Add img

examples/advanced_agents/llm_compiler/LLMCompiler.ipynb

@@ -15,7 +15,26 @@
     "3. Joiner: Responds to the user or triggers a second plan\n",
     "\n",
     "\n",
-    "This notebook walks through each component and shows how to wire them together using LangGraph."
+    "![diagram](./img/diagram.png)\n",
+    "\n",
+    "\n",
+    "This notebook walks through each component and shows how to wire them together using LangGraph. First, we will set up LangSmith for tracing, and configure our environment variables."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "abbd6948-e9a3-47ca-89c7-7ac2fc5eca8b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import getpass\n",
+    "\n",
+    "os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n",
+    "os.environ[\"LANGCHAIN_PROJECT\"] = \"LLMCompiler\"\n",
+    "os.environ[\"LANGCHAIN_API_KEY\"] = getpass.getpass(\"LangSmith API Key: \")\n",
+    "os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key: \")"
    ]
   },
   {
@@ -47,7 +66,19 @@
    "execution_count": 1,
    "id": "15dd9639-691f-4906-9012-83fd6e9ac126",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "ModuleNotFoundError",
+     "evalue": "No module named 'llm_compiler'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[1], line 7\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain_core\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mrunnables\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m RunnableBranch\n\u001b[1;32m      6\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mlangchain_core\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mtools\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m BaseTool\n\u001b[0;32m----> 7\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mllm_compiler\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01moutput_parser\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m LLMCompilerPlanParser\n\u001b[1;32m      9\u001b[0m END_OF_PLAN \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m<END_OF_PLAN>\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m     12\u001b[0m \u001b[38;5;66;03m# The required extra \"tool\"\u001b[39;00m\n",
+      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'llm_compiler'"
+     ]
+    }
+   ],
    "source": [
     "from typing import Optional, Sequence\n",
     "\n",
@@ -55,7 +86,8 @@
     "from langchain_core.prompts import ChatPromptTemplate\n",
     "from langchain_core.runnables import RunnableBranch\n",
     "from langchain_core.tools import BaseTool\n",
-    "from llm_compiler.output_parser import LLMCompilerPlanParser\n",
+    "\n",
+    "from output_parser import LLMCompilerPlanParser\n",
     "\n",
     "END_OF_PLAN = \"<END_OF_PLAN>\"\n",
     "\n",
@@ -707,9 +739,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import getpass\n",
-    "import os\n",
-    "\n",
     "os.environ[\"TAVILY_API_KEY\"] = (\n",
     "    os.environ.get(\"TAVILY_API_KEY\")\n",
     "    if \"TAVILY_API_KEY\" in os.environ\n",