Cross-platform distribution, UI improvements, and performance optimizations

- PyInstaller frozen sidecar: spec file, build script, and ffmpeg path resolver
  for self-contained distribution without Python prerequisites
- Dual-mode sidecar launcher: frozen binary (production) with dev mode fallback
- Parallel transcription + diarization pipeline (~30-40% faster)
- GPU auto-detection for diarization (CUDA when available)
- Async run_pipeline command for real-time progress event delivery
- Web Audio API backend for instant playback and seeking
- OpenAI-compatible provider replacing LiteLLM client-side routing
- Cross-platform RAM detection (Linux/macOS/Windows)
- Settings: speaker count hint, token reveal toggles, dark dropdown styling
- Loading splash screen, flexbox layout fix for viewport overflow
- Gitea Actions CI/CD pipeline (Linux, Windows, macOS ARM)
- Updated README and CLAUDE.md documentation

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

python/voice_to_notes/providers/litellm_provider.py

@@ -1,4 +1,4 @@
-"""LiteLLM provider — multi-provider gateway."""
+"""OpenAI-compatible provider — works with any OpenAI-compatible API endpoint."""
 
 from __future__ import annotations
 
@@ -7,36 +7,44 @@ from typing import Any
 from voice_to_notes.providers.base import AIProvider
 
 
-class LiteLLMProvider(AIProvider):
-    """Routes through LiteLLM for access to 100+ LLM providers."""
+class OpenAICompatibleProvider(AIProvider):
+    """Connects to any OpenAI-compatible API (LiteLLM proxy, Ollama, vLLM, etc.)."""
 
-    def __init__(self, model: str = "gpt-4o-mini", **kwargs: Any) -> None:
+    def __init__(
+        self,
+        api_key: str | None = None,
+        api_base: str | None = None,
+        model: str = "gpt-4o-mini",
+        **kwargs: Any,
+    ) -> None:
+        self._api_key = api_key or "sk-no-key"
+        self._api_base = api_base
         self._model = model
         self._extra_kwargs = kwargs
 
     def chat(self, messages: list[dict[str, str]], **kwargs: Any) -> str:
-        try:
-            import litellm
-        except ImportError:
-            raise RuntimeError("litellm package is required. Install with: pip install litellm")
+        from openai import OpenAI
 
-        merged_kwargs = {**self._extra_kwargs, **kwargs}
-        response = litellm.completion(
-            model=merged_kwargs.get("model", self._model),
+        client_kwargs: dict[str, Any] = {"api_key": self._api_key}
+        if self._api_base:
+            client_kwargs["base_url"] = self._api_base
+
+        client = OpenAI(**client_kwargs)
+        response = client.chat.completions.create(
+            model=kwargs.get("model", self._model),
             messages=messages,
-            temperature=merged_kwargs.get("temperature", 0.7),
-            max_tokens=merged_kwargs.get("max_tokens", 2048),
+            temperature=kwargs.get("temperature", 0.7),
+            max_tokens=kwargs.get("max_tokens", 2048),
         )
         return response.choices[0].message.content or ""
 
     def is_available(self) -> bool:
         try:
-            import litellm  # noqa: F401
-
-            return True
+            import openai  # noqa: F401
+            return bool(self._api_key and self._api_base)
         except ImportError:
             return False
 
     @property
     def name(self) -> str:
-        return "LiteLLM"
+        return "OpenAI Compatible"