working

Author: mike dupont

packages/plugin-groq/src/index.ts

@@ -17,6 +17,50 @@ import { generateObject, generateText } from 'ai';
 import { type TiktokenModel, encodingForModel } from 'js-tiktoken';
 import { z } from 'zod';
 
+/**
+ * Gets the Cloudflare Gateway base URL for a specific provider if enabled
+ * @param runtime The runtime environment
+ * @param provider The model provider name
+ * @returns The Cloudflare Gateway base URL if enabled, undefined otherwise
+ */
+function getCloudflareGatewayBaseURL(runtime: IAgentRuntime, provider: string): string | undefined {
+  const isCloudflareEnabled = runtime.getSetting('CLOUDFLARE_GW_ENABLED') === 'true';
+  const cloudflareAccountId = runtime.getSetting('CLOUDFLARE_AI_ACCOUNT_ID');
+  const cloudflareGatewayId = runtime.getSetting('CLOUDFLARE_AI_GATEWAY_ID');
+
+  logger.debug('Cloudflare Gateway Configuration:', {
+    isEnabled: isCloudflareEnabled,
+    hasAccountId: !!cloudflareAccountId,
+    hasGatewayId: !!cloudflareGatewayId,
+    provider: provider,
+  });
+
+  if (!isCloudflareEnabled) {
+    logger.debug('Cloudflare Gateway is not enabled');
+    return undefined;
+  }
+
+  if (!cloudflareAccountId) {
+    logger.warn('Cloudflare Gateway is enabled but CLOUDFLARE_AI_ACCOUNT_ID is not set');
+    return undefined;
+  }
+
+  if (!cloudflareGatewayId) {
+    logger.warn('Cloudflare Gateway is enabled but CLOUDFLARE_AI_GATEWAY_ID is not set');
+    return undefined;
+  }
+
+  const baseURL = `https://gateway.ai.cloudflare.com/v1/${cloudflareAccountId}/${cloudflareGatewayId}/${provider.toLowerCase()}`;
+  logger.info('Using Cloudflare Gateway:', {
+    provider,
+    baseURL,
+    accountId: cloudflareAccountId,
+    gatewayId: cloudflareGatewayId,
+  });
+
+  return baseURL;
+}
+
 /**
  * Asynchronously tokenizes the given text based on the specified model and prompt.
  *
@@ -62,11 +106,11 @@ async function detokenizeText(model: ModelTypeName, tokens: number[]) {
  * Defines the Groq plugin with its name, description, and configuration options.
  * @type {Plugin}
  * 
- *               elizaLogger.debug(
+ *               logger.debug(
                     "Initializing Groq model with Cloudflare check"
                 );
                 const baseURL = getCloudflareGatewayBaseURL(runtime, "groq");
-                elizaLogger.debug("Groq baseURL result:", { baseURL });
+                logger.debug("Groq baseURL result:", { baseURL });
                 const groq = createGroq({
                     apiKey,
                     fetch: runtime.fetch,
@@ -91,7 +135,7 @@ async function detokenizeText(model: ModelTypeName, tokens: number[]) {
                 });
 
                 response = groqResponse;
-                elizaLogger.debug("Received response from Groq model.");
+                logger.debug("Received response from Groq model.");
                 break;
             }
      async function handleGroq({
@@ -104,9 +148,9 @@ async function detokenizeText(model: ModelTypeName, tokens: number[]) {
     modelOptions,
     runtime,
 }: ProviderOptions): Promise<GenerationResult> {
-    elizaLogger.debug("Handling Groq request with Cloudflare check");
+    logger.debug("Handling Groq request with Cloudflare check");
     const baseURL = getCloudflareGatewayBaseURL(runtime, "groq");
-    elizaLogger.debug("Groq handleGroq baseURL:", { baseURL });
+    logger.debug("Groq handleGroq baseURL:", { baseURL });
 
     const groq = createGroq({ 
         apiKey, 
@@ -213,6 +257,8 @@ export const groqPlugin: Plugin = {
       try {
         const baseURL = getCloudflareGatewayBaseURL(runtime, 'groq');
 
+        const model = runtime.getSetting('EMBEDDING_GROQ_MODEL') ?? 'text-embedding-3-small';
+
         // Call the OpenAI API
         const response = await fetch(`${baseURL}/embeddings`, {
           method: 'POST',
@@ -568,7 +614,7 @@ export const groqPlugin: Plugin = {
           },
         },
         {
-          name: 'openai_test_text_embedding',
+          name: 'groq_test_text_embedding',
           fn: async (runtime) => {
             try {
               const embedding = await runtime.useModel(ModelType.TEXT_EMBEDDING, {