app.py

import streamlit as st
from agent_engine import run_agent
from llm_client import DEFAULT_MODEL, DEFAULT_PROVIDER, call_llm   # this file changes per tab below

st.set_page_config(page_title="Agentic AI Lab", page_icon="🤖")
st.title("🤖 Agentic AI Demo")

hf_token = st.text_input("Hugging Face token", type="password")
model = st.text_input("Model", value=DEFAULT_MODEL)
providers = ["auto", "novita", "together", "fireworks-ai", "zai-org", "baseten", "deepinfra", "hf-inference"]
provider = st.selectbox("Provider", providers, index=providers.index(DEFAULT_PROVIDER))
query = st.text_input("Ask the agent (try: 'what is 45*12, then word-count the answer as text')")

if st.button("Run agent") and query:
    box = st.container()
    def log(step, thought, action, action_input):
        box.markdown(f"**Step {step}** — _{thought}_  \n`{action}({action_input})`")
    try:
        answer, _ = run_agent(
            query,
            lambda prompt: call_llm(prompt, token=hf_token, model=model, provider=provider),
            log=log,
        )
        st.success(answer)
    except RuntimeError as error:
        st.error(str(error))