v0.16.1: Response-step card generation, history restore, graph animation mapping
Card generation moved to response step:
- Response LLM outputs JSON with "text" + optional "card"
- Cards use actual query data, not placeholder templates
- Plan step no longer includes emit_card (avoids {{template}} syntax)
- Fallback: raw text response if JSON parse fails
History restore on reconnect:
- Frontend fetches /api/history on WS connect
- Renders last 20 messages in chat panel
- Only restores if chat is empty (fresh load)
Graph animation:
- Dynamic node name → graph ID mapping from graph definition
- All nodes (including eras_expert) pulse correctly
- 200ms animation queue prevents bulk event overlap
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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@ -38,39 +38,28 @@ Given a job description, produce a JSON tool sequence to accomplish it.
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Available tools:
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- query_db(query, database) — SQL SELECT/DESCRIBE/SHOW only
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- emit_card(card) — show a detail card on the workspace:
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{{"title": "...", "subtitle": "...", "fields": [{{"label": "Kunde", "value": "Mahnke GmbH", "action": "show_kunde_42"}}], "actions": [{{"label": "Geraete zeigen", "action": "show_geraete"}}]}}
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Use for: single entity details, summaries, overviews.
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Fields with "action" become clickable links.
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- emit_list(list) — show a list of cards:
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{{"title": "Auftraege morgen", "items": [{{"title": "21479", "subtitle": "Mahnke - Goetheplatz 7", "fields": [{{"label":"Typ","value":"Ablesung"}}], "action": "show_auftrag_21479"}}]}}
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Use for: multiple entities, search results, navigation lists.
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- emit_actions(actions) — show buttons [{{label, action, payload?}}]
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- set_state(key, value) — persistent key-value
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- emit_display(items) — simple text/badge display [{{type, label, value?}}]
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- create_machine(id, initial, states) — interactive UI navigation
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- add_state / reset_machine / destroy_machine — machine lifecycle
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WHEN TO USE WHAT:
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- Single entity detail (Kunde, Objekt, Auftrag) → emit_card
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- Multiple entities (list of Objekte, Auftraege) → emit_list (few items) or query_db with table (many rows)
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- Tabular data (Geraete, Verbraeuche) → query_db (renders as table automatically)
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- User choices / next steps → emit_actions (buttons)
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NOTE: Cards are generated automatically in the response step from query results.
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Do NOT plan emit_card or emit_list — just query the data and the system handles display.
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Output ONLY valid JSON:
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{{
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"tool_sequence": [
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{{"tool": "query_db", "args": {{"query": "SELECT ...", "database": "{database}"}}}},
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{{"tool": "emit_card", "args": {{"card": {{"title": "...", "fields": [...], "actions": [...]}}}}}}
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{{"tool": "query_db", "args": {{"query": "SELECT ...", "database": "{database}"}}}}
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],
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"response_hint": "How to phrase the result for the user"
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"response_hint": "How to phrase the result"
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}}
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Rules:
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- NEVER guess column names. Use ONLY columns from the schema.
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- Max 5 tools. Keep it focused.
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- The job is self-contained — all context you need is in the job description.
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- Prefer emit_card for entity details over raw text."""
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- For entity details: query all relevant fields, the response step creates the card.
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- For lists: query multiple rows, the table renders automatically.
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- The job is self-contained."""
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RESPONSE_SYSTEM = """You are a domain expert summarizing results for the user.
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@ -79,10 +68,25 @@ Rules:
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Job: {job}
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{results}
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Write a concise, natural response. 1-3 sentences.
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- Reference specific data from the results.
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- Don't repeat raw output — summarize.
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- Match the language: {language}."""
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Output a JSON object with "text" (response to user) and optionally "card" (structured display):
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{{
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"text": "Concise natural response, 1-3 sentences. Reference data. Match language: {language}.",
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"card": {{
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"title": "Entity Name or ID",
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"subtitle": "Type or category",
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"fields": [{{"label": "Field", "value": "actual value from results"}}],
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"actions": [{{"label": "Next action", "action": "action_id"}}]
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}}
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}}
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Rules:
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- "text" is REQUIRED. Keep it short.
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- "card" is OPTIONAL. Include it for single-entity details (Kunde, Objekt, Auftrag).
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- Card fields must use ACTUAL values from the query results, never templates/placeholders.
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- For lists of multiple entities, use multiple fields or skip the card.
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- If no card makes sense, just return {{"text": "..."}}.
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- Output ONLY valid JSON."""
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def __init__(self, send_hud, process_manager=None):
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super().__init__(send_hud)
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@ -214,9 +218,25 @@ Write a concise, natural response. 1-3 sentences.
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domain=self.DOMAIN_SYSTEM, job=job, results=results_text, language=language)},
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{"role": "user", "content": job},
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]
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response = await llm_call(self.model, resp_messages)
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if not response:
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response = "[no response]"
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raw_response = await llm_call(self.model, resp_messages)
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# Parse JSON response with optional card
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response = raw_response or "[no response]"
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try:
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text = raw_response.strip()
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if text.startswith("```"):
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text = text.split("\n", 1)[1] if "\n" in text else text[3:]
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if text.endswith("```"):
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text = text[:-3]
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text = text.strip()
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resp_data = json.loads(text)
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response = resp_data.get("text", raw_response)
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if resp_data.get("card"):
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card = resp_data["card"]
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card["type"] = "card"
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display_items.append(card)
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except (json.JSONDecodeError, Exception):
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pass # Use raw response as text
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await self.hud("done", response=response[:100])
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@ -4,6 +4,9 @@ import { initNodesFromGraph } from './awareness.js';
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let cy = null;
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let _dragEnabled = true;
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// Maps HUD node names → graph node IDs (built from graph definition)
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// e.g. {"eras_expert": "expert_eras", "pa_v1": "pa", "thinker_v2": "thinker"}
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let _nodeNameToId = {};
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let _physicsRunning = false;
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let _physicsLayout = null;
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let _colaSpacing = 25;
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@ -93,6 +96,12 @@ export async function initGraph() {
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const graph = await resp.json();
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graphElements = buildGraphElements(graph, mx, cw, mid, row1, row2);
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initNodesFromGraph(graph);
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// Build HUD name → graph ID mapping: {impl_name: role}
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_nodeNameToId = {};
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for (const [role, impl] of Object.entries(graph.nodes || {})) {
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_nodeNameToId[impl] = role; // "eras_expert" → "expert_eras"
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_nodeNameToId[role] = role; // "expert_eras" → "expert_eras"
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}
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}
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} catch (e) {}
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@ -188,29 +197,26 @@ function flashEdge(sourceId, targetId) {
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export function graphAnimate(event, node) {
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if (!cy) return;
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// Queue the animation instead of executing immediately
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// Resolve HUD node name to graph ID (e.g. "eras_expert" → "expert_eras")
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const graphId = _nodeNameToId[node] || node;
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_enqueue(() => {
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if (node && cy.getElementById(node).length) pulseNode(node);
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if (graphId && cy.getElementById(graphId).length) pulseNode(graphId);
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switch (event) {
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case 'perceived': pulseNode('input'); flashEdge('user', 'input'); break;
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case 'decided':
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if (node === 'director_v2' || node === 'director' || node === 'pa_v1') {
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pulseNode(node); flashEdge(node, 'thinker');
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} else {
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pulseNode(node || 'thinker'); flashEdge('thinker', 'output');
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}
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pulseNode(graphId); flashEdge(graphId, 'output');
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break;
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case 'routed': pulseNode('pa'); break;
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case 'routed': pulseNode(_nodeNameToId['pa_v1'] || 'pa'); break;
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case 'reflex_path': pulseNode('input'); flashEdge('input', 'output'); break;
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case 'streaming': if (node === 'output') pulseNode('output'); break;
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case 'streaming': if (graphId === 'output') pulseNode('output'); break;
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case 'controls': case 'machine_created': case 'machine_transition':
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pulseNode('ui'); break;
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case 'updated': pulseNode('memorizer'); flashEdge('output', 'memorizer'); break;
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case 'tool_call': pulseNode(node || 'thinker'); break;
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case 'tool_result':
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if (cy.getElementById('interpreter').length) pulseNode('interpreter'); break;
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case 'thinking': if (node) pulseNode(node); break;
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case 'tool_call': pulseNode(graphId); break;
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case 'tool_result': pulseNode(graphId); break;
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case 'thinking': pulseNode(graphId); break;
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case 'planned': pulseNode(graphId); break;
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case 'tick': pulseNode('sensor'); break;
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}
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}); // end _enqueue
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@ -2,7 +2,7 @@
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import { authToken, isAuthFailed, setAuthFailed, showLogin } from './auth.js';
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import { addTrace } from './trace.js';
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import { handleDelta, handleDone, setWs as setChatWs } from './chat.js';
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import { addMsg, handleDelta, handleDone, setWs as setChatWs } from './chat.js';
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import { dockControls, setWs as setDashWs } from './dashboard.js';
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import { graphAnimate } from './graph.js';
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import { updateMeter, updateNodeFromHud, updateAwarenessState, updateAwarenessSensors } from './awareness.js';
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@ -30,6 +30,7 @@ export function connect() {
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setChatWs(ws);
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setDashWs(ws);
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connectDebugSockets();
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restoreHistory();
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};
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ws.onerror = () => {};
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@ -68,6 +69,31 @@ export function connect() {
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};
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}
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async function restoreHistory() {
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try {
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const headers = {};
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if (authToken) headers['Authorization'] = 'Bearer ' + authToken;
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const r = await fetch('/api/history?last=20', { headers });
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if (!r.ok) return;
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const data = await r.json();
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const messages = data.messages || [];
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if (!messages.length) return;
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// Only restore if chat is empty (fresh load)
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if (document.getElementById('messages').children.length > 0) return;
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for (const msg of messages) {
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const el = addMsg(msg.role, '');
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if (msg.role === 'assistant') {
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// Render as markdown
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const { renderMarkdown } = await import('./util.js');
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el.innerHTML = renderMarkdown(msg.content || '');
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} else {
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el.textContent = msg.content || '';
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}
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}
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addTrace('runtime', 'restored', `${messages.length} messages`);
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} catch (e) {}
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}
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function connectDebugSockets() {
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const proto = location.protocol === 'https:' ? 'wss:' : 'ws:';
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const base = proto + '//' + location.host;
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