fix(community) : Upgrade node-llama-cpp to be compatible with version 3

docs/core_docs/docs/integrations/chat/llama_cpp.mdx

@@ -12,14 +12,14 @@ This module is based on the [node-llama-cpp](https://github.com/withcatai/node-l
 
 ## Setup
 
-You'll need to install major version `2` of the [node-llama-cpp](https://github.com/withcatai/node-llama-cpp) module to communicate with your local model.
+You'll need to install major version `3` of the [node-llama-cpp](https://github.com/withcatai/node-llama-cpp) module to communicate with your local model.
 
 import IntegrationInstallTooltip from "@mdx_components/integration_install_tooltip.mdx";
 
 <IntegrationInstallTooltip></IntegrationInstallTooltip>
 
 ```bash npm2yarn
-npm install -S node-llama-cpp@2 @langchain/community @langchain/core
+npm install -S node-llama-cpp@3 @langchain/community @langchain/core
 ```
 
 You will also need a local Llama 2 model (or a model supported by [node-llama-cpp](https://github.com/withcatai/node-llama-cpp)). You will need to pass the path to this model to the LlamaCpp module as a part of the parameters (see example).

docs/core_docs/docs/integrations/llms/llama_cpp.mdx

@@ -12,10 +12,10 @@ This module is based on the [node-llama-cpp](https://github.com/withcatai/node-l
 
 ## Setup
 
-You'll need to install major version `2` of the [node-llama-cpp](https://github.com/withcatai/node-llama-cpp) module to communicate with your local model.
+You'll need to install major version `3` of the [node-llama-cpp](https://github.com/withcatai/node-llama-cpp) module to communicate with your local model.
 
 ```bash npm2yarn
-npm install -S node-llama-cpp@2
+npm install -S node-llama-cpp@3
 ```
 
 import IntegrationInstallTooltip from "@mdx_components/integration_install_tooltip.mdx";

docs/core_docs/docs/integrations/text_embedding/llama_cpp.mdx

@@ -12,10 +12,10 @@ This module is based on the [node-llama-cpp](https://github.com/withcatai/node-l
 
 ## Setup
 
-You'll need to install major version `2` of the [node-llama-cpp](https://github.com/withcatai/node-llama-cpp) module to communicate with your local model.
+You'll need to install major version `3` of the [node-llama-cpp](https://github.com/withcatai/node-llama-cpp) module to communicate with your local model.
 
 ```bash npm2yarn
-npm install -S node-llama-cpp@2
+npm install -S node-llama-cpp@3
 ```
 
 import IntegrationInstallTooltip from "@mdx_components/integration_install_tooltip.mdx";

examples/src/embeddings/llama_cpp_basic.ts

@@ -2,7 +2,7 @@ import { LlamaCppEmbeddings } from "@langchain/community/embeddings/llama_cpp";
 
 const llamaPath = "/Replace/with/path/to/your/model/gguf-llama2-q4_0.bin";
 
-const embeddings = new LlamaCppEmbeddings({
+const embeddings = await LlamaCppEmbeddings.initialize({
   modelPath: llamaPath,
 });
 

examples/src/embeddings/llama_cpp_docs.ts

@@ -4,7 +4,7 @@ const llamaPath = "/Replace/with/path/to/your/model/gguf-llama2-q4_0.bin";
 
 const documents = ["Hello World!", "Bye Bye!"];
 
-const embeddings = new LlamaCppEmbeddings({
+const embeddings = await LlamaCppEmbeddings.initialize({
   modelPath: llamaPath,
 });
 

examples/src/models/chat/integration_llama_cpp.ts

@@ -3,7 +3,7 @@ import { HumanMessage } from "@langchain/core/messages";
 
 const llamaPath = "/Replace/with/path/to/your/model/gguf-llama2-q4_0.bin";
 
-const model = new ChatLlamaCpp({ modelPath: llamaPath });
+const model = await ChatLlamaCpp.initialize({ modelPath: llamaPath });
 
 const response = await model.invoke([
   new HumanMessage({ content: "My name is John." }),

examples/src/models/chat/integration_llama_cpp_chain.ts

@@ -4,7 +4,10 @@ import { PromptTemplate } from "@langchain/core/prompts";
 
 const llamaPath = "/Replace/with/path/to/your/model/gguf-llama2-q4_0.bin";
 
-const model = new ChatLlamaCpp({ modelPath: llamaPath, temperature: 0.5 });
+const model = await ChatLlamaCpp.initialize({
+  modelPath: llamaPath,
+  temperature: 0.5,
+});
 
 const prompt = PromptTemplate.fromTemplate(
   "What is a good name for a company that makes {product}?"

examples/src/models/chat/integration_llama_cpp_stream.ts

@@ -2,7 +2,10 @@ import { ChatLlamaCpp } from "@langchain/community/chat_models/llama_cpp";
 
 const llamaPath = "/Replace/with/path/to/your/model/gguf-llama2-q4_0.bin";
 
-const model = new ChatLlamaCpp({ modelPath: llamaPath, temperature: 0.7 });
+const model = await ChatLlamaCpp.initialize({
+  modelPath: llamaPath,
+  temperature: 0.7,
+});
 
 const stream = await model.stream("Tell me a short story about a happy Llama.");
 

examples/src/models/chat/integration_llama_cpp_stream_invoke.ts

@@ -3,7 +3,10 @@ import { SystemMessage, HumanMessage } from "@langchain/core/messages";
 
 const llamaPath = "/Replace/with/path/to/your/model/gguf-llama2-q4_0.bin";
 
-const model = new ChatLlamaCpp({ modelPath: llamaPath, temperature: 0.7 });
+const model = await ChatLlamaCpp.initialize({
+  modelPath: llamaPath,
+  temperature: 0.7,
+});
 
 const controller = new AbortController();
 

examples/src/models/chat/integration_llama_cpp_stream_multi.ts

@@ -3,7 +3,10 @@ import { SystemMessage, HumanMessage } from "@langchain/core/messages";
 
 const llamaPath = "/Replace/with/path/to/your/model/gguf-llama2-q4_0.bin";
 
-const llamaCpp = new ChatLlamaCpp({ modelPath: llamaPath, temperature: 0.7 });
+const llamaCpp = await ChatLlamaCpp.initialize({
+  modelPath: llamaPath,
+  temperature: 0.7,
+});
 
 const stream = await llamaCpp.stream([
   new SystemMessage(

examples/src/models/chat/integration_llama_cpp_system.ts

@@ -3,7 +3,7 @@ import { SystemMessage, HumanMessage } from "@langchain/core/messages";
 
 const llamaPath = "/Replace/with/path/to/your/model/gguf-llama2-q4_0.bin";
 
-const model = new ChatLlamaCpp({ modelPath: llamaPath });
+const model = await ChatLlamaCpp.initialize({ modelPath: llamaPath });
 
 const response = await model.invoke([
   new SystemMessage(

examples/src/models/llm/llama_cpp.ts

@@ -3,7 +3,7 @@ import { LlamaCpp } from "@langchain/community/llms/llama_cpp";
 const llamaPath = "/Replace/with/path/to/your/model/gguf-llama2-q4_0.bin";
 const question = "Where do Llamas come from?";
 
-const model = new LlamaCpp({ modelPath: llamaPath });
+const model = await LlamaCpp.initialize({ modelPath: llamaPath });
 
 console.log(`You: ${question}`);
 const response = await model.invoke(question);

examples/src/models/llm/llama_cpp_stream.ts

@@ -2,7 +2,10 @@ import { LlamaCpp } from "@langchain/community/llms/llama_cpp";
 
 const llamaPath = "/Replace/with/path/to/your/model/gguf-llama2-q4_0.bin";
 
-const model = new LlamaCpp({ modelPath: llamaPath, temperature: 0.7 });
+const model = await LlamaCpp.initialize({
+  modelPath: llamaPath,
+  temperature: 0.7,
+});
 
 const prompt = "Tell me a short story about a happy Llama.";
 

libs/langchain-community/package.json

@@ -187,7 +187,7 @@
     "mongodb": "^5.2.0",
     "mysql2": "^3.9.8",
     "neo4j-driver": "^5.17.0",
-    "node-llama-cpp": "^2",
+    "node-llama-cpp": "3.1.1",
     "notion-to-md": "^3.1.0",
     "officeparser": "^4.0.4",
     "pdf-parse": "1.1.1",

libs/langchain-community/src/chat_models/llama_cpp.ts

@@ -3,7 +3,11 @@ import {
   LlamaModel,
   LlamaContext,
   LlamaChatSession,
-  type ConversationInteraction,
+  type Token,
+  ChatUserMessage,
+  ChatModelResponse,
+  ChatHistoryItem,
+  getLlama,
 } from "node-llama-cpp";
 
 import {
@@ -47,7 +51,7 @@ export interface LlamaCppCallOptions extends BaseLanguageModelCallOptions {
  * @example
  * ```typescript
  * // Initialize the ChatLlamaCpp model with the path to the model binary file.
- * const model = new ChatLlamaCpp({
+ * const model = await ChatLlamaCpp.initialize({
  *   modelPath: "/Replace/with/path/to/your/model/gguf-llama2-q4_0.bin",
  *   temperature: 0.5,
  * });
@@ -87,20 +91,35 @@ export class ChatLlamaCpp extends SimpleChatModel<LlamaCppCallOptions> {
     return "ChatLlamaCpp";
   }
 
-  constructor(inputs: LlamaCppInputs) {
+  public constructor(inputs: LlamaCppInputs) {
     super(inputs);
     this.maxTokens = inputs?.maxTokens;
     this.temperature = inputs?.temperature;
     this.topK = inputs?.topK;
     this.topP = inputs?.topP;
     this.trimWhitespaceSuffix = inputs?.trimWhitespaceSuffix;
-    this._model = createLlamaModel(inputs);
-    this._context = createLlamaContext(this._model, inputs);
     this._session = null;
   }
 
+  /**
+   * Initializes the llama_cpp model for usage in the chat models wrapper.
+   * @param inputs - the inputs passed onto the model.
+   * @returns A Promise that resolves to the ChatLlamaCpp type class.
+   */
+  public static async initialize(
+    inputs: LlamaBaseCppInputs
+  ): Promise<ChatLlamaCpp> {
+    const instance = new ChatLlamaCpp(inputs);
+    const llama = await getLlama();
+
+    instance._model = await createLlamaModel(inputs, llama);
+    instance._context = await createLlamaContext(instance._model, inputs);
+
+    return instance;
+  }
+
   _llmType() {
-    return "llama2_cpp";
+    return "llama_cpp";
   }
 
   /** @ignore */
@@ -146,7 +165,9 @@ export class ChatLlamaCpp extends SimpleChatModel<LlamaCppCallOptions> {
         signal: options.signal,
         onToken: async (tokens: number[]) => {
           options.onToken?.(tokens);
-          await runManager?.handleLLMNewToken(this._context.decode(tokens));
+          await runManager?.handleLLMNewToken(
+            this._model.detokenize(tokens.map((num) => num as Token))
+          );
         },
         maxTokens: this?.maxTokens,
         temperature: this?.temperature,
@@ -180,20 +201,23 @@ export class ChatLlamaCpp extends SimpleChatModel<LlamaCppCallOptions> {
     };
 
     const prompt = this._buildPrompt(input);
+    const sequence = this._context.getSequence();
 
     const stream = await this.caller.call(async () =>
-      this._context.evaluate(this._context.encode(prompt), promptOptions)
+      sequence.evaluate(this._model.tokenize(prompt), promptOptions)
     );
 
     for await (const chunk of stream) {
       yield new ChatGenerationChunk({
-        text: this._context.decode([chunk]),
+        text: this._model.detokenize([chunk]),
         message: new AIMessageChunk({
-          content: this._context.decode([chunk]),
+          content: this._model.detokenize([chunk]),
         }),
         generationInfo: {},
       });
-      await runManager?.handleLLMNewToken(this._context.decode([chunk]) ?? "");
+      await runManager?.handleLLMNewToken(
+        this._model.detokenize([chunk]) ?? ""
+      );
     }
   }
 
@@ -202,12 +226,12 @@ export class ChatLlamaCpp extends SimpleChatModel<LlamaCppCallOptions> {
     let prompt = "";
     let sysMessage = "";
     let noSystemMessages: BaseMessage[] = [];
-    let interactions: ConversationInteraction[] = [];
+    let interactions: ChatHistoryItem[] = [];
 
     // Let's see if we have a system message
-    if (messages.findIndex((msg) => msg._getType() === "system") !== -1) {
+    if (messages.findIndex((msg) => msg.getType() === "system") !== -1) {
       const sysMessages = messages.filter(
-        (message) => message._getType() === "system"
+        (message) => message.getType() === "system"
       );
 
       const systemMessageContent = sysMessages[sysMessages.length - 1].content;
@@ -222,7 +246,7 @@ export class ChatLlamaCpp extends SimpleChatModel<LlamaCppCallOptions> {
 
       // Now filter out the system messages
       noSystemMessages = messages.filter(
-        (message) => message._getType() !== "system"
+        (message) => message.getType() !== "system"
       );
     } else {
       noSystemMessages = messages;
@@ -231,9 +255,7 @@ export class ChatLlamaCpp extends SimpleChatModel<LlamaCppCallOptions> {
     // Lets see if we just have a prompt left or are their previous interactions?
     if (noSystemMessages.length > 1) {
       // Is the last message a prompt?
-      if (
-        noSystemMessages[noSystemMessages.length - 1]._getType() === "human"
-      ) {
+      if (noSystemMessages[noSystemMessages.length - 1].getType() === "human") {
         const finalMessageContent =
           noSystemMessages[noSystemMessages.length - 1].content;
         if (typeof finalMessageContent !== "string") {
@@ -261,23 +283,23 @@ export class ChatLlamaCpp extends SimpleChatModel<LlamaCppCallOptions> {
     // Now lets construct a session according to what we got
     if (sysMessage !== "" && interactions.length > 0) {
       this._session = new LlamaChatSession({
-        context: this._context,
-        conversationHistory: interactions,
+        contextSequence: this._context.getSequence(),
         systemPrompt: sysMessage,
       });
+      this._session.setChatHistory(interactions);
     } else if (sysMessage !== "" && interactions.length === 0) {
       this._session = new LlamaChatSession({
-        context: this._context,
+        contextSequence: this._context.getSequence(),
         systemPrompt: sysMessage,
       });
     } else if (sysMessage === "" && interactions.length > 0) {
       this._session = new LlamaChatSession({
-        context: this._context,
-        conversationHistory: interactions,
+        contextSequence: this._context.getSequence(),
       });
+      this._session.setChatHistory(interactions);
     } else {
       this._session = new LlamaChatSession({
-        context: this._context,
+        contextSequence: this._context.getSequence(),
       });
     }
 
@@ -287,8 +309,8 @@ export class ChatLlamaCpp extends SimpleChatModel<LlamaCppCallOptions> {
   // This builds a an array of interactions
   protected _convertMessagesToInteractions(
     messages: BaseMessage[]
-  ): ConversationInteraction[] {
-    const result: ConversationInteraction[] = [];
+  ): ChatHistoryItem[] {
+    const result: ChatHistoryItem[] = [];
 
     for (let i = 0; i < messages.length; i += 2) {
       if (i + 1 < messages.length) {
@@ -299,10 +321,13 @@ export class ChatLlamaCpp extends SimpleChatModel<LlamaCppCallOptions> {
             "ChatLlamaCpp does not support non-string message content."
           );
         }
-        result.push({
-          prompt,
-          response,
-        });
+        const llamaPrompt: ChatUserMessage = { type: "user", text: prompt };
+        const llamaResponse: ChatModelResponse = {
+          type: "model",
+          response: [response],
+        };
+        result.push(llamaPrompt);
+        result.push(llamaResponse);
       }
     }
 
@@ -313,19 +338,19 @@ export class ChatLlamaCpp extends SimpleChatModel<LlamaCppCallOptions> {
     const prompt = input
       .map((message) => {
         let messageText;
-        if (message._getType() === "human") {
+        if (message.getType() === "human") {
           messageText = `[INST] ${message.content} [/INST]`;
-        } else if (message._getType() === "ai") {
+        } else if (message.getType() === "ai") {
           messageText = message.content;
-        } else if (message._getType() === "system") {
+        } else if (message.getType() === "system") {
           messageText = `<<SYS>> ${message.content} <</SYS>>`;
         } else if (ChatMessage.isInstance(message)) {
           messageText = `\n\n${message.role[0].toUpperCase()}${message.role.slice(
             1
           )}: ${message.content}`;
         } else {
           console.warn(
-            `Unsupported message type passed to llama_cpp: "${message._getType()}"`
+            `Unsupported message type passed to llama_cpp: "${message.getType()}"`
           );
           messageText = "";
         }