zhiminy/EvalEng huggingface dataset:
Repository: pytorch/benchmark
Issue: Performance Signal Detected by TorchBench CI on '1.13.0.dev20220619+cu113'
Root cause: Algorithmic Error


TorchBench CI has detected a performance signal.

Base PyTorch version: 1.13.0.dev20220618+cu113

Base PyTorch commit: 1432a3d6acc7ac58269e5ea7ef6b2373e9a3dbf6

Affected PyTorch version: 1.13.0.dev20220619+cu113

Affected PyTorch commit: 0545c85f744cadc6f06616f15748052cd7cebe20

Affected Tests:
- test_eval[yolov3-cpu-eager]: +10.53924%


cc @xuzhao9


Workflow: https://github.com/pytorch/benchmark/actions/runs/2525394329
Empty result, closed.
Repository: pytorch/benchmark
Issue: V2 Performance Signal Detected by TorchBench CI on '1.13.0.dev20220620+cu113'
Root cause: External Dependency Breakage


TorchBench CI has detected a performance signal.

Base PyTorch version: 1.13.0.dev20220619+cu113

Base PyTorch commit: 0545c85f744cadc6f06616f15748052cd7cebe20

Affected PyTorch version: 1.13.0.dev20220620+cu113

Affected PyTorch commit: 332e43ed1a353a8b0a1d8e0167daaaed1e8b7a34

Affected Tests:
- test_eval[mnasnet1_0-cpu-jit]: +12.80260%
- test_eval[resnet18-cpu-jit]: +27.23483%
- test_train[timm_regnet-cpu-eager]: -13.28174%


cc @xuzhao9


Workflow: https://github.com/pytorch/benchmark/actions/runs/2530521817
Empty result, closed.
Repository: pytorch/benchmark
Issue: Performance Signal Detected by TorchBench CI on '1.13.0.dev20220620+cu113'
Root cause: Algorithmic Error


TorchBench CI has detected a performance signal.

Base PyTorch version: 1.13.0.dev20220619+cu113

Base PyTorch commit: 0545c85f744cadc6f06616f15748052cd7cebe20

Affected PyTorch version: 1.13.0.dev20220620+cu113

Affected PyTorch commit: 332e43ed1a353a8b0a1d8e0167daaaed1e8b7a34

Affected Tests:
- test_eval[yolov3-cpu-eager]: -7.27487%


cc @xuzhao9


Workflow: https://github.com/pytorch/benchmark/actions/runs/2531642263
Empty result, closed.
Repository: pytorch/benchmark
Issue: V2 Performance Signal Detected by TorchBench CI on '1.13.0.dev20220620+cu113'
Root cause: External Dependency Breakage


TorchBench CI has detected a performance signal.

Base PyTorch version: 1.13.0.dev20220619+cu113

Base PyTorch commit: 0545c85f744cadc6f06616f15748052cd7cebe20

Affected PyTorch version: 1.13.0.dev20220620+cu113

Affected PyTorch commit: 332e43ed1a353a8b0a1d8e0167daaaed1e8b7a34

Affected Tests:
- test_eval[mnasnet1_0-cpu-jit]: +51.41624%
- test_eval[shufflenet_v2_x1_0-cpu-eager]: -9.79499%
- test_train[timm_regnet-cpu-eager]: -11.17381%


cc @xuzhao9


Workflow: https://github.com/pytorch/benchmark/actions/runs/2537086178
Empty result, closed.
Repository: pytorch/benchmark
Issue: Performance Signal Detected by TorchBench CI on '1.13.0.dev20220620+cu113'
Root cause: Algorithmic Error


TorchBench CI has detected a performance signal.

Base PyTorch version: 1.13.0.dev20220619+cu113

Base PyTorch commit: 0545c85f744cadc6f06616f15748052cd7cebe20

Affected PyTorch version: 1.13.0.dev20220620+cu113

Affected PyTorch commit: 332e43ed1a353a8b0a1d8e0167daaaed1e8b7a34

Affected Tests:
- test_eval[yolov3-cpu-eager]: -7.98541%


cc @xuzhao9


Workflow: https://github.com/pytorch/benchmark/actions/runs/2539084822
Empty result, closed.
Repository: pytorch/benchmark
Issue: V2 Performance Signal Detected by TorchBench CI on '1.13.0.dev20220622+cu113'
Root cause: Others


TorchBench CI has detected a performance signal.

Base PyTorch version: 1.13.0.dev20220620+cu113

Base PyTorch commit: 332e43ed1a353a8b0a1d8e0167daaaed1e8b7a34

Affected PyTorch version: 1.13.0.dev20220622+cu113

Affected PyTorch commit: bd7cd7c3569bb708207a80c704355af2ca42b834

Affected Tests:
- test_eval[demucs-cpu-jit]: -7.84547%
- test_eval[mnasnet1_0-cpu-jit]: -34.32361%
- test_eval[mobilenet_v2_quantized_qat-cpu-eager]: -13.11520%
- test_eval[pytorch_stargan-cpu-jit]: -7.45173%
- test_eval[pytorch_stargan-cpu-eager]: -7.87160%
- test_eval[resnet50_quantized_qat-cpu-eager]: -16.76104%
- test_eval[shufflenet_v2_x1_0-cpu-eager]: +11.70387%
- test_train[timm_regnet-cpu-eager]: +14.87031%


cc @xuzhao9


Workflow: https://github.com/pytorch/benchmark/actions/runs/2543942235

Commit: 1cf3b24d42d
```
  "result": [
    {
      "commit1": "4749e86dd06",
      "commit1_time": "2022-06-21 00:04:16 +0000",
      "commit1_digest": {
        "test_eval[mobilenet_v2_quantized_qat-cpu-eager]": 0.009620139688754884,
        "test_eval[resnet50_quantized_qat-cpu-eager]": 0.010015229368582368
      },
      "commit2": "1cf3b24d42d",
      "commit2_time": "2022-06-21 00:04:17 +0000",
      "commit2_digest": {
        "test_eval[mobilenet_v2_quantized_qat-cpu-eager]": 0.00841696087495777,
        "test_eval[resnet50_quantized_qat-cpu-eager]": 0.008451340314096365
      }
    }
  ]
```

Matches https://github.com/pytorch/benchmark/issues/991, so probably this PR speeds up
Repository: pytorch/benchmark
Issue: unify the approach to train() and eval() implementation
Root cause: Architectural Constraint

some models implement by preparing data, .cuda() etc. in __init__ and do the bare minimum 'inner loop' in train()/eval() - this plays nicely with the benchmark setup.

Other models may use vanilla 'training_loop' functions from original model code, and call this from train() or eval(), which means  we could be benchmarking more overhead than we want. 

Audit the existing models and identify which ones if any are problematic, address them.

We have audited all the models to use the bare minimum train/eval approach.
Repository: pytorch/benchmark
Issue: V2 Performance Signal Detected by TorchBench CI on '1.13.0.dev20220625+cu113'
Root cause: Algorithmic Error


TorchBench CI has detected a performance signal.

Base PyTorch version: 1.13.0.dev20220623+cu113

Base PyTorch commit: 9f29d09b3bfbb6c4b64605703f52d7e2fe1fea7f

Affected PyTorch version: 1.13.0.dev20220625+cu113

Affected PyTorch commit: 80b50dfa3ab16de3e90dab8eeed003a98a0da1fe

Affected Tests:
- test_eval[demucs-cpu-jit]: +9.98261%
- test_eval[mnasnet1_0-cpu-jit]: +17.44315%
- test_train[pytorch_stargan-cpu-jit]: +7.69741%
- test_eval[pytorch_stargan-cpu-eager]: +7.40122%


cc @xuzhao9


Workflow: https://github.com/pytorch/benchmark/actions/runs/2561401825
Empty result, closed.
Repository: pytorch/benchmark
Issue: Performance Signal Detected by TorchBench CI on '1.13.0.dev20220625+cu113'
Root cause: Algorithmic Error


TorchBench CI has detected a performance signal.

Base PyTorch version: 1.13.0.dev20220620+cu113

Base PyTorch commit: 332e43ed1a353a8b0a1d8e0167daaaed1e8b7a34

Affected PyTorch version: 1.13.0.dev20220625+cu113

Affected PyTorch commit: 80b50dfa3ab16de3e90dab8eeed003a98a0da1fe

Affected Tests:
- test_eval[resnet50_quantized_qat-cpu-eager]: -10.09852%
- test_train[speech_transformer-cuda-eager]: +13.97036%


cc @xuzhao9


Workflow: https://github.com/pytorch/benchmark/actions/runs/2562026978
Commit: 1cf3b24d42d

Speedup recorded, closed.

```
  "result": [
    {
      "commit1": "4749e86dd06",
      "commit1_time": "2022-06-21 00:04:16 +0000",
      "commit1_digest": {
        "test_eval[resnet50_quantized_qat-cpu-eager]": 0.010097157360628398
      },
      "commit2": "1cf3b24d42d",
      "commit2_time": "2022-06-21 00:04:17 +0000",
      "commit2_digest": {
        "test_eval[resnet50_quantized_qat-cpu-eager]": 0.008327369296438052
      }
    }
  ]
```
Repository: pytorch/benchmark
Issue: V2 Performance Signal Detected by TorchBench CI on '1.13.0.dev20220626+cu113'
Root cause: External Dependency Breakage


TorchBench CI has detected a performance signal.

Base PyTorch version: 1.13.0.dev20220623+cu113

Base PyTorch commit: 9f29d09b3bfbb6c4b64605703f52d7e2fe1fea7f

Affected PyTorch version: 1.13.0.dev20220626+cu113

Affected PyTorch commit: 80b50dfa3ab16de3e90dab8eeed003a98a0da1fe

Affected Tests:
- test_eval[demucs-cpu-jit]: +12.17925%
- test_eval[demucs-cpu-eager]: +7.58308%
- test_eval[pytorch_stargan-cpu-eager]: +12.47289%
- test_train[timm_regnet-cpu-eager]: -13.09919%
- test_eval[timm_vovnet-cpu-jit]: +8.73963%


cc @xuzhao9


Workflow: https://github.com/pytorch/benchmark/actions/runs/2671914391

Empty result, closed.
Repository: pytorch/benchmark
Issue: V2 Performance Signal Detected by TorchBench CI on '1.13.0.dev20220628+cu113'
Root cause: Algorithmic Error


TorchBench CI has detected a performance signal.

Base PyTorch version: 1.13.0.dev20220626+cu113

Base PyTorch commit: 80b50dfa3ab16de3e90dab8eeed003a98a0da1fe

Affected PyTorch version: 1.13.0.dev20220628+cu113

Affected PyTorch commit: 8a45ef23f564cc092fa0805ea6c0f8f73eed209c

Affected Tests:
- test_train[LearningToPaint-cpu-eager]: -7.21279%
- test_eval[pytorch_stargan-cpu-jit]: +7.47611%
- test_eval[resnet18-cpu-jit]: +26.73436%
- test_eval[resnet50_quantized_qat-cpu-jit]: +7.14244%
- test_eval[shufflenet_v2_x1_0-cpu-eager]: -14.58747%
- test_train[timm_regnet-cpu-eager]: +18.18247%


cc @xuzhao9


Workflow: https://github.com/pytorch/benchmark/actions/runs/2678416375
Empty result, closed.
Repository: pytorch/benchmark
Issue: Support CUDA version comparisons in the benchmark workflow
Root cause: Unimplemented Feature Gap

We should support different CUDA versions in https://github.com/pytorch/benchmark/blob/main/.github/scripts/run-config.py

The config (https://github.com/pytorch/benchmark/blob/main/configs/detectron2_speedup/fx2trt-speedup-fp32.yaml) should support another dimension: `cuda_version`
Repository: qualifire-dev/rogue
Issue: [Bug] - Rogue TUI - Cannot insert `/` in Agent URL and Rogue Server URL
Root cause: Validation Gap

**Describe the bug**
The user cannot enter `/` in the Agent URL and the Rogue Server URL

**To Reproduce**
Steps to reproduce the behavior:
1. Open `rogue-tui`
2. Go to '/eval'
3. Try to manually enter `/` in the `Agent URL` field
4. See error

Steps to reproduce the behavior:
1. Open `rogue-tui`
2. Go to '/settings'
3. Try to manually enter `/` in the `Rogue Server URL` field
4. See error

**Expected behavior**
The `/` should be inserted into the text.

**Screenshots**

<img width="1316" height="502" alt="Image" src="https://github.com/user-attachments/assets/0ce081dc-cb2c-4333-89e0-614d6bb0b37b" />

<img width="1459" height="295" alt="Image" src="https://github.com/user-attachments/assets/3194984c-e11b-46bc-97de-91fc0e8a3d10" />



Fixed with #106
Repository: qualifire-dev/rogue
Issue: [Feature] - Add agent auth support in rogue-tui
Root cause: Unimplemented Feature Gap

**Describe the solution you'd like**
Add agent auth support to rogue-rui.
We currently support these authentication mehods: https://github.com/qualifire-dev/rogue/blob/main/sdks/python/rogue_sdk/types.py#L22
Those should be also implemented in the tui.

Note: we only need to fetch the auth data from the user and pass it to the rogue server. the server will handle the rest.


Hi, we already prepared a minimal working prototype aligned with types.py (no_auth, api_key, bearer_token, basic).
The TUI wizard collects the agent credentials and outputs a valid agent_config JSON fragment.

Implementation is ready to open as a PR (tested locally).

Before that, could you please confirm:

Which endpoint should be used for auth test (/whoami or /ping)?

Should BASIC auth be sent base64(user:pass) or plain?

Is local config persistence acceptable, or do you prefer in-memory only?

If you confirme it, we can open a clean PR (approx. 3 small Python modules + README).

Hi @Freeky7819 I think this issue refers to the Auth options of the protocols 

Meaning that the evaluator agent would be able to talk to other agents that needs some sort of Auth as part of the protocol https://modelcontextprotocol.io/specification/draft/basic/authorization for MCP

And https://a2aprotocol.ai/docs/guide/a2a-samples-hello-world#authenticated-endpoints for a2a

Prototype repo ready:
👉 [github.com/Freeky7819/rogue-auth-bridge](https://github.com/Freeky7819/rogue-auth-bridge)

It implements MCP + A2A protocol authentication headers for evaluator agents,
tested locally with bearer tokens and signed passports.

Hi @Freeky7819 we're looking for active contribution to the repo, please refer to the  [CONTRIBUTING.md](https://github.com/qualifire-dev/rogue/blob/main/CONTRIBUTING.md) for more details on how to contribute code
Repository: qualifire-dev/rogue
Issue: [Improvement] - Ping the agent on start to fail fast
Root cause: Architectural Constraint

**Describe the solution you'd like**
Currently, in the [rogue-cli](https://github.com/qualifire-dev/rogue/blob/main/rogue/run_cli.py), we check if we can communicate with the agent before starting.
We should move this logic to the rogue server to reduce code duplication.



We noticed that the recent MCP protocol support (#109) was merged into main.
Our agent-auth TUI draft (#112), already includes optional protocol and transport fields (default a2a), so it should remain compatible with the new MCP setup.
Once the server-side connectivity check lands (#113), we can verify that the same agent_config JSON works seamlessly across both transports.
Repository: qualifire-dev/rogue
Issue: [Improvement] - TUI code quality - Use consts for currentField
GitHub labels: good first issue

**Describe the solution you'd like**
The `EvaluationState.currentField` is an int. Currently, we use magic numbers in our code, instead of a const.
This is much harder to maintain, as these values spread across various places in the code.

We should create a const for easier maintainability.

Example code (current):

```go
case "backspace":
		// Handle backspace for text fields
		if m.evalState.currentField <= 1 && m.evalState.cursorPos > 0 {
			switch m.evalState.currentField {
			case 0: // AgentURL
				...
			case 1: // JudgeModel
				...
			case 2: // ParallelRuns (special handling for numbers)
				...
			}
			return m, nil
		}
```

Example code after refactor:

```go
case "backspace":
		// Handle backspace for text fields
		if m.evalState.currentField <= 1 && m.evalState.cursorPos > 0 {
			switch m.evalState.currentField {
			case AgentURLField: // AgentURL
				...
			case JudgeModelField: // JudgeModel
				...
			case ParallelRunsField: // ParallelRuns (special handling for numbers)
				...
			}
			return m, nil
		}
```

Hi @yuval-qf , tkaing this up! Excited to start contributing to this repo!

Hi @riturajFi have you started? I''ll pick this issue up if not

Yes @drorIvry will raise a PR latestby tomorrow EOD

Hi @yuval-qf , sorry for having missing this one out
Repository: qualifire-dev/rogue
Issue: [Bug] - Right border of viewport not fully visible in help screen

**Describe the bug**
The right border of the viewport in the help screen isn't showing up properly. It looks like the `viewportWidth` isn't being calculated correctly, which causes the border to get clipped. Adjusting the dimensions (`m.width` or `viewportWidth`) either messes up the text alignment or breaks the entire layout


**Expected behavior**
The right border of the viewport should be fully visible and aligned with the rest of the layout, regardless of the terminal width

**Screenshots**
<img width="1749" height="1061" alt="Image" src="https://github.com/user-attachments/assets/955616ac-6e74-44d7-8a09-caa4c0f7927f" />

**Additional context**
- The issue may be related to viewport width calculation, padding/margin applied by **lipgloss**, or clipping in combination with **glamour** markdown rendering
- The problem persists regardless of the terminal window size
Repository: qualifire-dev/rogue
Issue: [Bug] - Input handler logic error prevents character input in AgentURL

**Describe the bug**
In the TUI's "New Evaluation" form, the `AgentURL` input field correctly accepts character input but fails to process the backspace key, we can add to the URL but cannot delete characters

in `eval_form_controller.go`, the condition change breaks backspace for field 0 (AgentURL):
```go
 if m.evalState.currentField <= 1 && m.evalState.cursorPos > 0 
```

**Additional context**
This is likely a regression introduced by the logic changes for MCP support
- introduced in #115
Repository: qualifire-dev/rogue
Issue: [Improvement] - URL for Judge LLM
Root cause: Unimplemented Feature Gap

# Is your feature request related to a problem? Please describe.
It would be nice if we could change the address of our Judge LLM, for example instead of OpenAI we may use APIM / Azure OpenAI.
I wanted to use the tool, but I can't because I only have Azure OpenAI :)

# Describe the solution you'd like
Perhaps some sort of OPENAI_URL env var
Repository: qualifire-dev/rogue
Issue: [Improvement] Update a2a-sdk version to support the newer agent-card .well-known path.
Root cause: External Dependency Breakage

The current required version of A2A (a2a-sdk==0.2.10) uses a deprecated A2ACardResolver which checks the path `.well-known/agent.json` which has been updated to  `.well-known/agent-card.json`. Recommended solution would be to update to a2a-sdk>=0.3.0. 


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- [ ] <!-- {"checkboxId": "8d4f2b9c-3e1a-4f7c-a9b2-d5e8f1c4a7b9"} --> Create Plan

<details>
<summary>Examples</summary>

- [Example 1](https://github.com/coderabbitai/git-worktree-runner/issues/29#issuecomment-3589134556)
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To disable automatic issue enrichment, add the following to your `.coderabbit.yaml`:
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  auto_enrich:
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</details>

💬 Have feedback or questions? Drop into our [discord](https://discord.gg/coderabbit) or [schedule a call](https://calendly.com/parth-coderabbit/issues-feedback)!
Repository: qualifire-dev/rogue
Issue: [Feature] - Add support for MCP based communication
Root cause: Unimplemented Feature Gap

Instead of defaulting to a2a allow users to wrap their agents (that rogue will test) with MCP (with an implemented interface)

so that the agent under test is the MCP server and rogue is the MCP client.

we need at the very least `send_message(message: str) -> str` interface to handle the communication.
Repository: qualifire-dev/rogue
Issue: [Feature] - Validate model name and provider in CLI
Root cause: Validation Gap

In the CLI, validate that the given judge llm matches `lightllm`'s format of `provider/model` and make sure that the model in fact exists in `lightllm`.


first of all, define the expected format that means at least one slash (/) and the model and provider parts are non-empty strings after that check that the model exist in LightLLM and finally combine into a CLI validator

> first of all, define the expected format that means at least one slash (/) and the model and provider parts are non-empty strings after that check that the model exist in LightLLM and finally combine into a CLI validator

Exactly 😄
Thanks for the detailed implementation details!

@MohammadiHayatullah PRs are welcome!
Repository: qualifire-dev/rogue
Issue: [Feature] - Add ci/cd step for rogue import time
Root cause: Unimplemented Feature Gap

Add a CI/CD pipeline step for pull requests to measure and enforce the import time of the rogue package.

We've invested time in optimizing this (e.g., using if TYPE_CHECKING, moving imports inside functions) and need to ensure this performance doesn't degrade.

The step should fail the build if the import time exceeds 1.0 second.

Hi! 👋 Could you please assign this issue to me? I’d like to work on it. Thanks!

@MANASAB805 go for it
Repository: qualifire-dev/rogue
Issue: [Examples] - Create a typescript example for openai-agents
Root cause: Unimplemented Feature Gap

Create an example for an agent written using the [OpenAI's agents sdk](https://platform.openai.com/docs/guides/agents) wrapped in A2A.

This example should be in `examples/js/openai-agents-example/`

Make sure this example works with rogue.
Repository: qualifire-dev/rogue
Issue: [Feature] - Add support for custom ssl/tls certificates in installation
Root cause: Unimplemented Feature Gap

Implement support for loading custom SSL/TLS certificates (CA bundle) for outgoing HTTPS requests, particularly during the installation and update process.

This is necessary because users behind corporate or organizational HTTPS proxies (which often use custom root certificates) are currently unable to:

List releases from GitHub.

Download the latest rogue-tui binary.

The custom certificates should be configurable via an evironment variable or a dedicated `argparse` argument.
Repository: qualifire-dev/rogue
Issue: [Feature] - Installation script - add option to force reinstall rogue-tui
Root cause: Unimplemented Feature Gap

Currently when installing rogue (using `uvx rogue-ai`), if `rogue-tui` binary already exist, it will not redownload and reinstall it.

We should add a flag `--reinstall-tui` to force redownloading and reinstalling the `rogue-tui` binary.


Note: This should only apply to installation; the auto-upgrade mechanism already reinstalls the tui.

i'd like to take this issue.


@ignorant05 Happy to hear that! PRs are welcome 🎉
Repository: qualifire-dev/rogue
Issue: [Feature] - Add qualifire integration in the typescript SDK
Root cause: Unimplemented Feature Gap

There is a rogue <-> qualifire integration that enables storing and viewing the results in the qualifire app.
This is implemented in the python sdk, but it is not yet implemented in the typescript sdk.

The task:
Add a similar implementation of the rogue <-> qualifire integration in the typescript sdk.

i'd like to take this one since the other was stolen from me. Also, can you mention the python file path ?

Sure, its in the `rogue/server/services/qualifire_service.py` file. Thanks!
Repository: qualifire-dev/rogue
Issue: [Bug] - Glamour table rendering has the wrong background
Root cause: Algorithmic Error

**Describe the bug**
The BG color of tables in rendered MD is wrong
<img width="1423" height="450" alt="Image" src="https://github.com/user-attachments/assets/94241a2a-053b-4c6e-9e6c-9594f1804ea8" />


this is related to the file `packages/tui/internal/tui/markdown_renderer.go`


**To Reproduce**
run an evaluation and look at the results

**Expected behavior**
No BG color issues

**Desktop (please complete the following information):**
 - OS: macos
 - Version 0.1.12

**Smartphone (please complete the following information):**
 - Device: [e.g. iPhone6]
 - OS: [e.g. iOS8.1]
 - Browser [e.g. stock browser, safari]
 - Version [e.g. 22]

**Additional context**
Add any other context about the problem here.
Repository: qualifire-dev/rogue
Issue: [Feature] - Export report in various formats
Root cause: Unimplemented Feature Gap

**Describe the solution you'd like**
Support exporting the output report from a set of supported formats based on a user's choice:
- json
- yaml
- html


## Suggested implementation:

1. Support these export formats
2. Add support for the `format` argument in the `/llm/summary` server endpoint. This param should be optional.
3. Add an `exported_format: str | None` to the `ServerSummaryGenerationResponse` model. (feel free to find a better name)
4. Add support for reading and saving the `exported_format` in the various client-side (Gradio, cli, tui)
Repository: qualifire-dev/rogue
Issue: [Feature] - Add more agent examples to rogue
Root cause: Unimplemented Feature Gap

## This is an ongoing issue.

**Describe the solution you'd like**
Currently, we have only a few examples, all of them for a t-shirt store agent under different agent SDKs (adk, langchain).
We should add more examples for other agent use cases, ideally using different agent SDKs (like Pydantic AI).

Each example we add should be executable using the `--example` flag in `__main__.py`