introduced nb/chatbot_agentic_prebuilt.ipynb

notebooks/chatbot_agentic_prebuilt.ipynb

@@ -0,0 +1,106 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain_openai import ChatOpenAI\n",
+    "from langchain_community.tools import WikipediaQueryRun\n",
+    "from langchain_community.utilities import WikipediaAPIWrapper\n",
+    "from langchain_community.tools import DuckDuckGoSearchResults\n",
+    "from langchain_community.tools.yahoo_finance_news import YahooFinanceNewsTool\n",
+    "from langchain_core.messages import HumanMessage\n",
+    "from langgraph.checkpoint.memory import MemorySaver\n",
+    "from langgraph.prebuilt import create_react_agent\n",
+    "from langchain_core.tools import tool"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "@tool\n",
+    "def tool_mult(a: int, b: int) -> int:\n",
+    "    'Multiplies two given numbers'\n",
+    "    return a * b\n",
+    "\n",
+    "@tool\n",
+    "def tool_add(a:int, b:int) -> int:\n",
+    "    'Adds two given numbers'\n",
+    "    return a + b"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# create the agent\n",
+    "memory = MemorySaver()\n",
+    "llm = ChatOpenAI(model_name=\"gpt-4o-mini\", temperature=0)\n",
+    "tool_search = DuckDuckGoSearchResults(max_results=2)\n",
+    "tool_finance = YahooFinanceNewsTool()\n",
+    "tool_wiki = WikipediaQueryRun(\n",
+    "    api_wrapper=WikipediaAPIWrapper(\n",
+    "        top_k_results=2,\n",
+    "        doc_content_chars_max=500))\n",
+    "\n",
+    "tools = [tool_search, tool_finance, tool_wiki, tool_mult, tool_add]\n",
+    "agent_executor = create_react_agent(\n",
+    "    llm,\n",
+    "    tools,\n",
+    "    checkpointer = memory\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# use the agent\n",
+    "config = {'configurable': {'thread_id': '1'}}\n",
+    "\n",
+    "user_input = input(\"User: \")\n",
+    "\n",
+    "for chunk in agent_executor.stream(\n",
+    "    {\"messages\": [HumanMessage(content=user_input)]},\n",
+    "     config):\n",
+    "    print(chunk)\n",
+    "\n",
+    "# response = agent_executor.invoke(\n",
+    "#     input={\"messages\": [HumanMessage(content=user_input)]},\n",
+    "#     config=config)\n",
+    "# for chunk in response['messages']:\n",
+    "#     print(chunk)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "langchain_311",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}