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| from langchain_core.messages import SystemMessage | |
| from langchain_groq import ChatGroq | |
| from pydantic import BaseModel, Field | |
| from dotenv import load_dotenv | |
| load_dotenv() | |
| import os | |
| import numpy as np | |
| os.environ['GROQ_API_KEY']=os.getenv('GROQ_API_KEY') | |
| llm = ChatGroq( | |
| model="llama3-8b-8192", | |
| temperature=0, | |
| max_tokens=None, | |
| timeout=None, | |
| max_retries=2, | |
| ) | |
| class StoryFormatter(BaseModel): | |
| """Always use this tool to structure your response to the user.""" | |
| story: str=Field(description="How to introduce the scene and set the tone. What is happening in the scene? Describe key visuals and actions") | |
| narration:str=Field(description="Suggestions for narration or voiceover that complements the visuals." ) | |
| text_in_the_Video:str=Field(description="Propose important text overlays for key moments.") | |
| transitions:str=Field(description="Smooth transitions between scenes to maintain flow.") | |
| emotional_tone:str=Field(description="The mood and energy of the scenes (e.g., excitement, calm, tension, joy") | |
| key_visuals:str=Field(description="Important props, locations, sound effects, or background music to enhance the video.") | |
| class BrainstromTopicFormatter(BaseModel): | |
| topic1:str=Field(description="First brainstorming topic of the story") | |
| topic2:str=Field(description="Second brainstorming topic of the story") | |
| topic3:str=Field(description="Third brainstorming topic of the story") | |
| topic4:str=Field(description="Fourth brainstorming topic of the story") |