Pasted prompts (test cases, structured asks, JSON dumps) currently render
through the same markdown pipeline as assistant output, so '#'/'-'/'**'
characters are processed and long prompts dominate the scrollback.
- New UserMessageContent.vue: plain-text rendering (white-space: pre-wrap
preserves user-typed newlines and indentation), with auto-collapse beyond
8 lines and a "Show more (N more lines) / Show less" toggle. Soft mask
gradient at the collapse boundary instead of a hard cut.
- MessageBubble.vue: route role==='user' messages through the new component;
assistant messages keep the existing markdown pipeline unchanged.
- Add chat.expandLines / chat.collapse i18n keys (zh + en).
Verified end-to-end in browser preview: 15-line content collapses to 8,
toggle expands to full 15 with "Show less" label, raw '#' / '**' / '`' chars
shown literally with no <strong>/<h1>/<li> tags emitted.
- db/migration/mysql: replace ADD COLUMN/CREATE INDEX IF NOT EXISTS with
idempotent checks via information_schema (MySQL 8.0 <8.0.29 and some
forks don't support IF NOT EXISTS for ADD COLUMN). Affects V2/V4/V5/V7
/V8/V9/V11/V12/V13/V14. Fix: gitee#IIYHLJ.
- application-mysql.yml: add createDatabaseIfNotExist=true so MySQL
Connector/J auto-creates the schema on first connection (requires
CREATE privilege — documented fallback for restricted accounts).
- llm/OllamaAutoDiscoveryRunner: rewrite seed tag when fuzzy-matching,
prefer exact tag for default; skip models without tool support when
auto-activating a default (prevents the phantom ':latest' trap when
users pulled a specific size).
- agent/graph/NodeStreamingChatHelper: detect 'does not support tools'
and 'model not found' errors from Ollama and emit actionable Chinese
prompts guiding users to qwen3 / qwen2.5:7b+ / llama3.1:8b+ etc.
- ui/MessageBubble + types/chatError: surface the backend's actionable
rawMessage in the failed-message card instead of a generic '未知错误';
strip redundant prefixes (Bad request: / [错误] / LLM 调用失败:) since
the title already conveys the category.
Full-stack AI assistant built on Spring AI Alibaba.
Features: ReAct Agent, Plan-and-Execute, MCP Protocol, Multi-Model, Multi-Channel.
Apache-2.0 License
