Requirements removed time

agent_workshop.ipynb

@@ -0,0 +1,218 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "fc9a9b11",
+   "metadata": {},
+   "source": [
+    "## Build and Test the Agent\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7c721e15",
+   "metadata": {},
+   "source": [
+    "**Fetch Questions**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "a8ff3339",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import requests\n",
+    "\n",
+    "DEFAULT_API_URL = \"https://agents-course-unit4-scoring.hf.space\"\n",
+    "\n",
+    "api_url = DEFAULT_API_URL\n",
+    "questions_url = f\"{api_url}/questions\"\n",
+    "submit_url = f\"{api_url}/submit\"\n",
+    "\n",
+    "response = requests.get(questions_url)\n",
+    "response.raise_for_status()\n",
+    "questions_data = response.json()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "da4bec7d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Question 1: How many studio albums were published by Mercedes Sosa between 2000 and 2009 (included)? You can use the latest 2022 version of english wikipedia.\n",
+      "Question 2: In the video https://www.youtube.com/watch?v=L1vXCYZAYYM, what is the highest number of bird species to be on camera simultaneously?\n",
+      "Question 3: .rewsna eht sa \"tfel\" drow eht fo etisoppo eht etirw ,ecnetnes siht dnatsrednu uoy fI\n",
+      "Question 4: Review the chess position provided in the image. It is black's turn. Provide the correct next move for black which guarantees a win. Please provide your response in algebraic notation.\n",
+      "Question 5: Who nominated the only Featured Article on English Wikipedia about a dinosaur that was promoted in November 2016?\n"
+     ]
+    }
+   ],
+   "source": [
+    "for i, item in enumerate(questions_data[0:5]):\n",
+    "    print(f\"Question {i + 1}: {item['question']}\")\n",
+    "\n",
+    "\n",
+    "# Example\n",
+    "#questions_data[3]\n",
+    "# questions_data[0:5]\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1efa91ee",
+   "metadata": {},
+   "source": [
+    "## BUILD AGENT\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3b6e6e2b",
+   "metadata": {},
+   "source": [
+    "**Log in to HF for Serverless API**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "131f40b4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#from huggingface_hub import login\n",
+    "\n",
+    "#login()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "91d64b9f",
+   "metadata": {},
+   "source": [
+    "**Use a Local LLM Model**\n",
+    "\n",
+    "**LiteLLMModel** allows to easily use a wide range of LLM models. To use local ollama model the model name must be prefixed by `ollama/` at the model_id. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "48f92e59",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from smolagents import LiteLLMModel\n",
+    "\n",
+    "model = LiteLLMModel(\n",
+    "    model_id = \"ollama/llama3.2:latest\",\n",
+    "    api_base = \"http://127.0.0.1:11434\",\n",
+    "    num_ctx = 8192,\n",
+    "\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7dbaa9ed",
+   "metadata": {},
+   "source": [
+    "### **Small Agents**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "251b8788",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from smolagents import CodeAgent, DuckDuckGoSearchTool, ToolCallingAgent\n",
+    "\n",
+    "code_agent = CodeAgent(tools=[DuckDuckGoSearchTool()], model=model,\n",
+    "    name=\"CodeAgent\",\n",
+    "    description=\"A code agent that can write and execute code to answer questions.\",\n",
+    "    max_steps=5,\n",
+    ")\n",
+    "\n",
+    "Web_Search_agent = ToolCallingAgent(tools=[DuckDuckGoSearchTool()], model=model,\n",
+    "    name=\"Web_Search_agent\",\n",
+    "    description=\"A web search agent that can answer questions using the DuckDuckGo search engine.\",\n",
+    "    max_steps=5,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "aaf5c107",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#agent.run(\"Search for the best music recommendations for a party at the Wayne's mansion.\")\n",
+    "\n",
+    "# agent.run(questions_data[0]['question'])\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "c6b67e26",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "search_tool = DuckDuckGoSearchTool()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "d13e0a38",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "manager_agent = CodeAgent(\n",
+    "    model=model,\n",
+    "    name=\"ManagerAgent\",\n",
+    "    tools=[search_tool],\n",
+    "    managed_agents=[code_agent, Web_Search_agent],\n",
+    "    description=\"A manager agent that coordinates other agents to answer questions.\",\n",
+    "    additional_authorized_imports=[],\n",
+    "    planning_interval=5,\n",
+    "    verbosity_level=2,\n",
+    "    final_answer_checks=[],\n",
+    "    max_steps=15,\n",
+    ")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Agents-HuggingFace-ENV",
+   "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": "3.10.16"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

requirements.txt

@@ -1,4 +1,3 @@
 gradio
 requests
-smolagents
-time
+smolagents