TauricResearch · JuanmanDev · Oct 31, 2025
diff --git a/.env.example b/.env.example
@@ -1,2 +1,20 @@
+# API Keys - Set the ones you need based on your LLM provider choice
+OPENAI_API_KEY=openai_api_key_placeholder
+# ANTHROPIC_API_KEY=your-anthropic-api-key-here
+# GOOGLE_API_KEY=your-google-api-key-here
+# GROQ_API_KEY=your-groq-api-key-here
+# TOGETHER_API_KEY=your-together-api-key-here
+# AZURE_OPENAI_API_KEY=your-azure-key-here
+# AZURE_OPENAI_ENDPOINT=https://your-resource.openai.azure.com/
+
+# Data API Keys
 ALPHA_VANTAGE_API_KEY=alpha_vantage_api_key_placeholder
-OPENAI_API_KEY=openai_api_key_placeholder
+REDDIT_CLIENT_ID=your-reddit-client-id
+REDDIT_CLIENT_SECRET=your-reddit-client-secret
+REDDIT_USER_AGENT=TradingAgents
+
+# Optional: For local Ollama instance
+# OLLAMA_BASE_URL=http://localhost:11434
+
+# Optional: Results directory
+# TRADINGAGENTS_RESULTS_DIR=./results
diff --git a/CHANGES_SUMMARY.md b/CHANGES_SUMMARY.md
@@ -0,0 +1,334 @@
+# TradingAgents - AI Provider Agnostic Update - Summary
+
+## Overview
+
+Your TradingAgents project has been successfully updated to be **AI provider agnostic**. You can now use OpenAI, Ollama, Anthropic, Google, Groq, and many other providers instead of being locked to OpenAI only.
+
+## Key Changes Made
+
+### 1. Core Infrastructure
+
+#### New LLM Factory (`tradingagents/llm_factory.py`)
+- Unified interface for creating LLM instances from any provider
+- Automatic handling of provider-specific initialization
+- Supports 9+ providers out of the box
+- Clear error messages for missing dependencies
+
+#### Updated Configuration (`tradingagents/default_config.py`)
+- Added `llm_provider` setting (default: "openai")
+- Added `temperature` for model control
+- Added `llm_kwargs` for provider-specific parameters
+- Includes example configurations for all providers
+
+### 2. Code Refactoring
+
+#### `tradingagents/graph/trading_graph.py`
+- Removed hardcoded provider checks
+- Uses LLM factory for initialization
+- Cleaner, more maintainable code
+
+#### Type Annotations Updated
+- `tradingagents/graph/setup.py`
+- `tradingagents/graph/signal_processing.py`
+- `tradingagents/graph/reflection.py`
+- Now accept any LangChain-compatible LLM (not just ChatOpenAI)
+
+### 3. Dependencies
+
+#### `requirements.txt`
+- Organized by purpose with comments
+- Includes langchain-core and langchain-community
+- Optional packages documented for each provider
+
+#### `.env.example`
+- Added API key placeholders for all providers
+- Documented Ollama setup (no API key needed)
+
+## New Documentation
+
+### Comprehensive Guides
+
+1. **`docs/LLM_PROVIDER_GUIDE.md`** (Main Reference)
+   - Complete setup for each provider
+   - Environment variables needed
+   - Required packages
+   - Model recommendations by use case
+   - Troubleshooting section
+
+2. **`docs/MULTI_PROVIDER_SUPPORT.md`** (Quick Start)
+   - Quick code examples
+   - Installation notes
+   - Environment setup
+
+3. **`docs/MIGRATION_GUIDE.md`** (For Existing Users)
+   - What changed and why
+   - Migration steps
+   - Benefits of multi-provider support
+   - Breaking changes (none!)
+
+4. **`docs/README_ADDITION.md`** (README Enhancement)
+   - Suggested additions to main README
+   - Quick examples for each provider
+
+### Example Configurations
+
+5. **`examples/llm_provider_configs.py`**
+   - Pre-configured settings for all providers
+   - Ready-to-use code snippets
+   - Usage examples
+
+## Supported Providers
+
+| Provider | Type | Cost | Setup Difficulty | Best For |
+|----------|------|------|------------------|----------|
+| **OpenAI** | Cloud API | $$$ | Easy | Quality & Reliability |
+| **Ollama** | Local | FREE | Medium | Privacy & Cost Savings |
+| **Anthropic** | Cloud API | $$$ | Easy | Quality & Long Context |
+| **Google Gemini** | Cloud API | $$ | Easy | Cost-Effective Quality |
+| **Groq** | Cloud API | $ | Easy | Speed |
+| **OpenRouter** | Cloud API | Varies | Easy | Multi-Provider Access |
+| **Azure OpenAI** | Cloud API | $$$ | Medium | Enterprise |
+| **Together AI** | Cloud API | $ | Easy | Open Source Models |
+| **HuggingFace** | Cloud API | Varies | Easy | Model Variety |
+
+## Quick Start Guide
+
+### Current Setup (OpenAI) - No Changes Needed
+
+```python
+from tradingagents.graph.trading_graph import TradingAgentsGraph
+from tradingagents.default_config import DEFAULT_CONFIG
+
+# Your existing code still works!
+ta = TradingAgentsGraph(config=DEFAULT_CONFIG)
+```
+
+### Switch to Ollama (Free, Local)
+
+**1. Install Ollama:**
+```bash
+# Visit https://ollama.ai and install
+ollama pull llama3:70b
+ollama pull llama3:8b
+```
+
+**2. Install Package:**
+```bash
+pip install langchain-community
+```
+
+**3. Update Code:**
+```python
+from tradingagents.graph.trading_graph import TradingAgentsGraph
+from tradingagents.default_config import DEFAULT_CONFIG
+
+config = DEFAULT_CONFIG.copy()
+config["llm_provider"] = "ollama"
+config["deep_think_llm"] = "llama3:70b"
+config["quick_think_llm"] = "llama3:8b"
+config["backend_url"] = "http://localhost:11434"
+
+ta = TradingAgentsGraph(config=config)
+_, decision = ta.propagate("NVDA", "2024-05-10")
+```
+
+### Switch to Anthropic Claude
+
+**1. Get API Key:**
+```bash
+export ANTHROPIC_API_KEY=sk-ant-your-key-here
+```
+
+**2. Install Package:**
+```bash
+pip install langchain-anthropic  # Already in requirements.txt
+```
+
+**3. Update Code:**
+```python
+config = DEFAULT_CONFIG.copy()
+config["llm_provider"] = "anthropic"
+config["deep_think_llm"] = "claude-3-opus-20240229"
+config["quick_think_llm"] = "claude-3-haiku-20240307"
+
+ta = TradingAgentsGraph(config=config)
+```
+
+### Switch to Google Gemini
+
+**1. Get API Key:**
+```bash
+export GOOGLE_API_KEY=your-google-key-here
+```
+
+**2. Install Package:**
+```bash
+pip install langchain-google-genai  # Already in requirements.txt
+```
+
+**3. Update Code:**
+```python
+config = DEFAULT_CONFIG.copy()
+config["llm_provider"] = "google"
+config["deep_think_llm"] = "gemini-1.5-pro"
+config["quick_think_llm"] = "gemini-1.5-flash"
+
+ta = TradingAgentsGraph(config=config)
+```
+
+### Switch to Groq (Fast & Affordable)
+
+**1. Get API Key:**
+```bash
+export GROQ_API_KEY=gsk-your-groq-key
+```
+
+**2. Install Package:**
+```bash
+pip install langchain-groq
+```
+
+**3. Update Code:**
+```python
+config = DEFAULT_CONFIG.copy()
+config["llm_provider"] = "groq"
+config["deep_think_llm"] = "mixtral-8x7b-32768"
+config["quick_think_llm"] = "llama3-8b-8192"
+
+ta = TradingAgentsGraph(config=config)
+```
+
+## Benefits
+
+### 💰 Cost Savings
+- **Free:** Run Llama 3 locally with Ollama ($0/month)
+- **Cheap:** Use Groq or Google Gemini ($10-20/month)
+- **Flexible:** Mix providers based on task complexity
+
+### 🔒 Privacy
+- Run models completely locally with Ollama
+- No data sent to external APIs
+- Full control over your trading data
+
+### ⚡ Performance
+- Groq: Ultra-fast inference (500+ tokens/sec)
+- Ollama: No API latency
+- Choose the best tool for each job
+
+### 🎯 Flexibility
+- Not vendor-locked
+- Switch providers in seconds
+- Test multiple models easily
+
+## Model Recommendations
+
+### Best Quality
+- **Deep Think:** GPT-4o or Claude 3 Opus
+- **Quick Think:** GPT-4o-mini or Claude 3 Haiku
+
+### Best Cost (Free)
+- **Deep Think:** Llama 3 70B (Ollama)
+- **Quick Think:** Llama 3 8B (Ollama)
+
+### Best Speed
+- **Deep Think:** Mixtral 8x7B (Groq)
+- **Quick Think:** Llama 3 8B (Groq)
+
+### Best Balance
+- **Deep Think:** Gemini 1.5 Pro or Claude 3 Sonnet
+- **Quick Think:** Gemini 1.5 Flash or Claude 3 Haiku
+
+## Files Modified
+
+### Core Files
+- ✅ `tradingagents/llm_factory.py` (NEW)
+- ✅ `tradingagents/default_config.py`
+- ✅ `tradingagents/graph/trading_graph.py`
+- ✅ `tradingagents/graph/setup.py`
+- ✅ `tradingagents/graph/signal_processing.py`
+- ✅ `tradingagents/graph/reflection.py`
+- ✅ `requirements.txt`
+- ✅ `.env.example`
+
+### Documentation (NEW)
+- ✅ `docs/LLM_PROVIDER_GUIDE.md`
+- ✅ `docs/MULTI_PROVIDER_SUPPORT.md`
+- ✅ `docs/MIGRATION_GUIDE.md`
+- ✅ `docs/README_ADDITION.md`
+
+### Examples (NEW)
+- ✅ `examples/llm_provider_configs.py`
+
+## Testing
+
+Test the changes with:
+
+```python
+# Test with OpenAI (should work as before)
+from tradingagents.graph.trading_graph import TradingAgentsGraph
+from tradingagents.default_config import DEFAULT_CONFIG
+
+ta = TradingAgentsGraph(config=DEFAULT_CONFIG, debug=True)
+_, decision = ta.propagate("AAPL", "2024-05-10")
+print(f"Decision: {decision}")
+
+# Test LLM factory directly
+from tradingagents.llm_factory import LLMFactory
+
+llm = LLMFactory.create_llm(
+    provider="openai",
+    model="gpt-4o-mini",
+    temperature=0.7
+)
+response = llm.invoke("What is 2+2?")
+print(response.content)
+```
+
+## Next Steps
+
+1. **Review Documentation:**
+   - Read `docs/LLM_PROVIDER_GUIDE.md` for detailed setup
+   - Check `examples/llm_provider_configs.py` for ready-to-use configs
+
+2. **Try Ollama (Free):**
+   - Install Ollama from https://ollama.ai
+   - Pull a model: `ollama pull llama3`
+   - Update your config to use Ollama
+   - Save money while maintaining quality!
+
+3. **Experiment:**
+   - Test different providers for different tasks
+   - Compare quality vs. cost vs. speed
+   - Find the optimal setup for your use case
+
+4. **Update README (Optional):**
+   - Add the content from `docs/README_ADDITION.md` to your main README
+   - Let users know about multi-provider support
+
+## Backward Compatibility
+
+✅ **100% Backward Compatible**
+- Existing code continues to work
+- Default configuration still uses OpenAI
+- No breaking changes
+
+## Support
+
+If you encounter issues:
+
+1. Check `docs/LLM_PROVIDER_GUIDE.md` for setup instructions
+2. Verify API keys are set correctly
+3. Ensure required packages are installed
+4. For Ollama, make sure it's running (`ollama serve`)
+
+## Conclusion
+
+Your TradingAgents project is now **provider-agnostic** and supports multiple AI providers! You have the flexibility to:
+
+- Use free local models (Ollama)
+- Choose the best provider for each task
+- Optimize for cost, speed, or quality
+- Maintain privacy with local models
+- Future-proof against vendor changes
+
+All while maintaining **100% backward compatibility** with existing code. 🎉