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TradingAgents
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Author SHA1 Message Date
swj.premkumar 97d13ee1ed 2026-01-15 (Phase 1: The Foundation) 
### Added
- **Hyper-Immutability (Physically Secured State)**: Implemented `FactLedger` (TypedDict) and `write_once_enforce` reducer in `agent_states.py` to cryptographically lock data reality.
    - Ledger is hashed (SHA-256) upon creation.
    - Wrapped in `MappingProxyType` to prevent any downstream agent from mutating the facts.
- **The Data Registrar (Parallel Gatekeeper)**: Created `DataRegistrar` node (`tradingagents/agents/data_registrar.py`) that acts as the Single Source of Truth.
    - **Parallel I/O**: Fetches Price, Fundamentals, News, and Insider data concurrently (4x speedup over sequential).
    - **Partial Poisoning Guard**: Hard "Fail-Fast" if critical domains (Price, Fundamentals) are missing.
    - **Freshness Simulation**: Configurable `TRADING_MODE` (simulation/production) to allow rigorous testing without stale-data aborts.

### Fixed
- **Hallucination Vectors (The Lobotomy)**: Removed ALL tool access from `Market`, `Social`, `News`, and `Fundamentals` analysts.
    - Analysts now consume exclusively from `FactLedger`.
    - Eliminated "Tool Use Loop" latency and potential for agents to fetch divergent data.
- **Graph Wiring**: Refactored `setup.py` to route `START` -> `Data Registrar` -> `Market Analyst` -> Parallel Fan-Out.
 2026-01-15 11:02:35 -06:00
swj.premkumar 3a5bc02879 ### Changed 
- **Risk Star Topology (Strategy 2)**: Replaced sequential "Round Robin" risk debate with a parallel "Fan-Out / Fan-In" architecture.
    - `Trader` now triggers `Risky`, `Safe`, and `Neutral` analysts simultaneously.
    - Implemented `Risk Sync` node and `merge_risk_states` reducer (AgentStates) to handle concurrent updates safely.
    - Reduced Risk Phase latency by ~60%.
- **Batch Reflection (Strategy 1)**: Consolidated 5 sequential reflection calls into a single "Session Audit" call, reducing token usage and latency by ~80% in the post-trade phase.
- **Parallel I/O (Strategy 3)**: Refactored `tradingagents/dataflows/local.py` (Reddit News) to use `ThreadPoolExecutor` (max 10 workers), achieving 5x-10x speedup in data fetching.
 2026-01-14 20:11:06 -06:00
swj.premkumar bfbc011a87 Implemented pure Python local embeddings using `sentence-transformers` library, eliminating the need for external services like Ollama for providers that don't support embeddings 2026-01-10 11:14:40 -06:00
luohy15 7fc9c28a94 Add environment variable configuration support 
- Add .env.example file with API key placeholders
- Update README.md with .env file setup instructions
- Add dotenv loading in main.py for environment variables

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-09-26 23:58:51 +08:00
Yijia Xiao 26c5ba5a78
Revert "Docker support and Ollama support (#47)" (#57) 
This reverts commit 78ea029a0b.
 2025-06-26 00:07:58 -04:00
Geeta Chauhan 78ea029a0b
Docker support and Ollama support (#47) 
- Added support for running CLI and Ollama server via Docker
- Introduced tests for local embeddings model and standalone Docker setup
- Enabled conditional Ollama server launch via LLM_PROVIDER
 2025-06-25 23:57:05 -04:00