- Add complete Library RAG application (Flask + MCP server) - PDF processing pipeline with OCR and LLM extraction - Weaviate vector database integration (BGE-M3 embeddings) - Flask web interface with search and document management - MCP server for Claude Desktop integration - Comprehensive test suite (134 tests) - Clean up root directory - Remove obsolete documentation files - Remove backup and temporary files - Update autonomous agent configuration - Update prompts - Enhance initializer bis prompt with better instructions 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
179 lines
8.7 KiB
HTML
179 lines
8.7 KiB
HTML
{% extends "base.html" %}
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{% block title %}Upload Document{% endblock %}
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{% block content %}
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<section class="section">
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<h1>📄 Parser PDF/Markdown</h1>
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<p class="lead">Uploadez un fichier PDF ou Markdown pour l'analyser et structurer son contenu</p>
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{% if error %}
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<div class="alert alert-warning">
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<strong>Erreur :</strong> {{ error }}
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</div>
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{% endif %}
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<div class="search-box">
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<form method="post" enctype="multipart/form-data">
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<div class="form-group">
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<label class="form-label" for="file">Fichier PDF ou Markdown</label>
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<input
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type="file"
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name="file"
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id="file"
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class="form-control"
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accept=".pdf,.md"
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required
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>
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<div class="caption mt-1">Taille maximale : 50 MB</div>
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<div class="caption" style="color: var(--color-accent); margin-top: 0.25rem;">
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💡 Pour retester un document existant sans refaire l'OCR payant, cochez "Skip OCR"
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</div>
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</div>
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<div class="form-row mt-3">
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<div class="form-group">
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<label class="form-label">Options</label>
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<div style="display: flex; flex-direction: column; gap: 0.5rem;">
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<div style="display: flex; align-items: center; gap: 0.5rem;">
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<input
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type="checkbox"
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name="skip_ocr"
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id="skip_ocr"
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style="width: auto;"
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>
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<label for="skip_ocr" style="margin: 0; font-size: 0.95rem; text-transform: none; letter-spacing: 0;">
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⚡ Skip OCR (réutiliser markdown existant)
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</label>
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</div>
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<div style="display: flex; align-items: center; gap: 0.5rem;">
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<input
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type="checkbox"
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name="use_llm"
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id="use_llm"
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checked
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style="width: auto;"
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>
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<label for="use_llm" style="margin: 0; font-size: 0.95rem; text-transform: none; letter-spacing: 0;">
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Activer la structuration LLM (Ollama)
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</label>
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</div>
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<div style="display: flex; align-items: center; gap: 0.5rem;">
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<input
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type="checkbox"
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name="ingest_weaviate"
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id="ingest_weaviate"
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checked
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style="width: auto;"
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>
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<label for="ingest_weaviate" style="margin: 0; font-size: 0.95rem; text-transform: none; letter-spacing: 0;">
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Insérer dans Weaviate (vectorisation)
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</label>
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</div>
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</div>
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</div>
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<div class="form-group">
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<label class="form-label" for="llm_provider">Provider LLM</label>
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<select name="llm_provider" id="llm_provider" class="form-control" onchange="updateModelOptions()">
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<option value="mistral" selected>⚡ Mistral API (rapide)</option>
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<option value="ollama">🖥️ Ollama (local, lent)</option>
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</select>
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</div>
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<div class="form-group">
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<label class="form-label" for="llm_model">Modèle LLM</label>
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<select name="llm_model" id="llm_model" class="form-control">
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<!-- Options Mistral API -->
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<option value="mistral-small-latest" selected>mistral-small (rapide, économique)</option>
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<option value="mistral-medium-latest">mistral-medium (équilibré)</option>
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<option value="mistral-large-latest">mistral-large (puissant)</option>
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</select>
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</div>
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<script>
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function updateModelOptions() {
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const provider = document.getElementById('llm_provider').value;
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const modelSelect = document.getElementById('llm_model');
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if (provider === 'mistral') {
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modelSelect.innerHTML = `
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<option value="mistral-small-latest" selected>mistral-small (rapide, économique)</option>
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<option value="mistral-medium-latest">mistral-medium (équilibré)</option>
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<option value="mistral-large-latest">mistral-large (puissant)</option>
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`;
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} else {
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modelSelect.innerHTML = `
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<option value="qwen2.5:7b" selected>qwen2.5:7b (recommandé)</option>
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<option value="qwen2.5:14b">qwen2.5:14b</option>
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<option value="llama3.2:3b">llama3.2:3b (rapide)</option>
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<option value="mistral:7b">mistral:7b</option>
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`;
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}
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}
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</script>
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</div>
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<!-- Options Extraction TOC améliorée -->
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<div class="card mt-4" style="border-left: 3px solid #4CAF50;">
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<h4 style="color: #4CAF50;">📑 Extraction TOC améliorée (Recommandé)</h4>
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<p style="font-size: 0.9rem; color: #666;">
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Analyse l'indentation du texte pour détecter automatiquement la hiérarchie de la table des matières.
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<br><strong style="color: #4CAF50;">✅ Fiable, rapide et sans coût supplémentaire</strong>
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</p>
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<div style="display: flex; align-items: center; gap: 0.5rem; margin-top: 1rem;">
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<input
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type="checkbox"
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name="use_ocr_annotations"
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id="use_ocr_annotations"
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style="width: auto;"
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checked
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>
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<label for="use_ocr_annotations" style="margin: 0; font-size: 0.95rem; font-weight: 600;">
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Activer l'analyse d'indentation pour la TOC
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</label>
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</div>
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<div style="margin-top: 0.75rem; padding: 0.75rem; background: #f0f9f0; border-radius: 4px; font-size: 0.85rem;">
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<strong>Fonctionnement :</strong> Détecte les niveaux hiérarchiques en comptant les espaces d'indentation dans la table des matières.
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<br>
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<em>Idéal pour les documents académiques avec TOC structurée.</em>
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</div>
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</div>
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<div class="mt-3">
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<button type="submit" class="btn btn-primary">
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Analyser le document
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</button>
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</div>
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</form>
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</div>
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<hr class="divider">
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<div class="card">
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<h3>📋 Pipeline de traitement</h3>
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<div class="mt-2">
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<p><strong>1. OCR Mistral</strong> — Extraction du texte et des images via l'API Mistral</p>
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<p><strong>2. Markdown</strong> — Construction du document Markdown avec images</p>
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<p><strong>3. Hiérarchie</strong> — Analyse des titres pour créer une structure arborescente</p>
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<p><strong>4. LLM (optionnel)</strong> — Amélioration de la structure via Ollama</p>
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</div>
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</div>
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<div class="card mt-3">
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<h3>📁 Fichiers générés</h3>
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<div class="mt-2">
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<ul style="list-style: none;">
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<li class="mb-1"><span class="badge">document.md</span> Texte Markdown OCR</li>
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<li class="mb-1"><span class="badge">document_chunks.json</span> Chunks hiérarchiques</li>
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<li class="mb-1"><span class="badge">document_structured.json</span> Structure LLM</li>
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<li class="mb-1"><span class="badge">document_ocr.json</span> Réponse OCR brute</li>
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<li><span class="badge">images/</span> Images extraites</li>
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</ul>
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</div>
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</div>
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<div class="text-center mt-4">
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<a href="/documents" class="btn">Voir les documents traités</a>
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</div>
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</section>
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{% endblock %}
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