'
for i,(sname,icon,desc,p3) in enumerate(STAGES):
if p3: css="tn tn-phase3"
elif i
{chk}
'
f'{desc}
'
for key,em,name,role,active in SPY_AGENTS:
on = (key=="hitl" and hitl_active) or (key!="hitl" and current in active)
html += (f'
'
f'
{em}
'
f'
{name}
{role}
'
f'
')
html += '
"))
c = re.sub(r'\*\*(.+?)\*\*', r'\1', c)
if msg["role"] == "user":
msgs_html += (f'')
else:
css = "msg msg-a msg-ev" if msg.get("kind")=="ev" else "msg msg-a"
lbl = "Dr. Q — anomaly" if msg.get("kind")=="ev" else "Dr. Q"
think = msg.get("think", "")
think_html = ""
if think:
t = (think.replace("&","&").replace("<","<").replace(">",">")
.replace("\n","
"))
think_html = (
f''
f''
f'▶ Dr. Q\'s reasoning
'
f''
f'{t}
'
)
msgs_html += (f'')
st.markdown(
f''
f'
DR. Q — AI CO-PILOT{badge}
'
f'
{msgs_html}
'
f'
'
'⚛ SimQuantum
',
unsafe_allow_html=True,
)
# LLM connection — most important, top of sidebar
st.markdown(
'DR. Q — ENDPOINT
',
unsafe_allow_html=True,
)
new_url = st.text_input(
"Endpoint URL",
value=st.session_state.llm_url,
placeholder="https://api.fireworks.ai/inference/v1",
label_visibility="collapsed",
)
if new_url != st.session_state.llm_url:
st.session_state.llm_url = new_url
new_key = st.text_input(
"API Key",
value=st.session_state.llm_api_key,
placeholder="fw_xxxxxxxxxxxxxxxx",
type="password",
label_visibility="collapsed",
)
if new_key != st.session_state.llm_api_key:
st.session_state.llm_api_key = new_key
if st.session_state.llm_url:
st.markdown(
f'● connected to {st.session_state.llm_url}
',
unsafe_allow_html=True,
)
# Test button
if st.button("Test connection", use_container_width=True):
try:
import openai
url = st.session_state.llm_url.strip().rstrip("/")
api_key = st.session_state.llm_api_key.strip() or os.environ.get("QDOT_LLM_API_KEY", "EMPTY")
c = openai.OpenAI(base_url=url, api_key=api_key)
models = c.models.list()
names = [m.id for m in models.data][:3]
st.success(f"Connected ✓")
except Exception as e:
st.error(f"Failed: {e}")
else:
st.markdown(
'● offline — paste Fireworks URL + key above
',
unsafe_allow_html=True,
)
st.markdown('', unsafe_allow_html=True)
new_model = st.text_input(
"Model name",
value=st.session_state.llm_model,
label_visibility="visible",
disabled=running,
)
if new_model != st.session_state.llm_model:
st.session_state.llm_model = new_model
st.divider()
st.markdown(
'RUN CONFIGURATION
',
unsafe_allow_html=True,
)
st.session_state.use_cnn = st.toggle(
"CNN Charge Classifier", value=st.session_state.use_cnn, disabled=running)
st.session_state.meas_budget = st.slider(
"Measurement Budget", 512, 8192, st.session_state.meas_budget, 256,
disabled=running)
st.session_state.max_steps = st.slider(
"Max Steps", 10, 300, st.session_state.max_steps, 10, disabled=running)
st.divider()
if st.button("Reset session", use_container_width=True, disabled=running):
for k in ["agent","exp_state","narrator","hitl_manager","done_event","thread","chat"]:
st.session_state[k] = [] if k=="chat" else None
st.session_state.running = False
st.rerun()
st.markdown(
''
'Physics: CIM simulator (CPU)
'
'CNN: 5-model ensemble, 91.4% val acc
'
'LLM: Qwen3-8B on AMD MI300X
'
'BOOTSTRAPPING→CHARGE_ID: ✓ working
'
'NAVIGATION: Phase 3, in development'
'
',
unsafe_allow_html=True,
)
# ─────────────────────────────────────────────────────────────────────────────
# Check completion
# ─────────────────────────────────────────────────────────────────────────────
if done_event and done_event.is_set() and running:
st.session_state.running = False
running = False
if exp_state and exp_state.stage.name == "COMPLETE":
st.balloons()
# Ask Qwen for a post-run summary
already_summarised = any(m.get("kind")=="summary" for m in st.session_state.chat)
if not already_summarised and exp_state:
stage = exp_state.stage.name
meas = exp_state.total_measurements
budget = st.session_state.agent.measurement_budget if st.session_state.agent else 8096
bt = exp_state.total_backtracks
_add_msg("user",
f"The run just finished — it stopped at {stage}. "
f"{meas}/{budget} measurements used, {bt} backtracks. "
f"What happened and what should I know for the next run?")
if _llm_available():
reply = _call_qwen(
f"Post-run: stopped at {stage}, {meas}/{budget} measurements, {bt} backtracks.")
else:
reply = (f"Run stopped at {stage}. {meas}/{budget} measurements used, "
f"{bt} backtracks. Connect Qwen for a detailed analysis.")
_add_msg("assistant", reply, kind="summary")
# ─────────────────────────────────────────────────────────────────────────────
# Top bar
# ─────────────────────────────────────────────────────────────────────────────
tl,tr = st.columns([3,1])
with tl:
st.markdown(
''
'
⚛ SimQuantum Tuning Lab
'
'
Autonomous quantum dot tuning · AMD Developer Hackathon 2026 · Kudzai Musarandega
'
'
{b}
',
unsafe_allow_html=True)
# ─────────────────────────────────────────────────────────────────────────────
# Splash (pre-run)
# ─────────────────────────────────────────────────────────────────────────────
if exp_state is None:
if not st.session_state.chat:
if _llm_available():
# Let Qwen introduce itself
_add_msg("user", "Hello, introduce yourself briefly.")
intro = _call_qwen("Hello, introduce yourself briefly.")
_add_msg("assistant", intro)
else:
_add_msg("assistant",
"Ready. Set the vLLM endpoint in the sidebar to enable Qwen.\n\n"
"Type **start** to begin a tuning run, or ask me about the experiment.")
sl,sr = st.columns([3,2], gap="large")
with sl:
st.markdown("""
What this system does
SimQuantum autonomously tunes a double quantum dot device to the
(1,1) charge state — one electron per dot — required
for spin qubit operation. 6-stage POMDP planner, 5-model CNN ensemble
(91.4% val acc), Bayesian optimisation. Qwen3-8B on AMD MI300X
acts as Dr. Q — ask it anything, in any register.
Reading a stability diagram
Conductance G vs gate voltages (Vg₁, Vg₂).
Bright lines = Coulomb peaks (charge transitions).
Dark regions = Coulomb blockade (fixed electron number).
Intersections form a honeycomb: (0,0), (1,0), (0,1), (1,1)…
The agent navigates to the (1,1) diamond.
""", unsafe_allow_html=True)
img_path = Path(__file__).parent/"assets"/"simquantum.png"
if img_path.exists():
st.image(str(img_path), use_container_width=True)
with sr:
_render_chat()
# ─────────────────────────────────────────────────────────────────────────────
# Live dashboard
# ─────────────────────────────────────────────────────────────────────────────
else:
agent = st.session_state.agent
hitl_mgr = st.session_state.hitl_manager
current_stg = exp_state.stage.name
_timeline(current_stg, done_event)
_kpi(exp_state, agent)
pct = min(100, int(100*exp_state.total_measurements/agent.measurement_budget))
st.progress(pct/100, text=f"Measurement budget {pct}%")
pending = hitl_mgr.get_pending() if hitl_mgr else []
if pending:
req = pending[0]
st.markdown(
f''
f'
⚠ HITL GATE — Human approval required
'
f'
Step {req["step"]} · Stage {req["stage"]} · '
f'Risk {req["risk_score"]:.2f}
{req["trigger_reason"]}
'
f'
Charge Stability Diagram
',
unsafe_allow_html=True)
st.plotly_chart(_fig_stability(exp_state),use_container_width=True,
config={"displayModeBar":False},key=f"s_{time.monotonic_ns()}")
if exp_state.last_classification:
cls = exp_state.last_classification
ood_col = "#C84B00" if exp_state.is_ood else "#00897B"
ood_txt = "OOD warning" if exp_state.is_ood else "in-distribution"
st.markdown(
f'CNN Classification'
f'{ood_txt}
'
f'{cls.label.value.upper()}'
f''
f'conf {cls.confidence:.1%}
',
unsafe_allow_html=True)
bc1,bc2 = st.columns(2)
with bc1:
st.plotly_chart(_fig_belief(exp_state),use_container_width=True,
config={"displayModeBar":False},key=f"b_{time.monotonic_ns()}")
with bc2:
ft = _fig_traj(exp_state)
if ft:
st.plotly_chart(ft,use_container_width=True,
config={"displayModeBar":False},key=f"t_{time.monotonic_ns()}")
st.markdown('Agent Activity
',
unsafe_allow_html=True)
_spy(current_stg, bool(pending))
img_path = Path(__file__).parent/"assets"/"simquantum.png"
if img_path.exists():
st.image(str(img_path),use_container_width=True)
with right:
_render_chat()
if current_stg in STAGE_DESC:
desc,cost = STAGE_DESC[current_stg]
st.markdown(
f''
f'
Current stage · {current_stg}
'
f'
{desc}
'
f'
Budget: {cost}
'
f'
'
f'
{txt}
'
f'
'
f'Measurements: {exp_state.total_measurements}'
f'Steps: {agent.control_steps}'
f'Backtracks: {exp_state.total_backtracks}'
f'Reduction: {red:.0%}'
f'