{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PwkLlhmsoqnB"
   },
   "source": [
    "# Advanced RAG: Query Expansion\n",
    "_by Tuana Celik ([LI](https://www.linkedin.com/in/tuanacelik/),  [Twitter/X](https://x.com/tuanacelik))_\n",
    "\n",
    "> This is part one of the **Advanced Use Cases** series:\n",
    ">\n",
    "> 1️⃣ Extract Metadata from Queries to Improve Retrieval [cookbook](/cookbook/extracting_metadata_filters_from_a_user_query) & [full article](/blog/extracting-metadata-filter)\n",
    ">\n",
    "> 2️⃣ **Query Expansion & the [full article](/blog/query-expansion)**\n",
    ">\n",
    "> 3️⃣ Query Decomposition [cookbook](/cookbook/query_decomposition) & [full article](/blog/query-decomposition)\n",
    ">\n",
    "> 4️⃣ [Automated Metadata Enrichment](/cookbook/metadata_enrichment)\n",
    "\n",
    "In this cookbook, you'll learn how to implement query expansion for RAG. Query expansion consists of asking an LLM to produce a number of similar queries to a user query. We are then able to use each of these queries in the retrieval process, increasing the number and relevance of retrieved documents.\n",
    "\n",
    "📚 [Read the full article](https://haystack.deepset.ai/blog/query-expansion)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "JOJ-QAgRTf98",
    "outputId": "240f2beb-3121-41e4-b3f4-ad8c226e71b0",
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "!pip install haystack-ai wikipedia"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "id": "yrVx-gYoYf6Q"
   },
   "outputs": [],
   "source": [
    "import wikipedia\n",
    "import json\n",
    "\n",
    "from typing import List, Optional\n",
    "from haystack import Pipeline, component\n",
    "\n",
    "from haystack.components.builders import ChatPromptBuilder\n",
    "from haystack.components.generators.chat import OpenAIChatGenerator\n",
    "from haystack.components.preprocessors import DocumentCleaner, DocumentSplitter\n",
    "from haystack.components.retrievers import InMemoryBM25Retriever\n",
    "from haystack.components.writers import DocumentWriter\n",
    "\n",
    "from haystack.dataclasses import ChatMessage, Document\n",
    "\n",
    "from haystack.document_stores.in_memory import InMemoryDocumentStore\n",
    "from haystack.document_stores.types import DuplicatePolicy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "_SUCwtYcXDgA",
    "outputId": "eeebb0f7-5754-4d54-95bb-255971bf1e15"
   },
   "outputs": [],
   "source": [
    "import os\n",
    "from getpass import getpass\n",
    "\n",
    "if \"OPENAI_API_KEY\" not in os.environ:\n",
    "  os.environ['OPENAI_API_KEY'] = getpass(\"Your OpenAI API Key: \")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "j4gDkMDCsbpQ"
   },
   "source": [
    "## The Process of Query Expansion\n",
    "\n",
    "First, let's import the `QueryExpander` from **Haystack Experimental**.\n",
    "\n",
    "Next, we’ll create a `QueryExpander` instance. This component generates a specified number (default is 4) of additional queries that are similar to the original user query. It returns `queries`, which include the original query plus the generated similar ones."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "id": "qM5tZEnATjeN"
   },
   "outputs": [],
   "source": [
    "from haystack_experimental.components.query.query_expander import QueryExpander"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "hHrfU-UeTmEw",
    "outputId": "6f71c534-5e73-48f4-eb54-5facf2a4afcd"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'queries': ['natural language processing tools',\n",
       "  'free nlp libraries',\n",
       "  'open-source NLP platforms',\n",
       "  'public domain language processing frameworks',\n",
       "  'open source nlp frameworks']}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "expander = QueryExpander()\n",
    "expander.run(query=\"open source nlp frameworks\", n_expansions=4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "gsADarYUvurh"
   },
   "source": [
    "## Retrieval Without Query Expansion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "id": "slZF_6sgTp2U"
   },
   "outputs": [],
   "source": [
    "documents = [\n",
    "    Document(content=\"The effects of climate are many including loss of biodiversity\"),\n",
    "    Document(content=\"The impact of climate change is evident in the melting of the polar ice caps.\"),\n",
    "    Document(content=\"Consequences of global warming include the rise in sea levels.\"),\n",
    "    Document(content=\"One of the effects of environmental changes is the change in weather patterns.\"),\n",
    "    Document(content=\"There is a global call to reduce the amount of air travel people take.\"),\n",
    "    Document(content=\"Air travel is one of the core contributors to climate change.\"),\n",
    "    Document(content=\"Expect warm climates in Turkey during the summer period.\"),\n",
    "]\n",
    "\n",
    "doc_store = InMemoryDocumentStore(embedding_similarity_function=\"cosine\")\n",
    "doc_store.write_documents(documents)\n",
    "\n",
    "retriever = InMemoryBM25Retriever(document_store=doc_store, top_k=3)\n",
    "\n",
    "retrieval_pipeline = Pipeline()\n",
    "retrieval_pipeline.add_component(\"keyword_retriever\", retriever)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "8j6a-BL9oI8E",
    "outputId": "3626d26f-a640-470a-d964-b083051c97ad"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'keyword_retriever': {'documents': [Document(id=8b306c8303c59508a53e5139b4e688c3817fa0211b095bcc77ab3823defa0b32, content: 'Air travel is one of the core contributors to climate change.', score: 2.023895027544814),\n",
       "   Document(id=aa996058ca5b30d8b469d33e992e094058e707bfb0cf057ee1d5b55ac4320234, content: 'The impact of climate change is evident in the melting of the polar ice caps.', score: 1.8661960327485192),\n",
       "   Document(id=4d5f7ef8df12c93cb5728cc0247bf95282a14017ce9d0b35486091f8972347a5, content: 'The effects of climate are many including loss of biodiversity', score: 1.5532314806726806)]}}"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "query = \"climate change\"\n",
    "retrieval_pipeline.run({\"keyword_retriever\":{ \"query\": query, \"top_k\": 3}})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ZpJ0juxX0J-B"
   },
   "source": [
    "## Retrieval With Query Expansion\n",
    "\n",
    "Now let's have a look at what documents we are able to retrieve if we are to inluce query expansion in the process. For this step, let's create a `MultiQueryInMemoryBM25Retriever` that is able to use BM25 retrieval for each (expansded) query in turn.\n",
    "\n",
    "This component also handles the same document being retrieved for multiple queries and will not return duplicates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "id": "6zZrkocErf3N"
   },
   "outputs": [],
   "source": [
    "@component\n",
    "class MultiQueryInMemoryBM25Retriever:\n",
    "\n",
    "    def __init__(self, retriever: InMemoryBM25Retriever, top_k: int = 3):\n",
    "        self.retriever = retriever\n",
    "        self.top_k = top_k\n",
    "\n",
    "    @component.output_types(documents=List[Document])\n",
    "    def run(self, queries: List[str], top_k: int = None):\n",
    "        if top_k != None:\n",
    "            self.top_k = top_k\n",
    "\n",
    "        all_docs = {}\n",
    "        for query in queries:\n",
    "            result = self.retriever.run(query = query, top_k = self.top_k)\n",
    "            for doc in result['documents']:\n",
    "                all_docs[doc.id] = doc\n",
    "\n",
    "        all_docs = list(all_docs.values())\n",
    "        all_docs.sort(key=lambda x: x.score, reverse=True)\n",
    "        return {\"documents\": all_docs}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "EhL3bQTFoWDK",
    "outputId": "f6f51241-db88-4467-b534-ce9c7e40a0d7"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<haystack.core.pipeline.pipeline.Pipeline object at 0x10b2e9c10>\n",
       "🚅 Components\n",
       "  - expander: QueryExpander\n",
       "  - keyword_retriever: MultiQueryInMemoryBM25Retriever\n",
       "🛤️ Connections\n",
       "  - expander.queries -> keyword_retriever.queries (List[str])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "query_expander = QueryExpander()\n",
    "retriever = MultiQueryInMemoryBM25Retriever(InMemoryBM25Retriever(document_store=doc_store))\n",
    "\n",
    "expanded_retrieval_pipeline = Pipeline()\n",
    "expanded_retrieval_pipeline.add_component(\"expander\", query_expander)\n",
    "expanded_retrieval_pipeline.add_component(\"keyword_retriever\", retriever)\n",
    "\n",
    "expanded_retrieval_pipeline.connect(\"expander.queries\", \"keyword_retriever.queries\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "FJXF9nHYsym0",
    "outputId": "f6f2fc33-d6ec-4bca-f2ae-07fdc20f6d31"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'expander': {'queries': ['global warming',\n",
       "   'environmental climate shifts',\n",
       "   \"changes in Earth's climate\",\n",
       "   'effects of climate variability',\n",
       "   'climate change']},\n",
       " 'keyword_retriever': {'documents': [Document(id=0901b034998c7263f74ac60cad5d9d520df524e59b045f3afab8e6cf1710791d, content: 'Consequences of global warming include the rise in sea levels.', score: 3.5574227469366644),\n",
       "   Document(id=40fcd5a4a3670b7e105db664783c076167bb699cade9aa7fd6d409fac2efb49e, content: 'There is a global call to reduce the amount of air travel people take.', score: 2.409793821666657),\n",
       "   Document(id=395d2da61fff546098eec2838da741033d71fef84dfa7a91fc40b1d275631933, content: 'One of the effects of environmental changes is the change in weather patterns.', score: 2.185936012403085),\n",
       "   Document(id=8b306c8303c59508a53e5139b4e688c3817fa0211b095bcc77ab3823defa0b32, content: 'Air travel is one of the core contributors to climate change.', score: 2.023895027544814),\n",
       "   Document(id=aa996058ca5b30d8b469d33e992e094058e707bfb0cf057ee1d5b55ac4320234, content: 'The impact of climate change is evident in the melting of the polar ice caps.', score: 1.8661960327485192),\n",
       "   Document(id=4d5f7ef8df12c93cb5728cc0247bf95282a14017ce9d0b35486091f8972347a5, content: 'The effects of climate are many including loss of biodiversity', score: 1.5532314806726806)]}}"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "expanded_retrieval_pipeline.run({\"expander\": {\"query\": query}}, include_outputs_from=[\"expander\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TYwbeS1-zIt5"
   },
   "source": [
    "## Query Expansion for RAG\n",
    "\n",
    "Let's start off by populating a document store with chunks of context from various Wikipedia pages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "id": "zSxqDIoKvUih"
   },
   "outputs": [],
   "source": [
    "def get_doc_store():\n",
    "    raw_docs = []\n",
    "    wikipedia_page_titles = [\"Electric_vehicle\", \"Dam\", \"Electric_battery\", \"Tree\", \"Solar_panel\", \"Nuclear_power\",\n",
    "                             \"Wind_power\", \"Hydroelectricity\", \"Coal\", \"Natural_gas\", \"Greenhouse_gas\", \"Renewable_energy\",\n",
    "                             \"Fossil_fuel\"]\n",
    "    for title in wikipedia_page_titles:\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)\n",
    "\n",
    "    doc_store = InMemoryDocumentStore(embedding_similarity_function=\"cosine\")\n",
    "\n",
    "    indexing_pipeline = Pipeline()\n",
    "    indexing_pipeline.add_component(\"cleaner\", DocumentCleaner())\n",
    "    indexing_pipeline.add_component(\"splitter\", DocumentSplitter(split_by=\"passage\", split_length=1))\n",
    "    indexing_pipeline.add_component(\"writer\", DocumentWriter(document_store=doc_store, policy=DuplicatePolicy.SKIP))\n",
    "    indexing_pipeline.connect(\"cleaner\", \"splitter\")\n",
    "    indexing_pipeline.connect(\"splitter\", \"writer\")\n",
    "\n",
    "    indexing_pipeline.run({\"cleaner\": {\"documents\": raw_docs}})\n",
    "\n",
    "    return doc_store"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "id": "Ab7JL71ejhO5"
   },
   "outputs": [],
   "source": [
    "doc_store = get_doc_store()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "oR-lZeyrzY3M"
   },
   "source": [
    "### RAG without Query Expansion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "erV3yIS5n9GE",
    "outputId": "788c89b6-b603-4000-fb7c-b2bd4573e01f"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<haystack.core.pipeline.pipeline.Pipeline object at 0x10c433a50>\n",
       "🚅 Components\n",
       "  - keyword_retriever: InMemoryBM25Retriever\n",
       "  - chat_prompt_builder: ChatPromptBuilder\n",
       "  - llm: OpenAIChatGenerator\n",
       "🛤️ Connections\n",
       "  - keyword_retriever.documents -> chat_prompt_builder.documents (List[Document])\n",
       "  - chat_prompt_builder.prompt -> llm.messages (List[ChatMessage])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat_message = ChatMessage.from_user(\n",
    "    text=\"\"\"You are part of an information system that summarises related documents.\n",
    "You answer a query using the textual content from the documents retrieved for the\n",
    "following query.\n",
    "You build the summary answer based only on quoting information from the documents.\n",
    "You should reference the documents you used to support your answer.\n",
    "###\n",
    "Original Query: \"{{query}}\"\n",
    "Retrieved Documents: {{documents}}\n",
    "Summary Answer:\n",
    "\"\"\"\n",
    ")\n",
    "retriever = InMemoryBM25Retriever(document_store=doc_store)\n",
    "chat_prompt_builder = ChatPromptBuilder(template=[chat_message], required_variables=\"*\")\n",
    "llm = OpenAIChatGenerator()\n",
    "\n",
    "keyword_rag_pipeline = Pipeline()\n",
    "keyword_rag_pipeline.add_component(\"keyword_retriever\", retriever)\n",
    "keyword_rag_pipeline.add_component(\"chat_prompt_builder\", chat_prompt_builder)\n",
    "keyword_rag_pipeline.add_component(\"llm\", llm)\n",
    "\n",
    "keyword_rag_pipeline.connect(\"keyword_retriever.documents\", \"chat_prompt_builder.documents\")\n",
    "keyword_rag_pipeline.connect(\"chat_prompt_builder.prompt\", \"llm.messages\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "UD03G6MQoDhV",
    "outputId": "10dc9b16-4d13-455b-f5a6-e09b97c9d835"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'keyword_retriever': {'documents': [Document(id=b5544970917394145729c23e6447d57ca42aad99fd68d17641682b4726b326b5, content: 'Renewable energy (also called green energy) is energy made from renewable natural resources that are...', meta: {'title': 'Renewable energy', 'url': 'https://en.wikipedia.org/wiki/Renewable_energy', 'source_id': '2089cf2a38231b23fe28c73d1b8c847fdb84190acf6ea60fac87c733fad5694d', 'page_number': 1, 'split_id': 0, 'split_idx_start': 0}, score: 2.5931591814370085),\n",
       "   Document(id=30a6ac048f1c1b62b11b64b08bc62a416e26751a0209718426970a03279aa4f0, content: 'Wind power is the use of wind energy to generate useful work. Historically, wind power was used by s...', meta: {'title': 'Wind power', 'url': 'https://en.wikipedia.org/wiki/Wind_power', 'source_id': 'bf171fa3a08865668abc6b95bfa89aeeef6520aa05263e2c3166121553262c41', 'page_number': 1, 'split_id': 0, 'split_idx_start': 0}, score: 2.1698503702912926),\n",
       "   Document(id=6111c991130070bb618386d1028eaabe822aacec6c6d971570856a7e6f74240c, content: 'A fossil fuel is a flammable carbon compound- or hydrocarbon-containing material formed naturally in...', meta: {'title': 'Fossil fuel', 'url': 'https://en.wikipedia.org/wiki/Fossil_fuel', 'source_id': '518ec040573081a250fa14f8696301f2a7ea3fc3be40ad3f561c927fd5b8a8a3', 'page_number': 1, 'split_id': 0, 'split_idx_start': 0}, score: 1.9462904069647091)]},\n",
       " 'llm': {'replies': [ChatMessage(_role=<ChatRole.ASSISTANT: 'assistant'>, _content=[TextContent(text='Green energy sources refer to renewable energy, which is \"energy made from renewable natural resources\" (Document: [Renewable energy](https://en.wikipedia.org/wiki/Renewable_energy)). One notable example of a green energy source is wind power, which is utilized to generate useful work from wind energy (Document: [Wind power](https://en.wikipedia.org/wiki/Wind_power)). In contrast, fossil fuels, which are non-renewable and consist of flammable carbon compounds, represent a different category of energy source (Document: [Fossil fuel](https://en.wikipedia.org/wiki/Fossil_fuel)).')], _name=None, _meta={'model': 'gpt-4o-mini-2024-07-18', 'index': 0, 'finish_reason': 'stop', 'usage': {'completion_tokens': 125, 'prompt_tokens': 563, 'total_tokens': 688, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}})]}}"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "keyword_rag_pipeline.run({\"query\": \"green energy sources\", \"top_k\": 3}, include_outputs_from=[\"keyword_retriever\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MRx9_9pzzcxo"
   },
   "source": [
    "### RAG with Query Expansion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "gA6-RvHdn8pT",
    "outputId": "7ba03184-cba0-4882-cae3-4909eeea6a6a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<haystack.core.pipeline.pipeline.Pipeline object at 0x10c2c1710>\n",
       "🚅 Components\n",
       "  - expander: QueryExpander\n",
       "  - keyword_retriever: MultiQueryInMemoryBM25Retriever\n",
       "  - chat_prompt_builder: ChatPromptBuilder\n",
       "  - llm: OpenAIChatGenerator\n",
       "🛤️ Connections\n",
       "  - expander.queries -> keyword_retriever.queries (List[str])\n",
       "  - keyword_retriever.documents -> chat_prompt_builder.documents (List[Document])\n",
       "  - chat_prompt_builder.prompt -> llm.messages (List[ChatMessage])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat_message = ChatMessage.from_user(\n",
    "    text=\"\"\"You are part of an information system that summarises related documents.\n",
    "You answer a query using the textual content from the documents retrieved for the\n",
    "following query.\n",
    "You build the summary answer based only on quoting information from the documents.\n",
    "You should reference the documents you used to support your answer.\n",
    "###\n",
    "Original Query: \"{{query}}\"\n",
    "Retrieved Documents: {{documents}}\n",
    "Summary Answer:\n",
    "\"\"\"\n",
    ")\n",
    "query_expander = QueryExpander()\n",
    "retriever = MultiQueryInMemoryBM25Retriever(InMemoryBM25Retriever(document_store=doc_store))\n",
    "chat_prompt_builder = ChatPromptBuilder(template=[chat_message], required_variables=\"*\")\n",
    "llm = OpenAIChatGenerator()\n",
    "\n",
    "query_expanded_rag_pipeline = Pipeline()\n",
    "query_expanded_rag_pipeline.add_component(\"expander\", query_expander)\n",
    "query_expanded_rag_pipeline.add_component(\"keyword_retriever\", retriever)\n",
    "query_expanded_rag_pipeline.add_component(\"chat_prompt_builder\", chat_prompt_builder)\n",
    "query_expanded_rag_pipeline.add_component(\"llm\", llm)\n",
    "\n",
    "query_expanded_rag_pipeline.connect(\"expander.queries\", \"keyword_retriever.queries\")\n",
    "query_expanded_rag_pipeline.connect(\"keyword_retriever.documents\", \"chat_prompt_builder.documents\")\n",
    "query_expanded_rag_pipeline.connect(\"chat_prompt_builder.prompt\", \"llm.messages\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "OPgfePQw6SGn",
    "outputId": "d7231d48-ef64-4a8e-ab45-bcfc2ff15936"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "query_expanded_rag_pipeline.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "qfdrTpZijsnv",
    "outputId": "e22e6e34-1f06-4c7f-8bd7-473dc3654542"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'expander': {'queries': ['renewable energy sources',\n",
       "   'sustainable power generation',\n",
       "   'eco-friendly energy options',\n",
       "   'clean energy resources',\n",
       "   'green energy sources']},\n",
       " 'keyword_retriever': {'documents': [Document(id=bc480a9fbfd7d1e9bbd2deb6f714b6533a62673064f6d015b674b9121e128f67, content: 'An electric battery is a source of electric power consisting of one or more electrochemical cells wi...', meta: {'title': 'Electric battery', 'url': 'https://en.wikipedia.org/wiki/Electric_battery', 'source_id': '03300aed831e8407b7c7db4d7ead042d2c1c6858133809b03424185910318241', 'page_number': 1, 'split_id': 0, 'split_idx_start': 0}, score: 4.3266776407237),\n",
       "   Document(id=219c74b79bdebd2288deb0846466baa963cc685d90b824f91d2e3c1b9788aec5, content: 'An electric vehicle (EV) is a motor vehicle whose propulsion is powered fully or mostly by electrici...', meta: {'title': 'Electric vehicle', 'url': 'https://en.wikipedia.org/wiki/Electric_vehicle', 'source_id': '3f37bb285d46a2d30be6f670e4ad22ee6f99088f031768f32cd63ffd08b468f6', 'page_number': 1, 'split_id': 0, 'split_idx_start': 0}, score: 4.125736125230999),\n",
       "   Document(id=8a0c9682962456496887522a3ec9552057a67f7166ef50b311a3adc038ed58af, content: 'Nuclear power is the use of nuclear reactions to produce electricity. Nuclear power can be obtained ...', meta: {'title': 'Nuclear power', 'url': 'https://en.wikipedia.org/wiki/Nuclear_power', 'source_id': 'fad4070db55e2e0028d5eaf097b2ab15945c08653a321eaf4ab28668b998553f', 'page_number': 1, 'split_id': 0, 'split_idx_start': 0}, score: 2.640043921499558),\n",
       "   Document(id=b5544970917394145729c23e6447d57ca42aad99fd68d17641682b4726b326b5, content: 'Renewable energy (also called green energy) is energy made from renewable natural resources that are...', meta: {'title': 'Renewable energy', 'url': 'https://en.wikipedia.org/wiki/Renewable_energy', 'source_id': '2089cf2a38231b23fe28c73d1b8c847fdb84190acf6ea60fac87c733fad5694d', 'page_number': 1, 'split_id': 0, 'split_idx_start': 0}, score: 2.5931591814370085),\n",
       "   Document(id=30a6ac048f1c1b62b11b64b08bc62a416e26751a0209718426970a03279aa4f0, content: 'Wind power is the use of wind energy to generate useful work. Historically, wind power was used by s...', meta: {'title': 'Wind power', 'url': 'https://en.wikipedia.org/wiki/Wind_power', 'source_id': 'bf171fa3a08865668abc6b95bfa89aeeef6520aa05263e2c3166121553262c41', 'page_number': 1, 'split_id': 0, 'split_idx_start': 0}, score: 2.1698503702912926),\n",
       "   Document(id=6111c991130070bb618386d1028eaabe822aacec6c6d971570856a7e6f74240c, content: 'A fossil fuel is a flammable carbon compound- or hydrocarbon-containing material formed naturally in...', meta: {'title': 'Fossil fuel', 'url': 'https://en.wikipedia.org/wiki/Fossil_fuel', 'source_id': '518ec040573081a250fa14f8696301f2a7ea3fc3be40ad3f561c927fd5b8a8a3', 'page_number': 1, 'split_id': 0, 'split_idx_start': 0}, score: 1.9462904069647091),\n",
       "   Document(id=d726f9d1598e52a199ad3949700e1bc68de4d60d0a11a1c78fd6eae44f906458, content: 'Coal is a combustible black or brownish-black sedimentary rock, formed as rock strata called coal se...', meta: {'title': 'Coal', 'url': 'https://en.wikipedia.org/wiki/Coal', 'source_id': 'cdd0037a9e7d1d67721f1cf1a598b01a6d3a35780dc1a9211215a8a6636fb0d4', 'page_number': 1, 'split_id': 0, 'split_idx_start': 0}, score: 1.321711298057089)]},\n",
       " 'llm': {'replies': [ChatMessage(_role=<ChatRole.ASSISTANT: 'assistant'>, _content=[TextContent(text='Green energy sources refer to renewable energy that is derived from natural resources which are replenished over time. As stated, \"Renewable energy (also called green energy) is energy made from renewable natural resources that are...\" (Document: [Renewable energy](https://en.wikipedia.org/wiki/Renewable_energy)). \\n\\nAdditionally, specific examples of green energy sources include wind power, which \"is the use of wind energy to generate useful work\" (Document: [Wind power](https://en.wikipedia.org/wiki/Wind_power)). Other green energy sources may include solar power, hydroelectric power, and geothermal energy, although these were not directly mentioned in the retrieved documents.\\n\\nPlease refer to the detailed article on renewable energy for more comprehensive insights (source: [Renewable energy](https://en.wikipedia.org/wiki/Renewable_energy)).')], _name=None, _meta={'model': 'gpt-4o-mini-2024-07-18', 'index': 0, 'finish_reason': 'stop', 'usage': {'completion_tokens': 167, 'prompt_tokens': 1212, 'total_tokens': 1379, 'completion_tokens_details': {'accepted_prediction_tokens': 0, 'audio_tokens': 0, 'reasoning_tokens': 0, 'rejected_prediction_tokens': 0}, 'prompt_tokens_details': {'audio_tokens': 0, 'cached_tokens': 0}}})]}}"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "query_expanded_rag_pipeline.run({\"query\": \"green energy sources\", \"top_k\": 3}, include_outputs_from=[\"keyword_retriever\", \"expander\"])"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "nbconvert_exporter": "python",
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