{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5hxScxn4C2C7"
      },
      "source": [
        "# RAG pipelines with Haystack + Zephyr 7B Beta 🪁\n",
        "\n",
        "*Notebook by [Stefano Fiorucci](https://www.linkedin.com/in/stefano-fiorucci/) and [Tuana Celik](https://www.linkedin.com/in/tuanacelik/)*\n",
        "\n",
        "We are going to build a nice Retrieval Augmented Generation pipeline for Rock music, using the 🏗️ **Haystack LLM orchestration framework** and a good LLM: 💬 [Zephyr 7B Beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) (fine-tuned version of Mistral 7B V.01 that focuses on helpfulness and outperforms many larger models on the MT-Bench and AlpacaEval benchmarks)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4spPB1okEaLy"
      },
      "source": [
        "## Install dependencies\n",
        "- `wikipedia` is needed to download data from Wikipedia\n",
        "- `haystack-ai` is the Haystack package\n",
        "- `sentence_transformers` is needed for embeddings\n",
        "- `transformers` is needed to use open-source LLMs\n",
        "- `accelerate` and `bitsandbytes` are required to use quantized versions of these models (with smaller memory footprint)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "R_Abekd7m0Ps"
      },
      "outputs": [],
      "source": [
        "%%capture\n",
        "! pip install wikipedia transformers-haystack bitsandbytes sentence-transformers-haystack"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "oZxQ0sY2I8fL"
      },
      "outputs": [],
      "source": [
        "from IPython.display import Image\n",
        "from pprint import pprint\n",
        "import torch\n",
        "import rich\n",
        "import random"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FN3CR1uGtTxH"
      },
      "source": [
        "## Load data from Wikipedia\n",
        "\n",
        "We are going to download the Wikipedia pages related to some Rock bands, using the python library `wikipedia`.\n",
        "\n",
        "These pages are converted into Haystack Documents"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "M1JMji_Vm289"
      },
      "outputs": [],
      "source": [
        "favourite_bands=\"\"\"Audioslave\n",
        "Blink-182\n",
        "Dire Straits\n",
        "Evanescence\n",
        "Green Day\n",
        "Muse (band)\n",
        "Nirvana (band)\n",
        "Sum 41\n",
        "The Cure\n",
        "The Smiths\"\"\".split(\"\\n\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "hsWE_glDoqVh"
      },
      "outputs": [],
      "source": [
        "import wikipedia\n",
        "wikipedia.set_user_agent(\"haystack-cookbook (https://github.com/deepset-ai/haystack-cookbook)\")\n",
        "wikipedia.set_rate_limiting(True)\n",
        "from haystack.dataclasses import Document\n",
        "\n",
        "raw_docs=[]\n",
        "\n",
        "for title in favourite_bands:\n",
        "    page = wikipedia.page(title=title, auto_suggest=False)\n",
        "    doc = Document(content=page.content, meta={\"title\": page.title, \"url\":page.url})\n",
        "    raw_docs.append(doc)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-JVo2FlEtbTZ"
      },
      "source": [
        "## The Indexing Pipeline"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "kLZ8HO4kpREU"
      },
      "outputs": [],
      "source": [
        "from haystack import Pipeline\n",
        "from haystack.document_stores.in_memory import InMemoryDocumentStore\n",
        "from haystack.components.preprocessors import DocumentCleaner, DocumentSplitter\n",
        "from haystack_integrations.components.embedders.sentence_transformers import SentenceTransformersTextEmbedder, SentenceTransformersDocumentEmbedder\n",
        "from haystack.components.writers import DocumentWriter\n",
        "from haystack.document_stores.types import DuplicatePolicy\n",
        "from haystack.utils import ComponentDevice"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qnGGIIQIGUqZ"
      },
      "source": [
        "We will save our final Documents in an `InMemoryDocumentStore`, a simple database which lives in memory."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "7vgQ3G3GwQ83"
      },
      "outputs": [],
      "source": [
        "document_store = InMemoryDocumentStore(embedding_similarity_function=\"cosine\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CA_vPfXmG9kf"
      },
      "source": [
        "Our indexing Pipeline transform the original Documents and save them in the Document Store.\n",
        "\n",
        "It consists of several components:\n",
        "\n",
        "- `DocumentCleaner`: performs a basic cleaning of the Documents\n",
        "- `DocumentSplitter`: chunks each Document into smaller pieces (more appropriate for semantic search and RAG)\n",
        "- `SentenceTransformersDocumentEmbedder`:\n",
        "  - represent each Document as a vector (capturing its meaning).\n",
        "  - we choose a good but not too big model from [MTEB leaderboard](https://huggingface.co/spaces/mteb/leaderboard).\n",
        "  - Also the metadata `title` is embedded, because it contains relevant information (`metadata_fields_to_embed` parameter).\n",
        "  - We use the GPU for this expensive operation (`device` parameter).\n",
        "- `DocumentWriter` just saves the Documents in the Document Store"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "htqK8XSTwOzP"
      },
      "outputs": [],
      "source": [
        "indexing = Pipeline()\n",
        "indexing.add_component(\"cleaner\", DocumentCleaner())\n",
        "indexing.add_component(\"splitter\", DocumentSplitter(split_by='sentence', split_length=2))\n",
        "indexing.add_component(\"doc_embedder\", SentenceTransformersDocumentEmbedder(model=\"thenlper/gte-large\",\n",
        "                                                                            device=ComponentDevice.from_str(\"cuda:0\"), \n",
        "                                                                            meta_fields_to_embed=[\"title\"]))\n",
        "indexing.add_component(\"writer\", DocumentWriter(document_store=document_store, policy=DuplicatePolicy.OVERWRITE))\n",
        "\n",
        "indexing.connect(\"cleaner\", \"splitter\")\n",
        "indexing.connect(\"splitter\", \"doc_embedder\")\n",
        "indexing.connect(\"doc_embedder\", \"writer\")\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "j41GydA5KZhH"
      },
      "source": [
        "Let's draw the indexing pipeline"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 875
        },
        "id": "uRY6b4n3xUgP",
        "outputId": "027dd6bb-7dc2-4bb2-c591-0eeb1d2b09fd"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "indexing.draw(path=\"indexing.png\")\n",
        "Image(filename='indexing.png')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OdyNplHCIx6Q"
      },
      "source": [
        "We finally run the indexing pipeline"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 642,
          "referenced_widgets": [
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          },
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        },
        {
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              "version_minor": 0
            },
            "text/plain": [
              "Batches:   0%|          | 0/49 [00:00<?, ?it/s]"
            ]
          },
          "metadata": {},
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        },
        {
          "data": {
            "text/plain": [
              "{'writer': {'documents_written': 1554}}"
            ]
          },
          "execution_count": 9,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "indexing.run({\"cleaner\":{\"documents\":raw_docs}})"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2fKU3I7QI150"
      },
      "source": [
        "Let's inspect the total number of chunked Documents and examine a Document"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Sdm24cCyyGPg",
        "outputId": "bb325373-07c2-4d8f-d021-dccf15f64c29"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "1537"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "len(document_store.filter_documents())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "G4FQ2mCrHUWp",
        "outputId": "e5b8246c-21e2-4356-c01e-b23513c1a4fd"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{'title': 'Audioslave',\n",
              " 'url': 'https://en.wikipedia.org/wiki/Audioslave',\n",
              " 'source_id': 'e3deff3d39ef107e8b0d69415ea61644b73175086cfbeee03d5f5d6946619fcf'}"
            ]
          },
          "execution_count": 14,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "document_store.filter_documents()[0].meta"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-revytESzXct",
        "outputId": "416646fe-a098-463d-98d3-48ef388cb27e"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Document(id=3ca9785f81fb9fb0700f794b1fd2355626824599ecbce435e6f5e3babb05facc, content: 'Audioslave was an American rock supergroup formed in Glendale, California, in 2001. The four-piece b...', meta: {'title': 'Audioslave', 'url': 'https://en.wikipedia.org/wiki/Audioslave', 'source_id': 'e3deff3d39ef107e8b0d69415ea61644b73175086cfbeee03d5f5d6946619fcf'}, embedding: vector of size 1024)\n",
            "1024\n"
          ]
        }
      ],
      "source": [
        "pprint(document_store.filter_documents()[0])\n",
        "print(len(document_store.filter_documents()[0].embedding)) # embedding size"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MIl9x5WU3_yD"
      },
      "source": [
        "## The RAG Pipeline"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "p1Xuf4TgTHKz"
      },
      "source": [
        "### `TransformersChatGenerator` with `zephyr-7b-beta`\n",
        "\n",
        "- To load and manage Open Source LLMs in Haystack, we can use the `TransformersChatGenerator`.\n",
        "\n",
        "- The LLM we choose is [Zephyr 7B Beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta), a fine-tuned version of Mistral 7B V.01 that focuses on helpfulness and outperforms many larger models on the MT-Bench and AlpacaEval benchmarks; the model was fine-tuned by the Hugging Face team.\n",
        "\n",
        "- Since we are using a free Colab instance (with limited resources), we load the model using **4-bit quantization** (passing the appropriate `huggingface_pipeline_kwargs` to our Generator).\n",
        "For an introduction to Quantization in Hugging Face Transformers, you can read [this simple blog post](https://huggingface.co/blog/merve/quantization).\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "a4Qs0jAf3K82"
      },
      "outputs": [],
      "source": [
        "from transformers import BitsAndBytesConfig\n",
        "from haystack_integrations.components.generators.transformers import TransformersChatGenerator\n",
        "from haystack.dataclasses import ChatMessage"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "7EEZeWSV7ejs"
      },
      "outputs": [],
      "source": [
        "generator = TransformersChatGenerator(\"HuggingFaceH4/zephyr-7b-beta\",\n",
        "    huggingface_pipeline_kwargs={\"device_map\": \"auto\",\n",
        "        \"model_kwargs\": {\"quantization_config\": BitsAndBytesConfig(\n",
        "            load_in_4bit=True,\n",
        "            bnb_4bit_use_double_quant=True,\n",
        "            bnb_4bit_quant_type=\"nf4\",\n",
        "            bnb_4bit_compute_dtype=torch.bfloat16)}},\n",
        "    generation_kwargs={\"max_new_tokens\": 350})"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mc_6N6xJWMyf"
      },
      "source": [
        "Let's try the model..."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 268
        },
        "id": "FGaZ-c1HWlNA",
        "outputId": "3860e772-0341-4819-f22f-eee54dafc0ad"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "{\n",
              "    'replies': [\n",
              "        ChatMessage(\n",
              "            _role=<ChatRole.ASSISTANT: 'assistant'>,\n",
              "            _content=[TextContent(text=\"In sunny Italy, the land so bright,\\nWhere pasta's served with every sight,\\nThe streets are filled with laughter's light,\\nAnd love is in the air, day and night.\\n\\nThe Colosseum stands, a testament,\\nTo history's might, a story told,\\nThe Vatican's beauty, a grandament,\\nA sight that leaves one's heart so bold.\\n\\nThe rolling hills, a painter's dream,\\nThe Tuscan sun, a golden hue,\\nThe Amalfi Coast, a scene so gleam,\\nA place where love and beauty pursue.\\n\\nThe food, a symphony of flavors,\\nA feast for senses, heart and soul,\\nThe wine, a nectar, that enthralls,\\nA journey, that makes one whole.\\n\\nIn Italy, the heart beats strong,\\nA place where love and life are one,\\nA land where joy and passion throng,\\nA place where love has just begun.\")],\n",
              "            _name=None,\n",
              "            _meta={\n",
              "                'finish_reason': 'stop',\n",
              "                'index': 0,\n",
              "                'model': 'HuggingFaceH4/zephyr-7b-beta',\n",
              "                'usage': {'completion_tokens': 205, 'prompt_tokens': 24, 'total_tokens': 229}\n",
              "            }\n",
              "        )\n",
              "    ]\n",
              "}"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "# quick check\n",
        "rich.print(generator.run([ChatMessage.from_user(\"Please write a rhyme about Italy.\")]))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2xpzuCipXonU"
      },
      "source": [
        "Ok, nice!"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BDwuO18KXsOK"
      },
      "source": [
        "### `ChatPromptBuilder`\n",
        "\n",
        "It's a component that renders a list of `ChatMessage`s from a template, using the Jinja2 engine.\n",
        "\n",
        "We define a system message (instructions) and a user message (context + question). The model-specific chat template (with the right special tokens) is applied automatically by the `TransformersChatGenerator`, so we don't need to write Zephyr's special tokens (`<|system|>`, `<|user|>`, ...) by hand."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "kaU0aYEE3YmR"
      },
      "outputs": [],
      "source": [
        "from haystack.components.builders import ChatPromptBuilder\n",
        "\n",
        "prompt_template = [\n",
        "    ChatMessage.from_system(\n",
        "        \"Using the information contained in the context, give a comprehensive answer to the question.\\n\"\n",
        "        \"If the answer is contained in the context, also report the source URL.\\n\"\n",
        "        \"If the answer cannot be deduced from the context, do not give an answer.\"\n",
        "    ),\n",
        "    ChatMessage.from_user(\n",
        "        \"\"\"Context:\n",
        "  {% for doc in documents %}\n",
        "  {{ doc.content }} URL:{{ doc.meta['url'] }}\n",
        "  {% endfor %};\n",
        "  Question: {{query}}\n",
        "  \"\"\"\n",
        "    ),\n",
        "]\n",
        "prompt_builder = ChatPromptBuilder(template=prompt_template, required_variables=\"*\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zksvYdLQawH-"
      },
      "source": [
        "### Let's create the RAG pipeline"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "VdktvKPeCqk6"
      },
      "outputs": [],
      "source": [
        "from haystack.components.retrievers.in_memory import InMemoryEmbeddingRetriever"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wy0igRBObDHA"
      },
      "source": [
        "Our RAG Pipeline finds Documents relevant to the user query and pass them to the LLM to generate a grounded answer.\n",
        "\n",
        "It consists of several components:\n",
        "\n",
        "- `SentenceTransformersTextEmbedder`: represent the query as a vector (capturing its meaning).\n",
        "- `InMemoryEmbeddingRetriever`: finds the (top 5) Documents that are most similar to the query vector\n",
        "- `ChatPromptBuilder`\n",
        "- `TransformersChatGenerator`"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "TOzjzUuaCbFI"
      },
      "outputs": [],
      "source": [
        "rag = Pipeline()\n",
        "rag.add_component(\"text_embedder\", SentenceTransformersTextEmbedder(model=\"thenlper/gte-large\", \n",
        "                                                                    device=ComponentDevice.from_str(\"cuda:0\")))\n",
        "rag.add_component(\"retriever\", InMemoryEmbeddingRetriever(document_store=document_store, top_k=5))\n",
        "rag.add_component(\"prompt_builder\", prompt_builder)\n",
        "rag.add_component(\"llm\", generator)\n",
        "\n",
        "rag.connect(\"text_embedder\", \"retriever\")\n",
        "rag.connect(\"retriever.documents\", \"prompt_builder.documents\")\n",
        "rag.connect(\"prompt_builder.prompt\", \"llm.messages\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kuxOtfEUb41x"
      },
      "source": [
        "Visualize our pipeline!"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "kUTiTdMNDE8c",
        "outputId": "1425aa60-8d18-4a2b-ebc5-966556a347a9"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "rag.draw(path=\"rag.png\")\n",
        "Image(filename='rag.png')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TAXZcJfSb_dY"
      },
      "source": [
        "We create an utility function that runs the RAG pipeline and nicely prints the answer."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Y4kt0GPJDPXm"
      },
      "outputs": [],
      "source": [
        "def get_generative_answer(query):\n",
        "\n",
        "  results = rag.run({\n",
        "      \"text_embedder\": {\"text\": query},\n",
        "      \"prompt_builder\": {\"query\": query}\n",
        "    }\n",
        "  )\n",
        "\n",
        "  answer = results[\"llm\"][\"replies\"][0].text\n",
        "  rich.print(answer)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2BbF5qeocMzK"
      },
      "source": [
        "Let's try our RAG pipeline..."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
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          "base_uri": "https://localhost:8080/",
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        "id": "cYWX7sjtDqaL",
        "outputId": "3b190f0f-fa85-4236-93d7-f2068d178da8"
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      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "a038318b5fe244ae82a4e10ac41e599f",
              "version_major": 2,
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              "Batches:   0%|          | 0/1 [00:00<?, ?it/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py:1473: UserWarning: You have modified the pretrained model configuration to control generation. This is a deprecated strategy to control generation and will be removed soon, in a future version. Please use and modify the model generation configuration (see https://huggingface.co/docs/transformers/generation_strategies#default-text-generation-configuration )\n",
            "  warnings.warn(\n"
          ]
        }
      ],
      "source": [
        "get_generative_answer(\"What is the style of the Cure?\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
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        "id": "DzKtIIPxK1lN",
        "outputId": "436d6480-8bb1-4392-fa44-cbd14f291412"
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      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "e59399d1e0b94d0dafe8d4ada423983f",
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              "Batches:   0%|          | 0/1 [00:00<?, ?it/s]"
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
              "Based on the provided context, the question <span style=\"color: #008000; text-decoration-color: #008000\">\"Is the earth flat?\"</span> is not related to the information provided. \n",
              "Therefore, there is no answer to this question.\n",
              "</pre>\n"
            ],
            "text/plain": [
              "\n",
              "Based on the provided context, the question \u001b[32m\"Is the earth flat?\"\u001b[0m is not related to the information provided. \n",
              "Therefore, there is no answer to this question.\n"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "get_generative_answer(\"Is the earth flat?\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "30maVB75o1rS"
      },
      "source": [
        "More questions to try..."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "K823m5LTGjK1"
      },
      "outputs": [],
      "source": [
        "nice_questions_to_try=\"\"\"What was the original name of Sum 41?\n",
        "What was the title of Nirvana's breakthrough album released in 1991?\n",
        "Green Day's \"American Idiot\" is a rock opera. What's the story it tells?\n",
        "What is the most well-known album by Blink-182?\n",
        "Audioslave was formed by members of two iconic bands. Can you name the bands and discuss the sound of Audioslave in comparison?\n",
        "Evanescence's \"Bring Me to Life\" features a male vocalist. Who is he, and how does his voice complement Amy Lee's in the song?\n",
        "Was Ozzy Osbourne part of Blink 182?\n",
        "Dire Straits' \"Sultans of Swing\" is a classic rock track. How does Mark Knopfler's guitar work in this song stand out to you?\n",
        "What is Sum 41's debut studio album called?\n",
        "Which member of Muse is the lead vocalist and primary songwriter?\n",
        "Who was the lead singer of Audioslave?\n",
        "Who are the members of Green Day?\n",
        "When was Nirvana's first studio album, \"Bleach,\" released?\n",
        "Were the Smiths an influential band?\n",
        "What is the name of Evanescence's debut album?\n",
        "Which band was Morrissey the lead singer of before he formed The Smiths?\n",
        "What is the title of The Cure's most famous and successful album?\n",
        "Dire Straits' hit song \"Money for Nothing\" features a guest vocal by a famous artist. Who is this artist?\n",
        "Who played the song \"Like a stone\"?\"\"\".split('\\n')"
      ]
    },
    {
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        },
        "id": "FEMCBqjtCYi2",
        "outputId": "c6f5b4db-61f0-4581-c0fe-6525a30b076e"
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      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Who are the members of Green Day?\n"
          ]
        },
        {
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              "Batches:   0%|          | 0/1 [00:00<?, ?it/s]"
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
              "The members of Green Day, as stated in the context provided, are lead vocalist and guitarist Billie Joe Armstrong, \n",
              "bassist and backing vocalist Mike Dirnt, and drummer Tré Cool, who replaced John Kiffmeyer in <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1990</span> before the \n",
              "recording of the band's second studio album, Kerplunk <span style=\"font-weight: bold\">(</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1991</span><span style=\"font-weight: bold\">)</span>. This information can be found on the following URLs: \n",
              "A.R., S.O., O.A., and the main Wikipedia page for Green Day, which is also provided in the context.\n",
              "</pre>\n"
            ],
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              "\n",
              "The members of Green Day, as stated in the context provided, are lead vocalist and guitarist Billie Joe Armstrong, \n",
              "bassist and backing vocalist Mike Dirnt, and drummer Tré Cool, who replaced John Kiffmeyer in \u001b[1;36m1990\u001b[0m before the \n",
              "recording of the band's second studio album, Kerplunk \u001b[1m(\u001b[0m\u001b[1;36m1991\u001b[0m\u001b[1m)\u001b[0m. This information can be found on the following URLs: \n",
              "A.R., S.O., O.A., and the main Wikipedia page for Green Day, which is also provided in the context.\n"
            ]
          },
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      ],
      "source": [
        "q=random.choice(nice_questions_to_try)\n",
        "print(q)\n",
        "get_generative_answer(q)"
      ]
    },
    {
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          "text": [
            "Was Ozzy Osbourne part of Blink 182?\n"
          ]
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              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
              "Based on the context provided, Ozzy Osbourne was not part of Blink <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">182</span>. The information provided only details the \n",
              "history and current lineup of the band, and there is no mention of Ozzy Osbourne being a member at any point in \n",
              "time.\n",
              "\n",
              "Source URL: <span style=\"color: #0000ff; text-decoration-color: #0000ff; text-decoration: underline\">https://en.wikipedia.org/wiki/Blink-182</span>\n",
              "\n",
              "Question: Was Ozzy Osbourne part of Blink <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">182</span>?\n",
              "\n",
              "Answer: No, Ozzy Osbourne was not part of Blink <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">182</span>.\n",
              "</pre>\n"
            ],
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              "\n",
              "Based on the context provided, Ozzy Osbourne was not part of Blink \u001b[1;36m182\u001b[0m. The information provided only details the \n",
              "history and current lineup of the band, and there is no mention of Ozzy Osbourne being a member at any point in \n",
              "time.\n",
              "\n",
              "Source URL: \u001b[4;94mhttps://en.wikipedia.org/wiki/Blink-182\u001b[0m\n",
              "\n",
              "Question: Was Ozzy Osbourne part of Blink \u001b[1;36m182\u001b[0m?\n",
              "\n",
              "Answer: No, Ozzy Osbourne was not part of Blink \u001b[1;36m182\u001b[0m.\n"
            ]
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      "source": [
        "q=random.choice(nice_questions_to_try)\n",
        "print(q)\n",
        "get_generative_answer(q)"
      ]
    }
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