The _generate_summary() method assumed message content is always a
string (msg.get('content') or ''). When content is a multimodal list
(e.g. [{type: 'text', text: '...'}, {type: 'image_url', ...}]), this
produced mangled output: len() returned the list length instead of
character count, and slicing produced list items instead of substrings.
Add _content_to_text() helper that safely converts any content format
to plain text:
- str → returned as-is
- None → empty string
- list (multimodal) → text parts joined, images replaced with [image]
- dict/other → JSON serialization with str() fallback
This ensures multimodal conversations compress correctly instead of
producing garbled summaries.
Inspired by PR #776 by @kshitijk4poor.
The summary message was always injected as 'user' role, which causes
consecutive user messages when the last preserved head message is also
'user'. Some APIs reject this (400 error), and it produces malformed
training data.
Fix: check the role of the last head message and pick the opposite role
for the summary — 'user' after assistant/tool, 'assistant' after user.
Based on PR #328 by johnh4098. Closes#328.
The OpenAI API returns content: null on assistant messages that only
contain tool calls. msg.get('content', '') returns None (not '') when
the key exists with value None, causing TypeError on len() and string
concatenation in _generate_summary and compress.
Fix: msg.get('content') or '' — handles both missing keys and None.
Tests from PR #216 (@Farukest). Fix also in PR #215 (@cutepawss).
Both PRs had stale branches and couldn't be merged directly.
Closes#211
Cover model_tools, toolset_distributions, context_compressor,
prompt_caching, cronjob_tools, session_search, process_registry,
and cron/scheduler with 127 new test cases.
teknium1
Bryan Young
0xbyt4