refactor: Rename Chunk_v2/Summary_v2 collections to Chunk/Summary
- Add migrate_rename_collections.py script for data migration - Update flask_app.py to use new collection names - Update weaviate_ingest.py to use new collection names - Update schema.py documentation - Update README.md and ANALYSE_MCP_TOOLS.md Migration completed: 5372 chunks + 114 summaries preserved with vectors. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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@@ -37,7 +37,7 @@ ping()
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#### 2. `parse_pdf(pdf_path)`
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**Type**: Ingestion PDF
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**Collection cible**: Work, Chunk_v2, Summary_v2
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**Collection cible**: Work, Chunk, Summary
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**Paramètres**:
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- `pdf_path` (str): Chemin local ou URL vers le PDF
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@@ -87,7 +87,7 @@ ping()
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#### 3. `search_chunks(query, limit, min_similarity, author_filter, work_filter, language_filter)`
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**Type**: Recherche sémantique
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**Collection**: Chunk_v2 (5,372 chunks)
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**Collection**: Chunk (5,372 chunks)
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**Paramètres**:
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- `query` (str): Requête en langage naturel
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@@ -126,7 +126,7 @@ ping()
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#### 4. `search_summaries(query, limit, min_level, max_level)`
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**Type**: Recherche sémantique (haut niveau)
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**Collection**: Summary_v2 (114 résumés)
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**Collection**: Summary (114 résumés)
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**Paramètres**:
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- `query` (str): Requête en langage naturel
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@@ -161,7 +161,7 @@ ping()
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#### 5. `get_document(source_id, include_chunks, include_toc)`
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**Type**: Récupération document
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**Collections**: Work, Chunk_v2
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**Collections**: Work, Chunk
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**Paramètres**:
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- `source_id` (str): Identifiant du document
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@@ -226,7 +226,7 @@ ping()
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#### 7. `get_chunks_by_document(source_id, limit, offset)`
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**Type**: Récupération chunks
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**Collection**: Chunk_v2
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**Collection**: Chunk
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**Paramètres**:
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- `source_id` (str): Identifiant du document
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@@ -260,7 +260,7 @@ ping()
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#### 8. `filter_by_author(author, limit)`
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**Type**: Filtrage par auteur
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**Collections**: Work, Chunk_v2
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**Collections**: Work, Chunk
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**Paramètres**:
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- `author` (str): Nom de l'auteur
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@@ -294,7 +294,7 @@ ping()
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#### 9. `delete_document(source_id, confirm)`
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**Type**: Suppression
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**Collections**: Work, Chunk_v2, Summary_v2
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**Collections**: Work, Chunk, Summary
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**Paramètres**:
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- `source_id` (str): Identifiant du document
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@@ -605,7 +605,7 @@ ping()
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| Catégorie | Nombre | Collections utilisées | GPU Embedder |
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|-----------|--------|----------------------|--------------|
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| **Système** | 1 | - | - |
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| **Library RAG** | 8 | Work, Chunk_v2, Summary_v2 | ✅ |
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| **Library RAG** | 8 | Work, Chunk, Summary | ✅ |
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| **Memory** | 9 | Thought, Message, Conversation | ✅ |
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| **TOTAL** | **18** | **6 collections** | **5 vectorisées** |
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@@ -719,8 +719,8 @@ messages = search_messages("transformers architecture")
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RAG (3):
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- Work (no vectorizer) - 19 œuvres
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- Chunk_v2 (GPU embedder) - 5,372 chunks
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- Summary_v2 (GPU embedder) - 114 résumés
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- Chunk (GPU embedder) - 5,372 chunks
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- Summary (GPU embedder) - 114 résumés
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Memory (3):
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- Conversation (GPU embedder) - 12 conversations
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