feat: add GEMINI.md
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# Gemini Code Assistant Workspace Configuration
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This document provides a comprehensive guide for the Gemini Code Assistant to effectively understand and contribute to the `TradingAgents` project.
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## Project Overview
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`TradingAgents` is a multi-agent LLM framework for financial trading that simulates a real-world trading firm. It leverages a team of specialized LLM-powered agents, including analysts, researchers, and a trader, to collaboratively analyze market conditions and make informed trading decisions. The framework is built on `LangGraph`, which enables a modular and flexible agent-based architecture.
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The core of the project is the `TradingAgentsGraph`, which orchestrates the interactions between the different agents. The agents are organized into teams:
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* **Analyst Team:** Gathers and analyzes different types of data (e.g., fundamentals, news, social media).
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* **Researcher Team:** Debates the findings of the analyst team to form an investment plan.
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* **Trader Agent:** Makes the final trading decision based on the input from the other teams.
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* **Risk Management Team:** Assesses the risk of the proposed trade.
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## Getting Started
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### Installation
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1. Clone the repository:
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```bash
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git clone https://github.com/TauricResearch/TradingAgents.git
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cd TradingAgents
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```
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2. Create and activate a virtual environment:
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```bash
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conda create -n tradingagents python=3.13
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conda activate tradingagents
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```
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3. Install the required dependencies:
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```bash
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pip install -r requirements.txt
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```
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### API Keys
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The project requires the following API keys to be set as environment variables:
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* **FinnHub:** For financial data.
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```bash
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export FINNHUB_API_KEY=$YOUR_FINNHUB_API_KEY
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```
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* **OpenAI:** For the LLM agents.
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```bash
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export OPENAI_API_KEY=$YOUR_OPENAI_API_KEY
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```
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* **OpenRouter (optional):** If you want to use OpenRouter as your LLM provider.
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```bash
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export OPENROUTER_API_KEY=$YOUR_OPENROUTER_API_KEY
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```
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## Project Structure
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```
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C:\Users\kevin\repo\TradingAgents\
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├───.gitignore
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├───.python-version
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├───ERROR_HANDLING_GUIDE.md
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├───LICENSE
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├───main.py
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├───openrouter_status.py
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├───pyproject.toml
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├───README.md
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├───requirements.txt
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├───setup.py
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├───uv.lock
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├───.git\...
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├───.venv\
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│ ├───include\...
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│ ├───Lib\...
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│ ├───Scripts\...
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│ └───share\...
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├───assets\
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│ ├───analyst.png
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│ ├───researcher.png
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│ ├───risk.png
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│ ├───schema.png
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│ ├───TauricResearch.png
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│ ├───trader.png
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│ ├───wechat.png
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│ └───cli\
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│ ├───cli_init.png
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│ ├───cli_news.png
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│ ├───cli_technical.png
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│ └───cli_transaction.png
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├───cli\
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│ ├───__init__.py
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│ ├───main.py
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│ ├───models.py
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│ ├───utils.py
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│ ├───__pycache__\
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│ └───static\
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│ └───welcome.txt
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├───results\
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│ ├───AAPL\...
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│ └───TSLA\...
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└───tradingagents\
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├───default_config.py
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├───__pycache__\
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├───agents\
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│ ├───__init__.py
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│ ├───__pycache__\
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│ ├───analysts\
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│ │ ├───fundamentals_analyst.py
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│ │ ├───market_analyst.py
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│ │ ├───news_analyst.py
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│ │ ├───social_media_analyst.py
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│ │ └───__pycache__\
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│ ├───managers\
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│ │ ├───research_manager.py
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│ │ ├───risk_manager.py
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│ │ └───__pycache__\
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│ ├───researchers\
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│ │ ├───bear_researcher.py
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│ │ ├───bull_researcher.py
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│ │ └───__pycache__\
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│ ├───risk_mgmt\
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│ │ ├───aggresive_debator.py
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│ │ ├───conservative_debator.py
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│ │ ├───neutral_debator.py
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│ │ └───__pycache__\
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│ ├───trader\
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│ │ ├───trader.py
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│ │ └───__pycache__\
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│ └───utils\
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│ ├───agent_states.py
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│ ├───agent_utils.py
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│ ├───memory.py
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│ └───__pycache__\
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├───dataflows\
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│ ├───__init__.py
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│ ├───config.py
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│ ├───finnhub_utils.py
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│ ├───googlenews_utils.py
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│ ├───interface.py
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│ ├───reddit_utils.py
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│ ├───stockstats_utils.py
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│ ├───utils.py
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│ ├───yfin_utils.py
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│ ├───__pycache__\
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│ └───data_cache\
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└───graph\
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├───__init__.py
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├───conditional_logic.py
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├───propagation.py
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├───reflection.py
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├───setup.py
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├───signal_processing.py
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├───trading_graph.py
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└───__pycache__\
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```
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* **`main.py`**: A simple script demonstrating how to use the `TradingAgentsGraph` as a Python package.
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* **`cli/main.py`**: The main entry point for the command-line interface.
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* **`tradingagents/`**: The core Python package.
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* **`agents/`**: Contains the implementation of the different agents.
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* **`dataflows/`**: Handles data acquisition from various APIs.
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* **`graph/`**: Defines the `LangGraph` graph and the overall orchestration of the agents.
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* **`default_config.py`**: The default configuration for the project.
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* **`requirements.txt`**: A list of the Python dependencies.
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* **`pyproject.toml`**: Project metadata and dependencies.
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* **`README.md`**: The main README file for the project.
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## Core Concepts
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### TradingAgentsGraph
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The `TradingAgentsGraph` class in `tradingagents/graph/trading_graph.py` is the central orchestrator of the framework. It initializes the LLMs, tools, and agents, and then constructs a `LangGraph` graph to define the workflow. The `propagate` method executes the graph for a given company and date.
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### Agents
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Agents are defined in the `tradingagents/agents/` directory. Each agent is a "node" in the `LangGraph` graph. The agents are created by functions that take the LLM and other necessary components as input. These functions return a node function that processes the current state of the graph and returns an updated state.
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### Dataflows
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The `tradingagents/dataflows/` directory contains the logic for fetching data from various financial data APIs, such as Finnhub, Yahoo Finance, and Reddit. The `Toolkit` class in `tradingagents/agents/__init__.py` provides a unified interface for the agents to access these data sources.
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## Development Guidelines
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### Adding a New Agent
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1. Create a new Python file in the appropriate subdirectory of `tradingagents/agents/`.
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2. Define a `create_<agent_name>_agent` function that takes the LLM and any other necessary components as input.
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3. Inside this function, define a node function that takes the current state of the graph as input.
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4. Prepare a prompt for the LLM and invoke it.
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5. Return an updated state dictionary.
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6. Add the new agent to the `TradingAgentsGraph` in `tradingagents/graph/trading_graph.py`.
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### Adding a New Tool
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1. Add a new function to the appropriate file in `tradingagents/dataflows/`.
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2. Add the new function to the `Toolkit` class in `tradingagents/agents/__init__.py`.
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3. Add the new tool to the appropriate `ToolNode` in the `_create_tool_nodes` method of the `TradingAgentsGraph` class.
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### Running Tests
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This project does not currently have a dedicated test suite. When adding new features, it is recommended to add unit tests to ensure the correctness of the code.
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## Key Commands
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* **Run the CLI:**
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```bash
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python -m cli.main
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```
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* **Run the package example:**
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```bash
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python main.py
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```
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