[BLCKCHN-213] add vertex ai

Add support for Vertex AI in chatbot and service layers

- Introduced Vertex AI as a new provider option in the chatbot and service layers.
- Updated environment variable checks to include GOOGLE_PROJECT_ID.
- Enhanced .gitignore to exclude additional file types.
- Added VertexAIService class for handling interactions with Vertex AI.
- Updated LLM interfaces and factory to accommodate Vertex AI configurations.
- Implemented response generation methods for Vertex AI and updated existing services to support new functionality.

.gitignore

@@ -0,0 +1 @@
+*.md

ai/cryptocom-ai-agent-pychatbot/chat.py

@@ -7,9 +7,10 @@
 
 load_dotenv()
 
-# Check both API keys after load_dotenv()
+# Check API keys after load_dotenv()
 api_key = os.getenv("OPENAI_API_KEY")
 google_api_key = os.getenv("GOOGLE_API_KEY")
+google_project_id = os.getenv("GOOGLE_PROJECT_ID")
 
 if not api_key:
     print("Error: OPENAI_API_KEY not found in environment variables.")
@@ -25,6 +26,13 @@
 else:
     print("✓ GOOGLE_API_KEY has been imported successfully")
 
+if not google_project_id:
+    print("Error: GOOGLE_PROJECT_ID not found in environment variables.")
+    print("Please make sure you have set the GOOGLE_PROJECT_ID in your .env file.")
+    exit(1)
+else:
+    print("✓ GOOGLE_PROJECT_ID has been imported successfully")
+
 print()  # Add blank line after checks
 
 
@@ -46,6 +54,12 @@ def send_query(query: str, context: list = None, provider: str = "gemini") -> di
     provider_options = {}
     if provider == "openai":
         provider_options["openAI"] = {"apiKey": os.getenv("OPENAI_API_KEY")}
+    elif provider == "vertexai":
+        provider_options["vertexAI"] = {
+            "projectId": os.getenv("GOOGLE_PROJECT_ID"),
+            "location": "us-central1",
+            "model": "gemini-2.0-flash-exp",
+        }
     else:  # gemini
         provider_options["gemini"] = {"apiKey": os.getenv("GOOGLE_API_KEY")}
 
@@ -74,10 +88,12 @@ def main():
 
     # Ask for provider choice at startup - this will be fixed for the session
     while True:
-        provider = input("Choose your AI provider (openai/gemini): ").strip().lower()
-        if provider in ["openai", "gemini"]:
+        provider = (
+            input("Choose your AI provider (openai/gemini/vertexai): ").strip().lower()
+        )
+        if provider in ["openai", "gemini", "vertexai"]:
             break
-        print("Invalid choice. Please enter 'openai' or 'gemini'")
+        print("Invalid choice. Please enter 'openai', 'gemini', or 'vertexai'")
 
     print("\nType 'quit' to exit")
     print("Use up/down arrow keys to navigate command history")

ai/cryptocom-ai-agent-service/.gitignore

@@ -119,4 +119,9 @@ dist/*
 node_modules/*
 client/*
 .env
+.env.example
 *.lock
+*.sh
+*.json
+*.md
+*.txt

ai/cryptocom-ai-agent-service/package.json

@@ -27,7 +27,9 @@
     "openai": "4.63.0",
     "swagger-jsdoc": "^6.2.8",
     "swagger-ui-express": "5.0.1",
-    "winston": "3.14.2"
+    "winston": "3.14.2",
+    "@google-cloud/vertexai": "^0.5.0",
+    "@google/generative-ai": "^0.2.0"
   },
   "devDependencies": {
     "@eslint/js": "^9.11.0",

ai/cryptocom-ai-agent-service/src/services/agent/agent.interfaces.ts

@@ -1,6 +1,7 @@
 export enum LLMProvider {
   OpenAI = 'openai',
   Gemini = 'gemini',
+  VertexAI = 'vertexai',
 }
 
 export interface OpenAIOptions {
@@ -15,6 +16,7 @@ export interface ExplorerKeys {
 export interface Options {
   openAI?: OpenAIOptions;
   gemini?: GeminiOptions;
+  vertexAI?: VertexAIOptions;
   llmProvider?: LLMProvider;
   chainId: number;
   context: QueryContext[];
@@ -246,3 +248,9 @@ export interface GeminiOptions {
   apiKey: string;
   model?: string;
 }
+
+export interface VertexAIOptions {
+  projectId: string;
+  location?: string;
+  model?: string;
+}

ai/cryptocom-ai-agent-service/src/services/agent/agent.service.ts

@@ -24,6 +24,7 @@ import {
 import { LLMService } from '../llm/llm.interface.js';
 import { OpenAIService } from '../llm/openai.service.js';
 import { GeminiService } from '../llm/gemini.service.js';
+import { VertexAIService } from '../llm/vertexai.service.js';
 
 /**
  * Initialize Developer Platform SDK
@@ -133,6 +134,11 @@ export class AIAgentService {
           throw new Error('Gemini configuration is required when using Gemini provider');
         }
         return new GeminiService(this.options.gemini);
+      case LLMProvider.VertexAI:
+        if (!this.options.vertexAI) {
+          throw new Error('Vertex AI configuration is required when using Vertex AI provider');
+        }
+        return new VertexAIService(this.options.vertexAI);
       default:
         throw new Error(`Unsupported LLM provider: ${provider}`);
     }

ai/cryptocom-ai-agent-service/src/services/llm/gemini.service.ts

@@ -38,6 +38,9 @@ export class GeminiService implements LLMService {
   private lastAssistantMessage: AIMessageResponse | null = null;
 
   constructor(config: LLMConfig) {
+    if (!config.apiKey) {
+      throw new Error('Gemini API key is required');
+    }
     this.apiKey = config.apiKey;
     this.model = config.model || 'gemini-1.5-pro';
     this.baseUrl = 'https://generativelanguage.googleapis.com/v1beta/models';
@@ -188,4 +191,10 @@ export class GeminiService implements LLMService {
       throw new Error(`Gemini API error: ${error instanceof Error ? error.message : 'Unknown error'}`);
     }
   }
+
+  async generateResponse(context: QueryContext[]): Promise<AIMessageResponse> {
+    // Convert existing interpretUserQuery implementation to match new interface
+    const lastMessage = context[context.length - 1];
+    return this.interpretUserQuery(lastMessage.content, context);
+  }
 }

ai/cryptocom-ai-agent-service/src/services/llm/llm.factory.ts

@@ -0,0 +1,40 @@
+import { LLMProvider, Options } from '../agent/agent.interfaces.js';
+import { OpenAIService } from './openai.service.js';
+import { GeminiService } from './gemini.service.js';
+import { VertexAIService } from './vertexai.service.js';
+import { LLMService } from './llm.interface.js';
+
+export function createLLMService(options: Options): LLMService {
+  switch (options.llmProvider) {
+    case LLMProvider.OpenAI:
+      if (!options.openAI?.apiKey) {
+        throw new Error('OpenAI API key is required');
+      }
+      return new OpenAIService({
+        apiKey: options.openAI.apiKey,
+        model: options.openAI.model,
+      });
+
+    case LLMProvider.Gemini:
+      if (!options.gemini?.apiKey) {
+        throw new Error('Gemini API key is required');
+      }
+      return new GeminiService({
+        apiKey: options.gemini.apiKey,
+        model: options.gemini.model,
+      });
+
+    case LLMProvider.VertexAI:
+      if (!options.vertexAI?.projectId) {
+        throw new Error('Vertex AI project ID is required');
+      }
+      return new VertexAIService({
+        projectId: options.vertexAI.projectId,
+        location: options.vertexAI.location,
+        model: options.vertexAI.model,
+      });
+
+    default:
+      throw new Error(`Unsupported LLM provider: ${options.llmProvider}`);
+  }
+}

ai/cryptocom-ai-agent-service/src/services/llm/llm.interface.ts

@@ -1,15 +1,18 @@
-import { AIMessageResponse, FunctionCallResponse, QueryContext } from '../agent/agent.interfaces.js';
+import { AIMessageResponse, QueryContext, FunctionCallResponse } from '../agent/agent.interfaces.js';
+
+export interface LLMConfig {
+  apiKey?: string;
+  model?: string;
+  projectId?: string;
+  location?: string;
+}
 
 export interface LLMService {
+  generateResponse(context: QueryContext[]): Promise<AIMessageResponse>;
   interpretUserQuery(query: string, context: QueryContext[]): Promise<AIMessageResponse>;
   generateFinalResponse(
     query: string,
     functionResponses: FunctionCallResponse[],
     context: QueryContext[]
   ): Promise<string>;
 }
-
-export interface LLMConfig {
-  apiKey: string;
-  model?: string;
-}

ai/cryptocom-ai-agent-service/src/services/llm/openai.service.ts

@@ -113,4 +113,9 @@ export class OpenAIService implements LLMService {
       return 'Error generating final response';
     }
   }
+
+  async generateResponse(context: QueryContext[]): Promise<AIMessageResponse> {
+    const lastMessage = context[context.length - 1];
+    return this.interpretUserQuery(lastMessage.content, context);
+  }
 }