feat: Implement memory sharing for EvaluatorOptimizerLLM

[jingx8885]

feat: Implement memory sharing for EvaluatorOptimizerLLM

• Add a shared memory parameter to the EvaluatorOptimizerLLM class.
• Implement the share_memory_from method to enable memory sharing functionality.

This change aims to optimize memory management between the evaluator and optimizer.

For example, the optimizer_llm is often bound to an MCP server. After invoking the MCP and receiving content, the LLM might sometimes "hallucinate" or produce responses inconsistent with the MCP's returned content. The evaluator_llm, when performing its assessment, needs access to the optimizer_llm's memory to better determine if it is hallucinating or generating unexpected output. MeanWhile, optimizer_llm can do better work when having evaluator_llm's memory.

Summary by CodeRabbit

• New Features
  • Added an option to enable shared memory between the evaluator and optimizer, allowing them to reference the same history when desired.

[jingx8885]

@saqadri

[coderabbitai[bot]]

Walkthrough

A new boolean parameter, share_memory, was added to the EvaluatorOptimizerLLM class constructor. When enabled, this parameter causes the evaluator LLM's history to reference the optimizer LLM's history, allowing both to share memory. The change does not affect any other logic or control flow.

Changes

File(s)	Change Summary
src/mcp_agent/workflows/evaluator_optimizer/evaluator_optimizer.py	Added share_memory parameter to EvaluatorOptimizerLLM constructor; enables shared LLM history

Sequence Diagram(s)

sequenceDiagram
    participant Caller
    participant EvaluatorOptimizerLLM
    participant OptimizerLLM
    participant EvaluatorLLM

    Caller->>EvaluatorOptimizerLLM: __init__(..., share_memory=True)
    EvaluatorOptimizerLLM->>OptimizerLLM: initialize
    EvaluatorOptimizerLLM->>EvaluatorLLM: initialize
    alt share_memory is True
        EvaluatorOptimizerLLM->>EvaluatorLLM: set history to OptimizerLLM.history
    end
    EvaluatorOptimizerLLM-->>Caller: instance created

Poem

A toggle for memory, now in the code,
Where histories of LLMs can travel one road.
With a flag set to true, they share what they know,
Optimizer and evaluator in memory’s flow.
Hopping ahead, the agents are clever—
Together in thought, now closer than ever!
🐇✨

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📒 Files selected for processing (1)

• src/mcp_agent/workflows/evaluator_optimizer/evaluator_optimizer.py (3 hunks)

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• src/mcp_agent/workflows/evaluator_optimizer/evaluator_optimizer.py

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• GitHub Check: checks / test

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• [ ] 📝 Generate Docstrings

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