chore: migrate to langchain v0.1.11

README.md

@@ -188,7 +188,7 @@ const model = new GenAIModel({
 #### Basic usage
 
 ```typescript
-const response = await model.call(
+const response = await model.invoke(
   'What would be a good company name a company that makes colorful socks?',
 );
 
@@ -198,7 +198,7 @@ console.log(response); // Fantasy Sockery
 #### LLM Chain + Prompt Template
 
 ```typescript
-import { PromptTemplate } from 'langchain/prompts';
+import { PromptTemplate } from '@langchain/core/prompts';
 import { LLMChain } from 'langchain/chains';
 
 const prompt = new PromptTemplate({
@@ -230,20 +230,22 @@ const model = new GenAIModel({
   },
 });
 
-await model.call('Tell me a joke.', undefined, [
-  {
-    handleLLMNewToken(token: string) {
-      console.log(token);
+await model.invoke('Tell me a joke.', {
+  callbacks: [
+    {
+      handleLLMNewToken(token) {
+        console.log(token);
+      },
     },
-  },
-]);
+  ],
+});
 ```
 
 #### Chat support
 
 ```typescript
 import { GenAIChatModel } from '@ibm-generative-ai/node-sdk/langchain';
-import { SystemMessage, HumanMessage } from 'langchain/schema';
+import { SystemMessage, HumanMessage } from '@langchain/core/messages';
 
 const client = new GenAIChatModel({
   modelId: 'eleutherai/gpt-neox-20b',
@@ -285,7 +287,7 @@ This can be done via helper classes provided within our SDK.
 
 ```typescript
 import { GenAIPromptTemplate } from '@ibm-generative-ai/node-sdk/langchain';
-import { PromptTemplate } from 'langchain/prompts';
+import { PromptTemplate } from '@langchain/core/prompts';
 
 // Converting the LangChain Prompt Template (f-string) to GenAI Prompt Template'
 const promptTemplate = GenAIPromptTemplate.fromLangChain(

examples/langchain/llm-chat.ts

@@ -1,4 +1,4 @@
-import { HumanMessage } from 'langchain/schema';
+import { HumanMessage } from '@langchain/core/messages';
 
 import { GenAIChatModel } from '../../src/langchain/llm-chat.js';
 
@@ -30,7 +30,7 @@ const makeClient = (stream?: boolean) =>
   // Basic
   const chat = makeClient();
 
-  const response = await chat.call([
+  const response = await chat.invoke([
     new HumanMessage(
       'What is a good name for a company that makes colorful socks?',
     ),
@@ -43,11 +43,13 @@ const makeClient = (stream?: boolean) =>
   // Streaming
   const chat = makeClient(true);
 
-  await chat.call([new HumanMessage('Tell me a joke.')], undefined, [
-    {
-      handleLLMNewToken(token) {
-        console.log(token);
+  await chat.invoke([new HumanMessage('Tell me a joke.')], {
+    callbacks: [
+      {
+        handleLLMNewToken(token) {
+          console.log(token);
+        },
       },
-    },
-  ]);
+    ],
+  });
 }

examples/langchain/llm.ts

@@ -23,7 +23,7 @@ const makeClient = (stream?: boolean) =>
 
   const prompt = 'What is a good name for a company that makes colorful socks?';
   console.info(`Request: ${prompt}`);
-  const response = await model.call(prompt);
+  const response = await model.invoke(prompt);
   console.log(`Response: ${response}`);
 }
 

examples/langchain/prompt-templates.ts

@@ -1,4 +1,4 @@
-import { PromptTemplate } from 'langchain/prompts';
+import { PromptTemplate } from '@langchain/core/prompts';
 
 import { GenAIPromptTemplate } from '../../src/langchain/index.js';
 

package.json

@@ -64,11 +64,12 @@
     "example:chat": "yarn run example:run examples/chat.ts"
   },
   "peerDependencies": {
-    "langchain": ">=0.0.155"
+    "@langchain/core": ">=0.1.11"
   },
   "devDependencies": {
     "@commitlint/cli": "^18.0.0",
     "@commitlint/config-conventional": "^18.0.0",
+    "@langchain/core": "^0.1.11",
     "@types/lodash": "^4.14.200",
     "@types/node": "^20.8.8",
     "@types/promise-retry": "^1.1.5",
@@ -83,7 +84,6 @@
     "eslint-plugin-import": "^2.29.0",
     "husky": "^8.0.3",
     "jest-extended": "^4.0.2",
-    "langchain": "^0.0.171",
     "lint-staged": "^15.0.2",
     "lodash": "^4.17.21",
     "msw": "^1.3.2",

src/langchain/llm-chat.ts

@@ -1,11 +1,14 @@
-import { BaseChatModel, BaseChatModelParams } from 'langchain/chat_models/base';
+import {
+  BaseChatModel,
+  BaseChatModelParams,
+} from '@langchain/core/language_models/chat_models';
 import {
   BaseMessage,
-  ChatResult,
   MessageType,
   SystemMessage,
-} from 'langchain/schema';
-import { CallbackManagerForLLMRun } from 'langchain/callbacks';
+} from '@langchain/core/messages';
+import { CallbackManagerForLLMRun } from '@langchain/core/callbacks/manager';
+import { ChatResult } from '@langchain/core/outputs';
 
 import { InvalidInputError } from '../errors.js';
 import { GenerateOutput } from '../client/types.js';

src/langchain/llm.ts

@@ -1,7 +1,7 @@
-import { BaseLLM, BaseLLMParams } from 'langchain/llms/base';
-import { CallbackManagerForLLMRun } from 'langchain/callbacks';
-import type { LLMResult, Generation } from 'langchain/schema';
-import { GenerationChunk } from 'langchain/schema';
+import { BaseLLM, BaseLLMParams } from '@langchain/core/language_models/llms';
+import { CallbackManagerForLLMRun } from '@langchain/core/callbacks/manager';
+import type { LLMResult, Generation } from '@langchain/core/outputs';
+import { GenerationChunk } from '@langchain/core/outputs';
 
 import { Client, Configuration } from '../client/client.js';
 import {

src/langchain/prompt-template.test.ts

@@ -1,4 +1,4 @@
-import { PromptTemplate } from 'langchain/prompts';
+import { PromptTemplate } from '@langchain/core/prompts';
 
 import { InvalidInputError } from '../errors.js';
 

src/langchain/prompt-template.ts

@@ -1,4 +1,4 @@
-import { PromptTemplate as LangChainPromptTemplate } from 'langchain/prompts';
+import { PromptTemplate as LangChainPromptTemplate } from '@langchain/core/prompts';
 
 import type { PromptTemplateOutput as PromptTemplate } from '../client/types.js';
 import { InvalidInputError } from '../errors.js';

src/tests/e2e/client.test.ts

@@ -106,9 +106,9 @@ describe('client', () => {
 
       test('should correctly process moderation chunks during streaming', async () => {
         const stream = makeValidStream({
+          min_new_tokens: 1,
+          max_new_tokens: 5,
           moderations: {
-            min_new_tokens: 1,
-            max_new_tokens: 5,
             hap: {
               input: true,
               threshold: 0.01,

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

@@ -1,4 +1,4 @@
-import { HumanMessage, SystemMessage } from 'langchain/schema';
+import { HumanMessage, SystemMessage } from '@langchain/core/messages';
 
 import { GenAIChatModel } from '../../../langchain/index.js';
 import { describeIf } from '../../utils.js';
@@ -46,7 +46,7 @@ describeIf(process.env.RUN_LANGCHAIN_CHAT_TESTS === 'true')(
       test('should handle single question', async () => {
         const chat = makeClient();
 
-        const response = await chat.call([
+        const response = await chat.invoke([
           new HumanMessage(
             'What is a good name for a company that makes colorful socks?',
           ),
@@ -57,7 +57,7 @@ describeIf(process.env.RUN_LANGCHAIN_CHAT_TESTS === 'true')(
       test('should handle question with additional hint', async () => {
         const chat = makeClient();
 
-        const response = await chat.call([
+        const response = await chat.invoke([
           new SystemMessage(SYSTEM_MESSAGE),
           new HumanMessage('I love programming.'),
         ]);
@@ -94,14 +94,11 @@ describeIf(process.env.RUN_LANGCHAIN_CHAT_TESTS === 'true')(
           tokens.push(token);
         });
 
-        const output = await chat.call(
+        const output = await chat.invoke(
           [new HumanMessage('Tell me a joke.')],
-          undefined,
-          [
-            {
-              handleLLMNewToken: handleNewToken,
-            },
-          ],
+          {
+            callbacks: [{ handleLLMNewToken: handleNewToken }],
+          },
         );
 
         expect(handleNewToken).toHaveBeenCalled();

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

@@ -1,5 +1,5 @@
-import { PromptTemplate } from 'langchain/prompts';
-import { LLMChain } from 'langchain/chains';
+import { PromptTemplate } from '@langchain/core/prompts';
+import { StringOutputParser } from '@langchain/core/output_parsers';
 
 import { GenAIModel } from '../../../langchain/llm.js';
 
@@ -39,14 +39,14 @@ describe('Langchain', () => {
     test.skip('should handle empty modelId', async () => {
       const client = makeClient();
 
-      const data = await client.call('Who are you?');
+      const data = await client.invoke('Who are you?');
       expectIsString(data);
     }, 15_000);
 
     test('should return correct response for a single input', async () => {
       const client = makeClient('google/flan-ul2');
 
-      const data = await client.call('Hello, World');
+      const data = await client.invoke('Hello, World');
       expectIsString(data);
     }, 15_000);
 
@@ -97,7 +97,7 @@ describe('Langchain', () => {
       const model = makeClient('google/flan-ul2');
 
       await expect(
-        model.call('Hello, World', { timeout: 10 }),
+        model.invoke('Hello, World', { timeout: 10 }),
       ).rejects.toThrow();
     });
 
@@ -109,11 +109,13 @@ describe('Langchain', () => {
         tokens.push(token);
       });
 
-      const output = await client.call('Tell me a joke.', undefined, [
-        {
-          handleLLMNewToken: handleNewToken,
-        },
-      ]);
+      const output = await client.invoke('Tell me a joke.', {
+        callbacks: [
+          {
+            handleLLMNewToken: handleNewToken,
+          },
+        ],
+      });
 
       expect(handleNewToken).toHaveBeenCalled();
       expectIsString(output);
@@ -129,9 +131,10 @@ describe('Langchain', () => {
         template: 'What is a good name for a company that makes {product}?',
         inputVariables: ['product'],
       });
+      const outputParser = new StringOutputParser();
 
-      const chain = new LLMChain({ llm: model, prompt: prompt });
-      const { text } = await chain.call({ product: 'colorful socks' });
+      const chain = prompt.pipe(model).pipe(outputParser);
+      const text = await chain.invoke({ product: 'colorful socks' });
       expectIsString(text);
     }, 20_000);
   });