[Bug]: Context serialization fails when using Mem0Memory: "Can't instantiate abstract class BaseMemory"

### Bug Description

  ## Bug Description

  When using `Mem0Memory` with `AgentWorkflow` and attempting to save/restore workflow context using `Context.to_dict()` and `Context.from_dict()`, the
  deserialization fails with an error about instantiating abstract class `BaseMemory`.

  The issue occurs because `Mem0Memory` objects get serialized into the workflow context's `globals` section, but during deserialization, the system
  attempts to instantiate the abstract `BaseMemory` class instead of the concrete `Mem0Memory` implementation.

  ## Error Message
  WARNING: Failed to restore context, starting fresh: Failed to deserialize value for key memory: Can't instantiate abstract class BaseMemory with
  abstract methods from_defaults, get, get_all, put, reset, set

### Version

 - **LlamaIndex Core**: 0.12.31   - **LlamaIndex Memory Mem0**: 0.3.1   - **Python Version**: 3.11.12

### Steps to Reproduce

. Create an `AgentWorkflow` with `Mem0Memory`:

  ```python
  from llama_index.core.workflow import Context, JsonSerializer
  from llama_index.memory.mem0 import Mem0Memory
  from llama_index.core.agent.workflow import AgentWorkflow, FunctionAgent
  from pathlib import Path
  import json

  # Create Mem0Memory instance
  mem0_memory = Mem0Memory.from_client(
      context={"user_id": "test_user", "conversation_id": "test_conv"},
      search_msg_limit=10
  )

  # Create simple workflow
  agent = FunctionAgent(
      name="TestAgent",
      description="Test agent",
      system_prompt="You are a test agent",
      llm=your_llm,  # Your LLM instance
      tools=[],
  )

  workflow = AgentWorkflow(
      agents=[agent],
      root_agent=agent.name,
  )

  # First run - works fine
  ctx = Context(workflow)
  response = await workflow.run(user_msg="Hello", ctx=ctx, memory=mem0_memory)

  # Save context - this works
  serializer = JsonSerializer()
  context_data = ctx.to_dict(serializer=serializer)
  with open("test_context.json", "w") as f:
      json.dump(context_data, f)

  # Load context - this fails
  with open("test_context.json", "r") as f:
      context_data = json.load(f)

  # This line throws the error
  ctx_restored = Context.from_dict(workflow, context_data, serializer=serializer)
```
  2. Run the workflow once with memory
  3. Save the context using ctx.to_dict()
  4. Try to restore the context using Context.from_dict() - this fails

  Expected Behavior

  Context should serialize and deserialize correctly when using Mem0Memory objects, allowing for persistent workflow state across sessions.

  Actual Behavior

  Deserialization fails because the serialized Mem0Memory object in the context cannot be properly reconstructed, causing the system to attempt
  instantiation of the abstract BaseMemory class.

  Workaround

  Currently using context filtering to remove memory objects before serialization:

  # Before saving context
  context_data = ctx.to_dict(serializer=serializer)
  if "globals" in context_data and "memory" in context_data["globals"]:
      context_data["globals"].pop("memory", None)

  Additional Context

  - This issue appears to be specific to Mem0Memory - other memory implementations may not have the same serialization issues
  - The memory object gets embedded in the workflow context's globals section
  - Both JsonSerializer and JsonPickleSerializer exhibit the same behavior
  - The issue prevents proper stateful agent workflows that persist across sessions


### Relevant Logs/Tracbacks

```shell

```

Labels: bug, triage
State: closed