Merge pull request #111 from intelligentnode/110-add-anthropic-model

110 add anthropic model

IntelliNode/README.md

@@ -15,12 +15,12 @@
 
 </p>
 
-IntelliNode is the ultimate tool to integrate your data with the latest language models and deep learning frameworks using **javascript**. The library provides intuitive functions for sending input to models like ChatGPT, WaveNet and Stable diffusion, and receiving generated text, speech, or images. With just a few lines of code, you can easily access the power of cutting-edge AI models to enhance your projects.
+Integrate your data with the latest language models and deep learning frameworks using intellinode **javascript**. The library provides intuitive functions for sending input to models like ChatGPT, WaveNet and Stable diffusion, and receiving generated text, speech, or images. With just a few lines of code, you can easily access the power of cutting-edge AI models to enhance your projects.
 
 # Latest Updates
+- Add Anthropic claude 3 chat.
 - Add Google Gemini chat and vision.
 - Add Mistral SMoE model as a chatbot provider (open source mixture of experts).
-- Update Openai with DALL·E 3 vision, speech, and ChatGPT functions (automation).
 - Improve Llama v2 chat speed and support llama code models. 🦙
 - Update stable diffusion to use the XL model engine. 🎨
 - Add support for hugging face inference. 🤗
@@ -65,7 +65,7 @@ const geminiBot = new Chatbot(geminiApiKey, SupportedChatModels.GEMINI);
 const responses = await geminiBot.chat(geminiInput);
 ```
 
-The documentation on how to switch the chatbot between ChatGPT, Mistral and LLama can be found in the [IntelliNode Wiki](https://github.com/Barqawiz/IntelliNode/wiki/ChatBot).
+The documentation on how to switch between ChatGPT, Mistral, Anthropic and LLama can be found in the [IntelliNode Wiki](https://docs.intellinode.ai/docs/npm/chatbot/get-started).
 
 ### Semantic Search
 1. imports:

IntelliNode/config.json

@@ -66,6 +66,11 @@
       "visionEndpoint": "gemini-pro-vision:generateContent",
       "embeddingEndpoint": "embedding-001:embedContent",
       "batchEmbeddingEndpoint": "embedding-001:batchEmbedContents"
+    },
+    "anthropic": {
+      "base": "https://api.anthropic.com",
+      "messages": "/v1/messages",
+      "version": "2023-06-01"
     }
   },
   "models": {

IntelliNode/function/Chatbot.js

@@ -14,6 +14,7 @@ const CohereAIWrapper = require('../wrappers/CohereAIWrapper');
 const IntellicloudWrapper = require("../wrappers/IntellicloudWrapper");
 const MistralAIWrapper = require('../wrappers/MistralAIWrapper');
 const GeminiAIWrapper = require('../wrappers/GeminiAIWrapper');
+const AnthropicWrapper = require('../wrappers/AnthropicWrapper');
 const SystemHelper = require("../utils/SystemHelper");
 
 const {
@@ -25,7 +26,8 @@ const {
     CohereInput,
     LLamaSageInput,
     MistralInput,
-    GeminiInput
+    GeminiInput,
+    AnthropicInput
 } = require("../model/input/ChatModelInput");
 
 const SupportedChatModels = {
@@ -35,6 +37,7 @@ const SupportedChatModels = {
     COHERE: "cohere",
     MISTRAL: "mistral",
     GEMINI: "gemini",
+    ANTHROPIC: "anthropic",
 };
 
 class Chatbot {
@@ -68,6 +71,8 @@ class Chatbot {
             this.mistralWrapper = new MistralAIWrapper(keyValue);
         } else if (provider === SupportedChatModels.GEMINI) {
             this.geminiWrapper = new GeminiAIWrapper(keyValue);
+        } else if (provider === SupportedChatModels.ANTHROPIC) {
+            this.anthropicWrapper = new AnthropicWrapper(keyValue);
         } else {
             throw new Error("Invalid provider name");
         }
@@ -113,6 +118,9 @@ class Chatbot {
         } else if (this.provider === SupportedChatModels.GEMINI) {
             const result = await this._chatGemini(modelInput);
             return modelInput.attachReference ? { result, references } : result;
+        } else if (this.provider === SupportedChatModels.ANTHROPIC) {
+            const result = await this._chatAnthropic(modelInput);
+            return modelInput.attachReference ? { result, references } : result;
         } else {
             throw new Error("The provider is not supported");
         }
@@ -166,8 +174,6 @@ class Chatbot {
         if (lastMessage && lastMessage.role === "user") {
 
             const semanticResult = await this.extendedController.semanticSearch(lastMessage.content, modelInput.searchK);
-
-            // console.log('semanticResult: ', semanticResult);
 
             if (semanticResult && semanticResult.length > 0) {
 
@@ -178,8 +184,6 @@ class Chatbot {
                     }
                     return acc;
                   }, {});
-
-                // console.log('references: ', references);
 
                 let contextData = semanticResult.map(doc => doc.data.map(dataItem => dataItem.text).join('\n')).join('\n').trim();
                 const templateWrapper = new SystemHelper().loadStaticPrompt("augmented_chatbot");
@@ -190,19 +194,14 @@ class Chatbot {
                     promptLines.pop();
                     promptLines.push(`User: ${augmentedMessage}`);
                     modelInput.prompt = promptLines.join('\n');
-
-                    // console.log('----> prompt after update: ', modelInput.prompt);
                 } else if (modelInput instanceof ChatModelInput) {
                     modelInput.deleteLastMessage(lastMessage);
                     modelInput.addUserMessage(augmentedMessage);
-
-                    // console.log('----> modelInput after update: ', modelInput);
                 } else if (typeof modelInput === "object" && Array.isArray(modelInput.messages) && messages.length > 0) {
                     // replace the user message directly in the array
                     if (lastMessage.content) {
                         lastMessage.content = augmentedMessage;
                     }
-                    // console.log('----> messages after update: ', messages[messages.length - 1]);
                 }
             }
         }
@@ -416,6 +415,20 @@ class Chatbot {
         return responses;
     }
 
+    async _chatAnthropic(modelInput) {
+        let params;
+
+        if (modelInput instanceof AnthropicInput) {
+            params = modelInput.getChatInput();
+        } else {
+            throw new Error("Invalid input: Must be an instance of AnthropicInput");
+        }
+
+        const results = await this.anthropicWrapper.generateText(params);
+
+        return results.content.map(choice => choice.text);
+    }
+
 } /*chatbot class*/
 
 module.exports = {

IntelliNode/index.js

@@ -43,7 +43,8 @@ const {
   LLamaSageInput,
   CohereInput,
   MistralInput,
-  GeminiInput
+  GeminiInput,
+  AnthropicInput
 } = require('./model/input/ChatModelInput');
 const FunctionModelInput = require('./model/input/FunctionModelInput');
 const EmbedInput = require('./model/input/EmbedInput');
@@ -59,6 +60,7 @@ const AWSEndpointWrapper = require('./wrappers/AWSEndpointWrapper');
 const IntellicloudWrapper = require('./wrappers/IntellicloudWrapper');
 const MistralAIWrapper = require('./wrappers/MistralAIWrapper');
 const GeminiAIWrapper = require('./wrappers/GeminiAIWrapper');
+const AnthropicWrapper = require('./wrappers/AnthropicWrapper');
 // utils
 const { LLMEvaluation } = require('./utils/LLMEvaluation');
 const AudioHelper = require('./utils/AudioHelper');
@@ -120,5 +122,7 @@ module.exports = {
   SupportedFineTuneModels,
   FineTuneInput,
   GeminiInput,
-  GeminiAIWrapper
+  GeminiAIWrapper,
+  AnthropicInput,
+  AnthropicWrapper
 };

IntelliNode/model/input/ChatModelInput.js

@@ -156,7 +156,7 @@ class MistralInput extends ChatGPTInput {
   constructor(systemMessage, options = {}) {
     super(systemMessage, options);
 
-    this.model = options.model || 'mistral-tiny'; 
+    this.model = options.model || 'mistral-medium'; 
 
   }
 
@@ -232,6 +232,42 @@ class GeminiInput extends ChatModelInput {
 
 }
 
+class AnthropicInput extends ChatModelInput {
+
+  constructor(system, options = {}) {
+      super(options);
+      this.system = system;
+      this.model = options.model || 'claude-3-sonnet-20240229'; 
+      this.maxTokens = options.maxTokens  || 800;
+      this.temperature = options.temperature || 1.0;
+      this.messages = [];
+  }
+
+  addUserMessage(text) {
+      this.messages.push({
+          role: "user",
+          content: text
+      });
+  }
+
+  addAssistantMessage(text) {
+      this.messages.push({
+          role: "assistant",
+          content: text
+      });
+  }
+
+  getChatInput() {
+      return {
+          system: this.system,
+          model: this.model,
+          messages: this.messages,
+          max_tokens: this.maxTokens,
+          temperature: this.temperature,
+      };
+  }
+}
+
 class ChatLLamaInput extends ChatModelInput {
   constructor(systemMessage, options = {}) {
     super(options);
@@ -426,5 +462,6 @@ module.exports = {
   LLamaReplicateInput,
   CohereInput,
   MistralInput,
-  GeminiInput
+  GeminiInput,
+  AnthropicInput
 };

IntelliNode/package.json

@@ -1,7 +1,7 @@
 {
   "name": "intellinode",
-  "version": "1.8.4",
-  "description": "Connect your data, evaluate accuracy, and integrate with AI models including ChatGPT, Llama, Diffusion, Cohere, Gemini, and Hugging Face.",
+  "version": "1.8.5",
+  "description": "Evaluate and integrate with latest AI models including ChatGPT, Llama, Diffusion, Cohere, Gemini, and Hugging Face.",
   "main": "index.js",
   "keywords": [
     "ai",

IntelliNode/test/integration/AnthropicWrapper.test.js

@@ -0,0 +1,30 @@
+require('dotenv').config();
+const assert = require('assert');
+const AnthropicWrapper = require('../../wrappers/AnthropicWrapper');
+
+// initiate anthropic object
+const anthropic = new AnthropicWrapper(process.env.ANTHROPIC_API_KEY);
+
+async function testAnthropicGenerate() {
+    try {
+        const params = {
+            "model": "claude-3-sonnet-20240229",
+            "messages": [
+                {
+                    "role": "user",
+                    "content": "Who is the most renowned French painter? Provide a single direct short answer."
+                }
+            ],
+            "max_tokens": 256
+        };
+
+        const result = await anthropic.generateText(params);
+        console.log('Anthropic Language Model Result:', result.content[0].text);
+    } catch (error) {
+        console.error('Anthropic Language Model Error:', error);
+    }
+}
+
+(async () => {
+    await testAnthropicGenerate();
+})();

IntelliNode/test/integration/Chatbot.test.js

@@ -9,7 +9,8 @@ const { ChatGPTInput,
   LLamaReplicateInput,
   LLamaSageInput,
   MistralInput,
-  GeminiInput } = require("../../model/input/ChatModelInput");
+  GeminiInput,
+  AnthropicInput } = require("../../model/input/ChatModelInput");
 
 // env key
 const apiKey = process.env.OPENAI_API_KEY;
@@ -292,6 +293,19 @@ async function testGeminiChatCase2() {
   }
 }
 
+async function testAnthropicChatCase() {
+  console.log('\nAnthropic chat test case: \n');
+  const bot = new Chatbot(process.env.ANTHROPIC_API_KEY, SupportedChatModels.ANTHROPIC);
+
+  const input = new AnthropicInput("You are helpful asssitant.", {model: "claude-3-sonnet-20240229"});
+  input.addUserMessage("Tell me about the history of artificial intelligence.")
+  const responses = await bot.chat(input);
+
+  responses.forEach((response) => console.log("- " + response));
+
+  assert(responses.length > 0, "Anthropic chat response length should be greater than 0");
+}
+
 (async () => {
 
   console.log('### Openai model ###')
@@ -312,11 +326,14 @@ async function testGeminiChatCase2() {
   console.log('### Mistral model ###')
   await testMistralChatCase();
 
+  console.log('### Anthropic model ###')
+  await testAnthropicChatCase();
+
   console.log('### Gemini model ###')
   await testGeminiChatCase1();
   await testGeminiChatCase2();
 
   console.log('### SageMaker llama model ###')
   //await testSageMakerLLamaCase();
-
+  
 })();

IntelliNode/test/integration/ModelEvaluation.test.js

@@ -26,6 +26,11 @@ const mistralChat = {
   type: 'chat', model: 'mistral-medium', maxTokens: 50
 };
 
+const anthropicChat = {
+  apiKey: process.env.ANTHROPIC_API_KEY, provider: SupportedChatModels.ANTHROPIC,
+  type: 'chat', model: 'claude-3-sonnet-20240229', maxTokens: 50
+};
+
 // create the evaluation object
 const llmEvaluation = new LLMEvaluation(process.env.OPENAI_API_KEY, 'openai');
 
@@ -34,7 +39,7 @@ async function testLLMEvaluation() {
   const targetAnswers = ["Photosynthesis is the process where green plants use sunlight to turn carbon dioxide and water into glucose and oxygen. The glucose provides food for the plant, and the oxygen gets released back into the air.",
     "Photosynthesis is how plants make their own food. They take in water and carbon dioxide, use the energy from sunlight to transform them into glucose (their food) and oxygen, which they release into the air.",
     "In simple terms, photosynthesis is like cooking for plants but instead of a stove, they use sunlight. They mix water and carbon dioxide with the sunlight to create glucose, which is their food, and also produce oxygen."];
-  const providerSets = [llamaChat, openaiChat, cohereCompletion, geminiChat, mistralChat];
+  const providerSets = [llamaChat, openaiChat, cohereCompletion, geminiChat, mistralChat, anthropicChat];
 
   const results = await llmEvaluation.compareModels(inputString, targetAnswers, providerSets);
 

IntelliNode/utils/LLMEvaluation.js

@@ -2,7 +2,7 @@ const { RemoteEmbedModel, SupportedEmbedModels } = require('../controller/Remote
 const LanguageModelInput = require('../model/input/LanguageModelInput');
 const { Chatbot, SupportedChatModels } = require("../function/Chatbot");
 const { RemoteLanguageModel, SupportedLangModels } = require("../controller/RemoteLanguageModel");
-const { ChatGPTInput, LLamaReplicateInput, LLamaSageInput, GeminiInput, CohereInput, MistralInput } = require("../model/input/ChatModelInput");
+const { ChatGPTInput, LLamaReplicateInput, LLamaSageInput, GeminiInput, CohereInput, MistralInput, AnthropicInput } = require("../model/input/ChatModelInput");
 const MatchHelpers = require('../utils/MatchHelpers');
 const EmbedInput = require('../model/input/EmbedInput');
 const { ModelEvaluation } = require('./ModelEvaluation');
@@ -45,7 +45,9 @@ class LLMEvaluation extends ModelEvaluation {
       } else if (SupportedChatModels.COHERE == provider.toLowerCase()) {
         input = new CohereInput("provide direct answer", { maxTokens: maxTokens });
       } else if (SupportedChatModels.MISTRAL == provider.toLowerCase()) {
-        input = new MistralInput("provide direct answer", { maxTokens: maxTokens });
+        input = new MistralInput("provide direct answer", { model: modelName, maxTokens: maxTokens });
+      } else if (SupportedChatModels.ANTHROPIC == provider.toLowerCase()) {
+        input = new AnthropicInput("provide direct answer", { model: modelName, maxTokens: maxTokens });
       } else {
         input = new ChatGPTInput("provide direct answer", { model: modelName, maxTokens: maxTokens });
       }

IntelliNode/wrappers/AnthropicWrapper.js

@@ -0,0 +1,39 @@
+/*
+Apache License
+
+Copyright 2023 Github.com/Barqawiz/IntelliNode
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+*/
+const axios = require('axios');
+const config = require('../config.json');
+const connHelper = require('../utils/ConnHelper');
+
+class AnthropicWrapper {
+    constructor(apiKey) {
+        this.API_BASE_URL = config.url.anthropic.base;
+        this.API_VERSION = config.url.anthropic.version;
+        this.httpClient = axios.create({
+            baseURL: this.API_BASE_URL,
+            headers: {
+                'Content-Type': 'application/json',
+                'Accept': 'application/json',
+                'x-api-key': apiKey,
+                'anthropic-version': this.API_VERSION
+            }
+        });
+    }
+
+    async generateText(params) {
+        const url = config.url.anthropic.messages;
+        try {
+            const response = await this.httpClient.post(url, params);
+            return response.data;
+        } catch (error) {
+            throw new Error(connHelper.getErrorMessage(error));
+        }
+    }
+
+}
+
+module.exports = AnthropicWrapper;