v0.8.2: fix pipeline — skip Output for tools, process HUD, inline controls, structured actions
- Thinker tool results stream directly to user, skipping Output node (halves latency) - ProcessManager process_start/process_done events render as live cards in chat - UI controls sent before response text, not after - Button clicks route to handle_action(), skip Input, go straight to Thinker - Fix Thinker model: gemini-2.5-flash-preview -> gemini-2.5-flash (old ID expired) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Nico
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@ -90,10 +90,7 @@ def register_routes(app):
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data = await ws.receive_text()
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msg = json.loads(data)
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if msg.get("type") == "action":
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action_text = f"[user clicked: {msg.get('action', 'unknown')}]"
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if msg.get("data"):
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action_text += f" data: {json.dumps(msg['data'])}"
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await runtime.handle_message(action_text)
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await runtime.handle_action(msg.get("action", "unknown"), msg.get("data"))
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elif msg.get("type") == "cancel_process":
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runtime.process_manager.cancel(msg.get("pid", 0))
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else:
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@ -14,7 +14,7 @@ log = logging.getLogger("runtime")
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class ThinkerNode(Node):
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name = "thinker"
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model = "google/gemini-2.5-flash-preview"
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model = "google/gemini-2.5-flash"
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max_context_tokens = 4000
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SYSTEM = """You are the Thinker node — the brain of this cognitive runtime.
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@ -55,6 +55,43 @@ class Runtime:
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log.error(f"trace write error: {e}")
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self._broadcast(trace_entry)
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async def _stream_text(self, text: str):
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"""Stream pre-formed text to the client as deltas, simulating LLM output."""
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# Send in chunks to feel natural
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chunk_size = 12
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for i in range(0, len(text), chunk_size):
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chunk = text[i:i + chunk_size]
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await self.ws.send_text(json.dumps({"type": "delta", "content": chunk}))
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await self.ws.send_text(json.dumps({"type": "done"}))
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async def handle_action(self, action: str, data: dict = None):
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"""Handle a structured UI action (button click etc.)."""
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# Format as a structured message that Thinker can parse
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action_desc = f"ACTION: {action}"
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if data:
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action_desc += f" | data: {json.dumps(data)}"
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# Add to history as a system-level event, not user speech
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self.history.append({"role": "user", "content": action_desc})
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self.sensor.note_user_activity()
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sensor_lines = self.sensor.get_context_lines()
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mem_ctx = self.memorizer.get_context_block(sensor_lines=sensor_lines)
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# Skip Input node — this isn't speech to perceive, go straight to Thinker
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command = Command(instruction=f"User clicked UI button: {action}", source_text=action_desc)
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thought = await self.thinker.process(command, self.history, memory_context=mem_ctx)
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if thought.controls:
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await self.ws.send_text(json.dumps({"type": "controls", "controls": thought.controls}))
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await self._stream_text(thought.response)
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self.history.append({"role": "assistant", "content": thought.response})
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await self.memorizer.update(self.history)
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if len(self.history) > self.MAX_HISTORY:
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self.history = self.history[-self.MAX_HISTORY:]
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async def handle_message(self, text: str):
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envelope = Envelope(
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text=text,
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@ -75,22 +112,23 @@ class Runtime:
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thought = await self.thinker.process(command, self.history, memory_context=mem_ctx)
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# Send controls inline (before response text)
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if thought.controls:
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await self.ws.send_text(json.dumps({"type": "controls", "controls": thought.controls}))
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if thought.tool_used:
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command = Command(
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instruction=f"Thinker used {thought.tool_used} and says: {thought.response}",
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source_text=command.source_text
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)
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# Thinker already formulated response from tool output — stream directly
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await self._stream_text(thought.response)
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response = thought.response
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else:
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# Pure conversation — Output node adds personality and streams
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command = Command(
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instruction=f"Thinker says: {thought.response}",
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source_text=command.source_text
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)
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response = await self.output_node.process(command, self.history, self.ws, memory_context=mem_ctx)
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self.history.append({"role": "assistant", "content": response})
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if thought.controls:
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await self.ws.send_text(json.dumps({"type": "controls", "controls": thought.controls}))
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self.history.append({"role": "assistant", "content": response})
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await self.memorizer.update(self.history)
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@ -170,11 +170,13 @@ function handleHud(data) {
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const detail = JSON.stringify(data.state, null, 2);
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addTrace(node, 'state', pairs, 'state', detail);
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} else if (event === 'tool_call') {
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addTrace(node, 'tool: ' + data.tool, truncate(data.code || '', 80), 'instruction', data.code);
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} else if (event === 'process_start') {
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addTrace(node, 'run ' + (data.tool || 'python'), truncate(data.code || '', 80), 'instruction', data.code);
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showProcessCard(data.pid, data.tool || 'python', data.code || '');
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} else if (event === 'tool_result') {
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addTrace(node, 'result', truncate(data.output || '', 80), '', data.output);
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} else if (event === 'process_done') {
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addTrace(node, (data.exit_code === 0 ? 'done' : 'failed'), truncate(data.output || '', 80), data.exit_code === 0 ? '' : 'error', data.output);
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updateProcessCard(data.pid, data.exit_code === 0 ? 'done' : 'failed', data.output || '', data.elapsed);
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} else if (event === 'error') {
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addTrace(node, 'error', data.detail || '', 'error');
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@ -310,6 +312,32 @@ function cancelProcess(pid) {
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}
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}
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function showProcessCard(pid, tool, code) {
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const card = document.createElement('div');
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card.className = 'process-card running';
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card.id = 'proc-' + pid;
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card.innerHTML =
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'<span class="pc-tool">' + esc(tool) + '</span>' +
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'<span class="pc-status">running</span>' +
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'<button class="pc-stop" onclick="cancelProcess(' + pid + ')">Stop</button>' +
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'<pre class="pc-code">' + esc(truncate(code, 200)) + '</pre>' +
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'<pre class="pc-output"></pre>';
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msgs.appendChild(card);
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scroll(msgs);
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}
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function updateProcessCard(pid, status, output, elapsed) {
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const card = document.getElementById('proc-' + pid);
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if (!card) return;
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card.className = 'process-card ' + status;
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const statusEl = card.querySelector('.pc-status');
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if (statusEl) statusEl.textContent = status + (elapsed ? ' (' + elapsed + 's)' : '');
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const stopBtn = card.querySelector('.pc-stop');
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if (stopBtn) stopBtn.remove();
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const outEl = card.querySelector('.pc-output');
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if (outEl && output) outEl.textContent = output;
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}
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function updateMeter(node, tokens, maxTokens, fillPct) {
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const meter = document.getElementById('meter-' + node);
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if (!meter) return;
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@ -55,6 +55,8 @@ button:hover { background: #1d4ed8; }
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.trace-node.memorizer { color: #c084fc; }
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.trace-node.thinker { color: #fb923c; }
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.trace-node.runtime { color: #60a5fa; }
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.trace-node.process { color: #f97316; }
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.trace-node.sensor { color: #60a5fa; }
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.trace-event { color: #888; flex-shrink: 0; min-width: 6rem; }
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@ -79,6 +81,7 @@ button:hover { background: #1d4ed8; }
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.pc-tool { font-weight: 700; color: #fb923c; margin-right: 0.5rem; }
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.pc-status { color: #888; margin-right: 0.5rem; }
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.pc-stop { padding: 0.15rem 0.4rem; background: #ef4444; color: white; border: none; border-radius: 0.2rem; cursor: pointer; font-size: 0.7rem; }
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.pc-code { margin-top: 0.3rem; color: #666; white-space: pre-wrap; max-height: 4rem; overflow-y: auto; font-size: 0.7rem; }
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.pc-output { margin-top: 0.3rem; color: #888; white-space: pre-wrap; max-height: 8rem; overflow-y: auto; }
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/* Expandable trace detail */
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