From 713354371e954ae018e1df60573e987011d2e87e Mon Sep 17 00:00:00 2001
From: timothyafolami <timmyafolami8469@gmail.com>
Date: Thu, 15 Aug 2024 23:17:17 +0100
Subject: [PATCH] parallel processing added

---
 __pycache__/utils.cpython-311.pyc  | Bin 21162 -> 22890 bytes
 data/documents.json                |   1 -
 index/faiss_index_data/index.faiss | Bin 1047597 -> 1047597 bytes
 index/faiss_index_data/index.pkl   | Bin 1019951 -> 1019500 bytes
 loggings/app.log                   | 128 +++++++++++++
 requirements.txt                   |   3 +-
 search_note.ipynb                  | 287 ++++++++++++++++++++++++++++-
 utils.py                           | 157 +++++++++-------
 8 files changed, 500 insertions(+), 76 deletions(-)
 delete mode 100644 data/documents.json

diff --git a/__pycache__/utils.cpython-311.pyc b/__pycache__/utils.cpython-311.pyc
index e43127e3a03cf0b52c190691a6c1f1823531efb6..98455ab403c1bb87a8e0ed2f164c0285a6a33099 100644
GIT binary patch
delta 7794
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diff --git a/data/documents.json b/data/documents.json
deleted file mode 100644
index 40071c7b..00000000
--- a/data/documents.json
+++ /dev/null
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diff --git a/loggings/app.log b/loggings/app.log
index f3e75e05..17a9c530 100644
--- a/loggings/app.log
+++ b/loggings/app.log
@@ -533,3 +533,131 @@ To avoid injury, hold up the wheel when unscrewing the bolts.
 2024-08-15 12:50:08,732 - INFO - Vector store created
 2024-08-15 12:50:08,732 - INFO - Saving the vector store
 2024-08-15 12:50:08,745 - INFO - Vector store saved
+2024-08-15 22:27:53,640 - INFO - Loading data from ./data
+2024-08-15 22:28:26,454 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:15,773 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:18,312 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:21,194 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:23,563 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:25,707 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:28,079 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:30,046 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:32,244 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:33,863 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:34,996 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:37,244 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:39,593 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:41,416 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:42,381 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:43,283 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:45,605 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:46,734 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:50,144 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:53,144 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:54,149 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:29:56,683 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:30:01,059 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:30:04,416 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:30:07,578 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:30:08,304 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:30:12,904 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:30:16,304 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
+2024-08-15 22:30:19,593 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/audio/translations "HTTP/1.1 200 OK"
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+2024-08-15 22:38:18,873 - INFO - Loading data from ./data
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+2024-08-15 22:41:42,974 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/chat/completions "HTTP/1.1 200 OK"
+2024-08-15 22:41:43,339 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/chat/completions "HTTP/1.1 200 OK"
+2024-08-15 22:41:43,773 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/chat/completions "HTTP/1.1 200 OK"
+2024-08-15 22:41:44,140 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/chat/completions "HTTP/1.1 200 OK"
+2024-08-15 22:41:44,574 - INFO - HTTP Request: POST https://api.groq.com/openai/v1/chat/completions "HTTP/1.1 200 OK"
+2024-08-15 22:41:44,574 - INFO - Data loaded
+2024-08-15 22:41:44,574 - INFO - Creating vector store
+2024-08-15 22:41:46,104 - WARNING - C:\Users\timmy_3aupohg\anaconda3\envs\smog_env\Lib\site-packages\transformers\models\bert\modeling_bert.py:439: UserWarning: 1Torch was not compiled with flash attention. (Triggered internally at C:\cb\pytorch_1000000000000\work\aten\src\ATen\native\transformers\cuda\sdp_utils.cpp:555.)
+  attn_output = torch.nn.functional.scaled_dot_product_attention(
+
+2024-08-15 22:41:56,183 - INFO - Vector store created
+2024-08-15 22:41:56,198 - INFO - Saving the vector store
+2024-08-15 22:41:56,198 - INFO - Vector store saved
diff --git a/requirements.txt b/requirements.txt
index 0cf4c531..13f49dfa 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -18,4 +18,5 @@ groq
 python-dotenv
 pydub 
 moviepy
-ffmpeg-python
\ No newline at end of file
+ffmpeg-python
+langchain-groq
\ No newline at end of file
diff --git a/search_note.ipynb b/search_note.ipynb
index ad86dd88..a00b0774 100644
--- a/search_note.ipynb
+++ b/search_note.ipynb
@@ -6,30 +6,299 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from utils import search\n",
-    "import sys, os"
+    "# !pip install langchain-groq"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from utils import search\n",
+    "import sys, os\n",
+    "from dotenv import load_dotenv\n",
+    "from langchain_groq import ChatGroq\n",
+    "from langchain_core.prompts.prompt import PromptTemplate\n",
+    "from langchain_core.output_parsers import StrOutputParser\n",
+    "load_dotenv()"
+   ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "# setting up groq api key\n",
+    "os.environ[\"GROQ_API_KEY\"] = os.getenv('GROQ_API_KEY')"
+   ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "\n",
+    "# chat set up\n",
+    "GROQ_LLM = ChatGroq(temperature=0, model_name=\"llama3-8b-8192\", max_tokens=100)\n",
+    "\n",
+    "\n",
+    "### Chains #####\n",
+    "# Initiator\n",
+    "def doc_summarizer(document_page: list) -> str:\n",
+    "    initiator_prompt = PromptTemplate(\n",
+    "        template=\"\"\"<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n",
+    "        Create a short summary of the document based on the provided text. \n",
+    "        \n",
+    "        Start with: This document is about...\n",
+    "        \n",
+    "        <|eot_id|><|start_header_id|>user<|end_header_id|>\n",
+    "        DOCUMENT: {document_page} \\n\n",
+    "        \n",
+    "        <|eot_id|><|start_header_id|>assistant<|end_header_id|>\"\"\",\n",
+    "        input_variables=[\"document_page\"],\n",
+    "    )\n",
+    "\n",
+    "    initiator_router = initiator_prompt | GROQ_LLM | StrOutputParser()\n",
+    "    output = initiator_router.invoke({\"document_page\":document_page})\n",
+    "    return output\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "document_page = 'How to change the engine oil of a toyota corrolla.'\n",
+    "# testing the function\n",
+    "summary = doc_summarizer(document_page)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'This document is about providing a step-by-step guide on how to change the engine oil of a Toyota Corolla.'"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "summary"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "docs = search(document_page)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[{'source': './data\\\\How to change engine oil and filter on TOYOTA Corolla.txt',\n",
+       "  'page': 1,\n",
+       "  'file_type': 'text'},\n",
+       " {'source': './data\\\\corolla-2020-toyota-owners-manual.pdf', 'page': 438},\n",
+       " {'source': './data\\\\How to change engine oil and filter on TOYOTA Corolla.txt',\n",
+       "  'page': 3,\n",
+       "  'file_type': 'text'},\n",
+       " {'source': './data\\\\How to change engine oil and filter on TOYOTA Corolla.txt',\n",
+       "  'page': 2,\n",
+       "  'file_type': 'text'},\n",
+       " {'source': './data\\\\corolla-2020-toyota-owners-manual.pdf', 'page': 525},\n",
+       " {'source': './data\\\\How to change spark plugs on TOYOTA COROLLA.docx',\n",
+       "  'page': 2,\n",
+       "  'file_type': 'text'},\n",
+       " {'source': './data\\\\How to change spark plugs on TOYOTA COROLLA.docx',\n",
+       "  'page': 3,\n",
+       "  'file_type': 'text'},\n",
+       " {'source': './data\\\\How to change engine oil and filter on TOYOTA Corolla.txt',\n",
+       "  'page': 0,\n",
+       "  'file_type': 'text'},\n",
+       " {'source': './data\\\\How to change spark plugs on TOYOTA COROLLA.docx',\n",
+       "  'page': 5,\n",
+       "  'file_type': 'text'},\n",
+       " {'source': './data\\\\How to change spark plugs on TOYOTA COROLLA.docx',\n",
+       "  'page': 6,\n",
+       "  'file_type': 'text'},\n",
+       " {'source': './data\\\\corolla-2020-toyota-owners-manual.pdf', 'page': 526},\n",
+       " {'source': './data\\\\corolla-2020-toyota-owners-manual.pdf', 'page': 422},\n",
+       " {'source': './data\\\\corolla-2020-toyota-owners-manual.pdf', 'page': 514},\n",
+       " {'source': './data\\\\corolla-2020-toyota-owners-manual.pdf', 'page': 153},\n",
+       " {'filename': 'audio-2', 'duration': '0-3 minutes', 'file_type': 'audio'},\n",
+       " {'filename': 'audio-2', 'duration': '3-6 minutes', 'file_type': 'audio'},\n",
+       " {'source': './data\\\\corolla-2020-toyota-owners-manual.pdf', 'page': 149},\n",
+       " {'source': './data\\\\corolla-2020-toyota-owners-manual.pdf', 'page': 513},\n",
+       " {'source': './data\\\\corolla-2020-toyota-owners-manual.pdf', 'page': 436},\n",
+       " {'source': './data\\\\corolla-2020-toyota-owners-manual.pdf', 'page': 148}]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "docs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from collections import defaultdict\n",
+    "\n",
+    "def transform_file_data(input_data):\n",
+    "    # Create a dictionary to aggregate data by filename\n",
+    "    aggregated_data = defaultdict(lambda: {\n",
+    "        'filename': '',\n",
+    "        'pages': [],\n",
+    "        'timestamps': [],\n",
+    "        'description': 'lorem ipsum',\n",
+    "        'filetype': '',\n",
+    "        'thumbnail': '',\n",
+    "        'track_id': 123\n",
+    "    })\n",
+    "\n",
+    "    for item in input_data:\n",
+    "        if 'source' in item:\n",
+    "            file_path = item['source']\n",
+    "            filename = file_path.split('\\\\')[-1]\n",
+    "            extension = filename.split('.')[-1]\n",
+    "\n",
+    "            aggregated_data[filename]['filename'] = filename\n",
+    "            aggregated_data[filename]['filetype'] = extension\n",
+    "            aggregated_data[filename]['thumbnail'] = f\"{filename.split('.')[0]}.jpg\"\n",
+    "\n",
+    "            if extension in ['pdf', 'txt', 'docx']:\n",
+    "                aggregated_data[filename]['pages'].append(item['page'])\n",
+    "            elif extension in ['mp4', 'mkv', 'flv']:\n",
+    "                aggregated_data[filename]['timestamps'].append(item['page'])\n",
+    "            elif extension in ['mp3', 'wav', 'flac']:\n",
+    "                aggregated_data[filename]['timestamps'].append(item['page'])\n",
+    "            elif extension in ['jpg', 'jpeg', 'png', 'gif', 'bmp']:\n",
+    "                aggregated_data[filename].pop('pages', None)  # Remove pages if it's an image\n",
+    "                aggregated_data[filename].pop('timestamps', None)  # Remove timestamps if it's an image\n",
+    "\n",
+    "        elif 'filename' in item:\n",
+    "            filename = item['filename']\n",
+    "            extension = item['file_type']\n",
+    "            aggregated_data[filename]['filename'] = f\"{filename}.{extension}\"\n",
+    "            aggregated_data[filename]['filetype'] = extension\n",
+    "            aggregated_data[filename]['thumbnail'] = f\"{filename}.jpg\"\n",
+    "            if 'duration' in item:\n",
+    "                start_time, end_time = item['duration'].split(' minutes')[0].split('-')\n",
+    "                aggregated_data[filename]['timestamps'].append((int(start_time), int(end_time)))\n",
+    "\n",
+    "    # Convert aggregated data to the desired output format\n",
+    "    output_data = []\n",
+    "    for filename, data in aggregated_data.items():\n",
+    "        # Remove empty lists for pages and timestamps\n",
+    "        if not data['pages']:\n",
+    "            data.pop('pages', None)\n",
+    "        if not data['timestamps']:\n",
+    "            data.pop('timestamps', None)\n",
+    "        output_data.append(data)\n",
+    "\n",
+    "    return output_data\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'filename': 'How to change engine oil and filter on TOYOTA Corolla.txt', 'pages': [1, 3, 2, 0], 'description': 'lorem ipsum', 'filetype': 'txt', 'thumbnail': 'How to change engine oil and filter on TOYOTA Corolla.jpg', 'track_id': 123}\n",
+      "{'filename': 'corolla-2020-toyota-owners-manual.pdf', 'pages': [438, 525, 526, 422, 514, 153, 149, 513, 436, 148], 'description': 'lorem ipsum', 'filetype': 'pdf', 'thumbnail': 'corolla-2020-toyota-owners-manual.jpg', 'track_id': 123}\n",
+      "{'filename': 'How to change spark plugs on TOYOTA COROLLA.docx', 'pages': [2, 3, 5, 6], 'description': 'lorem ipsum', 'filetype': 'docx', 'thumbnail': 'How to change spark plugs on TOYOTA COROLLA.jpg', 'track_id': 123}\n",
+      "{'filename': 'audio-2.audio', 'timestamps': [(0, 3), (3, 6)], 'description': 'lorem ipsum', 'filetype': 'audio', 'thumbnail': 'audio-2.jpg', 'track_id': 123}\n"
+     ]
+    }
+   ],
+   "source": [
+    "output = transform_file_data(docs)\n",
+    "for item in output:\n",
+    "    print(item)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[{'filename': 'How to change engine oil and filter on TOYOTA Corolla.txt',\n",
+       "  'pages': [1, 3, 2, 0],\n",
+       "  'description': 'lorem ipsum',\n",
+       "  'filetype': 'txt',\n",
+       "  'thumbnail': 'How to change engine oil and filter on TOYOTA Corolla.jpg',\n",
+       "  'track_id': 123},\n",
+       " {'filename': 'corolla-2020-toyota-owners-manual.pdf',\n",
+       "  'pages': [438, 525, 526, 422, 514, 153, 149, 513, 436, 148],\n",
+       "  'description': 'lorem ipsum',\n",
+       "  'filetype': 'pdf',\n",
+       "  'thumbnail': 'corolla-2020-toyota-owners-manual.jpg',\n",
+       "  'track_id': 123},\n",
+       " {'filename': 'How to change spark plugs on TOYOTA COROLLA.docx',\n",
+       "  'pages': [2, 3, 5, 6],\n",
+       "  'description': 'lorem ipsum',\n",
+       "  'filetype': 'docx',\n",
+       "  'thumbnail': 'How to change spark plugs on TOYOTA COROLLA.jpg',\n",
+       "  'track_id': 123},\n",
+       " {'filename': 'audio-2.audio',\n",
+       "  'timestamps': [(0, 3), (3, 6)],\n",
+       "  'description': 'lorem ipsum',\n",
+       "  'filetype': 'audio',\n",
+       "  'thumbnail': 'audio-2.jpg',\n",
+       "  'track_id': 123}]"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "output"
+   ]
   },
   {
    "cell_type": "code",
diff --git a/utils.py b/utils.py
index 499ff917..9f79117c 100644
--- a/utils.py
+++ b/utils.py
@@ -6,14 +6,19 @@ from langchain_community.vectorstores import FAISS
 from langchain_community.document_loaders import PyPDFLoader
 from langchain_community.document_loaders import TextLoader
 from langchain_community.document_loaders import Docx2txtLoader
+from langchain_groq import ChatGroq
+from langchain_core.prompts.prompt import PromptTemplate
+from langchain_core.output_parsers import StrOutputParser
 from uuid import uuid4
 from langchain_core.documents  import Document
 from text_extractor import TextExtractor
 import os
+from concurrent.futures import ThreadPoolExecutor
 import math
 import json
 from groq import Groq
 import re
+import time
 import shutil
 import numpy as np
 from pydub import AudioSegment
@@ -26,10 +31,15 @@ load_dotenv()
 
 # OpenAI API Key
 api_key = os.getenv('OPENAI_API_KEY')
+# setting up groq api key
+os.environ["GROQ_API_KEY"] = os.getenv('GROQ_API_KEY')
 client = Groq(api_key = os.getenv('GROQ_API_KEY'))
 model = 'whisper-large-v3'
 
 
+# chat set up
+GROQ_LLM = ChatGroq(temperature=0, model_name="llama3-8b-8192", max_tokens=100)
+
 # ----------------------------------------------------------------------------------------------------
 # loading the embedding model
 def load_embedding_model():
@@ -337,6 +347,25 @@ def preprocess_video_data(video_path: str, time_interval: int):
     return documents
 
 
+#----------------------------------------------------DOC SUMMARIZER --------------------------------------------------
+def doc_summarizer(document_page: list) -> str:
+    initiator_prompt = PromptTemplate(
+        template="""<|begin_of_text|><|start_header_id|>system<|end_header_id|>
+        Create a short summary of the document based on the provided text. 
+        
+        Start with: This document is about...
+        
+        <|eot_id|><|start_header_id|>user<|end_header_id|>
+        DOCUMENT: {document_page} \n
+        
+        <|eot_id|><|start_header_id|>assistant<|end_header_id|>""",
+        input_variables=["document_page"],
+    )
+
+    initiator_router = initiator_prompt | GROQ_LLM | StrOutputParser()
+    output = initiator_router.invoke({"document_page":document_page})
+    return output
+
 
 #-----------------------------------------------------OTHERS--------------------------------------------------------------
 
@@ -348,88 +377,86 @@ def load_embedded_data(embeddings=embeddings, key="data"):
   embed_db = FAISS.load_local(f"index/faiss_index_{key}", embeddings, allow_dangerous_deserialization=True)
   return embed_db
 
+#-----------------------------------------------------Data Loading Process----------------------------------------------------
 
 # creating a function to load all documents from a directory. 
+def process_document(path, extension, text_doc, image_doc, audio_doc, video_doc):
+    doc_name = os.path.basename(path).split('.')[0]
+    
+    process_map = {
+        "text": load_document,
+        "image": create_image_document,
+        "audio": create_audio_document,
+        "video": preprocess_video_data
+    }
+    
+    if extension in text_doc:
+        doc = process_map["text"](path)
+        num_pages = len(doc)
+    elif extension in image_doc:
+        doc = process_map["image"](path)
+        num_pages = 1
+        doc_name = doc[0].metadata['filename']
+    elif extension in audio_doc:
+        doc = process_map["audio"](path)
+        num_pages = len(doc)
+        doc_name = doc[0].metadata['filename']
+    elif extension in video_doc:
+        doc = process_map["video"](path, time_interval=30)
+        num_pages = len(doc)
+        doc_name = doc[0].metadata['filename']
+    else:
+        return None, None, None  # Unhandled extension
+    
+    print(f"Document {doc_name} loaded")
+    return doc, doc_name, num_pages
+
 def load_documents_from_directory(directory_path: str):
     text_doc = ['pdf', 'txt', 'docx', 'doc', 'md']
     image_doc = ['jpg', 'jpeg', 'png', 'gif', 'bmp']
     audio_doc = ['mp3', 'wav', 'flac', 'ogg', 'm4a']
     video_doc = ['mp4', 'avi', 'mkv', 'flv', 'mov']
     
-    # accessing the name of the files in the directory
     files = os.listdir(directory_path)
-    # creating a list to store the documents
     documents = []
-    # another list for the document names 
     doc_names = []
-    # counting the number of pages in the document
-    num_pages= []
-    # iterating through the files in the directory
-    for file in files: 
-        # updating the path
-        path = os.path.join(directory_path, file)
-        # getting the file extension and doc name
-        doc_name, extension = path.split('/')[-1].split('.')[0] , file.split('.')[-1]
-        # checking if the file is a text document
-        if extension in text_doc:
-            # loading the document
-            doc = load_document(path)
-            # appending the document to the documents list
+    num_pages = []
+    doc_summary = []
+    
+    def process_with_delay(file):
+        result = process_document(os.path.join(directory_path, file), file.split('.')[-1], text_doc, image_doc, audio_doc, video_doc)
+        time.sleep(0.1)  # Introduce a 0.1s delay between processing each document
+        return result
+    
+    with ThreadPoolExecutor() as executor:
+        results = executor.map(process_with_delay, files)
+    
+    for doc, doc_name, pages in results:
+        if doc is not None:
             documents.append(doc)
-            # appending the number of pages in the document
-            num_pages.append(len(doc))
-            # adding the document name to the doc_names list
             doc_names.append(doc_name)
-            print(f"Document {doc_name} loaded")
-        elif extension in image_doc:
-            # creating an image document
-            doc = create_image_document(path)
-            # appending the document to the documents list
-            documents.append(doc)
-            # appending the number of pages in the document
-            num_pages.append(1)
-            # adding the document name to the doc_names list
-            doc_names.append(doc[0].metadata['filename'])
-            print(f"Document {doc[0].metadata['filename']} loaded")
-        elif extension in audio_doc:
-            # creating an audio document
-            doc = create_audio_document(path)
-            # appending the document to the documents list
-            documents.append(doc)
-            # appending the number of pages in the document
-            num_pages.append(len(doc))
-            # adding the document name to the doc_names list
-            doc_names.append(doc[0].metadata['filename'])
-            print(f"Document {doc[0].metadata['filename']} loaded")
-        elif extension in video_doc:
-            # creating a video document
-            doc = preprocess_video_data(path, time_interval=30)
-            # appending the document to the documents list
-            documents.append(doc)
-            # appending the number of pages in the document
-            num_pages.append(len(doc))
-            # adding the document name to the doc_names list
-            doc_names.append(doc[0].metadata['filename'])
-            print(f"Document {doc[0].metadata['filename']} loaded")
+            num_pages.append(pages)
             
-    # so we need to create a document id for each document
-    docs_id = [uuid4().hex for i in range(len(documents))]
-    # creating a json file to store the documents, checking if it exists then open it, else create it
-    json_file = f"{directory_path}/documents.json"
+            # creating doc summary
+            first_page = doc[0].page_content
+            summary = doc_summarizer(first_page)
+            doc_summary.append(summary)
+    
+    docs_id = [uuid4().hex for _ in range(len(documents))]
+    
+    json_file = os.path.join(directory_path, 'data.json')
+    data = {'doc_names': doc_names, 'docs_id': docs_id, 'num_pages': num_pages, 'doc_summaary': doc_summary}
+    
     if os.path.exists(json_file):
-        with open(json_file, 'r') as f:
-            data = json.load(f)
-            data['doc_names'] = doc_names
-            data['docs_id'] = docs_id
-            data['num_pages'] = num_pages
-        with open(json_file, 'w') as f:
-            json.dump(data, f)
+        with open(json_file, 'r+') as f:
+            existing_data = json.load(f)
+            existing_data.update(data)
+            f.seek(0)
+            json.dump(existing_data, f)
     else:
-        data = {'doc_names': doc_names, 'docs_id': docs_id, 'num_pages': num_pages}
         with open(json_file, 'w') as f:
             json.dump(data, f)
     
-    # returning the documents, and doc ids
     return documents, docs_id, num_pages
 
 
@@ -475,6 +502,6 @@ def search(query, k=20):
     all = []
     info = []
     for doc in docs:
-        all.append({doc.page_content})
+        # all.append({doc.page_content})
         info.append(dict(doc.metadata))
-    return docs[0].page_content, all, info
+    return info