made changes

README.md

@@ -9,4 +9,46 @@ app_file: app.py
 pinned: false
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# NBA Data Analysis with CrewAI
+
+An intelligent NBA data analysis application powered by CrewAI agents. Upload your NBA CSV data and get comprehensive analysis with insights, statistics, and engaging storylines.
+
+## Features
+
+- 📊 **Data Engineering**: Automatic data cleaning and preparation
+- 🔍 **Intelligent Analysis**: AI-powered insights and pattern detection
+- 📈 **Statistical Analysis**: Top performers, trends, and key metrics
+- 📝 **Storytelling**: Engaging headlines and narratives from data
+- 🎯 **Semantic Search**: Natural language queries on your data
+
+## How to Use
+
+1. **Upload a CSV file** with NBA data
+2. **Enter your analysis query** (or leave blank for comprehensive analysis)
+3. **Click "Analyze Dataset"** and wait for results
+4. **View insights** from Engineer, Analyst, and Storyteller agents
+
+## Example Queries
+
+- "Who are the top 5 three-point shooters?"
+- "Show me the best scoring games this season"
+- "Which players have the highest field goal percentage?"
+- "Analyze team performance trends"
+
+## Technology Stack
+
+- **CrewAI**: Multi-agent AI framework
+- **Gradio**: Web interface
+- **Pandas**: Data analysis
+- **ChromaDB**: Vector database for semantic search
+- **OpenRouter**: Free open-source LLM access
+
+## Free to Use
+
+This application uses free-tier services:
+- OpenRouter for LLM access (free tier)
+- Hugging Face Spaces for hosting (free tier)
+
+---
+
+Built with ❤️ using CrewAI

app.py

@@ -326,10 +326,9 @@ if __name__ == "__main__":
         print("Creating Gradio app...")
         app = create_app()
         print("Launching Gradio app...")
+        # For Hugging Face Spaces, use default launch settings
+        # Spaces will automatically handle server_name and port
         app.launch(
-            server_name="0.0.0.0",
-            server_port=7860,
-            share=False,
             show_error=True
         )
     except Exception as e:

config.py

@@ -7,31 +7,80 @@ from crewai import LLM
 # NBA Data Configuration
 NBA_DATA_PATH = "nba24-25.csv"
 
+# LLM Configuration - Choose your provider
+# Options: "openai", "ollama", "litellm", "openrouter"
+# Default to openrouter for free tier access
+LLM_PROVIDER = os.getenv("LLM_PROVIDER", "openrouter")  # Default to free tier
+
 # OpenAI Configuration
 OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
-OPENAI_MODEL = os.getenv("OPENAI_MODEL", "gpt-4o")  
+OPENAI_MODEL = os.getenv("OPENAI_MODEL", "gpt-4o")
+
+# Ollama Configuration (for local open-source models)
+OLLAMA_BASE_URL = os.getenv("OLLAMA_BASE_URL", "http://localhost:11434")
+OLLAMA_MODEL = os.getenv("OLLAMA_MODEL", "llama3.2")  # Options: llama3.2, mistral, qwen2.5, etc.
+
+# LiteLLM Configuration (for Hugging Face or other providers)
+LITELLM_MODEL = os.getenv("LITELLM_MODEL", "huggingface/meta-llama/Llama-3.2-3B-Instruct")
+LITELLM_API_KEY = os.getenv("LITELLM_API_KEY", "")  # Optional, depends on provider
 
-# Validate OpenAI API key (only raise error when actually trying to use LLM, not on import)
-# This allows the app to load even if API key isn't set yet
+# OpenRouter Configuration (access to many open-source models)
+OPENROUTER_API_KEY = os.getenv("OPENROUTER_API_KEY")
+OPENROUTER_MODEL = os.getenv("OPENROUTER_MODEL", "meta-llama/llama-3.2-3b-instruct:free")  # Free tier available
 
 
 def get_llm() -> LLM:
     """
-    Create and return a CrewAI LLM instance configured for OpenAI.
+    Create and return a CrewAI LLM instance based on the configured provider.
     
     Returns:
-        LLM: Configured CrewAI LLM instance for OpenAI
+        LLM: Configured CrewAI LLM instance
     
     Raises:
-        ValueError: If OPENAI_API_KEY is not set
+        ValueError: If required configuration is not set
     """
-    if not OPENAI_API_KEY:
-        raise ValueError(
-            "OPENAI_API_KEY environment variable is not set. "
-            "Please set it using: export OPENAI_API_KEY='your-api-key'"
+    if LLM_PROVIDER == "ollama":
+        # Option 1: Ollama (local open-source models)
+        # Install: brew install ollama (Mac) or see https://ollama.ai
+        # Run: ollama pull llama3.2
+        return LLM(
+            model=OLLAMA_MODEL,
+            base_url=OLLAMA_BASE_URL,
+            api_key="ollama"  # Ollama doesn't require a real API key, but CrewAI needs something
+        )
+    
+    elif LLM_PROVIDER == "litellm":
+        # Option 2: LiteLLM (supports Hugging Face, Together AI, etc.)
+        # Format: huggingface/model-name or together_ai/model-name
+        return LLM(
+            model=f"litellm/{LITELLM_MODEL}",
+            api_key=LITELLM_API_KEY if LITELLM_API_KEY else "dummy"  # Some providers don't need keys
+        )
+    
+    elif LLM_PROVIDER == "openrouter":
+        # Option 3: OpenRouter (access to many open-source models)
+        # Free tier available: https://openrouter.ai
+        # Note: For Hugging Face Spaces, set OPENROUTER_API_KEY as a secret
+        if not OPENROUTER_API_KEY:
+            # Try to use without key (some free models might work)
+            # But it's better to set the key for reliability
+            print("Warning: OPENROUTER_API_KEY not set. Some models may not work.")
+            print("Get a free key at https://openrouter.ai")
+        return LLM(
+            model=OPENROUTER_MODEL,
+            base_url="https://openrouter.ai/api/v1",
+            api_key=OPENROUTER_API_KEY if OPENROUTER_API_KEY else "free"
+        )
+    
+    else:
+        # Default: OpenAI (original configuration)
+        if not OPENAI_API_KEY:
+            raise ValueError(
+                "OPENAI_API_KEY environment variable is not set. "
+                "Please set it using: export OPENAI_API_KEY='your-api-key'"
+            )
+        return LLM(
+            model=OPENAI_MODEL,
+            api_key=OPENAI_API_KEY
         )
-    return LLM(
-        model=OPENAI_MODEL,
-        api_key=OPENAI_API_KEY
-    )
 

main.py

@@ -11,7 +11,8 @@ def main():
     """Main function to run the NBA data analysis crew."""
     print("=" * 60)
     print("NBA 2024-25 Data Analysis with CrewAI")
-    print("Using OpenAI")
+    from config import LLM_PROVIDER
+    print(f"Using LLM Provider: {LLM_PROVIDER.upper()}")
     print("=" * 60)
     print()