feat: Implement text manager API and database connection
- Added `text_manager.py` to handle the creation of text libraries via FastAPI. - Introduced database connection management in `conexion.py` using PostgreSQL credentials from environment variables. - Created abstract base class `EmbedderABC` in `Base_Embedder.py` for embedding models. - Developed `OpenAIEmbedder` class to generate embeddings using OpenAI's API. - Implemented `OpenAIEmbedderModel` and repository pattern for managing OpenAI embedders in `Openai_embedder_mmr.py`. - Established `Biblioteca` class for managing text libraries and their associated notes in `biblioteca.py`. - Created SQLAlchemy models and mappers for `Biblioteca` and `Nota` in `biblioteca_mmr.py` and `notas_biblioteca_mmr.py`. - Added functionality for dynamic table generation for notes associated with libraries. - Included comprehensive methods for adding, retrieving, and managing notes and libraries in their respective repositories.
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@@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 1,
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"id": "5206b9c6",
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"metadata": {},
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"outputs": [],
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@@ -14,7 +14,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 2,
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"id": "63a0b954",
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@@ -25,7 +25,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 3,
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"id": "0575f424",
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"metadata": {},
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@@ -38,17 +38,17 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 4,
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"id": "a5266309",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"1"
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"'PGCR20250510-02f3cf9610127084237'"
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]
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},
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"execution_count": 3,
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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@@ -72,7 +72,7 @@
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}
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],
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"source": [
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"modelo_cred = repo_cred.get_by_id(1)\n",
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"modelo_cred = repo_cred.get_by_id(\"PGCR20250510-02f3cf9610127084237\")\n",
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"\n",
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"print(modelo_cred.titulo)"
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]
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