Updated the final story generation

my_agent/utils/utils.py

@@ -7,16 +7,11 @@ from PIL import Image
 from io import BytesIO
 from fastapi import UploadFile
 from huggingface_hub import InferenceClient
-from .prompts import story_to_prompt
+from .prompts import story_to_prompt , final_story_prompt
 
-def generate_final_story(query):
-    if len(query['preferred_topics'])>0:
-        template = f'''I want to create a detailed storyline for a video in the given topic. You have to provide me that storyline what to include in the video.
-      Now, i am giving you the topic of the video. But the need is to generate the story focusing on the format that i'll provide to you.
-      You can use this format for the reference purpose, not for the exact similar generation. The format is:\n{query['retrievals'][-1]}.
-      \n\n Now let's start creating the storyline for my topic. The topic of the video is: \n\n{query['topic']}\n\n
-
-      **Final Reminder** You have to strongly focus on these topics while creating the storyline: {[item for sublist in query['preferred_topics'] for item in sublist]}'''
+def generate_final_story(final_state):
+    if len(final_state['preferred_topics'])>0:
+        template = final_story_prompt(final_state)
         messages = [SystemMessage(content=template)]
         response = llm.bind_tools([StoryFormatter]).invoke(messages)
         print('The final response is:',response)
@@ -31,7 +26,7 @@ def generate_final_story(query):
         return response
     
     else:
-        return query['stories'][-1]
+        return final_state['stories'][-1]