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feat: smart context length probing with persistent caching + banner display

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Replaces the unsafe 128K fallback for unknown models with a descending
probe strategy (2M → 1M → 512K → 200K → 128K → 64K → 32K). When a
context-length error occurs, the agent steps down tiers and retries.
The discovered limit is cached per model+provider combo in
~/.hermes/context_length_cache.yaml so subsequent sessions skip probing.

Also parses API error messages to extract the actual context limit
(e.g. 'maximum context length is 32768 tokens') for instant resolution.

The CLI banner now displays the context window size next to the model
name (e.g. 'claude-opus-4 · 200K context · Nous Research').

Changes:
- agent/model_metadata.py: CONTEXT_PROBE_TIERS, persistent cache
  (save/load/get), parse_context_limit_from_error(), get_next_probe_tier()
- agent/context_compressor.py: accepts base_url, passes to metadata
- run_agent.py: step-down logic in context error handler, caches on success
- cli.py + hermes_cli/banner.py: context length in welcome banner
- tests: 22 new tests for probing, parsing, and caching

Addresses #132. PR #319's approach (8K default) rejected — too conservative.
This commit is contained in:
teknium1 2026-03-05 16:09:57 -08:00
parent 55b173dd03
commit c886333d32
6 changed files with 324 additions and 16 deletions
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18
hermes_cli/banner.py
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@ -99,11 +99,23 @@ def get_available_skills() -> Dict[str, List[str]]:
# Welcome banner
# =========================================================================
def _format_context_length(tokens: int) -> str:
"""Format a token count for display (e.g. 128000 → '128K', 1048576 → '1M')."""
if tokens >= 1_000_000:
val = tokens / 1_000_000
return f"{val:g}M"
elif tokens >= 1_000:
val = tokens / 1_000
return f"{val:g}K"
return str(tokens)
def build_welcome_banner(console: Console, model: str, cwd: str,
tools: List[dict] = None,
enabled_toolsets: List[str] = None,
session_id: str = None,
get_toolset_for_tool=None):
get_toolset_for_tool=None,
context_length: int = None):
"""Build and print a welcome banner with caduceus on left and info on right.
Args:
@ -114,6 +126,7 @@ def build_welcome_banner(console: Console, model: str, cwd: str,
enabled_toolsets: List of enabled toolset names.
session_id: Session identifier.
get_toolset_for_tool: Callable to map tool name -> toolset name.
context_length: Model's context window size in tokens.
"""
from model_tools import check_tool_availability, TOOLSET_REQUIREMENTS
if get_toolset_for_tool is None:
@ -135,7 +148,8 @@ def build_welcome_banner(console: Console, model: str, cwd: str,
model_short = model.split("/")[-1] if "/" in model else model
if len(model_short) > 28:
model_short = model_short[:25] + "..."
left_lines.append(f"[#FFBF00]{model_short}[/] [dim #B8860B]·[/] [dim #B8860B]Nous Research[/]")
ctx_str = f" [dim #B8860B]·[/] [dim #B8860B]{_format_context_length(context_length)} context[/]" if context_length else ""
left_lines.append(f"[#FFBF00]{model_short}[/]{ctx_str} [dim #B8860B]·[/] [dim #B8860B]Nous Research[/]")
left_lines.append(f"[dim #B8860B]{cwd}[/]")
if session_id:
left_lines.append(f"[dim #8B8682]Session: {session_id}[/]")