Added support for Ollama in TS SDK (#2345)

Co-authored-by: Dev Khant <devkhant24@gmail.com>

mem0-ts/src/oss/examples/basic.ts

@@ -116,6 +116,36 @@ async function runTests(memory: Memory) {
   }
 }
 
+async function demoLocalMemory() {
+  console.log("\n=== Testing In-Memory Vector Store with Ollama===\n");
+
+  const memory = new Memory({
+    version: "v1.1",
+    embedder: {
+      provider: "ollama",
+      config: {
+        model: "nomic-embed-text:latest",
+      },
+    },
+    vectorStore: {
+      provider: "memory",
+      config: {
+        collectionName: "memories",
+        dimension: 768, // 768 is the dimension of the nomic-embed-text model
+      },
+    },
+    llm: {
+      provider: "ollama",
+      config: {
+        model: "llama3.1:8b",
+      },
+    },
+    // historyDbPath: "memory.db",
+  });
+
+  await runTests(memory);
+}
+
 async function demoMemoryStore() {
   console.log("\n=== Testing In-Memory Vector Store ===\n");
 
@@ -346,6 +376,9 @@ async function main() {
   // Test in-memory store
   await demoMemoryStore();
 
+  // Test in-memory store with Ollama
+  await demoLocalMemory();
+
   // Test graph memory if Neo4j environment variables are set
   if (
     process.env.NEO4J_URL &&
@@ -384,4 +417,4 @@ async function main() {
   }
 }
 
-// main();
+main();

mem0-ts/src/oss/examples/local-llms.ts

@@ -0,0 +1,93 @@
+import { Memory } from "../src";
+import { Ollama } from "ollama";
+import * as readline from "readline";
+
+const memory = new Memory({
+  embedder: {
+    provider: "ollama",
+    config: {
+      model: "nomic-embed-text:latest",
+    },
+  },
+  vectorStore: {
+    provider: "memory",
+    config: {
+      collectionName: "memories",
+      dimension: 768, // since we are using nomic-embed-text
+    },
+  },
+  llm: {
+    provider: "ollama",
+    config: {
+      model: "llama3.1:8b",
+    },
+  },
+  historyDbPath: "local-llms.db",
+});
+
+async function chatWithMemories(message: string, userId = "default_user") {
+  const relevantMemories = await memory.search(message, { userId: userId });
+
+  const memoriesStr = relevantMemories.results
+    .map((entry) => `- ${entry.memory}`)
+    .join("\n");
+
+  const systemPrompt = `You are a helpful AI. Answer the question based on query and memories.
+User Memories:
+${memoriesStr}`;
+
+  const messages = [
+    { role: "system", content: systemPrompt },
+    { role: "user", content: message },
+  ];
+
+  const ollama = new Ollama();
+  const response = await ollama.chat({
+    model: "llama3.1:8b",
+    messages: messages,
+  });
+
+  const assistantResponse = response.message.content || "";
+
+  messages.push({ role: "assistant", content: assistantResponse });
+  await memory.add(messages, { userId: userId });
+
+  return assistantResponse;
+}
+
+async function main() {
+  const rl = readline.createInterface({
+    input: process.stdin,
+    output: process.stdout,
+  });
+
+  console.log("Chat with AI (type 'exit' to quit)");
+
+  const askQuestion = (): Promise<string> => {
+    return new Promise((resolve) => {
+      rl.question("You: ", (input) => {
+        resolve(input.trim());
+      });
+    });
+  };
+
+  try {
+    while (true) {
+      const userInput = await askQuestion();
+
+      if (userInput.toLowerCase() === "exit") {
+        console.log("Goodbye!");
+        rl.close();
+        break;
+      }
+
+      const response = await chatWithMemories(userInput, "sample_user");
+      console.log(`AI: ${response}`);
+    }
+  } catch (error) {
+    console.error("An error occurred:", error);
+    rl.close();
+  }
+}
+
+main().catch(console.error);