Merge main into sweep/add-gradient-ai-support

CI/CD configuration file

@@ -0,0 +1,17 @@
+stages:
+  - build
+  - test
+  - deploy
+
+build:
+  script:
+    - tsc
+    - node main.js
+
+test:
+  script:
+    - npm run test
+
+deploy:
+  script:
+    - npm run deploy

packages/core/src/llm/LLM.ts

@@ -7,6 +7,7 @@ import {
   OpenAIStreamToken,
   StreamCallbackResponse,
 } from "../callbacks/CallbackManager";
+import { _BaseGradientLLM, GradientBaseModelLLM, GradientModelAdapterLLM } from "./gradient";
 
 import { LLMOptions } from "portkey-ai";
 import { globalsHelper, Tokenizers } from "../GlobalsHelper";
@@ -396,6 +397,14 @@ export const ALL_AVAILABLE_LLAMADEUCE_MODELS = {
       "a16z-infra/llama7b-v2-chat:4f0b260b6a13eb53a6b1891f089d57c08f41003ae79458be5011303d81a394dc",
   },
 };
+"GradientBaseModelLLM": {
+  contextWindow: 4096,
+  gradientApi: "gradient/baseModelLLM"
+},
+"GradientModelAdapterLLM": {
+  contextWindow: 4096,
+  gradientApi: "gradient/modelAdapterLLM"
+},
 
 export enum DeuceChatStrategy {
   A16Z = "a16z",
@@ -559,6 +568,7 @@ If a question does not make any sense, or is not factually coherent, explain why
     R = T extends true ? AsyncGenerator<string, void, unknown> : ChatResponse,
   >(messages: ChatMessage[], _parentEvent?: Event, streaming?: T): Promise<R> {
     const api = ALL_AVAILABLE_LLAMADEUCE_MODELS[this.model]
+    export { _BaseGradientLLM, GradientBaseModelLLM, GradientModelAdapterLLM };
       .replicateApi as `${string}/${string}:${string}`;
 
     const { prompt, systemPrompt } = this.mapMessagesToPrompt(messages);

packages/core/src/llm/gradient.ts

@@ -0,0 +1,47 @@
+export abstract class _BaseGradientLLM {
+  protected model: string;
+
+  constructor(model: string) {
+    this.model = model;
+  }
+
+  async initialize(): Promise<void> {
+    // Code to initialize the model
+  }
+  
+  async close(): Promise<void> {
+    // Code to close the model
+  }
+  
+  async completePrompt(prompt: string): Promise<string> {
+    // Code to complete the prompt using the model
+    return '';
+  }
+}
+
+export class GradientBaseModelLLM extends _BaseGradientLLM {
+  private baseModelSlug: string;
+
+  constructor(model: string, baseModelSlug: string) {
+    super(model);
+    this.baseModelSlug = baseModelSlug;
+  }
+
+  // Removed methods as they are already defined in the parent class
+}
+
+export class GradientModelAdapterLLM extends _BaseGradientLLM {
+  private adapter: any;
+
+  constructor(model: string, adapter: any) {
+    super(model);
+    this.adapter = adapter;
+  }
+
+  // Removed methods as they are already defined in the parent class
+
+  async completePrompt(prompt: string) {
+    // Code to complete the prompt using the model and the adapter
+    return '';
+  }
+}

packages/core/src/tests/gradient.test.ts

@@ -0,0 +1,41 @@
+const { GradientBaseModelLLM, GradientModelAdapterLLM } = require('../llm/gradient');
+
+describe('GradientBaseModelLLM', () => {
+  it('should initialize the model', async () => {
+    const model = new GradientBaseModelLLM('model', 'baseModelSlug');
+    await model.initialize();
+    // Add assertions here
+  });
+
+  it('should close the model', async () => {
+    const model = new GradientBaseModelLLM('model', 'baseModelSlug');
+    await model.close();
+    // Add assertions here
+  });
+
+  it('should complete the prompt', async () => {
+    const model = new GradientBaseModelLLM('model', 'baseModelSlug');
+    const result = await model.completePrompt('prompt');
+    // Add assertions here
+  });
+});
+
+describe('GradientModelAdapterLLM', () => {
+  it('should initialize the model', async () => {
+    const model = new GradientModelAdapterLLM('model', {});
+    await model.initialize();
+    // Add assertions here
+  });
+
+  it('should close the model', async () => {
+    const model = new GradientModelAdapterLLM('model', {});
+    await model.close();
+    // Add assertions here
+  });
+
+  it('should complete the prompt', async () => {
+    const model = new GradientModelAdapterLLM('model', {});
+    const result = await model.completePrompt('prompt');
+    // Add assertions here
+  });
+});