Bill/AI-Trader
1
0
Fork 0
mirror of https://github.com/Xe138/AI-Trader.git synced 2026-04-01 17:17:24 -04:00
Code Issues Packages Projects Releases Wiki Activity

docs: update for IF_TRADE and DeepSeek fixes

Browse Source 
- Document model factory architecture
- Add troubleshooting for DeepSeek validation errors
- Update changelog with version 0.4.2 fixes
This commit is contained in:
Bill Ballou
2025-11-06 07:58:43 -05:00
parent 81ec0ec53b
commit 872928a187
2 changed files with 29 additions and 2 deletions
Download Patch File Download Diff File Expand all files Collapse all files

15
CHANGELOG.md
View File

@@ -7,6 +7,21 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
## [Unreleased] ## [Unreleased]
## [0.4.2] - 2025-11-05
### Fixed
- Fixed "No trading" message always displaying despite trading activity by initializing `IF_TRADE` to `True` (trades expected by default)
- Resolved sporadic Pydantic validation errors for DeepSeek tool_calls arguments by switching to native `ChatDeepSeek` integration
### Added
- Added `agent/model_factory.py` for provider-specific model creation
- Added `langchain-deepseek` dependency for native DeepSeek support
- Added integration tests for DeepSeek tool calls argument parsing
### Changed
- `BaseAgent` now uses model factory instead of direct `ChatOpenAI` instantiation
- DeepSeek models (`deepseek/*`) now use `ChatDeepSeek` instead of OpenAI compatibility layer
## [0.4.1] - 2025-11-05 ## [0.4.1] - 2025-11-05
### Fixed ### Fixed

16
CLAUDE.md
View File

@@ -167,12 +167,18 @@ bash main.sh
### Agent System ### Agent System
**BaseAgent Key Methods:** **BaseAgent Key Methods:**
- `initialize()`: Connect to MCP services, create AI model - `initialize()`: Connect to MCP services, create AI model via model factory
- `run_trading_session(date)`: Execute single day's trading with retry logic - `run_trading_session(date)`: Execute single day's trading with retry logic
- `run_date_range(init_date, end_date)`: Process all weekdays in range - `run_date_range(init_date, end_date)`: Process all weekdays in range
- `get_trading_dates()`: Resume from last date in position.jsonl - `get_trading_dates()`: Resume from last date in position.jsonl
- `register_agent()`: Create initial position file with $10,000 cash - `register_agent()`: Create initial position file with $10,000 cash
**Model Factory:**
The `create_model()` factory automatically selects the appropriate chat model:
- `deepseek/*` models → `ChatDeepSeek` (native tool calling support)
- `openai/*` models → `ChatOpenAI`
- Other providers → `ChatOpenAI` (OpenAI-compatible endpoint)
**Adding Custom Agents:** **Adding Custom Agents:**
1. Create new class inheriting from `BaseAgent` 1. Create new class inheriting from `BaseAgent`
2. Add to `AGENT_REGISTRY` in `main.py`: 2. Add to `AGENT_REGISTRY` in `main.py`:
@@ -452,4 +458,10 @@ The project uses a well-organized documentation structure:
**Agent Doesn't Stop Trading:** **Agent Doesn't Stop Trading:**
- Agent must output `<FINISH_SIGNAL>` within `max_steps` - Agent must output `<FINISH_SIGNAL>` within `max_steps`
- Increase `max_steps` if agent needs more reasoning time - Increase `max_steps` if agent needs more reasoning time
- Check `log.jsonl` for errors preventing completion - Check `log.jsonl` for errors preventing completion
**DeepSeek Pydantic Validation Errors:**
- Error: "Input should be a valid dictionary [type=dict_type, input_value='...', input_type=str]"
- Cause: Using `ChatOpenAI` for DeepSeek models (OpenAI compatibility layer issue)
- Fix: Ensure `langchain-deepseek` is installed and basemodel uses `deepseek/` prefix
- The model factory automatically uses `ChatDeepSeek` for native support