dolly_3hf.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tkHmyqmmXnRe",
        "outputId": "740fa6b3-ed41-4bac-d91b-cc9158cbfa3a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "\u001b[?25h  Building wheel for sentence_transformers (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m4.3/4.3 MB\u001b[0m \u001b[31m115.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[?25h  Building wheel for python-docx (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for python-pptx (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for olefile (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "  Building wheel for transformers (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
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            "\u001b[?25h"
          ]
        }
      ],
      "source": [
        "!pip -qqq install langchain apify-client faiss-cpu sentence_transformers accelerate bitsandbytes\n",
        "!pip -q install langchain unstructured sentence_transformers faiss-cpu huggingface_hub OpenAI\n",
        "!pip -q install git+https://github.com/huggingface/transformers\n",
        "!pip install -q datasets loralib sentencepiece\n",
        "!pip -q install bitsandbytes accelerate einops\n",
        "# !pip install pdfplumber\n",
        "\n",
        "from langchain.document_loaders.base import Document\n",
        "from langchain.indexes import VectorstoreIndexCreator\n",
        "from langchain.utilities import ApifyWrapper\n",
        "from langchain.document_loaders import PyPDFDirectoryLoader\n",
        "from langchain.text_splitter import CharacterTextSplitter\n",
        "from langchain.embeddings import HuggingFaceEmbeddings\n",
        "from langchain.vectorstores import FAISS, Chroma\n",
        "from langchain.chains.question_answering import load_qa_chain\n",
        "from langchain.chains.qa_with_sources import load_qa_with_sources_chain\n",
        "from langchain.chains import RetrievalQA\n",
        "from langchain.chains import RetrievalQAWithSourcesChain\n",
        "from langchain.document_loaders import ApifyDatasetLoader\n",
        "from transformers import LlamaTokenizer, LlamaForCausalLM, GenerationConfig, pipeline, AutoTokenizer, AutoModelForCausalLM\n",
        "from langchain.llms import HuggingFacePipeline\n",
        "from langchain import PromptTemplate, LLMChain\n",
        "import torch"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "embeddings = HuggingFaceEmbeddings(model_name=\"intfloat/e5-large-v2\")"
      ],
      "metadata": {
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          "base_uri": "https://localhost:8080/",
          "height": 433,
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    },
    {
      "cell_type": "code",
      "source": [
        "!pip install pdfplumber\n",
        "import pdfplumber\n",
        "\n",
        "def pdf_loader(pdf_file):\n",
        "    with pdfplumber.open(pdf_file) as pdf:\n",
        "        pages = pdf.pages\n",
        "\n",
        "        documents = []\n",
        "        for page in pages:\n",
        "            text = page.extract_text()\n",
        "            documents.append(Document(page_content=text))\n",
        "\n",
        "    return documents\n",
        "\n",
        "documents = pdf_loader(\"football.pdf\")\n",
        "\n",
        "text_splitter = CharacterTextSplitter(\n",
        "    separator = \"\\n\",\n",
        "    chunk_size = 1000,\n",
        "    chunk_overlap  = 200\n",
        "    )\n",
        "\n",
        "docs = text_splitter.split_documents(documents)\n",
        "db = FAISS.from_documents(docs, embeddings)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nfauMlAK7maD",
        "outputId": "c36a0a44-1554-4af2-ecfe-753efc94e871"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: pdfplumber in /usr/local/lib/python3.10/dist-packages (0.9.0)\n",
            "Requirement already satisfied: pdfminer.six==20221105 in /usr/local/lib/python3.10/dist-packages (from pdfplumber) (20221105)\n",
            "Requirement already satisfied: Pillow>=9.1 in /usr/local/lib/python3.10/dist-packages (from pdfplumber) (10.0.0)\n",
            "Requirement already satisfied: Wand>=0.6.10 in /usr/local/lib/python3.10/dist-packages (from pdfplumber) (0.6.11)\n",
            "Requirement already satisfied: charset-normalizer>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from pdfminer.six==20221105->pdfplumber) (2.0.12)\n",
            "Requirement already satisfied: cryptography>=36.0.0 in /usr/local/lib/python3.10/dist-packages (from pdfminer.six==20221105->pdfplumber) (41.0.2)\n",
            "Requirement already satisfied: cffi>=1.12 in /usr/local/lib/python3.10/dist-packages (from cryptography>=36.0.0->pdfminer.six==20221105->pdfplumber) (1.15.1)\n",
            "Requirement already satisfied: pycparser in /usr/local/lib/python3.10/dist-packages (from cffi>=1.12->cryptography>=36.0.0->pdfminer.six==20221105->pdfplumber) (2.21)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import torch\n",
        "from instruct_pipeline import InstructionTextGenerationPipeline\n",
        "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
        "\n",
        "tokenizer = AutoTokenizer.from_pretrained(\"databricks/dolly-v2-3b\", padding_side=\"left\")\n",
        "model = AutoModelForCausalLM.from_pretrained(\"databricks/dolly-v2-3b\", device_map=\"auto\", torch_dtype=torch.bfloat16)\n",
        "\n",
        "# generate_text = InstructionTextGenerationPipeline(model=model, tokenizer=tokenizer)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 214,
          "referenced_widgets": [
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        },
        "id": "ZsBI22i1yKgm",
        "outputId": "2b7cff0e-9dbf-4ac5-de51-acbdedf28343"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)okenizer_config.json:   0%|          | 0.00/450 [00:00<?, ?B/s]"
            ],
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          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "a1ef280bde664ad8be8883e4e1d3fcde"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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              "version_major": 2,
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading pytorch_model.bin:   0%|          | 0.00/5.68G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "acbfe761bc07456a829e0aa92e82d1b8"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:accelerate.utils.modeling:The model weights are not tied. Please use the `tie_weights` method before using the `infer_auto_device` function.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "zSgYoWWoHhGg",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9adbc071-fc25-4edb-9c09-22f9bf7e479f"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Xformers is not installed correctly. If you want to use memory_efficient_attention to accelerate training use the following command to install Xformers\n",
            "pip install xformers.\n"
          ]
        }
      ],
      "source": [
        "pipe = pipeline(\n",
        "    \"text-generation\",\n",
        "    model=model,\n",
        "    tokenizer=tokenizer,\n",
        "    max_length=3000,\n",
        "    temperature=0,\n",
        "    top_p=0.95,\n",
        "    repetition_penalty=1.2,\n",
        ")\n",
        "\n",
        "local_llm = HuggingFacePipeline(pipeline=pipe)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "qa = RetrievalQA.from_chain_type(llm=local_llm,\n",
        "                                 chain_type=\"stuff\",\n",
        "                                 retriever=db.as_retriever(k=2),\n",
        "                                 return_source_documents=True,\n",
        "                                 verbose=True)\n",
        "\n",
        "query = \"what is football?\"\n",
        "result = qa(query)\n",
        "result"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ijs6kNKsyJbL",
        "outputId": "15ff380e-ec88-420e-90c5-67113289ac59"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Setting `pad_token_id` to `eos_token_id`:0 for open-end generation.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\n",
            "\u001b[1m> Entering new  chain...\u001b[0m\n",
            "\n",
            "\u001b[1m> Finished chain.\u001b[0m\n"
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              "{'query': 'what is football?',\n",
              " 'result': \" Football is a fast-moving game played between two teams of eleven players each. Each player has a ball and must pass it to another player on his team without letting go of his own handball. Players run onto a pitch marked out with lines representing the boundaries of the field. A referee officiates the game while referees for youth levels are usually coaches. There are four quarters followed by a half-time break where substitutions are allowed but not during actual play. The objective of the team that gets the ball through their opponents' defense three times in a row is scored. The first person to reach the opposition's goal line with the ball wins possession. The object of the game is to move the ball across the field until your teammate(s) score a goal. It is considered good form to support the strikers when they have the ball. This will help them create chances to get the ball into the net.\\n\\nThere are many variations of this basic rule set depending on the level of competition. For example, children often play with no offside rules whereas professional leagues typically enforce one side being able to advance the ball only if all members of their backline are behind the ball. Professional clubs use a round ball instead of a oblong one like amateur ones. Some countries even have different names for football: “futbol”, “kitschilfußball”, “futbol pérola”, etc.\\n\\n\",\n",
              " 'source_documents': [Document(page_content='7/11/23, 5:46 PM football -- Britannica Online Encyclopedia\\nfootball\\nfootball, also called association football or\\nTABLE OF CONTENTS\\nsoccer, game in which two teams of 11\\nplayers, using any part of their bodies\\nIntroduction\\nexcept their hands and arms, try to\\nHistory\\nmaneuver the ball into the opposing team’s\\nFootball around the world\\ngoal. Only the goalkeeper is permitted to\\nPlay of the game\\nhandle the ball and may do so only within\\nFIFA men’s World Cup winners\\nthe penalty area surrounding the goal. The\\nFIFA women’s World Cup winners\\nteam that scores more goals wins.\\nUEFA Champions League winners\\nUEFA Europa League winners\\nMajor League Soccer (MLS) Cup\\nwinners\\nFootball is the world’s most popular ball game in\\nCarlos Alberto Torres numbers of participants and spectators. Simple in its\\nprincipal rules and essential equipment, the sport can\\nbe played almost anywhere, from official football playing fields (pitches) to gymnasiums,', metadata={}),\n",
              "  Document(page_content='principal rules and essential equipment, the sport can\\nbe played almost anywhere, from official football playing fields (pitches) to gymnasiums,\\nstreets, school playgrounds, parks, or beaches. Football’s governing body, the Fédération\\nInternationale de Football Association (FIFA), estimated that at the turn of the 21st century\\nthere were approximately 250 million football players and over 1.3 billion people\\n“interested” in football; in 2010 a combined television audience of more than 26 billion\\nwatched football’s premier tournament, the quadrennial month-long World Cup finals.\\nFor a history of the origins of football sport, see football.\\nHistory\\nThe early years\\nModern football originated in Britain in the 19th century. Since before medieval times,\\n“folk football” games had been played in towns and villages according to local customs\\nand with a minimum of rules. Industrialization and urbanization, which reduced the amount', metadata={}),\n",
              "  Document(page_content='7/11/23, 5:46 PM football -- Britannica Online Encyclopedia\\nfrom other sports, including variant forms of football. In Canada, Scottish émigrés were\\nparticularly prominent in the game’s early development; however, Canadians subsequently\\nturned to ice hockey as their national sport.\\nIn the United States, gridiron football emerged early in the 20th century as the most\\npopular sport. But, beyond elite universities and schools, soccer (as the sport is popularly\\ncalled in the United States) was played widely in some cities with large immigrant\\npopulations such as Philadelphia, Chicago, Cleveland (Ohio), and St. Louis (Missouri), as\\nwell as New York City and Los Angeles after Hispanic migrations. The U.S. Soccer\\nFederation formed in 1913, affiliated with FIFA, and sponsored competitions. Between the\\nworld wars, the United States attracted scores of European emigrants who played football\\nfor local teams sometimes sponsored by companies.', metadata={}),\n",
              "  Document(page_content='“folk football” games had been played in towns and villages according to local customs\\nand with a minimum of rules. Industrialization and urbanization, which reduced the amount\\nof leisure time and space available to the working class, combined with a history of legal\\nprohibitions against particularly violent and destructive forms of folk football to undermine\\nthe game’s status from the early 19th century onward. However, football was taken up as a\\nhttps://www.britannica.com/print/article/550852 1/31', metadata={})]}"
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              "\" Football is a fast-moving game played between two teams of eleven players each. Each player has a ball and must pass it to another player on his team without letting go of his own handball. Players run onto a pitch marked out with lines representing the boundaries of the field. A referee officiates the game while referees for youth levels are usually coaches. There are four quarters followed by a half-time break where substitutions are allowed but not during actual play. The objective of the team that gets the ball through their opponents' defense three times in a row is scored. The first person to reach the opposition's goal line with the ball wins possession. The object of the game is to move the ball across the field until your teammate(s) score a goal. It is considered good form to support the strikers when they have the ball. This will help them create chances to get the ball into the net.\\n\\nThere are many variations of this basic rule set depending on the level of competition. For example, children often play with no offside rules whereas professional leagues typically enforce one side being able to advance the ball only if all members of their backline are behind the ball. Professional clubs use a round ball instead of a oblong one like amateur ones. Some countries even have different names for football: “futbol”, “kitschilfußball”, “futbol pérola”, etc.\\n\\n\""
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              "\"Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.\\n\\n{context}\\n\\nQuestion: {question}\\nHelpful Answer:\""
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