From 451f97aac61cdce0242338d714f16f85e8fc6a94 Mon Sep 17 00:00:00 2001 From: Sunile Manjee Date: Thu, 20 Jun 2024 13:09:14 -0500 Subject: [PATCH 01/11] updated readme.md to include fetch surrounding chunks updated readme.md to include example of fetch surrounding chunks --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index e12951f2..2e10695f 100644 --- a/README.md +++ b/README.md @@ -44,6 +44,7 @@ The [`notebooks`](notebooks/README.md) folder contains a range of executable Pyt - [`Document Chunking with Ingest Pipelines`](./notebooks/document-chunking/with-index-pipelines.ipynb) - [`Document Chunking with LangChain Splitters`](./notebooks/document-chunking/with-langchain-splitters.ipynb) - [`Calculating tokens for Semantic Search (ELSER and E5)`](./notebooks/document-chunking/tokenization.ipynb) +- [`Fetch surronding chucks`](./supporting-blog-content/fetch-surrounding-chunks/fetch-surrounding-chunks.ipynb) ### Search From 4141c042b34d09887136cdb89c2e5256c9a6179e Mon Sep 17 00:00:00 2001 From: Joe McElroy Date: Mon, 24 Jun 2024 09:56:20 +0100 Subject: [PATCH 02/11] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 2e10695f..5f98d856 100644 --- a/README.md +++ b/README.md @@ -44,7 +44,7 @@ The [`notebooks`](notebooks/README.md) folder contains a range of executable Pyt - [`Document Chunking with Ingest Pipelines`](./notebooks/document-chunking/with-index-pipelines.ipynb) - [`Document Chunking with LangChain Splitters`](./notebooks/document-chunking/with-langchain-splitters.ipynb) - [`Calculating tokens for Semantic Search (ELSER and E5)`](./notebooks/document-chunking/tokenization.ipynb) -- [`Fetch surronding chucks`](./supporting-blog-content/fetch-surrounding-chunks/fetch-surrounding-chunks.ipynb) +- [`Fetch surrounding chucks`](./supporting-blog-content/fetch-surrounding-chunks/fetch-surrounding-chunks.ipynb) ### Search From e6e194a819c6df32efb9a8a1ecf1e456cf319ebe Mon Sep 17 00:00:00 2001 From: Sunile Manjee Date: Tue, 15 Oct 2024 09:42:42 -0700 Subject: [PATCH 03/11] supporting notebook for PR 1270 https://github.com/elastic/search-labs-elastic-co/pull/1270 --- .../PDF_Parsing_Table_Extraction.ipynb | 189 ++++++++++++++++++ 1 file changed, 189 insertions(+) create mode 100644 supporting-blog-content/alternative-approach-for-parsing-pdfs-in-rag/PDF_Parsing_Table_Extraction.ipynb diff --git a/supporting-blog-content/alternative-approach-for-parsing-pdfs-in-rag/PDF_Parsing_Table_Extraction.ipynb b/supporting-blog-content/alternative-approach-for-parsing-pdfs-in-rag/PDF_Parsing_Table_Extraction.ipynb new file mode 100644 index 00000000..961db7e6 --- /dev/null +++ b/supporting-blog-content/alternative-approach-for-parsing-pdfs-in-rag/PDF_Parsing_Table_Extraction.ipynb @@ -0,0 +1,189 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "provenance": [] + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "language_info": { + "name": "python" + } + }, + "cells": [ + { + "cell_type": "markdown", + "source": [ + "# PDF Parsing - Table Extraction\n", + "\"Open\n" + ], + "metadata": { + "id": "e9-GuDRKCz_1" + } + }, + { + "cell_type": "markdown", + "source": [ + "##Objective\n", + "This Python script extracts text and tables from a PDF file, converts the tables into a human-readable text format using Azure OpenAI, and writes the processed content to a text file. The script uses pdfplumber to extract text and table data from each page of the PDF. For tables, it sends a cleaned version (handling any missing or None values) to Azure OpenAI, which generates a natural language summary of the table. The extracted non-table text and the summarized table text are then saved to a text file for easy search and readability." + ], + "metadata": { + "id": "MBdflc9G0ICc" + } + }, + { + "cell_type": "code", + "source": [ + "!pip install pdfplumber" + ], + "metadata": { + "id": "QBwz0_VNL1p6" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "This code imports necessary libraries for PDF extraction, data processing, and interacting with Azure OpenAI via API calls. It retrieves the Azure OpenAI API key and endpoint from Google Colab's userdata storage, sets up the required headers, and prepares for sending requests to the Azure OpenAI service." + ], + "metadata": { + "id": "QC37eVM90few" + } + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "X3vuHZTjK6l7" + }, + "outputs": [], + "source": [ + "import pdfplumber\n", + "import pandas as pd\n", + "import requests\n", + "import base64\n", + "import json\n", + "from getpass import getpass\n", + "import io # To create an in-memory file-like object\n", + "\n", + "\n", + "ENDPOINT = getpass(\"Azure OpenAI Completions Endpoint: \")\n", + "API_KEY = getpass(\"Azure OpenAI API Key: \")\n", + "\n", + "\n", + "headers = {\n", + " \"Content-Type\": \"application/json\",\n", + " \"api-key\": API_KEY,\n", + "}\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "source": [ + "This code defines two functions: extract_table_text_from_openai and parse_pdf. The extract_table_text_from_openai function sends a table's plain text to Azure OpenAI for conversion into a human-readable description by building a request payload and handling the response. The parse_pdf function processes a PDF file page by page, extracting both text and tables, and sends the extracted tables to Azure OpenAI for summarization, saving all the content (including summarized tables) to a text file." + ], + "metadata": { + "id": "79VOKKam0leA" + } + }, + { + "cell_type": "code", + "source": [ + "def extract_table_text_from_openai(table_text):\n", + " # Payload for the Azure OpenAI request\n", + " payload = {\n", + " \"messages\": [\n", + " {\n", + " \"role\": \"system\",\n", + " \"content\": [\n", + " {\n", + " \"type\": \"text\",\n", + " \"text\": \"You are an AI assistant that helps convert tables into a human-readable text.\"\n", + " }\n", + " ]\n", + " },\n", + " {\n", + " \"role\": \"user\",\n", + " \"content\": f\"Convert this table to a readable text format:\\n{table_text}\"\n", + " }\n", + " ],\n", + " \"temperature\": 0.7,\n", + " \"top_p\": 0.95,\n", + " \"max_tokens\": 4096\n", + " }\n", + "\n", + " # Send the request to Azure OpenAI\n", + " try:\n", + " response = requests.post(ENDPOINT, headers=headers, json=payload)\n", + " response.raise_for_status() # Raise error if the request fails\n", + " except requests.RequestException as e:\n", + " raise SystemExit(f\"Failed to make the request. Error: {e}\")\n", + "\n", + " # Process the response\n", + " return response.json().get('choices', [{}])[0].get('message', {}).get('content', '').strip()\n", + "\n", + "def parse_pdf_from_url(file_url):\n", + " # Download the PDF file from the URL\n", + " response = requests.get(file_url)\n", + " response.raise_for_status() # Ensure the request was successful\n", + "\n", + " # Open the PDF content with pdfplumber using io.BytesIO\n", + " pdf_content = io.BytesIO(response.content)\n", + "\n", + " with pdfplumber.open(pdf_content) as pdf, open(\"/content/parsed_output/parsed_output.txt\", \"w\") as output_file:\n", + " for page_num, page in enumerate(pdf.pages, 1):\n", + " print(f\"Processing page {page_num}\")\n", + "\n", + " # Extract text content\n", + " text = page.extract_text()\n", + " if text:\n", + " output_file.write(f\"Page {page_num} Text:\\n\")\n", + " output_file.write(text + \"\\n\\n\")\n", + " print(\"Text extracted:\", text)\n", + "\n", + " # Extract tables\n", + " tables = page.extract_tables()\n", + " for idx, table in enumerate(tables):\n", + " print(f\"Table {idx + 1} found on page {page_num}\")\n", + "\n", + " # Convert the table into plain text format (handling None values)\n", + " table_text = \"\\n\".join([\"\\t\".join([str(cell) if cell is not None else \"\" for cell in row]) for row in table[1:]])\n", + "\n", + " # Call Azure OpenAI to convert the table into a text representation\n", + " table_description = extract_table_text_from_openai(table_text)\n", + "\n", + " # Write the text representation to the file\n", + " output_file.write(f\"Table {idx + 1} (Page {page_num}) Text Representation:\\n\")\n", + " output_file.write(table_description + \"\\n\\n\")\n", + " print(\"Text representation of the table:\", table_description)\n" + ], + "metadata": { + "id": "CdMm1AKJLKbA" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "# URL of the PDF file\n", + "file_url = \"https://sunmanapp.blob.core.windows.net/publicstuff/pdfs/quarterly_report.pdf\"\n", + "##output stored here: /content/parsed_output/parsed_output.txt\n", + "\n", + "# Call the function to parse the PDF from the URL\n", + "parse_pdf_from_url(file_url)" + ], + "metadata": { + "id": "7ig9NSSnLMGt" + }, + "execution_count": null, + "outputs": [] + } + ] +} \ No newline at end of file From 649d811418cdd4fbd33fadd26d2670103daaa4cd Mon Sep 17 00:00:00 2001 From: Sunile Manjee Date: Tue, 15 Oct 2024 09:51:08 -0700 Subject: [PATCH 04/11] file names updated file names --- ...ve-approach-for-parsing-pdfs-in-rag.ipynb} | 100 +++++++++--------- 1 file changed, 50 insertions(+), 50 deletions(-) rename supporting-blog-content/alternative-approach-for-parsing-pdfs-in-rag/{PDF_Parsing_Table_Extraction.ipynb => alternative-approach-for-parsing-pdfs-in-rag.ipynb} (96%) diff --git a/supporting-blog-content/alternative-approach-for-parsing-pdfs-in-rag/PDF_Parsing_Table_Extraction.ipynb b/supporting-blog-content/alternative-approach-for-parsing-pdfs-in-rag/alternative-approach-for-parsing-pdfs-in-rag.ipynb similarity index 96% rename from supporting-blog-content/alternative-approach-for-parsing-pdfs-in-rag/PDF_Parsing_Table_Extraction.ipynb rename to supporting-blog-content/alternative-approach-for-parsing-pdfs-in-rag/alternative-approach-for-parsing-pdfs-in-rag.ipynb index 961db7e6..71a29be2 100644 --- a/supporting-blog-content/alternative-approach-for-parsing-pdfs-in-rag/PDF_Parsing_Table_Extraction.ipynb +++ b/supporting-blog-content/alternative-approach-for-parsing-pdfs-in-rag/alternative-approach-for-parsing-pdfs-in-rag.ipynb @@ -1,58 +1,44 @@ { - "nbformat": 4, - "nbformat_minor": 0, - "metadata": { - "colab": { - "provenance": [] - }, - "kernelspec": { - "name": "python3", - "display_name": "Python 3" - }, - "language_info": { - "name": "python" - } - }, "cells": [ { "cell_type": "markdown", + "metadata": { + "id": "e9-GuDRKCz_1" + }, "source": [ "# PDF Parsing - Table Extraction\n", "\"Open\n" - ], - "metadata": { - "id": "e9-GuDRKCz_1" - } + ] }, { "cell_type": "markdown", + "metadata": { + "id": "MBdflc9G0ICc" + }, "source": [ "##Objective\n", "This Python script extracts text and tables from a PDF file, converts the tables into a human-readable text format using Azure OpenAI, and writes the processed content to a text file. The script uses pdfplumber to extract text and table data from each page of the PDF. For tables, it sends a cleaned version (handling any missing or None values) to Azure OpenAI, which generates a natural language summary of the table. The extracted non-table text and the summarized table text are then saved to a text file for easy search and readability." - ], - "metadata": { - "id": "MBdflc9G0ICc" - } + ] }, { "cell_type": "code", - "source": [ - "!pip install pdfplumber" - ], + "execution_count": null, "metadata": { "id": "QBwz0_VNL1p6" }, - "execution_count": null, - "outputs": [] + "outputs": [], + "source": [ + "!pip install pdfplumber" + ] }, { "cell_type": "markdown", - "source": [ - "This code imports necessary libraries for PDF extraction, data processing, and interacting with Azure OpenAI via API calls. It retrieves the Azure OpenAI API key and endpoint from Google Colab's userdata storage, sets up the required headers, and prepares for sending requests to the Azure OpenAI service." - ], "metadata": { "id": "QC37eVM90few" - } + }, + "source": [ + "This code imports necessary libraries for PDF extraction, data processing, and interacting with Azure OpenAI via API calls. It retrieves the Azure OpenAI API key and endpoint from Google Colab's userdata storage, sets up the required headers, and prepares for sending requests to the Azure OpenAI service." + ] }, { "cell_type": "code", @@ -85,15 +71,20 @@ }, { "cell_type": "markdown", - "source": [ - "This code defines two functions: extract_table_text_from_openai and parse_pdf. The extract_table_text_from_openai function sends a table's plain text to Azure OpenAI for conversion into a human-readable description by building a request payload and handling the response. The parse_pdf function processes a PDF file page by page, extracting both text and tables, and sends the extracted tables to Azure OpenAI for summarization, saving all the content (including summarized tables) to a text file." - ], "metadata": { "id": "79VOKKam0leA" - } + }, + "source": [ + "This code defines two functions: extract_table_text_from_openai and parse_pdf. The extract_table_text_from_openai function sends a table's plain text to Azure OpenAI for conversion into a human-readable description by building a request payload and handling the response. The parse_pdf function processes a PDF file page by page, extracting both text and tables, and sends the extracted tables to Azure OpenAI for summarization, saving all the content (including summarized tables) to a text file." + ] }, { "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "CdMm1AKJLKbA" + }, + "outputs": [], "source": [ "def extract_table_text_from_openai(table_text):\n", " # Payload for the Azure OpenAI request\n", @@ -162,28 +153,37 @@ " output_file.write(f\"Table {idx + 1} (Page {page_num}) Text Representation:\\n\")\n", " output_file.write(table_description + \"\\n\\n\")\n", " print(\"Text representation of the table:\", table_description)\n" - ], - "metadata": { - "id": "CdMm1AKJLKbA" - }, - "execution_count": null, - "outputs": [] + ] }, { "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "7ig9NSSnLMGt" + }, + "outputs": [], "source": [ "# URL of the PDF file\n", "file_url = \"https://sunmanapp.blob.core.windows.net/publicstuff/pdfs/quarterly_report.pdf\"\n", "##output stored here: /content/parsed_output/parsed_output.txt\n", "\n", "# Call the function to parse the PDF from the URL\n", - "parse_pdf_from_url(file_url)" - ], - "metadata": { - "id": "7ig9NSSnLMGt" - }, - "execution_count": null, - "outputs": [] + "parse_pdf_from_url(file_url)\n" + ] + } + ], + "metadata": { + "colab": { + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + }, + "language_info": { + "name": "python" } - ] -} \ No newline at end of file + }, + "nbformat": 4, + "nbformat_minor": 0 +} From 247da1ccdcab064dbe08e6c9dc8cf88c401402ff Mon Sep 17 00:00:00 2001 From: Sunile Manjee Date: Tue, 15 Oct 2024 09:58:18 -0700 Subject: [PATCH 05/11] removed colab link removed colab link to check if that is why build is faling. --- .../alternative-approach-for-parsing-pdfs-in-rag.ipynb | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/supporting-blog-content/alternative-approach-for-parsing-pdfs-in-rag/alternative-approach-for-parsing-pdfs-in-rag.ipynb b/supporting-blog-content/alternative-approach-for-parsing-pdfs-in-rag/alternative-approach-for-parsing-pdfs-in-rag.ipynb index 71a29be2..db803de5 100644 --- a/supporting-blog-content/alternative-approach-for-parsing-pdfs-in-rag/alternative-approach-for-parsing-pdfs-in-rag.ipynb +++ b/supporting-blog-content/alternative-approach-for-parsing-pdfs-in-rag/alternative-approach-for-parsing-pdfs-in-rag.ipynb @@ -6,8 +6,7 @@ "id": "e9-GuDRKCz_1" }, "source": [ - "# PDF Parsing - Table Extraction\n", - "\"Open\n" + "# PDF Parsing - Table Extraction\n" ] }, { @@ -16,7 +15,7 @@ "id": "MBdflc9G0ICc" }, "source": [ - "##Objective\n", + "## Objective\n", "This Python script extracts text and tables from a PDF file, converts the tables into a human-readable text format using Azure OpenAI, and writes the processed content to a text file. The script uses pdfplumber to extract text and table data from each page of the PDF. For tables, it sends a cleaned version (handling any missing or None values) to Azure OpenAI, which generates a natural language summary of the table. The extracted non-table text and the summarized table text are then saved to a text file for easy search and readability." ] }, From 6b242a3f4e27e8ee7b53ae9bb145a0ea4a6f67dd Mon Sep 17 00:00:00 2001 From: Sunile Manjee Date: Tue, 15 Oct 2024 17:37:46 -0700 Subject: [PATCH 06/11] adding pdf adding pdf to branch --- .../quarterly_report.pdf | Bin 0 -> 14716233 bytes 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 supporting-blog-content/alternative-approach-for-parsing-pdfs-in-rag/quarterly_report.pdf diff --git a/supporting-blog-content/alternative-approach-for-parsing-pdfs-in-rag/quarterly_report.pdf b/supporting-blog-content/alternative-approach-for-parsing-pdfs-in-rag/quarterly_report.pdf new file mode 100644 index 0000000000000000000000000000000000000000..48776e9c6a16173ee7b9422c2f0a27c86f4ed207 GIT binary patch literal 14716233 zcmbUJ1y~))x;6}B!QFxc3r>)=7PgS!?(XjH8Z5X5cMTQ@?gV!YPH>kH++9DCnSJ)` 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