u/Pretty-Ad-2673

How to fix this issue:⚠️ Non-retryable error (HTTP 400) — trying fallback...?

Hey guys I am use Claude subscriptions oauth for Hermes agent. The channel I am using is telegram. It works well until sometimes I this error message. This issue has been happening all the time. So I basically cannot have a long session. Every time, I am working on something and all of the sudden this error and just kill my dynamic. Does anyone know the root cause and how to solve it? Thank you

❌ Non-retryable error (HTTP 400): HTTP 400: messages.5.content.1: thinking or redacted_thinking blocks in the latest assistant message cannot be modified. These blocks must remain as they were in the original response.

❌ Non-retryable error (HTTP 400): HTTP 400: messages.5.content.1: thinking or redacted_thinking blocks in the latest assistant message cannot be modified. These blocks must remain as they were in the original response.

⚠️ Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'messages.5.content.1: thinking or redacted_thinking blocks in the latest assistant message cannot be modified. These blocks must remain as they were in the original response.'}, 'request_id': 'req_011CbEkQh8gA3KSKTiaeDXFW'}

reddit.com
u/Pretty-Ad-2673 — 2 days ago

Refit the federal Bulletin 17C flood-frequency analysis for the Potomac at Little Falls (USGS 01646500) in ~12 lines of Python. Open-source toolkit, validated against FEMA FIS within ±10%

Hi everyone,

Wanted to share a quick result before pitching the toolkit. I refit the federal Bulletin 17C flood-frequency analysis for USGS gauge 01646500 (Potomac at Little Falls, 1931-2025, n=80) using a Python toolkit I've been building. The Log-Pearson III 100-year estimate is 443,000 cfs vs the FEMA DC FIS published value of 475,000 cfs, a delta of -6.7%. All four return periods (10/50/100/500-yr) match the FIS within ±10%.

Notebook with the full analysis, Q-Q diagnostic, and validation table:

https://github.com/Rekin226/aquascope-demos/tree/main/01_potomac_flood_frequency

The toolkit is AquaScope, MIT-licensed and open-source. It unifies 12 water-data APIs (USGS, FAO AQUASTAT, FAO WaPOR, GEMStat, EU WFD, Copernicus ERA5, Taiwan MOENV/WRA, Japan MLIT, Korea WAMIS, OpenMeteo, UN SDG 6, US WQ Portal) behind one Pydantic schema, then layers Bulletin 17C FFA (GEV, LP3, Gumbel, GPD, non-stationary GEV, EMA), baseflow separation (Lyne-Hollick, Eckhardt), 22 hydrological signatures, FAO-56 Penman-Monteith ET₀, and an AI methodology recommender on top. 534 tests, validated against the CAMELS benchmark.

Repo: https://github.com/Rekin226/aquascope

Install: pip install aquascope

What I'd really like feedback on is the non-stationary GEV implementation. We fit it as a maximum-likelihood GEV with time-varying location (μ = μ₀ + μ₁·t), and test the trend via likelihood ratio against the stationary fit. For folks who've done this in practice, is that the formulation you'd expect, or would you push back? Are there censored-data scenarios (EMA) where this approach would break down?

Open to other critique too, honest feedback welcome.

reddit.com
u/Pretty-Ad-2673 — 3 days ago