{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from llama_index.core import SimpleDirectoryReader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "passbook_id = \"user001\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Document(id_='2612cab8-acbb-48c8-87a7-839b628cf654', embedding=None, metadata={'file_path': 'passbooks\\\\user001.json', 'file_name': 'user001.json', 'file_type': 'application/json', 'file_size': 1878, 'creation_date': '2024-05-05', 'last_modified_date': '2024-05-06'}, excluded_embed_metadata_keys=['file_name', 'file_type', 'file_size', 'creation_date', 'last_modified_date', 'last_accessed_date'], excluded_llm_metadata_keys=['file_name', 'file_type', 'file_size', 'creation_date', 'last_modified_date', 'last_accessed_date'], relationships={}, text='[\\r\\n    {\\r\\n        \"entry_id\": 1,\\r\\n        \"date\": \"06-05-2024\",\\r\\n        \"description\": \"Groceries\",\\r\\n        \"debit\": 100.00,\\r\\n        \"credit\": null,\\r\\n        \"balance\": 25640.00\\r\\n    },\\r\\n\\r\\n    {\\r\\n        \"entry_id\": 2,\\r\\n        \"date\": \"06-05-2024\",\\r\\n        \"description\": \"Salary\",\\r\\n        \"debit\": null,\\r\\n        \"credit\": 1000.00,\\r\\n        \"balance\": 26640.00\\r\\n    },\\r\\n\\r\\n    {\\r\\n        \"entry_id\": 3,\\r\\n        \"date\": \"06-05-2024\",\\r\\n        \"description\": \"Rent\",\\r\\n        \"debit\": 500.00,\\r\\n        \"credit\": null,\\r\\n        \"balance\": 26140.00\\r\\n    },\\r\\n\\r\\n    {\\r\\n        \"entry_id\": 4,\\r\\n        \"date\": \"06-05-2024\",\\r\\n        \"description\": \"Electricity\",\\r\\n        \"debit\": 200.00,\\r\\n        \"credit\": null,\\r\\n        \"balance\": 25940.00\\r\\n    },\\r\\n\\r\\n    {\\r\\n        \"entry_id\": 5,\\r\\n        \"date\": \"06-05-2024\",\\r\\n        \"description\": \"Internet\",\\r\\n        \"debit\": 50.00,\\r\\n        \"credit\": null,\\r\\n        \"balance\": 25890.00\\r\\n    },\\r\\n\\r\\n    {\\r\\n        \"entry_id\": 6,\\r\\n        \"date\": \"06-05-2024\",\\r\\n        \"description\": \"Salary\",\\r\\n        \"debit\": null,\\r\\n        \"credit\": 1000.00,\\r\\n        \"balance\": 26890.00\\r\\n    },\\r\\n\\r\\n    {\\r\\n        \"entry_id\": 7,\\r\\n        \"date\": \"06-05-2024\",\\r\\n        \"description\": \"Groceries\",\\r\\n        \"debit\": 100.00,\\r\\n        \"credit\": null,\\r\\n        \"balance\": 26790.00\\r\\n    },\\r\\n\\r\\n    {\\r\\n        \"entry_id\": 8,\\r\\n        \"date\": \"06-05-2024\",\\r\\n        \"description\": \"Rent\",\\r\\n        \"debit\": 500.00,\\r\\n        \"credit\": null,\\r\\n        \"balance\": 26290.00\\r\\n    },\\r\\n\\r\\n    {\\r\\n        \"entry_id\": 9,\\r\\n        \"date\": \"06-05-2024\",\\r\\n        \"description\": \"Electricity\",\\r\\n        \"debit\": 200.00,\\r\\n        \"credit\": null,\\r\\n        \"balance\": 26090.00\\r\\n    },\\r\\n\\r\\n    {\\r\\n        \"entry_id\": 10,\\r\\n        \"date\": \"06-05-2024\",\\r\\n        \"description\": \"Internet\",\\r\\n        \"debit\": 50.00,\\r\\n        \"credit\": null,\\r\\n        \"balance\": 26040.00\\r\\n    }\\r\\n]', start_char_idx=None, end_char_idx=None, text_template='{metadata_str}\\n\\n{content}', metadata_template='{key}: {value}', metadata_seperator='\\n')]\n"
     ]
    }
   ],
   "source": [
    "json_file = SimpleDirectoryReader(\n",
    "    input_files = [f\"passbooks/{passbook_id}.json\"]\n",
    "    ).load_data()\n",
    "print(json_file)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from llama_index.core.prompts.prompts import SimpleInputPrompt\n",
    "\n",
    "system_prompt=\"\"\"\n",
    "You are a Q&A assistant. Your goal is to answer questions as accurately as possible based on the instructions and context provided.\n",
    "You will be provided with list of bank statements and you have to analyse the debits and credits based on the description and date and answer accordingly to user queries.\n",
    "\"\"\"\n",
    "\n",
    "query_wrapper_prompt=SimpleInputPrompt(\"<|USER|>{query_str}<|ASSISTANT|>\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3ac9bb85d9e1454cab179dd35d68acc9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "login()\n",
    "from huggingface_hub import login"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "67442839d6c2476ead1161d68bc1aeb8",
       "version_major": 2,
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d4247816f85c4b739086ee4f9d931524",
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      "text/plain": [
       "Downloading shards:   0%|          | 0/2 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e7d41810429e4265974a3fd1f1b08163",
       "version_major": 2,
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      "text/plain": [
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0d50b062af094dbe9b9e533f774afdad",
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "84ff3eea97f940819f3faad537d6099d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Loading checkpoint shards:   0%|          | 0/2 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e95f5b3a53c3415c86e47f4cdbec05ab",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:root:Some parameters are on the meta device device because they were offloaded to the cpu and disk.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "26503efe392d46dca3e2553747db4c13",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "dd746f7ec6674bb2afad573344f8b95c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d4e2ffaa78024eadb753ea3d87b12489",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "01c4aaaede0b40b28946a4bef395d0c6",
       "version_major": 2,
       "version_minor": 0
      },
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from llama_index.llms.huggingface import HuggingFaceLLM\n",
    "import torch\n",
    "\n",
    "\n",
    "llm = HuggingFaceLLM(\n",
    "    context_window=4096,\n",
    "    max_new_tokens=256,\n",
    "    generate_kwargs={\"temperature\": 0.0, \"do_sample\": False},\n",
    "    system_prompt=system_prompt,\n",
    "    query_wrapper_prompt=query_wrapper_prompt,\n",
    "    tokenizer_name=\"meta-llama/Llama-2-7b-chat-hf\",\n",
    "    model_name=\"meta-llama/Llama-2-7b-chat-hf\",\n",
    "    device_map=\"auto\",\n",
    "    model_kwargs={\"torch_dtype\": torch.float16},\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.embeddings.huggingface import HuggingFaceEmbeddings\n",
    "from llama_index.legacy.embeddings.langchain import LangchainEmbedding\n",
    "\n",
    "embed_model=LangchainEmbedding(\n",
    "    HuggingFaceEmbeddings(model_name=\"sentence-transformers/all-mpnet-base-v2\")\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\puran\\AppData\\Local\\Temp\\ipykernel_4904\\1600445012.py:2: DeprecationWarning: Call to deprecated class method from_defaults. (ServiceContext is deprecated, please use `llama_index.settings.Settings` instead.) -- Deprecated since version 0.10.0.\n",
      "  service_context = ServiceContext.from_defaults(\n"
     ]
    }
   ],
   "source": [
    "from llama_index.core import ServiceContext\n",
    "service_context = ServiceContext.from_defaults(\n",
    "    chunk_size=1024,\n",
    "    llm=llm,\n",
    "    embed_model=embed_model\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "from llama_index.core import VectorStoreIndex\n",
    "\n",
    "vector_index = VectorStoreIndex.from_documents(json_file, service_context=service_context)\n",
    "query_engine = vector_index.as_query_engine()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\puran\\OneDrive\\Desktop\\RAG_Testing\\rag\\lib\\site-packages\\transformers\\generation\\configuration_utils.py:492: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0.0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
      "  warnings.warn(\n",
      "c:\\Users\\puran\\OneDrive\\Desktop\\RAG_Testing\\rag\\lib\\site-packages\\transformers\\generation\\configuration_utils.py:497: UserWarning: `do_sample` is set to `False`. However, `top_p` is set to `0.9` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `top_p`.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "response=query_engine.query(\"where do i debit frequently?\")\n",
    "print(response)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "rag",
   "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": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}