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>

src/lib/components/AIChatPanel.svelte

@@ -1,6 +1,7 @@
 <script lang="ts">
   import { invoke } from '@tauri-apps/api/core';
   import { segments, speakers } from '$lib/stores/transcript';
+  import { settings } from '$lib/stores/settings';
 
   interface ChatMessage {
     role: 'user' | 'assistant';
@@ -43,9 +44,23 @@
         content: m.content,
       }));
 
+      // Ensure the provider is configured with current credentials before chatting
+      const s = $settings;
+      const configMap: Record<string, Record<string, string>> = {
+        openai: { api_key: s.openai_api_key, model: s.openai_model },
+        anthropic: { api_key: s.anthropic_api_key, model: s.anthropic_model },
+        litellm: { api_key: s.litellm_api_key, api_base: s.litellm_api_base, model: s.litellm_model },
+        local: { model: s.local_model_path, base_url: 'http://localhost:8080' },
+      };
+      const config = configMap[s.ai_provider];
+      if (config) {
+        await invoke('ai_configure', { provider: s.ai_provider, config });
+      }
+
       const result = await invoke<{ response: string }>('ai_chat', {
         messages: chatMessages,
         transcriptContext: getTranscriptContext(),
+        provider: s.ai_provider,
       });
 
       messages = [...messages, { role: 'assistant', content: result.response }];