Import AITURK IDE 1.0.0-beta.1 from Hermes 63279301; preserve MIT license

plugins/model-providers/meta-ai/__init__.py

@@ -0,0 +1,141 @@
+"""Meta Model API (Muse Spark) provider plugin for Hermes Agent.
+
+Provider profile for Meta Superintelligence Labs' Muse Spark family, served
+via the OpenAI-compatible Meta Model API at ``https://api.meta.ai/v1``.
+
+Bundled from https://github.com/albertodepaola/hermes-meta-provider. Hermes'
+provider discovery (``providers/__init__.py``) imports it on first
+``get_provider_profile()`` / ``list_providers()`` call, and the module-level
+``register_provider()`` below wires it into the registry.
+
+Design notes
+------------
+* **Zero core edits.** Everything rides on ``ProviderProfile`` hooks. No changes
+  to hermes' ``model_metadata.py`` / ``models.py`` / ``run_agent.py`` are needed:
+  - Context window (1M), reasoning and vision capabilities already resolve from
+    models.dev for the muse-spark family, so no static ctx table entry is required.
+  - The reasoning dial is emitted as a **top-level ``reasoning_effort``** kwarg
+    (returned in the ``top_level`` slot of ``build_api_kwargs_extras``), which the
+    chat-completions transport merges unconditionally. This deliberately avoids
+    the ``extra_body.reasoning`` path, whose emission is gated by a hardcoded
+    host allowlist in core (``AIAgent._supports_reasoning_extra_body``) that a
+    third-party plugin must not edit.
+* **Meta 400 on ``reasoning_effort: "none"``.** Muse rejects ``none``; disabling
+  reasoning maps to ``"minimal"`` instead.
+* **``default_max_tokens=16384``.** Muse spends completion budget on hidden
+  reasoning tokens first; small caps can finish with empty content.
+"""
+
+from __future__ import annotations
+
+import os
+from typing import Any
+
+from providers import register_provider
+from providers.base import ProviderProfile
+
+
+def _resolve_effort(reasoning_config: dict | None) -> str:
+    """Map Hermes' reasoning_config to a Meta-safe ``reasoning_effort`` value.
+
+    Meta's vocabulary (minimal..xhigh; rejects ``none``) is declared in
+    agent.reasoning_effort. Disabled/"none" maps to ``minimal`` (the closest
+    Meta has to off); unset/bespoke levels fall to ``medium``.
+    """
+    rc = reasoning_config or {}
+    if rc.get("enabled") is False:
+        return "minimal"
+    effort = str(rc.get("effort") or "").strip().lower()
+    if effort in {"", "none"}:
+        return "minimal" if effort == "none" else "medium"
+
+    from agent.reasoning_effort import META_AI_EFFORTS, clamp_effort
+
+    clamped = clamp_effort(effort, META_AI_EFFORTS)
+    return clamped if clamped in META_AI_EFFORTS else "medium"
+
+
+class MetaAIProfile(ProviderProfile):
+    """Meta Model API — top-level reasoning_effort, self-contained."""
+
+    # Non-chat model prefixes excluded from the agent picker.  The live
+    # /v1/models catalog includes image-generation and transcription models
+    # that are not suitable for agentic chat.
+    _NON_CHAT_PREFIXES = ("muse-image-", "muse-voice-")
+
+    def fetch_models(
+        self,
+        *,
+        api_key: str | None = None,
+        base_url: str | None = None,
+        timeout: float = 8.0,
+    ) -> list[str] | None:
+        """Fetch and filter the live catalog, excluding non-chat models."""
+        live = super().fetch_models(api_key=api_key, base_url=base_url, timeout=timeout)
+        if live is None:
+            return None
+        return [
+            m for m in live
+            if not any(m.startswith(p) for p in self._NON_CHAT_PREFIXES)
+        ]
+
+    def build_api_kwargs_extras(
+        self,
+        *,
+        reasoning_config: dict | None = None,
+        supports_reasoning: bool = False,  # noqa: ARG002 — we self-gate below
+        **context: Any,
+    ) -> tuple[dict[str, Any], dict[str, Any]]:
+        """Emit ``reasoning_effort`` as a top-level api kwarg.
+
+        We ignore the core ``supports_reasoning`` gate on purpose: that flag is
+        driven by a host allowlist in core we cannot (and should not) edit from
+        an out-of-tree plugin. Muse Spark always accepts ``reasoning_effort``,
+        so we resolve it from ``reasoning_config`` directly.
+        """
+        return {}, {"reasoning_effort": _resolve_effort(reasoning_config)}
+
+
+def _base_url() -> str:
+    """Allow a base-URL override via ``META_BASE_URL`` without editing config."""
+    return os.getenv("META_BASE_URL", "").strip() or "https://api.meta.ai/v1"
+
+
+meta_ai = MetaAIProfile(
+    name="meta-ai",
+    aliases=("meta", "muse", "muse-spark", "model-api", "msl"),
+    display_name="Meta Model API",
+    description="Meta Muse Spark family (Meta Superintelligence Labs)",
+    signup_url="https://developer.meta.com/ai/",
+    # MODEL_API_KEY is Meta's documented env var; the aliases are conveniences.
+    env_vars=("MODEL_API_KEY", "META_API_KEY", "META_MODEL_API_KEY", "META_BASE_URL"),
+    base_url=_base_url(),
+    auth_type="api_key",
+    # Responses API is the wire that engages Muse prompt caching: measured
+    # 0 cached tokens on /v1/chat/completions vs 93-99% cache hits on
+    # /v1/responses with prompt_cache_retention (see host_mandated_api_mode
+    # in hermes_cli/providers.py and the retention hint in
+    # agent/transports/codex.py). The MetaAIProfile chat-completions hook
+    # above still covers custom OpenAI-compatible endpoints configured with
+    # a non-api.meta.ai base URL, which fall through to chat_completions.
+    api_mode="codex_responses",
+    # Muse Spark is natively multimodal (image/video/pdf/audio in, text out).
+    supports_vision=True,
+    # ...but only on user turns: an image envelope inside a role:tool message
+    # 400s "messages[N].content did not match any supported type" (#101668).
+    supports_vision_tool_messages=False,
+    # Cheap contributor tier is a good default for auxiliary tasks
+    # (compaction, title generation, vision) when this is the main provider.
+    default_aux_model="muse-spark-1.2-contributor",
+    # Muse spends completion budget on hidden reasoning tokens first; a low cap
+    # can finish with empty content. 16k is a safe floor.
+    default_max_tokens=16384,
+    # Minimal fallback shown when the live /v1/models fetch fails or no
+    # credentials are configured yet. Keep this list small — just enough so
+    # the picker isn't empty when the API is unreachable.
+    fallback_models=(
+        "muse-spark-1.2",
+    ),
+)
+
+register_provider(meta_ai)

plugins/model-providers/meta-ai/plugin.yaml

@@ -0,0 +1,6 @@
+name: meta-ai-provider
+kind: model-provider
+version: 1.0.0
+description: Meta Model API — Muse Spark family (Meta Superintelligence Labs)
+author: Beto de Paola
+homepage: https://github.com/albertodepaola/hermes-meta-provider