Update main.py

main.py

@@ -106,27 +106,26 @@ async def generate_image(request: ImageRequest, background_tasks: BackgroundTask
         You are a professional assistant responsible for crafting a clear and visually compelling prompt for an image generation model. Your task is to generate a high-quality prompt for creating both the **main subject** and the **background** of the image.
 
         Image Specifications:
-        - **Subject**: Focus on **{subject}**, highlighting its defining features, expressions, and textures.
-        - **Style**: Emphasize the **{style}**, capturing its key characteristics.
-        - **Background**: Create a background with **{background_details}** that complements and enhances the subject. Ensure it aligns with the color theme and overall composition.
+        - **Subject**: Focus on **{request.subject}**, highlighting its defining features, expressions, and textures.
+        - **Style**: Emphasize the **{request.style}**, capturing its key characteristics.
+        - **Background**: Create a background with **{request.background_details}** that complements and enhances the subject. Ensure it aligns with the color theme and overall composition.
         - **Camera and Lighting**:
-          - Lighting: Apply **{lighting_conditions}**, emphasizing depth, highlights, and shadows to accentuate the subject and harmonize the background.
-        - **Framing**: Use a **{framing_style}** to enhance the composition around both the subject and the background.
-        - **Materials**: Highlight textures like **{material_details}**, with realistic details and natural imperfections on the subject and background.
-        - **Key Elements**: Include **{elements}** to enrich the subject’s details and add cohesive elements to the background.
-        - **Color Theme**: Follow the **{color_theme}** to set the mood and tone for the entire scene.
+          - Lighting: Apply **{request.lighting_conditions}**, emphasizing depth, highlights, and shadows to accentuate the subject and harmonize the background.
+        - **Framing**: Use a **{request.framing_style}** to enhance the composition around both the subject and the background.
+        - **Materials**: Highlight textures like **{request.material_details}**, with realistic details and natural imperfections on the subject and background.
+        - **Key Elements**: Include **{request.elements}** to enrich the subject’s details and add cohesive elements to the background.
+        - **Color Theme**: Follow the **{request.color_theme}** to set the mood and tone for the entire scene.
         - Negative Prompt: Avoid grainy, blurry, or deformed outputs.
-        - **Text to Include in Image**: Clearly display the text **"{text}"** as part of the composition (e.g., on a card, badge, or banner) attached to the subject in a realistic and contextually appropriate way.
+        - **Text to Include in Image**: Clearly display the text **"{request.text}"** as part of the composition (e.g., on a card, badge, or banner) attached to the subject in a realistic and contextually appropriate way.
         - Write the prompt only in the output. Do not include anything else except the prompt. Do not write Generated Image Prompt: in the output.
-        
+
         Chat History:
-        {chat_history_text}
-        
+        {chat_history}
+
         User Prompt:
-        {user_prompt}
-        
-        Generated Image Prompt:      
-        
+        {request.user_prompt}
+
+        Generated Image Prompt:
         """
         refined_prompt = llm.invoke(prompt).content.strip()
         collection.insert_one({"session_id": request.chat_id, "role": "user", "content": request.user_prompt})
@@ -146,8 +145,8 @@ async def generate_image(request: ImageRequest, background_tasks: BackgroundTask
         filepath = save_image_locally(img, filename)
         return filepath
 
-    task = executor.submit(process_request)
-    background_tasks.add_task(task)
+    # Add the wrapper function to background tasks
+    background_tasks.add_task(lambda: executor.submit(process_request))
     return {"status": "Processing"}
 
 @app.post("/upscale-image", response_model=dict)