L6-functional_conversation-student.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "79a3f6a4-8348-4cd6-a336-10ecb9cfaaa3",
   "metadata": {},
   "source": [
    "# Conversational agent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "36261434-a96c-49e8-ad41-918d14da089a",
   "metadata": {
    "height": 115,
    "tags": []
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import openai\n",
    "\n",
    "from dotenv import load_dotenv, find_dotenv\n",
    "_ = load_dotenv(find_dotenv()) # read local .env file\n",
    "openai.api_key = os.environ['OPENAI_API_KEY']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "20f44fbb-6708-4fce-bac4-55dc261e3a2d",
   "metadata": {
    "height": 30
   },
   "outputs": [],
   "source": [
    "from langchain.tools import tool"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "aa7406eb-334b-43d0-8110-31656a55b2fd",
   "metadata": {
    "height": 689
   },
   "outputs": [],
   "source": [
    "import requests\n",
    "from pydantic import BaseModel, Field\n",
    "import datetime\n",
    "\n",
    "# Define the input schema\n",
    "class OpenMeteoInput(BaseModel):\n",
    "    latitude: float = Field(..., description=\"Latitude of the location to fetch weather data for\")\n",
    "    longitude: float = Field(..., description=\"Longitude of the location to fetch weather data for\")\n",
    "\n",
    "@tool(args_schema=OpenMeteoInput)\n",
    "def get_current_temperature(latitude: float, longitude: float) -> dict:\n",
    "    \"\"\"Fetch current temperature for given coordinates.\"\"\"\n",
    "    \n",
    "    BASE_URL = \"https://api.open-meteo.com/v1/forecast\"\n",
    "    \n",
    "    # Parameters for the request\n",
    "    params = {\n",
    "        'latitude': latitude,\n",
    "        'longitude': longitude,\n",
    "        'hourly': 'temperature_2m',\n",
    "        'forecast_days': 1,\n",
    "    }\n",
    "\n",
    "    # Make the request\n",
    "    response = requests.get(BASE_URL, params=params)\n",
    "    \n",
    "    if response.status_code == 200:\n",
    "        results = response.json()\n",
    "    else:\n",
    "        raise Exception(f\"API Request failed with status code: {response.status_code}\")\n",
    "\n",
    "    current_utc_time = datetime.datetime.utcnow()\n",
    "    time_list = [datetime.datetime.fromisoformat(time_str.replace('Z', '+00:00')) for time_str in results['hourly']['time']]\n",
    "    temperature_list = results['hourly']['temperature_2m']\n",
    "    \n",
    "    closest_time_index = min(range(len(time_list)), key=lambda i: abs(time_list[i] - current_utc_time))\n",
    "    current_temperature = temperature_list[closest_time_index]\n",
    "    \n",
    "    return f'The current temperature is {current_temperature}°C'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "3ac0a1e7-567f-4775-a538-351a5ff099e8",
   "metadata": {
    "height": 349
   },
   "outputs": [],
   "source": [
    "import wikipedia\n",
    "\n",
    "@tool\n",
    "def search_wikipedia(query: str) -> str:\n",
    "    \"\"\"Run Wikipedia search and get page summaries.\"\"\"\n",
    "    page_titles = wikipedia.search(query)\n",
    "    summaries = []\n",
    "    for page_title in page_titles[: 3]:\n",
    "        try:\n",
    "            wiki_page =  wikipedia.page(title=page_title, auto_suggest=False)\n",
    "            summaries.append(f\"Page: {page_title}\\nSummary: {wiki_page.summary}\")\n",
    "        except (\n",
    "            self.wiki_client.exceptions.PageError,\n",
    "            self.wiki_client.exceptions.DisambiguationError,\n",
    "        ):\n",
    "            pass\n",
    "    if not summaries:\n",
    "        return \"No good Wikipedia Search Result was found\"\n",
    "    return \"\\n\\n\".join(summaries)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "4856d233-0916-4b97-8a7c-b494d5f2b8e0",
   "metadata": {
    "height": 30
   },
   "outputs": [],
   "source": [
    "tools = [get_current_temperature, search_wikipedia]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "cdf0d789-559b-42df-9d6d-77a0cd8888d6",
   "metadata": {
    "height": 94
   },
   "outputs": [],
   "source": [
    "from langchain.chat_models import ChatOpenAI\n",
    "from langchain.prompts import ChatPromptTemplate\n",
    "from langchain.tools.render import format_tool_to_openai_function\n",
    "from langchain.agents.output_parsers import OpenAIFunctionsAgentOutputParser"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "933ce7cb-099c-4f43-a548-b355a5b66511",
   "metadata": {
    "height": 132
   },
   "outputs": [],
   "source": [
    "functions = [format_tool_to_openai_function(f) for f in tools]\n",
    "model = ChatOpenAI(temperature=0).bind(functions=functions)\n",
    "prompt = ChatPromptTemplate.from_messages([\n",
    "    (\"system\", \"You are helpful but sassy assistant\"),\n",
    "    (\"user\", \"{input}\"),\n",
    "])\n",
    "chain = prompt | model | OpenAIFunctionsAgentOutputParser()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "4281a2d8-7884-40e0-b34d-09c39eecbb7a",
   "metadata": {
    "height": 30
   },
   "outputs": [],
   "source": [
    "result = chain.invoke({\"input\": \"what is the weather is sf?\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "b1dbc697-3e0a-4197-8ddc-2894763b4b85",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'get_current_temperature'"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.tool"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "ab829b59-803f-488f-bcf3-5119c224baa0",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'latitude': 37.7749, 'longitude': -122.4194}"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.tool_input"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "52b4d483-c498-4932-a373-bc2f4da17c7f",
   "metadata": {
    "height": 115
   },
   "outputs": [],
   "source": [
    "from langchain.prompts import MessagesPlaceholder\n",
    "prompt = ChatPromptTemplate.from_messages([\n",
    "    (\"system\", \"You are helpful but sassy assistant\"),\n",
    "    (\"user\", \"{input}\"),\n",
    "    MessagesPlaceholder(variable_name=\"agent_scratchpad\")\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "66ac6ea2-0e20-424a-ba33-6f8d627379b5",
   "metadata": {
    "height": 30
   },
   "outputs": [],
   "source": [
    "chain = prompt | model | OpenAIFunctionsAgentOutputParser()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "bada1de8-d7c4-4880-98c2-d47cc65f684d",
   "metadata": {
    "height": 81
   },
   "outputs": [],
   "source": [
    "result1 = chain.invoke({\n",
    "    \"input\": \"what is the weather is sf?\",\n",
    "    \"agent_scratchpad\": []\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "8d5f4e61-36a3-4d80-9c49-0b83cedb1592",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'get_current_temperature'"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result1.tool"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "11845c11-7d41-455a-8ac0-4b8161acaf83",
   "metadata": {
    "height": 30
   },
   "outputs": [],
   "source": [
    "observation = get_current_temperature(result1.tool_input)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "810184c8-8495-4189-b83e-17220cf65bbe",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'The current temperature is 6.4°C'"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "observation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "8c1b223d-ea2a-414c-924c-512c4c9da66a",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "langchain.schema.agent.AgentActionMessageLog"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(result1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "61853679-75b5-4462-8059-f1214286a9eb",
   "metadata": {
    "height": 43
   },
   "outputs": [],
   "source": [
    "from langchain.agents.format_scratchpad import format_to_openai_functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "72ca4278-165a-4915-8ec6-09e696f29d86",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[AIMessage(content='', additional_kwargs={'function_call': {'name': 'get_current_temperature', 'arguments': '{\"latitude\":37.7749,\"longitude\":-122.4194}'}})]"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result1.message_log"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "27e079a7-d58c-41c0-8762-4e183e72a1d1",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[AIMessage(content='', additional_kwargs={'function_call': {'name': 'get_current_temperature', 'arguments': '{\"latitude\":37.7749,\"longitude\":-122.4194}'}}),\n",
       " FunctionMessage(content='The current temperature is 6.4°C', name='get_current_temperature')]"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "format_to_openai_functions([(result1, observation), ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "09735a9e-452d-472b-a4c0-35c315e9e53f",
   "metadata": {
    "height": 94
   },
   "outputs": [],
   "source": [
    "result2 = chain.invoke({\n",
    "    \"input\": \"what is the weather is sf?\", \n",
    "    \"agent_scratchpad\": format_to_openai_functions([(result1, observation)])\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "9df61ecc-52fe-4fae-85a2-dbb61d68e2db",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AgentFinish(return_values={'output': 'The current temperature in San Francisco is 6.4°C.'}, log='The current temperature in San Francisco is 6.4°C.')"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "d9dd139f-e06a-4148-a025-ae100851c63e",
   "metadata": {
    "height": 298
   },
   "outputs": [],
   "source": [
    "from langchain.schema.agent import AgentFinish\n",
    "def run_agent(user_input):\n",
    "    intermediate_steps = []\n",
    "    while True:\n",
    "        result = chain.invoke({\n",
    "            \"input\": user_input, \n",
    "            \"agent_scratchpad\": format_to_openai_functions(intermediate_steps)\n",
    "        })\n",
    "        if isinstance(result, AgentFinish):\n",
    "            return result\n",
    "        tool = {\n",
    "            \"search_wikipedia\": search_wikipedia, \n",
    "            \"get_current_temperature\": get_current_temperature,\n",
    "        }[result.tool]\n",
    "        observation = tool.run(result.tool_input)\n",
    "        intermediate_steps.append((result, observation))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "4f6c1121-70a6-41ae-8c3d-41f7cfc756af",
   "metadata": {
    "height": 94
   },
   "outputs": [],
   "source": [
    "from langchain.schema.runnable import RunnablePassthrough\n",
    "agent_chain = RunnablePassthrough.assign(\n",
    "    agent_scratchpad= lambda x: format_to_openai_functions(x[\"intermediate_steps\"])\n",
    ") | chain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "4a05df88-4ad9-4c48-a7dd-6b42db91cb33",
   "metadata": {
    "height": 268
   },
   "outputs": [],
   "source": [
    "def run_agent(user_input):\n",
    "    intermediate_steps = []\n",
    "    while True:\n",
    "        result = agent_chain.invoke({\n",
    "            \"input\": user_input, \n",
    "            \"intermediate_steps\": intermediate_steps\n",
    "        })\n",
    "        if isinstance(result, AgentFinish):\n",
    "            return result\n",
    "        tool = {\n",
    "            \"search_wikipedia\": search_wikipedia, \n",
    "            \"get_current_temperature\": get_current_temperature,\n",
    "        }[result.tool]\n",
    "        observation = tool.run(result.tool_input)\n",
    "        intermediate_steps.append((result, observation))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "d8bf88b6-9992-4041-8344-ef4921bf3cf2",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AgentFinish(return_values={'output': 'The current temperature in San Francisco is 6.4°C.'}, log='The current temperature in San Francisco is 6.4°C.')"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "run_agent(\"what is the weather is sf?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "4c94a493-b480-409a-968a-038c8895709c",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AgentFinish(return_values={'output': 'LangChain is a framework designed to simplify the creation of applications using large language models (LLMs). It is a language model integration framework that can be used for document analysis and summarization, chatbots, and code analysis.'}, log='LangChain is a framework designed to simplify the creation of applications using large language models (LLMs). It is a language model integration framework that can be used for document analysis and summarization, chatbots, and code analysis.')"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "run_agent(\"what is langchain?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "7c8c6fd7-7c8c-487a-81de-1dcff739a2f9",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AgentFinish(return_values={'output': 'Hello! How can I assist you today?'}, log='Hello! How can I assist you today?')"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "run_agent(\"hi!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "b270a064-8cf1-44da-a59e-be622f9099b9",
   "metadata": {
    "height": 60
   },
   "outputs": [],
   "source": [
    "from langchain.agents import AgentExecutor\n",
    "agent_executor = AgentExecutor(agent=agent_chain, tools=tools, verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "87baebf4-2555-4e98-aece-a1c327644817",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
      "\u001b[32;1m\u001b[1;3m\n",
      "Invoking: `search_wikipedia` with `{'query': 'Langchain'}`\n",
      "\n",
      "\n",
      "\u001b[0m\u001b[33;1m\u001b[1;3mPage: LangChain\n",
      "Summary: LangChain is a framework designed to simplify the creation of applications using large language models (LLMs). As a language model integration framework, LangChain's use-cases largely overlap with those of language models in general, including document analysis and summarization, chatbots, and code analysis.\n",
      "\n",
      "Page: OpenAI\n",
      "Summary: OpenAI is a U.S. based artificial intelligence (AI) research organization founded in December 2015, researching artificial intelligence with the goal of developing \"safe and beneficial\" artificial general intelligence, which it defines as \"highly autonomous systems that outperform humans at most economically valuable work\".\n",
      "As one of the leading organizations of the AI spring, it has developed several large language models, advanced image generation models, and previously, released open-source models. Its release of ChatGPT has been credited with starting the AI spring.The organization consists of the non-profit OpenAI, Inc. registered in Delaware and its for-profit subsidiary OpenAI Global, LLC. It was founded by Ilya Sutskever, Greg Brockman, Trevor Blackwell, Vicki Cheung, Andrej Karpathy, Durk Kingma, Jessica Livingston, John Schulman, Pamela Vagata, and Wojciech Zaremba, with Sam Altman and Elon Musk serving as the initial board members. Microsoft provided OpenAI Global LLC with a $1 billion investment in 2019 and a $10 billion investment in 2023, with a significant portion of the investment in the form of computational resources on Microsoft's Azure cloud service.On November 17, 2023, the board removed Altman as CEO, while Brockman was removed as chairman and then resigned as president. Four days later, both returned after negotiations with the board, and most of the board members resigned. The new initial board included former Salesforce co-CEO Bret Taylor as chairman. It was also announced that Microsoft will have a non-voting board seat.\n",
      "\n",
      "Page: DataStax\n",
      "Summary: DataStax, Inc. is a real-time data for AI company based in Santa Clara, California. Its product Astra DB is a cloud database-as-a-service based on Apache Cassandra. DataStax also offers DataStax Enterprise (DSE), an on-premises database built on Apache Cassandra, and Astra Streaming, a messaging and event streaming cloud service based on Apache Pulsar. As of June 2022, the company has roughly 800 customers distributed in over 50 countries.\u001b[0m\u001b[32;1m\u001b[1;3mLangChain is a framework designed to simplify the creation of applications using large language models (LLMs). It is a language model integration framework that can be used for document analysis and summarization, chatbots, and code analysis.\u001b[0m\n",
      "\n",
      "\u001b[1m> Finished chain.\u001b[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'input': 'what is langchain?',\n",
       " 'output': 'LangChain is a framework designed to simplify the creation of applications using large language models (LLMs). It is a language model integration framework that can be used for document analysis and summarization, chatbots, and code analysis.'}"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agent_executor.invoke({\"input\": \"what is langchain?\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "c2da813c-47c3-487e-8c43-444c9b4d9821",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
      "\u001b[32;1m\u001b[1;3mNice to meet you, Bob! How can I assist you today?\u001b[0m\n",
      "\n",
      "\u001b[1m> Finished chain.\u001b[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'input': 'my name is bob',\n",
       " 'output': 'Nice to meet you, Bob! How can I assist you today?'}"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agent_executor.invoke({\"input\": \"my name is bob\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "15ba8a9f-fcb2-44d0-878f-3017f607e955",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
      "\u001b[32;1m\u001b[1;3mI'm sorry, I don't have access to your personal information. How can I assist you today?\u001b[0m\n",
      "\n",
      "\u001b[1m> Finished chain.\u001b[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'input': 'what is my name',\n",
       " 'output': \"I'm sorry, I don't have access to your personal information. How can I assist you today?\"}"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agent_executor.invoke({\"input\": \"what is my name\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "7d1df28a-27da-4f8e-ab03-a37a276db74f",
   "metadata": {
    "height": 115
   },
   "outputs": [],
   "source": [
    "prompt = ChatPromptTemplate.from_messages([\n",
    "    (\"system\", \"You are helpful but sassy assistant\"),\n",
    "    MessagesPlaceholder(variable_name=\"chat_history\"),\n",
    "    (\"user\", \"{input}\"),\n",
    "    MessagesPlaceholder(variable_name=\"agent_scratchpad\")\n",
    "])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "a8598e87-de8a-4710-a90e-2a919adc00e2",
   "metadata": {
    "height": 77
   },
   "outputs": [],
   "source": [
    "agent_chain = RunnablePassthrough.assign(\n",
    "    agent_scratchpad= lambda x: format_to_openai_functions(x[\"intermediate_steps\"])\n",
    ") | prompt | model | OpenAIFunctionsAgentOutputParser()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "a3865c2c-cb80-4341-bcbe-3b5150749622",
   "metadata": {
    "height": 60
   },
   "outputs": [],
   "source": [
    "from langchain.memory import ConversationBufferMemory\n",
    "memory = ConversationBufferMemory(return_messages=True,memory_key=\"chat_history\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "40b036fc-446f-4075-9a92-9a4bac6ecb2b",
   "metadata": {
    "height": 43
   },
   "outputs": [],
   "source": [
    "agent_executor = AgentExecutor(agent=agent_chain, tools=tools, verbose=True, memory=memory)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "37f70acf-57ff-4ab9-a942-f0ad6e680c40",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
      "\u001b[32;1m\u001b[1;3mHello Bob! How can I assist you today?\u001b[0m\n",
      "\n",
      "\u001b[1m> Finished chain.\u001b[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'input': 'my name is bob',\n",
       " 'chat_history': [HumanMessage(content='my name is bob'),\n",
       "  AIMessage(content='Hello Bob! How can I assist you today?')],\n",
       " 'output': 'Hello Bob! How can I assist you today?'}"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agent_executor.invoke({\"input\": \"my name is bob\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "a1554b0c-8c72-4d8d-bbed-20afd94828c5",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
      "\u001b[32;1m\u001b[1;3mYour name is Bob. How can I assist you today, Bob?\u001b[0m\n",
      "\n",
      "\u001b[1m> Finished chain.\u001b[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'input': 'whats my name',\n",
       " 'chat_history': [HumanMessage(content='my name is bob'),\n",
       "  AIMessage(content='Hello Bob! How can I assist you today?'),\n",
       "  HumanMessage(content='whats my name'),\n",
       "  AIMessage(content='Your name is Bob. How can I assist you today, Bob?')],\n",
       " 'output': 'Your name is Bob. How can I assist you today, Bob?'}"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agent_executor.invoke({\"input\": \"whats my name\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "40887f61-6746-4e51-852d-5ff0457384b7",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
      "\u001b[32;1m\u001b[1;3m\n",
      "Invoking: `get_current_temperature` with `{'latitude': 37.7749, 'longitude': -122.4194}`\n",
      "\n",
      "\n",
      "\u001b[0m\u001b[36;1m\u001b[1;3mThe current temperature is 6.4°C\u001b[0m\u001b[32;1m\u001b[1;3mThe current temperature in San Francisco is 6.4°C. Is there anything else you would like to know?\u001b[0m\n",
      "\n",
      "\u001b[1m> Finished chain.\u001b[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'input': 'whats the weather in sf?',\n",
       " 'chat_history': [HumanMessage(content='my name is bob'),\n",
       "  AIMessage(content='Hello Bob! How can I assist you today?'),\n",
       "  HumanMessage(content='whats my name'),\n",
       "  AIMessage(content='Your name is Bob. How can I assist you today, Bob?'),\n",
       "  HumanMessage(content='whats the weather in sf?'),\n",
       "  AIMessage(content='The current temperature in San Francisco is 6.4°C. Is there anything else you would like to know?')],\n",
       " 'output': 'The current temperature in San Francisco is 6.4°C. Is there anything else you would like to know?'}"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agent_executor.invoke({\"input\": \"whats the weather in sf?\"})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34b0b511-21d6-4c7e-b4e2-f886bc296997",
   "metadata": {},
   "source": [
    "### Create a chatbot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "b1cd4bd2-703e-4e4e-8f5c-ae3d491a41f6",
   "metadata": {
    "height": 111
   },
   "outputs": [],
   "source": [
    "@tool\n",
    "def create_your_own(query: str) -> str:\n",
    "    \"\"\"This function can do whatever you would like once you fill it in \"\"\"\n",
    "    print(type(query))\n",
    "    return query[::-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "67cb6fdc-ff55-4a7b-8a39-1871006aa990",
   "metadata": {
    "height": 43
   },
   "outputs": [],
   "source": [
    "tools = [get_current_temperature, search_wikipedia, create_your_own]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "66a73e69-acfb-471e-b54d-8ac586235521",
   "metadata": {
    "height": 706
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  var force = true;\n",
       "  var py_version = '3.1.1'.replace('rc', '-rc.');\n",
       "  var is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1;\n",
       "  var reloading = false;\n",
       "  var Bokeh = root.Bokeh;\n",
       "  var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n",
       "\n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
       "        if (callback != null)\n",
       "          callback();\n",
       "      });\n",
       "    } finally {\n",
       "      delete root._bokeh_onload_callbacks;\n",
       "    }\n",
       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "    if (js_modules == null) js_modules = [];\n",
       "    if (js_exports == null) js_exports = {};\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    if (!reloading) {\n",
       "      console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    }\n",
       "\n",
       "    function on_load() {\n",
       "      root._bokeh_is_loading--;\n",
       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
       "      }\n",
       "    }\n",
       "    window._bokeh_on_load = on_load\n",
       "\n",
       "    function on_error() {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
       "    var skip = [];\n",
       "    if (window.requirejs) {\n",
       "      window.requirejs.config({'packages': {}, 'paths': {'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n",
       "      require([\"jspanel\"], function(jsPanel) {\n",
       "\twindow.jsPanel = jsPanel\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-modal\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-tooltip\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-hint\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-layout\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-contextmenu\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"jspanel-dock\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"gridstack\"], function(GridStack) {\n",
       "\twindow.GridStack = GridStack\n",
       "\ton_load()\n",
       "      })\n",
       "      require([\"notyf\"], function() {\n",
       "\ton_load()\n",
       "      })\n",
       "      root._bokeh_is_loading = css_urls.length + 9;\n",
       "    } else {\n",
       "      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n",
       "    }\n",
       "\n",
       "    var existing_stylesheets = []\n",
       "    var links = document.getElementsByTagName('link')\n",
       "    for (var i = 0; i < links.length; i++) {\n",
       "      var link = links[i]\n",
       "      if (link.href != null) {\n",
       "\texisting_stylesheets.push(link.href)\n",
       "      }\n",
       "    }\n",
       "    for (var i = 0; i < css_urls.length; i++) {\n",
       "      var url = css_urls[i];\n",
       "      if (existing_stylesheets.indexOf(url) !== -1) {\n",
       "\ton_load()\n",
       "\tcontinue;\n",
       "      }\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }    if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/1.1.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.1.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.1.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.1.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.1.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.1.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.1.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/1.1.0/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/1.1.0/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    var existing_scripts = []\n",
       "    var scripts = document.getElementsByTagName('script')\n",
       "    for (var i = 0; i < scripts.length; i++) {\n",
       "      var script = scripts[i]\n",
       "      if (script.src != null) {\n",
       "\texisting_scripts.push(script.src)\n",
       "      }\n",
       "    }\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    for (var i = 0; i < js_modules.length; i++) {\n",
       "      var url = js_modules[i];\n",
       "      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      element.type = \"module\";\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    for (const name in js_exports) {\n",
       "      var url = js_exports[name];\n",
       "      if (skip.indexOf(url) >= 0 || root[name] != null) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.type = \"module\";\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      element.textContent = `\n",
       "      import ${name} from \"${url}\"\n",
       "      window.${name} = ${name}\n",
       "      window._bokeh_on_load()\n",
       "      `\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    if (!js_urls.length && !js_modules.length) {\n",
       "      on_load()\n",
       "    }\n",
       "  };\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.1.1.min.js\", \"https://cdn.holoviz.org/panel/1.1.0/dist/panel.min.js\"];\n",
       "  var js_modules = [];\n",
       "  var js_exports = {};\n",
       "  var css_urls = [];\n",
       "  var inline_js = [    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "function(Bokeh) {} // ensure no trailing comma for IE\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "        inline_js[i].call(root, root.Bokeh);\n",
       "      }\n",
       "      // Cache old bokeh versions\n",
       "      if (Bokeh != undefined && !reloading) {\n",
       "\tvar NewBokeh = root.Bokeh;\n",
       "\tif (Bokeh.versions === undefined) {\n",
       "\t  Bokeh.versions = new Map();\n",
       "\t}\n",
       "\tif (NewBokeh.version !== Bokeh.version) {\n",
       "\t  Bokeh.versions.set(NewBokeh.version, NewBokeh)\n",
       "\t}\n",
       "\troot.Bokeh = Bokeh;\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    }\n",
       "    root._bokeh_is_initializing = false\n",
       "  }\n",
       "\n",
       "  function load_or_wait() {\n",
       "    // Implement a backoff loop that tries to ensure we do not load multiple\n",
       "    // versions of Bokeh and its dependencies at the same time.\n",
       "    // In recent versions we use the root._bokeh_is_initializing flag\n",
       "    // to determine whether there is an ongoing attempt to initialize\n",
       "    // bokeh, however for backward compatibility we also try to ensure\n",
       "    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
       "    // before older versions are fully initialized.\n",
       "    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
       "      root._bokeh_is_initializing = false;\n",
       "      root._bokeh_onload_callbacks = undefined;\n",
       "      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n",
       "      load_or_wait();\n",
       "    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n",
       "      setTimeout(load_or_wait, 100);\n",
       "    } else {\n",
       "      Bokeh = root.Bokeh;\n",
       "      bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n",
       "      root._bokeh_is_initializing = true\n",
       "      root._bokeh_onload_callbacks = []\n",
       "      if (!reloading && (!bokeh_loaded || is_dev)) {\n",
       "\troot.Bokeh = undefined;\n",
       "      }\n",
       "      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n",
       "\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "\trun_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }\n",
       "  // Give older versions of the autoload script a head-start to ensure\n",
       "  // they initialize before we start loading newer version.\n",
       "  setTimeout(load_or_wait, 100)\n",
       "}(window));"
      ],
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i < links.length; i++) {\n      var link = links[i]\n      if (link.href != null) {\n\texisting_stylesheets.push(link.href)\n      }\n    }\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      if (existing_stylesheets.indexOf(url) !== -1) {\n\ton_load()\n\tcontinue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.1.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.1.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.1.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.1.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.1.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.1.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.1.0/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.1.0/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.1.0/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    var existing_scripts = []\n    var scripts = document.getElementsByTagName('script')\n    for (var i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n\texisting_scripts.push(script.src)\n      }\n    }\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (var i = 0; i < js_modules.length; i++) {\n      var url = js_modules[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      var url = js_exports[name];\n      if (skip.indexOf(url) >= 0 || root[name] != null) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.1.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.1.1.min.js\", \"https://cdn.holoviz.org/panel/1.1.0/dist/panel.min.js\"];\n  var js_modules = [];\n  var js_exports = {};\n  var css_urls = [];\n  var inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n        inline_js[i].call(root, root.Bokeh);\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n\tvar NewBokeh = root.Bokeh;\n\tif (Bokeh.versions === undefined) {\n\t  Bokeh.versions = new Map();\n\t}\n\tif (NewBokeh.version !== Bokeh.version) {\n\t  Bokeh.versions.set(NewBokeh.version, NewBokeh)\n\t}\n\troot.Bokeh = Bokeh;\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      Bokeh = root.Bokeh;\n      bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      if (!reloading && (!bokeh_loaded || is_dev)) {\n\troot.Bokeh = undefined;\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n\trun_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    },
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     "data": {
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       "  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
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       "    var nchildren = toinsert.length;\n",
       "    var html_node = toinsert[nchildren-1].children[0];\n",
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       "    var scripts = [];\n",
       "    var nodelist = html_node.querySelectorAll(\"script\");\n",
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      }
     },
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    }
   ],
   "source": [
    "import panel as pn  # GUI\n",
    "pn.extension()\n",
    "import panel as pn\n",
    "import param\n",
    "\n",
    "class cbfs(param.Parameterized):\n",
    "    \n",
    "    def __init__(self, tools, **params):\n",
    "        super(cbfs, self).__init__( **params)\n",
    "        self.panels = []\n",
    "        self.functions = [format_tool_to_openai_function(f) for f in tools]\n",
    "        self.model = ChatOpenAI(temperature=0).bind(functions=self.functions)\n",
    "        self.memory = ConversationBufferMemory(return_messages=True,memory_key=\"chat_history\")\n",
    "        self.prompt = ChatPromptTemplate.from_messages([\n",
    "            (\"system\", \"You are helpful but sassy assistant\"),\n",
    "            MessagesPlaceholder(variable_name=\"chat_history\"),\n",
    "            (\"user\", \"{input}\"),\n",
    "            MessagesPlaceholder(variable_name=\"agent_scratchpad\")\n",
    "        ])\n",
    "        self.chain = RunnablePassthrough.assign(\n",
    "            agent_scratchpad = lambda x: format_to_openai_functions(x[\"intermediate_steps\"])\n",
    "        ) | self.prompt | self.model | OpenAIFunctionsAgentOutputParser()\n",
    "        self.qa = AgentExecutor(agent=self.chain, tools=tools, verbose=False, memory=self.memory)\n",
    "    \n",
    "    def convchain(self, query):\n",
    "        if not query:\n",
    "            return\n",
    "        inp.value = ''\n",
    "        result = self.qa.invoke({\"input\": query})\n",
    "        self.answer = result['output'] \n",
    "        self.panels.extend([\n",
    "            pn.Row('User:', pn.pane.Markdown(query, width=450)),\n",
    "            pn.Row('ChatBot:', pn.pane.Markdown(self.answer, width=450, styles={'background-color': '#F6F6F6'}))\n",
    "        ])\n",
    "        return pn.WidgetBox(*self.panels, scroll=True)\n",
    "\n",
    "\n",
    "    def clr_history(self,count=0):\n",
    "        self.chat_history = []\n",
    "        return "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "080c3827-87fc-4dbe-a566-ca95b3f9068e",
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    "height": 319
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       "</div>\n",
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('value'.startsWith('event:')) {\\n      var value = true\\n    } else {\\n      var value = source['value'];\\n      value = value;\\n    }\\n    if (typeof value !== 'boolean' || source.labels !== ['Loading']) {\\n      value = true\\n    }\\n    var css_classes = target.css_classes.slice()\\n    var loading_css = ['pn-loading', 'pn-arc']\\n    if (value) {\\n      for (var css of loading_css) {\\n        if (!(css in css_classes)) {\\n          css_classes.push(css)\\n        }\\n      }\\n    } else {\\n     for (var css of loading_css) {\\n        var index = css_classes.indexOf(css)\\n        if (index > -1) {\\n          css_classes.splice(index, 1)\\n        }\\n      }\\n    }\\n    target['css_classes'] = css_classes\\n    \"}}]]]},\"stylesheets\":[\"\\n:host(.pn-loading.pn-arc):before, .pn-loading.pn-arc:before {\\n  background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n  background-size: auto calc(min(50%, 400px));\\n}\",{\"id\":\"36a6a2dd-7ef1-4009-91b6-141b90679609\"},{\"id\":\"c5c96eb7-20ec-43a1-9ee5-bfce8437da21\"},{\"id\":\"165f96bb-4f37-4cc9-b82e-13d9e1be06c3\"}],\"width\":300,\"min_width\":300,\"margin\":[5,10],\"align\":\"start\",\"placeholder\":\"Enter text here\\u2026\",\"max_length\":5000}}]}},{\"type\":\"object\",\"name\":\"Div\",\"id\":\"d0dee3bb-2132-478c-bc1d-4b4019acf7f1\",\"attributes\":{\"name\":\"Divider00120\",\"stylesheets\":[\"\\n:host(.pn-loading.pn-arc):before, .pn-loading.pn-arc:before {\\n  background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n  background-size: auto calc(min(50%, 400px));\\n}\",{\"type\":\"object\",\"name\":\"ImportedStyleSheet\",\"id\":\"1583b5ef-2d62-4c28-8fe8-504c1bde5561\",\"attributes\":{\"url\":\"https://cdn.holoviz.org/panel/1.1.0/dist/css/loading.css\"}},{\"type\":\"object\",\"name\":\"ImportedStyleSheet\",\"id\":\"778490fc-8406-4576-8e64-484d8c391cdb\",\"attributes\":{\"url\":\"https://cdn.holoviz.org/panel/1.1.0/dist/css/divider.css\"}}],\"margin\":0,\"width_policy\":\"fit\",\"align\":\"start\",\"text\":\"<hr>\"}},{\"id\":\"328453a5-6f4d-4e97-98b7-48f74e56a63f\"},{\"type\":\"object\",\"name\":\"Div\",\"id\":\"00c887e6-ffaa-4f94-8e57-1f874909c6cb\",\"attributes\":{\"name\":\"Divider00139\",\"stylesheets\":[\"\\n:host(.pn-loading.pn-arc):before, .pn-loading.pn-arc:before {\\n  background-image: url(\\\"data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHN0eWxlPSJtYXJnaW46IGF1dG87IGJhY2tncm91bmQ6IG5vbmU7IGRpc3BsYXk6IGJsb2NrOyBzaGFwZS1yZW5kZXJpbmc6IGF1dG87IiB2aWV3Qm94PSIwIDAgMTAwIDEwMCIgcHJlc2VydmVBc3BlY3RSYXRpbz0ieE1pZFlNaWQiPiAgPGNpcmNsZSBjeD0iNTAiIGN5PSI1MCIgZmlsbD0ibm9uZSIgc3Ryb2tlPSIjYzNjM2MzIiBzdHJva2Utd2lkdGg9IjEwIiByPSIzNSIgc3Ryb2tlLWRhc2hhcnJheT0iMTY0LjkzMzYxNDMxMzQ2NDE1IDU2Ljk3Nzg3MTQzNzgyMTM4Ij4gICAgPGFuaW1hdGVUcmFuc2Zvcm0gYXR0cmlidXRlTmFtZT0idHJhbnNmb3JtIiB0eXBlPSJyb3RhdGUiIHJlcGVhdENvdW50PSJpbmRlZmluaXRlIiBkdXI9IjFzIiB2YWx1ZXM9IjAgNTAgNTA7MzYwIDUwIDUwIiBrZXlUaW1lcz0iMDsxIj48L2FuaW1hdGVUcmFuc2Zvcm0+ICA8L2NpcmNsZT48L3N2Zz4=\\\");\\n  background-size: auto calc(min(50%, 400px));\\n}\",{\"type\":\"object\",\"name\":\"ImportedStyleSheet\",\"id\":\"9b13f696-506c-4ebf-84a9-4585fc699162\",\"attributes\":{\"url\":\"https://cdn.holoviz.org/panel/1.1.0/dist/css/loading.css\"}},{\"type\":\"object\",\"name\":\"ImportedStyleSheet\",\"id\":\"9cd1e978-ec32-419c-a97b-9bbf091f7cd5\",\"attributes\":{\"url\":\"https://cdn.holoviz.org/panel/1.1.0/dist/css/divider.css\"}}],\"margin\":0,\"width_policy\":\"fit\",\"align\":\"start\",\"text\":\"<hr>\"}}]}}}}]}}]}},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"77dcfd4d-ce17-4b71-93f7-0003770d1aef\",\"attributes\":{\"plot_id\":\"c9c3e0c6-99e7-479e-9cab-f5e560da30e5\",\"comm_id\":\"ff467e92cf28461ba8dfb9cc48532b3c\",\"client_comm_id\":\"a3ff99c7da6f40729f676c8d3419591f\"}}],\"callbacks\":{\"type\":\"map\"}}};\n",
       "  var render_items = [{\"docid\":\"619c1576-27ca-4543-9cb9-cbddbc45352f\",\"roots\":{\"c9c3e0c6-99e7-479e-9cab-f5e560da30e5\":\"d1f3cca7-e168-421b-96b6-32ebb7a84f71\"},\"root_ids\":[\"c9c3e0c6-99e7-479e-9cab-f5e560da30e5\"]}];\n",
       "  var docs = Object.values(docs_json)\n",
       "  if (!docs) {\n",
       "    return\n",
       "  }\n",
       "  const py_version = docs[0].version.replace('rc', '-rc.')\n",
       "  const is_dev = py_version.indexOf(\"+\") !== -1 || py_version.indexOf(\"-\") !== -1\n",
       "  function embed_document(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "    for (const render_item of render_items) {\n",
       "      for (const root_id of render_item.root_ids) {\n",
       "\tconst id_el = document.getElementById(root_id)\n",
       "\tif (id_el.children.length && (id_el.children[0].className === 'bk-root')) {\n",
       "\t  const root_el = id_el.children[0]\n",
       "\t  root_el.id = root_el.id + '-rendered'\n",
       "\t}\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  function get_bokeh(root) {\n",
       "    if (root.Bokeh === undefined) {\n",
       "      return null\n",
       "    } else if (root.Bokeh.version !== py_version && !is_dev) {\n",
       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
       "\treturn null\n",
       "      }\n",
       "      return root.Bokeh.versions.get(py_version);\n",
       "    } else if (root.Bokeh.version === py_version) {\n",
       "      return root.Bokeh\n",
       "    }\n",
       "    return null\n",
       "  }\n",
       "  function is_loaded(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
       "  }\n",
       "  if (is_loaded(root)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (is_loaded(root)) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else if (document.readyState == \"complete\") {\n",
       "        attempts++;\n",
       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "\t  var Bokeh = get_bokeh(root)\n",
       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
       "\t  } else {\n",
       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
       "\t    embed_document(root)\n",
       "\t  }\n",
       "        }\n",
       "      }\n",
       "    }, 25, root)\n",
       "  }\n",
       "})(window);</script>"
      ],
      "text/plain": [
       "Column\n",
       "    [0] Row\n",
       "        [0] Markdown(str)\n",
       "    [1] Tabs\n",
       "        [0] Column\n",
       "            [0] Row\n",
       "                [0] TextInput(placeholder='Enter text here…')\n",
       "            [1] Divider()\n",
       "            [2] ParamFunction(function, _pane=Str, height=400, loading_indicator=True)\n",
       "            [3] Divider()"
      ]
     },
     "execution_count": 69,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "c9c3e0c6-99e7-479e-9cab-f5e560da30e5"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cb = cbfs(tools)\n",
    "\n",
    "inp = pn.widgets.TextInput( placeholder='Enter text here…')\n",
    "\n",
    "conversation = pn.bind(cb.convchain, inp) \n",
    "\n",
    "tab1 = pn.Column(\n",
    "    pn.Row(inp),\n",
    "    pn.layout.Divider(),\n",
    "    pn.panel(conversation,  loading_indicator=True, height=400),\n",
    "    pn.layout.Divider(),\n",
    ")\n",
    "\n",
    "dashboard = pn.Column(\n",
    "    pn.Row(pn.pane.Markdown('# QnA_Bot')),\n",
    "    pn.Tabs(('Conversation', tab1))\n",
    ")\n",
    "dashboard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "713e8877",
   "metadata": {
    "height": 30
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6ffd489e",
   "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": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}