openclaw - 💡(How to fix) Fix DeepSeek preamble text leaks to Telegram after 3.13 → 4.5 upgrade (untagged assistant text bypasses commentary filter) [1 comments, 1 participants]

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openclaw/openclaw#62121Fetched 2026-04-08 03:08:44
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After upgrading from 2026.3.13 to 2026.4.5, DeepSeek (deepseek-chat) cron jobs that deliver to Telegram are leaking preamble/reasoning text ("Let me fetch the data...", "Based on my research...", "Now I have enough information...") that was not visible in 3.13.

Root Cause

The 4.5 commentary-buffering fix (#61282, #59150, #59643) only suppresses text tagged with phase: "commentary" metadata or wrapped in <think> tags. DeepSeek emits preamble as plain untagged assistant text — no phase metadata, no thinking tags — so it bypasses all filtering.

Related: #42062 (same class of issue for GLM-5 via Ollama).

The behavioral regression from 3.13 suggests the old delivery pipeline had different buffering/truncation behavior that incidentally filtered this text before it reached Telegram.

Fix Action

Workaround

Hardened prompt instructions ("CRITICAL RULE: first character must be 🇺🇸, delete any narration") partially mitigate but are not reliable — DeepSeek still slips.

RAW_BUFFERClick to expand / collapse

Description

After upgrading from 2026.3.13 to 2026.4.5, DeepSeek (deepseek-chat) cron jobs that deliver to Telegram are leaking preamble/reasoning text ("Let me fetch the data...", "Based on my research...", "Now I have enough information...") that was not visible in 3.13.

Environment

  • OpenClaw: 2026.4.5 (3e72c03), upgraded from 2026.3.13
  • Model: deepseek/deepseek-chat (V3)
  • Delivery: Telegram (cron jobs)
  • thinking: "off" set on all jobs
  • exec-approvals: security=full, ask=off

Reproduction

Any cron job using DeepSeek that instructs the model to output a formatted template (market data, news digest, etc.) occasionally emits preamble text before the formatted output. This preamble is delivered to Telegram as part of the message.

Same prompts on 3.13 produced clean output consistently.

Root Cause

The 4.5 commentary-buffering fix (#61282, #59150, #59643) only suppresses text tagged with phase: "commentary" metadata or wrapped in <think> tags. DeepSeek emits preamble as plain untagged assistant text — no phase metadata, no thinking tags — so it bypasses all filtering.

Related: #42062 (same class of issue for GLM-5 via Ollama).

The behavioral regression from 3.13 suggests the old delivery pipeline had different buffering/truncation behavior that incidentally filtered this text before it reached Telegram.

Suggested Fix

A post-delivery filter or configurable output sanitizer that can strip text preceding a known output marker (e.g., first emoji character, or a configurable outputStartsWith pattern in the cron job payload) would catch untagged preamble regardless of model.

Workaround

Hardened prompt instructions ("CRITICAL RULE: first character must be 🇺🇸, delete any narration") partially mitigate but are not reliable — DeepSeek still slips.

extent analysis

TL;DR

Implement a post-delivery filter or configurable output sanitizer to strip unwanted preamble text from DeepSeek output.

Guidance

  • Review the changes introduced in the 4.5 commentary-buffering fix (#61282, #59150, #59643) to understand how it affects the filtering of untagged assistant text.
  • Consider adding a configurable outputStartsWith pattern in the cron job payload to help identify the start of the desired output.
  • Test the suggested fix with different prompts and output markers to ensure it effectively strips preamble text.
  • Evaluate the reliability of the hardened prompt instructions as a temporary workaround and consider refining them for better results.

Example

No code snippet is provided as the issue does not contain explicit code references.

Notes

The suggested fix may require additional development and testing to ensure it works correctly with various output formats and markers. The workaround using hardened prompt instructions is not reliable and may not work in all cases.

Recommendation

Apply a workaround by implementing a post-delivery filter or configurable output sanitizer, as upgrading to a fixed version is not mentioned as an option in the issue. This approach allows for a targeted solution to the specific problem of stripping unwanted preamble text.

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