at pce /$bunfs/root/src/entrypoints/cli.js:124:1196 のときに疑うこと この症状は、Claude Code の issue では少なくとも 2 件まとまっていました。75923 は「Remote control session fails to receive questions or hangs waiting for input」、74932

at pce /$bunfs/root/src/entrypoints/cli.js:124:1196 のときに疑うこと この症状は、Claude Code の issue では少なくとも 2 件まとまっていました。75923 は「Remote control session fails to receive questions or hangs waiting for input」、74932

at pce /$bunfs/root/src/entrypoints/cli.js:124:1196 のときに疑うこと この症状は、Claude Code の issue では少なくとも 2 件まとまっていました。75923 は「Remote control session fails to receive questions or hangs waiting for input」、74932

at pce /$bunfs/root/src/entrypoints/cli.js:124:1196 のときに疑うこと この症状は、Claude Code の issue では少なくとも 2 件まとまっていました。75923 は「Remote control session fails to receive questions or hangs waiting for input」、74932

at pce /$bunfs/root/src/entrypoints/cli.js:124:1196 のときに疑うこと この症状は、Claude Code の issue では少なくとも 2 件まとまっていました。75923 は「Remote control session fails to receive questions or hangs waiting for input」、74932

at pce /$bunfs/root/src/entrypoints/cli.js:124:1196 のときに疑うこと この症状は、Claude Code の issue では少なくとも 2 件まとまっていました。75923 は「Remote control session fails to receive questions or hangs waiting for input」、74932

at bo / が出たとき、まず /context の表示崩れを疑う 同じ AxiosError: Request failed with status code 400 でも、今回集まっている issue は少し毛色が違います。報告されているのは、CLI の 400 そのものというより、画面の再描画や表示崩れに引きずられて見えているケースです。 ひとつは 72900 で、狭い端末幅の /cont

at bo / が出たとき、まず /context の表示崩れを疑う 同じ AxiosError: Request failed with status code 400 でも、今回集まっている issue は少し毛色が違います。報告されているのは、CLI の 400 そのものというより、画面の再描画や表示崩れに引きずられて見えているケースです。 ひとつは 72900 で、狭い端末幅の /cont

at bo / が出たとき、まず /context の表示崩れを疑う 同じ AxiosError: Request failed with status code 400 でも、今回集まっている issue は少し毛色が違います。報告されているのは、CLI の 400 そのものというより、画面の再描画や表示崩れに引きずられて見えているケースです。 ひとつは 72900 で、狭い端末幅の /cont

Bumps axios from 1.16.1 to 1.18.1. Release notes Sourced from axios's releases. v1.18.1 — June 21, 2026 This release focuses on Node HTTP adapter fixes, safer AxiosError serialisation, runtim...

Hi, I have a space that uses Streamlit to provide a Leaderboard for a benchmark. This requires users to upload a TSV file with their results through Streamlit’s `st.file_uploader`, which causes some problems. My observation is that if I upload a TSV file > 1MB, I get the error “AxiosError: Request failed with status code 413”. I found some posts about AxiosError 403 so I tried setting `maxUploadSize = 50`and `enableXsrfProtection = false` in `.streamlit/config.toml` and verifyed their values with: st.write("XSRF:", st.get_option("server.enableXsrfProtection")) st.write("Max Upload:", st.get_option("server.maxUploadSize")) Since this didn’t work and code 413 seems to be more related to the file size, I tried using the package `streamlit-chunk-file-uploader` to chunk the uploaded files, which didn’t work either. I also couldn’t find the official HF upload limits in the docs. So what are the actual file upload limits and is it possible to increase them? Thanks for your help!

John6666: > Adding it to the docker intialization solved the issue, seems like the config was not being read at all. Thanks!

This issue has existed for quite some time, and there is no known solution. Existing workarounds also do not work. I first asked the AI to summarize the workarounds currently known to address this issue. I will use this as a starting point to explore possible solutions. * * * Do these steps in order. 1. Confirm the cause XSRF cookies are restricted inside the Spaces iframe. Streamlit’s uploader then rejects the final POST with 403. (Hugging Face) 2. Verify your app actually disabled XSRF Add to your app and check on the deployed Space: import streamlit as st st.write("XSRF:", st.get_option("server.enableXsrfProtection")) It must show `False`. If it shows `True`, your config is not loaded. The config file must be at `.streamlit/config.toml` in the same working directory where `streamlit run` executes. (Streamlit document) 3. If you use the Streamlit SDK Space (no Docker) Create `.streamlit/config.toml`: [server] enableXsrfProtection = false # optional if you test large files: # maxUploadSize = 400 Redeploy, then re-check step 2. Max upload defaults to 200 MB; increase only if needed. (Streamlit document) 4. If you use a Docker Space Start Streamlit with flags so the setting is guaranteed: # Dockerfile (tail) EXPOSE 8501 CMD streamlit run /app/app.py --server.port=8501 --server.address=0.0.0.0 --server.enableXsrfProtection=false Spaces’ Streamlit guide shows the SDK and deployment pattern; running on 8501 is standard. (Hugging Face) 5. Ignore `enableCORS` for this error 403 on upload is almost always XSRF, not CORS, when embedded or proxied. (Streamlit) 6. Retest with a tiny file This isolates XSRF from size issues. If large files fail only due to size, raise `server.maxUploadSize` as in step 3. (Streamlit document) 7. If you’re behind auth or a reverse proxy Azure AD and some proxies strip or alter the `_xsrf` cookie. Either keep XSRF off or ensure cookies pass through with proper attributes. (GitHub) 8. Version sanity check If you’re on 1.30.x and still see 403 locally or elsewhere, upgrade to a newer Streamlit release; some users report 1.31.0+ resolved their 403. (Streamlit) 9. If the page was stale A stale client cookie can mismatch after redeploys. Hard refresh after redeploys if you still see 403. (Streamlit) Copy-paste samples you can deploy: A) SDK Space # .streamlit/config.toml [server] enableXsrfProtection = false # app.py import streamlit as st st.write("XSRF:", st.get_option("server.enableXsrfProtection")) f = st.file_uploader("Upload any file") if f: data = f.getvalue() st.write({"name": f.name, "size_bytes": len(data)}) B) Docker Space FROM python:3.11-slim RUN pip install --no-cache-dir streamlit==1.38.0 WORKDIR /app COPY app.py /app/app.py EXPOSE 8501 CMD streamlit run /app/app.py --server.port=8501 --server.address=0.0.0.0 --server.enableXsrfProtection=false This sequence fixes the 403 in Spaces by ensuring XSRF is actually disabled and verified at runtime. (Hugging Face, Streamlit document)

Great! Congrats.

I have been facing this error and even after checking similar discussions and adding `enableXsrfProtection false` to my `config.toml` file, I keep getting this. The upload bar fills up completely but it raises the error afterwards. In some discussions on Streamlit forums people also recommended adding `enableCORS = false` to the config, which I did but with no result. Tried it in incognito mode but also doesn’t work. Any idea on what might be causing this? If necessary I can provide the files to debug

: “Streamlit file_uploader always fails with 403 AxiosError, Space is running on CPU Basic, correct Dockerfile, EXPOSE 7860, ENTRYPOINT correct, no custom JS.”

Thank you for your response. I just removed my firewall and changed the url too. curl -X POST “https://api.openai.com/v1/realtime/calls/rtc_12dddb03e9304953b96cedb5f04b1c2c/refer” -H “Authorization: Bearer <OPEN_AI_KEY>” -H “Content-Type: application/json” -d ‘{“target_uri”: “sip:call_fa19aac3-2b15-4fc9-bde2-a903363102fe_1759795900083@xxx.xxxxxxx.com”}’ Getting these error details: [OpenAI-SIP] Error type: AxiosError [OpenAI-SIP] Error code: ECONNABORTED [OpenAI-SIP] Error message: timeout of 10000ms exceeded [OpenAI-SIP] No response received (timeout or network error) [OpenAI-SIP] REFER failed, will use fallback hangup method [OpenAI-SIP] Stack: AxiosError: timeout of 10000ms exceeded I think I’m having a firewall issue. Firewall removed and still having the issue. This is my latest call ID I tried with: rtc_491247ab8f6a4a868c202db0605f457d

**Description:** When updating an assistant that already has file attachments (file_ids) in the `code_interpreter` tool, sending an update payload with an empty array for `code_interpreter.file_ids` results in unexpected behavior. Although the files are removed, all other changes from the update are discarded, and the API returns a generic network error (AxiosError with code ERR_NETWORK) without any meaningful message. **Steps to Reproduce:** 1. Create an assistant with attached files by setting the `code_interpreter.file_ids` field with valid file IDs. 2. Update the assistant using the following payload: { "file_search": { "vector_store_ids": [] }, "code_interpreter": { "file_ids": [] } } This payload is intended to clear the attached files. 3. Observe that: * The update leads to the removal of the file attachments. * Any other changes included in the same update are discarded. * The request fails with a “Network Error” (AxiosError, ERR_NETWORK), with no error message provided. **Expected Behavior:** * The update should successfully clear the `code_interpreter.file_ids` field while preserving and applying all other changes included in the update payload. * The API should return a successful response (or a clear error indicating what, if anything, went wrong) rather than a generic network error when an empty array is sent. **Actual Behavior:** * If the assistant initially has files attached, sending an empty array for `code_interpreter.file_ids` removes the files but causes all other changes in the update to be discarded. * The response is a network error with the following details: { "message": "Network Error", "name": "AxiosError", "config": { ... }, "code": "ERR_NETWORK", "status": null } **Environment:** * API Endpoint: `https://api.openai.com/v1/assistants/{assistant_id}` * Request method: POST update (assistant update endpoint) * API Version: “OpenAI-Beta: assistants=v2” * Tools Involved: `code_interpreter` under `tool_resources` * Client: Axios-based client **Impact:** * This bug prevents users from resetting file attachments while preserving other configuration updates. * Shop owners cannot update their assistant configuration without encountering network errors when attempting to clear previously attached files. **Additional Notes:** * The issue only occurs when attempting to clear `code_interpreter.file_ids` on an assistant that already has file IDs attached. * When no files are attached, sending an empty array works as expected. * This behavior suggests an inconsistency in how updates are processed for the `code_interpreter` resource.