fix: Finalize LLM path for deployment

core/creative_chat.py

@@ -1,3 +1,4 @@
+
 import os
 import sys
 from llama_cpp import Llama
@@ -5,6 +6,7 @@ import json
 import re
 
 # Path setup to import VectorStore from the parent directory
+# This logic is correct and remains the same
 current_dir = os.path.dirname(os.path.abspath(__file__))
 parent_dir = os.path.dirname(current_dir)
 sys.path.append(parent_dir)
@@ -15,11 +17,17 @@ class CreativeDirector:
     def __init__(self):
         """Initialize Model and Memory once to save time."""
         
-        # Using TinyLlama as it is faster on CPU
-        model_path = os.path.join(parent_dir, "llm_model", "tinyllama-1.1b-chat-v1.0.Q4_K_M.gguf")
+        # ✅ THE FIX IS HERE: We now look for the model in the writable directory
+        # where main.py downloads it, not in the read-only application directory.
+        model_name = "tinyllama-1.1b-chat-v1.0.Q4_K_M.gguf"
+        # Hugging Face Spaces provides '/data' as a writable persistent directory.
+        writable_dir = os.environ.get("WRITABLE_DIR", "/data") 
+        model_path = os.path.join(writable_dir, "llm_model", model_name)
+        # =====================================================================
         
         if not os.path.exists(model_path):
-            raise FileNotFoundError(f"❌ Model not found at: {model_path}. Please check the llm_model folder.")
+            # This error will now correctly point to the writable directory
+            raise FileNotFoundError(f"❌ Model not found at: {model_path}. Please check the download logic in main.py.")
 
         print("🧠 Loading AI Director (TinyLlama - SUPER FAST MODE)...")
         
@@ -72,7 +80,6 @@ Response:"""
 
         conversation_summary = "\n".join([f"- {msg['content']}" for msg in history[-3:]])
 
-        # ✅ PROMPT: Ask for plain text with specific labels
         prompt = f"""Instruction: Create a video script for "{task_context}".
 Chat Summary: {conversation_summary}
 
@@ -96,14 +103,11 @@ Response:"""
             raw_text = response['choices'][0]['text'].strip()
             print(f"   - 🤖 Raw Text: {raw_text}")
 
-            # ✅ ROBUST PARSING (Regex)
-            # Text me se 'HOOK:', 'SCRIPT:' dhund kar nikalenge
             hook_match = re.search(r'HOOK:\s*(.*?)(?=\nSCRIPT:)', raw_text, re.DOTALL | re.IGNORECASE)
             script_match = re.search(r'SCRIPT:\s*(.*?)(?=\nVISUALS:)', raw_text, re.DOTALL | re.IGNORECASE)
             visuals_match = re.search(r'VISUALS:\s*(.*?)(?=\nTOOLS:)', raw_text, re.DOTALL | re.IGNORECASE)
             tools_match = re.search(r'TOOLS:\s*(.*)', raw_text, re.DOTALL | re.IGNORECASE)
 
-            # Agar match na mile to poora text script me daal do
             return {
                 "hook": hook_match.group(1).strip() if hook_match else "Start with a bang!",
                 "script": script_match.group(1).strip() if script_match else raw_text,
@@ -113,7 +117,6 @@ Response:"""
 
         except Exception as e:
             print(f"   - ❌ Final Plan Generation Error: {e}")
-            # Fallback JSON
             return {
                 "hook": "Error generating plan.",
                 "script": "Please try again later.",