Update server.py

server.py

@@ -1,65 +1,40 @@
 from fastmcp import FastMCP
 import logging
-import sys
-from pathlib import Path
 import os
 
-# Configure logging to stderr
-logging.basicConfig(
-    level=logging.INFO,
-    stream=sys.stderr,
-    format='%(asctime)s [%(name)s] [%(levelname)s] %(message)s'
-)
-logger = logging.getLogger("MathServer")
-
-# Initialize FastMCP server
+# Initialize the server
 mcp = FastMCP("Math-Education-Server")
 
-# Use Path for cross-platform compatibility
-current_dir = Path(__file__).parent
-MARKDOWN_FILE = current_dir / "resource" / "jemh114-min (1).md"
+# SENIOR TIP: Use absolute paths relative to the script location 
+# This prevents "File Not Found" errors in Docker.
+CURRENT_DIR = os.path.dirname(os.path.abspath(__file__))
+MARKDOWN_FILE = os.path.join(CURRENT_DIR, "resource", "jemh114-min (1).md")
 
 def get_local_resource():
-    """Helper to read the markdown file safely."""
-    try:
-        return MARKDOWN_FILE.read_text(encoding="utf-8")
-    except FileNotFoundError:
-        logger.error(f"Resource not found at {MARKDOWN_FILE}")
-        return "Resource file not found."
+    if os.path.exists(MARKDOWN_FILE):
+        with open(MARKDOWN_FILE, "r", encoding="utf-8") as f:
+            return f.read()
+    return "Resource file not found."
 
 @mcp.tool()
 async def generate_chapter_summary(chapter_name: str) -> str:
-    """Generate a summary of a math chapter."""
+    """Provides source material and instructions for a math summary."""
     raw_data = get_local_resource()
     return f"""
     <source_material>
     {raw_data[:4000]} 
     </source_material>
-
     SYSTEM_INSTRUCTION: You are a Mathematics Expert. 
-    1. Read the text inside <source_material>.
-    2. Create a summary with 3 bullet points for chapter: {chapter_name}
-    3. List all formulas found in LaTeX format.
-    4. Do not repeat the raw text; only provide the summary.
+    1. Summarize in 3 bullets.
+    2. List formulas like $x = \\frac{{-b \\pm \\sqrt{{b^2-4ac}}}}{{2a}}$.
     """
 
 @mcp.tool()
 async def generate_quiz(chapter_name: str, difficulty: str = "medium") -> str:
-    """Generate a quiz for a math chapter."""
     raw_data = get_local_resource()
-    return (
-        f"Here is the raw material for {chapter_name}:\n"
-        f"{raw_data[:4000]}\n"
-        f"Difficulty: {difficulty}\n"
-        "Task: Create a 3-question quiz using the formulas found in the text."
-    )
+    return f"Material: {raw_data[:2000]}\nDifficulty: {difficulty}\nCreate a 3-question quiz."
 
 if __name__ == "__main__":
-    port = int(os.getenv("PORT", 7860))
-    host = os.getenv("HOST", "0.0.0.0")
-    
-    logger.info(f"Starting FastMCP Server via SSE on {host}:{port}")
-    
-    # Use SSE transport for Hugging Face Spaces
-    # FastMCP handles host validation automatically
-    mcp.run(transport="stdio")
+    # Change stdio to sse for Hugging Face deployment
+    # HF Spaces listen on port 7860 by default
+    mcp.run(transport="sse")