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@Boreas618 Boreas618 commented Oct 17, 2025

Summary by CodeRabbit

Release Notes

  • New Features
    • Added deep research capability enabling multi-stage information gathering, analysis, and synthesis
    • Integrated Tavily search functionality for web-based research queries
    • Introduced MCP server architecture supporting research workflow coordination
    • Added research orchestration system with planning, execution, and result compression workflows

Description

This PR implements deep research with scaffolding.

Test Coverage

PR Checklist

Please review the following before submitting your PR:

  • PR description clearly explains what and why. If using CodeRabbit's summary, please make sure it makes sense.

  • PR Follows TRT-LLM CODING GUIDELINES to the best of your knowledge.

  • Test cases are provided for new code paths (see test instructions)

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  • CODEOWNERS updated if ownership changes

  • Documentation updated as needed

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  • Please check this after reviewing the above items as appropriate for this PR.

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@svc-trtllm-gh-bot svc-trtllm-gh-bot added the Community want to contribute PRs initiated from Community label Oct 17, 2025
@Boreas618 Boreas618 force-pushed the scaffolding-deep-research branch from 5dedf53 to 154bb5d Compare October 30, 2025 07:28
@Boreas618 Boreas618 marked this pull request as ready for review October 30, 2025 07:29
@Boreas618 Boreas618 requested a review from a team as a code owner October 30, 2025 07:29
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📝 Walkthrough

Walkthrough

This pull request introduces a comprehensive DeepResearch scaffolding module that orchestrates multi-step research workflows combining supervisor-researcher control patterns, MCP-based tool integration, and Tavily-powered web search capabilities, along with a complete example server and supporting utilities.

Changes

Cohort / File(s) Summary
DeepResearch Core Controllers
tensorrt_llm/scaffolding/contrib/DeepResearch/supervisor.py, tensorrt_llm/scaffolding/contrib/DeepResearch/researcher.py
New Supervisor and Researcher controller classes that orchestrate multi-step research workflows. Supervisor manages tool-based research orchestration with research brief generation and final report synthesis. Researcher handles iterative web search and reflection operations with compression phase. Both integrate task management and tool invocation.
DeepResearch Prompts & Utilities
tensorrt_llm/scaffolding/contrib/DeepResearch/prompts.py, tensorrt_llm/scaffolding/contrib/DeepResearch/utils.py
New prompts module defines six system prompts governing research brief generation, supervision, research execution, compression, and final report production. Utils module introduces RoleMessage dataclass hierarchy (UserMessage, AssistantMessage, SystemMessage) and date formatting utility for prompt construction.
DeepResearch Package Exports
tensorrt_llm/scaffolding/contrib/DeepResearch/__init__.py
Updated package exports to publicly expose Supervisor and Researcher classes via __all__.
TavilyMCP Example Server
examples/scaffolding/contrib/DeepResearch/TavilyMCP/README.md, examples/scaffolding/contrib/DeepResearch/TavilyMCP/pyproject.toml, examples/scaffolding/contrib/DeepResearch/TavilyMCP/travily.py
New example MCP server project integrating Tavily search API. Includes project configuration (Python >=3.12, dependencies: httpx, mcp, openai, tavily-python), FastMCP tool definition (tavily_search), and Starlette-based SSE server with uvicorn startup.
DeepResearch Orchestration Example
examples/scaffolding/contrib/DeepResearch/run_deep_research.py
New example script demonstrating full research orchestration using OpenaiWorker, MCPWorker, Supervisor, and ScaffoldingLlm to generate market analysis research output.
Chat Task Extension
tensorrt_llm/scaffolding/contrib/mcp/chat_task.py
Added static from_messages() constructor method to ChatTask for direct message and tool specification.

Sequence Diagram(s)

sequenceDiagram
    actor User
    participant RunScript as run_deep_research.py
    participant Supervisor
    participant Researcher
    participant MCPWorker as MCP<br/>(Tavily)
    participant OpenAI as OpenAI<br/>Worker

    User->>RunScript: Execute with prompt
    RunScript->>Supervisor: Create & start orchestration
    
    Supervisor->>OpenAI: Generate research brief<br/>(ChatTask)
    OpenAI-->>Supervisor: research_brief
    
    loop Up to max_research_iter
        Supervisor->>OpenAI: chat_with_tools<br/>(think_tool, conduct_research,<br/>complete_research)
        OpenAI-->>Supervisor: tool calls
        
        alt think_tool
            Supervisor->>Supervisor: Record reflection
        else conduct_research
            Supervisor->>Researcher: Create ResearchTask(s)
            
            loop Up to max_tools_iter
                Researcher->>OpenAI: Generate with<br/>research_system_prompt
                OpenAI-->>Researcher: tool calls
                Researcher->>MCPWorker: Execute tavily_search
                MCPWorker-->>Researcher: Search results
                Researcher->>Researcher: Accumulate results
            end
            
            Researcher->>OpenAI: Compress findings<br/>(compress_system_prompt)
            OpenAI-->>Researcher: Compressed research
            Researcher-->>Supervisor: ResearchTask with result
        else complete_research
            Supervisor->>Supervisor: Break loop
        end
    end
    
    Supervisor->>OpenAI: Generate final report<br/>(final_report_generation_prompt)
    OpenAI-->>Supervisor: final_report
    Supervisor-->>RunScript: Complete with output
    RunScript->>User: Print results
Loading

Estimated code review effort

🎯 4 (Complex) | ⏱️ ~50 minutes

  • Supervisor and Researcher workflows: Dense orchestration logic with multi-stage iteration, tool invocation handling, and task coordination requires careful tracing of control flow and state management across process generators.
  • Prompt engineering at scale: Six substantial system prompts with embedded formatting rules, constraints, and citation mechanics demand validation for consistency and correctness.
  • MCP integration: Tavily server implementation combines FastMCP tool definition, Starlette SSE routing, and transport layer setup; requires understanding of MCP SSE lifecycle.
  • Cross-module dependencies: Research orchestration spans multiple new modules (supervisor, researcher, prompts, utils) with interdependencies; integration points need verification.
  • Example orchestration: run_deep_research.py ties together AsyncOpenAI, MCPWorker, Supervisor, and ScaffoldingLlm; requires validation of async flow and worker lifecycle management.

Pre-merge checks and finishing touches

❌ Failed checks (2 warnings)
Check name Status Explanation Resolution
Description Check ⚠️ Warning The PR description is largely incomplete and fails to meet the template requirements. The Description section contains only one minimal sentence ("This PR implements deep research with scaffolding") without explaining the problem being solved or the solution in detail. The Test Coverage section is entirely empty with no test cases listed, and the PR Checklist remains unchecked despite being a required final confirmation. While the title format is correct, the substantive description sections that would help reviewers understand the scope, rationale, and testing strategy are absent or inadequate. The author should expand the Description section to explain what problem deep research solves and how the Researcher, Supervisor, and supporting components address it. The Test Coverage section must list specific tests or test scenarios that validate the new functionality. Additionally, the author should review the PR Checklist items (particularly regarding coding guidelines, test coverage, and dependency scanning) and check the box only after confirming all applicable items are satisfied.
Docstring Coverage ⚠️ Warning Docstring coverage is 9.52% which is insufficient. The required threshold is 80.00%. You can run @coderabbitai generate docstrings to improve docstring coverage.
✅ Passed checks (1 passed)
Check name Status Explanation
Title Check ✅ Passed The PR title "[None][feat] Deep Research Implemented with Scaffolding" directly and clearly describes the main objective of the changeset. The title correctly follows the repository format with [None] for no ticket and [feat] for feature type. The changeset contains numerous new files implementing deep research functionality (researchers, supervisors, prompts, MCP integration, utilities, and example scripts) all aligned with the title's scope. The title is specific enough for a developer scanning history to immediately understand this PR adds a deep research feature using the scaffolding framework.
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Actionable comments posted: 9

🧹 Nitpick comments (3)
examples/scaffolding/contrib/DeepResearch/TavilyMCP/README.md (1)

7-9: Add a language tag to the fenced block.

Markdownlint is flagging this fence; please annotate it (e.g., ```bash) so the snippet renders and linting passes.

tensorrt_llm/scaffolding/contrib/DeepResearch/__init__.py (1)

1-4: Sort __all__ to satisfy RUF022.

Ruff expects __all__ in isort order, so please swap the entries to ["Researcher", "Supervisor"].
(docs.astral.sh)

examples/scaffolding/contrib/DeepResearch/TavilyMCP/travily.py (1)

22-31: Validate the Tavily API key before performing searches.

If TAVILY_API_KEY is missing, TavilyClient raises MissingAPIKeyError when search runs; failing fast with a descriptive exception (or defaulting to TavilyClient() so it auto-loads the key) makes debugging much easier for users.
(docs.tavily.com)

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Reviewing files that changed from the base of the PR and between 6b755fd and 154bb5d.

📒 Files selected for processing (10)
  • examples/scaffolding/contrib/DeepResearch/TavilyMCP/README.md (1 hunks)
  • examples/scaffolding/contrib/DeepResearch/TavilyMCP/pyproject.toml (1 hunks)
  • examples/scaffolding/contrib/DeepResearch/TavilyMCP/travily.py (1 hunks)
  • examples/scaffolding/contrib/DeepResearch/run_deep_research.py (1 hunks)
  • tensorrt_llm/scaffolding/contrib/DeepResearch/__init__.py (1 hunks)
  • tensorrt_llm/scaffolding/contrib/DeepResearch/prompts.py (1 hunks)
  • tensorrt_llm/scaffolding/contrib/DeepResearch/researcher.py (1 hunks)
  • tensorrt_llm/scaffolding/contrib/DeepResearch/supervisor.py (1 hunks)
  • tensorrt_llm/scaffolding/contrib/DeepResearch/utils.py (1 hunks)
  • tensorrt_llm/scaffolding/contrib/mcp/chat_task.py (2 hunks)
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**/*.{h,hpp,hh,hxx,cpp,cxx,cc,cu,cuh,py}

📄 CodeRabbit inference engine (CODING_GUIDELINES.md)

Use only spaces, no tabs; indent with 4 spaces.

Files:

  • examples/scaffolding/contrib/DeepResearch/run_deep_research.py
  • examples/scaffolding/contrib/DeepResearch/TavilyMCP/travily.py
  • tensorrt_llm/scaffolding/contrib/DeepResearch/supervisor.py
  • tensorrt_llm/scaffolding/contrib/DeepResearch/utils.py
  • tensorrt_llm/scaffolding/contrib/DeepResearch/__init__.py
  • tensorrt_llm/scaffolding/contrib/mcp/chat_task.py
  • tensorrt_llm/scaffolding/contrib/DeepResearch/prompts.py
  • tensorrt_llm/scaffolding/contrib/DeepResearch/researcher.py
**/*.py

📄 CodeRabbit inference engine (CODING_GUIDELINES.md)

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Indent Python code with 4 spaces; do not use tabs.
Maintain module namespace when importing; prefer 'from package.subpackage import foo' then 'foo.SomeClass()' instead of importing the class directly.
Python filenames should be snake_case (e.g., some_file.py).
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Files:

  • examples/scaffolding/contrib/DeepResearch/run_deep_research.py
  • examples/scaffolding/contrib/DeepResearch/TavilyMCP/travily.py
  • tensorrt_llm/scaffolding/contrib/DeepResearch/supervisor.py
  • tensorrt_llm/scaffolding/contrib/DeepResearch/utils.py
  • tensorrt_llm/scaffolding/contrib/DeepResearch/__init__.py
  • tensorrt_llm/scaffolding/contrib/mcp/chat_task.py
  • tensorrt_llm/scaffolding/contrib/DeepResearch/prompts.py
  • tensorrt_llm/scaffolding/contrib/DeepResearch/researcher.py
**/*.{cpp,cxx,cc,h,hpp,hh,hxx,cu,cuh,py}

📄 CodeRabbit inference engine (CODING_GUIDELINES.md)

Prepend the NVIDIA Apache-2.0 copyright header with current year to the top of all source files (e.g., .cpp, .h, .cu, .py).

Files:

  • examples/scaffolding/contrib/DeepResearch/run_deep_research.py
  • examples/scaffolding/contrib/DeepResearch/TavilyMCP/travily.py
  • tensorrt_llm/scaffolding/contrib/DeepResearch/supervisor.py
  • tensorrt_llm/scaffolding/contrib/DeepResearch/utils.py
  • tensorrt_llm/scaffolding/contrib/DeepResearch/__init__.py
  • tensorrt_llm/scaffolding/contrib/mcp/chat_task.py
  • tensorrt_llm/scaffolding/contrib/DeepResearch/prompts.py
  • tensorrt_llm/scaffolding/contrib/DeepResearch/researcher.py
🧬 Code graph analysis (5)
examples/scaffolding/contrib/DeepResearch/run_deep_research.py (5)
tensorrt_llm/scaffolding/worker.py (2)
  • OpenaiWorker (62-120)
  • register_task_handler (20-23)
tensorrt_llm/scaffolding/scaffolding_llm.py (1)
  • ScaffoldingLlm (22-237)
tensorrt_llm/scaffolding/contrib/DeepResearch/researcher.py (2)
  • Researcher (30-138)
  • WorkerTag (32-33)
tensorrt_llm/scaffolding/contrib/DeepResearch/supervisor.py (2)
  • Supervisor (31-202)
  • WorkerTag (33-34)
tensorrt_llm/scaffolding/contrib/mcp/chat_task.py (1)
  • ChatTask (8-29)
examples/scaffolding/contrib/DeepResearch/TavilyMCP/travily.py (1)
tests/unittest/disaggregated/test_cluster_storage.py (1)
  • Server (29-41)
tensorrt_llm/scaffolding/contrib/DeepResearch/supervisor.py (5)
tensorrt_llm/scaffolding/contrib/mcp/chat_task.py (3)
  • ChatTask (8-29)
  • create_from_prompt (15-20)
  • from_messages (23-29)
tensorrt_llm/scaffolding/controller.py (1)
  • Controller (15-31)
tensorrt_llm/scaffolding/task.py (1)
  • Task (12-20)
tensorrt_llm/scaffolding/contrib/DeepResearch/researcher.py (5)
  • Researcher (30-138)
  • ResearchTask (18-27)
  • WorkerTag (32-33)
  • process (75-138)
  • from_topic (23-27)
tensorrt_llm/scaffolding/contrib/DeepResearch/utils.py (5)
  • AssistantMessage (43-46)
  • SystemMessage (50-53)
  • UserMessage (36-39)
  • get_today_str (6-13)
  • to_dict (27-28)
tensorrt_llm/scaffolding/contrib/DeepResearch/__init__.py (2)
tensorrt_llm/scaffolding/contrib/DeepResearch/researcher.py (1)
  • Researcher (30-138)
tensorrt_llm/scaffolding/contrib/DeepResearch/supervisor.py (1)
  • Supervisor (31-202)
tensorrt_llm/scaffolding/contrib/DeepResearch/researcher.py (5)
tensorrt_llm/scaffolding/controller.py (1)
  • Controller (15-31)
tensorrt_llm/scaffolding/task.py (1)
  • Task (12-20)
tensorrt_llm/scaffolding/contrib/mcp/chat_task.py (2)
  • ChatTask (8-29)
  • from_messages (23-29)
tensorrt_llm/scaffolding/contrib/DeepResearch/utils.py (5)
  • AssistantMessage (43-46)
  • SystemMessage (50-53)
  • UserMessage (36-39)
  • get_today_str (6-13)
  • to_dict (27-28)
tensorrt_llm/scaffolding/contrib/DeepResearch/supervisor.py (2)
  • WorkerTag (33-34)
  • process (90-202)
🪛 markdownlint-cli2 (0.18.1)
examples/scaffolding/contrib/DeepResearch/TavilyMCP/README.md

7-7: Fenced code blocks should have a language specified

(MD040, fenced-code-language)

🪛 Ruff (0.14.2)
examples/scaffolding/contrib/DeepResearch/run_deep_research.py

31-31: f-string without any placeholders

Remove extraneous f prefix

(F541)

examples/scaffolding/contrib/DeepResearch/TavilyMCP/travily.py

44-44: Unused noqa directive (non-enabled: SLF001)

Remove unused noqa directive

(RUF100)


62-62: Unused noqa directive (unknown: WPS437)

Remove unused noqa directive

(RUF100)


67-67: Possible binding to all interfaces

(S104)

tensorrt_llm/scaffolding/contrib/DeepResearch/supervisor.py

40-40: Undefined name tools

(F821)


90-90: Unused method argument: kwargs

(ARG002)

tensorrt_llm/scaffolding/contrib/DeepResearch/__init__.py

4-4: __all__ is not sorted

Apply an isort-style sorting to __all__

(RUF022)

tensorrt_llm/scaffolding/contrib/DeepResearch/researcher.py

75-75: Unused method argument: kwargs

(ARG002)


126-128: Consider iterable unpacking instead of concatenation

Replace with iterable unpacking

(RUF005)

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--test-backend "pytorch, cpp" (OPTIONAL) : Skip test stages which don't match the specified backends. Only support [pytorch, cpp, tensorrt, triton]. Examples: "pytorch, cpp" (does not run test stages with tensorrt or triton backend). Note: Does NOT update GitHub pipeline status.

--only-multi-gpu-test (OPTIONAL) : Only run the multi-GPU tests. Note: Does NOT update GitHub check status.

--disable-multi-gpu-test (OPTIONAL) : Disable the multi-GPU tests. Note: Does NOT update GitHub check status.

--add-multi-gpu-test (OPTIONAL) : Force run the multi-GPU tests in addition to running L0 pre-merge pipeline.

--post-merge (OPTIONAL) : Run the L0 post-merge pipeline instead of the ordinary L0 pre-merge pipeline.

--extra-stage "H100_PCIe-TensorRT-Post-Merge-1, xxx" (OPTIONAL) : Run the ordinary L0 pre-merge pipeline and specified test stages. Examples: --extra-stage "H100_PCIe-TensorRT-Post-Merge-1, xxx".

--detailed-log (OPTIONAL) : Enable flushing out all logs to the Jenkins console. This will significantly increase the log volume and may slow down the job.

--debug (OPTIONAL) : Experimental feature. Enable access to the CI container for debugging purpose. Note: Specify exactly one stage in the stage-list parameter to access the appropriate container environment. Note: Does NOT update GitHub check status.

kill

kill

Kill all running builds associated with pull request.

skip

skip --comment COMMENT

Skip testing for latest commit on pull request. --comment "Reason for skipping build/test" is required. IMPORTANT NOTE: This is dangerous since lack of user care and validation can cause top of tree to break.

reuse-pipeline

reuse-pipeline

Reuse a previous pipeline to validate current commit. This action will also kill all currently running builds associated with the pull request. IMPORTANT NOTE: This is dangerous since lack of user care and validation can cause top of tree to break.

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/bot run --disable-fail-fast

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PR_Github #23569 Bot args parsing error: usage: /bot [-h]
{run,kill,skip,submit,reviewers,reuse-pipeline,reuse-review} ...
/bot: error: unrecognized arguments: --disable-fail-test

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PR_Github #23572 Bot args parsing error: usage: /bot [-h]
{run,kill,skip,submit,reviewers,reuse-pipeline,reuse-review} ...
/bot: error: unrecognized arguments: --help

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PR_Github #23574 [ run ] triggered by Bot. Commit: 35f9bc6

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PR_Github #23574 [ run ] completed with state SUCCESS. Commit: 35f9bc6
/LLM/main/L0_MergeRequest_PR pipeline #17739 completed with status: 'FAILURE'

@WeiHaocheng WeiHaocheng force-pushed the scaffolding-deep-research branch from 35f9bc6 to 04a7753 Compare November 5, 2025 09:41
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/bot run --disable-fail-test

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PR_Github #23629 Bot args parsing error: usage: /bot [-h]
{run,kill,skip,submit,reviewers,reuse-pipeline,reuse-review} ...
/bot: error: unrecognized arguments: --disable-fail-test

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/bot run

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PR_Github #23646 [ run ] triggered by Bot. Commit: 04a7753

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PR_Github #23646 [ run ] completed with state SUCCESS. Commit: 04a7753
/LLM/main/L0_MergeRequest_PR pipeline #17791 completed with status: 'FAILURE'

@WeiHaocheng WeiHaocheng force-pushed the scaffolding-deep-research branch from 04a7753 to 5e53d68 Compare November 5, 2025 14:42
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/bot run

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@WeiHaocheng
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/bot run

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PR_Github #23656 [ run ] triggered by Bot. Commit: 5e53d68

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PR_Github #23655 [ run ] triggered by Bot. Commit: 5e53d68

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PR_Github #23656 [ run ] completed with state ABORTED. Commit: 5e53d68
LLM/main/L0_MergeRequest_PR #17796 (Blue Ocean) completed with status: ABORTED

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PR_Github #23655 [ run ] completed with state SUCCESS. Commit: 5e53d68
/LLM/main/L0_MergeRequest_PR pipeline #17797 completed with status: 'SUCCESS'

@WeiHaocheng WeiHaocheng merged commit cc12d33 into NVIDIA:main Nov 6, 2025
4 of 5 checks passed
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5 participants