feat(oss): port v3 pipeline with hybrid search, entity extraction, and additive scoring (#4805)

Co-authored-by: Soumil Rathi <soumilrathi@gmail.com>
Co-authored-by: Saket Aryan <saketaryan2002@gmail.com>
Co-authored-by: chaithanyak42 <chaithanya.kumar42a@gmail.com>
Co-authored-by: kartik-mem0 <kartik.labhshetwar@mem0.ai>

mem0-ts/src/oss/tests/config-manager.test.ts

@@ -363,78 +363,6 @@ describe("ConfigManager", () => {
   });
 });
 
-// ─────────────────────────────────────────────────────────────────────────
-// Graph store LLM config propagation (issue #3425)
-// ─────────────────────────────────────────────────────────────────────────
-describe("mergeConfig - graph store LLM config (issue #3425)", () => {
-  const baseEmbedder = {
-    provider: "openai",
-    config: { apiKey: "test-key" },
-  };
-  const baseVectorStore = {
-    provider: "memory",
-    config: { collectionName: "test" },
-  };
-  const graphStoreNeo4j = {
-    provider: "neo4j",
-    config: {
-      url: "neo4j://localhost:7687",
-      username: "neo4j",
-      password: "password",
-    },
-  };
-
-  it("should NOT have a default graphStore.llm — root llm should be the fallback", () => {
-    const config = ConfigManager.mergeConfig({
-      embedder: baseEmbedder,
-      vectorStore: baseVectorStore,
-      llm: {
-        provider: "anthropic",
-        config: { model: "claude-sonnet-4-20250514" },
-      },
-      graphStore: graphStoreNeo4j,
-    });
-
-    // graphStore should NOT have its own llm after merge
-    expect(config.graphStore?.llm).toBeUndefined();
-    // root llm should be anthropic
-    expect(config.llm.provider).toBe("anthropic");
-    expect(config.llm.config.model).toBe("claude-sonnet-4-20250514");
-  });
-
-  it("should preserve explicit graphStore.llm when user provides it", () => {
-    const config = ConfigManager.mergeConfig({
-      embedder: baseEmbedder,
-      vectorStore: baseVectorStore,
-      llm: {
-        provider: "anthropic",
-        config: { model: "claude-sonnet-4-20250514" },
-      },
-      graphStore: {
-        ...graphStoreNeo4j,
-        llm: { provider: "openai", config: { model: "gpt-4o" } },
-      },
-    });
-
-    // graphStore should have its own llm
-    expect(config.graphStore?.llm?.provider).toBe("openai");
-    expect(config.graphStore?.llm?.config).toEqual({ model: "gpt-4o" });
-    // root llm should still be anthropic
-    expect(config.llm.provider).toBe("anthropic");
-  });
-
-  it("should not have graphStore.llm when user does not provide one", () => {
-    const config = ConfigManager.mergeConfig({
-      embedder: baseEmbedder,
-      vectorStore: baseVectorStore,
-      llm: { provider: "openai", config: { model: "gpt-4o" } },
-    });
-
-    // Default graphStore should not have llm
-    expect(config.graphStore?.llm).toBeUndefined();
-  });
-});
-
 // ─────────────────────────────────────────────────────────────────────────
 // Memory class – LM Studio end-to-end flow (mocked factories)
 // ─────────────────────────────────────────────────────────────────────────
@@ -520,7 +448,7 @@ describe("Memory – LM Studio end-to-end flow", () => {
       disableHistory: true,
     });
 
-    await mem.getAll({ userId: "u1" });
+    await mem.getAll({ filters: { user_id: "u1" } });
 
     expect(mockEmbedderFactory.create).toHaveBeenCalledWith(
       "lmstudio",
@@ -555,7 +483,7 @@ describe("Memory – LM Studio end-to-end flow", () => {
       disableHistory: true,
     });
 
-    await mem.getAll({ userId: "u1" });
+    await mem.getAll({ filters: { user_id: "u1" } });
 
     expect(mockEmbedder.embed).toHaveBeenCalledWith("dimension probe");
     const vsCall = mockVectorStoreFactory.create.mock.calls[0];
@@ -583,7 +511,7 @@ describe("Memory – LM Studio end-to-end flow", () => {
       disableHistory: true,
     });
 
-    await mem.getAll({ userId: "u1" });
+    await mem.getAll({ filters: { user_id: "u1" } });
 
     expect(mockEmbedderFactory.create).toHaveBeenCalledWith(
       "lmstudio",
@@ -636,7 +564,7 @@ describe("Memory – LM Studio end-to-end flow", () => {
     });
 
     const result = await mem.search("What does the user like?", {
-      userId: "u1",
+      filters: { user_id: "u1" },
     });
 
     expect(mockEmbedder.embed).toHaveBeenCalledWith("What does the user like?");