add jupyter notebook

Author: ToJen

agents/web_search_agent/README.md

@@ -59,7 +59,7 @@ curl -X 'POST' \
 
 4. AgentOps will automatically capture the session:
 - View the [agentops.log](agentops.log) file
-- See the[AgentOps Dashboard](https://app.agentops.ai/drilldown)
+- See the [AgentOps Dashboard](https://app.agentops.ai/drilldown)
 
 ## Dependencies
 

agents/web_search_agent/web_search_agent.ipynb

@@ -0,0 +1,108 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Web Search Agent\n",
+    "This notebook demonstrates a web search agent using SwarmZero framework and Tavily API."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "source": [
+    "import os\n",
+    "\n",
+    "import agentops\n",
+    "from dotenv import load_dotenv\n",
+    "from swarmzero import Agent\n",
+    "from tavily import TavilyClient\n",
+    "\n",
+    "load_dotenv()\n",
+    "agentops.init(os.getenv(\"AGENTOPS_API_KEY\"))\n",
+    "tavily_client = TavilyClient(api_key=os.getenv(\"TAVILY_API_KEY\"))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Define Search Functions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "source": [
+    "async def web_search(query: str) -> dict:\n",
+    "    response = tavily_client.search(query)\n",
+    "    results = []\n",
+    "    for result in response[\"results\"][:3]:\n",
+    "        results.append({\"title\": result[\"title\"], \"url\": result[\"url\"], \"content\": result[\"content\"]})\n",
+    "    return results\n",
+    "\n",
+    "\n",
+    "async def extract_from_urls(urls: list[str]) -> dict:\n",
+    "    response = tavily_client.extract(urls=urls)\n",
+    "\n",
+    "    if response[\"failed_results\"]:\n",
+    "        print(f\"Failed to extract from {response['failed_results']}\")\n",
+    "\n",
+    "    results = []\n",
+    "    for result in response[\"results\"]:\n",
+    "        results.append({\"url\": result[\"url\"], \"raw_content\": result[\"raw_content\"]})\n",
+    "\n",
+    "    return results"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Initialize and Run Agent"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "source": [
+    "my_agent = Agent(\n",
+    "    name=\"workflow-assistant\",\n",
+    "    functions=[\n",
+    "        web_search,\n",
+    "        extract_from_urls,\n",
+    "    ],\n",
+    "    config_path=\"./swarmzero_config.toml\",\n",
+    "    instruction=\"You are a helpful assistant that can search the web and extract information from a given URL.\",\n",
+    ")\n",
+    "\n",
+    "my_agent.run()  # see agent API at localhost:8000/docs"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}