Previous refactor (89f01ad) moved to OpenRouter because no sk-ant-api-* key
was found in Vault. Turns out claude-agent-service-spare-{1,2} hold
sk-ant-oat01-* OAuth tokens (108 chars, scope user:inference, 1-year TTL,
minted via 'claude setup-token' — see memory id=832).
These tokens work with the Anthropic SDK via the auth_token= constructor
argument (routes to Authorization: Bearer ... instead of x-api-key: ...).
They consume the Enterprise Claude subscription quota rather than
per-call billing, so the OpenRouter zero-credit problem goes away.
- llm_analyzer.py: revert OpenAI client to AsyncAnthropic; tool-use API
+ cache_control restored
- config.py: openrouter_api_key -> anthropic_oauth_token; model slug
reverted from anthropic/claude-sonnet-4.5 -> claude-sonnet-4-5
- main.py: AsyncOpenAI -> AsyncAnthropic(auth_token=...), drop OpenRouter
attribution headers
- pyproject: openai>=1.50 -> anthropic>=0.40 in meet_kevin extras
- tests: mocks ported back to messages.create + tool_use blocks
User's Vault has openrouter_api_key but no direct sk-ant-* Anthropic key.
OpenRouter passes through Claude Sonnet 4.6 (~3% markup over Anthropic
list pricing) and matches the existing gpt_mini_endpoint pattern used
by recruiter-responder.
- Replace anthropic.AsyncAnthropic with openai.AsyncOpenAI + base_url
- Convert Anthropic tool-use API to OpenAI function-calling
- System prompt unchanged (analyst instructions are model-agnostic)
- Drop cache_control (not in OpenAI API); revisit later if cost matters
- Model slug: anthropic/claude-sonnet-4.5 (OpenRouter's current Claude tier)
- Pricing: $3.10/M input, $15.50/M output (OpenRouter pass-through)
- Config field anthropic_api_key -> openrouter_api_key
- pyproject extras: anthropic>=0.40 -> openai>=1.50
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
- Change BacktestRequest from strategy_weights dict to strategies list to match frontend
- Add tickers field so users can select which stocks to backtest
- Fetch historical bars from Alpaca StockHistoricalDataClient instead of empty data loader
- Register all 9 strategies (momentum, mean_reversion, news_driven, value, macd_crossover,
bollinger_breakout, vwap, liquidity, ma_stack) filtered by user selection
- Fix response format: use frontend field names (max_drawdown, total_trades, win_rate as
0-1 decimal), include equity_curve and run_id in response
- Add ticker selector with checkboxes and custom ticker input to dashboard
- Add alpaca-py to api dependency group in pyproject.toml
- Add pytz to trading extras (alpaca-py requires it but doesn't declare it)
- Remove host port mapping from ollama container to avoid conflict with
local ollama instance
Add integration tests for the news pipeline (test_news_pipeline.py) and
trading flow (test_trading_flow.py) using real Redis with mocked FinBERT
and Alpaca. Add seed_strategies.py to insert default strategies (momentum,
mean_reversion, news_driven) with equal weights. Add smoke_test.sh for
end-to-end stack validation. Update pyproject.toml with integration marker
and scripts package discovery.
- pyproject.toml with core deps and optional dep groups per service
- shared/config.py: Pydantic BaseSettings with TRADING_ env prefix
- shared/redis_streams.py: StreamPublisher/StreamConsumer wrappers
- shared/telemetry.py: OpenTelemetry + Prometheus metric export
- tests for Redis Streams helpers (5 passing)
