rag_experiments_camel5b.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "id": "trYJrn2cu_My"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/s448780/miniconda3/envs/pydev/lib/python3.8/site-packages/pydantic/_internal/_fields.py:160: UserWarning: Field \"model_id\" has conflict with protected namespace \"model_\".\n",
      "\n",
      "You may be able to resolve this warning by setting `model_config['protected_namespaces'] = ()`.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "from llama_index.core import SimpleDirectoryReader\n",
    "from llama_index.core.prompts import PromptTemplate\n",
    "\n",
    "from llama_index.core.llms import ChatMessage, MessageRole\n",
    "from llama_index.core import ChatPromptTemplate\n",
    "from llama_index.core.response.notebook_utils import display_response\n",
    "\n",
    "import torch\n",
    "from llama_index.llms.huggingface import HuggingFaceLLM # llm\n",
    "from llama_index.embeddings.huggingface import HuggingFaceEmbedding # embedding\n",
    "from llama_index.core import Settings # pass llm and embedding\n",
    "\n",
    "from llama_index.core import VectorStoreIndex # GPTVectorStoreIndex has been renamed to VectorStoreIndex, but it is only a cosmetic change. Please see the following links for more details on usage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from dotenv import load_dotenv\n",
    "load_dotenv()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "hf_token = os.getenv(\"hf_token\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The token has not been saved to the git credentials helper. Pass `add_to_git_credential=True` in this function directly or `--add-to-git-credential` if using via `huggingface-cli` if you want to set the git credential as well.\n",
      "Token is valid (permission: write).\n",
      "Your token has been saved to /home/s448780/.cache/huggingface/token\n",
      "Login successful\n"
     ]
    }
   ],
   "source": [
    "from huggingface_hub import login\n",
    "login(hf_token)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mkdir: cannot create directory ‘test/’: File exists\n"
     ]
    }
   ],
   "source": [
    "!mkdir test/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "id": "rSuHnW09pIW4"
   },
   "outputs": [],
   "source": [
    "documents = SimpleDirectoryReader(\"./test\").load_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "96g9pNfy8Yiy",
    "outputId": "74712d63-e97e-4d1c-f9c1-4e44784f8541"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'ucl_2023.pdf', 'ucl_2024.pdf'}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "books = set()\n",
    "for book in documents:\n",
    "  books.add(book.metadata[\"file_name\"])\n",
    "\n",
    "books"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "id": "ePMkWICPwETf"
   },
   "outputs": [],
   "source": [
    "model_id = \"Writer/camel-5b-hf\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4N2YE00MxKcU"
   },
   "source": [
    "## Plain prompt  template"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "id": "VhMsPLulwUZH"
   },
   "outputs": [],
   "source": [
    "# from open ai docs\n",
    "query_wrapper_prompt = PromptTemplate(\n",
    "    \"Always answer the question, even if the context isn't helpful.\"\n",
    "    \"Write a response that appropriately completes the request.\\n\"\n",
    "    \"Always use the most recent information.\\n\\n\"\n",
    "    \"### Instruction:\\n Using the most recent data answer- {query_str}\\n\\n### Response:\"\n",
    ")"
   ]
  },
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    },
    "id": "cMzO3x8rxk9Q",
    "outputId": "b257eafd-e58d-4aa8-81af-a7781de75a6c"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "The `load_in_4bit` and `load_in_8bit` arguments are deprecated and will be removed in the future versions. Please, pass a `BitsAndBytesConfig` object in `quantization_config` argument instead.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a356dd1774cb4b06b668871573e77910",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Loading checkpoint shards:   0%|          | 0/3 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "llm = HuggingFaceLLM(\n",
    "    context_window=2048,\n",
    "    max_new_tokens=256,\n",
    "    generate_kwargs={\"temperature\": 0, \"do_sample\": False},\n",
    "    query_wrapper_prompt=query_wrapper_prompt,\n",
    "    tokenizer_name=model_id,\n",
    "    model_name=model_id,\n",
    "    device_map=\"auto\",\n",
    "    tokenizer_kwargs={\"max_length\": 2048},\n",
    "    model_kwargs={\"torch_dtype\": torch.float16, \"load_in_8bit\" : True}\n",
    ")"
   ]
  },
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      "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n"
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      "Setting `pad_token_id` to `eos_token_id`:50256 for open-end generation.\n"
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