github / github/app

Auto-compaction never fires for a custom (BYOK) model: context meter undercounts ~1.4× (657,843 shown vs 921,487 charged), so the session dies on 400s and cannot self-recover

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Description

Summary

With a custom (BYOK) provider whose tokenizer the app does not model, the local context
meter undercounts tokens by ~40%. Background compaction (trigger "threshold") and the
buffer-exhaustion blocking threshold both evaluate that undercounted number, so neither can
fire before the provider rejects the request. The session hard-fails with 400s until the user
runs /compact manually.

Environment

  • GitHub Copilot desktop app 1.1.20 (github.exe, %LOCALAPPDATA%\Programs\GitHub Copilot), Windows
  • Agent runtime: copilot 1.0.84-5 (%LOCALAPPDATA%\github-copilot-sdk\cli\1.0.84-5\copilot.exe)
  • Provider: custom DeepSeekauthKind: api_key, baseUrl: https://api.deepseek.com,
    wireApi: responses; model id deepseek-flash (provider id ab5a407d-9560-461f-9e02-a63c36bd4c08)
  • Model config: Max prompt tokens 840,000, Max output tokens 128,000,
    reasoning efforts none / low / high / max
  • MCP servers attached: aspire, github, microsoft-learn, nuget, playwright — all "tools": ["*"]
  • Session 53c1a09d-6bdc-407d-b133-b817e4dc0184, 2026-09-14T02:20:32Z → 2026-09-14T14:18:32Z
    (640 assistant turns, 998 tool executions, 18 images, 18 user messages, 86 autopilot objective changes)

Steps to reproduce

  1. Configure a custom provider whose model accepts 1,048,576 input tokens; set Max prompt
    tokens = 840,000 and Max output tokens = 128,000.
  2. Run one long agentic session (hundreds of turns with large tool outputs and several MCP servers).
  3. Compare the app's context meter with the token count the provider reports in its usage/error responses.

Expected

session.compaction_start with "trigger":"threshold" when the meter crosses the compaction
threshold (observed elsewhere at ~80% of tokenLimit; here that would be 672,000), well before
the provider limit — and no 400 "maximum context length" errors.

Actual

  • No threshold compaction ever fired during the 12-hour session. The only compaction is
    user-initiated: session.compaction_start … "trigger":"manual", timestamp
    2026-09-14T14:18:05.353Z (app log: command_name="compact" at 14:18:04.923Z).
  • At that moment the app's meter read:
    • systemTokens 15,768 + conversationTokens 590,768 + toolDefinitionsTokens 51,304
      = currentTokens 657,843, with tokenLimit 840,00078.3%
    • i.e. 14,157 tokens short of the ~80% (672,000) trip point — the trigger never came close.
  • DeepSeek counted the same conversation at 921,487 tokens. Two model calls failed:
    • 2026-09-14T08:25:35.172Z — 400 This model's maximum context length is 1048576 tokens. However, you requested 1049487 tokens (921487 in the messages, 128000 in the completion). Please reduce the length of the messages or completion.
    • 2026-09-14T08:26:11.368Z — same, 1050149 tokens (922149 in the messages, 128000 in the completion)
    • (8 records total, counting the errorOccurred / sessionEnd hook payloads and the runtime stack.)
  • Undercount factor: 921,487 / 657,843 = 1.400.
  • The manual compaction itself worked: messagesRemoved 1,322, tokensRemoved 572,553,
    590,771 → 18,218 — so compaction is functional; only the automatic trigger's input was wrong.

Control: threshold compaction works for hosted models

Ten sessions on hosted models auto-compacted correctly at ~80% of their limit, e.g.:

  • {"currentTokens":102931,"tokenLimit":128000,"trigger":"threshold"}
  • {"currentTokens":104691,"tokenLimit":128000,"trigger":"threshold"}
  • {"currentTokens":105120,"tokenLimit":128000,"trigger":"threshold"}

Range observed: 102,931–105,120 (80.4%–82.1% of 128,000). The trigger logic is fine; the token
input is wrong for the custom model.

Additional metadata mismatch

The session's model metadata carried max_context_window_tokens: 200000 while the endpoint
enforces 1,048,576 (per the provider's own error), alongside max_prompt_tokens: 840000,
max_output_tokens: 128000.

Impact

  • Background compaction and the buffer-exhaustion blocking threshold (documented default 95%,
    SessionContextInfo.bufferTokens) both operate on the undercounted number, so for BYOK models
    they cannot fire before the provider rejects the request.
  • The session cannot self-recover: retries repeat the same request and the same 400.
  • The context meter is misleading near the limit (~78% shown while the real request was already
    over the window once the 128,000 output reserve is counted).

Likely cause / suggested fixes

  • SessionContextAttribution documents that totals are "tokenized against the resolved model
    (feeds the per-model token multiplier)". For this custom model that multiplier does not match
    the provider's tokenizer.
  • Consider: calibrating the multiplier from provider-reported usage (the runtime already
    receives compactionTokensUsed.inputTokens, cacheReadTokens, etc.), applying a conservative
    safety factor for custom providers, and/or gating compaction on provider-reported input tokens.
  • Re-check attribution of tool/MCP schema mass: five MCP servers at "tools": ["*"] were credited
    only 51,304 tokens here, while the meter/actual gap is ~264,000 tokens.

Evidence

  • Session events: %USERPROFILE%\.copilot\session-state\53c1a09d-6bdc-407d-b133-b817e4dc0184\events.jsonl
    (lines 7523–7549: error events, session.compaction_start / session.compaction_complete)
  • Runtime log: %USERPROFILE%\.copilot\logs\process-1789352396024-130936.log
    (Persisted compaction checkpoint, Compacted conversation history {"messages_removed":1322,"tokens_removed":572553.0,"generation":1})
  • App log: %USERPROFILE%\.copilot\logs\github-app.138040.log (session command compact, 14:18:04.923Z)
  • Schema references: %LOCALAPPDATA%\Programs\GitHub Copilot\copilot-sdk\generated\rpc.d.ts
    (SessionContextInfo.compactionThreshold, promptTokenLimit, bufferTokens, categories.mcpTools)

Field Value
App version 1.1.20
OS Windows 10.0.26200
Theme GitHub
Path /chat
Tenure Week 15

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the session events.jsonl lines 7523–7549 and the generated rpc.d.ts definitions for compactionThreshold, promptTokenLimit, bufferTokens, and mcpTools. Compare the reported context counters with the provider errors and runtime compaction checkpoint. Done means custom-provider sessions trigger compaction before the provider rejects an oversized request and the buffer threshold can prevent the same failure.

Written by the indexing model from the issue text.

Assessment

Tech stack
github
Domain
ai, backend
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Active
Clarity
Mostly clear
Newbie friendliness
48/100

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