7 Commits

Author SHA1 Message Date
Yijia-Xiao bba147798f feat: structured-output Trader and Research Manager (#434, finishes the trio)
Extends the canonical structured-output pattern from the Portfolio Manager
to the other two decision-making agents.  Each of the three agents now
returns a typed Pydantic instance via llm.with_structured_output() in a
single primary call, and a render helper turns the result into the same
markdown shape downstream agents and saved reports already consume.

- ResearchPlan: 5-tier recommendation, conversational rationale, concrete
  strategic actions for the trader.
- TraderProposal: 3-tier action (transaction direction is naturally Buy /
  Hold / Sell — position sizing happens later at the Portfolio Manager),
  reasoning, and optional entry_price / stop_loss / position_sizing.
  Rendered output preserves the trailing "FINAL TRANSACTION PROPOSAL:
  **BUY/HOLD/SELL**" line for backward compatibility with the analyst
  stop-signal text.
- PortfolioDecision: 5-tier rating, executive summary, investment thesis,
  optional price_target / time_horizon (unchanged).

The shared try-structured-then-fallback pattern is extracted into
tradingagents/agents/utils/structured.py (bind_structured +
invoke_structured_or_freetext) so all three agents go through the same
code path and log the same warning when a provider lacks structured
output and the agent falls back to free-text generation.

Net effect for users: every saved markdown report (research/manager.md,
trading/trader.md, portfolio/decision.md) now has consistent section
headers across runs and providers, easier to scan.

Net effect for the runtime: the rating extraction round-trip is gone —
the rating comes from the structured response itself, not a second
LLM call. SignalProcessor was already simplified to a heuristic adapter
in the previous commit.

11 new tests in tests/test_structured_agents.py cover the Trader and
Research Manager render functions, structured-output happy paths, and
free-text fallback. Full suite: 88 tests pass in ~2s without API keys.
2026-04-25 20:27:23 +00:00
Yijia-Xiao 0fda24515f feat: structured-output Portfolio Manager + 5-tier rating consistency (#434)
Three related changes that take the rating pipeline from heuristic-only
to type-safe at the source.

1) Research Manager prompt now uses the same 5-tier scale (Buy /
   Overweight / Hold / Underweight / Sell) as the Portfolio Manager,
   signal_processing, and the memory log.  The prior 3-tier wording
   (Buy / Sell / Hold) was the only remaining inconsistency in the
   pipeline.

2) Centralise the 5-tier vocabulary and the heuristic prose-rating
   parser into tradingagents/agents/utils/rating.py.  Both the memory
   log and the signal processor now share the same parser instead of
   duplicating regex and word-walker logic.

3) Make structured output a first-class part of the Portfolio Manager's
   primary call.  The PM uses llm.with_structured_output(PortfolioDecision)
   so each provider's native structured-output mode (json_schema for
   OpenAI/xAI, response_schema for Gemini, tool-use for Anthropic,
   function_calling for OpenAI-compatible providers) yields a typed
   Pydantic instance directly.  A render helper turns that instance back
   into the same markdown shape downstream consumers (memory log, CLI
   display, saved reports) already expect, so no other code has to know
   the PM now produces structured output.  Providers without structured
   support fall back gracefully to free-text + the deterministic
   heuristic.

   The previous SignalProcessor had been making a second LLM call to
   re-extract the rating from the PM's prose; that round-trip is now
   eliminated.  SignalProcessor is a thin adapter over parse_rating(),
   makes zero LLM calls, and stays for backwards compatibility with
   process_signal() callers.

Schema (PortfolioDecision) captures rating + executive_summary +
investment_thesis + optional price_target + time_horizon, with field
descriptions doubling as output instructions.  Agent prose remains the
primary artifact; structured output is layered onto the PM only because
it is the one agent whose output has machine-readable downstream
consumers.

15 new tests cover the heuristic parser (markdown-bold edge cases that
had no coverage before), the structured PM happy path, the free-text
fallback path, and that SignalProcessor never invokes the LLM.  Full
suite: 77 tests pass in ~2s without API keys.
2026-04-25 19:57:26 +00:00
Zhigong Liu 6abc768c1d feat: replace per-agent BM25 memory with persistent append-only decision log
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-19 22:43:14 -04:00
Yijia-Xiao bdb9c29d44 refactor: remove stale imports, use configurable results path (#499) 2026-04-04 07:35:35 +00:00
CadeYu 7d200d834a style: inline single-use instrument context vars 2026-03-21 21:31:38 +08:00
CadeYu 08bfe70a69 fix: preserve exchange-qualified tickers across agent prompts 2026-03-21 21:10:13 +08:00
Yijia-Xiao cc97cb6d5d chore(release): v0.1.0 – initial public release of TradingAgents 2025-06-05 04:27:57 -07:00