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Description

add benchmark script for evaluating the accuracy of deep research agent.

Copilot AI review requested due to automatic review settings July 11, 2025 09:05
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github-actions bot commented Jul 11, 2025

Dependency Review

✅ No vulnerabilities or license issues found.

Scanned Files

  • DeepResearchAgent/requirements.txt

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Pull Request Overview

Adds a benchmarking harness for measuring the accuracy of the Deep Research Agent by integrating dataset loaders, an LLM-based scoring function, and CLI support.

  • Wraps the agent’s raw output in a JSON field ("answer") in research_agent.py.
  • Introduces eval.py to load questions, invoke the agent, score answers via an LLM judge, and save results.
  • Updates documentation under benchmark/accuracy and the main README to cover setup and usage.

Reviewed Changes

Copilot reviewed 4 out of 4 changed files in this pull request and generated 1 comment.

File Description
DeepResearchAgent/research_agent.py Return payload now wrapped as {"answer": ...}
DeepResearchAgent/benchmark/accuracy/eval.py New benchmark script for accuracy evaluation
DeepResearchAgent/benchmark/accuracy/README.md Instructions for running the accuracy benchmark
DeepResearchAgent/README.md Added note on configuring deep_researcher.yaml in setup
Comments suppressed due to low confidence (2)

DeepResearchAgent/benchmark/accuracy/eval.py:93

  • [nitpick] There are no unit tests covering key functions like load_questions, process_single_question, or run_benchmark. Adding tests will help ensure correctness when loading datasets and computing accuracy.
def load_questions(dataset_names: list[str] | None = None) -> list[dict[str, str]]:

DeepResearchAgent/benchmark/accuracy/eval.py:334

  • The args.agent_config field is referenced in metadata but no --agent-config argument is defined in the parser. Consider adding a corresponding parser argument or renaming this field to match --service-url or another existing flag.
            "agent_config": args.agent_config,

@joshuayao joshuayao added this to the v1.4 milestone Jul 14, 2025
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Can you add some benchmark results in README? And add some recommendations about what LLMs to use with vllm-gaudi?

@lkk12014402
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Can you add some benchmark results in README? And add some recommendations about what LLMs to use with vllm-gaudi?

no problem. I will

@lkk12014402
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Can you add some benchmark results in README? And add some recommendations about what LLMs to use with vllm-gaudi?

add togethercomputer/together-search-bench benchmark accuracy data

@joshuayao joshuayao added this to OPEA Aug 13, 2025
@joshuayao joshuayao moved this to In review in OPEA Aug 13, 2025
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Hi @lkk12014402 could you please help check the CI failures? Thanks.

@joshuayao joshuayao moved this from In review to In progress in OPEA Aug 14, 2025
@chensuyue chensuyue merged commit fe1527f into main Aug 20, 2025
19 checks passed
@chensuyue chensuyue deleted the deep_research_agent_benchmark branch August 20, 2025 03:37
@github-project-automation github-project-automation bot moved this from In progress to Done in OPEA Aug 20, 2025
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8 participants