Mini-Projects/Doc_RAG.ipynb

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      "source": [
        "!pip install transformers faiss-gpu torch accelerate sentencepiece nltk pypdf2 pymupdf\n",
        "from IPython.display import clear_output\n",
        "clear_output()"
      ]
    },
    {
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      "metadata": {
        "id": "dS8NxyUz1E_H"
      },
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      "source": [
        "import torch\n",
        "from transformers import pipeline, AutoTokenizer, AutoModel\n",
        "import requests\n",
        "from bs4 import BeautifulSoup\n",
        "import faiss\n",
        "import nltk\n",
        "import numpy as np"
      ]
    },
    {
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        "outputId": "9c7e279b-f144-4715-9972-85190a2980b4"
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      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Unzipping tokenizers/punkt.zip.\n"
          ]
        }
      ],
      "source": [
        "nltk.download('punkt')\n",
        "from nltk.tokenize import sent_tokenize"
      ]
    },
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        "outputId": "f2ce3be9-7b78-4661-8539-800b98bc8352"
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      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
            "  warnings.warn(\n"
          ]
        },
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              "config.json:   0%|          | 0.00/819 [00:00<?, ?B/s]"
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              "instruct_pipeline.py:   0%|          | 0.00/9.16k [00:00<?, ?B/s]"
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          "text": [
            "A new version of the following files was downloaded from https://huggingface.co/databricks/dolly-v2-3b:\n",
            "- instruct_pipeline.py\n",
            ". Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "pytorch_model.bin:   0%|          | 0.00/5.68G [00:00<?, ?B/s]"
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          "metadata": {}
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        {
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          "data": {
            "text/plain": [
              "tokenizer_config.json:   0%|          | 0.00/450 [00:00<?, ?B/s]"
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        {
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          "data": {
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              "tokenizer.json:   0%|          | 0.00/2.11M [00:00<?, ?B/s]"
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          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884\n",
            "  warnings.warn(\n"
          ]
        }
      ],
      "source": [
        "llm = pipeline(model=\"databricks/dolly-v2-3b\",\n",
        "               torch_dtype=torch.bfloat16,\n",
        "               trust_remote_code=True,\n",
        "               device_map=\"auto\")"
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        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The Secret of Elysium Woods\n",
            " \n",
            "It all started with a missing dog. Benny, a sprightly golden retriever with a tendency to wander off, had disappeared from the yard again. For \n",
            "twelve-year-old Sarah, this was becoming a frustrating routine. Her parents had warned her countless times to keep the gate locked, but \n",
            "somehow Benny always found a way to slip away. This time, however, Benny hadn’t returned by evening. The sun had long since set, casting a \n",
            "deep blue shadow over the small town of Elysium, and Sarah felt a growing knot of worry in her stomach. \n",
            " \n",
            "\"He's probably just chasing squirrels in the woods,\" her older brother Jack had said, though he didn't seem too concerned. Jack, at sixteen, had a \n",
            "way of brushing off everything like it didn’t matter.\n",
            " \n",
            "But for Sarah, it did matter. Benny wasn’t just a dog—he was her best friend, her only companion during the long, lazy summer days when \n",
            "school was out. So, despite her parents' protests, Sarah grabbed a flashlight, pulled on her hoodie, and headed out to look for him. \n",
            " \n",
            "The woods that bordered the edge of town, known as Elysium Woods, had always intrigued Sarah. They were dense and dark, filled with \n",
            "towering trees that seemed to stretch endlessly toward the sky. It was said that no one really knew how deep the woods went, or what lay \n",
            "hidden beyond the first few miles. Local legends spoke of strange occurrences—unexplained lights at night, whispers carried on the wind, and \n",
            "figures that seemed to vanish the moment you turned to look. None of the adults ever took those stories seriously, of course, but kids like Sarah \n",
            "had always wondered. \n",
            " \n",
            "As she approached the tree line, the familiar rustling of leaves and the soft hooting of owls greeted her. She called out Benny’s name, her voice \n",
            "shaking a little in the stillness of the night. No response, except for the wind stirring the branches. \n",
            " \n",
            "Sarah ventured deeper into the woods, the beam of her flashlight cutting through the darkness in jittery patterns. She kept calling for Benny, the \n",
            "sound of her own voice the only thing keeping her grounded in the eerie quiet. After what felt like an hour of walking, she spotted something in \n",
            "the distance—a faint, flickering light, like a candle struggling to stay lit. \n",
            " Her heart leaped. *Maybe someone found Benny*, she thought. She quickened her pace, weaving through the trees and over fallen logs, her \n",
            "sneakers crunching softly against the undergrowth. But as she got closer, she realized the light wasn’t coming from a flashlight or a lantern. It \n",
            "was... floating. \n",
            " \n",
            "Sarah stopped in her tracks, her breath catching in her throat. The glowing orb hovered about three feet off the ground, pulsing with a soft, \n",
            "warm glow. It reminded her of a firefly, only much larger and... stranger. She stood frozen, staring at it, when suddenly it darted off deeper into \n",
            "the woods, as if beckoning her to follow. \n",
            " \n",
            "Against her better judgment, Sarah ran after it, the light of her flashlight bobbing wildly as she hurried through the trees. The glowing orb moved \n",
            "faster, darting left and right, leading her down paths she had never ventured before. She lost track of how long she had been running—ten \n",
            "minutes, twenty minutes, maybe more. The trees grew thicker, and the air seemed heavier, cooler. \n",
            " \n",
            "Just as she thought she had lost the orb, it stopped. The glowing light hovered in place for a moment before slowly dimming, as if its energy \n",
            "was fading. Sarah slowed her steps, approaching cautiously. Then, she saw it—an ancient, stone archway hidden amongst the trees, covered in \n",
            "moss and vines. The orb flickered one last time before disappearing altogether.\n",
            " \n",
            "Sarah stood before the archway, her heart pounding. It looked like something out of a fairy tale. Intricate carvings lined the stone, worn with age \n",
            "but still recognizable. Strange symbols she had never seen before were etched into the surface, and there was something written across the top \n",
            "in an ancient script she couldn’t decipher.\n",
            " \n",
            "She hesitated, glancing around to make sure no one else was there. The woods were still, almost unnaturally so. Swallowing her fear, Sarah \n",
            "stepped through the archway.\n",
            " \n",
            "On the other side, the world felt different—quieter, almost dreamlike. The trees here were even older, their trunks wide and gnarled, their \n",
            "branches twisting toward the sky like the arms of ancient giants. The air was thick with the scent of earth and rain, though no storm had \n",
            "passed. And there, in the middle of a clearing, sat Benny. \n",
            "He was lying in the grass, calm and content, as if nothing was out of the ordinary. Sarah’s heart surged with relief. “Benny!” she cried, rushing \n",
            "over to him. But as she knelt down to pet him, she noticed something strange. His fur shimmered faintly, as if dusted with a soft, golden light. \n",
            " \n",
            "Before she could react, she heard a voice—a deep, melodic sound that seemed to come from everywhere and nowhere at once.\n",
            " \n",
            "\"You have found the gateway.\"\n",
            " \n",
            "Sarah jumped to her feet, spinning around. There was no one there. The woods were empty, yet the voice lingered, echoing in her ears.\n",
            " \n",
            "“The gateway to what?” she asked, her voice shaking.\n",
            " \n",
            "“To the place where the lost things go. Few have ever found it, but those who do, never return the same.”\n",
            " \n",
            "Sarah’s mind raced. What did that mean? She glanced back at Benny, who was now sitting up, looking at her with those same gentle eyes, but \n",
            "something was different. His gaze seemed wiser, more knowing, as if he understood something she didn’t.\n",
            " \n",
            "“Why is Benny here?” she asked, trying to steady her voice. “What is this place?”\n",
            " \n",
            "The voice was silent for a moment before it answered. “This is Elysium, the heart of the woods, where the boundary between worlds is thin. \n",
            "Your dog has wandered into the in-between, a place of secrets and forgotten things. But now that you have crossed the threshold, you are part \n",
            "of the secret, too.”\n",
            " Sarah’s breath caught in her throat. Part of the secret? She hadn’t asked for this. All she wanted was to find her dog and go home. But \n",
            "something told her that leaving wouldn’t be so simple.\n",
            " \n",
            "As the wind stirred the leaves around her, Sarah realized she had stumbled into something far bigger than she could have ever imagined. The \n",
            "woods held a secret—a secret that was now hers to uncover.\n",
            " \n",
            "The voice spoke one last time, quieter now, almost a whisper. “Be careful, child. Once you’ve seen the other side, there is no going back.”\n",
            " \n",
            "And with that, the forest fell silent once more, leaving Sarah alone with Benny and the weight of a mystery she didn’t know how to solve.\n",
            " \n",
            " \n"
          ]
        }
      ],
      "source": [
        "from PyPDF2 import PdfReader\n",
        "\n",
        "reader = PdfReader(\"/content/sample-story.pdf\")\n",
        "content = \"\".join([page.extract_text() for page in reader.pages])\n",
        "print(content)"
      ]
    },
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      "source": [
        "tokenizer = AutoTokenizer.from_pretrained(\"sentence-transformers/all-mpnet-base-v2\")\n",
        "model = AutoModel.from_pretrained(\"sentence-transformers/all-mpnet-base-v2\")"
      ]
    },
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      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ELzRRqRl4xB5",
        "outputId": "2b27717b-2f68-4581-d86d-a073e1ec9df2"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of content chunks (sentences): 81\n"
          ]
        }
      ],
      "source": [
        "def chunk_content_by_sentence(content):\n",
        "    return sent_tokenize(content)\n",
        "\n",
        "content_chunks = chunk_content_by_sentence(content)\n",
        "print(f\"Number of content chunks (sentences): {len(content_chunks)}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ABYGjbLr6IJD",
        "outputId": "e8a6201f-71b4-43ee-a3d5-2c844f66d8b3"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Shape of embeddings: (81, 768)\n"
          ]
        }
      ],
      "source": [
        "chunk_embeddings = []\n",
        "for chunk in content_chunks:\n",
        "    inputs = tokenizer(chunk, return_tensors='pt', max_length=512, truncation=True)\n",
        "    with torch.no_grad():\n",
        "        embedding = model(**inputs).last_hidden_state.mean(dim=1).numpy()\n",
        "    chunk_embeddings.append(embedding)\n",
        "\n",
        "embeddings_np = np.vstack(chunk_embeddings)\n",
        "print(f\"Shape of embeddings: {embeddings_np.shape}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ggR5RiKq6MNS",
        "outputId": "cf27f5fd-0612-4048-e904-309d779d361c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of vectors in the FAISS index: 81\n"
          ]
        }
      ],
      "source": [
        "dimension = embeddings_np.shape[1]\n",
        "index = faiss.IndexFlatL2(dimension)\n",
        "index.add(embeddings_np)\n",
        "print(\"Number of vectors in the FAISS index:\", index.ntotal)"
      ]
    },
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      "cell_type": "code",
      "execution_count": 25,
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        "id": "C3ZKidW86PFB"
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        "def generate_rag_response(query, model, tokenizer, index, content_chunks):\n",
        "\n",
        "    query_inputs = tokenizer(query, return_tensors='pt')\n",
        "    with torch.no_grad():\n",
        "        query_embedding = model(**query_inputs).last_hidden_state.mean(dim=1).detach().numpy()\n",
        "    k = 2\n",
        "    distances, indices = index.search(query_embedding, k)\n",
        "    relevant_contexts = [content_chunks[i] for i in indices[0]]\n",
        "    combined_context = \" \".join(relevant_contexts)\n",
        "\n",
        "    input_text = (\n",
        "        f\"### Context Overview:\\n\"\n",
        "        f\"This is the {combined_context}\\n\"\n",
        "        f\"### Instructions:\\n\"\n",
        "        f\"Using the provided context, please answer the following question. Your response should:\\n\"\n",
        "        f\"- Be as clear and concise as possible.\\n\"\n",
        "        f\"- If the answer is not present in the context, respond with 'I don't know' instead of providing an incorrect answer.\\n\"\n",
        "        f\"- Make a proper, meaningful sentence for answering.\\n\\n\"\n",
        "        f\"### Question:\\n\"\n",
        "        f\"{query}\\n\\n\"\n",
        "        f\"### Your Answer:\"\n",
        "    )\n",
        "\n",
        "\n",
        "    response = llm(input_text, temperature=0.3)\n",
        "    return response[0]['generated_text'].strip()"
      ]
    },
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      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "colab": {
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        },
        "id": "aCArJpqf7XAs",
        "outputId": "130f42b3-9eb9-4ed3-e736-3fc5162ba1a1"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Generated Response: The missing dog's name was Benny.\n"
          ]
        }
      ],
      "source": [
        "query = \"What was the missing dog's name?\"\n",
        "response = generate_rag_response(query, model, tokenizer, index, content_chunks)\n",
        "print(\"Generated Response:\", response)"
      ]
    }
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