chore(langchain): updates

README.md

@@ -243,6 +243,7 @@ await model.call('Tell me a joke.', undefined, [
 
 ```typescript
 import { GenAIChatModel } from '@ibm-generative-ai/node-sdk/langchain';
+import { SystemMessage, HumanMessage } from 'langchain/schema';
 
 const client = new GenAIChatModel({
   modelId: 'eleutherai/gpt-neox-20b',
@@ -268,13 +269,13 @@ const client = new GenAIChatModel({
 });
 
 const response = await client.call([
-  new SystemChatMessage(
+  new SystemMessage(
     'You are a helpful assistant that translates English to Spanish.',
   ),
-  new HumanChatMessage('I love programming.'),
+  new HumanMessage('I love programming.'),
 ]);
 
-console.info(response.text); // "Me encanta la programación."
+console.info(response.content); // "Me encanta la programación."
 ```
 
 #### Prompt Templates (GenAI x LangChain)

examples/langchain/llm-chat.ts

@@ -1,4 +1,4 @@
-import { HumanChatMessage } from 'langchain/schema';
+import { HumanMessage } from 'langchain/schema';
 
 import { GenAIChatModel } from '../../src/langchain/llm-chat.js';
 
@@ -31,7 +31,7 @@ const makeClient = (stream?: boolean) =>
   const chat = makeClient();
 
   const response = await chat.call([
-    new HumanChatMessage(
+    new HumanMessage(
       'What is a good name for a company that makes colorful socks?',
     ),
   ]);
@@ -43,7 +43,7 @@ const makeClient = (stream?: boolean) =>
   // Streaming
   const chat = makeClient(true);
 
-  await chat.call([new HumanChatMessage('Tell me a joke.')], undefined, [
+  await chat.call([new HumanMessage('Tell me a joke.')], undefined, [
     {
       handleLLMNewToken(token) {
         console.log(token);

examples/langchain/llm.ts

@@ -0,0 +1,49 @@
+import { GenAIModel } from '../../src/langchain/index.js';
+
+const makeClient = (stream?: boolean) =>
+  new GenAIModel({
+    modelId: 'google/flan-t5-xl',
+    stream,
+    configuration: {
+      endpoint: process.env.ENDPOINT,
+      apiKey: process.env.API_KEY,
+    },
+    parameters: {
+      decoding_method: 'greedy',
+      min_new_tokens: 5,
+      max_new_tokens: 25,
+      repetition_penalty: 1.5,
+    },
+  });
+
+{
+  // Basic
+  console.info('---Single Input Example---');
+  const model = makeClient();
+
+  const prompt = 'What is a good name for a company that makes colorful socks?';
+  console.info(`Request: ${prompt}`);
+  const response = await model.call(prompt);
+  console.log(`Response: ${response}`);
+}
+
+{
+  console.info('---Multiple Inputs Example---');
+  const model = makeClient();
+
+  const prompts = ['What is IBM?', 'What is WatsonX?'];
+  console.info('Request prompts:', prompts);
+  const response = await model.generate(prompts);
+  console.info('Response:', response);
+}
+
+{
+  console.info('---Streaming Example---');
+  const chat = makeClient(true);
+
+  const prompt = 'What is a molecule?';
+  console.info(`Request: ${prompt}`);
+  for await (const token of await chat.stream(prompt)) {
+    console.info(`Received token: ${token}`);
+  }
+}

src/langchain/llm-chat.ts

@@ -74,7 +74,7 @@ export class GenAIChatModel extends BaseChatModel {
             `Unsupported message type "${msg._getType()}"`,
           );
         }
-        return `${type.stopSequence}${msg.text}`;
+        return `${type.stopSequence}${msg.content}`;
       })
       .join('\n')
       .concat(this.#rolesMapping.system.stopSequence);

src/tests/e2e/langchain/llm-chat.test.ts

@@ -1,4 +1,4 @@
-import { HumanChatMessage, SystemChatMessage } from 'langchain/schema';
+import { HumanMessage, SystemMessage } from 'langchain/schema';
 
 import { GenAIChatModel } from '../../../langchain/index.js';
 import { describeIf } from '../../utils.js';
@@ -47,34 +47,34 @@ describeIf(process.env.RUN_LANGCHAIN_CHAT_TESTS === 'true')(
         const chat = makeClient();
 
         const response = await chat.call([
-          new HumanChatMessage(
+          new HumanMessage(
             'What is a good name for a company that makes colorful socks?',
           ),
         ]);
-        expectIsNonEmptyString(response.text);
+        expectIsNonEmptyString(response.content);
       });
 
       test('should handle question with additional hint', async () => {
         const chat = makeClient();
 
         const response = await chat.call([
-          new SystemChatMessage(SYSTEM_MESSAGE),
-          new HumanChatMessage('I love programming.'),
+          new SystemMessage(SYSTEM_MESSAGE),
+          new HumanMessage('I love programming.'),
         ]);
-        expectIsNonEmptyString(response.text);
+        expectIsNonEmptyString(response.content);
       });
 
       test('should handle multiple questions', async () => {
         const chat = makeClient();
 
         const response = await chat.generate([
           [
-            new SystemChatMessage(SYSTEM_MESSAGE),
-            new HumanChatMessage('I love programming.'),
+            new SystemMessage(SYSTEM_MESSAGE),
+            new HumanMessage('I love programming.'),
           ],
           [
-            new SystemChatMessage(SYSTEM_MESSAGE),
-            new HumanChatMessage('I love artificial intelligence.'),
+            new SystemMessage(SYSTEM_MESSAGE),
+            new HumanMessage('I love artificial intelligence.'),
           ],
         ]);
 
@@ -95,7 +95,7 @@ describeIf(process.env.RUN_LANGCHAIN_CHAT_TESTS === 'true')(
         });
 
         const output = await chat.call(
-          [new HumanChatMessage('Tell me a joke.')],
+          [new HumanMessage('Tell me a joke.')],
           undefined,
           [
             {
@@ -105,8 +105,8 @@ describeIf(process.env.RUN_LANGCHAIN_CHAT_TESTS === 'true')(
         );
 
         expect(handleNewToken).toHaveBeenCalled();
-        expectIsNonEmptyString(output.text);
-        expect(tokens.join('')).toStrictEqual(output.text);
+        expectIsNonEmptyString(output.content);
+        expect(tokens.join('')).toStrictEqual(output.content);
       });
     });
   },