Update utils/planner.py

utils/planner.py

@@ -1,64 +1,20 @@
 # utils/planner.py
 
-import openai
 import os
-from openai import OpenAI
-from dotenv import load_dotenv
 import json
-load_dotenv()
-
-client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
-
-SYSTEM_INSTRUCTIONS = """
-You are a scene planning assistant for an AI image generation system.
-Your job is to take the user's prompt and return a structured JSON with:
-- scene (environment, setting)
-- subject (main actor)
-- objects (main product or items)
-- layout (foreground/background elements and their placement)
-- rules (validation rules to ensure visual correctness)
-Respond ONLY in raw JSON format. Do NOT include explanations.
-"""
-
-def extract_scene_plan(prompt: str) -> dict:
-    try:
-        response = client.chat.completions.create(
-            model="gpt-4o-mini-2024-07-18",
-            messages=[
-                {"role": "system", "content": SYSTEM_INSTRUCTIONS},
-                {"role": "user", "content": prompt}
-            ],
-            temperature=0.3,
-            max_tokens=500
-        )
-        json_output = response.choices[0].message.content
-        print("🧠 Scene Plan (Raw):", json_output)
-        return json.loads(json_output) # Be cautious: Use `json.loads()` if possible
-
-    except Exception as e:
-        print("❌ extract_scene_plan() Error:", e)
-        return {
-            "scene": None,
-            "subject": None,
-            "objects": [],
-            "layout": {},
-            "rules": {}
-        }
-
-
-# utils/planner.py
-
-import openai
-import os
-from openai import OpenAI
 from dotenv import load_dotenv
-import json
-load_dotenv()
+from openai import OpenAI
 
+# ----------------------------
+# 🔐 Load Environment & Client
+# ----------------------------
+load_dotenv()
 client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
 
+# ----------------------------
 # 🧠 Scene Plan Extractor
-SYSTEM_INSTRUCTIONS = """
+# ----------------------------
+SCENE_SYSTEM_INSTRUCTIONS = """
 You are a scene planning assistant for an AI image generation system.
 Your job is to take the user's prompt and return a structured JSON with:
 - scene (environment, setting)
@@ -74,7 +30,7 @@ def extract_scene_plan(prompt: str) -> dict:
         response = client.chat.completions.create(
             model="gpt-4o-mini-2024-07-18",
             messages=[
-                {"role": "system", "content": SYSTEM_INSTRUCTIONS},
+                {"role": "system", "content": SCENE_SYSTEM_INSTRUCTIONS},
                 {"role": "user", "content": prompt}
             ],
             temperature=0.3,
@@ -94,19 +50,19 @@ def extract_scene_plan(prompt: str) -> dict:
             "rules": {}
         }
 
-# 🧠 GPT-Based Prompt Variation Generator
+# ----------------------------
+# 🧠 Prompt Variation Generator
+# ----------------------------
 def generate_prompt_variations_from_scene(scene_plan: dict, base_prompt: str, n: int = 3) -> list:
     try:
         system_msg = f"""
 You are a creative prompt variation generator for an AI image generation system.
-
 Given a base user prompt and its structured scene plan, generate {n} diverse image generation prompts.
 Each prompt should:
 - Be visually rich and descriptive
 - Include stylistic or contextual variation
 - Reference the same product and environment
 - Stay faithful to the base prompt and extracted plan
-
 Respond ONLY with a JSON array of strings. No explanations.
 """
 
@@ -129,4 +85,5 @@ Respond ONLY with a JSON array of strings. No explanations.
 
     except Exception as e:
         print("❌ generate_prompt_variations_from_scene() Error:", e)
-        return [base_prompt]  # fallback to original if anything fails
+        return [base_prompt]  # fallback to original
+