Three bugs in gateway session hygiene pre-compression caused 'Session too
large' errors for ~200K context models like GLM-5-turbo on z.ai:
1. Gateway hygiene called get_model_context_length(model) without passing
config_context_length, provider, or base_url — so user overrides like
model.context_length: 180000 were ignored, and provider-aware detection
(models.dev, z.ai endpoint) couldn't fire. The agent's own compressor
correctly passed all three (run_agent.py line 1038).
2. The 1.4x safety factor on rough token estimates pushed the compression
threshold above the model's actual context limit:
200K * 0.85 * 1.4 = 238K > 200K (model limit)
So hygiene never compressed, sessions grew past the limit, and the API
rejected the request.
3. Same issue for the warn threshold: 200K * 0.95 * 1.4 = 266K.
Fix:
- Read model.context_length, provider, and base_url from config.yaml
(same as run_agent.py does) and pass them to get_model_context_length()
- Resolve provider/base_url from runtime when not in config
- Cap the 1.4x-adjusted compress threshold at 95% of context_length
- Cap the 1.4x-adjusted warn threshold at context_length
Affects: z.ai GLM-5/GLM-5-turbo, any ~200K or smaller context model
where the 1.4x factor would push 85% above 100%.
Ref: Discord report from Ddox — glm-5-turbo on z.ai coding plan
b2b4a9ee7d