cohere[minor]: Add support for tool calling cohere

docs/core_docs/docs/integrations/chat/cohere.mdx

@@ -62,6 +62,14 @@ import StatefulChatExample from "@examples/models/chat/cohere/stateful_conversat
 You can see the LangSmith traces from this example [here](https://smith.langchain.com/public/8e67b05a-4e63-414e-ac91-a91acf21b262/r) and [here](https://smith.langchain.com/public/50fabc25-46fe-4727-a59c-7e4eb0de8e70/r)
 :::
 
+### Tools
+
+The Cohere API supports tool calling, along with multi-hop-tool calling. The following example demonstrates how to call tools:
+
+import ToolCallingExample from "@examples/models/chat/cohere/tool_calling.ts";
+
+<CodeBlock language="typescript">{ToolCallingExample}</CodeBlock>
+
 ### RAG
 
 Cohere also comes out of the box with RAG support.

examples/src/models/chat/cohere/chat_cohere.ts

@@ -3,7 +3,6 @@ import { ChatPromptTemplate } from "@langchain/core/prompts";
 
 const model = new ChatCohere({
   apiKey: process.env.COHERE_API_KEY, // Default
-  model: "command", // Default
 });
 const prompt = ChatPromptTemplate.fromMessages([
   ["ai", "You are a helpful assistant"],

examples/src/models/chat/cohere/chat_stream_cohere.ts

@@ -4,7 +4,6 @@ import { StringOutputParser } from "@langchain/core/output_parsers";
 
 const model = new ChatCohere({
   apiKey: process.env.COHERE_API_KEY, // Default
-  model: "command", // Default
 });
 const prompt = ChatPromptTemplate.fromMessages([
   ["ai", "You are a helpful assistant"],

examples/src/models/chat/cohere/connectors.ts

@@ -3,7 +3,6 @@ import { HumanMessage } from "@langchain/core/messages";
 
 const model = new ChatCohere({
   apiKey: process.env.COHERE_API_KEY, // Default
-  model: "command", // Default
 });
 
 const response = await model.invoke(

examples/src/models/chat/cohere/rag.ts

@@ -3,7 +3,6 @@ import { HumanMessage } from "@langchain/core/messages";
 
 const model = new ChatCohere({
   apiKey: process.env.COHERE_API_KEY, // Default
-  model: "command", // Default
 });
 
 const documents = [

examples/src/models/chat/cohere/stateful_conversation.ts

@@ -3,7 +3,6 @@ import { HumanMessage } from "@langchain/core/messages";
 
 const model = new ChatCohere({
   apiKey: process.env.COHERE_API_KEY, // Default
-  model: "command", // Default
 });
 
 const conversationId = `demo_test_id-${Math.random()}`;

examples/src/models/chat/cohere/tool_calling.ts

@@ -0,0 +1,57 @@
+import { ChatCohere } from "@langchain/cohere";
+import { HumanMessage } from "@langchain/core/messages";
+import { z } from "zod";
+import { DynamicStructuredTool } from "@langchain/core/tools";
+
+const model = new ChatCohere({
+  apiKey: process.env.COHERE_API_KEY, // Default
+});
+
+const magicFunctionTool = new DynamicStructuredTool({
+  name: "magic_function",
+  description: "Apply a magic function to the input number",
+  schema: z.object({
+    num: z.number().describe("The number to apply the magic function for"),
+  }),
+  func: async ({ num }) => {
+    return `The magic function of ${num} is ${num + 5}`;
+  },
+});
+
+const tools = [magicFunctionTool];
+const modelWithTools = model.bindTools(tools);
+
+const messages = [new HumanMessage("What is the magic function of number 5?")];
+const response = await modelWithTools.invoke(messages);
+/*
+  AIMessage {
+    content: 'I will use the magic_function tool to answer this question.',
+    name: undefined,
+    additional_kwargs: {
+      response_id: 'd0b189e5-3dbf-493c-93f8-99ed4b01d96d',
+      generationId: '8982a68f-c64c-48f8-bf12-0b4bea0018b6',
+      chatHistory: [ [Object], [Object] ],
+      finishReason: 'COMPLETE',
+      meta: { apiVersion: [Object], billedUnits: [Object], tokens: [Object] },
+      toolCalls: [ [Object] ]
+    },
+    response_metadata: {
+      estimatedTokenUsage: { completionTokens: 54, promptTokens: 920, totalTokens: 974 },
+      response_id: 'd0b189e5-3dbf-493c-93f8-99ed4b01d96d',
+      generationId: '8982a68f-c64c-48f8-bf12-0b4bea0018b6',
+      chatHistory: [ [Object], [Object] ],
+      finishReason: 'COMPLETE',
+      meta: { apiVersion: [Object], billedUnits: [Object], tokens: [Object] },
+      toolCalls: [ [Object] ]
+    },
+    tool_calls: [
+      {
+        name: 'magic_function',
+        args: [Object],
+        id: '4ec98550-ba9a-4043-adfe-566230e5'
+      }
+    ],
+    invalid_tool_calls: [],
+    usage_metadata: { input_tokens: 920, output_tokens: 54, total_tokens: 974 }
+  }
+*/

libs/langchain-cohere/.eslintrc.cjs

@@ -33,6 +33,7 @@ module.exports = {
     "@typescript-eslint/no-unused-vars": ["warn", { args: "none" }],
     "@typescript-eslint/no-floating-promises": "error",
     "@typescript-eslint/no-misused-promises": "error",
+    "arrow-body-style": 0,
     camelcase: 0,
     "class-methods-use-this": 0,
     "import/extensions": [2, "ignorePackages"],

libs/langchain-cohere/package.json

@@ -35,8 +35,11 @@
   "author": "LangChain",
   "license": "MIT",
   "dependencies": {
-    "@langchain/core": ">=0.2.5 <0.3.0",
-    "cohere-ai": "^7.10.5"
+    "@langchain/core": ">=0.2.14 <0.3.0",
+    "cohere-ai": "^7.10.5",
+    "uuid": "^10.0.0",
+    "zod": "^3.23.8",
+    "zod-to-json-schema": "^3.23.1"
   },
   "devDependencies": {
     "@jest/globals": "^29.5.0",