create chunk that are dense in relevant information and minimize near-duplicate or 
+loosely related passages, provide a paragraph on whats new to this document using 
+the SUGGESTION START and END.
+"""
+
+def format_answer(answer):
+    return f"We obtained the following methodology:"+answer["methodology"]+"\n\nThe context is :"+answer["context"]+"\n\nThe problem description is :"+answer["problem"]
+
+def extract_json(text: str) -> dict:
+    match = re.search(r'\{.*\}', text, re.DOTALL)
+    if not match:
+        raise ValueError("Aucun JSON trouvé")
+    return json.loads(match.group())
+
+# --- Pydantic Models ---
+
+class ProcessRequest(BaseModel):
+    file_id: str
+    filename: str
+    working_group: str
+    meeting: str
+    type: str # doc.Type
+    status: str # doc["TDoc Status"]
+    agenda_item: str # doc["Agenda item description"]
+    url: str
+
+class InnovationResponse(BaseModel):
+    id: str
+    file_name: str
+    answer: str
+    classification: str
+
+class PatternResponse(BaseModel):
+    pattern_id: int
+    pattern_name: str
+    prompt: str
+
+class AnalyzeRequest(BaseModel):
+    file_id: str = None
+    text: str = None
+    pattern_id: int
+
+class AnalyzeResponse(BaseModel):
+    id: int
+    file_name: str
+    content: str
+    methodology: str
+    context: str
+    problem: str
+    pattern_name: str
+
+class ClassificationRequest(BaseModel):
+    result_id: int
+    classification: str
+
+class ResultResponse(BaseModel):
+    id: int
+    file_name: str
+    content: str
+    classification: str
+    pattern_name: str
+    methodology: str
+    context: str
+    problem: str
+
+# --- Helper Functions ---
+
+def fetch_text_content(req: AnalyzeRequest):
+    """
+    fetches text content from request or database.
+    """
+    if req.text:
+        return req.text
+    elif req.file_id:
+        content = data_service.get_file_content(req.file_id)
+        if content:
+            return content
+        else:
+            refined = data_service.get_refined_output(req.file_id)
+            if refined:
+                return refined
+    return None
+
+# --- API Endpoints ---
+
+@app.get("/get_all")
+def get_all():
+    return data_service.get_all_files()
+
+@app.get("/patterns", response_model=list[PatternResponse])
+def get_patterns():
+    return data_service.get_patterns()
+
+class PatternRequest(BaseModel):
+    pattern_name: str
+    prompt: str
+
+@app.post("/patterns", response_model=PatternResponse)
+def create_pattern(req: PatternRequest):
+    try:
+        pattern_id = data_service.add_pattern(req.pattern_name, req.prompt)
+        return {
+            "pattern_id": pattern_id,
+            "pattern_name": req.pattern_name,
+            "prompt": req.prompt
+        }
+    except Exception as e:
+        logger.error(f"Error creating pattern: {e}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.put("/patterns/{pattern_id}", response_model=PatternResponse)
+def update_pattern(pattern_id: int, req: PatternRequest):
+    try:
+        updated = data_service.update_pattern(pattern_id, req.pattern_name, req.prompt)
+        if not updated:
+             raise HTTPException(status_code=404, detail="Pattern not found")
+
+        return {
+            "pattern_id": pattern_id,
+            "pattern_name": req.pattern_name,
+            "prompt": req.prompt
+        }
+    except HTTPException as he:
+        raise he
+    except Exception as e:
+        logger.error(f"Error updating pattern: {e}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.post("/analyze", response_model=AnalyzeResponse)
+async def analyze_content(req: AnalyzeRequest):
+    print("Start of analyse")
+    
+    try:
+        # 1. Check for existing result (caching strategy)
+        existing_result, refined_id, file_name = data_service.get_existing_result(req.file_id)
+        
+        if existing_result:
+            # Cache Hit
+            return {
+                "id": existing_result['result_id'],
+                "file_name": file_name,
+                "content": existing_result['content'],
+                "methodology": existing_result['methodology'],
+                "context": existing_result['context'],
+                "problem": existing_result['problem'],
+                "pattern_name": existing_result['pattern_name']
+            }
+
+        # 2. Cache Miss - Perform Analysis
+        print('Performing new analysis')
+        text_content = fetch_text_content(req)
+        
+        if not text_content:
+            raise HTTPException(status_code=400, detail="No content found to analyze")
+
+        pattern = data_service.get_pattern(req.pattern_id)
+        if not pattern:
+            raise HTTPException(status_code=404, detail="Pattern not found")
+
+        pattern_name = pattern['pattern_name']
+        pattern_prompt = pattern['prompt']
+        
+        # Call LLM
+        response = ask_gemini(f"Pattern: {pattern_name}\nPrompt: {pattern_prompt}\n\nContext:\n", text_content)
+        json_response = extract_json(response)
+        answer = format_answer(json_response)
+        
+        methodology = json_response["methodology"]
+        context = json_response["context"]
+        problem = json_response["problem"]
+
+        # Save Result
+        # We need refined_id. If get_existing_result returned it (even if no result matched), use it. 
+        # But get_existing_result returns it.
+        # If refined_id is None, it means the file wasn't refined?
+        # Ideally fetch_text_content doesn't give refined_id.
+        # Let's get refined_id again if missing.
+        if not refined_id and req.file_id:
+            ref_row = data_service.get_refined_by_file_id(req.file_id)
+            if ref_row:
+                refined_id = ref_row["refined_id"]
+
+        result_id = data_service.add_result(req.pattern_id, refined_id, answer, methodology, context, problem)
+
+        print("End of analyse")
+        return {
+            "id": result_id,
+            "file_name": file_name,
+            "content": answer,
+            "methodology": methodology,
+            "context": context,
+            "problem": problem,
+            "pattern_name": pattern_name
+        }
+
+    except Exception as e:
+        logger.error(f"Error during analysis: {e}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.post("/classify")
+def classify_result(req: ClassificationRequest):
+    try:
+        updated = data_service.update_classification(req.result_id, req.classification)
+        if not updated:
+            raise HTTPException(status_code=404, detail="Result not found")
+        return {"id": req.result_id, "status": "updated"}
+    except Exception as e:
+        logger.error(f"Error updating classification: {e}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.get("/results", response_model=list[ResultResponse])
+def get_results():
+    try:
+        return data_service.get_all_results_joined()
+    except Exception as e:
+        logger.error(f"Error fetching results: {e}")
+        return []
+
+
+@app.post("/process", response_model=InnovationResponse)
+async def process_document(req: ProcessRequest):
+    try:
+        existing_content = data_service.get_file_content(req.file_id)
+        
+        text_content = ""
+        content = ""
+
+        if existing_content:
+            logger.info(f"File {req.file_id} found in DB.")
+            text_content = existing_content
+        else:
+            try:
+                print(req.url)
+                hf_response = requests.post(
+                    'https://organizedprogrammers-docxtract.hf.space/docs/extract_text_from_url',
+                    json={"url": req.url},
+                    timeout=30
+                )
+
+                if hf_response.status_code == 200:
+                    data = hf_response.json()
+                    text_content = data.get('text') or data.get('content') or ""
+                else:
+                    logger.error(f"Failed to fetch content from HF: {hf_response.text}")
+                    text_content = "Extraction failed."
+            except Exception as e:
+                logger.error(f"Error fetching content: {e}")
+                text_content = "Extraction error."
+            
+            # Add file to DataService
+            data_service.add_file({
+                "file_id": req.file_id,
+                "working_group": req.working_group,
+                "meeting": req.meeting,
+                "type": req.type,
+                "status": req.status,
+                "agenda_item": req.agenda_item,
+                "content": text_content,
+                "filename": req.filename,
+                "timestamp": datetime.now().isoformat()
+            })
+
+        refined_output = data_service.get_refined_output(req.file_id)
+        
+        md = mistune.create_markdown()
+        if refined_output:
+            content = md(refined_output)
+        else:
+            print(text_content)
+            answer = ask_gemini(PROCESS_PROMPT, text_content)
+
+            content = md(answer)
+
+            data_service.add_refined(req.file_id, answer)
+            
+        return {
+            "id": req.file_id,
+            "file_name": req.filename,
+            "answer": content,
+            "classification": "UNCLASSIFIED",
+        }
+
+    except Exception as e:
+        logger.error(f"Error processing: {e}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+    import uvicorn
+    uvicorn.run(app, host="0.0.0.0", port=8000)
+
+# Serve Static Files for Deployment (must be after API routes)
+static_dir = "static"
+if os.path.exists(static_dir):
+    # Mount assets folder
+    if os.path.exists(os.path.join(static_dir, "assets")):
+        app.mount("/assets", StaticFiles(directory=os.path.join(static_dir, "assets")), name="assets")
+    
+    # Catch-all for SPA and other static files at root
+    @app.get("/{full_path:path}")
+    async def serve_frontend(full_path: str):
+        # Check if it's a specific file that exists
+        file_path = os.path.join(static_dir, full_path)
+        if os.path.isfile(file_path):
+            return FileResponse(file_path)
+            
+        # Default to index.html for SPA routing
+        return FileResponse(os.path.join(static_dir, "index.html"))

backend/migrate_db.py

@@ -0,0 +1,82 @@
+
+import sqlite3
+import pandas as pd
+import os
+from dotenv import load_dotenv
+from huggingface_hub import login
+from datasets import Dataset
+
+# Load env vars
+load_dotenv()
+load_dotenv("../.env.local") # Try loading from root .env.local as well
+HF_TOKEN = os.getenv("HF_TOKEN")
+HF_DATASET_NAME = os.getenv("HF_DATASET_NAME")
+
+if not HF_TOKEN or not HF_DATASET_NAME:
+    print("Error: HF_TOKEN or HF_DATASET_NAME not found in environment.")
+    exit(1)
+
+login(token=HF_TOKEN)
+
+DB_FILE = "innovations.db"
+
+def migrate():
+    conn = sqlite3.connect(DB_FILE)
+    
+    # 1. Migrate Files
+    print("Migrating 'file' table...")
+    try:
+        df_files = pd.read_sql_query("SELECT * FROM file", conn)
+        if not df_files.empty:
+            ds = Dataset.from_pandas(df_files)
+            ds.push_to_hub(HF_DATASET_NAME, config_name="files", token=HF_TOKEN)
+            print(f"Pushed {len(df_files)} rows to 'files' config.")
+        else:
+            print("Table 'file' is empty.")
+    except Exception as e:
+        print(f"Error migrating 'file': {e}")
+
+    # 2. Migrate Refined
+    print("Migrating 'refined' table...")
+    try:
+        df_refined = pd.read_sql_query("SELECT * FROM refined", conn)
+        if not df_refined.empty:
+            ds = Dataset.from_pandas(df_refined)
+            ds.push_to_hub(HF_DATASET_NAME, config_name="refined", token=HF_TOKEN)
+            print(f"Pushed {len(df_refined)} rows to 'refined' config.")
+        else:
+            print("Table 'refined' is empty.")
+    except Exception as e:
+        print(f"Error migrating 'refined': {e}")
+
+    # 3. Migrate Patterns
+    print("Migrating 'pattern' table...")
+    try:
+        df_patterns = pd.read_sql_query("SELECT * FROM pattern", conn)
+        if not df_patterns.empty:
+            ds = Dataset.from_pandas(df_patterns)
+            ds.push_to_hub(HF_DATASET_NAME, config_name="patterns", token=HF_TOKEN)
+            print(f"Pushed {len(df_patterns)} rows to 'patterns' config.")
+        else:
+            print("Table 'pattern' is empty.")
+    except Exception as e:
+        print(f"Error migrating 'pattern': {e}")
+
+    # 4. Migrate Results
+    print("Migrating 'result' table...")
+    try:
+        df_results = pd.read_sql_query("SELECT * FROM result", conn)
+        if not df_results.empty:
+            ds = Dataset.from_pandas(df_results)
+            ds.push_to_hub(HF_DATASET_NAME, config_name="results", token=HF_TOKEN)
+            print(f"Pushed {len(df_results)} rows to 'results' config.")
+        else:
+            print("Table 'result' is empty.")
+    except Exception as e:
+        print(f"Error migrating 'result': {e}")
+
+    conn.close()
+    print("Migration complete!")
+
+if __name__ == "__main__":
+    migrate()

backend/patterns.py

@@ -0,0 +1,53 @@
+patterns = [
+    {
+        "pattern_name": "TRIZ method",
+        "prompt": """
+# On the provided context follow this step-by-step Process
+
+## Step-by-Step Process
+1.	Identify the contradiction - "IF I improve X, THEN Y worsens"
+2.	Map to TRIZ parameters - Find which of the 39 parameters best match X and Y
+3.	Locate intersection - Find the cell where improving parameter (row) meets worsening parameter (column)
+4.	Read suggested principles - The cell contains 3-4 principle numbers ranked by frequency of use
+5.	Apply principles - Interpret each suggested principle in your specific context
+6.	Generate a context and problem description - Find in this context the most important and innovative problem, write its context and description 
+
+### The Contradiction Matrix is a 39×39 table where:
+•	Rows represent the parameter you want to IMPROVE
+•	Columns represent the parameter that WORSENS
+•	Intersections contain suggested Inventive Principles (by number)
+Complete Parameter List
+No.	Parameter	No.	Parameter
+1	Weight of moving object	21	Power
+2	Weight of stationary object	22	Waste of energy
+3	Length of moving object	23	Waste of substance
+4	Length of stationary object	24	Loss of information
+5	Area of moving object	25	Waste of time
+6	Area of stationary object	26	Amount of substance
+7	Volume of moving object	27	Reliability
+8	Volume of stationary object	28	Accuracy of measurement
+9	Speed	29	Accuracy of manufacturing
+10	Force	30	Harmful factors acting on object
+11	Tension, pressure	31	Harmful side effects
+12	Shape	32	Manufacturability
+13	Stability of object	33	Convenience of use
+14	Strength	34	Repairability
+15	Durability of moving object	35	Adaptability
+16	Durability of stationary object	36	Complexity of device
+17	Temperature	37	Complexity of control
+18	Brightness	38	Level of automation
+19	Energy spent by moving object	39	Productivity
+20	Energy spent by stationary object
+
+### Return the answer as a valid JSON object 
+Follow this schema:
+ {'methodology': string,
+  'context': string,
+  'problem': string
+  }.
+
+In methodology provide the all of the content of step 1, 2, 3, 4 and 5.
+In Context provide the generated context at the step 6.
+In Problem provide the generated problem description at the step 6.
+"""}
+]

backend/requirements.txt

@@ -0,0 +1,12 @@
+fastapi
+uvicorn
+pydantic
+python-multipart
+requests
+groq
+python-dotenv
+huggingface_hub
+datasets
+pandas
+google-genai
+mistune

components/DocFilterBar.tsx

@@ -0,0 +1,164 @@
+import React, { useState, useEffect } from 'react';
+import { MeetingDoc } from '../types';
+import { Filter, X } from 'lucide-react';
+
+interface DocFilterBarProps {
+    docs: MeetingDoc[];
+    onFilterChange: (filteredDocs: MeetingDoc[]) => void;
+}
+
+const DocFilterBar: React.FC<DocFilterBarProps> = ({ docs, onFilterChange }) => {
+    // Extract unique values
+    const allTypes = Array.from(new Set<string>(docs.map(d => d.Type))).sort();
+    const allStatuses = Array.from(new Set<string>(docs.map(d => d['TDoc Status']))).sort();
+    const allAgendas = Array.from(new Set<string>(docs.map(d => d['Agenda item description']))).sort();
+
+    // Default selections
+    const defaultTypes = ["LS out", "LS in", "pCR", "CR"];
+    const defaultStatuses = ["noted", "revised", "approved", "agreed"];
+
+    // State
+    const [selectedTypes, setSelectedTypes] = useState<string[]>([]);
+    const [selectedStatuses, setSelectedStatuses] = useState<string[]>([]);
+    const [selectedAgendas, setSelectedAgendas] = useState<string[]>([]);
+
+    // Initialize defaults when docs change
+    useEffect(() => {
+        if (docs.length > 0) {
+            const initialTypes = allTypes.filter(t => defaultTypes.includes(t));
+            // If no default types match, maybe select all or none? Let's stick to defaults.
+            // If the default list is empty (none found), user can select manually.
+            setSelectedTypes(initialTypes.length > 0 ? initialTypes : []);
+
+            const initialStatuses = allStatuses.filter(s => defaultStatuses.includes(s));
+            setSelectedStatuses(initialStatuses.length > 0 ? initialStatuses : []);
+
+            // Select all agendas by default
+            setSelectedAgendas(allAgendas);
+        }
+    }, [docs]); // Re-run when docs source changes
+
+    // Filter logic
+    useEffect(() => {
+        const filtered = docs.filter(doc => {
+            const typeMatch = selectedTypes.length === 0 || selectedTypes.includes(doc.Type);
+            const statusMatch = selectedStatuses.length === 0 || selectedStatuses.includes(doc['TDoc Status']);
+            const agendaMatch = selectedAgendas.length === 0 || selectedAgendas.includes(doc['Agenda item description']);
+            return typeMatch && statusMatch && agendaMatch;
+        });
+        onFilterChange(filtered);
+    }, [selectedTypes, selectedStatuses, selectedAgendas, docs]);
+
+
+    const toggleSelection = (item: string, current: string[], setter: (val: string[]) => void) => {
+        if (current.includes(item)) {
+            setter(current.filter(i => i !== item));
+        } else {
+            setter([...current, item]);
+        }
+    };
+
+    const toggleAll = (all: string[], current: string[], setter: (val: string[]) => void) => {
+        if (current.length === all.length) {
+            setter([]);
+        } else {
+            setter(all);
+        }
+    };
+
+    if (docs.length === 0) return null;
+
+    return (
+        <div className="bg-white p-4 rounded-xl shadow-sm border border-slate-200 mb-6 animate-fade-in">
+            <div className="flex items-center mb-3">
+                <Filter className="w-4 h-4 text-slate-500 mr-2" />
+                <h3 className="text-sm font-semibold text-slate-800">Filter Documents</h3>
+                <span className="ml-auto text-xs text-slate-500">{docs.length} total docs</span>
+            </div>
+
+            <div className="grid grid-cols-1 md:grid-cols-3 gap-6">
+
+                {/* Type Filter */}
+                <div>
+                    <div className="flex justify-between items-center mb-2">
+                        <label className="text-xs font-medium text-slate-600 uppercase tracking-wider">Type</label>
+                        <button
+                            onClick={() => toggleAll(allTypes, selectedTypes, setSelectedTypes)}
+                            className="text-[10px] text-blue-600 hover:text-blue-800"
+                        >
+                            {selectedTypes.length === allTypes.length ? 'Clear' : 'All'}
+                        </button>
+                    </div>
+                    <div className="max-h-32 overflow-y-auto custom-scrollbar space-y-1">
+                        {allTypes.map(type => (
+                            <label key={type} className="flex items-center space-x-2 cursor-pointer hover:bg-slate-50 p-1 rounded">
+                                <input
+                                    type="checkbox"
+                                    checked={selectedTypes.includes(type)}
+                                    onChange={() => toggleSelection(type, selectedTypes, setSelectedTypes)}
+                                    className="rounded border-slate-300 text-blue-600 focus:ring-blue-500 h-3.5 w-3.5"
+                                />
+                                <span className="text-xs text-slate-700 truncate" title={type}>{type}</span>
+                            </label>
+                        ))}
+                    </div>
+                </div>
+
+                {/* Status Filter */}
+                <div>
+                    <div className="flex justify-between items-center mb-2">
+                        <label className="text-xs font-medium text-slate-600 uppercase tracking-wider">Status</label>
+                        <button
+                            onClick={() => toggleAll(allStatuses, selectedStatuses, setSelectedStatuses)}
+                            className="text-[10px] text-blue-600 hover:text-blue-800"
+                        >
+                            {selectedStatuses.length === allStatuses.length ? 'Clear' : 'All'}
+                        </button>
+                    </div>
+                    <div className="max-h-32 overflow-y-auto custom-scrollbar space-y-1">
+                        {allStatuses.map(status => (
+                            <label key={status} className="flex items-center space-x-2 cursor-pointer hover:bg-slate-50 p-1 rounded">
+                                <input
+                                    type="checkbox"
+                                    checked={selectedStatuses.includes(status)}
+                                    onChange={() => toggleSelection(status, selectedStatuses, setSelectedStatuses)}
+                                    className="rounded border-slate-300 text-blue-600 focus:ring-blue-500 h-3.5 w-3.5"
+                                />
+                                <span className="text-xs text-slate-700 truncate" title={status}>{status}</span>
+                            </label>
+                        ))}
+                    </div>
+                </div>
+
+                {/* Agenda Filter */}
+                <div>
+                    <div className="flex justify-between items-center mb-2">
+                        <label className="text-xs font-medium text-slate-600 uppercase tracking-wider">Agenda Item</label>
+                        <button
+                            onClick={() => toggleAll(allAgendas, selectedAgendas, setSelectedAgendas)}
+                            className="text-[10px] text-blue-600 hover:text-blue-800"
+                        >
+                            {selectedAgendas.length === allAgendas.length ? 'Clear' : 'All'}
+                        </button>
+                    </div>
+                    <div className="max-h-32 overflow-y-auto custom-scrollbar space-y-1">
+                        {allAgendas.map(agenda => (
+                            <label key={agenda} className="flex items-center space-x-2 cursor-pointer hover:bg-slate-50 p-1 rounded">
+                                <input
+                                    type="checkbox"
+                                    checked={selectedAgendas.includes(agenda)}
+                                    onChange={() => toggleSelection(agenda, selectedAgendas, setSelectedAgendas)}
+                                    className="rounded border-slate-300 text-blue-600 focus:ring-blue-500 h-3.5 w-3.5"
+                                />
+                                <span className="text-xs text-slate-700 truncate" title={agenda}>{agenda}</span>
+                            </label>
+                        ))}
+                    </div>
+                </div>
+
+            </div>
+        </div>
+    );
+};
+
+export default DocFilterBar;

components/FileContentCard.tsx

@@ -0,0 +1,64 @@
+import React, { useState } from 'react';
+import { Innovation, Classification } from '../types';
+import { ChevronDown, ChevronUp, Trash2, Check, Zap, FileText } from 'lucide-react';
+import { COLOR_MAP } from '../constants';
+
+interface InnovationCardProps {
+  innovation: Innovation;
+  onClassify: (id: string, classification: Classification) => void;
+}
+
+const InnovationCard: React.FC<InnovationCardProps> = ({ innovation, onClassify }) => {
+  const [isExpanded, setIsExpanded] = useState(false);
+
+  return (
+    <div
+      className={`bg-white rounded-lg shadow-sm border border-slate-200 mb-4 overflow-hidden transition-all duration-200 ${innovation.classification === Classification.DELETE ? 'opacity-50' : ''}`}>
+      <div className="p-4">
+        <div className="flex justify-between items-start">
+          <div className="flex-1 cursor-pointer" onClick={() => setIsExpanded(!isExpanded)}>
+            <div className="px-4 pb-4 bg-slate-50 border-t border-slate-100 pt-3 text-sm">
+              <div className="grid grid-cols-1 md:grid-cols-2 gap-4">
+                <div>
+                  <p className="font-semibold text-slate-700 mb-1">File name</p>
+                  <p className="text-slate-600">{innovation.file_name}</p>
+                </div>
+                {/* <div>
+                  <p className="font-semibold text-slate-700 mb-1">Innovation Potential</p>
+                  <p className="text-slate-600">{ }</p>
+                </div> */}
+              </div>
+            </div>
+          </div>
+
+          <div className="flex items-center ml-4">
+            <button
+              onClick={(e) => {
+                e.stopPropagation();
+                onClassify(innovation.id, Classification.DELETE);
+              }}
+              className="text-red-400 hover:text-red-600 p-1 mr-2 text-xs font-medium border border-red-200 rounded px-2"
+            >
+              Delete
+            </button>
+            <button
+              onClick={() => setIsExpanded(!isExpanded)}
+              className="text-slate-400 hover:text-slate-600 p-1"
+            >
+              {isExpanded ? <ChevronUp size={20} /> : <ChevronDown size={20} />}
+            </button>
+          </div>
+        </div>
+      </div>
+
+      {isExpanded && (
+        <div
+          className="flex flex-col gap-2 m-2"
+          dangerouslySetInnerHTML={{ __html: innovation.answer }}
+        />
+      )}
+    </div>
+  );
+};
+
+export default InnovationCard;

components/FilterBar.tsx

@@ -0,0 +1,121 @@
+import React from 'react';
+import { WORKING_GROUPS } from '../constants';
+import { Search, Loader2 } from 'lucide-react';
+
+interface FilterBarProps {
+  onFetch: (wg: string, meeting: string) => void;
+  isFetching: boolean;
+}
+
+const FilterBar: React.FC<FilterBarProps> = ({ onFetch, isFetching }) => {
+  const [selectedWg, setSelectedWg] = React.useState(WORKING_GROUPS[0]);
+  const [meetings, setMeetings] = React.useState<Record<string, string>>({});
+  const [selectedMeeting, setSelectedMeeting] = React.useState('');
+  const [isLoadingMeetings, setIsLoadingMeetings] = React.useState(false);
+
+  React.useEffect(() => {
+    const fetchMeetings = async () => {
+      setIsLoadingMeetings(true);
+      try {
+        const response = await fetch('https://organizedprogrammers-docxtract.hf.space/docs/get_meetings',
+          { method: 'POST', body: JSON.stringify({ "working_group": selectedWg }), headers: { 'Content-Type': 'application/json' } });
+        if (response.ok) {
+          const data = await response.json();
+          if (data.meetings) {
+            setMeetings(data.meetings);
+            const firstMeetingValue = Object.values(data.meetings)[0] as string;
+            if (firstMeetingValue) {
+              setSelectedMeeting(firstMeetingValue);
+            }
+          }
+        } else {
+          console.error("Failed to fetch meetings");
+        }
+      } catch (error) {
+        console.error("Error fetching meetings:", error);
+      } finally {
+        setIsLoadingMeetings(false);
+      }
+    };
+
+    fetchMeetings();
+  }, [selectedWg]);
+
+  return (
+    <div className="bg-white p-6 rounded-xl shadow-sm border border-slate-200 mb-6">
+      <div className="grid grid-cols-1 md:grid-cols-12 gap-4 items-end">
+
+        <div className="md:col-span-3">
+          <label className="block text-sm font-medium text-slate-600 mb-1">Working Group</label>
+          <div className="relative">
+            <select
+              value={selectedWg}
+              onChange={(e) => setSelectedWg(e.target.value)}
+              className="w-full appearance-none bg-slate-50 border border-slate-300 text-slate-700 py-2.5 px-3 rounded-lg focus:outline-none focus:ring-2 focus:ring-blue-500 focus:border-transparent"
+            >
+              {WORKING_GROUPS.map(wg => <option key={wg} value={wg}>{wg}</option>)}
+            </select>
+            <div className="pointer-events-none absolute inset-y-0 right-0 flex items-center px-2 text-slate-500">
+              <svg className="fill-current h-4 w-4" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 20 20"><path d="M9.293 12.95l.707.707L15.657 8l-1.414-1.414L10 10.828 5.757 6.586 4.343 8z" /></svg>
+            </div>
+          </div>
+        </div>
+
+        <div className="md:col-span-4">
+          <label className="block text-sm font-medium text-slate-600 mb-1">Meeting</label>
+          <div className="relative">
+            <select
+              value={selectedMeeting}
+              onChange={(e) => setSelectedMeeting(e.target.value)}
+              disabled={isLoadingMeetings}
+              className="w-full appearance-none bg-slate-50 border border-slate-300 text-slate-700 py-2.5 px-3 rounded-lg focus:outline-none focus:ring-2 focus:ring-blue-500 focus:border-transparent disabled:opacity-50"
+            >
+              {isLoadingMeetings ? (
+                <option>Loading meetings...</option>
+              ) : (
+                Object.entries(meetings).map(([displayName, value]) => (
+                  <option key={value} value={value}>{displayName}</option>
+                ))
+              )}
+            </select>
+            <div className="pointer-events-none absolute inset-y-0 right-0 flex items-center px-2 text-slate-500">
+              <svg className="fill-current h-4 w-4" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 20 20"><path d="M9.293 12.95l.707.707L15.657 8l-1.414-1.414L10 10.828 5.757 6.586 4.343 8z" /></svg>
+            </div>
+          </div>
+        </div>
+
+        <div className="md:col-span-3">
+          <label className="block text-sm font-medium text-slate-600 mb-2">Doc Types</label>
+          <div className="flex space-x-4">
+            <label className="inline-flex items-center">
+              <input type="checkbox" className="form-checkbox text-blue-600 h-4 w-4 rounded border-slate-300" defaultChecked />
+              <span className="ml-2 text-slate-700">CR</span>
+            </label>
+            <label className="inline-flex items-center">
+              <input type="checkbox" className="form-checkbox text-blue-600 h-4 w-4 rounded border-slate-300" defaultChecked />
+              <span className="ml-2 text-slate-700">PCR</span>
+            </label>
+          </div>
+        </div>
+
+        <div className="md:col-span-2">
+          <button
+            onClick={() => onFetch(selectedWg, selectedMeeting)}
+            disabled={isFetching}
+            className="w-full flex items-center justify-center bg-blue-600 hover:bg-blue-700 text-white font-semibold py-2.5 px-4 rounded-lg transition-colors disabled:opacity-50 disabled:cursor-not-allowed"
+          >
+            {isFetching ? (
+              <Loader2 className="w-4 h-4 mr-2 animate-spin" />
+            ) : (
+              <Search className="w-4 h-4 mr-2" />
+            )}
+            Fetch Docs
+          </button>
+        </div>
+
+      </div>
+    </div>
+  );
+};
+
+export default FilterBar;

components/InnovationCard.tsx

@@ -0,0 +1,95 @@
+import React, { useState } from 'react';
+import { Innovation, Classification, ResultResponse } from '../types';
+import { ChevronDown, ChevronUp, Trash2, Check, Zap, FileText } from 'lucide-react';
+import { COLOR_MAP } from '../constants';
+
+interface InnovationCardProps {
+  innovation: ResultResponse;
+  onClassify: (id: string, classification: Classification) => void;
+}
+
+const InnovationCard: React.FC<InnovationCardProps> = ({ innovation, onClassify }) => {
+  const [isExpanded, setIsExpanded] = useState(false);
+
+  const getBorderColor = (cls: Classification) => {
+    return cls === Classification.UNCLASSIFIED ? 'border-l-4 border-l-slate-300' : `border-l-4 border-l-[${COLOR_MAP[cls]}]`;
+  };
+
+  // Inline style for border color since Tailwind arbitrary values in template literals can be tricky
+  const borderStyle = { borderLeftColor: COLOR_MAP[innovation.classification] };
+
+  // Extraction Logic
+  console.log(innovation)
+  const contextText = innovation.context;
+  const problemText = innovation.problem;
+
+  return (
+    <div
+      className={`bg-white rounded-lg shadow-sm border border-slate-200 mb-4 overflow-hidden transition-all duration-200 ${innovation.classification === Classification.DELETE ? 'opacity-50' : ''}`}
+      style={borderStyle}
+    >
+      <div className="p-4">
+        <div className="flex justify-between items-start">
+          <div className="flex-1 cursor-pointer" onClick={() => setIsExpanded(!isExpanded)}>
+            <div className="px-4 pb-4 bg-slate-50 border-t border-slate-100 pt-3 text-sm">
+              <div className="grid grid-cols-1 md:grid-cols-2 gap-4">
+                <div>
+                  <p className="font-semibold text-slate-700 mb-1">Context</p>
+                  <p className="text-slate-600 text-xs">{contextText}</p>
+                </div>
+                <div>
+                  <p className="font-semibold text-slate-700 mb-1">Problem Description</p>
+                  <p className="text-slate-600 text-xs">{problemText}</p>
+                </div>
+              </div>
+            </div>
+          </div>
+
+          <button
+            onClick={() => setIsExpanded(!isExpanded)}
+            className="ml-4 text-slate-400 hover:text-slate-600 p-1"
+          >
+            {isExpanded ? <ChevronUp size={20} /> : <ChevronDown size={20} />}
+          </button>
+        </div>
+
+        {/* Quick Actions (Always visible) */}
+        <div className="mt-4 flex gap-2 border-t border-slate-100 pt-3">
+          <button
+            onClick={() => onClassify(innovation.id.toString(), Classification.DELETE)}
+            className={`flex-1 flex items-center justify-center px-3 py-1.5 text-xs font-medium rounded transition-colors ${innovation.classification === Classification.DELETE ? 'bg-slate-800 text-white' : 'bg-slate-50 text-slate-600 hover:bg-slate-100'}`}
+          >
+            <Trash2 className="w-3 h-3 mr-1.5" /> Delete
+          </button>
+          <button
+            onClick={() => onClassify(innovation.id.toString(), Classification.LOW)}
+            className={`flex-1 flex items-center justify-center px-3 py-1.5 text-xs font-medium rounded transition-colors ${innovation.classification === Classification.LOW ? 'bg-blue-600 text-white' : 'bg-blue-50 text-blue-700 hover:bg-blue-100'}`}
+          >
+            Low
+          </button>
+          <button
+            onClick={() => onClassify(innovation.id.toString(), Classification.MEDIUM)}
+            className={`flex-1 flex items-center justify-center px-3 py-1.5 text-xs font-medium rounded transition-colors ${innovation.classification === Classification.MEDIUM ? 'bg-yellow-500 text-white' : 'bg-yellow-50 text-yellow-700 hover:bg-yellow-100'}`}
+          >
+            Medium
+          </button>
+          <button
+            onClick={() => onClassify(innovation.id.toString(), Classification.HIGH)}
+            className={`flex-1 flex items-center justify-center px-3 py-1.5 text-xs font-medium rounded transition-colors ${innovation.classification === Classification.HIGH ? 'bg-green-600 text-white' : 'bg-green-50 text-green-700 hover:bg-green-100'}`}
+          >
+            <Zap className="w-3 h-3 mr-1.5" /> High
+          </button>
+        </div>
+      </div>
+
+      {isExpanded && (
+        <div
+          className="flex flex-col gap-2 m-2"
+          dangerouslySetInnerHTML={{ __html: innovation.content }}
+        />
+      )}
+    </div>
+  );
+};
+
+export default InnovationCard;

components/StatsDashboard.tsx

@@ -0,0 +1,151 @@
+import React, { useEffect, useState } from 'react';
+import { PieChart, Pie, Cell, ResponsiveContainer, BarChart, Bar, XAxis, YAxis, Tooltip, Legend } from 'recharts';
+import { Classification, Innovation, StatsData, ResultResponse } from '../types';
+import { COLOR_MAP } from '../constants';
+import { backendService } from '../services/backendService';
+import InnovationCard from './InnovationCard';
+import { CircleDashed } from 'lucide-react';
+
+interface StatsDashboardProps {
+  innovations: Innovation[];
+  isVisible: boolean;
+}
+
+const StatsDashboard: React.FC<StatsDashboardProps> = ({ isVisible }) => {
+  const [dbInnovations, setDbInnovations] = useState<ResultResponse[]>([]);
+  const [loading, setLoading] = useState(false);
+
+  // Fetch from DB for the "True" state
+  const fetchDbInnovations = async () => {
+    setLoading(true);
+    const results = await backendService.fetchClassifiedInnovations();
+
+    // Transform ResultResponse -> Innovation
+    const transformed: ResultResponse[] = results.map((r: any) => ({
+      id: r.id,
+      file_name: r.file_name,
+      content: r.content,
+      context: r.context || "N/A",
+      problem: r.problem || "N/A",
+      methodology: r.methodology || "N/A",
+      classification: r.classification,
+    }));
+
+    setDbInnovations(transformed);
+    setLoading(false);
+  };
+
+  useEffect(() => {
+    if (isVisible) {
+      fetchDbInnovations();
+    }
+  }, [isVisible]);
+
+
+  const handleClassify = async (id: string, classification: Classification) => {
+    // Find the innovation
+    const inv = dbInnovations.find(i => i.id === Number(id));
+    if (inv && inv.id) {
+      // Optimistic update
+      setDbInnovations(prev => prev.map(i => i.id === Number(id) ? { ...i, classification } : i));
+      await backendService.saveClassification(Number(id), classification);
+    }
+  };
+
+  // Filter for Display (High, Medium, Low, Unclassified)
+  const displayInnovations = dbInnovations.filter(i =>
+    [Classification.HIGH, Classification.MEDIUM, Classification.LOW, Classification.UNCLASSIFIED].includes(i.classification as Classification)
+  );
+
+  // Stats Logic - Use DB data for charts to be consistent with the list below
+  const statsSource = dbInnovations.length > 0 ? dbInnovations : [];
+
+  const data: StatsData[] = [
+    { name: 'High Priority', value: statsSource.filter(i => i.classification === Classification.HIGH).length, fill: COLOR_MAP[Classification.HIGH] },
+    { name: 'Medium Priority', value: statsSource.filter(i => i.classification === Classification.MEDIUM).length, fill: COLOR_MAP[Classification.MEDIUM] },
+    { name: 'Low Priority', value: statsSource.filter(i => i.classification === Classification.LOW).length, fill: COLOR_MAP[Classification.LOW] },
+    { name: 'Rejected', value: statsSource.filter(i => i.classification === Classification.DELETE).length, fill: COLOR_MAP[Classification.DELETE] },
+    { name: 'Unclassified', value: statsSource.filter(i => i.classification === Classification.UNCLASSIFIED).length, fill: COLOR_MAP[Classification.UNCLASSIFIED] },
+  ];
+
+  // Mock context data (unchanged)
+  const contextData = [
+    { name: 'Network Opt', count: 12 },
+    { name: 'Security', count: 8 },
+    { name: 'QoS', count: 15 },
+    { name: 'New Use Cases', count: 5 },
+  ];
+
+  return (
+    <div className="space-y-8">
+      {/* Charts Section */}
+      <div className="grid grid-cols-1 md:grid-cols-2 gap-6">
+        <div className="bg-white p-6 rounded-lg shadow-sm border border-slate-200">
+          <h3 className="text-lg font-semibold text-slate-800 mb-4">Classification Status</h3>
+          <div className="h-64">
+            <ResponsiveContainer width="100%" height="100%">
+              <PieChart>
+                <Pie
+                  data={data}
+                  cx="50%"
+                  cy="50%"
+                  innerRadius={60}
+                  outerRadius={80}
+                  paddingAngle={5}
+                  dataKey="value"
+                >
+                  {data.map((entry, index) => (
+                    <Cell key={`cell-${index}`} fill={entry.fill} />
+                  ))}
+                </Pie>
+                <Tooltip />
+                <Legend />
+              </PieChart>
+            </ResponsiveContainer>
+          </div>
+        </div>
+
+        <div className="bg-white p-6 rounded-lg shadow-sm border border-slate-200">
+          <h3 className="text-lg font-semibold text-slate-800 mb-4">Innovation Contexts (Trends)</h3>
+          <div className="h-64">
+            <ResponsiveContainer width="100%" height="100%">
+              <BarChart data={contextData}>
+                <XAxis dataKey="name" fontSize={12} tickLine={false} axisLine={false} />
+                <YAxis hide />
+                <Tooltip cursor={{ fill: 'transparent' }} />
+                <Bar dataKey="count" fill="#3b82f6" radius={[4, 4, 0, 0]} />
+              </BarChart>
+            </ResponsiveContainer>
+          </div>
+        </div>
+      </div>
+
+      {/* Classified List Section */}
+      <div className="bg-white p-6 rounded-lg shadow-sm border border-slate-200">
+        <div className="flex items-center justify-between mb-6">
+          <h3 className="text-lg font-semibold text-slate-800">Classified Innovations</h3>
+          <button onClick={fetchDbInnovations} className="text-sm text-slate-500 hover:text-blue-600 flex items-center">
+            {loading && <CircleDashed className="w-4 h-4 mr-1 animate-spin" />}
+            Refresh
+          </button>
+        </div>
+
+        {displayInnovations.length === 0 ? (
+          <p className="text-center text-slate-500 py-8">No items (High, Medium, Low, Unclassified) found.</p>
+        ) : (
+          <div className="space-y-4">
+            {displayInnovations.map(inv => (
+              <InnovationCard
+                key={inv.id}
+                innovation={inv}
+                onClassify={handleClassify}
+              />
+            ))}
+          </div>
+        )}
+      </div>
+    </div>
+  );
+};
+
+export default StatsDashboard;

constants.ts

@@ -0,0 +1,43 @@
+import { Innovation, Classification } from './types';
+
+export const WORKING_GROUPS = ['SA1', 'SA2', 'SA3', 'SA4', 'SA5', 'SA6', 'RAN1', 'RAN2'];
+export const MEETINGS = ['Dallas (Nov 2024)', 'Maastricht (Aug 2024)', 'Jeju (May 2024)', 'Athens (Feb 2024)'];
+
+export const MOCK_INNOVATIONS_POOL: Omit<Innovation, 'id' | 'batch_id' | 'classification'>[] = [
+  {
+    problem_id: "CP-882",
+    context: "Satellite integration in 5G Non-Terrestrial Networks (NTN)",
+    problem_statement: "High latency variations in LEO satellite constellations cause handover failures during fast UE movement.",
+    innovation_potential: "Proposes a predictive QoS-based handover trigger that utilizes satellite ephemeris data to pre-allocate resources.",
+    source_reference: "TR 38.821 Sec 4.2",
+  },
+  {
+    problem_id: "CP-901",
+    context: "XR/VR Traffic handling in RAN",
+    problem_statement: "Current semi-persistent scheduling (SPS) does not account for jitter inherent in cloud-rendered VR frames.",
+    innovation_potential: "Introduces a frame-aware scheduling buffer that aligns grants with application-layer frame boundaries.",
+    source_reference: "TS 38.300 Sec 12",
+  },
+  {
+    problem_id: "CP-112",
+    context: "Sidelink positioning for V2X",
+    problem_statement: "GPS unavailability in urban canyons degrades V2X safety application reliability.",
+    innovation_potential: "Utilizes cooperative ranging between vehicles using relative signal strength and RTT to establish local relative positioning.",
+    source_reference: "TR 38.885 Sec 6.1",
+  },
+  {
+    problem_id: "CP-445",
+    context: "Network Energy Saving",
+    problem_statement: "Sleep mode transitions for gNBs are too slow to react to bursty IoT traffic.",
+    innovation_potential: "AI-driven traffic prediction model resident at the DU to trigger micro-sleep states.",
+    source_reference: "TS 28.310 Sec 5",
+  },
+];
+
+export const COLOR_MAP: Record<Classification, string> = {
+  [Classification.UNCLASSIFIED]: '#94a3b8',
+  [Classification.DELETE]: '#ef4444',
+  [Classification.LOW]: '#3b82f6',
+  [Classification.MEDIUM]: '#eab308',
+  [Classification.HIGH]: '#22c55e',
+};

index.html

@@ -0,0 +1,25 @@
+<!DOCTYPE html>
+<html lang="en">
+  <head>
+    <meta charset="UTF-8" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <title>3GPP Innovation Extractor</title>
+    <script src="https://cdn.tailwindcss.com"></script>
+  <script type="importmap">
+{
+  "imports": {
+    "react": "https://aistudiocdn.com/react@^19.2.0",
+    "react/": "https://aistudiocdn.com/react@^19.2.0/",
+    "react-dom/": "https://aistudiocdn.com/react-dom@^19.2.0/",
+    "lucide-react": "https://aistudiocdn.com/lucide-react@^0.555.0",
+    "recharts": "https://aistudiocdn.com/recharts@^3.5.0"
+  }
+}
+</script>
+<link rel="stylesheet" href="/index.css">
+</head>
+  <body>
+    <div id="root"></div>
+  <script type="module" src="/index.tsx"></script>
+</body>
+</html>

index.tsx

@@ -0,0 +1,15 @@
+import React from 'react';
+import ReactDOM from 'react-dom/client';
+import App from './App';
+
+const rootElement = document.getElementById('root');
+if (!rootElement) {
+  throw new Error("Could not find root element to mount to");
+}
+
+const root = ReactDOM.createRoot(rootElement);
+root.render(
+  <React.StrictMode>
+    <App />
+  </React.StrictMode>
+);

metadata.json

@@ -0,0 +1,5 @@
+{
+  "name": "3GPP Innovation Extractor",
+  "description": "A React application for extracting and classifying innovation context-problems from 3GPP documents using Open Notebook architecture.",
+  "requestFramePermissions": []
+}

openapi.json

@@ -0,0 +1 @@
+{"openapi":"3.1.0","info":{"title":"Open Notebook API","description":"API for Open Notebook - Research Assistant","version":"0.2.2"},"paths":{"/api/auth/status":{"get":{"tags":["auth","auth"],"summary":"Get Auth Status","description":"Check if authentication is enabled.\nReturns whether a password is required to access the API.","operationId":"get_auth_status_api_auth_status_get","responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}}}}},"/api/config":{"get":{"tags":["config"],"summary":"Get Config","description":"Get frontend configuration.\n\nReturns version information and health status.\nNote: The frontend determines the API URL via its own runtime-config endpoint,\nso this endpoint no longer returns apiUrl.\n\nAlso checks for version updates from GitHub (with caching and error handling).","operationId":"get_config_api_config_get","responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}}}}},"/api/notebooks":{"get":{"tags":["notebooks"],"summary":"Get Notebooks","description":"Get all notebooks with optional filtering and ordering.","operationId":"get_notebooks_api_notebooks_get","parameters":[{"name":"archived","in":"query","required":false,"schema":{"anyOf":[{"type":"boolean"},{"type":"null"}],"description":"Filter by archived status","title":"Archived"},"description":"Filter by archived status"},{"name":"order_by","in":"query","required":false,"schema":{"type":"string","description":"Order by field and direction","default":"updated desc","title":"Order By"},"description":"Order by field and direction"}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"type":"array","items":{"$ref":"#/components/schemas/NotebookResponse"},"title":"Response Get Notebooks Api Notebooks Get"}}}},"422":{"description":"Validation 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Id"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/NotebookResponse"}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}},"put":{"tags":["notebooks"],"summary":"Update Notebook","description":"Update a notebook.","operationId":"update_notebook_api_notebooks__notebook_id__put","parameters":[{"name":"notebook_id","in":"path","required":true,"schema":{"type":"string","title":"Notebook Id"}}],"requestBody":{"required":true,"content":{"application/json":{"schema":{"$ref":"#/components/schemas/NotebookUpdate"}}}},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/NotebookResponse"}}}},"422":{"description":"Validation 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reference).","operationId":"add_source_to_notebook_api_notebooks__notebook_id__sources__source_id__post","parameters":[{"name":"notebook_id","in":"path","required":true,"schema":{"type":"string","title":"Notebook Id"}},{"name":"source_id","in":"path","required":true,"schema":{"type":"string","title":"Source Id"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}},"delete":{"tags":["notebooks"],"summary":"Remove Source From Notebook","description":"Remove a source from a notebook (delete the reference).","operationId":"remove_source_from_notebook_api_notebooks__notebook_id__sources__source_id__delete","parameters":[{"name":"notebook_id","in":"path","required":true,"schema":{"type":"string","title":"Notebook Id"}},{"name":"source_id","in":"path","required":true,"schema":{"type":"string","title":"Source Id"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/search":{"post":{"tags":["search"],"summary":"Search Knowledge Base","description":"Search the knowledge base using text or vector search.","operationId":"search_knowledge_base_api_search_post","requestBody":{"content":{"application/json":{"schema":{"$ref":"#/components/schemas/SearchRequest"}}},"required":true},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/SearchResponse"}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/search/ask":{"post":{"tags":["search"],"summary":"Ask Knowledge Base","description":"Ask the knowledge base a question using AI models.","operationId":"ask_knowledge_base_api_search_ask_post","requestBody":{"content":{"application/json":{"schema":{"$ref":"#/components/schemas/AskRequest"}}},"required":true},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/search/ask/simple":{"post":{"tags":["search"],"summary":"Ask Knowledge Base Simple","description":"Ask the knowledge base a question and return a simple response (non-streaming).","operationId":"ask_knowledge_base_simple_api_search_ask_simple_post","requestBody":{"content":{"application/json":{"schema":{"$ref":"#/components/schemas/AskRequest"}}},"required":true},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/AskResponse"}}}},"422":{"description":"Validation 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configuration.","operationId":"create_model_api_models_post","requestBody":{"required":true,"content":{"application/json":{"schema":{"$ref":"#/components/schemas/ModelCreate"}}}},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/ModelResponse"}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/models/{model_id}":{"delete":{"tags":["models"],"summary":"Delete Model","description":"Delete a model configuration.","operationId":"delete_model_api_models__model_id__delete","parameters":[{"name":"model_id","in":"path","required":true,"schema":{"type":"string","title":"Model Id"}}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{}}}},"422":{"description":"Validation 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Transformation","description":"Create a new transformation.","operationId":"create_transformation_api_transformations_post","requestBody":{"content":{"application/json":{"schema":{"$ref":"#/components/schemas/TransformationCreate"}}},"required":true},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/TransformationResponse"}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/transformations/execute":{"post":{"tags":["transformations"],"summary":"Execute Transformation","description":"Execute a transformation on input text.","operationId":"execute_transformation_api_transformations_execute_post","requestBody":{"content":{"application/json":{"schema":{"$ref":"#/components/schemas/TransformationExecuteRequest"}}},"required":true},"responses":{"200":{"description":"Successful 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prompt.","operationId":"update_default_prompt_api_transformations_default_prompt_put","requestBody":{"content":{"application/json":{"schema":{"$ref":"#/components/schemas/DefaultPromptUpdate"}}},"required":true},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/DefaultPromptResponse"}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}}},"/api/transformations/{transformation_id}":{"get":{"tags":["transformations"],"summary":"Get Transformation","description":"Get a specific transformation by ID.","operationId":"get_transformation_api_transformations__transformation_id__get","parameters":[{"name":"transformation_id","in":"path","required":true,"schema":{"type":"string","title":"Transformation Id"}}],"responses":{"200":{"description":"Successful 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ID","title":"Notebook Id"},"description":"Filter by notebook ID"}],"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"type":"array","items":{"$ref":"#/components/schemas/NoteResponse"},"title":"Response Get Notes Api Notes Get"}}}},"422":{"description":"Validation Error","content":{"application/json":{"schema":{"$ref":"#/components/schemas/HTTPValidationError"}}}}}},"post":{"tags":["notes"],"summary":"Create Note","description":"Create a new note.","operationId":"create_note_api_notes_post","requestBody":{"required":true,"content":{"application/json":{"schema":{"$ref":"#/components/schemas/NoteCreate"}}}},"responses":{"200":{"description":"Successful Response","content":{"application/json":{"schema":{"$ref":"#/components/schemas/NoteResponse"}}}},"422":{"description":"Validation 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+          "optional": true
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+          "optional": true
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+        "tsx": {
+          "optional": true
+        },
+        "yaml": {
+          "optional": true
+        }
+      }
+    },
+    "node_modules/yallist": {
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+      "resolved": "https://registry.npmjs.org/yallist/-/yallist-3.1.1.tgz",
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+      "dev": true,
+      "license": "ISC"
+    }
+  }
+}

package.json

@@ -0,0 +1,25 @@
+{
+  "name": "3gpp-innovation-extractor",
+  "private": true,
+  "version": "0.0.0",
+  "type": "module",
+  "scripts": {
+    "dev": "vite",
+    "build": "vite build",
+    "preview": "vite preview"
+  },
+  "dependencies": {
+    "dexie": "^4.2.1",
+    "dexie-react-hooks": "^4.2.0",
+    "lucide-react": "^0.555.0",
+    "react": "^19.2.0",
+    "react-dom": "^19.2.0",
+    "recharts": "^3.5.0"
+  },
+  "devDependencies": {
+    "@types/node": "^22.14.0",
+    "@vitejs/plugin-react": "^5.0.0",
+    "typescript": "~5.8.2",
+    "vite": "^6.2.0"
+  }
+}

services/backendService.ts

@@ -0,0 +1,157 @@
+import { DocumentFile, Innovation } from '../types';
+
+const BACKEND_API_URL = 'http://localhost:8000';
+
+export interface ProcessResponse {
+    id: string;
+    file_name: string;
+    answer: string;
+    classification: string;
+    // id: string;
+    // innovation_name: string;
+    // problem_id: string;
+    // problem_statement: string;
+    // context: string;
+    // proposed_solution: string;
+    // technical_classification: string;
+    // classification: string;
+}
+
+export const backendService = {
+    /**
+     * Sends a document to the backend for processing.
+     * The backend handles extraction, storage (SQLite), and mock refinement.
+     */
+    processDocument: async (file: DocumentFile, workingGroup: string, meeting: string): Promise<Innovation | null> => {
+        if (!file.url) {
+            console.warn(`Skipping file ${file.filename}: No URL`);
+            return null;
+        }
+
+        try {
+            const payload = {
+                file_id: file.id,
+                filename: file.filename,
+                working_group: workingGroup,
+                meeting: meeting,
+                type: file.type,
+                status: file.status || "Unknown",
+                agenda_item: file.agendaItem || "Unknown",
+                url: file.url
+            };
+
+            const response = await fetch(`${BACKEND_API_URL}/process`, {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify(payload)
+            });
+
+            if (!response.ok) {
+                console.error(`Backend processing failed for ${file.filename}: ${response.statusText}`);
+                return null;
+            }
+
+            const data: ProcessResponse = await response.json();
+
+            // Map response to Innovation type
+            return {
+                id: file.id,
+                file_name: file.filename,
+                answer: data.answer,
+                classification: "UNCLASSIFIED",
+            } as Innovation;
+
+        } catch (error) {
+            console.error(`Error processing document ${file.filename}:`, error);
+            return null;
+        }
+    },
+
+    getPatterns: async (): Promise<any[]> => {
+        try {
+            const response = await fetch(`${BACKEND_API_URL}/patterns`);
+            if (response.ok) {
+                return await response.json();
+            }
+            return [];
+        } catch (error) {
+            console.error("Error fetching patterns:", error);
+            return [];
+        }
+    },
+
+    analyzeContent: async (patternId: number, fileId?: string, text?: string): Promise<{ content: string; result_id: number; methodology: string; context: string; problem: string; pattern_name: string } | null> => {
+        try {
+            const response = await fetch(`${BACKEND_API_URL}/analyze`, {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({
+                    pattern_id: patternId,
+                    file_id: fileId,
+                    text: text
+                })
+            });
+
+            if (response.ok) {
+                const data = await response.json();
+                return { content: data.content, result_id: data.id, methodology: data.methodology, context: data.context, problem: data.problem, pattern_name: data.pattern_name };
+            }
+            return null;
+        } catch (error) {
+            console.error("Error analyzing content:", error);
+            return null;
+        }
+    },
+
+    saveClassification: async (resultId: number, classification: string): Promise<boolean> => {
+        try {
+            const response = await fetch(`${BACKEND_API_URL}/classify`, {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ result_id: resultId, classification })
+            });
+            return response.ok;
+        } catch (error) {
+            console.error("Error saving classification:", error);
+            return false;
+        }
+    },
+
+    fetchClassifiedInnovations: async (): Promise<any[]> => {
+        try {
+            const response = await fetch(`${BACKEND_API_URL}/results`);
+            if (response.ok) {
+                return await response.json();
+            }
+            return [];
+        } catch (error) {
+            console.error("Error fetching classified innovations:", error);
+            return [];
+        }
+    },
+
+    fetchAllFiles: async (): Promise<DocumentFile[]> => {
+        try {
+            const response = await fetch(`${BACKEND_API_URL}/get_all`);
+            if (response.ok) {
+                const rows = await response.json();
+                // Map tuple to DocumentFile: 
+                // [file_id, working_group, meeting, type, status, agenda_item, content, filename, timestamp]
+                return rows.map((row: any) => ({
+                    id: row[0],
+                    filename: row[7],
+                    size: 'Unknown',
+                    type: row[3],
+                    uploaded: true, // It's from DB, so treated as processed/uploaded
+                    status: row[4],
+                    agendaItem: row[5],
+                    url: '' // Not stored explicitly usually, or maybe we don't need it for display
+                }));
+            }
+            return [];
+        } catch (error) {
+            console.error("Error fetching all files:", error);
+            return [];
+        }
+    }
+};

tsconfig.json

@@ -0,0 +1,29 @@
+{
+  "compilerOptions": {
+    "target": "ES2022",
+    "experimentalDecorators": true,
+    "useDefineForClassFields": false,
+    "module": "ESNext",
+    "lib": [
+      "ES2022",
+      "DOM",
+      "DOM.Iterable"
+    ],
+    "skipLibCheck": true,
+    "types": [
+      "node"
+    ],
+    "moduleResolution": "bundler",
+    "isolatedModules": true,
+    "moduleDetection": "force",
+    "allowJs": true,
+    "jsx": "react-jsx",
+    "paths": {
+      "@/*": [
+        "./*"
+      ]
+    },
+    "allowImportingTsExtensions": true,
+    "noEmit": true
+  }
+}

types.ts

@@ -0,0 +1,69 @@
+export enum Classification {
+  UNCLASSIFIED = 'UNCLASSIFIED',
+  DELETE = 'DELETE',
+  LOW = 'LOW',
+  MEDIUM = 'MEDIUM',
+  HIGH = 'HIGH',
+}
+
+export interface Innovation {
+  id: string;
+  file_name: string;
+  answer: string;
+  //  problem_statement: string;
+  //  innovation_potential: string;
+  //  source_reference: string;
+  classification: Classification;
+  analysis_result?: string;
+  result_id?: number;
+
+  // Analysis metadata
+  methodology?: string;
+  context?: string;
+  problem?: string;
+  pattern_name?: string;
+}
+
+export interface ResultResponse {
+  id: number;
+  file_name: string;
+  content: string;
+  classification: Classification;
+  methodology: string;
+  context: string;
+  problem: string;
+}
+
+export interface MeetingDoc {
+  TDoc: string;
+  Title: string;
+  Type: string;
+  For: string;
+  "TDoc Status": string;
+  "Agenda item description": string;
+  URL: string;
+}
+
+export interface DocumentFile {
+  id: string;
+  filename: string;
+  size: string;
+  type: string;
+  uploaded: boolean;
+  // Optional metadata from API
+  status?: string;
+  agendaItem?: string;
+  url?: string;
+}
+
+export interface ProcessingBatch {
+  id: number;
+  files: DocumentFile[];
+  status: 'pending' | 'uploading' | 'processing' | 'completed';
+}
+
+export interface StatsData {
+  name: string;
+  value: number;
+  fill: string;
+}

vite.config.ts

@@ -0,0 +1,23 @@
+import path from 'path';
+import { defineConfig, loadEnv } from 'vite';
+import react from '@vitejs/plugin-react';
+
+export default defineConfig(({ mode }) => {
+    const env = loadEnv(mode, '.', '');
+    return {
+      server: {
+        port: 3000,
+        host: '0.0.0.0',
+      },
+      plugins: [react()],
+      define: {
+        'process.env.API_KEY': JSON.stringify(env.GEMINI_API_KEY),
+        'process.env.GEMINI_API_KEY': JSON.stringify(env.GEMINI_API_KEY)
+      },
+      resolve: {
+        alias: {
+          '@': path.resolve(__dirname, '.'),
+        }
+      }
+    };
+});