- trader/alpaca/: Full Trader interface implementation for Alpaca
- Paper/Live trading support (market orders, stop/limit)
- GetBalance, GetPositions, GetMarketPrice via Alpaca API
- Fractional share support (4 decimal places)
- Commission-free trading
- Agent trade routing: stock symbols (AAPL, TSLA) → Alpaca
- isStockSymbol() heuristic to distinguish crypto vs stock
- execute_trade tool updated for stock buy/sell semantics
- get_market_price works for both crypto and stocks
- TraderManager + API: Alpaca registered as exchange type
- Factory case in auto_trader.go
- Config mapping in trader_manager.go
- Temp trader creation in handler_trader.go for balance query
- Frontend: PositionsPanel distinguishes stock vs crypto
- US flag emoji for stock positions
- Dollar prefix for stock PnL/prices
- 'Shares' label instead of 'Qty' for stocks
- System prompts updated for stock trading capabilities
- Guard GridCount-1 division by zero in grid spacing calculation (both grid.go and grid_levels.go)
- Rate-limit /wallet/validate and /wallet/generate endpoints (prevent DoS on key generation)
- Wrap JSON.parse(localStorage) in try-catch in AuthContext (corrupted data → graceful re-login)
- Wrap handleJSONResponse JSON.parse in try-catch with descriptive error
- Add HTTP status code checks for Lighter GetActiveOrders and sendTx
- Replace deprecated strings.Title with cases.Title (golang.org/x/text)
- Reuse HTTP client in checkClaw402Health (was creating new client per call)
- Propagate request context through MCP client (Request.Ctx field)
— Client disconnects now cancel in-flight LLM API calls (both streaming and non-streaming)
— Prevents wasted LLM tokens when user navigates away mid-response
- proxyBinance: use http.NewRequestWithContext for context-aware upstream calls
— Client disconnects cancel Binance proxy requests
— Distinguishes client cancellation from upstream failures
- Fix SSE parse bug in AgentChatPage: catch block was swallowing error events
— throw new Error(data) for 'error' events was caught by the same try/catch
— Now parse JSON separately, then handle events outside try/catch
- Add io.LimitReader to Hyperliquid coins.go JSON decoder (4MB limit)
- Use safe.ReadAllLimited in batch ticker handler for consistency
- Sanitize URL validation error in handler_ai_model.go (was leaking raw error)
- Cache agent tool definitions (built once, reused per message)
- Sort trade history by exit time for consistent ordering
- Fix thinkAndActStream: emit delta event for non-tool responses (was silent)
- Add fallback to streaming on first LLM call failure
- Add batch ticker endpoint /api/agent/tickers (3 API calls → 1)
- Update MarketTicker to use batch endpoint, remove unused state
- Warn loudly when JWT_SECRET uses default value
- Fix 华为 mapping (was incorrectly mapped to Tencent)
- Replace ioutil.ReadAll with safe.ReadAllLimited in nofxos client
- Remove unused variable in hyperliquid trader_account
- Wrap CoinAnk WS readers with safe.GoNamed for panic recovery
- Use 100dvh for mobile viewport in AgentChatPage
- console.log → console.warn for auth events
- handler_klines.go: pass c.Request.Context() to all external API calls
instead of context.Background(). Client disconnects now cancel upstream
requests to CoinAnk, Alpaca, TwelveData, Hyperliquid.
- Extract renderMessageContent + renderInline into
components/agent/MessageRenderer.tsx (187 lines).
AgentChatPage.tsx reduced from 1009 → 825 lines.
- / now defaults to AgentChatPage (NOFXi's main interface)
- Agent page accessible without login
- LandingPage only shown at /landing or for non-agent pages when not logged in
- Add chatHistory store (in-memory, per user, last 20 messages)
- Agent now passes full conversation context to LLM via CallWithRequest
- Records both user messages and assistant responses
- Add /clear command to reset conversation history
- Add 'Clear' quick action button in frontend
- Supports natural multi-turn conversations (follow-up questions, context)
- Rewrite AgentChatPage as primary interface with Perplexity-style layout
- Add right sidebar with Market Ticker, Positions, and Trader Status panels
- Sidebar is collapsible and responsive (auto-hides on mobile)
- Each sidebar section independently collapsible
- Chat area: centered 720px max-width with smooth streaming effect
- Simple markdown rendering (bold, code blocks, inline code)
- Quick action chips redesigned as pill buttons with hover effects
- Input upgraded to auto-resizing textarea
- New components: MarketTicker, PositionsPanel, TraderStatusPanel
- Dark theme consistent with NOFXi brand colors
- Real-time data via SWR for positions and trader status
Key changes:
- Agent API routes (/api/agent/*) registered directly on NOFX's :8080 server
- No more separate :8900 port — everything on :8080
- AgentChatPage.tsx added to React frontend
- Agent tab (🤖 Agent) added to navigation bar, set as DEFAULT page
- Branding: NOFX → NOFXi everywhere (title, header, branding.ts, i18n)
- Default landing page is now Agent chat, not competition
This is THE change: there is no more 'NOFX' vs 'NOFXi'.
Users open localhost:8080, they see NOFXi.
Agent chat is the first thing they see.
All other pages (Traders, Dashboard, Strategy, Data) are still there.
One binary. One port. One product. NOFXi.
Critical fixes:
1. Agent now uses NOFX's MCP client for AI calls (real models, not placeholder)
- Gets AI client from first configured trader's MCP config
- Added AutoTrader.GetMCPClient() export
2. /analyze uses REAL market data (market.Get → EMA/MACD/RSI/BB/OI/funding)
then sends to AI — no more hallucinated prices
3. AI chat enriches prompts with live market data when user mentions a coin
4. Fallback: if AI unavailable, shows raw formatted market data (still useful)
Router improvements:
- Better natural language detection for Chinese
- '该不该买' '走势' '趋势' '行情' → analyze intent
- '多少钱' '赚了' '亏了' → query intent
- Fewer messages falling through to generic chat
Web UI:
- Endpoints updated to /api/agent/* namespace
- nofxi.html served at agent root (localhost:8900)
Result: AI analysis now shows real BTC price, real RSI, real EMA — not fiction.
This is the key architectural change: NOFXi is no longer a separate
sub-project in nofxi/, but a first-class module in agent/ that sits
on top of NOFX's existing engine.
agent/ package:
- agent.go: Core orchestrator, directly uses NOFX's TraderManager,
Store, and Market packages. No wrapper/bridge needed.
- brain.go: Proactive intelligence (news scan, market briefs, signal handling)
- sentinel.go: Market anomaly detection (price breakout, volume spike, funding rate)
- scheduler.go: Daily reports, position risk checks
- router.go: Intent routing for natural language (中/英 bilingual)
- i18n.go: Full Chinese/English message catalog
- web.go: Agent REST API on :8900 (chat, klines, ticker)
main.go changes:
- Banner: NOFX → NOFXi
- Agent auto-starts with NOFX (sentinel + brain + scheduler + web)
- Zero breaking changes to existing NOFX functionality
Key difference from old nofxi/:
- Agent reads LIVE data from TraderManager (positions, balances, status)
- Uses market.Get() for full technical indicators (EMA/MACD/RSI/BB)
- No duplicate code — kernel, trader, store all used directly
- Old nofxi/ sub-project will be removed once migration is verified
Architecture:
NOFX (engine) → kernel + trader + market + store + mcp + telegram
NOFXi (brain) → agent/ package → uses all of the above
sonner's toast.promise() returns a toast ID (not a Promise), so
await resolves immediately and subsequent data refresh fetches stale
data. Users had to manually reload to see changes.
Fixed across AITradersPage, SettingsPage, and TraderConfigModal.
CoinSourceEditor constructs keys as `${value}Desc` where value='oi_top',
expecting 'oi_topDesc' but the translation key was 'oiTopDesc' (camelCase).
This caused ts(undefined, lang) → "Cannot read properties of undefined".
- Add missing configResponse.ok check in handleCreateStrategy to prevent
rendering with invalid config data when API fails
- Remove deleted benefit3 translation key reference from LoginRequiredOverlay
The .gitignore had a Python-inherited `lib/` rule that blocked the
entire web/src/lib/api/ directory from being tracked. The original
api.ts was a file (not matched), but the split created a directory
inside lib/ which was ignored. Remove the `lib/` gitignore rule and
add the api module split files that were missing from the previous commit.
Remove the entire AI Debate Arena module (~5,300 lines) to simplify
the codebase. This removes the multi-AI debate trading decision system
including backend engine, API handlers, database store, frontend page,
navigation, translations, and documentation references.
* feat(telegram): add AI agent bot with streaming and account context
- Add Telegram bot with long-polling and AI agent loop (api_call tool)
- SSE streaming with real-time message editing and ⏳ placeholder
- Account state injection at conversation start (models, exchanges,
strategies, traders, per-trader PnL and statistics)
- Lane semaphore per chat serializes concurrent messages (60s timeout)
- Idle timeout watchdog (60s) prevents hung streaming connections
- Look-ahead buffer prevents partial <api_call> tag leaking to user
- Fix PUT /strategies/:id to merge config (read-then-merge pattern)
- Add route registry with full API schema for LLM documentation
- Add TelegramConfig store and Web UI config modal
- Add GetAnyEnabled to AIModel store for bot LLM client selection
* fix(telegram): eliminate narration, add full-setup workflow and tests
- Rewrite NO NARRATION rule: response is EITHER api_call tag alone OR
final text reply — no text before api_call under any circumstances
- Ban all narration patterns: 现在我将/好的/正在/I will/Let me etc.
- Add 'create strategy + create trader + start' full setup workflow
- Add 12 automated tests covering:
- No narration leaking to user (5 narration variants tested)
- api_call tag never leaks to user
- Full setup workflow: POST strategy → verify → POST trader → start
- Start existing trader workflow
- Max iterations safety, tag stripping, parser edge cases
* refactor(agent): replace XML api_call with native function calling
Migrate the Telegram bot agent from an XML tag hack (<api_call>) to
OpenAI-native function calling via CallWithRequestFull.
Key changes:
- mcp/interface.go: add parseMCPResponseFull to clientHooks interface
- mcp/client.go: route callWithRequestFull through hooks for overridability
- mcp/claude_client.go: override parseMCPResponseFull for Claude response
format (tool_use blocks instead of choices[].message.tool_calls)
- telegram/agent/agent.go: rewrite Run() to use CallWithRequestFull;
define api_request tool with JSON Schema; implement tool-call loop
with role="tool" result messages; remove XML parsing entirely
- telegram/agent/apicall.go: remove parseAPICall (dead code)
- telegram/agent/prompt.go: simplify — remove XML format instructions,
replace with concise api_request tool usage instructions
- telegram/agent/agent_test.go: rebuild all tests using LLMResponse
objects; add TestNarrationStructurallyImpossible, TestOnChunkCalledWithFinalReply,
TestToolCallIDPropagated; remove XML-specific tests
Architecture advantage: with native function calling, the LLM returns
EITHER ToolCalls OR Content — never both. Narration is now structurally
impossible at the protocol level, not just enforced by prompt rules.
All 11 agent tests pass. mcp package tests pass.
* refactor(mcp): route buildRequestBodyFromRequest through hooks + full Anthropic format
Problem: callWithRequest/Full/Stream all called client.buildRequestBodyFromRequest
directly (not via hooks), so ClaudeClient could never override it. This meant
tool calling sent OpenAI format to Anthropic (wrong field names, wrong roles).
Changes:
mcp/interface.go
- Add buildRequestBodyFromRequest(*Request) map[string]any to clientHooks
- Improve comments: document what each hook group does and why
mcp/client.go
- All three paths (callWithRequest, callWithRequestFull, CallWithRequestStream)
now call client.hooks.buildRequestBodyFromRequest — ClaudeClient picks up
mcp/claude_client.go
- Full rewrite with format comparison table in package doc
- buildRequestBodyFromRequest: produces correct Anthropic wire format
* system prompt → top-level "system" field
* tools: parameters → input_schema, no "type:function" wrapper
* tool_choice "auto" → {"type":"auto"} object
* assistant tool calls → content[{type:tool_use, id, name, input}]
* role=tool results → role=user content[{type:tool_result,...}]
* consecutive tool results merged into single user turn
- convertMessagesToAnthropic: handles all three message types
- parseMCPResponseFull: extracts text + tool_use blocks
- parseMCPResponse: delegates to parseMCPResponseFull
All mcp and agent tests pass.
* fix(telegram): fix claude client dispatch + strategy creation workflow
- telegram/bot.go: clientForProvider now returns NewClaudeClient() for
'claude' provider (was incorrectly falling back to DeepSeekClient which
uses OpenAI wire format, breaking Anthropic API calls)
- api/server.go: fix scan_interval_minutes schema default (3, not 60);
POST /api/strategies now clearly states config is OPTIONAL with complete
working defaults; POST /api/traders removes redundant GET workflow note
- telegram/agent/prompt.go: simplify strategy creation — just POST {name}
without config (backend applies full working defaults automatically);
only include config when user requests custom settings
* test(mcp): add ClaudeClient wire format tests
Tests cover all Anthropic-specific format conversions:
- system prompt lifted to top-level field
- tools use input_schema (not parameters)
- tool_choice is object {type:auto} not string
- assistant tool calls → content[{type:tool_use}]
- consecutive tool results merged into single user turn
- parseMCPResponseFull: text, tool_use, and error cases
- x-api-key header (not Authorization: Bearer)
- /messages endpoint URL
* fix(telegram): clientForProvider returns correct client for all 7 providers
Previously qwen/kimi/grok/gemini all fell back to DeepSeekClient.
Each provider now gets its own dedicated client with correct default
base URL and model. All 7 providers now fully supported:
openai, deepseek, claude, qwen, kimi, grok, gemini
* fix(telegram): newLLMClient uses bound user's model, not any user's model
GetAnyEnabled() searched across all users in DB — if user B has an
enabled model, bot could use their API key while acting as user A.
Now uses GetDefault(botUserID) which only looks up the bound user's
enabled model, matching the same user scope as all API calls.
* fix(auth): single-user deployment by default, no open registration
Registration logic redesigned:
- Empty DB (first-time setup): registration always open, no config needed
- After first user exists: registration closed by default
- Multi-user opt-in: set REGISTRATION_ENABLED=true + MAX_USERS=N in .env
Config defaults changed:
- RegistrationEnabled: true → false (closed after first user)
- MaxUsers: 10 → 1 (single-user deployment default)
This eliminates the confusion of multiple users appearing in a personal
deployment where Telegram is bound to a single admin account.
* feat(solo): beginner-friendly onboarding — smart setup guide + direct config commands
start.sh:
- Interactive Telegram Bot Token prompt on first run
- Token format validation (must match 12345:ABC... pattern)
- Friendly step-by-step startup instructions after launch
telegram/bot.go:
- /start now shows context-aware setup guide based on actual config state:
- No AI model → explains how to configure, lists all providers
- AI model OK but no exchange → guides to configure exchange via chat
- All configured → full capabilities welcome message
- New: direct setup commands ('配置 deepseek sk-xxx') bypass LLM entirely
so AI model can be configured even before any model exists (bootstrap fix)
- All messages now in Chinese (匹配用户语言)
telegram/agent/prompt.go:
- Added first-time setup detection section
- Agent told to never ask user to visit web UI — everything via chat
* feat(i18n): bilingual EN/ZH setup guide with language selection
store/telegram_config.go:
- Add Language field to TelegramConfig (persisted in DB)
- Add SetLanguage(lang) and GetLanguage() methods
- Default language: English (en)
telegram/bot.go:
- First /start triggers language selection (1=English, 2=中文)
- /lang command to change language at any time
- awaitingLang state machine handles language choice before any other input
- buildSetupGuide() now fully bilingual (EN/ZH), context-aware:
Step 1: configure AI model (no model yet)
Step 2: configure exchange (model OK, no exchange)
Ready: show full capabilities
- tryHandleSetupCommand() bilingual: 'configure/配置 <provider> <key>'
- helpMessage(lang) fully bilingual
- All error/status messages bilingual
Default: English. isLangDefault() detects whether user has explicitly
chosen a language vs falling back to the 'en' default.
* fix(telegram): use Markdown rendering + simplify language selection condition
- sendMarkdownMsg() helper: sends with ParseMode=Markdown, falls back to plain text
- All formatted messages (langSelectionMsg, buildSetupGuide, helpMessage) now render
bold text and code blocks correctly in Telegram
- Simplify /start language check: isLangDefault(st) alone is sufficient
(lang == 'en' && isLangDefault was redundant — GetLanguage returns 'en' when empty)
* fix(start.sh): translate all user-facing text to English
Entire script was in Chinese. Now English-first throughout:
- startup banner, prompts, success/error messages
- setup_telegram(): English instructions and validation messages
- start(): English next-steps after launch
- stop/restart/clean/update/regenerate-keys/show_help: all English
* fix(telegram): remove 'default' user fallback — resolve user dynamically
- botUserID no longer captured once at startup (was 'default' if no user yet)
- resolveBotUser() reads first registered user from DB on demand:
* called on every /start (handles: registered after bot launch)
* called before every AI message (handles mid-session registration)
- If no user registered: clear English error 'No account found. Please register on the web UI first'
- start.sh: fix set_env_var appending without newline (token was concatenated to prev line)
* refactor(telegram): clean onboarding — web UI for setup, Telegram for operations
- /start shows clean status: 'setup required → open web UI' or 'ready → examples'
- Removed tryHandleSetupCommand (no more CLI-style 'configure deepseek sk-xxx')
- Removed automatic language selection on /start (use /lang anytime instead)
- newLLMClient returns nil when no model → clear guard, not fallback
- statusMsg() replaces buildSetupGuide(): two states only (missing config / ready)
- Bot is now purely an operations interface; config lives in the web UI
* refactor: single-user web-based setup — replace env config with Settings UI
Move from multi-user env-var config to single-user web-first architecture:
- Add SetupPage for first-time initialization (replaces /register)
- Add SettingsPage for AI models, exchanges, Telegram, and password management
- Enrich all API route schemas with exact ID usage documentation
- Add PUT /user/password endpoint for in-app password changes
- Remove REGISTRATION_ENABLED, MAX_USERS, TELEGRAM_BOT_TOKEN from env config
- Simplify LoginPage design, remove admin mode and registration links
- Telegram bot now resolves user email for identity display
- start.sh no longer runs interactive Telegram setup
* feat: add blockRun (x402 USDC) support to all AI model consumers
- telegram/bot.go: add blockrun-base, blockrun-sol, minimax to
clientForProvider; fix newLLMClient to prefer TelegramConfig.ModelID
over GetDefault; log USDC payment provider usage
- debate/engine.go: add blockrun-base, blockrun-sol to InitializeClients
- api/strategy.go: add blockrun-base, blockrun-sol to runRealAITest
- backtest/ai_client.go: add blockrun-base, blockrun-sol to configureMCPClient
* feat: add Claw402 (claw402.ai) x402 USDC payment provider
Add Claw402Client for claw402.ai's x402 micropayment gateway (Base USDC).
Supports 15+ AI models (GPT-5.4, Claude Opus, DeepSeek, Qwen, Grok, etc.)
with per-model endpoint routing.
- mcp/claw402.go: new client with model→endpoint mapping, x402 v2 payment flow
- mcp/blockrun_base.go: extract shared signX402Payment() for reuse
- Register "claw402" provider in all 6 consumer switch statements:
api/server.go, api/strategy.go, trader/auto_trader.go,
telegram/bot.go, debate/engine.go, backtest/ai_client.go
* feat: redesign Claw402 model config UI — friendly wallet setup, USDC guide, official logo, nginx no-cache for index.html
* refactor: centralize x402 payment flow into shared mcp/x402.go
Extract duplicated doRequestWithPayment/call/CallWithRequestFull/buildRequest/
setAuthHeader (~165 lines x3) into shared helpers in mcp/x402.go. Consolidate
shared types (x402v2PaymentRequired, x402AcceptOption, x402Resource) and remove
duplicate Solana types. Fix validAfter to 0 (official SDK standard), drain 402
body before retry, log Payment-Response tx hash, check Payment-Required before
X-Payment-Required.
* fix: stop PR template bot from overwriting user-written descriptions
The pr-template-suggester workflow was triggered on opened/edited/synchronize
events and forcefully replaced the PR body with a template when body < 100 chars.
This caused user-written descriptions to be overwritten.
Replace with a lightweight labeler (OpenClaw-style) that:
- Only adds labels (backend/frontend/docs, size: XS/S/M/L/XL)
- Never modifies the PR body
- Simplified unified PR template at .github/pull_request_template.md
* chore: simplify PR template (OpenClaw-style)
Integrates BlockRun (blockrun.ai) as a new AI provider option via x402
micropayment protocol, allowing users to access top AI models with USDC
without requiring individual API keys.
- Add BlockRun Base (EVM) and Solana wallet providers to model selector
- Implement x402 v2 EIP-712 payment signing for Base (mcp/blockrun_base.go)
- Implement x402 v2 SPL TransferChecked signing for Solana (mcp/blockrun_sol.go)
- Wire blockrun-base and blockrun-sol into trader factory (auto_trader.go)
- Register both providers in supported models API (server.go)
- Add BlockRun card UI with wallet key input in Step 0/1 of model config modal
- Add BlockRun SVG icon and ModelIcons support
- Add setup guides for Base and Solana wallet configuration (docs/)
- Available flagship models: GPT-5.4, Claude Opus 4.6, Gemini 3.1 Pro,
Grok 3, DeepSeek Chat, MiniMax M2.5
Add MiniMax as a new AI model provider with OpenAI-compatible API.
Supported models:
- MiniMax-M2.5 (default) - Peak Performance, Ultimate Value
- MiniMax-M2.5-highspeed - Same performance, faster and more agile
Changes:
- Add MiniMax client (mcp/minimax_client.go) with OpenAI-compatible API
- Add comprehensive unit tests (mcp/minimax_client_test.go)
- Add WithMiniMaxConfig option (mcp/options.go)
- Register MiniMax provider in trader, debate engine, backtest, and API
- Add MiniMax to frontend provider config and model icons
- Add MiniMax SVG icon
API Base URL: https://api.minimax.io/v1
- Add 'id' to Language type in translations.ts
- Add ~1000 Indonesian translation keys covering all UI sections
- Update LanguageContext to persist 'id' in localStorage
- Add ID button to Header.tsx language toggle
- Add �� option to HeaderBar.tsx desktop dropdown and mobile toggle
- Add Indonesian translations to inline text objects in
LoginRequiredOverlay, StrategyMarketPage, PositionHistory
Closes #XX
* feat(i18n): add 42 translation keys for TraderConfigModal
- Add new translation keys for all hardcoded Chinese strings
- Replace hardcoded UI text with t('key', language) calls
- Support both English and Chinese languages
Modified files:
- web/src/i18n/translations.ts: +88 lines (42 new keys)
- web/src/components/TraderConfigModal.tsx: replaced 48 hardcoded strings
* feat(i18n): add consolidated translation keys (en + zh + es)
- 275+ translation keys from 8 strategy components
- 3 languages: English, Chinese, Spanish
- Ready for integration into translations.ts
- Pre-aggregated exports for zhStrategy, enStrategy, esStrategy
Related to PR #1343 (maker95) and #1374 (xsa-dev)
- Add new translation keys for all hardcoded Chinese strings
- Replace hardcoded UI text with t('key', language) calls
- Support both English and Chinese languages
Modified files:
- web/src/i18n/translations.ts: +88 lines (42 new keys)
- web/src/components/TraderConfigModal.tsx: replaced 48 hardcoded strings
- Rename 'Bias Ratio' to 'Bias Strength' (偏向强度)
- Add direction modes explanation (neutral/long/short/long_bias/short_bias)
- Show actual buy/sell ratios for both long_bias and short_bias modes
- Add bilingual support (Chinese/English)
- Clarify that X% applies differently to long_bias vs short_bias
