M3: chat widget, owner dashboard, super-admin panel

- Embeddable vanilla-JS chat widget (one script tag + tenant public key):
  WebSocket, resumable sessions (24h localStorage token), honeypot + per-IP
  and per-message rate limits, Bosnian UI (§7)
- Session auth (bcrypt + signed cookies), owner accounts + super-admins,
  admin impersonation ('otvori kao salon', §11)
- Owner dashboard (§10, Bosnian): requests with same actions as email,
  call/chat history with transcripts, usage bar; settings for profile,
  working hours (manual + LLM paste-to-parse), services CRUD + 'Zalijepi
  cjenovnik' LLM import with review step, scheduling (Google OAuth free/busy
  read-only + calendar mappings + buffers, partner status), telephony
  (forwarding MMI codes per operator, ring group, worker SIP creds + QR),
  agent voice/price-mode/notes + widget snippet, notifications/SMS templates
- Super-admin panel (§11): tenant CRUD incl. plan/minutes/paid-until,
  partner API config (encrypted secrets), number/SIM registry + assignment,
  connectivity test (live availability + dry-run push), versioned prompt
  template editor with publish/rollback, playground, usage overview, health
- Fixes: WAL + busy_timeout for sqlite tests, no awaits in WS disconnect
  path (deadlock), template publish autoflush bug
- 76 tests green (incl. widget WS e2e booking flow); dashboard, widget and
  admin verified live in a browser against Postgres

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

gogo/dashboard/parse.py

@@ -0,0 +1,125 @@
+"""'Zalijepi cjenovnik' paste-to-parse (§10.2): LLM turns a free-text price list
+(from a website, Word, Facebook…) into structured services the owner reviews.
+Same approach for working hours."""
+
+from __future__ import annotations
+
+import json
+import logging
+
+from gogo.agent.llm import LLMProvider, get_llm
+
+log = logging.getLogger("gogo.parse")
+
+_SERVICES_TOOL = {
+    "name": "save_services",
+    "description": "Save the parsed price list as structured services.",
+    "input_schema": {
+        "type": "object",
+        "properties": {
+            "services": {
+                "type": "array",
+                "items": {
+                    "type": "object",
+                    "properties": {
+                        "name": {"type": "string"},
+                        "duration_min": {
+                            "type": "integer",
+                            "description": "estimate a realistic duration if not stated",
+                        },
+                        "price_min": {"type": "number"},
+                        "price_max": {
+                            "type": "number",
+                            "description": "same as price_min when a single price",
+                        },
+                        "home_visit": {"type": "boolean", "default": False},
+                        "note": {"type": "string"},
+                    },
+                    "required": ["name", "duration_min"],
+                },
+            }
+        },
+        "required": ["services"],
+    },
+}
+
+_HOURS_TOOL = {
+    "name": "save_hours",
+    "description": "Save the parsed working hours.",
+    "input_schema": {
+        "type": "object",
+        "properties": {
+            day: {
+                "type": "array",
+                "description": f"open intervals for {day} as [\"HH:MM\",\"HH:MM\"] pairs; empty if closed",
+                "items": {
+                    "type": "array",
+                    "items": {"type": "string"},
+                    "minItems": 2,
+                    "maxItems": 2,
+                },
+            }
+            for day in ["mon", "tue", "wed", "thu", "fri", "sat", "sun"]
+        },
+        "required": ["mon", "tue", "wed", "thu", "fri", "sat", "sun"],
+    },
+}
+
+
+async def parse_price_list(text: str, llm: LLMProvider | None = None) -> list[dict]:
+    """Returns a list of service dicts for the owner to review (never saved directly)."""
+    llm = llm or get_llm()
+    response = await llm.complete(
+        system=(
+            "You parse beauty-salon price lists written in Bosnian/Serbian/Croatian "
+            "into structured data. Prices are in KM (BAM). A range like '60-90 KM' "
+            "means price_min=60, price_max=90. Estimate realistic durations when "
+            "missing (šišanje ~45, farbanje ~90, manikir ~45, pedikir ~60, "
+            "depilacija ~30 minutes). Set home_visit only when the text explicitly "
+            "mentions coming to the client's home. Keep names as written (fix only "
+            "obvious typos). Call save_services exactly once."
+        ),
+        messages=[{"role": "user", "content": text[:8000]}],
+        tools=[_SERVICES_TOOL],
+        max_tokens=4096,
+    )
+    for tu in response.tool_uses:
+        if tu.name == "save_services":
+            return list(tu.input.get("services", []))
+    log.warning("price-list parse produced no tool call")
+    return []
+
+
+async def parse_working_hours(text: str, llm: LLMProvider | None = None) -> dict | None:
+    llm = llm or get_llm()
+    response = await llm.complete(
+        system=(
+            "You parse salon working hours written in Bosnian/Serbian/Croatian into "
+            "structured JSON. 'pon-pet 9-18' means mon..fri [[\"09:00\",\"18:00\"]]. "
+            "'pauza 13-14' splits the day into two intervals. Closed days get []. "
+            "Call save_hours exactly once."
+        ),
+        messages=[{"role": "user", "content": text[:2000]}],
+        tools=[_HOURS_TOOL],
+        max_tokens=2048,
+    )
+    for tu in response.tool_uses:
+        if tu.name == "save_hours":
+            hours = {k: tu.input.get(k, []) for k in
+                     ["mon", "tue", "wed", "thu", "fri", "sat", "sun"]}
+            return _validate_hours(hours)
+    return None
+
+
+def _validate_hours(hours: dict) -> dict | None:
+    try:
+        for _day, intervals in hours.items():
+            for iv in intervals:
+                a, b = iv
+                for t in (a, b):
+                    h, m = t.split(":")
+                    assert 0 <= int(h) <= 23 and 0 <= int(m) <= 59
+        return hours
+    except (ValueError, AssertionError, TypeError):
+        log.warning("parsed hours failed validation: %s", json.dumps(hours)[:200])
+        return None