feat(ts-sdk): add LiteLLM as LLM provider (#5830)

Co-authored-by: kartik-mem0 <kartik.labhshetwar@mem0.ai>

docs/components/llms/models/litellm.mdx

@@ -4,9 +4,12 @@ description: "Use LiteLLM as an LLM provider in Mem0 to access over 100 language
 ---
 [Litellm](https://litellm.vercel.app/docs/) is compatible with over 100 large language models (LLMs), all using a standardized input/output format. You can explore the [available models](https://litellm.vercel.app/docs/providers) to use with Litellm. Ensure you set the `API_KEY` for the model you choose to use.
 
+In the TypeScript SDK, run LiteLLM as a [proxy server](https://docs.litellm.ai/docs/simple_proxy) (an OpenAI-compatible endpoint) and point Mem0 at it via `LITELLM_API_BASE` (defaults to `http://localhost:4000`).
+
 ## Usage
 
-```python
+<CodeGroup>
+```python Python
 import os
 from mem0 import Memory
 
@@ -33,6 +36,33 @@ messages = [
 m.add(messages, user_id="alice", metadata={"category": "movies"})
 ```
 
+```typescript TypeScript
+import { Memory } from 'mem0ai/oss';
+
+// Point Mem0 at your LiteLLM proxy. apiKey defaults to "sk-anything"
+// (the proxy handles real auth); baseURL defaults to http://localhost:4000.
+const config = {
+  llm: {
+    provider: 'litellm',
+    config: {
+      apiKey: process.env.LITELLM_API_KEY || 'sk-anything',
+      baseURL: process.env.LITELLM_API_BASE || 'http://localhost:4000',
+      model: 'gpt-5-mini',
+    },
+  },
+};
+
+const memory = new Memory(config);
+const messages = [
+    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
+    {"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
+    {"role": "user", "content": "I’m not a big fan of thriller movies but I love sci-fi movies."},
+    {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
+];
+await memory.add(messages, { userId: 'alice', metadata: { category: 'movies' } });
+```
+</CodeGroup>
+
 ## Config
 
 All available parameters for the `litellm` config are present in [Master List of All Params in Config](../config).

mem0-ts/src/oss/src/index.ts

@@ -18,6 +18,7 @@ export * from "./llms/ollama";
 export * from "./llms/lmstudio";
 export * from "./llms/mistral";
 export * from "./llms/langchain";
+export * from "./llms/litellm";
 export * from "./vector_stores/base";
 export * from "./vector_stores/memory";
 export * from "./vector_stores/qdrant";

mem0-ts/src/oss/src/llms/litellm.ts

@@ -0,0 +1,39 @@
+import { OpenAILLM } from "./openai";
+import { LLMConfig, Message } from "../types";
+import { LLMResponse } from "./base";
+
+export class LiteLLM extends OpenAILLM {
+  constructor(config: LLMConfig) {
+    super({
+      ...config,
+      apiKey: config.apiKey || process.env.LITELLM_API_KEY || "sk-anything",
+      baseURL:
+        config.baseURL ||
+        process.env.LITELLM_API_BASE ||
+        "http://localhost:4000",
+      model: config.model || "gpt-5-mini",
+    });
+  }
+
+  async generateResponse(
+    messages: Message[],
+    responseFormat?: { type: string },
+    tools?: any[],
+  ): Promise<string | LLMResponse> {
+    try {
+      return await super.generateResponse(messages, responseFormat, tools);
+    } catch (err) {
+      const message = err instanceof Error ? err.message : String(err);
+      throw new Error(`LiteLLM failed: ${message}`);
+    }
+  }
+
+  async generateChat(messages: Message[]): Promise<LLMResponse> {
+    try {
+      return await super.generateChat(messages);
+    } catch (err) {
+      const message = err instanceof Error ? err.message : String(err);
+      throw new Error(`LiteLLM failed: ${message}`);
+    }
+  }
+}

mem0-ts/src/oss/src/utils/factory.ts

@@ -22,6 +22,7 @@ import { RedisDB } from "../vector_stores/redis";
 import { OllamaLLM } from "../llms/ollama";
 import { LMStudioLLM } from "../llms/lmstudio";
 import { DeepSeekLLM } from "../llms/deepseek";
+import { LiteLLM } from "../llms/litellm";
 import { SupabaseDB } from "../vector_stores/supabase";
 import { SQLiteManager } from "../storage/SQLiteManager";
 import { MemoryHistoryManager } from "../storage/MemoryHistoryManager";
@@ -85,6 +86,8 @@ export class LLMFactory {
         return new LangchainLLM(config);
       case "deepseek":
         return new DeepSeekLLM(config);
+      case "litellm":
+        return new LiteLLM(config);
       default:
         throw new Error(`Unsupported LLM provider: ${provider}`);
     }

mem0-ts/src/oss/tests/factory.unit.test.ts

@@ -92,6 +92,11 @@ jest.mock("../src/llms/deepseek", () => ({
     .fn()
     .mockImplementation((config) => ({ type: "deepseek-llm", config })),
 }));
+jest.mock("../src/llms/litellm", () => ({
+  LiteLLM: jest
+    .fn()
+    .mockImplementation((config) => ({ type: "litellm-llm", config })),
+}));
 
 jest.mock("../src/vector_stores/qdrant", () => ({
   Qdrant: jest
@@ -206,6 +211,7 @@ describe("LLMFactory", () => {
     ["langchain"],
     ["lmstudio"],
     ["deepseek"],
+    ["litellm"],
   ])("creates LLM for provider '%s'", (provider) => {
     expect(() => LLMFactory.create(provider, dummyLLMConfig)).not.toThrow();
   });

mem0-ts/src/oss/tests/litellm.test.ts

@@ -0,0 +1,131 @@
+/// <reference types="jest" />
+/**
+ * LiteLLM — unit tests (mocked OpenAI).
+ */
+
+import { LiteLLM } from "../src/llms/litellm";
+
+const mockCreate = jest.fn();
+
+jest.mock("openai", () => {
+  return jest.fn().mockImplementation(() => ({
+    chat: { completions: { create: mockCreate } },
+  }));
+});
+
+describe("LiteLLM (unit)", () => {
+  beforeEach(() => mockCreate.mockClear());
+
+  it("uses default baseURL when none is provided", () => {
+    const llm = new LiteLLM({});
+    expect(llm).toBeDefined();
+  });
+
+  it("generateResponse() returns a text response", async () => {
+    mockCreate.mockResolvedValueOnce({
+      choices: [
+        {
+          message: {
+            content: "Hello, world!",
+            role: "assistant",
+            tool_calls: null,
+          },
+        },
+      ],
+    });
+
+    const llm = new LiteLLM({ baseURL: "http://localhost:4000" });
+    const result = await llm.generateResponse([
+      { role: "user", content: "Hi" },
+    ]);
+
+    expect(mockCreate).toHaveBeenCalledTimes(1);
+    expect(result).toBe("Hello, world!");
+  });
+
+  it("generateResponse() handles tool calls", async () => {
+    mockCreate.mockResolvedValueOnce({
+      choices: [
+        {
+          message: {
+            content: "",
+            role: "assistant",
+            tool_calls: [
+              {
+                function: {
+                  name: "get_weather",
+                  arguments: '{"city": "London"}',
+                },
+              },
+            ],
+          },
+        },
+      ],
+    });
+
+    const llm = new LiteLLM({});
+    const result = await llm.generateResponse(
+      [{ role: "user", content: "What is the weather?" }],
+      undefined,
+      [{ type: "function", function: { name: "get_weather" } }],
+    );
+
+    expect(result).toEqual({
+      content: "",
+      role: "assistant",
+      toolCalls: [{ name: "get_weather", arguments: '{"city": "London"}' }],
+    });
+  });
+
+  it("generateResponse() wraps API errors with a clear message", async () => {
+    mockCreate.mockRejectedValueOnce(new Error("Connection refused"));
+
+    const llm = new LiteLLM({});
+
+    await expect(
+      llm.generateResponse([{ role: "user", content: "Hi" }]),
+    ).rejects.toThrow("LiteLLM failed: Connection refused");
+  });
+
+  it("generateChat() returns LLMResponse shape", async () => {
+    mockCreate.mockResolvedValueOnce({
+      choices: [
+        {
+          message: { content: "I can help with that.", role: "assistant" },
+        },
+      ],
+    });
+
+    const llm = new LiteLLM({});
+    const result = await llm.generateChat([
+      { role: "user", content: "Help me" },
+    ]);
+
+    expect(result).toEqual({
+      content: "I can help with that.",
+      role: "assistant",
+    });
+  });
+
+  it("generateChat() wraps API errors with a clear message", async () => {
+    mockCreate.mockRejectedValueOnce(new Error("Timeout"));
+
+    const llm = new LiteLLM({});
+
+    await expect(
+      llm.generateChat([{ role: "user", content: "Hi" }]),
+    ).rejects.toThrow("LiteLLM failed: Timeout");
+  });
+
+  it("respects LITELLM_API_BASE env var", () => {
+    const original = process.env.LITELLM_API_BASE;
+    process.env.LITELLM_API_BASE = "http://custom-proxy:8080";
+    try {
+      const llm = new LiteLLM({});
+      expect(llm).toBeDefined();
+    } finally {
+      if (original !== undefined) process.env.LITELLM_API_BASE = original;
+      else delete process.env.LITELLM_API_BASE;
+    }
+  });
+});