{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "9f853e403eabd4f8",
   "metadata": {
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   "source": [
    "# An agent for interacting with a SQL database\n",
    "\n",
    "In this tutorial, we will walk through how to build an agent that can answer questions about a SQL database. \n",
    "\n",
    "At a high level, the agent will:\n",
    "1. Fetch the available tables from the database\n",
    "2. Decide which tables are relevant to the question\n",
    "3. Fetch the DDL for the relevant tables\n",
    "4. Generate a query based on the question and information from the DDL\n",
    "5. Double-check the query for common mistakes using an LLM\n",
    "6. Execute the query and return the results\n",
    "7. Correct mistakes surfaced by the database engine until the query is successful\n",
    "8. Formulate a response based on the results\n",
    "\n",
    "The end-to-end workflow will look something like below:\n",
    "\n",
    "![](sql-agent-diagram.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5a87813ffe7e4d2",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "source": [
    "## Setup\n",
    "\n",
    "First let's install our required packages and set our API keys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4a4be247",
   "metadata": {},
   "outputs": [],
   "source": [
    "%capture --no-stderr\n",
    "%pip install -U langgraph langchain_openai langchain_community"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6c05a600f1afb5b6",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-06-12T21:24:00.532147Z",
     "start_time": "2024-06-12T21:24:00.526043Z"
    },
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "import getpass\n",
    "import os\n",
    "\n",
    "\n",
    "def _set_env(key: str):\n",
    "    if key not in os.environ:\n",
    "        os.environ[key] = getpass.getpass(f\"{key}:\")\n",
    "\n",
    "\n",
    "_set_env(\"OPENAI_API_KEY\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80559636",
   "metadata": {},
   "source": [
    "<div class=\"admonition tip\">\n",
    "    <p class=\"admonition-title\">Set up <a href=\"https://smith.langchain.com\">LangSmith</a> for LangGraph development</p>\n",
    "    <p style=\"padding-top: 5px;\">\n",
    "        Sign up for LangSmith to quickly spot issues and improve the performance of your LangGraph projects. LangSmith lets you use trace data to debug, test, and monitor your LLM apps built with LangGraph — read more about how to get started <a href=\"https://docs.smith.langchain.com\">here</a>. \n",
    "    </p>\n",
    "</div>    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "877d8c85825089d8",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "source": [
    "## Configure the database\n",
    "\n",
    "We will be creating a SQLite database for this tutorial. SQLite is a lightweight database that is easy to set up and use. We will be loading the `chinook` database, which is a sample database that represents a digital media store.\n",
    "Find more information about the database [here](https://www.sqlitetutorial.net/sqlite-sample-database/).\n",
    "\n",
    "For convenience, we have hosted the database (`Chinook.db`) on a public GCS bucket."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "64b0bf1b14c2e902",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-06-12T21:24:09.918436Z",
     "start_time": "2024-06-12T21:24:09.608563Z"
    },
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "File downloaded and saved as Chinook.db\n"
     ]
    }
   ],
   "source": [
    "import requests\n",
    "\n",
    "url = \"https://storage.googleapis.com/benchmarks-artifacts/chinook/Chinook.db\"\n",
    "\n",
    "response = requests.get(url)\n",
    "\n",
    "if response.status_code == 200:\n",
    "    # Open a local file in binary write mode\n",
    "    with open(\"Chinook.db\", \"wb\") as file:\n",
    "        # Write the content of the response (the file) to the local file\n",
    "        file.write(response.content)\n",
    "    print(\"File downloaded and saved as Chinook.db\")\n",
    "else:\n",
    "    print(f\"Failed to download the file. Status code: {response.status_code}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61c8304aa5ceb6a5",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "source": [
    "We will use a handy SQL database wrapper available in the `langchain_community` package to interact with the database. The wrapper provides a simple interface to execute SQL queries and fetch results. We will also use the `langchain_openai` package to interact with the OpenAI API for language models later in the tutorial."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a60191bd3489f278",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-06-12T21:24:14.663745Z",
     "start_time": "2024-06-12T21:24:13.527958Z"
    },
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "%%capture --no-stderr --no-display\n",
    "!pip install langgraph langchain_community langchain_openai"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1f1e1f4f86ed54",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-06-12T21:24:15.891582Z",
     "start_time": "2024-06-12T21:24:15.289782Z"
    },
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sqlite\n",
      "['Album', 'Artist', 'Customer', 'Employee', 'Genre', 'Invoice', 'InvoiceLine', 'MediaType', 'Playlist', 'PlaylistTrack', 'Track']\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "\"[(1, 'AC/DC'), (2, 'Accept'), (3, 'Aerosmith'), (4, 'Alanis Morissette'), (5, 'Alice In Chains'), (6, 'Antônio Carlos Jobim'), (7, 'Apocalyptica'), (8, 'Audioslave'), (9, 'BackBeat'), (10, 'Billy Cobham')]\""
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from langchain_community.utilities import SQLDatabase\n",
    "\n",
    "db = SQLDatabase.from_uri(\"sqlite:///Chinook.db\")\n",
    "print(db.dialect)\n",
    "print(db.get_usable_table_names())\n",
    "db.run(\"SELECT * FROM Artist LIMIT 10;\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6959e93141d8099c",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "source": [
    "## Utility functions\n",
    "\n",
    "We will define a few utility functions to help us with the agent implementation. Specifically, we will wrap a `ToolNode` with a fallback to handle errors and surface them to the agent."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "deae8460e4cf72b1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-06-12T21:24:17.557848Z",
     "start_time": "2024-06-12T21:24:17.508550Z"
    },
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   },
   "outputs": [],
   "source": [
    "from typing import Any\n",
    "\n",
    "from langchain_core.messages import ToolMessage\n",
    "from langchain_core.runnables import RunnableLambda, RunnableWithFallbacks\n",
    "from langgraph.prebuilt import ToolNode\n",
    "\n",
    "\n",
    "def create_tool_node_with_fallback(tools: list) -> RunnableWithFallbacks[Any, dict]:\n",
    "    \"\"\"\n",
    "    Create a ToolNode with a fallback to handle errors and surface them to the agent.\n",
    "    \"\"\"\n",
    "    return ToolNode(tools).with_fallbacks(\n",
    "        [RunnableLambda(handle_tool_error)], exception_key=\"error\"\n",
    "    )\n",
    "\n",
    "\n",
    "def handle_tool_error(state) -> dict:\n",
    "    error = state.get(\"error\")\n",
    "    tool_calls = state[\"messages\"][-1].tool_calls\n",
    "    return {\n",
    "        \"messages\": [\n",
    "            ToolMessage(\n",
    "                content=f\"Error: {repr(error)}\\n please fix your mistakes.\",\n",
    "                tool_call_id=tc[\"id\"],\n",
    "            )\n",
    "            for tc in tool_calls\n",
    "        ]\n",
    "    }"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d0196604f8cbb07b",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "source": [
    "## Define tools for the agent\n",
    "\n",
    "We will define a few tools that the agent will use to interact with the database.\n",
    "\n",
    "1. `list_tables_tool`: Fetch the available tables from the database\n",
    "2. `get_schema_tool`: Fetch the DDL for a table\n",
    "3. `db_query_tool`: Execute the query and fetch the results OR return an error message if the query fails\n",
    "\n",
    "For the first two tools, we will grab them from the `SQLDatabaseToolkit`, also available in the `langchain_community` package."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "452d049a3d2a4406",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-06-12T20:18:15.838940Z",
     "start_time": "2024-06-12T20:18:15.734199Z"
    },
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Album, Artist, Customer, Employee, Genre, Invoice, InvoiceLine, MediaType, Playlist, PlaylistTrack, Track\n",
      "\n",
      "CREATE TABLE \"Artist\" (\n",
      "\t\"ArtistId\" INTEGER NOT NULL, \n",
      "\t\"Name\" NVARCHAR(120), \n",
      "\tPRIMARY KEY (\"ArtistId\")\n",
      ")\n",
      "\n",
      "/*\n",
      "3 rows from Artist table:\n",
      "ArtistId\tName\n",
      "1\tAC/DC\n",
      "2\tAccept\n",
      "3\tAerosmith\n",
      "*/\n"
     ]
    }
   ],
   "source": [
    "from langchain_community.agent_toolkits import SQLDatabaseToolkit\n",
    "from langchain_openai import ChatOpenAI\n",
    "\n",
    "toolkit = SQLDatabaseToolkit(db=db, llm=ChatOpenAI(model=\"gpt-4o\"))\n",
    "tools = toolkit.get_tools()\n",
    "\n",
    "list_tables_tool = next(tool for tool in tools if tool.name == \"sql_db_list_tables\")\n",
    "get_schema_tool = next(tool for tool in tools if tool.name == \"sql_db_schema\")\n",
    "\n",
    "print(list_tables_tool.invoke(\"\"))\n",
    "\n",
    "print(get_schema_tool.invoke(\"Artist\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c16359edada327fa",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "source": [
    "The third will be defined manually. For the `db_query_tool`, we will execute the query against the database and return the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f7eb708ecb4c7cfc",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-06-12T20:39:35.759834Z",
     "start_time": "2024-06-12T20:39:35.740255Z"
    },
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(1, 'AC/DC'), (2, 'Accept'), (3, 'Aerosmith'), (4, 'Alanis Morissette'), (5, 'Alice In Chains'), (6, 'Antônio Carlos Jobim'), (7, 'Apocalyptica'), (8, 'Audioslave'), (9, 'BackBeat'), (10, 'Billy Cobham')]\n"
     ]
    }
   ],
   "source": [
    "from langchain_core.tools import tool\n",
    "\n",
    "\n",
    "@tool\n",
    "def db_query_tool(query: str) -> str:\n",
    "    \"\"\"\n",
    "    Execute a SQL query against the database and get back the result.\n",
    "    If the query is not correct, an error message will be returned.\n",
    "    If an error is returned, rewrite the query, check the query, and try again.\n",
    "    \"\"\"\n",
    "    result = db.run_no_throw(query)\n",
    "    if not result:\n",
    "        return \"Error: Query failed. Please rewrite your query and try again.\"\n",
    "    return result\n",
    "\n",
    "\n",
    "print(db_query_tool.invoke(\"SELECT * FROM Artist LIMIT 10;\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1d66db8b8621639",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "source": [
    "While not strictly a tool, we will prompt an LLM to check for common mistakes in the query and later add this as a node in the workflow."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "293017e8f05ac2b3",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-06-12T20:18:19.658322Z",
     "start_time": "2024-06-12T20:18:18.756256Z"
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_la8JTjHox6P1VjTqc15GSgdk', 'function': {'arguments': '{\"query\":\"SELECT * FROM Artist LIMIT 10;\"}', 'name': 'db_query_tool'}, 'type': 'function'}], 'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 20, 'prompt_tokens': 221, 'total_tokens': 241}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_a2ff031fb5', 'finish_reason': 'stop', 'logprobs': None}, id='run-dd7873ef-d2f7-4769-a5c0-e6776ec2c515-0', tool_calls=[{'name': 'db_query_tool', 'args': {'query': 'SELECT * FROM Artist LIMIT 10;'}, 'id': 'call_la8JTjHox6P1VjTqc15GSgdk', 'type': 'tool_call'}], usage_metadata={'input_tokens': 221, 'output_tokens': 20, 'total_tokens': 241})"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from langchain_core.prompts import ChatPromptTemplate\n",
    "\n",
    "query_check_system = \"\"\"You are a SQL expert with a strong attention to detail.\n",
    "Double check the SQLite query for common mistakes, including:\n",
    "- Using NOT IN with NULL values\n",
    "- Using UNION when UNION ALL should have been used\n",
    "- Using BETWEEN for exclusive ranges\n",
    "- Data type mismatch in predicates\n",
    "- Properly quoting identifiers\n",
    "- Using the correct number of arguments for functions\n",
    "- Casting to the correct data type\n",
    "- Using the proper columns for joins\n",
    "\n",
    "If there are any of the above mistakes, rewrite the query. If there are no mistakes, just reproduce the original query.\n",
    "\n",
    "You will call the appropriate tool to execute the query after running this check.\"\"\"\n",
    "\n",
    "query_check_prompt = ChatPromptTemplate.from_messages(\n",
    "    [(\"system\", query_check_system), (\"placeholder\", \"{messages}\")]\n",
    ")\n",
    "query_check = query_check_prompt | ChatOpenAI(model=\"gpt-4o\", temperature=0).bind_tools(\n",
    "    [db_query_tool], tool_choice=\"required\"\n",
    ")\n",
    "\n",
    "query_check.invoke({\"messages\": [(\"user\", \"SELECT * FROM Artist LIMIT 10;\")]})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66f88452151e8188",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "source": [
    "## Define the workflow\n",
    "\n",
    "We will then define the workflow for the agent. The agent will first force-call the `list_tables_tool` to fetch the available tables from the database, then follow the steps mentioned at the beginning of the tutorial."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "90d04ceea7b6b010",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-06-12T20:21:09.799829Z",
     "start_time": "2024-06-12T20:21:09.765928Z"
    },
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   "outputs": [],
   "source": [
    "from typing import Annotated, Literal\n",
    "\n",
    "from langchain_core.messages import AIMessage\n",
    "from langchain_core.pydantic_v1 import BaseModel, Field\n",
    "from langchain_openai import ChatOpenAI\n",
    "from typing_extensions import TypedDict\n",
    "\n",
    "from langgraph.graph import END, StateGraph, START\n",
    "from langgraph.graph.message import AnyMessage, add_messages\n",
    "\n",
    "\n",
    "# Define the state for the agent\n",
    "class State(TypedDict):\n",
    "    messages: Annotated[list[AnyMessage], add_messages]\n",
    "\n",
    "\n",
    "# Define a new graph\n",
    "workflow = StateGraph(State)\n",
    "\n",
    "\n",
    "# Add a node for the first tool call\n",
    "def first_tool_call(state: State) -> dict[str, list[AIMessage]]:\n",
    "    return {\n",
    "        \"messages\": [\n",
    "            AIMessage(\n",
    "                content=\"\",\n",
    "                tool_calls=[\n",
    "                    {\n",
    "                        \"name\": \"sql_db_list_tables\",\n",
    "                        \"args\": {},\n",
    "                        \"id\": \"tool_abcd123\",\n",
    "                    }\n",
    "                ],\n",
    "            )\n",
    "        ]\n",
    "    }\n",
    "\n",
    "\n",
    "def model_check_query(state: State) -> dict[str, list[AIMessage]]:\n",
    "    \"\"\"\n",
    "    Use this tool to double-check if your query is correct before executing it.\n",
    "    \"\"\"\n",
    "    return {\"messages\": [query_check.invoke({\"messages\": [state[\"messages\"][-1]]})]}\n",
    "\n",
    "\n",
    "workflow.add_node(\"first_tool_call\", first_tool_call)\n",
    "\n",
    "# Add nodes for the first two tools\n",
    "workflow.add_node(\n",
    "    \"list_tables_tool\", create_tool_node_with_fallback([list_tables_tool])\n",
    ")\n",
    "workflow.add_node(\"get_schema_tool\", create_tool_node_with_fallback([get_schema_tool]))\n",
    "\n",
    "# Add a node for a model to choose the relevant tables based on the question and available tables\n",
    "model_get_schema = ChatOpenAI(model=\"gpt-4o\", temperature=0).bind_tools(\n",
    "    [get_schema_tool]\n",
    ")\n",
    "workflow.add_node(\n",
    "    \"model_get_schema\",\n",
    "    lambda state: {\n",
    "        \"messages\": [model_get_schema.invoke(state[\"messages\"])],\n",
    "    },\n",
    ")\n",
    "\n",
    "\n",
    "# Describe a tool to represent the end state\n",
    "class SubmitFinalAnswer(BaseModel):\n",
    "    \"\"\"Submit the final answer to the user based on the query results.\"\"\"\n",
    "\n",
    "    final_answer: str = Field(..., description=\"The final answer to the user\")\n",
    "\n",
    "\n",
    "# Add a node for a model to generate a query based on the question and schema\n",
    "query_gen_system = \"\"\"You are a SQL expert with a strong attention to detail.\n",
    "\n",
    "Given an input question, output a syntactically correct SQLite query to run, then look at the results of the query and return the answer.\n",
    "\n",
    "DO NOT call any tool besides SubmitFinalAnswer to submit the final answer.\n",
    "\n",
    "When generating the query:\n",
    "\n",
    "Output the SQL query that answers the input question without a tool call.\n",
    "\n",
    "Unless the user specifies a specific number of examples they wish to obtain, always limit your query to at most 5 results.\n",
    "You can order the results by a relevant column to return the most interesting examples in the database.\n",
    "Never query for all the columns from a specific table, only ask for the relevant columns given the question.\n",
    "\n",
    "If you get an error while executing a query, rewrite the query and try again.\n",
    "\n",
    "If you get an empty result set, you should try to rewrite the query to get a non-empty result set. \n",
    "NEVER make stuff up if you don't have enough information to answer the query... just say you don't have enough information.\n",
    "\n",
    "If you have enough information to answer the input question, simply invoke the appropriate tool to submit the final answer to the user.\n",
    "\n",
    "DO NOT make any DML statements (INSERT, UPDATE, DELETE, DROP etc.) to the database.\"\"\"\n",
    "query_gen_prompt = ChatPromptTemplate.from_messages(\n",
    "    [(\"system\", query_gen_system), (\"placeholder\", \"{messages}\")]\n",
    ")\n",
    "query_gen = query_gen_prompt | ChatOpenAI(model=\"gpt-4o\", temperature=0).bind_tools(\n",
    "    [SubmitFinalAnswer]\n",
    ")\n",
    "\n",
    "\n",
    "def query_gen_node(state: State):\n",
    "    message = query_gen.invoke(state)\n",
    "\n",
    "    # Sometimes, the LLM will hallucinate and call the wrong tool. We need to catch this and return an error message.\n",
    "    tool_messages = []\n",
    "    if message.tool_calls:\n",
    "        for tc in message.tool_calls:\n",
    "            if tc[\"name\"] != \"SubmitFinalAnswer\":\n",
    "                tool_messages.append(\n",
    "                    ToolMessage(\n",
    "                        content=f\"Error: The wrong tool was called: {tc['name']}. Please fix your mistakes. Remember to only call SubmitFinalAnswer to submit the final answer. Generated queries should be outputted WITHOUT a tool call.\",\n",
    "                        tool_call_id=tc[\"id\"],\n",
    "                    )\n",
    "                )\n",
    "    else:\n",
    "        tool_messages = []\n",
    "    return {\"messages\": [message] + tool_messages}\n",
    "\n",
    "\n",
    "workflow.add_node(\"query_gen\", query_gen_node)\n",
    "\n",
    "# Add a node for the model to check the query before executing it\n",
    "workflow.add_node(\"correct_query\", model_check_query)\n",
    "\n",
    "# Add node for executing the query\n",
    "workflow.add_node(\"execute_query\", create_tool_node_with_fallback([db_query_tool]))\n",
    "\n",
    "\n",
    "# Define a conditional edge to decide whether to continue or end the workflow\n",
    "def should_continue(state: State) -> Literal[END, \"correct_query\", \"query_gen\"]:\n",
    "    messages = state[\"messages\"]\n",
    "    last_message = messages[-1]\n",
    "    # If there is a tool call, then we finish\n",
    "    if getattr(last_message, \"tool_calls\", None):\n",
    "        return END\n",
    "    if last_message.content.startswith(\"Error:\"):\n",
    "        return \"query_gen\"\n",
    "    else:\n",
    "        return \"correct_query\"\n",
    "\n",
    "\n",
    "# Specify the edges between the nodes\n",
    "workflow.add_edge(START, \"first_tool_call\")\n",
    "workflow.add_edge(\"first_tool_call\", \"list_tables_tool\")\n",
    "workflow.add_edge(\"list_tables_tool\", \"model_get_schema\")\n",
    "workflow.add_edge(\"model_get_schema\", \"get_schema_tool\")\n",
    "workflow.add_edge(\"get_schema_tool\", \"query_gen\")\n",
    "workflow.add_conditional_edges(\n",
    "    \"query_gen\",\n",
    "    should_continue,\n",
    ")\n",
    "workflow.add_edge(\"correct_query\", \"execute_query\")\n",
    "workflow.add_edge(\"execute_query\", \"query_gen\")\n",
    "\n",
    "# Compile the workflow into a runnable\n",
    "app = workflow.compile()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c344ae086ba8d22",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "source": [
    "## Visualize the graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4f200d1813897000",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-06-12T20:21:11.813905Z",
     "start_time": "2024-06-12T20:21:11.712945Z"
    },
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import Image, display\n",
    "from langchain_core.runnables.graph import MermaidDrawMethod\n",
    "\n",
    "display(\n",
    "    Image(\n",
    "        app.get_graph().draw_mermaid_png(\n",
    "            draw_method=MermaidDrawMethod.API,\n",
    "        )\n",
    "    )\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bdf78dc68548522c",
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "source": [
    "## Run the agent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "85958809-03c5-4e52-97cc-e7c0ae986f60",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'The sales agent who made the most in sales in 2009 is Steve Johnson with total sales of 164.34.'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "messages = app.invoke(\n",
    "    {\"messages\": [(\"user\", \"Which sales agent made the most in sales in 2009?\")]}\n",
    ")\n",
    "json_str = messages[\"messages\"][-1].tool_calls[0][\"args\"][\"final_answer\"]\n",
    "json_str"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "3bf7709f-500c-4f28-bb85-dda317286c63",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'first_tool_call': {'messages': [AIMessage(content='', tool_calls=[{'name': 'sql_db_list_tables', 'args': {}, 'id': 'tool_abcd123', 'type': 'tool_call'}])]}}\n",
      "{'list_tables_tool': {'messages': [ToolMessage(content='Album, Artist, Customer, Employee, Genre, Invoice, InvoiceLine, MediaType, Playlist, PlaylistTrack, Track', name='sql_db_list_tables', tool_call_id='tool_abcd123')]}}\n",
      "{'model_get_schema': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_z1tyC7cEAawi5oIQn731Uknp', 'function': {'arguments': '{\"table_names\":\"Employee, Invoice\"}', 'name': 'sql_db_schema'}, 'type': 'function'}], 'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 18, 'prompt_tokens': 177, 'total_tokens': 195}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_a2ff031fb5', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-c91a5aad-fc05-4881-87f9-0662d703c3c8-0', tool_calls=[{'name': 'sql_db_schema', 'args': {'table_names': 'Employee, Invoice'}, 'id': 'call_z1tyC7cEAawi5oIQn731Uknp', 'type': 'tool_call'}], usage_metadata={'input_tokens': 177, 'output_tokens': 18, 'total_tokens': 195})]}}\n",
      "{'get_schema_tool': {'messages': [ToolMessage(content='\\nCREATE TABLE \"Employee\" (\\n\\t\"EmployeeId\" INTEGER NOT NULL, \\n\\t\"LastName\" NVARCHAR(20) NOT NULL, \\n\\t\"FirstName\" NVARCHAR(20) NOT NULL, \\n\\t\"Title\" NVARCHAR(30), \\n\\t\"ReportsTo\" INTEGER, \\n\\t\"BirthDate\" DATETIME, \\n\\t\"HireDate\" DATETIME, \\n\\t\"Address\" NVARCHAR(70), \\n\\t\"City\" NVARCHAR(40), \\n\\t\"State\" NVARCHAR(40), \\n\\t\"Country\" NVARCHAR(40), \\n\\t\"PostalCode\" NVARCHAR(10), \\n\\t\"Phone\" NVARCHAR(24), \\n\\t\"Fax\" NVARCHAR(24), \\n\\t\"Email\" NVARCHAR(60), \\n\\tPRIMARY KEY (\"EmployeeId\"), \\n\\tFOREIGN KEY(\"ReportsTo\") REFERENCES \"Employee\" (\"EmployeeId\")\\n)\\n\\n/*\\n3 rows from Employee table:\\nEmployeeId\\tLastName\\tFirstName\\tTitle\\tReportsTo\\tBirthDate\\tHireDate\\tAddress\\tCity\\tState\\tCountry\\tPostalCode\\tPhone\\tFax\\tEmail\\n1\\tAdams\\tAndrew\\tGeneral Manager\\tNone\\t1962-02-18 00:00:00\\t2002-08-14 00:00:00\\t11120 Jasper Ave NW\\tEdmonton\\tAB\\tCanada\\tT5K 2N1\\t+1 (780) 428-9482\\t+1 (780) 428-3457\\tandrew@chinookcorp.com\\n2\\tEdwards\\tNancy\\tSales Manager\\t1\\t1958-12-08 00:00:00\\t2002-05-01 00:00:00\\t825 8 Ave SW\\tCalgary\\tAB\\tCanada\\tT2P 2T3\\t+1 (403) 262-3443\\t+1 (403) 262-3322\\tnancy@chinookcorp.com\\n3\\tPeacock\\tJane\\tSales Support Agent\\t2\\t1973-08-29 00:00:00\\t2002-04-01 00:00:00\\t1111 6 Ave SW\\tCalgary\\tAB\\tCanada\\tT2P 5M5\\t+1 (403) 262-3443\\t+1 (403) 262-6712\\tjane@chinookcorp.com\\n*/\\n\\n\\nCREATE TABLE \"Invoice\" (\\n\\t\"InvoiceId\" INTEGER NOT NULL, \\n\\t\"CustomerId\" INTEGER NOT NULL, \\n\\t\"InvoiceDate\" DATETIME NOT NULL, \\n\\t\"BillingAddress\" NVARCHAR(70), \\n\\t\"BillingCity\" NVARCHAR(40), \\n\\t\"BillingState\" NVARCHAR(40), \\n\\t\"BillingCountry\" NVARCHAR(40), \\n\\t\"BillingPostalCode\" NVARCHAR(10), \\n\\t\"Total\" NUMERIC(10, 2) NOT NULL, \\n\\tPRIMARY KEY (\"InvoiceId\"), \\n\\tFOREIGN KEY(\"CustomerId\") REFERENCES \"Customer\" (\"CustomerId\")\\n)\\n\\n/*\\n3 rows from Invoice table:\\nInvoiceId\\tCustomerId\\tInvoiceDate\\tBillingAddress\\tBillingCity\\tBillingState\\tBillingCountry\\tBillingPostalCode\\tTotal\\n1\\t2\\t2009-01-01 00:00:00\\tTheodor-Heuss-Straße 34\\tStuttgart\\tNone\\tGermany\\t70174\\t1.98\\n2\\t4\\t2009-01-02 00:00:00\\tUllevålsveien 14\\tOslo\\tNone\\tNorway\\t0171\\t3.96\\n3\\t8\\t2009-01-03 00:00:00\\tGrétrystraat 63\\tBrussels\\tNone\\tBelgium\\t1000\\t5.94\\n*/', name='sql_db_schema', tool_call_id='call_z1tyC7cEAawi5oIQn731Uknp')]}}\n",
      "{'query_gen': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_ErWLktUfxKsHGNGr74m72yYD', 'function': {'arguments': '{\"table_names\":\"Customer\"}', 'name': 'sql_db_schema'}, 'type': 'function'}], 'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 16, 'prompt_tokens': 1179, 'total_tokens': 1195}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_a2ff031fb5', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-19e02169-5e1e-40d9-90a2-384336ca5069-0', tool_calls=[{'name': 'sql_db_schema', 'args': {'table_names': 'Customer'}, 'id': 'call_ErWLktUfxKsHGNGr74m72yYD', 'type': 'tool_call'}], usage_metadata={'input_tokens': 1179, 'output_tokens': 16, 'total_tokens': 1195}), ToolMessage(content='Error: The wrong tool was called: sql_db_schema. Please fix your mistakes. Remember to only call SubmitFinalAnswer to submit the final answer. Generated queries should be outputted WITHOUT a tool call.', id='de5d25f5-b891-4e47-8282-d04dc9b93e9e', tool_call_id='call_ErWLktUfxKsHGNGr74m72yYD')]}}\n",
      "{'query_gen': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_TFaA52SbhgEqm3ElEAd4HCsn', 'function': {'arguments': '{\"table_names\":[\"Customer\"]}', 'name': 'sql_db_schema'}, 'type': 'function'}], 'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 17, 'prompt_tokens': 1245, 'total_tokens': 1262}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_a2ff031fb5', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-2c5f800f-43dc-4224-847b-49b5079efd2a-0', tool_calls=[{'name': 'sql_db_schema', 'args': {'table_names': ['Customer']}, 'id': 'call_TFaA52SbhgEqm3ElEAd4HCsn', 'type': 'tool_call'}], usage_metadata={'input_tokens': 1245, 'output_tokens': 17, 'total_tokens': 1262}), ToolMessage(content='Error: The wrong tool was called: sql_db_schema. Please fix your mistakes. Remember to only call SubmitFinalAnswer to submit the final answer. Generated queries should be outputted WITHOUT a tool call.', id='6c962a35-fc24-4f27-86f0-6ec05256d478', tool_call_id='call_TFaA52SbhgEqm3ElEAd4HCsn')]}}\n",
      "{'query_gen': {'messages': [AIMessage(content=\"To determine which sales agent made the most in sales in 2009, we need to join the `Invoice`, `Customer`, and `Employee` tables. Here is the query to find the top sales agent:\\n\\n```sql\\nSELECT e.FirstName, e.LastName, SUM(i.Total) as TotalSales\\nFROM Invoice i\\nJOIN Customer c ON i.CustomerId = c.CustomerId\\nJOIN Employee e ON c.SupportRepId = e.EmployeeId\\nWHERE strftime('%Y', i.InvoiceDate) = '2009'\\nGROUP BY e.EmployeeId\\nORDER BY TotalSales DESC\\nLIMIT 1;\\n```\", additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 125, 'prompt_tokens': 1312, 'total_tokens': 1437}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_3aa7262c27', 'finish_reason': 'stop', 'logprobs': None}, id='run-6cacd10d-d3aa-49ae-b9d7-8cc209fc4ccc-0', usage_metadata={'input_tokens': 1312, 'output_tokens': 125, 'total_tokens': 1437})]}}\n",
      "{'correct_query': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_FwCE2c7WORU7lKHdSWqMv0ON', 'function': {'arguments': '{\"query\":\"SELECT e.FirstName, e.LastName, SUM(i.Total) as TotalSales\\\\nFROM Invoice i\\\\nJOIN Customer c ON i.CustomerId = c.CustomerId\\\\nJOIN Employee e ON c.SupportRepId = e.EmployeeId\\\\nWHERE strftime(\\'%Y\\', i.InvoiceDate) = \\'2009\\'\\\\nGROUP BY e.EmployeeId\\\\nORDER BY TotalSales DESC\\\\nLIMIT 1;\"}', 'name': 'db_query_tool'}, 'type': 'function'}], 'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 90, 'prompt_tokens': 337, 'total_tokens': 427}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_a2ff031fb5', 'finish_reason': 'stop', 'logprobs': None}, id='run-71067e75-80f6-4356-8239-518e466b3526-0', tool_calls=[{'name': 'db_query_tool', 'args': {'query': \"SELECT e.FirstName, e.LastName, SUM(i.Total) as TotalSales\\nFROM Invoice i\\nJOIN Customer c ON i.CustomerId = c.CustomerId\\nJOIN Employee e ON c.SupportRepId = e.EmployeeId\\nWHERE strftime('%Y', i.InvoiceDate) = '2009'\\nGROUP BY e.EmployeeId\\nORDER BY TotalSales DESC\\nLIMIT 1;\"}, 'id': 'call_FwCE2c7WORU7lKHdSWqMv0ON', 'type': 'tool_call'}], usage_metadata={'input_tokens': 337, 'output_tokens': 90, 'total_tokens': 427})]}}\n",
      "{'execute_query': {'messages': [ToolMessage(content=\"[('Steve', 'Johnson', 164.34)]\", name='db_query_tool', tool_call_id='call_FwCE2c7WORU7lKHdSWqMv0ON')]}}\n",
      "{'query_gen': {'messages': [AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_fHJ4lvdiFM9HY6gupE6vLZV4', 'function': {'arguments': '{\"final_answer\":\"The sales agent who made the most in sales in 2009 is Steve Johnson with total sales of 164.34.\"}', 'name': 'SubmitFinalAnswer'}, 'type': 'function'}], 'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 41, 'prompt_tokens': 1553, 'total_tokens': 1594}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_cb7cc8e106', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-2ec7bf3a-2a16-47bd-aa9c-b7d6dc531c1b-0', tool_calls=[{'name': 'SubmitFinalAnswer', 'args': {'final_answer': 'The sales agent who made the most in sales in 2009 is Steve Johnson with total sales of 164.34.'}, 'id': 'call_fHJ4lvdiFM9HY6gupE6vLZV4', 'type': 'tool_call'}], usage_metadata={'input_tokens': 1553, 'output_tokens': 41, 'total_tokens': 1594})]}}\n"
     ]
    }
   ],
   "source": [
    "for event in app.stream(\n",
    "    {\"messages\": [(\"user\", \"Which sales agent made the most in sales in 2009?\")]}\n",
    "):\n",
    "    print(event)"
   ]
  },
  {
   "attachments": {
    "b92325b1-2c9a-4efa-94f5-49a75b1ffb64.png": {
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"
    }
   },
   "cell_type": "markdown",
   "id": "490f07a9-d816-4b53-b784-b33dbc6d74b1",
   "metadata": {},
   "source": [
    "## Eval\n",
    "\n",
    "Now, we can evaluate this agent! We previously defined [simple SQL agent](https://github.com/langchain-ai/langsmith-cookbook/blob/main/testing-examples/agent-evals-with-langgraph/langgraph_sql_agent_eval.ipynb) as part of our LangSmith evaluation cookbooks, and evaluated responses to 5 questions about our database. We can compare this agent to our prior one on the same dataset. [Agent evaluation](https://docs.smith.langchain.com/concepts/evaluation#agents) can focus on 3 things:\n",
    "\n",
    "* `Response`: The inputs are a prompt and a list of tools. The output is the agent response.\n",
    "* `Single tool`: As before, the inputs are a prompt and a list of tools. The output the tool call.\n",
    "* `Trajectory`: As before, the inputs are a prompt and a list of tools. The output is the list of tool calls\n",
    "\n",
    "![Screenshot 2024-06-13 at 2.13.30 PM.png](attachment:b92325b1-2c9a-4efa-94f5-49a75b1ffb64.png)\n",
    "\n",
    "### Response\n",
    "\n",
    "We'll evaluate end-to-end responses of our agent relative to reference answers. Let's run [response evaluation](https://docs.smith.langchain.com/concepts/evaluation#evaluating-an-agents-final-response) [on the same dataset](https://smith.langchain.com/public/20808486-67c3-4e30-920b-6d49d6f2b6b8/d)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "a80f4adc-a8dc-403c-9bef-6de5e873b9bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "\n",
    "\n",
    "def predict_sql_agent_answer(example: dict):\n",
    "    \"\"\"Use this for answer evaluation\"\"\"\n",
    "    msg = {\"messages\": (\"user\", example[\"input\"])}\n",
    "    messages = app.invoke(msg)\n",
    "    json_str = messages[\"messages\"][-1].tool_calls[0][\"args\"]\n",
    "    response = json_str[\"final_answer\"]\n",
    "    return {\"response\": response}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "1040233f-3751-4bd3-902f-709fc2e1ecf5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain import hub\n",
    "from langchain_openai import ChatOpenAI\n",
    "\n",
    "# Grade prompt\n",
    "grade_prompt_answer_accuracy = prompt = hub.pull(\"langchain-ai/rag-answer-vs-reference\")\n",
    "\n",
    "\n",
    "def answer_evaluator(run, example) -> dict:\n",
    "    \"\"\"\n",
    "    A simple evaluator for RAG answer accuracy\n",
    "    \"\"\"\n",
    "\n",
    "    # Get question, ground truth answer, chain\n",
    "    input_question = example.inputs[\"input\"]\n",
    "    reference = example.outputs[\"output\"]\n",
    "    prediction = run.outputs[\"response\"]\n",
    "\n",
    "    # LLM grader\n",
    "    llm = ChatOpenAI(model=\"gpt-4-turbo\", temperature=0)\n",
    "\n",
    "    # Structured prompt\n",
    "    answer_grader = grade_prompt_answer_accuracy | llm\n",
    "\n",
    "    # Run evaluator\n",
    "    score = answer_grader.invoke(\n",
    "        {\n",
    "            \"question\": input_question,\n",
    "            \"correct_answer\": reference,\n",
    "            \"student_answer\": prediction,\n",
    "        }\n",
    "    )\n",
    "    score = score[\"Score\"]\n",
    "\n",
    "    return {\"key\": \"answer_v_reference_score\", \"score\": score}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eb814b85-70ba-4699-9038-20266b53efbd",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langsmith.evaluation import evaluate\n",
    "\n",
    "dataset_name = \"SQL Agent Response\"\n",
    "experiment_results = evaluate(\n",
    "    predict_sql_agent_answer,\n",
    "    data=dataset_name,\n",
    "    evaluators=[answer_evaluator],\n",
    "    num_repetitions=3,\n",
    "    experiment_prefix=\"sql-agent-multi-step-response-v-reference\",\n",
    "    metadata={\"version\": \"Chinook, gpt-4o multi-step-agent\"},\n",
    ")"
   ]
  },
  {
   "attachments": {
    "e9a91890-3299-4b71-9ab2-21d737a120ba.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "23ddb587-d52c-45d5-9316-ff0e86f90ef6",
   "metadata": {},
   "source": [
    "Summary metrics (see dataset [here](https://smith.langchain.com/public/20808486-67c3-4e30-920b-6d49d6f2b6b8/d)):\n",
    "\n",
    "* The `multi-step` agent here out performs the previously defined [base case SQL agent](https://github.com/langchain-ai/langsmith-cookbook/blob/main/testing-examples/agent-evals-with-langgraph/langgraph_sql_agent_eval.ipynb)\n",
    "\n",
    "![Screenshot 2024-06-13 at 2.09.57 PM.png](attachment:e9a91890-3299-4b71-9ab2-21d737a120ba.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fb7f738-11d4-4a55-8b28-58727ead9838",
   "metadata": {},
   "source": [
    "### Trajectory\n",
    "\n",
    "Let's run [trajectory evaluation](https://docs.smith.langchain.com/concepts/evaluation#evaluating-an-agents-trajectory) on this same dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "ef84d2f7-fa52-46ca-8939-616e5ac4d101",
   "metadata": {},
   "outputs": [],
   "source": [
    "# These are the tools that we expect the agent to use\n",
    "expected_trajectory = [\n",
    "    \"sql_db_list_tables\",  # first: list_tables_tool node\n",
    "    \"sql_db_schema\",  # second: get_schema_tool node\n",
    "    \"db_query_tool\",  # third: execute_query node\n",
    "    \"SubmitFinalAnswer\",\n",
    "]  # fourth: query_gen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "1b7b007a-1dd2-4f3e-b157-b9d7ec2ea0a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "def predict_sql_agent_messages(example: dict):\n",
    "    \"\"\"Use this for answer evaluation\"\"\"\n",
    "    msg = {\"messages\": (\"user\", example[\"input\"])}\n",
    "    messages = app.invoke(msg)\n",
    "    return {\"response\": messages}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "ae2fe538-1c6d-4186-80dd-1d240d253f40",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langsmith.schemas import Example, Run\n",
    "\n",
    "\n",
    "def find_tool_calls(messages):\n",
    "    \"\"\"\n",
    "    Find all tool calls in the messages returned\n",
    "    \"\"\"\n",
    "    tool_calls = [\n",
    "        tc[\"name\"] for m in messages[\"messages\"] for tc in getattr(m, \"tool_calls\", [])\n",
    "    ]\n",
    "    return tool_calls\n",
    "\n",
    "\n",
    "def contains_all_tool_calls_in_order_exact_match(\n",
    "    root_run: Run, example: Example\n",
    ") -> dict:\n",
    "    \"\"\"\n",
    "    Check if all expected tools are called in exact order and without any additional tool calls.\n",
    "    \"\"\"\n",
    "    expected_trajectory = [\n",
    "        \"sql_db_list_tables\",\n",
    "        \"sql_db_schema\",\n",
    "        \"db_query_tool\",\n",
    "        \"SubmitFinalAnswer\",\n",
    "    ]\n",
    "    messages = root_run.outputs[\"response\"]\n",
    "    tool_calls = find_tool_calls(messages)\n",
    "\n",
    "    # Print the tool calls for debugging\n",
    "    print(\"Here are my tool calls:\")\n",
    "    print(tool_calls)\n",
    "\n",
    "    # Check if the tool calls match the expected trajectory exactly\n",
    "    if tool_calls == expected_trajectory:\n",
    "        score = 1\n",
    "    else:\n",
    "        score = 0\n",
    "\n",
    "    return {\"score\": int(score), \"key\": \"multi_tool_call_in_exact_order\"}\n",
    "\n",
    "\n",
    "def contains_all_tool_calls_in_order(root_run: Run, example: Example) -> dict:\n",
    "    \"\"\"\n",
    "    Check if all expected tools are called in order,\n",
    "    but it allows for other tools to be called in between the expected ones.\n",
    "    \"\"\"\n",
    "    messages = root_run.outputs[\"response\"]\n",
    "    tool_calls = find_tool_calls(messages)\n",
    "\n",
    "    # Print the tool calls for debugging\n",
    "    print(\"Here are my tool calls:\")\n",
    "    print(tool_calls)\n",
    "\n",
    "    it = iter(tool_calls)\n",
    "    if all(elem in it for elem in expected_trajectory):\n",
    "        score = 1\n",
    "    else:\n",
    "        score = 0\n",
    "    return {\"score\": int(score), \"key\": \"multi_tool_call_in_order\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf02e843-438d-4168-a27a-8f1e0266f8d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "experiment_results = evaluate(\n",
    "    predict_sql_agent_messages,\n",
    "    data=dataset_name,\n",
    "    evaluators=[\n",
    "        contains_all_tool_calls_in_order,\n",
    "        contains_all_tool_calls_in_order_exact_match,\n",
    "    ],\n",
    "    num_repetitions=3,\n",
    "    experiment_prefix=\"sql-agent-multi-step-tool-calling-trajecory-in-order\",\n",
    "    metadata={\"version\": \"Chinook, gpt-4o multi-step-agent\"},\n",
    ")"
   ]
  },
  {
   "attachments": {
    "9a1084c0-4c7c-4e6f-8329-80499d293e0a.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "a34d5022-c0c5-4037-afc5-75c173b882f6",
   "metadata": {},
   "source": [
    "The aggregate scores show that we never correctly call the tools in exact order:\n",
    "\n",
    "![Screenshot 2024-06-13 at 2.46.34 PM.png](attachment:9a1084c0-4c7c-4e6f-8329-80499d293e0a.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a9e4a0e6-fc0f-4101-bda5-d96d1294cbb9",
   "metadata": {},
   "source": [
    "Looking at the logging, we can see something interesting - \n",
    "\n",
    "```\n",
    "['sql_db_list_tables', 'sql_db_schema', 'sql_db_query', 'db_query_tool', 'SubmitFinalAnswer']\n",
    "```\n",
    "\n",
    "We appear to inject a hallucinated tool call, `sql_db_query`, into our trajectory for most of the runs.\n",
    "\n",
    "This is why `multi_tool_call_in_exact_order` fails, but `multi_tool_call_in_order` still passes. \n",
    "\n",
    "We will explore ways to resolve this using LangGraph in future cookbooks!"
   ]
  }
 ],
 "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": "3.11.9"
  }
 },
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}