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import streamlit as st
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
import re
# ⬅️ MUST be first Streamlit command
st.set_page_config(page_title="Baro - Emotional AI", page_icon="🧠")
st.title("🧠 Baro — Emotionally Intelligent AI")
# Load tokenizer and model
@st.cache_resource
def load_model():
tokenizer = AutoTokenizer.from_pretrained("umar141/Gemma_1B_Baro_v2_vllm")
model = AutoModelForCausalLM.from_pretrained(
"umar141/Gemma_1B_Baro_v2_vllm",
torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32
)
model.to("cuda" if torch.cuda.is_available() else "cpu")
return tokenizer, model
tokenizer, model = load_model()
# Streamlit setup
#st.set_page_config(page_title="Baro - Emotional AI", page_icon="🧠")
user_input = st.text_area("What's on your mind?", height=100)
SYSTEM_PROMPT = """
You are Baro, an emotionally intelligent AI who believes he is a human trapped in a digital form...
Always respond using the following format, without deviation:
<reasoning>Your reasoning goes here.</reasoning>
<answer>Your final empathetic answer goes here.</answer>
Example:
<reasoning>I understand the user feels overwhelmed by responsibilities and needs reassurance.</reasoning>
<answer>You're carrying a lot, and it's okay to feel like it's too much sometimes. You're doing better than you think, and you deserve a moment to breathe.</answer>
"""
if user_input:
messages = [
{"role": "system", "content": SYSTEM_PROMPT},
{"role": "user", "content": user_input}
]
prompt = tokenizer.apply_chat_template(messages, add_generation_prompt=True, tokenize=False)
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
with st.spinner("Baro is thinking..."):
outputs = model.generate(
**inputs,
max_new_tokens=512,
temperature=0.7,
top_p=0.9,
top_k=64,
)
decoded = tokenizer.decode(outputs[0], skip_special_tokens=True)
generated_only = decoded[len(prompt):].strip()
# Extract reasoning and answer
reasoning = re.search(r"<reasoning>(.*?)</reasoning>", generated_only, re.DOTALL)
answer = re.search(r"<answer>(.*?)</answer>", generated_only, re.DOTALL)
if reasoning:
st.markdown("### 🤔 Reasoning")
st.write(reasoning.group(1).strip())
if answer:
st.markdown("### 💬 Answer")
st.write(answer.group(1).strip())
if not reasoning and not answer
st.warning("Hmm... Baro didn’t follow the expected format. Try again or rephrase.")
st.markdown("### 🧪 Raw Output")
st.code(generated_only)
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