fixed

prepare_kb.ipynb

@@ -1,118 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "f5a0d75d",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import chromadb\n",
-    "from llama_index.core import StorageContext\n",
-    "from llama_index.vector_stores.chroma import ChromaVectorStore\n",
-    "# from llama_index.embeddings.fastembed import FastEmbedEmbedding\n",
-    "from llama_index.core import VectorStoreIndex, SimpleDirectoryReader\n",
-    "from llama_index.core import SimpleDirectoryReader, StorageContext, VectorStoreIndex\n",
-    "\n",
-    "# embed_model = FastEmbedEmbedding(model_name=\"BAAI/bge-small-en-v1.5\")\n",
-    "data_dir = r\"knowledge_base\\raw\\classification\"\n",
-    "\n",
-    "documents = SimpleDirectoryReader(str(data_dir)).load_data()\n",
-    "data_path = r\"knowledge_base\\vector\\classification\"\n",
-    "db = chromadb.PersistentClient(path=data_path)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "b52b6ba8",
-   "metadata": {},
-   "source": [
-    "### Storing the data locally"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "348df588",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "chroma_collection = db.get_or_create_collection(\"classification_db\")\n",
-    "vector_store = ChromaVectorStore(chroma_collection=chroma_collection)\n",
-    "storage_context = StorageContext.from_defaults(vector_store=vector_store)\n",
-    "index = VectorStoreIndex.from_documents(\n",
-    "    documents=documents,\n",
-    "    storage_context=storage_context,\n",
-    "    show_progress=True,\n",
-    "    # embed_model=embed_model\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f7411c03",
-   "metadata": {},
-   "source": [
-    "### Loading the locally stored vector index"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "4d9cbd1b",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import chromadb\n",
-    "from llama_index.core import StorageContext\n",
-    "from llama_index.core import VectorStoreIndex\n",
-    "from llama_index.core.retrievers import VectorIndexRetriever\n",
-    "from llama_index.vector_stores.chroma import ChromaVectorStore\n",
-    "# from llama_index.embeddings.fastembed import FastEmbedEmbedding\n",
-    "\n",
-    "# embed_model = FastEmbedEmbedding(model_name=\"BAAI/bge-small-en-v1.5\")\n",
-    "\n",
-    "data_path = r\"knowledge_base\\vector\\classification\"\n",
-    "db = chromadb.PersistentClient(path=data_path)\n",
-    "chroma_collection = db.get_or_create_collection(\"classification_db\")\n",
-    "vector_store = ChromaVectorStore(chroma_collection=chroma_collection)\n",
-    "storage_context = StorageContext.from_defaults(vector_store=vector_store)\n",
-    "\n",
-    "index = VectorStoreIndex.from_vector_store(vector_store, storage_context=storage_context)\n",
-    "retriever = VectorIndexRetriever(\n",
-    "    index, \n",
-    "    # embed_model=embed_model\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "05804310",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "dev",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.11.4"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}