providers: presets for polza/openai/ollama (--provider), keys from env, gpt-5.6-luna default for polza, multimodal heuristic for cloud ids

.playwright-mcp/console-2026-08-08T09-11-01-487Z.log

@@ -7505,3 +7505,56 @@
 [28512300ms] [ERROR] WebSocket connection to 'ws://127.0.0.1:8001/' failed: Error in connection establishment: net::ERR_CONNECTION_REFUSED @ http://127.0.0.1:8000/:40
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testbed/chat.py

@@ -32,11 +32,14 @@ import sys
 from aicc.client import AICCClient
 from aicc.transport.websocket import WebSocketClientTransport
 
-from testbed.llm_agent import CHAT_MISSION, LLMController, ollama_models
+from testbed.llm_agent import (
+    CHAT_MISSION,
+    LLMController,
+    ollama_models,
+    resolve_provider,
+)
 
 DEFAULT_URL = "ws://127.0.0.1:8765"
-DEFAULT_BASE_URL = "http://localhost:11434/v1"
-DEFAULT_MODEL = "gemma4:e2b"
 
 HELP = """\
 You are talking to the capsule's brain (LLM). Type what you want, e.g.:
@@ -393,12 +396,26 @@ def main() -> int:
         help=f"bridge WebSocket URL (default {DEFAULT_URL})",
     )
     parser.add_argument(
-        "--base-url", default=DEFAULT_BASE_URL, help="OpenAI-compatible endpoint"
+        "--base-url",
+        default=None,
+        help="OpenAI-compatible endpoint (default per --provider)",
     )
     parser.add_argument(
-        "--model", default=DEFAULT_MODEL, help="model id on the endpoint"
+        "--provider",
+        choices=["polza", "openai", "ollama"],
+        default=None,
+        help="provider preset: endpoint + key from env (POLZA_API_KEY/OPENAI_API_KEY)",
+    )
+    parser.add_argument(
+        "--model",
+        default=None,
+        help="model id on the endpoint (default per provider: polza -> openai/gpt-5.6-luna)",
+    )
+    parser.add_argument(
+        "--api-key",
+        default=None,
+        help="API key (default: $POLZA_API_KEY / $OPENAI_API_KEY per provider)",
     )
-    parser.add_argument("--api-key", default="ollama", help="API key for the endpoint")
     parser.add_argument(
         "--auto-steps",
         type=int,
@@ -447,6 +464,18 @@ def main() -> int:
         help="attach a fresh camera frame every N turns (0 disables; default 3)",
     )
     args = parser.parse_args()
+    try:
+        args.base_url, args.api_key, args.model = resolve_provider(
+            provider=args.provider,
+            base_url=args.base_url,
+            api_key=args.api_key,
+            model=args.model,
+        )
+        if args.provider:
+            print(f"[chat] provider: {args.provider} -> {args.base_url}  model: {args.model}")
+    except ValueError as exc:
+        print(f"[chat] {exc}")
+        return 1
     try:
         return asyncio.run(run(args))
     except KeyboardInterrupt:

testbed/demo.py

@@ -37,9 +37,9 @@ from aicc.protocol import SessionInit
 from aicc.transport.websocket import WebSocketClientTransport
 from PIL import Image
 
+from testbed.llm_agent import resolve_provider
+
 DEFAULT_URL = "ws://127.0.0.1:8765"
-DEFAULT_BASE_URL = "http://localhost:11434/v1"
-DEFAULT_MODEL = "gemma4:e2b"
 
 
 class FrameRecorder:
@@ -392,12 +392,26 @@ def main() -> int:
         help="agent driver (default auto: LLM if reachable, else scripted)",
     )
     parser.add_argument(
-        "--base-url", default=DEFAULT_BASE_URL, help="OpenAI-compatible endpoint"
+        "--base-url",
+        default=None,
+        help="OpenAI-compatible endpoint (default per --provider)",
     )
     parser.add_argument(
-        "--model", default=DEFAULT_MODEL, help="model id on the endpoint"
+        "--provider",
+        choices=["polza", "openai", "ollama"],
+        default=None,
+        help="provider preset: endpoint + key from env (POLZA_API_KEY/OPENAI_API_KEY)",
+    )
+    parser.add_argument(
+        "--model",
+        default=None,
+        help="model id on the endpoint (default per provider: polza -> openai/gpt-5.6-luna)",
+    )
+    parser.add_argument(
+        "--api-key",
+        default=None,
+        help="API key (default: $POLZA_API_KEY / $OPENAI_API_KEY per provider)",
     )
-    parser.add_argument("--api-key", default="ollama", help="API key for the endpoint")
     parser.add_argument("--max-steps", type=int, default=60, help="max agent steps")
     parser.add_argument(
         "--vision",
@@ -429,6 +443,18 @@ def main() -> int:
         "into this directory, plus demo.gif animation and demo_summary.png",
     )
     args = parser.parse_args()
+    try:
+        args.base_url, args.api_key, args.model = resolve_provider(
+            provider=args.provider,
+            base_url=args.base_url,
+            api_key=args.api_key,
+            model=args.model,
+        )
+        if args.provider:
+            print(f"[demo] provider: {args.provider} -> {args.base_url}  model: {args.model}")
+    except ValueError as exc:
+        print(f"[demo] {exc}")
+        return 1
     try:
         summary = asyncio.run(run_demo(args))
     except KeyboardInterrupt:

testbed/llm_agent.py

@@ -67,6 +67,97 @@ NUDGE = (
     "then call a tool (turn or move, or interact if within 1.6 m)."
 )
 
+# ---------------------------------------------------------------------------
+# Provider presets (OpenAI-compatible endpoints)
+# ---------------------------------------------------------------------------
+
+PROVIDERS: dict[str, dict[str, str | None]] = {
+    "polza": {
+        "base_url": "https://polza.ai/api/v1",
+        "env_key": "POLZA_API_KEY",
+        "default_model": "openai/gpt-5.6-luna",
+    },
+    "openai": {
+        "base_url": "https://api.openai.com/v1",
+        "env_key": "OPENAI_API_KEY",
+        "default_model": "gpt-4o-mini",
+    },
+    "ollama": {
+        "base_url": "http://localhost:11434/v1",
+        "env_key": None,
+        "default_model": "gemma4:e2b",
+    },
+}
+
+# Best-effort multimodal detection for non-ollama providers (no way to
+# introspect remotely): ids carrying these markers usually accept images.
+_MULTIMODAL_HINTS = (
+    "gpt-4o",
+    "gpt-4.1",
+    "gpt-5",
+    "gemma",
+    "gemini",
+    "claude",
+    "vl-",
+    "vision",
+    "luna",
+)
+
+
+def resolve_provider(
+    *,
+    provider: str | None,
+    base_url: str | None,
+    api_key: str | None,
+    model: str | None,
+) -> tuple[str, str, str]:
+    """Resolve endpoint + key + model from a provider preset (or explicit args).
+
+    Keys come from the environment (POLZA_API_KEY / OPENAI_API_KEY) so nothing
+    secret lives in the repo or on the command line.
+    """
+    import os
+
+    if provider:
+        preset = PROVIDERS.get(provider)
+        if preset is None:
+            raise ValueError(
+                f"unknown provider {provider!r}; available: {', '.join(PROVIDERS)}"
+            )
+        base_url = preset["base_url"]
+        if model is None:
+            model = preset["default_model"]
+        env_key = preset["env_key"]
+        if api_key is None and env_key:
+            api_key = os.environ.get(env_key)
+        if api_key is None:
+            raise ValueError(
+                f"provider {provider!r} needs an API key: set ${env_key} "
+                "(see https://polza.ai/dashboard/api-keys)"
+            )
+    else:
+        base_url = base_url or str(PROVIDERS["ollama"]["base_url"])
+        model = model or str(PROVIDERS["ollama"]["default_model"])
+        if api_key is None:
+            host = base_url.replace("http://", "").replace("https://", "").split("/")[0]
+            if "polza" in host:
+                api_key = os.environ.get("POLZA_API_KEY")
+                if not api_key:
+                    raise ValueError("set $POLZA_API_KEY (polza.ai/dashboard/api-keys)")
+            elif "openai" in host:
+                api_key = os.environ.get("OPENAI_API_KEY")
+                if not api_key:
+                    raise ValueError("set $OPENAI_API_KEY")
+            else:
+                api_key = "ollama"  # local ollama ignores the key
+    return base_url, api_key, model
+
+
+def looks_multimodal(model: str) -> bool:
+    low = model.lower()
+    return any(h in low for h in _MULTIMODAL_HINTS)
+
+
 COLOR_NAMES = [
     ("beacon_cyan", (120, 210, 235)),
     ("beacon_yellow", (255, 190, 90)),
@@ -236,7 +327,7 @@ class LLMController:
         self.client = client
         self.model = model
         if multimodal is None:
-            multimodal = detect_multimodal(base_url, model)
+            multimodal = looks_multimodal(model) or detect_multimodal(base_url, model)
         self.multimodal = multimodal
         # The color-grid digest is the fallback channel for text-only models.
         # For multimodal models it is off unless explicitly requested.