Turn defects, compatibility failures, and integration breakage into a reproducible repair path

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Summary In a long-running Codex conversation that uses other Codex agents/subagents to send updates back to the main thread, receiving a new inter-agent message can cause the main Codex to respond to a much older user message instead of the newly received agent update/current task state. The old user message had already been handled earlier in the conversation. When this happens, the new response is visibly…”

“Setup: GLM-5.2-FP8, prefill instance DP=8 x TP1 on one 8xH200 node, `--enable-expert-parallel`, `--all2all-backend deepep_low_latency`, `--moe-backend deep_gemm`, MTP (`--speculative-config {"method":"mtp","num_speculative_tokens":3}`), default compilation and CUDA-graph settings, `6f91edf9`. The first `execute_dummy_batch()` a rank ever runs takes ~10 s. Observed with py-spy on the `EngineCore` main thread…”

“### Describe the bug `CSVDocumentCleaner` converts nonempty strings such as `NA`, `NULL`, `N/A`, `NaN`, and `None` into missing values while reading CSV content. This can delete entire rows/columns or silently replace cells with empty strings. It also happens with both cleaning options disabled. For example, `NA` can be a region/category code that should survive indexing into a RAG knowledge base. ### Reproduce…”

“### What happened? `validate_metadata()` accepts any Python `float`, including `inf` and `nan`. These values pass client-side validation, but they are not JSON-serializable, so they are silently dropped during persistence/serialization. Consequences: 1. **Silent metadata loss** — adding `{"score": float("inf"), "source": "a"}` persists `source` but silently drops `score`; adding `{"score": float("inf")}` as the…”

“### Your current environment The output of python collect_env.py ```text Your output of `python collect_env.py` here ``` docker pull vllm/vllm-openai:qwen38-flash-next-x86_64-cu129 pip list | grep vllm vllm 0.1.dev20073+g8e685d198.cu129 GPU：4*5090 ### 🐛 Describe the bug Follow the document https://recipes.vllm.ai/Qwen/Qwen3.8-Flash-Next?hardware=rtx_pro_6000_4x # shell ``` VLLM_PLE_CPU_OFFLOAD=1 vllm serve…”

“### Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangGraph rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangGraph (or the specific integration package). -…”

“### Operating System Windows 11 (reproduced headlessly against `main`; the formatter is platform-independent) ### Installation Method From source (`npm run`) ### Agent Canvas Version main @ 82203bb ### Bug Description `formatCompactTokenCount` (`src/utils/format-token-count.ts`) picks the display unit from the raw value, but rounds to one decimal *after* that choice. A value that rounds up to 1000 inside the `k`…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Bug Description `CodeActAgent.__init__` crashes when `code_act_system_prompt` is passed as a `PromptTemplate`/`BasePromptTemplate` and `system_prompt` is left at its default of `None`. In the `elif isinstance(code_act_system_prompt, BasePromptTemplate)` branch, the local `code_act_system_str` is assigned only inside the nested `if system_prompt:` block (lines 107-109), but it is read unconditionally on line…”

“**Describe the bug** `JsonSchemaValidator.run([])` raises a bare `IndexError` while trying to read `messages[-1]`. The component accepts a list of messages and documents validation errors, but it does not validate that the list contains a message before indexing it. **Error message** ```text IndexError: list index out of range ``` **Expected behavior** An empty message list should raise a descriptive…”

“**Describe the bug** `JsonSchemaValidator` rejects an empty JSON Schema (`{}`). Empty schemas are valid under the JSON Schema specification and match every JSON value. There are two affected paths: - `JsonSchemaValidator(json_schema={}).run(...)` raises `ValueError`. - Passing `json_schema={}` to `run()` does not override a stricter schema from `__init__`. The `or` fallback silently uses the init schema instead.…”

“### Bug Description The tree-select query prompt enumerates choices as 1 to N and asks the model to reply `ANSWER: `. Both consumers of that answer only check the upper bound before indexing with `number - 1`: - `TreeSelectLeafRetriever._query_level` and `._select_nodes` (indices/tree/select_leaf_retriever.py): `if number > len(cur_node_list)` guards over-range answers, but nothing guards 0. -…”

“**Operating System:** Linux **Installation Method:** From source (`npm run dev` / `npm run dev:minimal`) **Agent Canvas Version:** main @ 82203bb (Sep 16, 2026) **Bug Description** `compareAgentServerVersions` in `src/api/agent-server-compatibility.ts` compares prerelease tags with `localeCompare`, which reads multi-digit numeric identifiers character by character: `"alpha.10"` sorts before `"alpha.2"` because…”

“### Bug Description `SimplePropertyGraphStore.get_rel_map` walks the graph depth by depth and tracks visited triplets in `seen_triplets`, but the seen-set starts empty and is only updated with the *next* depth's triplets: ```python graph_triplets = self.get_triplets(ids=[gn.id for gn in graph_nodes]) seen_triplets = set() while len(graph_triplets) > 0 and cur_depth B pair, depth=2 returns each triplet twice (see…”

“### Bug Description Both selector paths in `llama_index.core.selectors` ask the model to answer with 1-based choice numbers (`_build_choices_text` enumerates choices as `(1)`, `(2)`, ...), then subtract 1 from the model's answer without validating it: - `_structured_output_to_selector_result` (llm_selectors.py): `SingleSelection(index=answer.choice - 1, ...)` - `_pydantic_output_to_selector_result`…”

“### Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangGraph rather than my code. - [x] The bug is present on the current `main` branch. - [x] This is not related to `langchain-community`. - [x] The example…”

“### Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangGraph rather than my code. - [x] The bug is present on the current `main` branch. - [x] This is not related to `langchain-community`. - [x] The example…”

“### What happened Ollama's GPU discovery returned **no devices** at server startup, so every model fell back to CPU for the entire lifetime of that server process. A plain restart (same version, same env) detected the iGPU immediately and everything ran on GPU. The laptop had gone through several Modern Standby (S0 low-power idle) suspend/resume cycles shortly before the failing start, so I suspect Vulkan device…”

“### System Info - transformers 5.17.0.dev0 (main 41f519e741) - accelerate 1.14.0 - torch 2.13.0+cu130 - python 3.13.13 - 2x H100 80GB ### Who can help? @SunMarc ### Information - [x] My own modified scripts ### Tasks - [x] My own task or dataset (give details below) ### Reproduction Under FSDP2 + context parallelism, `Trainer.predict` returns predictions with `cp_size` times too many rows, and the unlabeled path…”

“### System Info - transformers 5.17.0.dev0 (main 41f519e741) - accelerate 1.14.0 - torch 2.13.0+cu130 - python 3.13.13 - 1x H100 80GB ### Who can help? @SunMarc ### Information - [x] My own modified scripts ### Tasks - [x] My own task or dataset (give details below) ### Reproduction Calling `evaluate` or `predict` on a Trainer that has not trained raises under FSDP2. No context parallelism involved, plain FSDP2…”

“### Browser Use Version d8110c5ff87ccba887aaa726cdb780f2f84bef8d ### Bug Description, Steps to Reproduce, Screenshots CDP defines three shadow root types — `user-agent`, `open`, `closed` — but the code tests only for `closed` and treats everything else as open. Chrome's internal shadow roots for native form controls are therefore reported to the agent as author-written open shadow DOM. Four call sites share the…”

“## Summary On an Intel Lunar Lake iGPU with the Vulkan backend, `llama-server` can end up in a state where it never processes another request: no output, no runner log lines, CPU idle, process parked in the DRM ioctl `drm_syncobj_array_wait_timeout`. The server meanwhile still reports the model as loaded (`ollama ps` → `100% GPU`), so callers just hang. Only a backend restart (`ollama stop `) restores service. It…”

“### System Info - `transformers` version: 5.6.2 - Platform: Linux (WSL2), Python 3.11.15 - PyTorch version (GPU?): 2.11.0+cu130 (True), CUDA 13.0 - Model: `microsoft/VibeVoice-ASR-HF` (also reproduced with an NF4-quantized copy of the same architecture) As of 2026-09-15 the divergence is still present on `main`: the processor counts placeholders with `np.ceil` (float64) while `get_audio_features` recomputes the…”

“## Summary Codex is automatically reviewing pull requests in a connected public repository even though I have not enabled automatic code review and did not explicitly request a review. This looks very similar to the previously reported and closed issue #32224, so this may be a regression or a remaining trigger path. ## Account and repository setup - ChatGPT Pro - Codex in ChatGPT Cloud - GitHub repository:…”

“# Codex tool declaration and Windows command transport failures Sanitized maintainer report. Observations below were collected on September 13, 2026; this submission does not claim a newer-build reproduction. This report focuses on the measured oversized PowerShell command passed to exec_command. Related reports: #9688 (large apply_patch input), #38985 (sandbox setup payload). The numeric-bound observation below…”

“## Customer complaint / usability regression Please restore the active conversation name in the header of ordinary Chat conversations in the desktop application. ## Observed behavior On Windows, my Work/Codex conversation visibly displays its project icon and name (for example, “F10 Finish Line Manager”) in the top header row. In the ordinary, non-Work Chat conversation shown in my comparison, the equivalent…”

“## Summary The original-detail image token estimator uses a process-global 32-entry LRU cache. Repeated sequential scans of 33 distinct images miss on every lookup, causing all 33 images to be fully decoded again just to recover their dimensions. I reproduced this using the upstream estimator/cache function bodies and the actual upstream image-preparation utility. This is a component-level reproduction, not an…”

“Title: Claude Desktop "Apps" integration: ~50s latency + malformed tool-call output on every message, regardless of model Ollama version: 0.34.0 (fresh install 2026-09-15) OS / Hardware: macOS 26.2, Apple Silicon, unified memory Models tested: gemma4:e4b, llama3.1:8b (both affected identically) Integration: Ollama Apps panel → Claude Desktop (native "third-party gateway provider" integration) Steps to reproduce:…”

“### Your current environment The output of python collect_env.py ```text vLLM Version: 0.25.1 (also reproduced on current main, commit 2026-09) Python: 3.12 Platform: Linux x86_64, NVIDIA H200, CUDA 12.x Install: pip wheel ``` ### 🐛 Describe the bug When a client request is cancelled (disconnect or timeout) while `AsyncLLM.add_request()` is in flight, the API server process permanently retains the full…”

“### Name and Version $ ./llama-cli --version version: 0.1.0-dev (build 10436, commit 6f04274cc) built with GNU 15.2.0 for Windows AMD64 ### Operating systems Windows ### Which llama.cpp modules do you know to be affected? libllama (core library) ### Command line ```shell probe.exe model.gguf embd5.f32 repeat 6 1 probe.exe model.gguf embd5.f32 tokens 6 1 ``` ### Problem description & steps to reproduce # Title CPU…”

“### Bug When generating descriptions for pictures in documents using preset parameters (`PictureDescriptionVlmEngineOptions.from_preset()` see `docling/datamodel/pipeline_options.py`, line 921 and `docling/datamodel/stage_model_specs.py` line 758) via the VLM engine system (`PictureDescriptionVlmEngineModel` in `docling/models/stages/picture_description/picture_description_vlm_engine_model.py`, line 30), the…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Bug Description `llama-index-vector-stores-qdrant` declares `requires-python = ">=3.10, =3.10, =3.10, =3.10, =3.11, =3.10, =1.16.0` → 1.19.0 declares `requires-python >=3.10` and a `Programming Language :: Python :: 3.14` classifier - `grpcio>=1.60.0, =0.13.0, =3.10, =3.10, =3.10, =0.8.0" ``` Then, to show the cap is the only thing in the way: ```console $ .venv/bin/pip install --ignore-requires-python…”

“### Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used GitHub search to look for the same `llm_input_messages=[]` / `pre_model_hook` behavior and did not find an existing report. - [x] I am sure this is a bug in LangGraph rather than my code. - [x] The bug reproduces with the latest stable `langgraph` and…”

“### Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangGraph rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangGraph (or the specific integration package). -…”

“### Component Python SDK ### Summary `AWSBedrockLLM._parse_response` returns `""` for every legacy Amazon (Titan) text response, so `generate_response()` silently yields an empty string and `Memory.add()` stores nothing. For `provider == "amazon"` and a model id that does not contain `nova`, `_generate_standard()` sends a Titan-shaped request body (`{"inputText": ..., "textGenerationConfig": {...}}`,…”

“### Initial Checks - [x] I'm using the [latest version](https://github.com/pydantic/pydantic-ai/releases/latest) of Pydantic AI - [x] I've searched for my issue in [the issue tracker](https://github.com/pydantic/pydantic-ai/issues) before opening this issue ### Description `deepseek:deepseek-flash` (DeepSeek-V4.1-Flash) returns a 400 on the first request of any run that uses a structured output_type: > Traceback…”

“### Describe the bug `make_spec_decoding_stats` guards on the **raw** draft count before subtracting invalid spec tokens, and `observe_draft` increments `num_drafts` unconditionally — so a request whose drafts were **all** invalidated still bumps the `drafts` counter, inflating the denominator of the acceptance-rate metrics. ### Code path (current main `ca67438c`) `vllm/v1/core/sched/scheduler.py:2826`: ```python…”

“### Your current environment - vLLM nightly `0.28.1rc1.dev681+ge7edf17ce` (2026-09-11, also reproduced on `dev628+g2a02f6efe`, 2026-09-10), image `vllm/vllm-openai` nightly aarch64, torch 2.13 + cu130 - 1 tray of GB200 NVL72 (4× GB200, SM100, 184 GiB each) - Model `zai-org/GLM-5.3-Flash` (FP8 checkpoint), `--kv-cache-dtype fp8 --max-model-len 16384` ### 🐛 Describe the bug GLM-5.3-Flash served with TP=1 per rank…”

“## What happened Skill output schemas lose their `enum` constraints when they are converted to Pydantic models. A field declared as `{"type": "string", "enum": ["ok", "error"]}` still accepts any string, so an invalid skill result passes validation. ## Reproduction ```python from browser_use.skills.utils import convert_json_schema_to_pydantic Model = convert_json_schema_to_pydantic( { "type": "object",…”

“**Describe the bug** With `split_unit="word"` and `split_overlap > 0`, `RecursiveDocumentSplitter` sets `split_idx_start` one character (the length of the previous chunk's trailing separator) too far for every chunk after the first, and the `_split_overlap` ranges inherit the same shift. The repro from #11710 still fails on `main` (`f1e61b5`). Cause, in `_run_one`: the position advances by `len(chunk) -…”

“### Bug Description MediaResource.hash hashes the path via str(self.path), which embeds the OS path separator. The same logical path therefore produces a different hash on Windows than on Linux/macOS: - str(Path("foo/bar/baz")) → foo/bar/baz on POSIX - str(Path("foo/bar/baz")) → foo\bar\baz on Windows Because Node.hash aggregates the resource hashes (llama-index-core/llama_index/core/schema.py:752-762), any node…”

“## Browser Use Version 0.13.10 (`origin/main` @ `843819cb`) ## Bug Description, Steps to Reproduce, Screenshots `_add_overlay_to_image` in `browser_use/agent/gif.py` accepts `display_step: bool = True`, but calling it with `display_step=False` crashes: ```text UnboundLocalError: cannot access local variable 'y_step' where it is not associated with a value ``` Root cause: `y_step` (line 358) and `padding` (line…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Operating System macOS ### Installation Method npm (`npx @openhands/agent-canvas` or `npm install -g @openhands/agent-canvas`) ### Agent Canvas Version 1.18.0 ### Bug Description Occasionally when I use /btw I get this error ``` HTTP request failed (500 Internal Server Error): {"detail":"Internal Server Error","exception":"cannot pickle 'generator' object","error_id":"f6de8cc9a19847aea2c6b90ad4b5a4df"} ```…”

“## Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find any. - [x] I am sure this is a bug in LangGraph rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangGraph (or the specific integration package). - [x]…”

“### Operating System macOS ### Installation Method npm (`npx @openhands/agent-canvas` or `npm install -g @openhands/agent-canvas`) ### Agent Canvas Version 1.18.0 ### Bug Description we're inconsistent w/ our wording: the tag says 'default' but the picker says 'active'. IMO it should be the former. ### Steps to Reproduce n/a ### Actual Behavior n/a ### Expected Behavior n/a ### Relevant Logs ```shell ``` ###…”

“## Problem The ChatGPT Chrome extension is installed from the Chrome Web Store, but it cannot connect to the desktop app. Its side panel says “Install the app to use ChatGPT in Chrome.” Clicking “open the app” launches ChatGPT but does not change the connection status. The desktop app's Computer use settings report “Browser extension not installed” for Google Chrome. On the Chrome settings detail page, both…”

“## Environment - Surface: ChatGPT web - Workflow: Codex / Work Mode with the GitHub connector - Target: a GitHub-hosted website repository - File type: attached PNG/JPEG image ## What happened The GitHub connector was available and could perform Git Data operations such as `create_blob`, `create_tree`, `create_commit`, and `update_ref`. The image was also present as a ChatGPT attachment and had been copied to a…”

“### What issue are you seeing? Codex appears to have regressed in how it handles a usage limit that is reached **during an already-running turn**. Previously, if I submitted one long task and the usage allowance was exhausted while Codex was already executing that task, the active turn could continue working and finish the task. I could not start another turn afterward, which was reasonable, but the task already…”

“### Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangGraph rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangGraph (or the specific integration package). -…”

“### Your current environment ```text Source checkout at 767d1c4 (main, 2026-09-14), CPU only, no GPU or model weights. Python 3.12.13, torch 2.13.0, transformers 5.17.0, macOS 26.5.2 arm64. vllm/collect_env.py does not run on a checkout without the compiled extension; the reproduction below only imports the tool parsers and the request protocol. ``` ### 🐛 Describe the bug `pythonic` and `llama4_pythonic` decide…”

“### Bug Description `max_iterations` and `early_stopping_method` passed to `.run()` only take effect the first time a `Context` is used. On every later run with the same `ctx`, both are silently ignored and the values from the first run still apply. `_init_context` writes them only when the store has no value yet: ```python if not await ctx.store.get("max_iterations", default=None): max_iterations =…”

“## Environment - Linux (Strato2 remote compute host) - Managed Codex unified exec; reporter version was not captured - Same-host control: `codex-cli 0.154.0` - Long command wrapped by `KB_COMPACT_KEEP_LOG=1 kb-run-compact ...` ## Intermittent reproduction 1. Start a multi-minute foreground command through `exec_command` with a short `yield_time_ms` so it returns an inner `session_id`. 2. Keep the owning turn…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Page Not a page on docs.mem0.ai — it is the docstring that `BaseEmbedderConfig` carries in the source, `mem0/configs/embeddings/base.py:59`. Filing it here because the `pr-gate` bot asked for an issue before the fix, and because a wrong docstring is read far more often than a docs page when someone is reading their own traceback. ### What's Wrong or Missing The docstring states a default that the code does…”

“### Problem or Motivation Reproducing a reported OpenHands session today requires the reporter's model key, the same model, and the same luck. There is no documented way to run a past session again without calling the provider. That makes "I cannot reproduce this" a common dead end on bug reports, and makes a failed session hard to turn into a regression test. `docs/DefenseClaw.md` establishes that third-party…”

“# [Bug]: SettingsService cache can reuse settings from a previous local backend after switching backends ## Summary `SettingsService` keeps a single module-level in-memory cache for local Agent Server settings. The cache contains both: * redacted settings used for display * encrypted settings used when starting conversations and is considered valid for five minutes based only on its timestamp. When the active…”

“**Describe the bug** `InMemoryDocumentStore.count_unique_metadata_by_filter()` raises `TypeError` when a requested metadata field contains a JSON-serializable list or dictionary. The async variant fails through the same implementation. **Error message** ```text TypeError: unhashable type: list TypeError: unhashable type: dict ``` **Expected behavior** The method should count distinct JSON-serializable metadata…”

“### What happened? [Bug]: Hi I can see docker command is wrong in documents page. Its written as -rm but should be --rm ### Versions [Bug]: Hi I can see docker command is wrong in documents page. Its written as -rm but should be --rm ### Relevant log output ```shell ```”

“## Summary On Windows, the desktop app can display the built-in browser, but the browser automation tool cannot enumerate or control it. This blocks an authorized website deployment workflow. ## Reproduction 1. Open a page in the built-in browser. 2. Run `await cua.getState();` through `mcp__cua_repl.js`. ## Actual result After approximately 21 seconds, the tool returns: ```json…”

“### Environment | Item | Value | |------|-------| | OS | Ubuntu 24.04.5 LTS (kernel 7.0.0-31-generic) | | GPU | **NVIDIA GeForce RTX 5090 Laptop GPU** (sm_120 / compute capability 12.0, 24 GB) | | Driver | 595.99.02 | | CUDA | 13.0.88 (V13.0.88) | | Compiler | GCC 13.3.0 | | Build | CMake + Ninja, `-DGGML_CUDA=ON -DCMAKE_CUDA_ARCHITECTURES=120 -DGGML_CUDA_FORCE_CUBLAS=OFF -DGGML_CUDA_MXFP4=OFF…”

“### What happened? Codex Desktop crashed natively on macOS while attempting to recover from an already-broken UI state. The process had been running for several days. It was already exhibiting the packaged-resource failure documented in #37551 / electron/electron#52804, where some ASAR-backed resources could no longer be loaded because Electron retained a cached path to a temporary extracted file that had since…”

“## Bug description The official curated `data-analytics` plugin requires fetching history and showing a trend for every metric/KPI answer, even when the user explicitly asks only for the latest value or a period-over-period change. ## Current source - Plugin: `data-analytics` `1.0.8` - Remote plugin ID: `Plugin_fc9843a6fb34819195d6c7802398a8a7` - File: `skills/index/SKILL.md`, lines 73-79 The current rule says: >…”

“## Bug report: Chrome BrowserSkill 0.2.1 rejects Codex API-key authentication ### Summary The Codex Chrome/browser integration stopped working after a recent update. The browser extension is discovered, but any attempt to enumerate or read Chrome tabs fails with: `unsupported Codex auth method: apikey` This worked normally last week on the same Windows workstation and Chrome profile. ### Environment - OS: Windows…”

“### Before submitting your bug report - [x] I've tried finding an answer on the [Continue docs site](https://docs.continue.dev/) - [x] I'm not able to find an [open issue](https://github.com/continuedev/continue/issues?q=is%3Aopen+is%3Aissue) that reports the same bug - [x] I've seen the [troubleshooting guide](https://docs.continue.dev/troubleshooting) on the Continue Docs ### Relevant environment info…”

“### Name and Version `version: 0.4.0-dev`, master `5f436dddb` (2026-09-13). Also tested `9113cc188`, `451b89bae`, `16378d93f`. ### Operating systems Linux (Ubuntu 24.04 container) ### GGML backends HIP/ROCm — `-DGGML_HIP=ON -DAMDGPU_TARGETS=gfx1201`, HIP 7.15 / ROCm 10.0 ### Hardware **Radeon AI PRO R9700 (Navi 48, gfx1201, RDNA4), single GPU, 32 GiB** ### Models Qwen3.8-27B-UD-Q4_K_XL — arch `qwen35`, 65 layers,…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Component Plugin ### Description ### Summary Canceling a DSH turn while automatic memory search is pending can mark returned memories as seen without delivering them to the model. Later automatic recall skips those memories in the same session, so the agent may answer without relevant stored information(if agent does not use search_memory). ### Steps to Reproduce 1. On the commit listed below, insert the…”

“**Summary** The traceback filtering added in #4054 (`bfd271e00`, "Remove internal frames from stack traces", 2025-03-27) has been a silent no-op since #5252 (`8c4e698c5`, "solidify public/private differentiations", 2025-07-02). `EXCLUDED_FRAME_FNAMES` in `libs/langgraph/langgraph/pregel/_runner.py` still lists the pre-rename module paths: ```python EXCLUDED_FRAME_FNAMES = ( "langgraph/pregel/retry.py", # now…”

“### Name and Version ``` version: 0.4.0-dev (build 10809, commit 5266f24da7) built with GNU 16.2.1 for Linux x86_64 ``` Also reproduced on master at `b6b003d2c` ### Operating systems Linux ### GGML backends CPU, CUDA ### Hardware AMD Ryzen 9900X ### Models Only vocab: - [google/mt5-small](https://huggingface.co/google/mt5-small) regression test target -…”

“### Name and Version llama-server version: 0.4.0-dev (build 1, commit 4a89937) built with IntelLLVM 2026.1.1 for Linux x86_64 ### Operating systems Linux ### GGML backends SYCL ### Hardware Ryzen 5950X + Intel Arc A770 + AMD 6900XT ### Models Qwen3.8-27b from various sources and quants ### Problem description & steps to reproduce Enabling ngram-mod spec draft causes the SYCL backend to request an outsize…”

“I recorded a browser-use run at the HTTP boundary to the model provider, killed the provider, and replayed it. Posting the result because the interesting part is not that it worked — it's the exact thing that failed to reproduce, which turns out to be a browser-use implementation detail worth knowing. Setup A static page on 127.0.0.1:8300 so the web itself is not a variable, an ordinary agent, and a deterministic…”

“### Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangGraph rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangGraph (or the specific integration package). -…”

“# kimi-k3:cloud crashes (HTTP 500) on image content in tool-role messages — regression from kimi-k2.6 + glm-5.3-flash both work ## Bug Summary `kimi-k3:cloud` on ollama-cloud's OpenAI-compatible endpoint (`/v1/chat/completions`) returns **HTTP 500 Internal Server Error** when a message with `role: "tool"` contains an `image_url` content part. The same payload works correctly on `kimi-k2.6:cloud` and…”

“### What issue are you seeing? In `sdk/typescript/src/thread.ts`, `runStreamedInternal` parses each subprocess line and casts it unchecked (lines 99-109): ```ts let parsed: ThreadEvent; try { parsed = JSON.parse(item) as ThreadEvent; } catch (error) { throw new Error(`Failed to parse item: ${item}`, { cause: error }); } if (parsed.type === "thread.started") { this._id = parsed.thread_id; } else if (parsed.type…”

“# Codex app bug report (draft for OpenAI) **Summary:** In the Codex desktop app, permission prompts can be answered "declined" by the app itself, and the result is then treated as the user's choice. Two cases: (1) a website prompt in the built-in browser was auto-declined and saved permanently for that conversation, with no way to see or undo it in Settings; (2) in Full access mode, Messages read and send…”

“## Problem Canvas rejects the canonical PR reviewer automation because its bundle reuses `plugins/qa-changes/scripts/prompt.py`. The extensions bundle schema already permits package files under `plugins/`, but Canvas's setup validator only permits `skills/` and `automations/`. The catalog launcher consequently falls back to an assisted conversation instead of the available setup form. ## Reproduction Use the…”

“## Problem The local Canvas static server caches sirv's file inventory at startup. If a rebuild replaces hashed assets, an existing browser can request a removed asset and trigger an unhandled ENOENT ReadStream error, terminating the server. This occurred during a fresh-install software-factory walkthrough. ## Reproduction 1. Start the static server against a build directory containing a JavaScript asset. 2.…”

“### Operating System macOS ### Installation Method From source (`npm run dev` / `npm run dev:minimal`) ### Agent Canvas Version 1.18.0 (source checkout; rendering code identical to `main` @ 60877198a) · agent-server / SDK 1.46.0 · claude-agent-acp 0.63.0 (Canvas default command) ### Bug Description ACP tool-call cards never render the ACP `content` field. `getACPToolCallContent`…”

“### Operating System Linux ### Installation Method Docker (`ghcr.io/openhands/agent-canvas`) ### Agent Canvas Version 1.18.0 (`ghcr.io/openhands/agent-canvas:1.18.0`, build commit `9120ff6cbbe23640f0e475661e5a9c9729cdbf1f`). Also reproduced from source on `main` at `28464621d879e3e9b3ceeae9d70a71d96da6212d`. ### Bug Description If you attach an image in a conversation and send it with the text box empty, the…”

“### System Info transformers `main` (415e6d2), torch 2.14, accelerate 1.15. Observed on 8×H100 80 GB loading a large MoE with `device_map="auto"`; reproducible on CPU with the unit test in the linked PR. ### Who can help? @SunMarc @Cyrilvallez (device_map / loading) ### Reproduction Any model that declares `_no_placement_params` — in-tree, `qwen4_exp` (`ple.ple_embedding.ngram_embedding.weight`, ~95 GiB).…”

“Orchestrator: VS Code × Codex × Jira, in one free, open-source Mac app. Orchestrator connects a Codex task to the repository, agent conversation and resulting diff in the same workspace. The aim is to make it easier to follow what happened between “please implement this” and “done”. For people using Codex on a Mac, the workflow is: Organise work on a Kanban board and start from a specific task. Browse repository…”

“### Name and Version 790cf51aa ### Operating systems Linux ### Which llama.cpp modules do you know to be affected? Test code ### Command line ```shell build-ci-debug/bin/test-quant-type-selection ``` ### Problem description & steps to reproduce ```console $ build-ci-debug/bin/test-quant-type-selection === Qwen3-0.6B === PASS Qwen3-0.6B: 33/33 ftype sections passed (198 tensors) === GLM-4.6V === PASS GLM-4.6V:…”

“### What is the issue? **Model:** Gemma4 31B based (though it shouldn't matter) **Steps to reproduce:** 1. Upload image with EXIF orientation tag set to 3 (rotate 180) 2. Ask model what it sees 3. Model comments on unusual orientation Cause: - Images with EXIF orientation tag set to anything other than `0` or `1` must be flipped and/or rotated correctly, example code for deciding what operations are needed: ```…”

“**Describe the bug** The `Label pull request / add_label` job fails on every pull request opened from a fork. The run is rejected at the environment gate before any step executes, with: > Branch "main" is not allowed to deploy to github-app-auth due to environment > protection rules. The deployment was rejected or didn't satisfy other protection rules. The job fails in 1-2 seconds. `label-pr.yml` runs on…”

“### What version of Codex CLI is running? CLI version not available; source checkout based on openai/codex main at a592c38c16 ### What subscription do you have? Not applicable — source-level bug report ### Which model were you using? Not applicable ### What platform is your computer? Darwin 25.2.0 arm64 arm (macOS) ### What terminal emulator and version are you using (if applicable)? iTerm2 3.6.11; no multiplexer…”

“### Before submitting your bug report - [x] I've tried finding an answer on the [Continue docs site](https://docs.continue.dev/) - [x] I'm not able to find an [open issue](https://github.com/continuedev/continue/issues?q=is%3Aopen+is%3Aissue) that reports the same bug - [x] I've seen the [troubleshooting guide](https://docs.continue.dev/troubleshooting) on the Continue Docs ### Relevant environment info…”

“Type: Bug Environment OS: macOS 15.7.2 Device: Apple M4 Please fill in: client name / version (app or web), browser (if web) Summary In the chat view, a white area (blank panel) appears on the right side and covers part of the message text on the left. The hidden text cannot be revealed by scrolling, resizing, or dragging the view in any direction. Steps to Reproduce Open a conversation with enough content to…”

“### Name and Version version: 0.4.0-dev (build 10909, commit a2878d30d) built with GNU 11.4.0 for Linux x86_64 ### Operating systems Linux ### GGML backends Vulkan ### Hardware Device 0 [AMD Radeon RX 9070 XT], Device 1 [Tesla P40], AMD Ryzen 9 5900X Yes, Mixed GPU brands. ### Models google_gemma-4-31B-it-Q8_0.gguf ### Problem description & steps to reproduce Have the main agent call a tool with incremental…”

“### Name and Version llama-server --version version: 0.4.0-dev (build 10934, commit acecd5603) built with GNU 13.3.0 for Linux x86_64 Linux Mint 22.3 (Ubuntu 24.04) , CUDA 12.9.2 , NCCL 2.31.2 for CUDA 12.9 ### Operating systems Linux ### GGML backends CUDA ### Hardware Ryzen 9950X , 2x RTX 3090 ### Models unsloth/DeepSeek-V4-Flash-0731-GGUF UD-Q8_K_XL ### Problem description & steps to reproduce Segmentation…”

“## Summary The ChatGPT Android app unexpectedly changed its UI language from English to Bosnian without any user action. Android's system language remained English. This occurred around the same time as a prior Voice conversation becoming stuck/crashed in a persistent spinning state, so the two may be related app-state issues, though that is not confirmed. ## Environment - App: ChatGPT Android - ChatGPT app…”

“## What happened Every successful `ollama create --quantize q4_K_M` from a safetensors directory leaves a ~50 GB blob in `~/.ollama/models/blobs` that no manifest references. `ollama rm ` does not remove it (it only removes layers in the manifest). After 12 imports of a 26B model I had 948 GB in `~/.ollama/models` while `ollama list` summed to 188 GB — 69 unreferenced blobs, 830 GB. The mtime of each 50.5 GB…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Name and Version version: 0.4.0-dev (build 158, commit 311d4211b) ### Operating systems Mac ### Which llama.cpp modules do you know to be affected? llama-server ### Command line ```shell llama serve --port 8080 --models-preset corral-preset.ini --api-key 6614372 --api-key-file keys.txt（use 123 and 234) ``` ### Problem description & steps to reproduce In router mode, --api-key and --api-key-file are supposed…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Description The `cn` prompt editor does not provide the usual Windows text-editing behavior for physical Delete and End, and there is no documented keybinding configuration to make these keys behave as expected. Physical Delete is handled as backward deletion, exactly like Backspace. End is also unsupported in the inspected input path. This makes editing prompts frustrating. | Key | Expected behavior |…”

“### Operating System Linux ### Installation Method Docker (`ghcr.io/openhands/agent-canvas`) ### Agent Canvas Version 1.18.0 ### Bug Description Local conversations are grouped by workspace using browser localStorage instead of persistent server data. As a result, workspace grouping disappears on another device/browser or after clearing site data. Conversations that are still correctly bound to a workspace on the…”

“### Operating System macOS ### Installation Method npm (`npx @openhands/agent-canvas` or `npm install -g @openhands/agent-canvas`) ### Agent Canvas Version 1.18.0 ### Bug Description A saved LLM profile backed by an encrypted provider connection works correctly when used by a top-level conversation, but fails with HTTP 401 when the same profile is referenced by a file-based subagent. The subagent correctly…”

“### Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangGraph rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangGraph (or the specific integration package). -…”

“### Summary `PGVector` (mem0-ts, open-source mode) keeps a single `pg.Client` and never attaches an `error` listener. When PostgreSQL terminates that connection server-side — e.g. a container restart or `pg_terminate_backend`, both of which send `FATAL 57P01 terminating connection due to administrator command` — the idle client emits an `'error'` event with no listener. Node then throws it as an uncaught…”

“## What happened Codex is sometimes inserting unrelated gambling/adult/spam-like Chinese text into otherwise normal research tasks. I have seen this in two places: 1. **Auto-generated conversation titles** - `完成立场测试 国产成人精` - `科研记忆原则 天空彩票网` The added suffixes are completely unrelated to the conversations. 2. **Agent work/reasoning output** - Similar unrelated gambling/adult text occasionally appears while Codex is…”

“## Summary I am seeing a conversation-state desynchronization in the ChatGPT iOS app where the visible transcript and the context used to generate the next assistant response appear to diverge. This is **regular ChatGPT inside a Project chat, not Codex Remote Control**. Two related symptoms occurred in the same conversation: 1. Newly sent messages/images were briefly visible, then disappeared from the iOS…”

“### Name and Version version: 0.4.0-dev (build 10930, commit 56381e407) built with GNU 15.2.0 for Linux x86_64 System: - 1x4090 - 3x3090 - 192GB DDR4 After pulling in master yesterday, I've noticed that I'm receiving consistent OOM crashes. This occurs when running 3 concurrent requests with context at 262k for each. I have been running this set up for quite awhile regularly building from master and can confirm…”

“## What is the issue? On a Linux hybrid-graphics laptop (Intel Raptor Lake-S iGPU + discrete NVIDIA RTX 4080 Laptop GPU, compute 8.9 — the same hardware family reported in #16667, but on Linux instead of Windows), `llama-server` (bundled with `ollama serve`) repeatedly crashes with `SIGABRT` during backend/device-loading, both when invoked as `--list-devices` and during normal model-serving startup. The crash…”

“### Operating System macOS ### Installation Method From source (`npm run dev` / `npm run dev:minimal`) ### Agent Canvas Version 1.18.0 ### Bug Description I opened a workspace whose origin is an Azure DevOps SSH remote, and the git control bar shows the repository as `v3/myorg/myproject/myrepo`. The `v3/` belongs to Azure's SSH URL, it isn't part of the repo name. The branch chip next to it also has no link on…”

“### What version of the Codex App are you using (From “About Codex” dialog)? 0.154.0 ### What subscription do you have? chatgpt - plus ### What platform is your computer? MX-Linux-23.6 ### What issue are you seeing? ## What version of Codex CLI is running? The regression occurs with: `codex-cli 0.154.0` Downgrading to: `codex-cli 0.153.4` immediately restores the previous behavior. ## Platform * MX Linux 23.6…”

“### What version of the Codex App are you using (From “About Codex” dialog)? latest ### What subscription do you have? pro 20x ### What platform is your computer? max os ### What issue are you seeing? an existing thread / task not allowing me send follow up messages. shows error as stated in headline. ### What steps can reproduce the bug? hmm not sure as the task is still ongoing but it was started on astra…”

“### Name and Version ``` $ ./llama-bench --version version: b10707 (62acc89) — also present in b10920 built with the official ubuntu-vulkan-x64 release binaries ``` ### Operating systems Linux ### GGML backends Vulkan ### Hardware AMD Radeon RX 5600 XT (Navi 10 / gfx1010, RDNA1), RADV, Mesa 26.1.6 Second GPU is a 7900 XTX (Navi 31) — unaffected by this, same binary. ### Models Qwen3.8-27B UD-Q4_K_XL (`qwen35`)…”

“### Name and Version ``` $ ./llama-bench --version version: b10707 (62acc89) and b10920 — both reproduce built with the official ubuntu-vulkan-x64 release binaries ``` ### Operating systems Linux ### GGML backends Vulkan ### Hardware AMD Radeon RX 5600 XT (Navi 10 / gfx1010, RDNA1), RADV, Mesa 26.1.6 Second GPU in the box is a 7900 XTX (Navi 31) — unaffected, same binary. ### Models Qwen3.8-27B UD-Q4_K_XL…”

“### System Info - transformers: `main` at `df04b01222` - PyTorch 2.11.0, torchvision 0.26.0, Python 3.13.15, Linux, CPU - The reproduction builds the processors from their class defaults and downloads nothing. ### Who can help? @molbap @guarin ### Reproduction I swept all 92 model families that ship both an `XImageProcessor` (torchvision) and an `XImageProcessorPil`, ran the same image through both, and compared…”

“### Component Examples ### Description `examples/misc/vllm_example.py` no longer runs on v3. Two problems: 1. `search()` and `get_all()` pass `user_id` as a top-level argument (lines 110 and 116). v3 removed this form and raises: ``` ValueError: Top-level entity parameters {'user_id'} are not supported in search(). Use filters={'user_id': '...'} instead. ``` 2. Both methods now return `{"results": [...]}`. The…”

“### Your current environment The output of python collect_env.py ```text Platform: s390x (IBM Z / LinuxONE) vLLM version: 0.28.0 Python: 3.11 OS: RHEL / UBI 9 (s390x) GPU / accel: IBM Spyre (custom accelerator, not CUDA) xgrammar: not installed — no pre-built wheel available for s390x; apache-tvm-ffi (build dependency) also has no s390x support ``` ### 🐛 Describe the bug On `s390x` (IBM Z / LinuxONE), vLLM…”

“### Your current environment The output of python collect_env.py ```text Collecting environment information... ============================== System Info ============================== OS : Ubuntu 26.04 LTS (x86_64) GCC version : (Ubuntu 15.2.0-16ubuntu1) 15.2.0 Clang version : Could not collect CMake version : version 4.2.3 Libc version : glibc-2.43 ============================== PyTorch Info…”

“### What version of Codex CLI is running? 0.153.4 ### What subscription do you have? ChatGPT Pro ### Which model were you using? gpt-6-astra, gpt-5.6-luna ### What platform is your computer? Darwin 24.6.0 arm64 (macOS 15.6.0) ### What terminal emulator and version are you using (if applicable)? iTerm2 (Build 3.6.10) / Ghostty ### Codex doctor report not available ### What issue are you seeing? In Codex TUI, when…”

“### What issue are you seeing? The remote daemon fails during SQLite state initialization on NFS. Desktop's bootstrap reports success, but the control socket is absent. codex app-server proxy then exits with ENOENT, and Desktop surfaces the result as a generic HTTP-client ECONNRESET / socket hang up. **In more detail** Codex Desktop Remote SSH successfully authenticates to the Linux host, but the connection…”

“## Problem Codex's work efficiency has been very low over the past few days. It frequently stops at making excuses and defending its behavior instead of completing the requested task. When corrected, it often continues explaining or justifying what went wrong rather than fixing the problem and finishing the work. The user has to repeatedly push it to continue. ## Expected behavior Act on corrections, fix the…”

“### Bug Every conversion fails immediately, before any document I/O happens, with: ``` pydantic_core._pydantic_core.PydanticSerializationError: Error serializing to JSON: PydanticSerializationError: Error calling function ` `: ValueError: Circular reference detected (id repeated) ``` This isn't specific to any input file, URL, or pipeline options. It reproduces with a bare default `PdfPipelineOptions()`:…”

“### What issue are you seeing? In Codex within the ChatGPT Android app, references to skills appear as the generic filename `SKILL.md` instead of the actual skill name. The references cannot be tapped to open and read the referenced skill contents. This makes different skills hard to distinguish and prevents the user from inspecting the instructions Codex is referencing. ### What steps can reproduce the bug?…”

“### Name and Version b10236 ### Operating systems Linux ### Which llama.cpp modules do you know to be affected? libllama (jinja caps), llama-server ### Problem description & steps to reproduce minja doesn't support numeric dotted attribute access (`x.0`); Jinja2 treats it as `x[0]`. A template using it makes the caps probe throw, and `caps_get` then returns **all** capabilities false rather than keeping what the…”

“### Bug Description CodeSplitter accepts chunk_lines and chunk_lines_overlap, validates them (both must be > 0), and documents them as "The number of lines to include in each chunk" and "How many lines of code each chunk overlaps with". Neither parameter is ever read by the chunking logic: _chunk_node splits purely by max_chars (or max_tokens in token mode). Two very different line settings produce byte-identical…”

“## Summary Loading a DFlash2 draft model (`--model-draft`) on the SYCL backend against dual Intel Arc Pro B70 GPUs causes a GPU driver TDR (Timeout Detection and Recovery) event — Windows force-resets the GPU driver — rather than a normal crash or clean load. The process disappears with no application-level error logged; the only trace is a `LiveKernelEvent` (Bug Check `0x141` = `VIDEO_TDR_TIMEOUT_DETECTED`) in…”

“## Summary Loading a DFlash2 draft model (`--model-draft`) against a target model with `--split-mode tensor` crashes with a `GGML_ASSERT` in `ggml-backend-meta.cpp` during graph allocation. The identical launch succeeds with `--split-mode layer`. ## Environment - Build: local checkout of #27342 at commit `1deefcca3` ("Add p_min in DFlash2"), built with CUDA backend (`build-cuda`) - Hardware: 2x NVIDIA RTX 3060…”

“llama.cpp b10909 commit a2878d30df0130dde503a7d9ba30d3d21bd71b9f Windows 11 build 26200 ROCm 10 AMD clang 23.0.0 ### Operating systems Windows ### GGML backends HIP ### Hardware AMD Ryzen 9 5900X + AMD Radeon AI PRO R9700 (gfx1201) ### Models Gemma4 31B ### Problem description & steps to reproduce I am seeing a reproducible HIP/ROCm correctness issue on Windows with an AMD Radeon AI PRO R9700 (gfx1201). Using the…”

“Sharing a community tool, not an issue: https://github.com/chenhz01/zhengming-openai-plugins converts Agent Skills SKILL.md folders into compliant Codex plugin manifests (.codex-plugin/plugin.json + skills/ layout + marketplace index), enforcing the upload hard constraints (≤1024 description, reserved names) in CI, with behavior regression tests. Feedback welcome — especially on manifest fields we may have mapped…”

“Continue's CLI implemented "invokable skills and import any skill" — the import direction. We built the publish direction: SKILL.md folders → Codex plugin bundles, with behavior regression tests (https://github.com/chenhz01/zhengming-openai-plugins, MIT). Same road, opposite lane — would you accept docs/tooling PRs linking the two, or is there an export story planned? Ref: AS-B10”

“OpenHands now manages per-conversation skills in the cloud (visible in the Sept releases). Most existing skills live as local SKILL.md folders — we open-sourced a converter that turns them into Codex plugin bundles with regression tests (https://github.com/chenhz01/zhengming-openai-plugins). Would a bridge from local SKILL.md collections into OpenHands cloud sessions fit the roadmap? Ref: AS-B08”

“### Name and Version 0.4.0-dev 41fc7584f built with Clang 24.0.0 for Linux x86_64 ### Operating systems Linux ### GGML backends SYCL ### Hardware Intel Arc Pro B70 Graphics Intel UHD Graphics 770 ### Models any model, e.g. Llama-3.2-1B-Instruct-Q4_K_M ### Problem description & steps to reproduce SYCL backend crashes with OOM error at the first decode of any model only if output tensor of the model is located on…”

“### Before submitting your bug report - [x] I've tried finding an answer on the [Continue docs site](https://docs.continue.dev/) - [x] I'm not able to find an [open issue](https://github.com/continuedev/continue/issues?q=is%3Aopen+is%3Aissue) that reports the same bug - [x] I've seen the [troubleshooting guide](https://docs.continue.dev/troubleshooting) on the Continue Docs ### Relevant environment info…”

“### Bug Relative hyperlinks are stored on `TextItem.hyperlink` as a `Path` (the field is `AnyUrl | Path`). On Windows that is a `WindowsPath`, and the serializers turn the hyperlink into text with `str(...)`, so a link written as `sub/next.html` in the source comes out as `sub\next.html`: - Markdown: `[next page](sub\next.html)` (`MarkdownDocSerializer.serialize_hyperlink` uses `f"[{text}]({hyperlink!s})"`) -…”

“## Bug description After every OpenHands update, I have to run a local post-install script (`apply_fix_all_envs-ivanov-fix1.py`) against every cached copy of `openhands/sdk/llm/message.py`. Without this patch, strict OpenAI-compatible providers routed through TokenRouter (GLM) reject serialized empty assistant messages. The affected `_list_serializer()` can emit both of the following forms: - `{"content":…”

“## Background `ggml_cuda_mmq_get_config` (ggml-cuda/mmq.cuh) routes every NVIDIA arch `>= VOLTA` to `ggml_cuda_mmq_get_config_ampere` — there is no Turing-specific table (the closest arch-specific table anywhere in the mmq config set is Blackwell). sm_75 differs from sm_80 in exactly the dimensions this table's parameters are budgeted against: - shared memory per SM: 64 KiB vs 164 KiB, - max resident warps per…”

“### Name and Version ```bash bin/llama-cli --version version: 0.4.0-dev (build 10905, commit 16378d93f) built with IntelLLVM 2026.1.1 for Linux x86_64 ``` Ubuntu `24.04.5` LTS (Noble Numbat) Linux kernel: `6.17.0-42-generic` AMD Ryzen 7 5800X 8-Core Processor System RAM: 128 GB GPU: Intel Arc Pro B70 (32GB VRAM) 2nd card present, not used (used for display only) Radeon RX 6600 ### Operating systems Linux ###…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Bug `ReadingOrderModel._merge_elements()` computes the `ProvenanceItem.charspan` before applying dehyphenation. When the left text ends with either a soft hyphen (`\u00ad`) or a hard hyphen followed by a lowercase continuation, the merged text becomes 2 characters shorter than the span calculation assumes. As a result, the provenance span can extend past `len(new_item.text)` and is therefore inconsistent with…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“## What happens Cloud models wedge after about 45 minutes of serving on 0.34.0. The same account and the same model work fine on 0.33.1. `deepseek-v4-pro:cloud` responds normally for a while (2 to 8 seconds per request). Then latency climbs steadily. 16s, 17s, 28s. Then one request hangs for 4m15s. After that every request returns 502. The server log shows the degradation curve and the 502s, but no underlying…”

“### Your current environment AMD MI308X ### 🐛 Describe the bug First, a huge thank you to the entire vLLM engineering team and community. Your work on making high-performance LLM serving accessible across NVIDIA, AMD ROCm, Intel, TPU, and CPU backends is genuinely transformative — the pace of model coverage (DeepSeek V4, V4.1-Flash, Kimi-K3, GLM-5.3, …), the unified frontends (Python + Rust), the disaggregation…”

“### Name and Version ``` root@db159f83e6c2:/app# ./llama-cli --version version: 0.4.0-dev (build 10902, commit df03399b8) built with IntelLLVM 2025.3.3 for Linux x86_64 ``` ### Operating systems Linux ### GGML backends SYCL ### Hardware B580 + Ryzen 7 5700X3D + 48GB at 3133MHz ### Models Qwen3.6-35B-A3B-UD-Q5_K_XL.gguf ### Problem description & steps to reproduce 1. `./llama-server --host 0.0.0.0 --port 8080…”

“## Summary After the latest Codex Desktop update on macOS, running a local web app from a Codex conversation causes Codex UI/renderer processes to consume very high CPU. Closing the local website immediately drops CPU usage back down. This appears to be a Codex Desktop renderer/performance regression rather than normal load from the local web app itself. ## Observed behavior While the local site was open/running,…”

“### What version of the Codex App are you using? Exact version was not captured yet. The issue began on September 9, 2026 and is still being observed on September 11, 2026. ### What subscription do you have? This is reproducible across two separate ChatGPT accounts on the same user's setup: - one Pro account used for work/company use - one personal Plus account ### What platform is your computer? macOS / Apple…”

“### Summary Codex Desktop on Windows repeatedly terminated while its automatic Git review/turn-diff processing handled an unusually large staged diff. Crashpad classified every retained crash as an Electron browser-process crash. This may share underlying symptoms with #41268 and appears related to the Git review/output-pressure reports in #35776 and #30820, but this report isolates a reproducible workload…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Name and Version n/a ### Operating systems _No response_ ### Which llama.cpp modules do you know to be affected? _No response_ ### Command line ```shell ``` ### Problem description & steps to reproduce ``` /usr/ports/misc/llama-cpp/work/llama.cpp-b10900/src/llama-graph.cpp:1929:13: error: use of undeclared identifier 'ggml_prec_set_acc' 1929 | ggml_prec_set_acc(cur, GGML_PREC_F32); | ^~~~~~~~~~~~~~~~~…”

“### System Info ``` - `transformers` version: 5.18.0.dev0 - Platform: Linux-7.0.0-31-generic-x86_64-with-glibc2.39 - Python version: 3.10.20 - Huggingface_hub version: 1.15.0 - Safetensors version: 0.8.0 - Accelerate version: 1.13.0 - Accelerate config: not found - DeepSpeed version: not installed - PyTorch version (accelerator?): 2.12.0+cu130 (CUDA) - Using distributed or parallel set-up in script?: no - Using…”

“## What happened On ollama **0.24.0** (Linux, Fedora, AMD Strix Halo–class UMA APU, runner using the **Vulkan ggml backend** — `/usr/local/lib/ollama/vulkan/libggml-vulkan.so`), the runner process wedged and stayed wedged for ~40 hours until restarted: - ONE runner thread pinned at 100% of a core (~14.66M CPU ticks accumulated), all sibling threads idle (~13k ticks). - GPU busy 0% throughout. - A `gdb -p -batch…”

“**What happened** After a manual "Compact context" succeeds, the Usage drawer's context meter keeps showing the pre-compaction fill, and the compaction flow reports that no tokens were freed. This starts with the first compaction in a conversation and repeats on every later one. **Why** `stats.usage_to_metrics` carries one entry per LLM usage id - the agent's own entry (`default`) plus secondary ones such as…”

“### Operating System Windows ### Installation Method npm (`npx @openhands/agent-canvas` or `npm install -g @openhands/agent-canvas`) ### Agent Canvas Version 1.17.0 ### Bug Description When trying to add a local llm I use the Advanced tab and I set: But when hitting save it always gives this error: ``` litellm.BadRequestError: LLM Provider NOT provided. Pass in the LLM provider you are trying to call. You passed…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Summary With `average_tokens_across_devices=True`, `Trainer` scales the entire scalar returned by Qwen3-MoE to compensate for global token normalization, including the router auxiliary loss. DDP already averages that auxiliary term across ranks, so its effective coefficient grows with the number of processes. Moving the same logical batch from one rank to two therefore changes the router gradient, even with…”

“### Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title. ### Description `RemoteGraph.invoke()` / `ainvoke()` drain the langgraph-sdk stream and return the final state chunk verbatim, so message lists in the graph state come back as raw `list[dict]`. Local `Pregel` execution hydrates message channels through the `add_messages` reducer into `BaseMessage`…”

“### What version of Codex CLI is running? `codex-cli 0.153.1` (also reproduced against `rust-v0.153.3`) ### What subscription do you have? Not relevant to this report — the defect is reproducible from the `codex-rs` crate tests and involves no account state. ### Which model were you using? Any. The failure is in the unified-exec process manager and is independent of the model. ### What platform is your computer?…”

“### Your current environment - vLLM `v0.1.dev20904+g179dd0fa9` - Image `vllm/vllm-openai:deepseekv41-flash-0909` - Model `deepseek-ai/DeepSeek-V4.1-Flash` - Python frontend; multimodal enabled ### 🐛 Describe the bug `/v1/responses` rejects valid structured text input before inference. ```bash curl http://localhost:8000/v1/responses \ -H 'Content-Type: application/json' \ -d…”

“### Bug With **docling-core** version 2.96.0, a regression has been introduced, due to PR https://github.com/docling-project/docling-core/pull/723. This PR was aimed at improving the markdown serialization of tables with multi-row column headers (see issue https://github.com/docling-project/docling-core/issues/722 ). However, it has introduced a bug in the markdown serialization of tables with row headers (_pivot…”

“**Describe the bug** During peak load, Codex Desktop returns "Selected model is at capacity. Please try a different model." and hard-fails. Codex Web, on the same account and model, automatically falls back to a less-loaded model and continues working. This leaves Pro subscribers unable to work in Desktop whenever the newest models are overloaded. **Environment** - Plan: ChatGPT Pro - Client: Codex Desktop…”

“### Your current environment ============================== System Info ============================== OS : Ubuntu 26.04 LTS (x86_64) GCC version : (Ubuntu 15.2.0-16ubuntu1) 15.2.0 Clang version : Could not collect CMake version : Could not collect Libc version : glibc-2.43 ============================== PyTorch Info ============================== PyTorch version : 2.13.0+cu130 Is debug build : False CUDA used to…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“## Problem Computer Use in the Codex/ChatGPT desktop app on Windows detects D5 Render and reads its accessibility tree, including the open project's title and imported model, but cannot activate the window or send clicks. This prevents continuing a rendering workflow. ## Reproduction observed in this session 1. Open D5 Render with a project (also reproduced in an empty scene). 2. Initialize the bundled Computer…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“Lenovo IdeaCentre Mini 01Q8X10 – Copilot+ PC with Snapdragon X X1‑26‑100, 32GB LPDDR5x, 512GB PCIe 4.0 SSD & Adreno Graphics | Windows 11 Home. On the above machine I have tried to dual boot with ubuntu-26.04.1-desktop-arm64.iso on two different Kingston bootable pendrives, but after pressing Enter with 'Try or Install Ubuntu' higlighted the screen goes blank, then 10-20 seconds later the Lenovo startup…”

“### System Info Transformers v5.17 ### Who can help? @Rocketknight1 @pengzhiliang @ArthurZucker ### Information - [ ] The official example scripts - [ ] My own modified scripts ### Tasks - [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...) - [ ] My own task or dataset (give details below) ### Reproduction Looks like this change did it:…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“**Component:** Python SDK ## Description ### Summary When spaCy is installed (`mem0ai[nlp]`) but `en_core_web_sm` is not, `mem0/utils/spacy_models.py::_ensure_model_available` calls `spacy.cli.download("en_core_web_sm")` from inside the first `add()` or `search()`, while holding the module lock. That shells out to `pip install`, or to `uv pip install` when `pip` is not importable. spaCy's CLI reports failure with…”

“### Browser Use Version 0.13.10 (`main` at `50f205533`) ### Bug Description Starting and killing `BrowserSession` repeatedly hangs on a GitHub `windows-latest` runner. The process does not error, does not time out, and does not recover. It stops making progress until the job's `timeout-minutes` cap kills it, and Chrome processes survive that. I hit this while adding a Windows job to `test.yaml` (#5706). The job…”

“## Bug: approximate facet counts non-candidate values in the sampling filter-iter plan When a facet field has more than `sample_target` unique values and the request carries a selective filter, `sampled_approximate_facet` (lib/segment/src/segment/read_view/facet.rs) samples candidate values, builds a candidate MATCH filter, merges it with the request filter, and then picks one of two plans for phase 2. The…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Bug description `JSONNodeParser.get_nodes_from_node` has two edge behaviors that produce silently wrong output: 1. An empty JSON object becomes a node with empty text. `JSONNodeParser().get_nodes_from_documents([Document(text="{}")])` returns one `TextNode` whose `text` is `""`, while an empty array `[]` returns zero nodes. `[{}, {"a": 1}]` emits an empty-text node next to the real one. Empty-text nodes then…”

“### Name and Version lama-server --version version: 0.4.0-dev (build 10883, commit 91f6a6cf3) built with GNU 11.4.0 for Linux x86_64 ### Operating systems Linux ### GGML backends Vulkan ### Hardware AMD Ryzen™ 5 5625U ### Models all models ### Problem description & steps to reproduce Hi, i get this error when i extract the last ubuntu x64 vulkan on linux ubuntu here is the error lama-server -m…”

“**Operating System:** Linux **Installation Method:** From source (`npm run dev` / `npm run dev:minimal`) **Agent Canvas Version:** main @ a879e18 (Sep 9, 2026) **Bug Description** The edit-automation modal's custom cron validator (`validateCronSchedule` in `src/utils/automation-schedule.ts`) rejects some cron expressions that croniter accepts and can schedule, reporting them as unreachable. In `parseCronField`, a…”

“### System Info - `transformers` version: `5.17.0.dev0` - Platform: Linux - Python version: 3.12 - PyTorch version: 2.14.0 - Using distributed or parallel set-up: no - Using GPU: no (reproduces on CPU) ### Reproduction Several ASR feature extractors warn that they are averaging the channels to convert multi-channel audio to mono, but the per-example mean is assigned to a local loop variable and never written back…”

“**Describe the bug** `DocumentSplitter` with `split_by="token"` no longer emits overlap-only trailing chunks since #12661, but the character-based modes sharing `_concatenate_units` (`word`, `period`, `page`, `passage`, `line`, `sentence`) still do. A trailing window consisting solely of already-covered overlap units (plus the empty artifact of a trailing delimiter) becomes its own chunk, duplicating text that is…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“## Bug: `mashriram/gemma3nTools:e4b` emits ` ` natively, but Ollama `/v1/chat/completions` returns neither `tool_calls` nor the content ### Environment - Ollama: 0.33.3 - OS: Debian 13 - Model: `mashriram/gemma3nTools:e4b` - Base architecture: gemma3n - Quantization: Q4_K_M - Custom variant: `gemma3nTools:e4b-65536` with `PARAMETER num_ctx 65536` - Hermes Agent: v0.21.0 ### Model metadata `ollama show…”

“### Describe the bug `smolagents.local_python_executor` silently ignores the `else` clause of `for` and `while` loops. In Python, a loop's `else` block runs when the loop terminates *normally* (i.e. the iterator is exhausted or the `while` condition becomes false) and is skipped only when the loop is exited via `break`. The interpreter's `evaluate_for` and `evaluate_while` never look at the loop's `orelse` body,…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### What happened? On Windows, the desktop app's built-in browser clips the left side of a webpage in the pane beside the chat. The horizontal scrollbar is already at its leftmost position, so scrolling cannot reveal the missing content. The bottom scrollbar is also difficult to access. This makes account setup forms difficult to use. ### Steps to reproduce 1. Open a chat and the built-in browser side by side. 2.…”

“### Problem A valid Gemma4 tool call can return empty `content` and no `tool_calls` when it contains many string values followed by a string array. This reproduces with `gemma4:cloud`; the same parser defect is present on `main` at `159b1c3331a176abf7e8484e44d517db726707db`. ### Minimal reproduction Generate a request containing 45 scalar string values followed by a two-string array: ```python import json values…”

“### Name and Version version: 0.4.0-dev (build 10883, commit 91f6a6cf3) built with Clang 20.1.8 for Windows x86_64 ### Operating systems Windows ### GGML backends CUDA ### Hardware Nvidia T1000 ### Models LFM2.5 1.2B Thinking ### Problem description & steps to reproduce This model produces reasoning content in the content fields and does not display it's reasoning properly showing the ` ` tags. It looks like…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Name and Version version: 0.4.0-dev (build 10881, commit 22397c31a) built with GNU 11.4.0 for Linux x86_64 ### Operating systems Linux ### GGML backends Vulkan ### Hardware NVIDIA GeForce RTX 3060 ### Models https://huggingface.co/empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF its a qwen 3.5 variant ### Problem description & steps to reproduce my tools cant show images to the model at all i verified it…”

“### Operating System Any ### Installation Method From source (`npm run dev` / `npm run dev:minimal`) ### Agent Canvas Version main ### Bug Description The model picker and LLM-profile picker in the chat composer open **upward** (`position: top` / `bottom-full`). When the trigger sits near the bottom of the viewport, the popover's top edge is pushed above the visible area and the top rows are clipped by the…”

“### Before submitting your bug report - [x] I've tried finding an answer on the [Continue docs site](https://docs.continue.dev/) - [x] I'm not able to find an [open issue](https://github.com/continuedev/continue/issues?q=is%3Aopen+is%3Aissue) that reports the same bug - [x] I've seen the [troubleshooting guide](https://docs.continue.dev/troubleshooting) on the Continue Docs ### Relevant environment info…”

“### Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangGraph rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangGraph (or the specific integration package). -…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### System Info - `transformers`: current `main` - Model: InternVL / `InternVLForConditionalGeneration` - Reproduced directly with PyTorch, without Accelerate, DeepSpeed, DDP, or an external training runner ### Who can help? @amyeroberts ### Information - [x] The official example scripts - [x] My own modified scripts ### Reproduction `InternVLConfig` accepts patch-grid/downsample combinations that cannot be…”

“### Name and Version version: 0.4.0-dev (build 10879, commit 9cf3bf256) built with Clang 24.0.0 for Linux x86_64 ### Operating systems Linux ### GGML backends SYCL ### Hardware Intel Arc Pro B70 ### Models N/A ### Problem description & steps to reproduce `get_scratchpad_mem` function keeps oneDNN's scratchpad globally (in the backend's context) and never releases it. `ggml_sycl_pool_vmm` is a LIFO stack. The…”

“### Checked other resources - [x] This is a bug, not a usage question. - [x] I used GitHub search to check for an existing report or PR. - [x] I reproduced this on the current main branch. - [x] The example below is self-contained and does not require a server. ### Reproduction from unittest.mock import MagicMock from langgraph.pregel.remote import RemoteGraph client = MagicMock()…”

“### System Info Reproduced on current `transformers` main with PyTorch/CUDA in a direct single-process `DeepseekV3ForCausalLM` run. ### Who can help? _No response_ ### Information - [x] The official example scripts - [x] My own modified scripts ### Tasks - [x] An officially supported task in the `examples` folder - [x] My own task or dataset ### Reproduction `DeepseekV3Config` accepts odd `qk_rope_head_dim`…”

“### System Info - Transformers: current `main` - PyTorch grouped matrix multiplication path in `src/transformers/integrations/moe.py` ### Who can help? Leaving this to the core maintainers to route; this is in the MoE/grouped matrix multiplication integration path. ### Information - [ ] The official example scripts - [x] My own modified scripts ### Tasks - [ ] An officially supported task in the `examples` folder…”

“### System Info - Transformers: current `main` - Minimal reproducer uses a standalone `LlamaConfig`; no dataset or distributed setup is required. ### Who can help? Leaving this to the core maintainers to route; this is in the Llama attention/configuration path. ### Information - [ ] The official example scripts - [x] My own modified scripts ### Tasks - [ ] An officially supported task in the `examples` folder -…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Browser Use Version 0.13.10; upstream commit 2b1f9d377999a59fe7627c1a5aa88c12aa42e11f ### Bug Description, Steps to Reproduce, Screenshots The `evaluate` action discards the useful part of Chromium's JavaScript exception and returns only `JavaScript execution error: Uncaught`. This is reproducible with a direct tool call on `about:blank`; no LLM, credentials, iframe, or external website is needed. For…”

“### Browser Use Version 0.13.10 ### Bug Description, Steps to Reproduce, Screenshots Description During long-running browser automation tasks, browser-use performance gradually degrades due to repeated full DOM processing, increasing message history size, and unnecessary browser state synchronization. After analyzing the repository architecture and execution pipeline, the main bottlenecks appear to be: Full DOM…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Name and Version llama-server version 0.3.0-dev (build 10797, commit 832fd6f17) Built with Clang 20.1.8 for Windows x86_64 ### Operating systems Windows ### Which llama.cpp modules do you know to be affected? llama-server ### Command line ```shell ``` ### Problem description & steps to reproduce Duplicate clear ("×") buttons shown in sidebar search input when typing text. Steps to reproduce: 1. Start the…”

“### Name and Version version: 0.3.0-dev (build 10788, commit e107984bc) / built with IntelLLVM 2026.1.1 for Linux x86_64 ### Operating systems Linux ### Which llama.cpp modules do you know to be affected? llama-server ### Command line ```shell llama-server -m --port 8080 ``` ### Problem description & steps to reproduce $ lscpu | grep -E 'Model name|Thread\(s\) per core' Model name: Intel(R) Core(TM) Ultra 7 265K…”

“### 🐛 Describe the bug ### Your current environment v0.27.1, launched with `VLLM_USE_RUST_FRONTEND=1`. ### Problem description The scale-out render endpoints exist only in the Python (FastAPI) frontend. They are registered unconditionally in `vllm/entrypoints/openai/api_server.py` (`build_app` → `register_scale_out_api_routers`, see `vllm/entrypoints/scale_out/render/api_router.py`) whenever `"generate"` is in…”

“### Environment Reproduced from main at `a97dacb7106ee49f39f3d1fc6ae1800ff724e01d`, using Python 3.12 on macOS arm64. These are benchmark-result export bugs; the reproductions call the actual exporter without loading a model or starting a server. ### Describe the bugs Two cases in `vllm/benchmarks/lib/utils.py::use_compile` affect PyTorch benchmark export when `SAVE_TO_PYTORCH_BENCHMARK_FORMAT=1`. **1. Unset…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### System Info - `transformers` version: 5.17.0.dev0 - Platform: Linux-7.0.0-31-generic-x86_64-with-glibc2.39 - Python version: 3.10.20 - Huggingface_hub version: 1.15.0 - Safetensors version: 0.8.0 - Accelerate version: 1.13.0 - Accelerate config: not found - DeepSpeed version: not installed - PyTorch version (accelerator?): 2.12.0+cu130 (CUDA) - Using distributed or parallel set-up in script?: no - Using GPU…”

“### Bug Description The final onboarding modal gives no meaningful indication that a conversation is starting after the user submits the suggested web-page task. The wait was noticeably long on a Docker-backed Canvas deployment; the cause and duration of latency have not been measured. ### Steps to Reproduce Run method: source `agent-canvas` isolated stack via `run-agent-canvas.sh --isolated`, frontend built with…”

“### Bug Description After successful onboarding with gpt-5.6-luna through a ChatGPT subscription, the conversation composer reports that the LLM is not configured. ### Steps to Reproduce Run method: source `agent-canvas` isolated stack via `run-agent-canvas.sh --isolated`, frontend built with `npm run build`, Docker-backed conversation runtime (SDK PR #3403). 1. Open Canvas and complete onboarding. 2. Select…”

“### What happened? `SpaceToolWrapper.forward` (created by `Tool.from_space`) post-processes the gradio client result with: ```python if isinstance(output, tuple) or isinstance(output, list): if isinstance(output[1], str): raise ValueError("The space returned this message: " + output[1]) output = output[0] # result is at index 0 ``` `output[1]` is accessed whenever the output is a tuple **or list**, with no length…”

“### Summary `tests/test_retry.py::test_error_handler_resumes_after_crash_multiple_nodes` **fails when the full suite runs, but passes in isolation**. This makes it an order-dependent / global-state flake that can turn CI red intermittently. ### Reproduction ```bash cd libs/langgraph pytest tests/ -q # -> 1 failed (this test) pytest tests/test_retry.py -q # -> 105 passed pytest…”

“### Name and Version version: 0.4.0-dev (build 10853, commit 9dcf84e5a) ### Operating systems Linux ### GGML backends CPU ### Hardware ASUS Nuc 14 Pro. Intel Core Ultra Series 1 (155H) Meteor Lake. ### Models LFM2.5-8B-A1B-Q4_K_M.gguf LFM2.5-8B-A1B-DSpark-Q8_0.gguf ### Problem description & steps to reproduce Command: llama-server -m LFM2.5-8B-A1B-Q4_K_M.gguf \ -md LFM2.5-8B-A1B-DSpark-Q8_0.gguf \ --spec-type…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“## Bug Description When `McpToolSpec(include_resources=True)` is enabled, `fetch_resources()` combines static MCP resources with `resource_templates`, and `to_tool_list_async()` exposes both as LlamaIndex `FunctionTool`s. For a dynamic resource template, the current implementation takes `resource.template` and builds a zero-argument function: ```python elif hasattr(resource, "template"): uri = resource.template…”

“### Before submitting your bug report - [x] I've tried finding an answer on the [Continue docs site](https://docs.continue.dev/) - [x] I'm not able to find an [open issue](https://github.com/continuedev/continue/issues?q=is%3Aopen+is%3Aissue) that reports the same bug - [ ] I've seen the [troubleshooting guide](https://docs.continue.dev/troubleshooting) on the Continue Docs ### Relevant environment info…”

“### Operating System Windows ### Installation Method Other ### Agent Canvas Version 1.16.0 ### Bug Description I'm trying to use different agent roles. For that i have the agent.md files in the right structure (.agents/agents/*.md) However when the agent tries to access these files (or do any terminal command) it doesn't work (most of the time) with an output of [Command finished execution with no output] It then…”

“## Bug An OpenAI Chat response that streams text, a tool call, then more text produces a `PartDeltaEvent` for a text part that has already ended. With `VercelAIAdapter(sdk_version=6)`, this becomes a `text-delta` after `text-end` for the same ID, and the frontend raises: > Received text-delta for missing text part with ID "...". Ensure a "text-start" chunk is sent before any "text-delta" chunks. This was observed…”

“### Operating System Linux ### Installation Method Docker (`ghcr.io/openhands/agent-canvas`) ### Agent Canvas Version 1.16.0 ### Bug Description 9Router works by connecting multiple LLM API providers and exposing their models via a single openAI compatible endpoint. In case of ollama, it has a prefix of "ollama-local". Such provider doesn't exist in litellm, causing an error "LLM Provider NOT provided". Openhands…”

“### Bug Description `BasicMCPClient._configure_tool_call_logs_callback()` currently relies on `logging.basicConfig(..., handlers=[stream_handler])` to attach a temporary `StringIO` handler before an MCP tool call. `logging.basicConfig()` is intentionally a no-op once the root logger already has handlers unless `force=True` is supplied. In a typical FastAPI/Jupyter/CLI application where logging has already been…”

“### Checked other resources - [x] This is a bug, not a usage question. - [x] I searched the issue tracker for `RedisCache`, `namespace`, `colon`, and `cache collision`. - [x] I found #8660 for the analogous SQLite namespace-separator problem, but no Redis-specific report. ### Description `RedisCache` flattens a `Namespace` tuple and the final cache key into one colon-delimited string: ```python def…”

“### Bug Description `McpToolSpec.allowed_tools` is documented as a filter for **tools**, but `fetch_resources()` currently reuses the same list to filter MCP resources and resource templates. That means a caller who intentionally restricts callable tools while enabling resources can unexpectedly lose all resources unless a resource happens to have the same name as one of the allowed tools. Current constructor…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Name and Version llama.cpp at `64e9bceb2c3a856efed96feda784a50947049feb`, Release build with Metal enabled. ### Operating systems Mac: macOS 27.0 (26A5425a), Apple M5 Max, 128 GiB memory. ### Which llama.cpp modules do you know to be affected? llama-cli, Metal backend. ### Problem description & steps to reproduce MiniCPM3-4B crashes with `-fa auto` on Metal. The same model and command generate normally with…”

“### Description The root Makefile's package loops can return success after a child command fails. A later successful command, or even a trailing directory skipped by the `if` guard, overwrites the loop's exit status. This affects the root `install`, `lint`, `format`, `lock`, `lock-upgrade`, and `test` targets. ### Reproduction On main at `81bf17b23123e4ef8b9d5f49fa09a0122fc2edd1`, run from the repository root:…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“`Agent._update_loop_detector_actions()` counts every action in the model's proposed batch, including actions that `multi_act()` never dispatches. A skipped action can therefore reach the repetition threshold and produce a false loop warning. This was found by source inspection and deterministic regression tests against main commit `2b1f9d377999a59fe7627c1a5aa88c12aa42e11f`. This report does not attribute any…”

“### Describe the bug `LocalPythonExecutor` never applies decorators. `ast.FunctionDef.decorator_list` and `ast.ClassDef.decorator_list` are read nowhere in `local_python_executor.py`: `evaluate_function_def` builds the function from the node and returns it, and `evaluate_class_def` puts each method into the class dict through the same path. The decorated object is therefore the undecorated one, and nothing…”

“**Current Behavior** With strict mode enabled and `search_allow_exact: false`, a gRPC `Facet` request with `exact: true` is accepted and runs an exact facet count. The equivalent REST request (`POST /collections/{collection_name}/facet` with `"exact": true`) is correctly rejected with a strict-mode error, so REST and gRPC disagree. **Expected Behavior** Both APIs should reject `exact: true` when strict mode…”

“**Checked other resources** - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangGraph rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangGraph (or the specific integration package). -…”

“### Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangGraph rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangGraph (or the specific integration package). -…”

“## Bug description The model-visible GitHub app tool named `github_add_comment_to_issue` exposes this required parameter: ```ts pr_number: number // Pull request number in the repository. ``` The tool name and purpose say it adds a top-level comment to an issue thread, but the required identifier is named and documented as PR-only. This is ambiguous for ordinary GitHub issues and causes agents to either avoid the…”

“## Bug On Windows, Codex Desktop can lose the local project registry after a startup state/index failure. Re-adding the project folders with Ctrl+O restores only empty project shells; historical local sessions are not re-associated with the restored projects. The underlying session data may still exist locally, including image-heavy sessions. ## Environment - Product: Codex Desktop - Platform: Windows - Scope:…”

“### Proposal to improve performance _No response_ ### Report of performance regression _No response_ ### Misc discussion on performance The code for `pad_spec_decode` in the current Scheduler is written as follows: ```py # Pad new decode requests to uniform spec decoding size to # preserve full cudagraph for this step. # Not for diffusion where draft tokens can't be padded. if ( (self.num_spec_tokens > 0 and…”

“### Browser Use Version 0.13.8 (local source checkout). The affected code is also present at upstream commit [2b56dc8f599001d2257fd89f8fd2327d1a3cc995](https://github.com/browser-use/browser-use/blob/2b56dc8f599001d2257fd89f8fd2327d1a3cc995/browser_use/browser/watchdogs/default_action_watchdog.py#L1408-L1409). ### Bug Description When replacing an existing value, the `input` action clears the field and…”

“## Question Does Ollama currently support running the `IQ3_S` quantization of `Qwen3.8-27B-GSQ-RCO-GGUF` from hf.co? ## Problem When running `hf.co/ISTA-DASLab/Qwen3.8-27B-GSQ-RCO-GGUF:IQ3_S` via Ollama: - Generation completes (`done_reason: "stop"`) - `content` field is always an **empty string** - No error or warning is shown ## Steps to reproduce ```bash ollama pull…”

“> This issue was posted by Codex Desktop using gpt-6-astra on behalf of David. Reduce avoidable capability traceback frames and expensive formatting of run state during exception capture. A user reported a memory increase after a Sentry SDK upgrade automatically enabled its Pydantic AI integration; investigating tool errors exposed repeated formatting of substantial dependencies through traceback locals. The…”

“### Name and Version [https://github.com/ggml-org/llama.cpp/blob/master/docs/backend/OPENVINO.md#validated-models](https://github.com/ggml-org/llama.cpp/blob/master/docs/backend/OPENVINO.md#validated-models) ### Operating systems Windows ### GGML backends OpenVINO ### Hardware Intel Ultra 7 265 ### Models Qwen3.5 with Q8_0 ### Problem description & steps to reproduce When to support Qwen3.5 model for OpenVIVO…”

“Summary I am a very heavy Codex user working on a large custom Unity RPG system. I have used multiple generations of GPT/Codex extensively on the same long-running project, so I have a fairly stable longitudinal baseline for model behavior. I am reporting what I believe is a regression in a capability that is difficult to capture with normal coding benchmarks: problem formation, exploratory search, framing…”

“### Bug `MsWordDocumentBackend._convert_elements_via_docx` dominates DOCX parse time on figure-bearing documents. On 3GPP TS 23.501 v18.7.0 (7.8 MB, 150 EMF figures) our stage ledger recorded **131.0 min and 130.5 min** for the parse on two independent runs; with the one-line change below it is **2.94 min**, output byte-identical. When a DOCX contains DrawingML/EMF figures needing LibreOffice rasterization, the…”

“### Your current environment The output of python collect_env.py ```text Collecting environment information... ============================== System Info ============================== OS : Ubuntu 26.04 LTS (x86_64) GCC version : (Ubuntu 15.2.0-16ubuntu1) 15.2.0 Clang version : Could not collect CMake version : version 4.2.3 Libc version : glibc-2.43 ============================== PyTorch Info…”

“### Before submitting your bug report - [x] I've tried finding an answer on the [Continue docs site](https://docs.continue.dev/) - [x] I'm not able to find an [open issue](https://github.com/continuedev/continue/issues?q=is%3Aopen+is%3Aissue) that reports the same bug - [x] I've seen the [troubleshooting guide](https://docs.continue.dev/troubleshooting) on the Continue Docs ### Relevant environment info…”

“### Your current environment Environment ``` vLLM built from main (verified on 808f8cd3ac and 58ad1f3b89) Serving GLM-5.3-Flash NVFP4, 2x H200 NVL (SM90), TP2, --kv-cache-dtype fp8, --max-model-len 1048576, --max-num-seqs 32, MTP k=3. The numbers below come from calling the backend directly inside that serving image, so they do not depend on the serving flags. ``` ### 🐛 Describe the bug…”

“### System Info - `transformers` 5.17.0.dev0 (`main`). `align_special_tokens` is byte-identical on `v5.16.1`. The alignment itself has been in `Trainer` since 4.56.0 (#38441), so the behavior is not new. - Python 3.12.9, torch 2.8.0, CPU. No accelerator needed to reproduce. ### Who can help? @gante (author of #38441), @SunMarc ### Reproduction `Trainer.train()` calls `align_special_tokens`…”

“## Describe the bug When `InMemoryDocumentStore` is constructed with `return_embedding=False`, `filter_documents` strips embeddings with: ```python docs = [replace(doc, embedding=None) for doc in docs] ``` `dataclasses.replace` is a **shallow** copy. The returned `Document` is a new object, but it still shares the same `meta` dict (and nested mutables) with the document kept in `storage`. Mutating `returned.meta`…”

“## Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find any. - [x] I am sure that this is a bug in LangGraph rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangGraph (or the specific integration package). -…”

“## Describe the bug `DocumentJoiner` `weights=[w0, w1, …]` are zipped positionally onto the Variadic `documents` list. That list order is **not** `Pipeline.connect()` order: - sync `run`: independent senders run in alphabetical component-name order, so weights bind to alphabetical arrival - `run_async`: completion/arrival order (nondeterministic) Users reasonably assume `connect(sparse); connect(dense)` +…”

“## Bug: file-level and inline comments in `breakpoint.py` claim snapshot saving is enabled by default (it is disabled) **Haystack version**: 3.1.0rc0 (upstream `de7b89c98`) **Affected code**: `haystack/core/pipeline/breakpoint.py` - File-level comment, line 19: `# Environment variable to control pipeline snapshot file saving (enabled by default)` - Inline comment, line 165: `# Check if snapshot saving is enabled…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“## Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find any. - [x] I am sure this is a bug in LangGraph rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangGraph (or the specific integration package). - [x]…”

“### Bug Description Every multimodal retrieval path in `llama-index-indices-managed-lancedb` raises `TypeError` before it can return a result. The four image branches in `utils.py` construct `NodeWithScore` with the document as a **positional** argument:…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“## Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find any. - [x] I am sure this is a bug in LangGraph rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangGraph (or the specific integration package). - [x]…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“### What version of the Codex App are you using (From “About Codex” dialog)? Current Codex Desktop for Windows as of 2026-09-07. Exact build number was not captured when filing this report. ### What subscription do you have? ChatGPT Plus ### What platform is your computer? Windows 11 with WSL / Ubuntu ### What issue are you seeing? Custom pets cannot be read and displayed correctly when Codex Desktop is…”

“(First time filing an issue here, sorry if I get some formatting wrong.) Quick disclosure since it's relevant to how thorough this writeup is: I noticed my self-hosted fitness app's AI chat was giving wrong/missing results when I asked about two foods in one message. I used Claude Code (I run it locally against my own model-serving box) to help dig into why. It's the one that actually ran the isolation tests…”

“### Describe the bug `Tool.from_langchain` wraps a LangChain tool and, in `forward`, maps positional arguments onto `self.inputs`. Each positional value uses `next(iter(self.inputs))`, which is always the first key. A two-argument call overwrites that one field and drops the rest. On `main` at `30bb116`: ```python input_key = next(iter(self.inputs)) tool_input[input_key] = argument ``` `wrapped.forward(3, 7)`…”

“### Your current environment ``` vLLM version: 0.28.0+cpu (official prebuilt CPU wheel from GitHub Releases) torch: 2.13.0+cpu Python: 3.12.14 OS: Ubuntu 26.04 (x86_64) Backend: CPU only (device_config=cpu) ``` ### 🐛 Describe the bug Several log lines and Prometheus metric *names* hardcode "GPU" regardless of `current_platform`, which is misleading when running the CPU backend (and presumably XPU/TPU too). The…”

“### What is the issue? ollama run qwen3-coder:30b terminates with exit status 0xc0000409 on an RTX 5070 Ti Laptop (Blackwell, sm_120). The error surfaces as CUDA error: shared object initialization failed, which reads like a memory problem but is not — the memory fit succeeds, all 49 layers load, and the crash happens afterwards during warmup, inside the flash-attention MMA kernel while it reserves dynamic shared…”

“### Name and Version version: 0.4.0-dev (build 10809, commit 5266f24da7) built with GNU 16.2.1 for Linux x86_64 ### Operating systems Linux ### GGML backends Vulkan ### Hardware Radeon 7900 XTX ### Models https://huggingface.co/unsloth/gemma-4-26B-A4B-it-qat-GGUF ### Problem description & steps to reproduce The template is classified as not supporting typed content: ``` ❯ curl…”

“### Name and Version version: 0.4.0-dev (build 10825, commit 9e0e22059) built with Clang 20.1.8 for Windows x86_64 ### Operating systems Windows ### GGML backends CUDA ### Hardware . ### Models _No response_ ### Problem description & steps to reproduce I have download llama and relative dlls and put them into the same directory and run llama but gpu is not used. Now I know that llama does not find dlls from its…”

“## Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find any. - [x] I am sure this is a bug in LangGraph rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangGraph (or the specific integration package). - [x]…”

“## Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find any. - [x] I am sure this is a bug in LangGraph rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangGraph (or the specific integration package). - [x]…”

“### What is the issue? Current [implementation](https://github.com/ollama/ollama/blob/83ed7d9965b1ee07e0f0b29fd46e47c31f0fcab8/types/model/name.go#L340-L341) validate the model name with 80 characters limit. This prevent pulling huggingface model with long name and/or filename. E.g.…”

“### System Info - `transformers` version: 5.17.0.dev0 (main @ c93057d483) - Platform: Linux-7.0.0-31-generic-x86_64-with-glibc2.39 - Python version: 3.10.20 - Huggingface_hub version: 1.15.0 - Safetensors version: 0.8.0 - Accelerate version: 1.13.0 - Accelerate config: not found - DeepSpeed version: not installed - PyTorch version (accelerator?): 2.12.0+cu130 (CUDA) - Using distributed or parallel set-up in…”

“### Title Vulkan backend fails with "Not enough memory for command submission" loading a 66 GB model on AMD iGPU (regression since v0.32.12) ### Environment - OS / distro: Winux 11.26.03.1 (Ubuntu-based), kernel 7.0.0-31-generic - Ollama version that WORKS: v0.32.9 - Ollama versions that FAIL: v0.32.14 and v0.33.3 - GPU: AMD Radeon Graphics (RADV RENOIR) — integrated GPU, shared system memory - Vulkan driver:…”

“### Submission checklist - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x]…”

“## Problem A normal `return` inside a `with` block is passed to the context manager's `__exit__` as an exception. A SQLite transaction therefore rolls back even though the function returns successfully. This can silently discard writes made by code executed by an agent. ## Steps to reproduce On current main, `30bb1161095dbae2271e6bc3cc4c219cc3897a57` (`smolagents==1.27.0.dev0`), run the following with the…”

“## Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find any. - [x] I am sure this is a bug in LangGraph rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangGraph (or the specific integration package). - [x]…”

“### What is the issue? Environment: macOS, MacBook Air M4, 32GB RAM Model: muse-glimmer:30b-mlx (digest 015fa21845be) ``` $ ollama show muse-glimmer:30b-mlx | grep -i quant quantization nvfp4 ``` Description: Running this specific MLX-backend model tag repeatedly enters a persistent "Stopping..." state in ollama ps output that does not resolve, even with OLLAMA_KEEP_ALIVE=30m explicitly set. This occurred across…”

“## Summary After resuming an interrupted local task, Codex Desktop repeatedly shows an older conversation state when refreshed or reopened. Later user messages and the completed assistant response are still present in the durable rollout JSONL, but the paginated history projection no longer advances. This report adds a two-record ordinal regression on bundled CLI 0.153.4 and a specific suspected deserialization…”

“### Summary Vim mode in the Codex CLI does not support `Ctrl+C` as a way to leave Insert mode and return to Normal mode. Instead, pressing `Ctrl+C` clears the entire prompt. When an agent turn is running, it can also cancel the turn. The missing mode transition affects ordinary prompt editing even when the agent is idle, not just editing during an active turn. ### Steps to reproduce 1. Enable Vim mode in the…”

“**Problem** The model-visible declaration for Gmail `search_emails` requires `emails[].from: string`. Returned email records instead contain `from_`, with `from` absent. This remains observable after accommodating the separate `result` wrapper discrepancy. **Reproduction** Connect Gmail and use a query that matches at least one message. Run inside `functions.exec`: ```js const response = await…”

“**Problem** In Code Mode, the model-visible tool declarations describe `CallToolResult `. Successful calls instead return the payload directly inside `structuredContent`. This causes code following the declared return type to read `undefined`. **Reproduction** With the GitHub connector available, inspect the declaration for `github_fetch_issue`, then run this inside `functions.exec`: ```js const response = await…”

“# Issue: UnicodeDecodeError on Windows when stdin contains Chinese characters ## Environment - OS: Windows 11 (zh-CN) - Python: 3.11.4 - browser-use: 0.1.9 - Shell: MSYS/git-bash ## Problem When using the browser-use CLI, passing Chinese characters via stdin causes a `UnicodeDecodeError`. The error occurs when the CLI reads the Python code from stdin: ``` Traceback (most recent call last): ... File " ", line 322,…”

“### Summary `--attention-backend FLASHINFER` fails the startup KV-cache-memory check at a `--max-model-len` that the default backend (FLASH_ATTN) serves fine, on the same GPUs with the same `--gpu-memory-utilization`. The failure message points the user at `gpu_memory_utilization` / `max_model_len` but never mentions that the attention backend is the variable that changed. Because `--kv-cache-dtype fp8` selects…”

“--- `create_function` in `src/smolagents/local_python_executor.py` binds call arguments to parameters by hand, and the binding diverges from CPython in six ways. Most of them produce a **silently wrong value** rather than an error, so an agent's code action keeps running on bad data. `evaluate_lambda` has the same defects independently. ## Reproduction ```python from smolagents.default_tools import…”

“### Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used GitHub search to check open and closed issues and pull requests. - [x] I am sure that this is a bug in LangGraph rather than my code. - [x] The bug reproduces on the latest current `main`. - [x] This is not related to the `langchain-community` package. - [x]…”