feat(ts-sdk): add Sarvam LLM provider to OSS SDK (#6130)

Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
Co-authored-by: kartik-mem0 <kartik.labhshetwar@mem0.ai>

docs/components/llms/models/sarvam.mdx

@@ -9,7 +9,8 @@ To use Sarvam AI's models, please set the `SARVAM_API_KEY` which you can get fro
 
 ## Usage
 
-```python
+<CodeGroup>
+```python Python
 import os
 from mem0 import Memory
 
@@ -34,8 +35,35 @@ messages = [
     {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
 ]
 m.add(messages, user_id="alex")
+
 ```
 
+```typescript TypeScript
+import { Memory } from 'mem0ai/oss';
+
+const config = {
+  llm: {
+    provider: 'sarvam',
+    config: {
+      apiKey: process.env.SARVAM_API_KEY || '',
+      model: 'sarvam-m',
+      temperature: 0.7,
+    },
+  },
+};
+
+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: 'alex' });
+```
+
+</CodeGroup>
+
 ## Advanced Usage with Sarvam-Specific Features
 
 ```python

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

@@ -0,0 +1,52 @@
+import { OpenAILLM } from "./openai";
+import { LLMConfig, Message } from "../types";
+import { LLMResponse } from "./base";
+
+/**
+ * Sarvam AI LLM provider.
+ *
+ * Sarvam's API is OpenAI-compatible, so this simply reuses {@link OpenAILLM}
+ * and overrides the connection defaults — mirroring `mem0/llms/sarvam.py` in the
+ * Python SDK. The API key resolves from `config.apiKey` or the `SARVAM_API_KEY`
+ * env var, and the base URL from `config.baseURL`, `SARVAM_API_BASE`, else
+ * `https://api.sarvam.ai/v1`.
+ */
+export class SarvamLLM extends OpenAILLM {
+  constructor(config: LLMConfig) {
+    const apiKey = config.apiKey || process.env.SARVAM_API_KEY;
+    if (!apiKey) {
+      throw new Error("Sarvam API key is required");
+    }
+    super({
+      ...config,
+      apiKey,
+      baseURL:
+        config.baseURL ||
+        process.env.SARVAM_API_BASE ||
+        "https://api.sarvam.ai/v1",
+      model: config.model || "sarvam-m",
+    });
+  }
+
+  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(`Sarvam LLM 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(`Sarvam LLM failed: ${message}`);
+    }
+  }
+}

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

@@ -25,6 +25,7 @@ import { OllamaLLM } from "../llms/ollama";
 import { LMStudioLLM } from "../llms/lmstudio";
 import { DeepSeekLLM } from "../llms/deepseek";
 import { XAILLM } from "../llms/xai";
+import { SarvamLLM } from "../llms/sarvam";
 import { LiteLLM } from "../llms/litellm";
 import { MiniMaxLLM } from "../llms/minimax";
 import { TogetherLLM } from "../llms/together";
@@ -109,6 +110,8 @@ export class LLMFactory {
         return new DeepSeekLLM(config);
       case "xai":
         return new XAILLM(config);
+      case "sarvam":
+        return new SarvamLLM(config);
       case "litellm":
         return new LiteLLM(config);
       case "minimax":

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

@@ -107,6 +107,11 @@ jest.mock("../src/llms/xai", () => ({
     .fn()
     .mockImplementation((config) => ({ type: "xai-llm", config })),
 }));
+jest.mock("../src/llms/sarvam", () => ({
+  SarvamLLM: jest
+    .fn()
+    .mockImplementation((config) => ({ type: "sarvam-llm", config })),
+}));
 jest.mock("../src/llms/litellm", () => ({
   LiteLLM: jest
     .fn()
@@ -269,6 +274,7 @@ describe("LLMFactory", () => {
     ["lmstudio"],
     ["deepseek"],
     ["xai"],
+    ["sarvam"],
     ["litellm"],
     ["minimax"],
     ["together"],

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

@@ -0,0 +1,153 @@
+/// <reference types="jest" />
+/**
+ * Sarvam LLM — unit tests (mocked OpenAI).
+ */
+
+import { SarvamLLM } from "../src/llms/sarvam";
+
+const mockCreate = jest.fn();
+const mockOpenAICtor = jest.fn();
+
+jest.mock("openai", () => {
+  return jest.fn().mockImplementation((config) => {
+    mockOpenAICtor(config);
+    return { chat: { completions: { create: mockCreate } } };
+  });
+});
+
+describe("SarvamLLM (unit)", () => {
+  const ORIGINAL_ENV = process.env;
+
+  beforeEach(() => {
+    jest.clearAllMocks();
+    process.env = { ...ORIGINAL_ENV };
+    delete process.env.SARVAM_API_KEY;
+    delete process.env.SARVAM_API_BASE;
+    mockCreate.mockResolvedValue({
+      choices: [{ message: { content: "hi", role: "assistant" } }],
+    });
+  });
+
+  afterAll(() => {
+    process.env = ORIGINAL_ENV;
+  });
+
+  it("defaults to sarvam-m and the Sarvam base URL (matching the Python provider)", async () => {
+    const llm = new SarvamLLM({ apiKey: "test-key" });
+    const result = await llm.generateResponse([
+      { role: "user", content: "hello" },
+    ]);
+
+    expect(mockOpenAICtor).toHaveBeenCalledWith(
+      expect.objectContaining({
+        apiKey: "test-key",
+        baseURL: "https://api.sarvam.ai/v1",
+      }),
+    );
+    expect(mockCreate).toHaveBeenCalledWith(
+      expect.objectContaining({ model: "sarvam-m" }),
+    );
+    expect(result).toBe("hi");
+  });
+
+  it("resolves SARVAM_API_KEY / SARVAM_API_BASE from the environment", () => {
+    process.env.SARVAM_API_KEY = "env-key";
+    process.env.SARVAM_API_BASE = "https://custom.sarvam.ai/v1";
+
+    new SarvamLLM({});
+
+    expect(mockOpenAICtor).toHaveBeenCalledWith(
+      expect.objectContaining({
+        apiKey: "env-key",
+        baseURL: "https://custom.sarvam.ai/v1",
+      }),
+    );
+  });
+
+  it("prefers explicit config over defaults and the environment", async () => {
+    process.env.SARVAM_API_KEY = "env-key";
+
+    const llm = new SarvamLLM({
+      apiKey: "explicit-key",
+      baseURL: "https://proxy.example.com/v1",
+      model: "sarvam-2b",
+    });
+    await llm.generateResponse([{ role: "user", content: "hello" }]);
+
+    expect(mockOpenAICtor).toHaveBeenCalledWith(
+      expect.objectContaining({
+        apiKey: "explicit-key",
+        baseURL: "https://proxy.example.com/v1",
+      }),
+    );
+    expect(mockCreate).toHaveBeenCalledWith(
+      expect.objectContaining({ model: "sarvam-2b" }),
+    );
+  });
+
+  it("throws when no API key is provided", () => {
+    expect(() => new SarvamLLM({})).toThrow("Sarvam API key is required");
+  });
+
+  it("generateResponse() handles tool calls", async () => {
+    mockCreate.mockResolvedValueOnce({
+      choices: [
+        {
+          message: {
+            content: "",
+            role: "assistant",
+            tool_calls: [
+              {
+                function: { name: "get_weather", arguments: '{"city": "SF"}' },
+              },
+            ],
+          },
+        },
+      ],
+    });
+
+    const llm = new SarvamLLM({ apiKey: "test-key" });
+    const result = await llm.generateResponse(
+      [{ role: "user", content: "weather?" }],
+      undefined,
+      [{ type: "function", function: { name: "get_weather" } }],
+    );
+
+    expect(result).toEqual({
+      content: "",
+      role: "assistant",
+      toolCalls: [{ name: "get_weather", arguments: '{"city": "SF"}' }],
+    });
+  });
+
+  it("generateResponse() wraps downstream errors with a Sarvam-specific message", async () => {
+    mockCreate.mockRejectedValueOnce(new Error("Connection refused"));
+    const llm = new SarvamLLM({ apiKey: "test-key" });
+
+    await expect(
+      llm.generateResponse([{ role: "user", content: "hi" }]),
+    ).rejects.toThrow("Sarvam LLM failed: Connection refused");
+  });
+
+  it("generateChat() returns the LLMResponse shape", async () => {
+    mockCreate.mockResolvedValueOnce({
+      choices: [{ message: { content: "I can help.", role: "assistant" } }],
+    });
+
+    const llm = new SarvamLLM({ apiKey: "test-key" });
+    const result = await llm.generateChat([
+      { role: "user", content: "help me" },
+    ]);
+
+    expect(result).toEqual({ content: "I can help.", role: "assistant" });
+  });
+
+  it("generateChat() wraps downstream errors with a Sarvam-specific message", async () => {
+    mockCreate.mockRejectedValueOnce(new Error("Timeout"));
+    const llm = new SarvamLLM({ apiKey: "test-key" });
+
+    await expect(
+      llm.generateChat([{ role: "user", content: "hi" }]),
+    ).rejects.toThrow("Sarvam LLM failed: Timeout");
+  });
+});