import gradio as gr import os from groq import Groq # Initialize Groq client api_key = os.getenv("GROQ_API_KEY") client = Groq(api_key=api_key) # Initialize conversation history conversation_history = [] def chat_with_bot_stream(user_input): global conversation_history conversation_history.append({"role": "user", "content": user_input}) if len(conversation_history) == 1: conversation_history.insert(0, { "role": "system", "content": "You are an expert in storyboarding. Provide structured and insightful responses to queries about creating and refining storyboards." }) completion = client.chat.completions.create( model="llama3-70b-8192", messages=conversation_history, temperature=1, max_tokens=1024, top_p=1, stream=True, stop=None, ) response_content = "" for chunk in completion: response_content += chunk.choices[0].delta.content or "" conversation_history.append({"role": "assistant", "content": response_content}) return [(msg["content"] if msg["role"] == "user" else None, msg["content"] if msg["role"] == "assistant" else None) for msg in conversation_history] # Function to generate a storyboard def generate_storyboard(scenario): if not scenario.strip(): return "Please provide a scenario to generate the storyboard." messages = [ {"role": "system", "content": "You are an AI storyteller. Generate a storyboard in a structured table with six scenes."}, {"role": "user", "content": f"Generate a 6-scene storyboard for: {scenario}"} ] completion = client.chat.completions.create( model="llama3-70b-8192", messages=messages, temperature=1, max_tokens=1024, top_p=1, stream=False, stop=None, ) return completion.choices[0].message.content TITLE = """