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fix: warn on invalid context_length format in config.yaml (#10067)

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Previously, non-integer context_length values (e.g. '256K') in
config.yaml were silently ignored, causing the agent to fall back
to 128K auto-detection with no user feedback. This was confusing
for users with custom LiteLLM endpoints expecting larger context.

Now prints a clear stderr warning and logs at WARNING level when
model.context_length or custom_providers[].models.<model>.context_length
cannot be parsed as an integer, telling users to use plain integers
(e.g. 256000 instead of '256K').

Reported by community user ChFarhan via Discord.
This commit is contained in:
Teknium 2026-04-14 22:14:27 -07:00 • committed by GitHub
parent a8b7db35b2
commit 93fe4ead83
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2 changed files with 138 additions and 1 deletions
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28
run_agent.py
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@ -1268,6 +1268,19 @@ class AIAgent:
try:
_config_context_length = int(_config_context_length)
except (TypeError, ValueError):
logger.warning(
"Invalid model.context_length in config.yaml: %r — "
"must be a plain integer (e.g. 256000, not '256K'). "
"Falling back to auto-detection.",
_config_context_length,
)
import sys
print(
f"\n⚠ Invalid model.context_length in config.yaml: {_config_context_length!r}\n"
f" Must be a plain integer (e.g. 256000, not '256K').\n"
f" Falling back to auto-detected context window.\n",
file=sys.stderr,
)
_config_context_length = None
# Store for reuse in switch_model (so config override persists across model switches)
@ -1296,7 +1309,20 @@ class AIAgent:
try:
_config_context_length = int(_cp_ctx)
except (TypeError, ValueError):
pass
logger.warning(
"Invalid context_length for model %r in "
"custom_providers: %r — must be a plain "
"integer (e.g. 256000, not '256K'). "
"Falling back to auto-detection.",
self.model, _cp_ctx,
)
import sys
print(
f"\n⚠ Invalid context_length for model {self.model!r} in custom_providers: {_cp_ctx!r}\n"
f" Must be a plain integer (e.g. 256000, not '256K').\n"
f" Falling back to auto-detected context window.\n",
file=sys.stderr,
)
break
# Select context engine: config-driven (like memory providers).