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"Author-email: \n", + "License: MIT\n", + "Location: /usr/local/lib/python3.10/dist-packages\n", + "Requires: aiohttp, async-timeout, dataclasses-json, langchain-community, langchain-core, langchain-text-splitters, langsmith, numpy, pydantic, PyYAML, requests, SQLAlchemy, tenacity\n", + "Required-by: \n", + "---\n", + "Name: chromadb\n", + "Version: 0.5.0\n", + "Summary: Chroma.\n", + "Home-page: \n", + "Author: \n", + "Author-email: Jeff Huber , Anton Troynikov \n", + "License: \n", + "Location: /usr/local/lib/python3.10/dist-packages\n", + "Requires: bcrypt, build, chroma-hnswlib, fastapi, grpcio, importlib-resources, kubernetes, mmh3, numpy, onnxruntime, opentelemetry-api, opentelemetry-exporter-otlp-proto-grpc, opentelemetry-instrumentation-fastapi, opentelemetry-sdk, orjson, overrides, posthog, pydantic, pypika, PyYAML, requests, tenacity, tokenizers, tqdm, typer, typing-extensions, uvicorn\n", + "Required-by: \n", + "---\n", + "Name: sentence-transformers\n", + "Version: 2.7.0\n", + "Summary: Multilingual text embeddings\n", + "Home-page: https://www.SBERT.net\n", + "Author: Nils Reimers\n", + "Author-email: info@nils-reimers.de\n", + "License: Apache License 2.0\n", + "Location: /usr/local/lib/python3.10/dist-packages\n", + "Requires: huggingface-hub, numpy, Pillow, scikit-learn, scipy, torch, tqdm, transformers\n", + "Required-by: \n" + ] + } + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "GL6I0pRh8ESZ", + "outputId": "353fa6e6-4cc3-4dbf-d167-7515b5af7f40" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m302.9/302.9 kB\u001b[0m \u001b[31m2.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m20.8 MB/s\u001b[0m eta 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This behaviour is the source of the following dependency conflicts.\n", + "spacy 3.7.4 requires typer<0.10.0,>=0.3.0, but you have typer 0.12.3 which is incompatible.\n", + "weasel 0.3.4 requires typer<0.10.0,>=0.3.0, but you have typer 0.12.3 which is incompatible.\u001b[0m\u001b[31m\n", + "\u001b[0m" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "!pip install sentence-transformers" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "rDPhz4pfnPHo", + "outputId": "d29d8d1d-96ac-490d-c821-cb318009d77c" + }, + "execution_count": 6, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Collecting sentence-transformers\n", + " Downloading sentence_transformers-2.7.0-py3-none-any.whl (171 kB)\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m171.5/171.5 kB\u001b[0m \u001b[31m1.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[?25hRequirement already satisfied: 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"documents = parser.load_data(\"/content/kashani.pdf\")\n", + "\n", + "# async\n", + "# documents = await parser.aload_data(\"./my_file.pdf\")" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "pWCRKu9vUzrf", + "outputId": "1c3139aa-a3a3-4ef1-8f94-21ab18dd0bc3" + }, + "execution_count": 8, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Started parsing the file under job_id 90b9b05a-4243-4cda-b9f0-22cf9f098518\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "documents = [\n", + " doc.to_langchain_format()\n", + " for doc in documents\n", + "]" + ], + "metadata": { + "id": "W3pCMQJFYRRD" + }, + "execution_count": 9, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "Embedding and storing" + ], + "metadata": { + "id": "pk_z_w_6dYHh" + } + }, + { + "cell_type": "code", + "source": [ + "from langchain_text_splitters import RecursiveCharacterTextSplitter\n", + "from langchain_community.vectorstores import Chroma\n", + "from langchain_community.embeddings import OllamaEmbeddings\n", + "from langchain_community.embeddings.huggingface import HuggingFaceEmbeddings" + ], + "metadata": { + "id": "V3o6v2D1dcTe" + }, + "execution_count": 10, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "splitter=RecursiveCharacterTextSplitter(chunk_size=1000,chunk_overlap=200)\n", + "docs=splitter.split_documents(documents)" + ], + "metadata": { + "id": "mxn7-Rwnd8S6" + }, + "execution_count": 11, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "embeds=OllamaEmbeddings(model='nomic-embed-text',base_url='http://localhost:11434')" + ], + "metadata": { + "id": "6af68LZ-jXTg" + }, + "execution_count": 10, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "embeds=HuggingFaceEmbeddings(model_name=\"BAAI/bge-base-en-v1.5\")" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 528, + 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does not exist in your Colab secrets.\n", + "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n", + "You will be able to reuse this secret in all of your notebooks.\n", + "Please note that authentication is recommended but still optional to access public models or datasets.\n", + " warnings.warn(\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "modules.json: 0%| | 0.00/349 [00:00