00-playground/42-functions-tools-agents-langchain/L6-functional_conversation-student.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "79a3f6a4-8348-4cd6-a336-10ecb9cfaaa3",
   "metadata": {},
   "source": [
    "# Conversational agent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "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": 2,
   "id": "20f44fbb-6708-4fce-bac4-55dc261e3a2d",
   "metadata": {
    "height": 30
   },
   "outputs": [],
   "source": [
    "from langchain.tools import tool"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "aa7406eb-334b-43d0-8110-31656a55b2fd",
   "metadata": {
    "height": 693
   },
   "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": 4,
   "id": "3ac0a1e7-567f-4775-a538-351a5ff099e8",
   "metadata": {
    "height": 353
   },
   "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": 5,
   "id": "4856d233-0916-4b97-8a7c-b494d5f2b8e0",
   "metadata": {
    "height": 30
   },
   "outputs": [],
   "source": [
    "tools = [get_current_temperature, search_wikipedia]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cdf0d789-559b-42df-9d6d-77a0cd8888d6",
   "metadata": {
    "height": 98
   },
   "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": 7,
   "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": 8,
   "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": 9,
   "id": "b1dbc697-3e0a-4197-8ddc-2894763b4b85",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'get_current_temperature'"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.tool"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ab829b59-803f-488f-bcf3-5119c224baa0",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'latitude': 37.7749, 'longitude': -122.4194}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.tool_input"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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": 12,
   "id": "66ac6ea2-0e20-424a-ba33-6f8d627379b5",
   "metadata": {
    "height": 30
   },
   "outputs": [],
   "source": [
    "chain = prompt | model | OpenAIFunctionsAgentOutputParser()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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": 14,
   "id": "8d5f4e61-36a3-4d80-9c49-0b83cedb1592",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'get_current_temperature'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result1.tool"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "11845c11-7d41-455a-8ac0-4b8161acaf83",
   "metadata": {
    "height": 30
   },
   "outputs": [],
   "source": [
    "observation = get_current_temperature(result1.tool_input)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "810184c8-8495-4189-b83e-17220cf65bbe",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'The current temperature is 8.1°C'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "observation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "8c1b223d-ea2a-414c-924c-512c4c9da66a",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "langchain.schema.agent.AgentActionMessageLog"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(result1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "61853679-75b5-4462-8059-f1214286a9eb",
   "metadata": {
    "height": 47
   },
   "outputs": [],
   "source": [
    "from langchain.agents.format_scratchpad import format_to_openai_functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result1.message_log"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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 8.1°C', name='get_current_temperature')]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "format_to_openai_functions([(result1, observation), ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "09735a9e-452d-472b-a4c0-35c315e9e53f",
   "metadata": {
    "height": 98
   },
   "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": 22,
   "id": "9df61ecc-52fe-4fae-85a2-dbb61d68e2db",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AgentFinish(return_values={'output': 'The current temperature in San Francisco is 8.1°C.'}, log='The current temperature in San Francisco is 8.1°C.')"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "d9dd139f-e06a-4148-a025-ae100851c63e",
   "metadata": {
    "height": 302
   },
   "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": 24,
   "id": "4f6c1121-70a6-41ae-8c3d-41f7cfc756af",
   "metadata": {
    "height": 98
   },
   "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": 25,
   "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": 26,
   "id": "d8bf88b6-9992-4041-8344-ef4921bf3cf2",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AgentFinish(return_values={'output': 'The current temperature in San Francisco is 8.1°C.'}, log='The current temperature in San Francisco is 8.1°C.')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "run_agent(\"what is the weather is sf?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "4c94a493-b480-409a-968a-038c8895709c",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AgentFinish(return_values={'output': 'LangChain is a software framework that helps facilitate the integration of large language models (LLMs) into applications. It is used for document analysis and summarization, chatbots, and code analysis.'}, log='LangChain is a software framework that helps facilitate the integration of large language models (LLMs) into applications. It is used for document analysis and summarization, chatbots, and code analysis.')"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "run_agent(\"what is langchain?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7c8c6fd7-7c8c-487a-81de-1dcff739a2f9",
   "metadata": {
    "height": 30
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AgentFinish(return_values={'output': 'Well, hello there! How can I sass... I mean, assist you today?'}, log='Well, hello there! How can I sass... I mean, assist you today?')"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "run_agent(\"hi!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "b270a064-8cf1-44da-a59e-be622f9099b9",
   "metadata": {
    "height": 64
   },
   "outputs": [],
   "source": [
    "from langchain.agents import AgentExecutor\n",
    "agent_executor = AgentExecutor(agent=agent_chain, tools=tools, verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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 software framework that helps facilitate the integration of large language models (LLMs) into applications. 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: Milvus (vector database)\n",
      "Summary: Milvus is a distributed vector database developed by Zilliz. It is available as both open-source software and a cloud service.\n",
      "Milvus is an open-source project under LF AI & Data Foundation distributed under the Apache License 2.0.\n",
      "\n",
      "\n",
      "\n",
      "Page: Retrieval-augmented generation\n",
      "Summary: Retrieval-Augmented Generation (RAG) is a technique that grants generative artificial intelligence models information retrieval capabilities. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to augment information drawn from its own vast, static training data. This allows LLMs to use domain-specific and/or updated information.  \n",
      "Use cases include providing chatbot access to internal company data or giving factual information only from an authoritative source.\n",
      "\n",
      "\u001b[0m\u001b[32;1m\u001b[1;3mLangChain is a software framework that helps facilitate the integration of large language models (LLMs) into applications. It is 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 software framework that helps facilitate the integration of large language models (LLMs) into applications. It is used for document analysis and summarization, chatbots, and code analysis.'}"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agent_executor.invoke({\"input\": \"what is langchain?\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "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;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', 'output': 'Hello Bob! How can I assist you today?'}"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agent_executor.invoke({\"input\": \"my name is bob\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agent_executor.invoke({\"input\": \"what is my name\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "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": 35,
   "id": "a8598e87-de8a-4710-a90e-2a919adc00e2",
   "metadata": {
    "height": 81
   },
   "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": 36,
   "id": "a3865c2c-cb80-4341-bcbe-3b5150749622",
   "metadata": {
    "height": 64
   },
   "outputs": [],
   "source": [
    "from langchain.memory import ConversationBufferMemory\n",
    "memory = ConversationBufferMemory(return_messages=True,memory_key=\"chat_history\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "40b036fc-446f-4075-9a92-9a4bac6ecb2b",
   "metadata": {
    "height": 47
   },
   "outputs": [],
   "source": [
    "agent_executor = AgentExecutor(agent=agent_chain, tools=tools, verbose=True, memory=memory)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "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": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agent_executor.invoke({\"input\": \"my name is bob\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agent_executor.invoke({\"input\": \"whats my name\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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 8.1°C\u001b[0m\u001b[32;1m\u001b[1;3mThe current temperature in San Francisco is 8.1°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 8.1°C. Is there anything else you would like to know?')],\n",
       " 'output': 'The current temperature in San Francisco is 8.1°C. Is there anything else you would like to know?'}"
      ]
     },
     "execution_count": 40,
     "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": 41,
   "id": "b1cd4bd2-703e-4e4e-8f5c-ae3d491a41f6",
   "metadata": {
    "height": 115
   },
   "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": 42,
   "id": "67cb6fdc-ff55-4a7b-8a39-1871006aa990",
   "metadata": {
    "height": 30
   },
   "outputs": [],
   "source": [
    "tools = [get_current_temperature, search_wikipedia, create_your_own]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "66a73e69-acfb-471e-b54d-8ac586235521",
   "metadata": {
    "height": 710
   },
   "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));"
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     "metadata": {},
     "output_type": "display_data"
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     "data": {
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       "    var html_node = toinsert[nchildren-1].children[0];\n",
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       "    var nodelist = html_node.querySelectorAll(\"script\");\n",
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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 "
   ]
  },
  {
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   "execution_count": 44,
   "id": "080c3827-87fc-4dbe-a566-ca95b3f9068e",
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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\":\"d563f99a-d9a8-49fb-80c6-30a84513958b\"},{\"id\":\"434fab47-14d0-4151-8674-389078db12b0\"},{\"id\":\"aea653ea-0458-4557-a63d-8fd00997c56a\"}],\"width\":300,\"min_width\":300,\"margin\":[5,10],\"align\":\"start\",\"placeholder\":\"Enter text here\\u2026\",\"max_length\":5000}}]}},{\"type\":\"object\",\"name\":\"Div\",\"id\":\"001f494b-5737-4923-a9ef-8b5209fa92a6\",\"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\":\"0bf692a2-67b4-411f-a86f-952b7feb125c\",\"attributes\":{\"url\":\"https://cdn.holoviz.org/panel/1.1.0/dist/css/loading.css\"}},{\"type\":\"object\",\"name\":\"ImportedStyleSheet\",\"id\":\"9fda0975-36cb-47c0-a0e4-ffce908a3af9\",\"attributes\":{\"url\":\"https://cdn.holoviz.org/panel/1.1.0/dist/css/divider.css\"}}],\"margin\":0,\"width_policy\":\"fit\",\"align\":\"start\",\"text\":\"<hr>\"}},{\"id\":\"0c8dfbe7-a40e-4b77-93f2-cf25b0c6d32d\"},{\"type\":\"object\",\"name\":\"Div\",\"id\":\"8e3d8f50-db9b-47a0-bb44-2e065d065ca1\",\"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,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\\\");\\n  background-size: auto calc(min(50%, 400px));\\n}\",{\"type\":\"object\",\"name\":\"ImportedStyleSheet\",\"id\":\"38700c5c-530f-439c-968b-53a0ae5bb0f6\",\"attributes\":{\"url\":\"https://cdn.holoviz.org/panel/1.1.0/dist/css/loading.css\"}},{\"type\":\"object\",\"name\":\"ImportedStyleSheet\",\"id\":\"302ea3c9-7da3-49e0-a020-440a0d3b7ed0\",\"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\":\"e27f68d2-efc3-49be-9b84-5ee1b8a7feb6\",\"attributes\":{\"plot_id\":\"f7772483-b487-43d8-98fd-8de3f1901b4d\",\"comm_id\":\"6e9227899d5e4830b594c25cc89284f3\",\"client_comm_id\":\"9357320494854e22aaaecf56847af9e5\"}}],\"callbacks\":{\"type\":\"map\"}}};\n",
       "  var render_items = [{\"docid\":\"656e1420-29e1-4f9d-9958-76831404496e\",\"roots\":{\"f7772483-b487-43d8-98fd-8de3f1901b4d\":\"f24ec6e2-2bbc-48c6-83cc-54577d4d93a0\"},\"root_ids\":[\"f7772483-b487-43d8-98fd-8de3f1901b4d\"]}];\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": 44,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "f7772483-b487-43d8-98fd-8de3f1901b4d"
      }
     },
     "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": "41804e2f-4dc1-4763-8893-5e76ab5d8f14",
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 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.19"
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 },
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