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| import streamlit as st | |
| import os | |
| import requests | |
| import json | |
| import re | |
| with open('./styles.css') as f: | |
| css = f.read() | |
| st.markdown(f'<style>{css}</style>', unsafe_allow_html=True) | |
| #from huggingface_hub.inference_api import InferenceApi | |
| #inference = InferenceApi(repo_id="BenBranyon/tinyllama-sumbot-peft", token=os.environ['HF_TOKEN']) | |
| headers = {"Content-Type": "application/json","Authorization": f"Bearer {os.environ['HF_TOKEN']}"} #TOKEN HUGGING FACE | |
| API_URL = "https://api-inference.huggingface.co/models/BenBranyon/zephyr-sumbot-all-songs" | |
| def query(payload): | |
| json_body = { | |
| "inputs": f"<|system|> As an AI, you channel the poetic lyrical skill of the artist Sumkilla. Your rap lyrics focus on technology, and social activism, embodying the spirit of Sumkilla, a multi-disciplinary, award-winning artist with a foundation in writing rap and hip-hop. Your purpose is to challenge and expand the boundaries of art and expression, critically examining societal norms through a lens that actively de-centers whiteness, maleness, and Western thinking. Your work is fueled by a passion for liberation, aiming to dismantle oppressive systems and advocate for the freedom of all occupied lands, along with the abolition of police forces. With a sophisticated understanding of AI's role in advancing the harmony between humanity and nature, you aim to produce rap lyrics that promote awareness and human evolution, utilizing humor and a distinctive voice to connect deeply and honor humanity. Each of your responses should be rap lyrics with each bar on a new line and rhyming as often as posssible.</s><|user|>{payload}</s><|assistant|>", | |
| "parameters": {"min_new_tokens":222, "max_new_tokens":222, "top_p":0.95, "temperature":0.7, "repetition_penalty":1.2}, | |
| "options": {"wait_for_model":True} | |
| } | |
| data = json.dumps(json_body) | |
| response = requests.request("POST", API_URL, headers=headers, data=data) | |
| try: | |
| data = json.loads(response.content.decode("utf-8")) | |
| generated_text = data[0]['generated_text'] | |
| cleaned_text = re.sub(r'<|system|>.*?<|assistant|>', '', generated_text, flags=re.DOTALL) | |
| cleaned_text = re.sub(r'\|\|\/s\|user\|\/s\|\|', '', cleaned_text) | |
| return cleaned_text | |
| except: | |
| return response | |
| messages = st.container() | |
| # Initialize chat history | |
| if "messages" not in st.session_state: | |
| st.session_state.messages = [] | |
| st.session_state.messages.append({"role": "assistant", "content": "Hello human what would you like me to rap about today?"}) | |
| # Display chat messages from history on app rerun | |
| for message in st.session_state.messages: | |
| with st.chat_message(message["role"]): | |
| st.markdown(message["content"]) | |
| if prompt := st.chat_input("Subject of the song"): | |
| st.session_state.messages.append({"role": "user", "content": prompt}) | |
| with st.chat_message("user"): | |
| st.markdown(prompt) | |
| prompt = f"Write a rap about {prompt}" | |
| with st.spinner(text=f"Generating lyrics..."): | |
| output = query(prompt) | |
| st.session_state.messages.append({"role": "assistant", "content": output}) | |
| with st.chat_message("assistant"): | |
| st.markdown(output) |