Commit Graph
25 Commits
Author SHA1 Message Date
Guoyu Su de44fddf29 feat(ai): add Pi Coding Agent provider 2026-07-29 02:10:06 +08:00
Guoyu Su c7e7b7c9d9 feat(ai): unify model discovery and effort handling 2026-07-28 21:37:55 +08:00
Abeautifulsnow cb9d0f7cbf fix(ai): harden write SQL confirmation flow 2026-07-28 11:56:23 +08:00
wbean 98d1ab3ab3 feat(sidebar): add persistent table filters 2026-07-25 08:46:12 +08:00
Abeautifulsnow 9253203d99 feat(ai): make agent turn limit configurable 2026-07-23 13:57:06 +08:00
Guoyu Su d3947d246c feat(ai): add Claude Code CLI provider 2026-07-17 01:17:06 +08:00
t8y2 5a666b1f48 fix(ai): improve assistant execution and MCP settings 2026-07-10 14:31:08 +08:00
lexmin0412 ac4b98c97c feat(ai): add general action mode 2026-07-08 19:31:19 +08:00
Abeautifulsnow ffc0279352 fix(ai): make stop button actually cancel the agent stream
The stop button called aiCancelStream -> notify_one(), but the four
stream_*_with_tools SSE loops only `break`ed and returned Ok(token_usage)
when cancelled. run_agent_loop treated that as a normal completed turn and
kept going (often into contract-repair or the next turn), so isGenerating
stayed true and a single click did not stop the agent.

Return Err(AGENT_CANCELLED_ERROR) from the cancel branch so the existing
Err-cancel match arm sets loop_exit = Cancelled and stops the loop cleanly,
preserving whatever was streamed so far.

Additional:
- Promote AGENT_CANCELLED_ERROR to a shared `pub const` in ai.rs; agent_loop
  now references ai::AGENT_CANCELLED_ERROR.
- Check cancellation before executing requested tools, so a stop landing
  between stream-end and tool execution is honored.
- Wire cancellation into the text-only fallback (previously `_cancelled`,
  ignored) via tokio::select! racing ai::complete against cancelled.notified().

Known limitation left: in-flight tool execution (e.g. execute_query) is
still not interruptible mid-call.
2026-07-08 18:44:13 +08:00
Abeautifulsnow 8539011f25 feat(ai): split Ask/Agent action menus with task-oriented Agent actions
* feat(ai): add task-oriented Agent actions with per-action contract

Introduce three Agent-native actions — query, exploreSchema,
executeAndExplain — so Agent mode surfaces task-oriented operations
instead of reusing Ask's SQL-producing action set.

- ai.ts: extend AiAction with the new actions; add ASK_ACTIONS /
  AGENT_ACTIONS and defaultActionForMode / isValidActionForMode
  helpers; raise maxTokens for the explanatory task actions.
- aiSkills.ts: add skill definitions (zh/en) for the three actions.
- aiAgentPlan.ts: task actions no longer emit a misleading
  "unsupported_action" execute step; they execute via the
  execute_query tool events, not the legacy client-side path.
- agent_loop.rs: per-action task-contract rules in both the prompt
  augmentation and repair paths (query -> execute & answer from real
  data; exploreSchema -> list_tables/get_columns; executeAndExplain
  -> run current SQL & explain).
- i18n (en/zh-CN/zh-TW): new action labels, placeholders, a
  generateNoExec label for Agent mode, and a task-oriented agent
  modeHint.

es/it/ja/pt-BR have no `ai` section and fall back to `en`, matching
existing coverage.

* feat(ai): split Ask/Agent action menus with mode-aware defaults

Wire the new Agent task actions into the assistant UI so each mode
shows a distinct, intent-matching action set.

- actionButtons is now a computed returning Ask or Agent buttons
  based on assistantMode. Agent menu: query / exploreSchema /
  executeAndExplain / generate (labeled "生成但不执行" via
  generateNoExec). Ask menu is unchanged.
- Switching mode lands on that mode's default (Ask -> generate,
  Agent -> query); the shared `generate` is not carried across
  because its label/semantics differ per mode. Vector DBs stay on
  `generate` since their action menu is hidden and they lack SQL
  tools (no execute_query contract).
- External Ask-style triggers (Fix with AI, Explain history) switch
  to Ask mode when invoked from Agent mode so the action is valid
  and the menu reflects what runs.
- Reset the active action to the mode default after each send.

* test(ai): cover Agent task-action contract and mode/action mapping

Lock in the deterministic parts of the Ask/Agent split so only the
LLM-behavior criteria need manual verification.

Backend (agent_loop.rs):
- query contract instructs the LLM to call execute_query and is not
  treated as a SQL-producing action.
- exploreSchema contract points to list_tables/get_columns and says
  not to execute data queries.
- executeAndExplain contract tells the LLM to run the current SQL.
- task actions do not require a SQL deliverable (a conclusion without
  a fenced SQL block still satisfies the contract).
- query repair prompt also targets execute_query.

Frontend (aiActions.spec.ts):
- defaultActionForMode: Ask -> generate, Agent -> query (not generate).
- isValidActionForMode: generate valid in both; Ask-only actions
  rejected in Agent mode and vice versa.
- ASK_ACTIONS / AGENT_ACTIONS composition (Agent menu starts with
  query and still offers generate).

* fix(ai): correct action menu on mode-switched triggers and i18n gaps

Issues found during review of the Ask/Agent action split:

- [#I01] triggerAction (Fix with AI / Explain history) invoked from
  Agent mode switched to Ask and set the action, but the mode-switch
  watch then reset activeAction to the Ask default ("generate"),
  overwriting the action just set — so the menu showed "Generate SQL"
  during a fix. Add a suppressModeActionReset flag so programmatic
  mode switches don't clobber the explicitly-set action.
- [#C01] Remove dead `unsupported_action` reason: buildAiAgentPlan no
  longer produces it, so drop the type variant and the unreachable
  skippedTitleKey case.
- [#I02] es/it/ja/pt-BR were missing the new Agent action keys
  (query/exploreSchema/executeAndExplain/generateNoExec) and their
  placeholders, causing English fallback in the Agent menu. Add the
  translations to match each locale's existing style.

* test(ai): align app-tests with task-action split

- aiSkills: add query/exploreSchema/executeAndExplain to the expected
  action set; broaden the id check (new ids are not _sql-suffixed) and
  relax the userInstruction assertion (schema inspection need not mention SQL).
- aiAgentPlan: drop the unsupported_action skipped step for non-generate
  actions (#C01 removed it from the plan and the reason union); add coverage
  for task-oriented Agent actions not driving client-side execution.

* test(ai): pin locale in dialect prompt spec

buildSystemPrompt selects zh/en copy via currentLocale(), which reflects the
host navigator.language. The spec asserts English strings, so it failed on
zh-CN machines (e.g. Windows with a Chinese system locale) while passing on
CI's en-US runners. Pin the locale to en in beforeAll so the assertions are
deterministic regardless of the host OS locale.
2026-07-06 14:41:39 +08:00
Abeautifulsnow e7dffeca37 fix(ai): tool call status cards, table overflow, streaming TextDelta
* fix(ai): merge tool call status cards

* fix(ai): constrain markdown table overflow

* fix(ai): restore streaming of answer text via TextDelta events

The on_chunk closure was missing live AgentEvent::TextDelta emission for text content, causing the AI answer text to appear all at once after the turn completed. Reasoning deltas were unaffected.

Root cause: commit c30033628 rewrote the on_chunk closure and accidentally dropped the TextDelta emit line while keeping ReasoningDelta intact.

Fix: restore TextDelta emit in on_chunk for incremental streaming, and remove the post-turn full-TextDelta workaround which would duplicate content.

* test(ai): extract chunk_to_events and add streaming event tests

Extract the event-generation logic from the on_chunk closure into a pure function chunk_to_events() to make it testable, and add 6 unit tests covering all chunk content combinations: text-only, reasoning-only, mixed, empty, and edge cases.

This ensures a regression like the one fixed in the previous commit (where TextDelta emission was dropped while ReasoningDelta was kept) would be caught by tests.
2026-07-02 18:49:50 +08:00
t8y2 3e01840825 fix(ai): remove temperature from AI requests 2026-07-02 17:58:35 +08:00
lexmin0412 bc409cffc0 feat(ai): add vector DB assistant tools 2026-06-29 11:46:41 +08:00
Abeautifulsnow 5f2b24d700 fix(ai): enforce SQL task contracts structurally instead of keyword heuristics
* fix: enforce agent task contracts

* fix(ai): enforce SQL task contracts structurally
2026-06-26 13:18:49 +08:00
Abeautifulsnow ebfc50e4ff fix(agent-loop): preserve output on exhaustion, interruption, and cancellation 2026-06-24 13:27:23 +08:00
Oleksandr Liakhevych 4f5d09aaa8 feat(ai): add Codex CLI as a no-API-key AI provider for Desktop
* codex cli provider

* fixes

* mcp check

* reasoning

* simplify

* minor fixes
2026-06-19 08:51:10 +08:00
t8y2 22b8ba17bb fix(schema): handle view DDL object types 2026-06-17 19:29:24 +08:00
t8y2 c57e18bf3e fix: resolve clippy warnings and missing struct fields in tests 2026-06-16 00:55:32 +08:00
Abeautifulsnow c300336281 feat(ai): context window management and token usage tracking
* @
feat(ai): add conversation context management and token usage tracking (Phase 4)

## Background
Phase 4 of AI agent loop upgrade: token usage extraction from LLM responses,
cost estimation display, and automatic context window management (summarization
when approaching limits).

## Changes

### Backend (Rust)
- New token_usage::TokenUsage — cross-turn token accumulation
- New agent_loop::maybe_compact — proactive context compaction: token estimation
  → cut-point selection → LLM summarization → fallback summary
  → tool-pair integrity protection → drain/insert
- New agent_loop::context_window_for_model — auto-detect context window by model
- New agent_loop::is_context_length_error — detect upstream context-length errors
- New agent_loop::compact_tool_result_for_context — JSON/text sampling for large results
- Modified agent_loop::run_agent_loop — pre-turn compaction check, retry on context error
- Modified agent_events::AgentEnd — split total_tokens into input_tokens/output_tokens
- New agent_events::ContextCompacted — compaction event with metrics
- New AiConfig.context_window — user-configurable context window size
- New AiChatMessage.kind — context summary message marker
- Modified stream_with_tools & 3 provider stream functions — extract TokenUsage
  - Claude: message_start(input) + message_delta(output)
  - OpenAI: stream_options { include_usage } → final usage chunk
  - Gemini: usageMetadata per chunk, keep last

### Frontend (TypeScript/Vue)
- AiAssistant.vue: token + cost display row, estimateCost() with 7 model families,
  contextCompacted UI step, pendingCompaction deferred apply,
  messagesForAgentHistory post-compaction history reconstruction
- EditorSettingsDialog.vue: contextWindow input (min=1000, auto-detect)
- settingsStore.ts: AiConfig.contextWindow field
- tauri.ts: AgentEvent type updates, AiChatMessage.kind
- i18n: 6 new keys in en.ts and zh-CN.ts

## Fixed Issues
- messages[0] dropped from LLM context after compaction
- estimate_text_tokens hard threshold causing 2.8x estimate jump
- context_compacted event field semantics mismatch with frontend insert position
- validate_summary English-only keywords causing fallback on non-English LLMs
- Stale agentTokens after conversation switch
@

* remove cost computation logic
2026-06-15 18:55:22 +08:00
Abeautifulsnow d845a318c6 feat(ai-agent): Phase 3 — explain_query tool, parallel/sequential execution, DB gating (#1187)
- Add explain_query tool with structured EXPLAIN result, gated on supports_explain_plan()
- Add supports_sql_query() to gate execute_query/get_sample_data for non-SQL DBs (Redis, ES, MongoDB, etc.)
- Split agent loop tool dispatch: execute_query runs sequentially, all others run in parallel via join_all
- Wire explain_query result button to ExplainPlanViewer in AiAssistant + App.vue
- Fix O(n²) agentSteps rebuild: incremental O(1) push per event during streaming
- finally block falls back to full rebuild only when streaming push did not occur
2026-06-15 13:14:59 +08:00
t8y2 30afcb8e69 fix(sidebar): page large table groups 2026-06-13 13:40:36 +08:00
runstone 100124da3e feat(ai): Phase 2 SQL 风险分类 + Agent 模式工具调用结果渲染
后端:
  - 新增 sql_risk.rs:基于 sqlparser AST 的 SQL 风险分类(ReadOnly/Write/Ddl/Transaction)
  - agent_tools.rs:新增 execute_query 和 get_sample_data 工具,写操作/DDL 被风险分类阻止
  - agent_loop.rs:支持 is_agent_mode 参数,Agent 模式下暴露全部工具,Ask 模式仅暴露只读工具
  - agent_loop/web/tauri:mode 参数全链路传递(前端→HTTP→Tauri→Rust)

  前端:
  - AiAgentStepItem 接口扩展:toolName/toolArgs/toolResult/isError 字段
  - AiAssistant.vue:工具调用结果实时+最终渲染,SQL 查询结果/错误信息展示
  - ai.ts/http.ts/tauri.ts:mode 参数透传到后端
2026-06-12 17:42:23 +08:00
runstone 2d75667b9a feat(ai): upgrade agent loop tool calling to true SSE streaming
Move tool calling from non-streaming (complete) API calls to real
streaming SSE, so text, reasoning, and tool call arguments all arrive
incrementally — users see the AI think and act in real time.

- Extract ~370 lines of non-streaming tool-call functions from
  agent_loop.rs (call_with_tools, call_openai_with_tools,
  call_claude_with_tools, call_gemini_with_tools) and replace with
  a single ai::stream_with_tools() dispatch call.

- Add streaming-with-tools infrastructure to ai.rs (~550 lines):
  - StreamToolEvent enum: Chunk, ToolCallStart, ToolCallDelta,
    ToolCallComplete — provider-agnostic, feeds into the
    StreamingToolCallAccumulator
  - stream_claude_with_tools(): parse SSE content_block_start/delta/
    stop events, incremental input_json_delta for tool arguments
  - stream_openai_with_tools(): parse SSE delta.tool_calls with
    incremental function.arguments
  - stream_gemini_with_tools(): parse SSE functionCall (Gemini
    sends complete objects, not deltas — emit as one chunk)
  - Cancellation support via tokio::select! in every streaming loop
  - Extended timeout for reasoning models (600s vs 120s)

- StreamingToolCallAccumulator: collect partial tool call fragments
  from streaming deltas, then deserialize into complete ToolCall
  objects in index order once the stream ends.
2026-06-12 11:43:09 +08:00
runstone 9939e3191f fix bug 2026-06-12 10:31:15 +08:00
runstone 9ab41795d6 @
feat(ai): add agent loop with tool calling, fix connection routing and Gemini compatibility

## 背景说明
将 dbx AI 助手从单次 SQL 文本生成器升级为具备 tool calling 的数据库 Agent。
Phase 1 实现 Agent Loop 框架 + 只读工具(list_tables、get_columns)。
参考:Pi agent-core,.trellis/tasks/06-11-feat-ai-agent-loop-tool-calling-upgrade

## 修改内容
- 新增 agent_loop.rs:Agent Loop 核心,支持 OpenAI/Claude/Gemini Provider 的 tool calling,最大 10 轮,Ollama 自动降级为 text-only
- 新增 agent_tools.rs:read_only_tools (list_tables, get_columns) 的工具定义与执行器
- 新增 agent_events.rs:AgentEvent/ToolCall/ToolResult/ToolDefinition 类型定义
- 修改 ai.rs:AiMessage 新增 tool_call_id 字段
- 修改 lib.rs:注册 agent_events、agent_loop、agent_tools 模块
- 修改 routes/ai.rs & commands/ai.rs:新增 ai_agent_stream SSE 端点
- 修改 tauri.ts & http.ts:新增 AgentEvent 类型与 aiAgentStream 函数
- 修改 api.ts:注册 aiAgentStream 转发
- 修改 ai.ts:新增 runAgentStream,AiContext 增加 connectionId 字段
- 修改 AiAssistant.vue:接入 runAgentStream,解析 AgentEvent 渲染工具调用步骤
- 修改 en.ts / zh-CN.ts:新增 agentSteps 国际化文案

## 修复的问题
- [#I01] connectionName 误传为 connectionId → add connectionId to AiContext
- [#I02] agent loop 取消操作无效 → add cancel checks before each turn
- [#C01] TODO 缺少 issue 引用 → add PRD reference to TODO
- [#C02] stream_with_tools 命名不准确 → add clarifying doc comment
- [#C03] Gemini functionResponse.name 解析错误 → fix tool_call_id format and extraction

## 测试建议
- execute_get_columns:合法表名/空表名/SQL 注入字符拒绝
- call_openai_with_tools:空 choices/空 tool_calls/非 JSON arguments
- call_gemini_with_tools:空 candidates/parts 无 functionCall
- runAgentStream:有效 connectionId 正常调用
@
2026-06-11 18:27:24 +08:00