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+{
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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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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "import json\n",
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+ "import os\n",
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+ "import torch\n",
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+ "from pathlib import Path\n",
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+ "import re\n",
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+ "from transformers import pipeline"
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+ ]
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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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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "# Use Llama 3.3 for high-quality rewriting\n",
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+ "DEFAULT_MODEL = \"meta-llama/Llama-3.3-70B-Instruct\" \n",
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+ "\n",
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+ "# Set up directories\n",
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+ "base_dir = Path(\"llama_data\")\n",
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+ "reports_dir = base_dir / \"final_reports\"\n",
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+ "rewritten_dir = base_dir / \"rewritten_reports\"\n",
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+ "rewritten_dir.mkdir(exist_ok=True)"
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+ ]
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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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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "ORIGINAL_USER_INPUT = "
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+ ]
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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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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "SYS_PROMPT ="
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+ ]
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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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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "text_pipeline = pipeline(\n",
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+ " \"text-generation\",\n",
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+ " model=DEFAULT_MODEL,\n",
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+ " model_kwargs={\"torch_dtype\": torch.bfloat16},\n",
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+ " device_map=\"auto\",\n",
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+ ")"
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+ ]
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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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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "def get_report_files():\n",
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+ " \"\"\"Get all report files from the final_reports directory\"\"\"\n",
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+ " report_files = []\n",
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+ " \n",
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+ " if not reports_dir.exists():\n",
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+ " print(f\"Error: Reports directory '{reports_dir}' not found.\")\n",
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+ " return []\n",
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+ " \n",
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+ " for file in reports_dir.glob(\"report_*.txt\"):\n",
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+ " report_files.append(file)\n",
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+ " \n",
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+ " # Sort by report number to process in consistent order\n",
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+ " report_files.sort()\n",
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+ " \n",
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+ " print(f\"Found {len(report_files)} report files.\")\n",
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+ " return report_files"
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+ ]
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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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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "def rewrite_report(report_path, original_user_input):\n",
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+ " \"\"\"Rewrite a single report using Llama 3.3\"\"\"\n",
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+ " \n",
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+ " # Extract report number and title from filename\n",
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+ " report_filename = report_path.name\n",
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+ " report_id = re.search(r'report_(\\d+)_', report_filename).group(1) if re.search(r'report_(\\d+)_', report_filename) else \"unknown\"\n",
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+ " \n",
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+ " print(f\"Processing report {report_id}: {report_filename}\")\n",
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+ " \n",
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+ " # Read the report content\n",
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+ " try:\n",
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+ " with open(report_path, \"r\", encoding=\"utf-8\") as f:\n",
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+ " report_content = f.read()\n",
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+ " except Exception as e:\n",
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+ " print(f\"Error reading report file: {str(e)}\")\n",
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+ " return None\n",
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+ " \n",
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+ " # Extract the report title from the content\n",
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+ " title_match = re.search(r'^# (.+?)\\n', report_content)\n",
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+ " report_title = title_match.group(1) if title_match else \"Unknown Report\"\n",
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+ " \n",
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+ " # Create the prompt for rewriting\n",
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+ " user_prompt = f\"\"\"\n",
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+ "{original_user_input}\n",
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+ "\n",
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+ "Here's the report to rewrite:\n",
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+ "\n",
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+ "{report_content}\n",
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+ "\"\"\"\n",
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+ " \n",
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+ " # Set up the conversation\n",
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+ " conversation = [\n",
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+ " {\"role\": \"system\", \"content\": SYS_PROMPT},\n",
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+ " {\"role\": \"user\", \"content\": user_prompt}\n",
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+ " ]\n",
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+ " \n",
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+ " # Generate the rewritten report\n",
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+ " output = text_pipeline(\n",
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+ " conversation,\n",
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+ " max_new_tokens=4000,\n",
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+ " temperature=0.7,\n",
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+ " do_sample=True,\n",
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+ " )\n",
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+ " \n",
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+ " # Extract the assistant's response\n",
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+ " assistant_response = output[0][\"generated_text\"][-1]\n",
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+ " rewritten_content = assistant_response[\"content\"]\n",
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+ " \n",
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+ " # Save the rewritten report\n",
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+ " rewritten_filename = f\"rewritten_{report_id}_{report_title.replace(' ', '_')[:30]}.txt\"\n",
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+ " rewritten_path = rewritten_dir / rewritten_filename\n",
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+ " \n",
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+ " with open(rewritten_path, \"w\", encoding=\"utf-8\") as f:\n",
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+ " f.write(rewritten_content)\n",
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+ " \n",
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+ " print(f\" Saved rewritten report to: {rewritten_path}\")\n",
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+ " return rewritten_path"
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+ ]
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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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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "def rewrite_all_reports():\n",
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+ " \"\"\"Rewrite all reports in the final_reports directory\"\"\"\n",
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+ " \n",
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+ " # Get all report files\n",
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+ " report_files = get_report_files()\n",
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+ " \n",
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+ " if not report_files:\n",
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+ " print(\"No reports to rewrite.\")\n",
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+ " return []\n",
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+ " \n",
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+ " rewritten_paths = []\n",
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+ " \n",
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+ " # Process each report file\n",
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+ " for report_path in report_files:\n",
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+ " # Rewrite the report\n",
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+ " rewritten_path = rewrite_report(report_path, ORIGINAL_USER_INPUT)\n",
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+ " \n",
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+ " if rewritten_path:\n",
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+ " rewritten_paths.append(rewritten_path)\n",
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+ " \n",
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+ " # IMPORTANT: Force garbage collection to ensure no history is kept between reports\n",
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+ " # This simulates removing the old report from input history\n",
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+ " import gc\n",
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+ " gc.collect()\n",
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+ " \n",
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+ " print(\"\\n--------\\n\")\n",
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+ " \n",
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+ " return rewritten_paths"
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+ ]
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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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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "print(\"Starting report rewriting process...\")\n",
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+ "\n",
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+ "# Validate user input\n",
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+ "if ORIGINAL_USER_INPUT == \"[Your input here - describe what you want Llama to do with these reports]\":\n",
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+ " print(\"Please edit the ORIGINAL_USER_INPUT cell to specify your request before running this cell.\")\n",
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+ "else:\n",
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+ " # Process all reports\n",
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+ " rewritten_paths = rewrite_all_reports()\n",
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+ " \n",
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+ " print(\"\\nReport rewriting complete!\")\n",
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+ " print(f\"Rewritten {len(rewritten_paths)} reports.\")\n",
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+ " \n",
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+ " # List all rewritten reports\n",
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+ " if rewritten_paths:\n",
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+ " print(\"\\nRewritten reports:\")\n",
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+ " for path in rewritten_paths:\n",
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+ " print(f\"- {path}\")"
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+ ]
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+ }
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+ ],
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+ "metadata": {
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+ "kernelspec": {
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+ "display_name": "Python 3",
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+ "language": "python",
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+ "name": "python3"
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+ },
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+ "language_info": {
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+ "codemirror_mode": {
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+ "name": "ipython",
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+ "version": 3
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+ },
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+ "file_extension": ".py",
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+ "mimetype": "text/x-python",
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+ "name": "python",
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+ "nbconvert_exporter": "python",
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+ "pygments_lexer": "ipython3",
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+ "version": "3.8.5"
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+ }
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+ },
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+ "nbformat": 4,
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+ "nbformat_minor": 4
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+}
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Sanyam Bhutani