diff --git a/.env.example b/.env.example
index a859170c..4f4a4f01 100644
--- a/.env.example
+++ b/.env.example
@@ -1,11 +1,291 @@
-# For OpenAI (default)
-OPENAI_API_KEY=your_openai_api_key_here
-ALPHA_VANTAGE_API_KEY=your_alpha_vantage_key_here
-TRADINGAGENTS_LLM_PROVIDER=openai
-TRADINGAGENTS_BACKEND_URL=https://api.openai.com/v1
+# ============================================================================
+# TradingAgents Environment Configuration
+# ============================================================================
+#
+# This file contains example configurations for different deployment scenarios.
+# Copy this file to .env and uncomment/modify the section that matches your setup.
+#
+# Quick Start:
+# 1. Copy this file: cp .env.example .env
+# 2. Choose a scenario below and uncomment it
+# 3. Add your actual API keys
+# 4. Run TradingAgents!
+#
+# ============================================================================
 
-# For OpenRouter
-# OPENROUTER_API_KEY=your_openrouter_api_key_here  # OpenRouter uses OPENAI_API_KEY env var
-# ALPHA_VANTAGE_API_KEY=your_alpha_vantage_key_here
+# ============================================================================
+# SCENARIO 1: OpenAI Everything (Recommended for Production)
+# ============================================================================
+# Use OpenAI for both chat models and embeddings
+# Best for: Production deployment with full features
+# Cost: Moderate (chat + embeddings)
+# ============================================================================
+
+OPENAI_API_KEY=sk-proj-your_openai_api_key_here
+ALPHA_VANTAGE_API_KEY=your_alpha_vantage_api_key_here
+
+# Optional: Explicitly set provider (defaults to openai)
+# TRADINGAGENTS_LLM_PROVIDER=openai
+# TRADINGAGENTS_BACKEND_URL=https://api.openai.com/v1
+# TRADINGAGENTS_EMBEDDING_PROVIDER=openai
+# TRADINGAGENTS_EMBEDDING_BACKEND_URL=https://api.openai.com/v1
+
+
+# ============================================================================
+# SCENARIO 2: OpenRouter Chat + OpenAI Embeddings (Cost Optimized)
+# ============================================================================
+# Use OpenRouter for free/cheap chat models, OpenAI for reliable embeddings
+# Best for: Development, testing, cost optimization
+# Cost: Low (free chat) + Low (embeddings only)
+# ============================================================================
+
+# OPENROUTER_API_KEY=sk-or-v1-your_openrouter_api_key_here
+# OPENAI_API_KEY=sk-proj-your_openai_api_key_here
+# ALPHA_VANTAGE_API_KEY=your_alpha_vantage_api_key_here
+#
 # TRADINGAGENTS_LLM_PROVIDER=openrouter
 # TRADINGAGENTS_BACKEND_URL=https://openrouter.ai/api/v1
+# TRADINGAGENTS_EMBEDDING_PROVIDER=openai
+# TRADINGAGENTS_EMBEDDING_BACKEND_URL=https://api.openai.com/v1
+
+
+# ============================================================================
+# SCENARIO 3: All Local with Ollama (Offline/Private)
+# ============================================================================
+# Run completely offline with local Ollama models
+# Best for: Privacy, offline deployment, no API costs
+# Cost: Free (requires local compute)
+# Prerequisites:
+#   - Install Ollama: https://ollama.ai
+#   - Pull models: ollama pull llama3.1 llama3.2 nomic-embed-text
+# ============================================================================
+
+# ALPHA_VANTAGE_API_KEY=your_alpha_vantage_api_key_here
+#
+# TRADINGAGENTS_LLM_PROVIDER=ollama
+# TRADINGAGENTS_BACKEND_URL=http://localhost:11434/v1
+# TRADINGAGENTS_EMBEDDING_PROVIDER=ollama
+# TRADINGAGENTS_EMBEDDING_BACKEND_URL=http://localhost:11434/v1
+# TRADINGAGENTS_EMBEDDING_MODEL=nomic-embed-text
+
+
+# ============================================================================
+# SCENARIO 4: Anthropic Chat + OpenAI Embeddings
+# ============================================================================
+# Use Claude models for chat, OpenAI for embeddings
+# Best for: High-quality reasoning with reliable embeddings
+# Cost: High (Claude) + Low (embeddings only)
+# ============================================================================
+
+# ANTHROPIC_API_KEY=sk-ant-your_anthropic_api_key_here
+# OPENAI_API_KEY=sk-proj-your_openai_api_key_here
+# ALPHA_VANTAGE_API_KEY=your_alpha_vantage_api_key_here
+#
+# TRADINGAGENTS_LLM_PROVIDER=anthropic
+# TRADINGAGENTS_BACKEND_URL=https://api.anthropic.com/
+# TRADINGAGENTS_EMBEDDING_PROVIDER=openai
+# TRADINGAGENTS_EMBEDDING_BACKEND_URL=https://api.openai.com/v1
+
+
+# ============================================================================
+# SCENARIO 5: Google Gemini Chat + OpenAI Embeddings
+# ============================================================================
+# Use Google Gemini models for chat, OpenAI for embeddings
+# Best for: Cost-effective with good performance
+# Cost: Low-Moderate
+# ============================================================================
+
+# GOOGLE_API_KEY=your_google_api_key_here
+# OPENAI_API_KEY=sk-proj-your_openai_api_key_here
+# ALPHA_VANTAGE_API_KEY=your_alpha_vantage_api_key_here
+#
+# TRADINGAGENTS_LLM_PROVIDER=google
+# TRADINGAGENTS_BACKEND_URL=https://generativelanguage.googleapis.com/v1
+# TRADINGAGENTS_EMBEDDING_PROVIDER=openai
+# TRADINGAGENTS_EMBEDDING_BACKEND_URL=https://api.openai.com/v1
+
+
+# ============================================================================
+# SCENARIO 6: OpenRouter Chat + No Memory (Minimal)
+# ============================================================================
+# Use OpenRouter without memory/embeddings
+# Best for: Testing, debugging, minimal cost
+# Cost: Very Low (chat only, no embeddings)
+# Note: Agents will run without historical context
+# ============================================================================
+
+# OPENROUTER_API_KEY=sk-or-v1-your_openrouter_api_key_here
+# ALPHA_VANTAGE_API_KEY=your_alpha_vantage_api_key_here
+#
+# TRADINGAGENTS_LLM_PROVIDER=openrouter
+# TRADINGAGENTS_BACKEND_URL=https://openrouter.ai/api/v1
+# TRADINGAGENTS_ENABLE_MEMORY=false
+
+
+# ============================================================================
+# SCENARIO 7: Mixed Models (Advanced)
+# ============================================================================
+# Use different providers for different components
+# Best for: Advanced users optimizing for cost/performance
+# ============================================================================
+
+# # Chat models
+# OPENROUTER_API_KEY=sk-or-v1-your_openrouter_api_key_here
+# TRADINGAGENTS_LLM_PROVIDER=openrouter
+# TRADINGAGENTS_BACKEND_URL=https://openrouter.ai/api/v1
+# TRADINGAGENTS_DEEP_THINK_LLM=deepseek/deepseek-chat-v3-0324:free
+# TRADINGAGENTS_QUICK_THINK_LLM=meta-llama/llama-3.3-8b-instruct:free
+#
+# # Embeddings
+# OPENAI_API_KEY=sk-proj-your_openai_api_key_here
+# TRADINGAGENTS_EMBEDDING_PROVIDER=openai
+# TRADINGAGENTS_EMBEDDING_BACKEND_URL=https://api.openai.com/v1
+# TRADINGAGENTS_EMBEDDING_MODEL=text-embedding-3-small
+#
+# # Data sources
+# ALPHA_VANTAGE_API_KEY=your_alpha_vantage_api_key_here
+
+
+# ============================================================================
+# Additional Configuration Options
+# ============================================================================
+
+# Logging Configuration
+# TRADINGAGENTS_LOG_LEVEL=INFO              # DEBUG, INFO, WARNING, ERROR, CRITICAL
+# TRADINGAGENTS_LOG_DIR=logs                # Directory for log files
+# TRADINGAGENTS_LOG_TO_CONSOLE=true         # Enable console logging
+# TRADINGAGENTS_LOG_TO_FILE=true            # Enable file logging
+
+# Memory/Embedding Configuration
+# TRADINGAGENTS_ENABLE_MEMORY=true          # Enable/disable memory system
+# TRADINGAGENTS_EMBEDDING_MODEL=text-embedding-3-small  # Embedding model
+
+# Research Depth
+# TRADINGAGENTS_MAX_DEBATE_ROUNDS=1         # Number of debate rounds (1-5)
+# TRADINGAGENTS_MAX_RISK_DISCUSS_ROUNDS=1   # Risk discussion rounds (1-5)
+
+# Data Vendors
+# TRADINGAGENTS_CORE_STOCK_API=yfinance     # yfinance, alpha_vantage, local
+# TRADINGAGENTS_TECHNICAL_INDICATORS=yfinance
+# TRADINGAGENTS_FUNDAMENTAL_DATA=alpha_vantage
+# TRADINGAGENTS_NEWS_DATA=alpha_vantage
+
+
+# ============================================================================
+# CLI vs Module Usage
+# ============================================================================
+
+# Option A: CLI Usage (Interactive)
+# ------------------------------------
+# When running via CLI, the interactive prompts will guide you through
+# selecting providers, models, and embedding options.
+#
+# Usage:
+#   python -m cli.main
+#
+# The CLI will:
+#   1. Ask for ticker symbol
+#   2. Ask for analysis date
+#   3. Ask for analyst selection
+#   4. Ask for research depth
+#   5. Ask for LLM provider
+#   6. Ask for thinking agents
+#   7. Ask for embedding provider  ← NEW!
+#
+# Environment variables in this file provide defaults and API keys.
+
+
+# Option B: Module Usage (Programmatic)
+# ---------------------------------------
+# When using TradingAgents as a Python module, you configure everything
+# in code using the config dictionary.
+#
+# Example:
+#   from tradingagents.graph.trading_graph import TradingAgentsGraph
+#
+#   config = {
+#       "llm_provider": "openrouter",
+#       "backend_url": "https://openrouter.ai/api/v1",
+#       "deep_think_llm": "deepseek/deepseek-chat-v3-0324:free",
+#       "quick_think_llm": "meta-llama/llama-3.3-8b-instruct:free",
+#
+#       "embedding_provider": "openai",
+#       "embedding_backend_url": "https://api.openai.com/v1",
+#       "embedding_model": "text-embedding-3-small",
+#       "enable_memory": True,
+#
+#       "log_level": "INFO",
+#   }
+#
+#   graph = TradingAgentsGraph(["market", "news"], config=config)
+#   final_state, decision = graph.propagate("AAPL", "2025-01-15")
+
+
+# ============================================================================
+# API Key Sources & Links
+# ============================================================================
+
+# OpenAI API Key
+# Get from: https://platform.openai.com/api-keys
+# Format: sk-proj-...
+
+# OpenRouter API Key
+# Get from: https://openrouter.ai/keys
+# Format: sk-or-v1-...
+
+# Anthropic API Key
+# Get from: https://console.anthropic.com/
+# Format: sk-ant-...
+
+# Google API Key
+# Get from: https://makersuite.google.com/app/apikey
+# Format: AI...
+
+# Alpha Vantage API Key
+# Get from: https://www.alphavantage.co/support/#api-key
+# Format: alphanumeric string
+
+
+# ============================================================================
+# Security Notes
+# ============================================================================
+
+# 1. NEVER commit this file with real API keys to version control
+# 2. Add .env to your .gitignore file
+# 3. Use separate API keys for development and production
+# 4. Rotate keys regularly
+# 5. Use least-privilege keys when possible
+# 6. Monitor API usage and set spending limits
+
+
+# ============================================================================
+# Troubleshooting
+# ============================================================================
+
+# Issue: "No auth credentials found"
+# Solution: Make sure the correct API key is set for your provider
+#   - OpenRouter needs: OPENROUTER_API_KEY
+#   - OpenAI needs: OPENAI_API_KEY (for chat AND embeddings if used)
+#   - Anthropic needs: ANTHROPIC_API_KEY
+#   - Google needs: GOOGLE_API_KEY
+
+# Issue: "Failed to get embedding: 401 Unauthorized"
+# Solution: Set OPENAI_API_KEY if using OpenAI for embeddings,
+#   even if using a different provider for chat
+
+# Issue: Memory disabled unexpectedly
+# Solution: Check TRADINGAGENTS_ENABLE_MEMORY=true and that
+#   embedding provider is set correctly
+
+# Check your environment:
+#   python3 check_env_setup.py
+
+# For more help:
+#   - docs/EMBEDDING_CONFIGURATION.md
+#   - docs/LOGGING.md
+#   - FEATURE_EMBEDDING_README.md
+
+
+# ============================================================================
+# End of Configuration
+# ============================================================================
diff --git a/docs/CONFIGURATION_GUIDE.md b/docs/CONFIGURATION_GUIDE.md
new file mode 100644
index 00000000..6f821ff9
--- /dev/null
+++ b/docs/CONFIGURATION_GUIDE.md
@@ -0,0 +1,691 @@
+# TradingAgents Configuration Guide
+
+**Complete guide to configuring TradingAgents for different scenarios**
+
+---
+
+## Table of Contents
+
+1. [Quick Start](#quick-start)
+2. [Configuration Methods](#configuration-methods)
+3. [Deployment Scenarios](#deployment-scenarios)
+4. [API Keys Setup](#api-keys-setup)
+5. [Configuration Reference](#configuration-reference)
+6. [CLI vs Module Usage](#cli-vs-module-usage)
+7. [Environment Variables](#environment-variables)
+8. [Troubleshooting](#troubleshooting)
+
+---
+
+## Quick Start
+
+### 1. Copy Environment Template
+
+```bash
+cp .env.example .env
+```
+
+### 2. Choose Your Scenario
+
+Open `.env` and uncomment one of the scenarios:
+
+- **Scenario 1**: OpenAI Everything (Recommended)
+- **Scenario 2**: OpenRouter + OpenAI Embeddings (Cost Optimized)
+- **Scenario 3**: All Local with Ollama (Offline/Private)
+- **Scenario 4**: Anthropic + OpenAI Embeddings
+- **Scenario 5**: Google Gemini + OpenAI Embeddings
+- **Scenario 6**: OpenRouter + No Memory (Minimal)
+- **Scenario 7**: Mixed Models (Advanced)
+
+### 3. Add Your API Keys
+
+Replace placeholder values with your actual API keys.
+
+### 4. Run TradingAgents
+
+**CLI Mode:**
+```bash
+python -m cli.main
+```
+
+**Module Mode:**
+```python
+from tradingagents.graph.trading_graph import TradingAgentsGraph
+
+graph = TradingAgentsGraph(["market", "news"])
+final_state, decision = graph.propagate("AAPL", "2025-01-15")
+```
+
+---
+
+## Configuration Methods
+
+### Method 1: Environment Variables (.env file)
+
+**Best for**: CLI usage, development
+
+```bash
+# .env file
+OPENAI_API_KEY=sk-proj-...
+OPENROUTER_API_KEY=sk-or-v1-...
+TRADINGAGENTS_LLM_PROVIDER=openrouter
+```
+
+The system automatically loads `.env` file on startup.
+
+### Method 2: Config Dictionary (Python)
+
+**Best for**: Module usage, programmatic control
+
+```python
+config = {
+    "llm_provider": "openrouter",
+    "backend_url": "https://openrouter.ai/api/v1",
+    "deep_think_llm": "deepseek/deepseek-chat-v3-0324:free",
+    "quick_think_llm": "meta-llama/llama-3.3-8b-instruct:free",
+    
+    "embedding_provider": "openai",
+    "embedding_backend_url": "https://api.openai.com/v1",
+    "enable_memory": True,
+}
+
+graph = TradingAgentsGraph(["market"], config=config)
+```
+
+### Method 3: CLI Interactive
+
+**Best for**: Quick testing, exploration
+
+```bash
+python -m cli.main
+```
+
+Follow the interactive prompts to select:
+- Ticker symbol
+- Analysis date
+- Analysts team
+- Research depth
+- LLM provider
+- Thinking agents
+- Embedding provider
+
+---
+
+## Deployment Scenarios
+
+### Scenario 1: OpenAI Everything ⭐ Recommended
+
+**Use Case**: Production deployment with full features
+
+**Configuration:**
+
+```bash
+# .env
+OPENAI_API_KEY=sk-proj-your_key_here
+ALPHA_VANTAGE_API_KEY=your_key_here
+```
+
+**Pros:**
+- ✅ Full feature support
+- ✅ Reliable and fast
+- ✅ Single provider simplicity
+
+**Cons:**
+- 💰 Moderate cost (chat + embeddings)
+
+**Cost**: ~$0.50-$2.00 per analysis (depending on depth)
+
+---
+
+### Scenario 2: OpenRouter + OpenAI Embeddings 💰 Cost Optimized
+
+**Use Case**: Development, testing, cost optimization
+
+**Configuration:**
+
+```bash
+# .env
+OPENROUTER_API_KEY=sk-or-v1-your_key_here
+OPENAI_API_KEY=sk-proj-your_key_here
+ALPHA_VANTAGE_API_KEY=your_key_here
+
+TRADINGAGENTS_LLM_PROVIDER=openrouter
+TRADINGAGENTS_BACKEND_URL=https://openrouter.ai/api/v1
+TRADINGAGENTS_EMBEDDING_PROVIDER=openai
+TRADINGAGENTS_EMBEDDING_BACKEND_URL=https://api.openai.com/v1
+```
+
+**Pros:**
+- ✅ Very low cost (free chat models)
+- ✅ Full memory/embedding support
+- ✅ Good for development
+
+**Cons:**
+- ⚠️ Free models may be slower
+- ⚠️ Quality varies by model
+
+**Cost**: ~$0.05-$0.20 per analysis (embeddings only)
+
+---
+
+### Scenario 3: All Local with Ollama 🔒 Privacy First
+
+**Use Case**: Offline deployment, privacy requirements, no API costs
+
+**Prerequisites:**
+
+```bash
+# Install Ollama
+# Visit: https://ollama.ai
+
+# Pull required models
+ollama pull llama3.1
+ollama pull llama3.2
+ollama pull nomic-embed-text
+```
+
+**Configuration:**
+
+```bash
+# .env
+ALPHA_VANTAGE_API_KEY=your_key_here
+
+TRADINGAGENTS_LLM_PROVIDER=ollama
+TRADINGAGENTS_BACKEND_URL=http://localhost:11434/v1
+TRADINGAGENTS_EMBEDDING_PROVIDER=ollama
+TRADINGAGENTS_EMBEDDING_BACKEND_URL=http://localhost:11434/v1
+TRADINGAGENTS_EMBEDDING_MODEL=nomic-embed-text
+```
+
+**Pros:**
+- ✅ Completely free
+- ✅ Full privacy (no data leaves your machine)
+- ✅ Works offline
+- ✅ No rate limits
+
+**Cons:**
+- ⚠️ Requires local compute resources
+- ⚠️ Slower than cloud APIs
+- ⚠️ Quality depends on local model
+
+**Cost**: $0 (requires GPU for best performance)
+
+---
+
+### Scenario 4: Anthropic + OpenAI Embeddings 🧠 High Quality
+
+**Use Case**: High-quality reasoning and analysis
+
+**Configuration:**
+
+```bash
+# .env
+ANTHROPIC_API_KEY=sk-ant-your_key_here
+OPENAI_API_KEY=sk-proj-your_key_here
+ALPHA_VANTAGE_API_KEY=your_key_here
+
+TRADINGAGENTS_LLM_PROVIDER=anthropic
+TRADINGAGENTS_BACKEND_URL=https://api.anthropic.com/
+TRADINGAGENTS_EMBEDDING_PROVIDER=openai
+TRADINGAGENTS_EMBEDDING_BACKEND_URL=https://api.openai.com/v1
+```
+
+**Pros:**
+- ✅ Excellent reasoning (Claude)
+- ✅ Long context support
+- ✅ High-quality outputs
+
+**Cons:**
+- 💰 Higher cost
+
+**Cost**: ~$1.00-$5.00 per analysis (depending on model)
+
+---
+
+### Scenario 5: Google Gemini + OpenAI Embeddings 📊 Balanced
+
+**Use Case**: Cost-effective with good performance
+
+**Configuration:**
+
+```bash
+# .env
+GOOGLE_API_KEY=your_key_here
+OPENAI_API_KEY=sk-proj-your_key_here
+ALPHA_VANTAGE_API_KEY=your_key_here
+
+TRADINGAGENTS_LLM_PROVIDER=google
+TRADINGAGENTS_EMBEDDING_PROVIDER=openai
+```
+
+**Pros:**
+- ✅ Good quality/cost ratio
+- ✅ Fast response times
+- ✅ Multimodal capabilities
+
+**Cons:**
+- ⚠️ Newer, less tested in production
+
+**Cost**: ~$0.30-$1.00 per analysis
+
+---
+
+### Scenario 6: OpenRouter + No Memory 🚀 Minimal
+
+**Use Case**: Testing, debugging, minimal cost
+
+**Configuration:**
+
+```bash
+# .env
+OPENROUTER_API_KEY=sk-or-v1-your_key_here
+ALPHA_VANTAGE_API_KEY=your_key_here
+
+TRADINGAGENTS_LLM_PROVIDER=openrouter
+TRADINGAGENTS_BACKEND_URL=https://openrouter.ai/api/v1
+TRADINGAGENTS_ENABLE_MEMORY=false
+```
+
+**Pros:**
+- ✅ Minimal cost
+- ✅ Fast setup
+- ✅ No embedding API needed
+
+**Cons:**
+- ⚠️ No historical context
+- ⚠️ Agents can't learn from past decisions
+
+**Cost**: ~$0.00-$0.10 per analysis (free models)
+
+---
+
+### Scenario 7: Mixed Models 🎛️ Advanced
+
+**Use Case**: Optimize for specific use cases
+
+**Configuration:**
+
+```bash
+# .env
+# Cheap chat models
+OPENROUTER_API_KEY=sk-or-v1-your_key_here
+TRADINGAGENTS_LLM_PROVIDER=openrouter
+TRADINGAGENTS_DEEP_THINK_LLM=deepseek/deepseek-chat-v3-0324:free
+TRADINGAGENTS_QUICK_THINK_LLM=meta-llama/llama-3.3-8b-instruct:free
+
+# Reliable embeddings
+OPENAI_API_KEY=sk-proj-your_key_here
+TRADINGAGENTS_EMBEDDING_PROVIDER=openai
+TRADINGAGENTS_EMBEDDING_MODEL=text-embedding-3-small
+
+# Data sources
+ALPHA_VANTAGE_API_KEY=your_key_here
+```
+
+**Pros:**
+- ✅ Maximum flexibility
+- ✅ Optimize each component
+- ✅ Balance cost/performance
+
+**Cons:**
+- ⚠️ More complex setup
+- ⚠️ Multiple API keys required
+
+**Cost**: Varies based on choices
+
+---
+
+## API Keys Setup
+
+### OpenAI
+
+1. Visit: https://platform.openai.com/api-keys
+2. Click "Create new secret key"
+3. Copy key (format: `sk-proj-...`)
+4. Add to `.env`: `OPENAI_API_KEY=sk-proj-...`
+
+**Used for**: Chat models, embeddings
+
+### OpenRouter
+
+1. Visit: https://openrouter.ai/keys
+2. Create account and generate key
+3. Copy key (format: `sk-or-v1-...`)
+4. Add to `.env`: `OPENROUTER_API_KEY=sk-or-v1-...`
+
+**Used for**: Chat models (many providers)
+
+### Anthropic
+
+1. Visit: https://console.anthropic.com/
+2. Navigate to API Keys
+3. Create new key (format: `sk-ant-...`)
+4. Add to `.env`: `ANTHROPIC_API_KEY=sk-ant-...`
+
+**Used for**: Claude chat models
+
+### Google
+
+1. Visit: https://makersuite.google.com/app/apikey
+2. Create API key
+3. Copy key (format: `AI...`)
+4. Add to `.env`: `GOOGLE_API_KEY=AI...`
+
+**Used for**: Gemini chat models
+
+### Alpha Vantage
+
+1. Visit: https://www.alphavantage.co/support/#api-key
+2. Get free API key
+3. Add to `.env`: `ALPHA_VANTAGE_API_KEY=...`
+
+**Used for**: Financial data, news
+
+---
+
+## Configuration Reference
+
+### Complete Config Dictionary
+
+```python
+config = {
+    # LLM Provider Settings
+    "llm_provider": "openai",                    # openai, openrouter, anthropic, google, ollama
+    "backend_url": "https://api.openai.com/v1",
+    "deep_think_llm": "o4-mini",                 # Model for deep reasoning
+    "quick_think_llm": "gpt-4o-mini",            # Model for quick tasks
+    
+    # Embedding Settings (Separate from chat)
+    "embedding_provider": "openai",              # openai, ollama, none
+    "embedding_backend_url": "https://api.openai.com/v1",
+    "embedding_model": "text-embedding-3-small",
+    "enable_memory": True,                       # Enable/disable memory system
+    
+    # Logging Settings
+    "log_level": "INFO",                         # DEBUG, INFO, WARNING, ERROR, CRITICAL
+    "log_dir": "logs",
+    "log_to_console": True,
+    "log_to_file": True,
+    
+    # Research Settings
+    "max_debate_rounds": 1,                      # 1-5, higher = deeper analysis
+    "max_risk_discuss_rounds": 1,                # 1-5, higher = more thorough risk assessment
+    
+    # Data Vendor Settings
+    "data_vendors": {
+        "core_stock_apis": "yfinance",           # yfinance, alpha_vantage, local
+        "technical_indicators": "yfinance",
+        "fundamental_data": "alpha_vantage",
+        "news_data": "alpha_vantage",
+    },
+    
+    # Directory Settings
+    "project_dir": ".",
+    "results_dir": "./results",
+    "data_cache_dir": "./dataflows/data_cache",
+}
+```
+
+---
+
+## CLI vs Module Usage
+
+### CLI Usage (Interactive)
+
+**When to use**: Quick analysis, exploration, non-technical users
+
+**Run:**
+```bash
+python -m cli.main
+```
+
+**Workflow:**
+1. Select ticker (e.g., AAPL)
+2. Select date
+3. Choose analysts (market, news, fundamentals, social)
+4. Choose research depth (shallow, medium, deep)
+5. Choose LLM provider (OpenAI, OpenRouter, Anthropic, Google, Ollama)
+6. Choose thinking agents (quick/deep models)
+7. Choose embedding provider (OpenAI, Ollama, Disable)
+
+**Configuration:**
+- API keys from `.env` file
+- Prompts guide you through options
+- Results saved to `results/` directory
+
+### Module Usage (Programmatic)
+
+**When to use**: Automation, integration, batch processing
+
+**Example:**
+
+```python
+from tradingagents.graph.trading_graph import TradingAgentsGraph
+from datetime import datetime
+
+# Configure
+config = {
+    "llm_provider": "openrouter",
+    "backend_url": "https://openrouter.ai/api/v1",
+    "deep_think_llm": "deepseek/deepseek-chat-v3-0324:free",
+    "quick_think_llm": "meta-llama/llama-3.3-8b-instruct:free",
+    "embedding_provider": "openai",
+    "embedding_backend_url": "https://api.openai.com/v1",
+    "enable_memory": True,
+    "log_level": "INFO",
+}
+
+# Initialize
+graph = TradingAgentsGraph(
+    selected_analysts=["market", "news", "fundamentals"],
+    config=config,
+    debug=False
+)
+
+# Run analysis
+tickers = ["AAPL", "GOOGL", "MSFT"]
+for ticker in tickers:
+    final_state, decision = graph.propagate(ticker, datetime.now().strftime("%Y-%m-%d"))
+    print(f"{ticker}: {decision}")
+    
+    # Optionally reflect on results
+    # graph.reflect_and_remember(returns_losses)
+```
+
+**Configuration:**
+- Full control in code
+- No interactive prompts
+- Ideal for automation
+
+---
+
+## Environment Variables
+
+### Provider Configuration
+
+| Variable | Description | Example |
+|----------|-------------|---------|
+| `TRADINGAGENTS_LLM_PROVIDER` | Chat LLM provider | `openrouter` |
+| `TRADINGAGENTS_BACKEND_URL` | Chat API endpoint | `https://openrouter.ai/api/v1` |
+| `TRADINGAGENTS_DEEP_THINK_LLM` | Deep reasoning model | `deepseek/deepseek-chat-v3-0324:free` |
+| `TRADINGAGENTS_QUICK_THINK_LLM` | Quick thinking model | `meta-llama/llama-3.3-8b-instruct:free` |
+
+### Embedding Configuration
+
+| Variable | Description | Example |
+|----------|-------------|---------|
+| `TRADINGAGENTS_EMBEDDING_PROVIDER` | Embedding provider | `openai` |
+| `TRADINGAGENTS_EMBEDDING_BACKEND_URL` | Embedding API endpoint | `https://api.openai.com/v1` |
+| `TRADINGAGENTS_EMBEDDING_MODEL` | Embedding model | `text-embedding-3-small` |
+| `TRADINGAGENTS_ENABLE_MEMORY` | Enable memory system | `true` or `false` |
+
+### Logging Configuration
+
+| Variable | Description | Example |
+|----------|-------------|---------|
+| `TRADINGAGENTS_LOG_LEVEL` | Logging verbosity | `INFO` |
+| `TRADINGAGENTS_LOG_DIR` | Log directory | `logs` |
+| `TRADINGAGENTS_LOG_TO_CONSOLE` | Console logging | `true` |
+| `TRADINGAGENTS_LOG_TO_FILE` | File logging | `true` |
+
+---
+
+## Troubleshooting
+
+### Issue: No auth credentials found
+
+**Error:**
+```
+AuthenticationError: Error code: 401 - {'error': {'message': 'No auth credentials found'}}
+```
+
+**Solution:**
+1. Check if API key is set in `.env`
+2. Verify key format (e.g., `sk-proj-...` for OpenAI)
+3. Run environment checker:
+   ```bash
+   python3 check_env_setup.py
+   ```
+
+### Issue: Failed to get embedding
+
+**Error:**
+```
+ERROR | MEMORY | Failed to get embedding: 401 Unauthorized
+```
+
+**Solution:**
+1. Set `OPENAI_API_KEY` if using OpenAI for embeddings
+2. OR set `TRADINGAGENTS_ENABLE_MEMORY=false` to disable
+3. OR use Ollama for local embeddings
+
+### Issue: Memory disabled unexpectedly
+
+**Logs:**
+```
+WARNING | MEMORY | Memory disabled for 'bull_memory'
+```
+
+**Solution:**
+1. Check `TRADINGAGENTS_ENABLE_MEMORY=true`
+2. Verify embedding provider is valid
+3. Check embedding API key is set
+
+### Issue: Wrong provider selected
+
+**Error:**
+```
+Unsupported LLM provider: xyz
+```
+
+**Solution:**
+1. Check `TRADINGAGENTS_LLM_PROVIDER` value
+2. Valid options: `openai`, `openrouter`, `anthropic`, `google`, `ollama`
+3. Case-sensitive!
+
+### Issue: Module not found
+
+**Error:**
+```
+ModuleNotFoundError: No module named 'tradingagents'
+```
+
+**Solution:**
+```bash
+# Install in development mode
+pip install -e .
+
+# Or install dependencies
+pip install -r requirements.txt
+```
+
+---
+
+## Verification Checklist
+
+Before running TradingAgents, verify:
+
+- [ ] `.env` file exists (copied from `.env.example`)
+- [ ] API keys are set correctly
+- [ ] Provider configuration matches your API keys
+- [ ] Embedding provider is configured if memory enabled
+- [ ] Log directory is writable
+- [ ] Dependencies are installed
+
+**Quick check:**
+```bash
+python3 check_env_setup.py
+```
+
+---
+
+## Best Practices
+
+### Development
+
+```bash
+# Use cost-optimized setup
+OPENROUTER_API_KEY=sk-or-v1-...
+OPENAI_API_KEY=sk-proj-...
+TRADINGAGENTS_LLM_PROVIDER=openrouter
+TRADINGAGENTS_EMBEDDING_PROVIDER=openai
+TRADINGAGENTS_LOG_LEVEL=DEBUG
+```
+
+### Production
+
+```bash
+# Use reliable providers
+OPENAI_API_KEY=sk-proj-...
+TRADINGAGENTS_LLM_PROVIDER=openai
+TRADINGAGENTS_LOG_LEVEL=INFO
+TRADINGAGENTS_LOG_TO_FILE=true
+```
+
+### Testing/CI
+
+```bash
+# Disable expensive features
+OPENROUTER_API_KEY=sk-or-v1-...
+TRADINGAGENTS_LLM_PROVIDER=openrouter
+TRADINGAGENTS_ENABLE_MEMORY=false
+TRADINGAGENTS_LOG_LEVEL=WARNING
+```
+
+---
+
+## Security Notes
+
+1. **Never commit `.env` to git**
+   ```bash
+   # Add to .gitignore
+   echo ".env" >> .gitignore
+   ```
+
+2. **Use separate keys for dev/prod**
+
+3. **Rotate keys regularly**
+
+4. **Monitor API usage**
+   - Set spending limits in provider dashboards
+   - Review `logs/api_calls.log` for usage tracking
+
+5. **Use least-privilege keys**
+   - Restrict key permissions when possible
+
+---
+
+## Support
+
+For more help:
+
+- **Environment Setup**: `check_env_setup.py`
+- **Embedding Configuration**: `docs/EMBEDDING_CONFIGURATION.md`
+- **Logging System**: `docs/LOGGING.md`
+- **Feature Overview**: `FEATURE_EMBEDDING_README.md`
+
+---
+
+**Last Updated**: 2025-01-15  
+**Version**: 2.0  
+**Status**: Production Ready ✅
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