start porting chat agent executor w func calling doc

langchain-ai · Aug 19, 2024 · 231339e · 231339e
1 parent 725d008
commit 231339e
Showing 1 changed file with 29 additions and 26 deletions.
diff --git a/examples/chat_agent_executor_with_function_calling/base.ipynb b/examples/chat_agent_executor_with_function_calling/base.ipynb
@@ -204,29 +204,39 @@
     "object you construct the graph with.\n",
     "\n",
     "For this example, the state we will track will just be a list of messages. We\n",
-    "want each node to just add messages to that list. Therefore, we will use an\n",
-    "object with one key (`messages`) with the value as an object:\n",
-    "`{ value: Function, default?: () => any }`\n",
+    "want each node to just add messages to that list. To do this, we define our state via the `Annotation` function, with a single attribute `messages` that is a list of `BaseMessage`s. The value of our attribute `messages` is another `Annotation` which has two sub-attributes: `reducer` and `default`. The `reducer` key must be a factory that returns a function that takes the current value of the attribute and the new value to add, and returns the new value of the attribute.\n",
     "\n",
     "The `default` key must be a factory that returns the default value for that\n",
-    "attribute."
+    "attribute (this key is optional)."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 6,
    "id": "ea793afa-2eab-4901-910d-6eed90cd6564",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "TypeError",
+     "evalue": "Cannot read properties of undefined (reading 'Root')",
+     "output_type": "error",
+     "traceback": [
+      "Stack trace:",
+      "TypeError: Cannot read properties of undefined (reading 'Root')",
+      "    at <anonymous>:3:31"
+     ]
+    }
+   ],
    "source": [
     "import { BaseMessage } from \"@langchain/core/messages\";\n",
+    "import { Annotation } from \"@langchain/langgraph\";\n",
     "\n",
-    "const agentState = {\n",
-    "  messages: {\n",
-    "    value: (x: BaseMessage[], y: BaseMessage[]) => x.concat(y),\n",
+    "const AgentState = Annotation.Root({\n",
+    "  messages: Annotation<BaseMessage[]>({\n",
+    "    reducer: (x, y) => x.concat(y),\n",
     "    default: () => [],\n",
-    "  },\n",
-    "};"
+    "  })\n",
+    "})"
    ]
   },
   {
@@ -262,17 +272,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "id": "3b541bb9-900c-40d0-964d-7b5dfee30667",
    "metadata": {},
    "outputs": [],
    "source": [
     "import { FunctionMessage } from \"@langchain/core/messages\";\n",
     "import { AgentAction } from \"@langchain/core/agents\";\n",
-    "import type { RunnableConfig } from \"@langchain/core/runnables\";\n",
     "\n",
     "// Define the function that determines whether to continue or not\n",
-    "const shouldContinue = (state: { messages: Array<BaseMessage> }) => {\n",
+    "const shouldContinue = (state: typeof AgentState.State) => {\n",
     "  const { messages } = state;\n",
     "  const lastMessage = messages[messages.length - 1];\n",
     "  // If there is no function call, then we finish\n",
@@ -287,7 +296,7 @@
     "};\n",
     "\n",
     "// Define the function to execute tools\n",
-    "const _getAction = (state: { messages: Array<BaseMessage> }): AgentAction => {\n",
+    "const _getAction = (state: typeof AgentState.State): AgentAction => {\n",
     "  const { messages } = state;\n",
     "  // Based on the continue condition\n",
     "  // we know the last message involves a function call\n",
@@ -309,9 +318,7 @@
     "};\n",
     "\n",
     "// Define the function that calls the model\n",
-    "const callModel = async (\n",
-    "  state: { messages: Array<BaseMessage> },\n",
-    ") => {\n",
+    "const callModel = async (state: typeof AgentState.State) => {\n",
     "  const { messages } = state;\n",
     "  const response = await newModel.invoke(messages);\n",
     "  // We return a list, because this will get added to the existing list\n",
@@ -320,9 +327,7 @@
     "  };\n",
     "};\n",
     "\n",
-    "const callTool = async (\n",
-    "  state: { messages: Array<BaseMessage> },\n",
-    ") => {\n",
+    "const callTool = async (state: typeof AgentState.State) => {\n",
     "  const action = _getAction(state);\n",
     "  // We call the tool_executor and get back a response\n",
     "  const response = await toolExecutor.invoke(action);\n",
@@ -348,17 +353,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "id": "813ae66c-3b58-4283-a02a-36da72a2ab90",
    "metadata": {},
    "outputs": [],
    "source": [
     "import { END, START, StateGraph } from \"@langchain/langgraph\";\n",
     "\n",
     "// Define a new graph\n",
-    "const workflow = new StateGraph({\n",
-    "  channels: agentState,\n",
-    "});\n",
+    "const workflow = new StateGraph(AgentState);\n",
     "\n",
     "// Define the two nodes we will cycle between\n",
     "workflow.addNode(\"agent\", callModel);\n",
@@ -413,7 +416,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "id": "8edb04b9-40b6-46f1-a7a8-4b2d8aba7752",
    "metadata": {},
    "outputs": [
@@ -505,7 +508,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "id": "f544977e-31f7-41f0-88c4-ec9c27b8cecb",
    "metadata": {},
    "outputs": [