examples/rag/langgraph_crag_mistral.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "19969669-b47f-47f3-b6d4-f7b155434840",
   "metadata": {},
   "outputs": [],
   "source": [
    "! pip install --quiet langchain_community tiktoken langchain-openai langchainhub chromadb langchain langgraph tavily-python langchain-mistralai gpt4all llama-cpp-python"
   ]
  },
  {
   "attachments": {
    "a65940f9-5c51-4d7c-9ca1-ae576e4bb51a.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "id": "92ddc4f4-f7bf-4e0e-b5a5-5abd8a008b21",
   "metadata": {},
   "source": [
    "# Corrective RAG\n",
    "\n",
    "Self-reflection can enhance RAG, enabling correction of poor quality retrieval or generations.\n",
    "\n",
    "Several recent papers focus on this theme, but implementing the ideas can be tricky.\n",
    "\n",
    "Here we show how to implement self-reflective RAG using `Mistral` and `LangGraph`.\n",
    "\n",
    "We'll focus on ideas from one paper, `Corrective RAG (CRAG)` [here](https://arxiv.org/pdf/2401.15884.pdf).\n",
    "\n",
    "![Screenshot 2024-02-07 at 1.21.51 PM.png](attachment:a65940f9-5c51-4d7c-9ca1-ae576e4bb51a.png)\n",
    "\n",
    "## Setup\n",
    "\n",
    "### Using APIs \n",
    "\n",
    "* Set `MISTRAL_API_KEY` and set up Subscription to activate it.\n",
    "* Set `TAVILY_API_KEY` to enable web search [here](https://app.tavily.com/sign-in).\n",
    "\n",
    "### Using CoLab \n",
    "\n",
    "* [Here](https://colab.research.google.com/drive/1U5OcwWjoXZSud30q4XOk1UlIJNjaD3kX?usp=sharing) is a link to a CoLab for this notebook. \n",
    "\n",
    "### Running Locally \n",
    "\n",
    "#### Embeddings\n",
    "\n",
    "There are several options for local embeddings.\n",
    "\n",
    "(1) You can use `GPT4AllEmbeddings()` from Nomic.\n",
    "\n",
    "(2) You can also use Nomic's recently released [v1](https://blog.nomic.ai/posts/nomic-embed-text-v1) and [v1.5](https://blog.nomic.ai/posts/nomic-embed-matryoshka) embeddings.\n",
    "\n",
    "For these, simply:\n",
    "\n",
    "Clone [`llama.cpp`](https://github.com/ggerganov/llama.cpp):\n",
    "\n",
    "```\n",
    "git clone https://github.com/ggerganov/llama.cpp\n",
    "```\n",
    "\n",
    "Download GGUF weights for Nomic's embedding model(s), allowing them to be run locally: \n",
    "\n",
    "* https://huggingface.co/nomic-ai/nomic-embed-text-v1-GGUF\n",
    "* https://huggingface.co/nomic-ai/nomic-embed-text-v1.5-GGUF\n",
    "\n",
    "Add to `llama.cpp/model` directory.\n",
    "\n",
    "Build llama.cpp:\n",
    "```\n",
    "cd llama.cpp\n",
    "make\n",
    "```\n",
    "\n",
    "### LLM\n",
    "\n",
    "(1) Download [Ollama app](https://ollama.ai/).\n",
    "\n",
    "(2) Download a `Mistral` model from various Mistral versions [here](https://ollama.ai/library/mistral) and Mixtral versions [here](https://ollama.ai/library/mixtral) available.\n",
    "```\n",
    "ollama pull mistral:instruct\n",
    "```\n",
    "\n",
    "### Tracing \n",
    "\n",
    "* Optionally, use [LangSmith](https://docs.smith.langchain.com/) for tracing (shown at bottom) by setting: \n",
    "\n",
    "```\n",
    "export LANGCHAIN_TRACING_V2=true\n",
    "export LANGCHAIN_ENDPOINT=https://api.smith.langchain.com\n",
    "export LANGCHAIN_API_KEY=<your-api-key>\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "abc064ab-7de1-4d03-a987-cd3078438d61",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Check API keys\n",
    "import os\n",
    "\n",
    "mistral_api_key = os.environ.get(\"MISTRAL_API_KEY\")\n",
    "tavily_api_key = os.environ.get(\"TAVILY_API_KEY\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9f644869-436e-4bf6-a267-b2465c7b5aef",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Flags for running locally\n",
    "\n",
    "run_local = \"Yes\"\n",
    "local_llm = \"mistral:instruct\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e2b6eed-3b3f-44b5-a34a-4ade1e94caf0",
   "metadata": {},
   "source": [
    "## Indexing\n",
    "\n",
    "First, let's index a popular blog post on agents. \n",
    "\n",
    "We can use [Mistral embeddings](https://python.langchain.com/docs/integrations/text_embedding/mistralai).\n",
    "\n",
    "For local, we can use [GPT4All](https://python.langchain.com/docs/integrations/text_embedding/gpt4all), which is a CPU optimized SBERT model [here](https://docs.gpt4all.io/gpt4all_python_embedding.html).\n",
    "\n",
    "We'll use a local vectorstore, [Chroma](https://python.langchain.com/docs/integrations/vectorstores/chroma)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "254ae533-79e0-42f4-b200-1ec9160e1d3d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "bert_load_from_file: gguf version     = 2\n",
      "bert_load_from_file: gguf alignment   = 32\n",
      "bert_load_from_file: gguf data offset = 695552\n",
      "bert_load_from_file: model name           = BERT\n",
      "bert_load_from_file: model architecture   = bert\n",
      "bert_load_from_file: model file type      = 1\n",
      "bert_load_from_file: bert tokenizer vocab = 30522\n"
     ]
    }
   ],
   "source": [
    "from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
    "from langchain_community.document_loaders import WebBaseLoader\n",
    "from langchain_community.vectorstores import Chroma\n",
    "from langchain_mistralai import MistralAIEmbeddings\n",
    "from langchain_community.embeddings import GPT4AllEmbeddings\n",
    "from langchain_community.embeddings import LlamaCppEmbeddings\n",
    "\n",
    "# Load\n",
    "url = \"https://lilianweng.github.io/posts/2023-06-23-agent/\"\n",
    "loader = WebBaseLoader(url)\n",
    "docs = loader.load()\n",
    "\n",
    "# Split\n",
    "text_splitter = RecursiveCharacterTextSplitter.from_tiktoken_encoder(\n",
    "    chunk_size=500, chunk_overlap=100\n",
    ")\n",
    "all_splits = text_splitter.split_documents(docs)\n",
    "\n",
    "# Embed and index\n",
    "if run_local == \"Yes\":\n",
    "    # GPT4All\n",
    "    embedding = GPT4AllEmbeddings()\n",
    "    # Nomic v1 or v1.5\n",
    "    # embd_model_path = \"/Users/rlm/Desktop/Code/llama.cpp/models/nomic-embd/nomic-embed-text-v1.Q4_K_S.gguf\"\n",
    "    # embedding = LlamaCppEmbeddings(model_path=embd_model_path, n_batch=512)\n",
    "else:\n",
    "    embedding = MistralAIEmbeddings(mistral_api_key=mistral_api_key)\n",
    "\n",
    "# Index\n",
    "vectorstore = Chroma.from_documents(\n",
    "    documents=all_splits,\n",
    "    collection_name=\"rag-chroma\",\n",
    "    embedding=embedding,\n",
    ")\n",
    "retriever = vectorstore.as_retriever()"
   ]
  },
  {
   "attachments": {
    "a2fac558-b18e-4610-bfa7-0d40c92e0ede.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "id": "fe7fd10a-f64a-48de-a116-6d5890def1af",
   "metadata": {},
   "source": [
    "## Corrective RAG\n",
    "\n",
    "Let's implement self-reflective RAG with some ideas from the CRAG (Corrective RAG) [paper](https://arxiv.org/pdf/2401.15884.pdf):\n",
    "\n",
    "* Grade documents for relevance relative to the question.\n",
    "* If any are irrelevant, then we will supplement the context used for generation with web search.\n",
    "* For web search, we will re-phrase the question and use Tavily API.\n",
    "* We will then pass retrieved documents and web results to an LLM for final answer generation.\n",
    "\n",
    "Here is a schematic of our graph in more detail:\n",
    "\n",
    "![crag.png](attachment:a2fac558-b18e-4610-bfa7-0d40c92e0ede.png)\n",
    "\n",
    "We will implement this using [LangGraph](https://python.langchain.com/docs/langgraph): \n",
    "\n",
    "* See video [here](https://www.youtube.com/watch?ref=blog.langchain.dev&v=pbAd8O1Lvm4&feature=youtu.be)\n",
    "* See blog post [here](https://blog.langchain.dev/agentic-rag-with-langgraph/)\n",
    "\n",
    "---\n",
    "\n",
    "### State\n",
    "\n",
    "Every node in our graph will modify `state`, which is dict that contains values (`question`, `documents`, etc) relevant to RAG."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "10028794-2fbc-43f9-aa4c-7fe3abd69c1e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from typing import Annotated, Dict, TypedDict\n",
    "\n",
    "from langchain_core.messages import BaseMessage\n",
    "\n",
    "\n",
    "class GraphState(TypedDict):\n",
    "    \"\"\"\n",
    "    Represents the state of our graph.\n",
    "\n",
    "    Attributes:\n",
    "        keys: A dictionary where each key is a string.\n",
    "    \"\"\"\n",
    "\n",
    "    keys: Dict[str, any]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0081ff31-4a91-4dbc-9977-8bcdc7dd0aeb",
   "metadata": {},
   "source": [
    "### Nodes and Edges\n",
    "\n",
    "Every node in the graph we laid out above is a function.\n",
    "\n",
    "Each node will modify the state in some way.\n",
    "\n",
    "Each edge will choose which node to call next."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "447d1333-082d-479a-a6fa-0ac0df78bb9d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import operator\n",
    "from typing import Annotated, Sequence, TypedDict\n",
    "\n",
    "from langchain import hub\n",
    "from langchain_core.output_parsers import JsonOutputParser\n",
    "from langchain.prompts import PromptTemplate\n",
    "from langchain.schema import Document\n",
    "from langchain_community.chat_models import ChatOllama\n",
    "from langchain_community.tools.tavily_search import TavilySearchResults\n",
    "from langchain_community.vectorstores import Chroma\n",
    "from langchain_core.output_parsers import StrOutputParser\n",
    "from langchain_core.runnables import RunnablePassthrough\n",
    "from langchain_mistralai.chat_models import ChatMistralAI\n",
    "\n",
    "### Nodes ###\n",
    "\n",
    "\n",
    "def retrieve(state):\n",
    "    \"\"\"\n",
    "    Retrieve documents\n",
    "\n",
    "    Args:\n",
    "        state (dict): The current graph state\n",
    "\n",
    "    Returns:\n",
    "        state (dict): New key added to state, documents, that contains retrieved documents\n",
    "    \"\"\"\n",
    "    print(\"---RETRIEVE---\")\n",
    "    state_dict = state[\"keys\"]\n",
    "    question = state_dict[\"question\"]\n",
    "    local = state_dict[\"local\"]\n",
    "    documents = retriever.get_relevant_documents(question)\n",
    "    return {\"keys\": {\"documents\": documents, \"local\": local, \"question\": question}}\n",
    "\n",
    "\n",
    "def generate(state):\n",
    "    \"\"\"\n",
    "    Generate answer\n",
    "\n",
    "    Args:\n",
    "        state (dict): The current graph state\n",
    "\n",
    "    Returns:\n",
    "        state (dict): New key added to state, generation, that contains generation\n",
    "    \"\"\"\n",
    "    print(\"---GENERATE---\")\n",
    "    state_dict = state[\"keys\"]\n",
    "    question = state_dict[\"question\"]\n",
    "    documents = state_dict[\"documents\"]\n",
    "    local = state_dict[\"local\"]\n",
    "\n",
    "    # Prompt\n",
    "    prompt = hub.pull(\"rlm/rag-prompt\")\n",
    "\n",
    "    # LLM\n",
    "    if local == \"Yes\":\n",
    "        llm = ChatOllama(model=local_llm, temperature=0)\n",
    "    else:\n",
    "        llm = ChatMistralAI(\n",
    "            model=\"mistral-medium\", temperature=0, mistral_api_key=mistral_api_key\n",
    "        )\n",
    "\n",
    "    # Post-processing\n",
    "    def format_docs(docs):\n",
    "        return \"\\n\\n\".join(doc.page_content for doc in docs)\n",
    "\n",
    "    # Chain\n",
    "    rag_chain = prompt | llm | StrOutputParser()\n",
    "\n",
    "    # Run\n",
    "    generation = rag_chain.invoke({\"context\": documents, \"question\": question})\n",
    "    return {\n",
    "        \"keys\": {\"documents\": documents, \"question\": question, \"generation\": generation}\n",
    "    }\n",
    "\n",
    "\n",
    "def grade_documents(state):\n",
    "    \"\"\"\n",
    "    Determines whether the retrieved documents are relevant to the question.\n",
    "\n",
    "    Args:\n",
    "        state (dict): The current graph state\n",
    "\n",
    "    Returns:\n",
    "        state (dict): Updates documents key with relevant documents\n",
    "    \"\"\"\n",
    "\n",
    "    print(\"---CHECK RELEVANCE---\")\n",
    "    state_dict = state[\"keys\"]\n",
    "    question = state_dict[\"question\"]\n",
    "    documents = state_dict[\"documents\"]\n",
    "    local = state_dict[\"local\"]\n",
    "\n",
    "    # LLM\n",
    "    if local == \"Yes\":\n",
    "        llm = ChatOllama(model=local_llm, format=\"json\", temperature=0)\n",
    "    else:\n",
    "        llm = ChatMistralAI(\n",
    "            mistral_api_key=mistral_api_key, temperature=0, model=\"mistral-medium\"\n",
    "        )\n",
    "\n",
    "    prompt = PromptTemplate(\n",
    "        template=\"\"\"You are a grader assessing relevance of a retrieved document to a user question. \\n \n",
    "        Here is the retrieved document: \\n\\n {context} \\n\\n\n",
    "        Here is the user question: {question} \\n\n",
    "        If the document contains keywords related to the user question, grade it as relevant. \\n\n",
    "        It does not need to be a stringent test. The goal is to filter out erroneous retrievals. \\n\n",
    "        Give a binary score 'yes' or 'no' score to indicate whether the document is relevant to the question. \\n\n",
    "        Provide the binary score as a JSON with a single key 'score' and no premable or explaination.\"\"\",\n",
    "        input_variables=[\"question\", \"context\"],\n",
    "    )\n",
    "\n",
    "    chain = prompt | llm | JsonOutputParser()\n",
    "\n",
    "    # Score\n",
    "    filtered_docs = []\n",
    "    search = \"No\"  # Default do not opt for web search to supplement retrieval\n",
    "    for d in documents:\n",
    "        score = chain.invoke(\n",
    "            {\n",
    "                \"question\": question,\n",
    "                \"context\": d.page_content,\n",
    "            }\n",
    "        )\n",
    "        grade = score[\"score\"]\n",
    "        if grade == \"yes\":\n",
    "            print(\"---GRADE: DOCUMENT RELEVANT---\")\n",
    "            filtered_docs.append(d)\n",
    "        else:\n",
    "            print(\"---GRADE: DOCUMENT NOT RELEVANT---\")\n",
    "            search = \"Yes\"  # Perform web search\n",
    "            continue\n",
    "\n",
    "    return {\n",
    "        \"keys\": {\n",
    "            \"documents\": filtered_docs,\n",
    "            \"question\": question,\n",
    "            \"local\": local,\n",
    "            \"run_web_search\": search,\n",
    "        }\n",
    "    }\n",
    "\n",
    "\n",
    "def transform_query(state):\n",
    "    \"\"\"\n",
    "    Transform the query to produce a better question.\n",
    "\n",
    "    Args:\n",
    "        state (dict): The current graph state\n",
    "\n",
    "    Returns:\n",
    "        state (dict): Updates question key with a re-phrased question\n",
    "    \"\"\"\n",
    "\n",
    "    print(\"---TRANSFORM QUERY---\")\n",
    "    state_dict = state[\"keys\"]\n",
    "    question = state_dict[\"question\"]\n",
    "    documents = state_dict[\"documents\"]\n",
    "    local = state_dict[\"local\"]\n",
    "\n",
    "    # Create a prompt template with format instructions and the query\n",
    "    prompt = PromptTemplate(\n",
    "        template=\"\"\"You are generating questions that is well optimized for retrieval. \\n \n",
    "        Look at the input and try to reason about the underlying sematic intent / meaning. \\n \n",
    "        Here is the initial question:\n",
    "        \\n ------- \\n\n",
    "        {question} \n",
    "        \\n ------- \\n\n",
    "        Provide an improved question without any premable, only respond with the updated question: \"\"\",\n",
    "        input_variables=[\"question\"],\n",
    "    )\n",
    "\n",
    "    # Grader\n",
    "    # LLM\n",
    "    if local == \"Yes\":\n",
    "        llm = ChatOllama(model=local_llm, temperature=0)\n",
    "    else:\n",
    "        llm = ChatMistralAI(\n",
    "            mistral_api_key=mistral_api_key, temperature=0, model=\"mistral-medium\"\n",
    "        )\n",
    "\n",
    "    # Prompt\n",
    "    chain = prompt | llm | StrOutputParser()\n",
    "    better_question = chain.invoke({\"question\": question})\n",
    "\n",
    "    return {\n",
    "        \"keys\": {\"documents\": documents, \"question\": better_question, \"local\": local}\n",
    "    }\n",
    "\n",
    "\n",
    "def web_search(state):\n",
    "    \"\"\"\n",
    "    Web search based on the re-phrased question using Tavily API.\n",
    "\n",
    "    Args:\n",
    "        state (dict): The current graph state\n",
    "\n",
    "    Returns:\n",
    "        state (dict): Web results appended to documents.\n",
    "    \"\"\"\n",
    "\n",
    "    print(\"---WEB SEARCH---\")\n",
    "    state_dict = state[\"keys\"]\n",
    "    question = state_dict[\"question\"]\n",
    "    documents = state_dict[\"documents\"]\n",
    "    local = state_dict[\"local\"]\n",
    "\n",
    "    tool = TavilySearchResults()\n",
    "    docs = tool.invoke({\"query\": question})\n",
    "    web_results = \"\\n\".join([d[\"content\"] for d in docs])\n",
    "    web_results = Document(page_content=web_results)\n",
    "    documents.append(web_results)\n",
    "\n",
    "    return {\"keys\": {\"documents\": documents, \"local\": local, \"question\": question}}\n",
    "\n",
    "\n",
    "### Edges\n",
    "\n",
    "\n",
    "def decide_to_generate(state):\n",
    "    \"\"\"\n",
    "    Determines whether to generate an answer or re-generate a question for web search.\n",
    "\n",
    "    Args:\n",
    "        state (dict): The current state of the agent, including all keys.\n",
    "\n",
    "    Returns:\n",
    "        str: Next node to call\n",
    "    \"\"\"\n",
    "\n",
    "    print(\"---DECIDE TO GENERATE---\")\n",
    "    state_dict = state[\"keys\"]\n",
    "    question = state_dict[\"question\"]\n",
    "    filtered_documents = state_dict[\"documents\"]\n",
    "    search = state_dict[\"run_web_search\"]\n",
    "\n",
    "    if search == \"Yes\":\n",
    "        # All documents have been filtered check_relevance\n",
    "        # We will re-generate a new query\n",
    "        print(\"---DECISION: TRANSFORM QUERY and RUN WEB SEARCH---\")\n",
    "        return \"transform_query\"\n",
    "    else:\n",
    "        # We have relevant documents, so generate answer\n",
    "        print(\"---DECISION: GENERATE---\")\n",
    "        return \"generate\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6096626d-dfa5-48e0-8a24-3747b298bc67",
   "metadata": {},
   "source": [
    "## Build Graph\n",
    "\n",
    "This just follows the flow we outlined in the figure above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0a63776c-f9cd-46ce-b8cf-95c066dc5b06",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pprint\n",
    "\n",
    "from langgraph.graph import END, StateGraph\n",
    "\n",
    "workflow = StateGraph(GraphState)\n",
    "\n",
    "# Define the nodes\n",
    "workflow.add_node(\"retrieve\", retrieve)  # retrieve\n",
    "workflow.add_node(\"grade_documents\", grade_documents)  # grade documents\n",
    "workflow.add_node(\"generate\", generate)  # generatae\n",
    "workflow.add_node(\"transform_query\", transform_query)  # transform_query\n",
    "workflow.add_node(\"web_search\", web_search)  # web search\n",
    "\n",
    "# Build graph\n",
    "workflow.set_entry_point(\"retrieve\")\n",
    "workflow.add_edge(\"retrieve\", \"grade_documents\")\n",
    "workflow.add_conditional_edges(\n",
    "    \"grade_documents\",\n",
    "    decide_to_generate,\n",
    "    {\n",
    "        \"transform_query\": \"transform_query\",\n",
    "        \"generate\": \"generate\",\n",
    "    },\n",
    ")\n",
    "workflow.add_edge(\"transform_query\", \"web_search\")\n",
    "workflow.add_edge(\"web_search\", \"generate\")\n",
    "workflow.add_edge(\"generate\", END)\n",
    "\n",
    "# Compile\n",
    "app = workflow.compile()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac0a868a-f0f9-4aa9-b955-a78da2359af8",
   "metadata": {},
   "source": [
    "## Run\n",
    "\n",
    "`Mistral API -` \n",
    "\n",
    "Trace for below run: https://smith.langchain.com/public/0a5cbc97-a2f6-4697-856c-90a6302fd13e/r"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3ab1d8df-a74e-4b48-a30b-e39bbfd5925a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---RETRIEVE---\n",
      "\"Node 'retrieve':\"\n",
      "'\\n---\\n'\n",
      "---CHECK RELEVANCE---\n",
      "---GRADE: DOCUMENT RELEVANT---\n",
      "---GRADE: DOCUMENT RELEVANT---\n",
      "---GRADE: DOCUMENT RELEVANT---\n",
      "---GRADE: DOCUMENT RELEVANT---\n",
      "\"Node 'grade_documents':\"\n",
      "'\\n---\\n'\n",
      "---DECIDE TO GENERATE---\n",
      "---DECISION: GENERATE---\n",
      "---GENERATE---\n",
      "\"Node 'generate':\"\n",
      "'\\n---\\n'\n",
      "\"Node '__end__':\"\n",
      "'\\n---\\n'\n",
      "(' In an LLM (large language model)-powered autonomous agent system, LLM '\n",
      " 'functions as the agent’s brain, complemented by several key components: '\n",
      " 'planning and memory.\\n'\n",
      " '\\n'\n",
      " 'Planning involves breaking down large tasks into smaller subgoals for '\n",
      " 'efficient handling of complex tasks and self-criticism and refinement to '\n",
      " 'improve results.\\n'\n",
      " '\\n'\n",
      " 'Memory includes short-term memory, which utilizes in-context learning, and '\n",
      " 'long-term memory, providing the agent with the capability to retain and '\n",
      " 'recall information over extended periods using an external vector store and '\n",
      " 'fast retrieval. The agent also learns to call external APIs for missing '\n",
      " 'information.\\n'\n",
      " '\\n'\n",
      " 'Types of Memory:\\n'\n",
      " '1. Sensory Memory: retains impressions of sensory information for a few '\n",
      " 'seconds.\\n'\n",
      " '2. Short-Term Memory (STM) or Working Memory: stores information needed for '\n",
      " 'complex cognitive tasks and lasts for 20-30 seconds.\\n'\n",
      " '3. Long-Term Memory (LTM): stores information for a remarkably long time, '\n",
      " 'with two subtypes: explicit/declarative memory and implicit/procedural '\n",
      " 'memory.\\n'\n",
      " '\\n'\n",
      " 'The agent uses LLM as its core controller, which can be extended beyond '\n",
      " 'generating well-written copies, stories, essays, and programs to a powerful '\n",
      " 'general problem solver.')\n"
     ]
    }
   ],
   "source": [
    "# Run\n",
    "inputs = {\n",
    "    \"keys\": {\n",
    "        \"question\": \"Explain how the different types of agent memory work?\",\n",
    "        \"local\": run_local,\n",
    "    }\n",
    "}\n",
    "for output in app.stream(inputs):\n",
    "    for key, value in output.items():\n",
    "        # Node\n",
    "        pprint.pprint(f\"Node '{key}':\")\n",
    "        # Optional: print full state at each node\n",
    "        # pprint.pprint(value[\"keys\"], indent=2, width=80, depth=None)\n",
    "    pprint.pprint(\"\\n---\\n\")\n",
    "\n",
    "# Final generation\n",
    "pprint.pprint(value[\"keys\"][\"generation\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03ee2be9-2368-46ea-9edd-dc064a7c7c96",
   "metadata": {},
   "source": [
    "`Local (Ollama) -` \n",
    "\n",
    "Trace for blow run: https://smith.langchain.com/public/3b23a1d4-720a-4b26-8f34-70d2f20f8832/r"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "16ea2032-59c7-433d-aca4-2828a1239074",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---RETRIEVE---\n",
      "\"Node 'retrieve':\"\n",
      "'\\n---\\n'\n",
      "---CHECK RELEVANCE---\n",
      "---GRADE: DOCUMENT RELEVANT---\n",
      "---GRADE: DOCUMENT RELEVANT---\n",
      "---GRADE: DOCUMENT RELEVANT---\n",
      "---GRADE: DOCUMENT RELEVANT---\n",
      "\"Node 'grade_documents':\"\n",
      "'\\n---\\n'\n",
      "---DECIDE TO GENERATE---\n",
      "---DECISION: GENERATE---\n",
      "---GENERATE---\n",
      "\"Node 'generate':\"\n",
      "'\\n---\\n'\n",
      "\"Node '__end__':\"\n",
      "'\\n---\\n'\n",
      "(' In an LLM (large language model)-powered autonomous agent system, LLM '\n",
      " 'functions as the agent’s brain, complemented by several key components: '\n",
      " 'planning and memory.\\n'\n",
      " '\\n'\n",
      " 'Planning involves breaking down large tasks into smaller subgoals for '\n",
      " 'efficient handling of complex tasks and self-criticism and refinement to '\n",
      " 'improve results.\\n'\n",
      " '\\n'\n",
      " 'Memory includes short-term memory, which utilizes in-context learning, and '\n",
      " 'long-term memory, providing the agent with the capability to retain and '\n",
      " 'recall information over extended periods using an external vector store and '\n",
      " 'fast retrieval. The agent also learns to call external APIs for missing '\n",
      " 'information.\\n'\n",
      " '\\n'\n",
      " 'Types of Memory:\\n'\n",
      " '1. Sensory Memory: retains impressions of sensory information for a few '\n",
      " 'seconds.\\n'\n",
      " '2. Short-Term Memory (STM) or Working Memory: stores information needed for '\n",
      " 'complex cognitive tasks and lasts for 20-30 seconds.\\n'\n",
      " '3. Long-Term Memory (LTM): stores information for a remarkably long time, '\n",
      " 'with two subtypes: explicit/declarative memory and implicit/procedural '\n",
      " 'memory.\\n'\n",
      " '\\n'\n",
      " 'The agent uses LLM as its core controller, which can be extended beyond '\n",
      " 'generating well-written copies, stories, essays, and programs to a powerful '\n",
      " 'general problem solver.')\n"
     ]
    }
   ],
   "source": [
    "# Run\n",
    "inputs = {\n",
    "    \"keys\": {\n",
    "        \"question\": \"Explain how the different types of agent memory work?\",\n",
    "        \"local\": run_local,\n",
    "    }\n",
    "}\n",
    "for output in app.stream(inputs):\n",
    "    for key, value in output.items():\n",
    "        # Node\n",
    "        pprint.pprint(f\"Node '{key}':\")\n",
    "        # Optional: print full state at each node\n",
    "        # pprint.pprint(value[\"keys\"], indent=2, width=80, depth=None)\n",
    "    pprint.pprint(\"\\n---\\n\")\n",
    "\n",
    "# Final generation\n",
    "pprint.pprint(value[\"keys\"][\"generation\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "deb28175-27a1-4afc-9747-2983e87fc881",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "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",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}