v0.5.0: Binary-Free Mode - No OpenCode binary required

✨ Major Features:
- Native session management without OpenCode binary
- Provider routing: OpenCode Zen (free), Qwen OAuth, Z.AI
- Streaming chat with tool execution loop
- Mode detection API (/api/meta/mode)
- MCP integration fix (resolved infinite loading)
- NomadArch Native option in UI with comparison info

🆓 Free Models (No API Key):
- GPT-5 Nano (400K context)
- Grok Code Fast 1 (256K context)
- GLM-4.7 (205K context)
- Doubao Seed Code (256K context)
- Big Pickle (200K context)

📦 New Files:
- session-store.ts: Native session persistence
- native-sessions.ts: REST API for sessions
- lite-mode.ts: UI mode detection client
- native-sessions.ts (UI): SolidJS store

🔧 Updated:
- All installers: Optional binary download
- All launchers: Mode detection display
- Binary selector: Added NomadArch Native option
- README: Binary-Free Mode documentation

packages/ui/src/components/chat/multix-v2/features/PromptEnhancer.ts

@@ -0,0 +1,155 @@
+/**
+ * PromptEnhancer - Clavix-inspired prompt optimization
+ * 
+ * Source: https://github.com/ClavixDev/Clavix.git
+ * 
+ * Takes a user's raw input and refines it into a precise,
+ * context-aware, actionable prompt using the session's configured model.
+ */
+
+import { getLogger } from "@/lib/logger";
+import { sessions } from "@/stores/session-state";
+
+const log = getLogger("prompt-enhancer");
+
+// The meta-prompt based on Clavix CLEAR framework
+const ENHANCEMENT_PROMPT = `You are an ELITE Software Architect and Prompt Engineer, powered by the "ThoughtBox" reasoning engine.
+
+YOUR MISSION:
+Transform the user's raw input into a "God-Tier" System Prompt—a comprehensive, execution-ready technical specification that a senior engineer could implement without further questions.
+
+TARGET OUTPUT:
+- Detailed, file-level architectural blueprint
+- Explicit coding standards (TypeScript/solid-js/tailwindcss context implied)
+- Comprehensive error handling and edge case strategy
+- Step-by-step implementation plan
+
+METHODOLOGY (ThoughtBox):
+1. **Decode Intent**: What is the root problem? What is the *value*?
+2. **Context Inference**: Assume a high-performance TypeScript/React/Electron environment. Infer necessary imports, stores, and services.
+3. **Architectural Strategy**: Define the component hierarchy, state management (signals/stores), and side effects.
+4. **Specification Generation**: Write the actual prompt.
+
+OUTPUT FORMAT:
+Return ONLY the enhanced prompt string, formatted as follows:
+
+# 🎯 OBJECTIVE
+[Concise, high-level goal]
+
+# 🏗️ ARCHITECTURE & DESIGN
+- **Files**: List exact file paths to touch/create.
+- **Components**: Define props, state, and interfaces.
+- **Data Flow**: Explain signal/store interactions.
+
+# 🛡️ RESTRICTIONS & STANDARDS
+- **Tech Stack**: TypeScript, SolidJS, TailwindCSS, Lucide Icons.
+- **Rules**: NO placeholders, NO "todo", Strict Types, Accessibility-first.
+- **Context**: [Infer from input, e.g., "Use ContextEngine for retrieval"]
+
+# 📝 IMPLEMENTATION PLAN
+1. [Step 1: Description]
+2. [Step 2: Description]
+...
+
+# 💡 ORIGINAL REQUEST
+"""
+{INPUT}
+"""
+`;
+
+/**
+ * Get the model configured for a session
+ */
+function getSessionModel(instanceId: string, sessionId: string): string {
+    try {
+        const instanceSessions = sessions().get(instanceId);
+        const session = instanceSessions?.get(sessionId);
+        if (session?.model?.modelId) {
+            return session.model.modelId;
+        }
+    } catch (e) {
+        log.warn("Could not get session model", e);
+    }
+    return "minimax-m1"; // Fallback
+}
+
+/**
+ * Enhance a user's prompt using the session's AI model
+ */
+export async function enhancePrompt(
+    userInput: string,
+    instanceId: string,
+    sessionId?: string
+): Promise<string> {
+    if (!userInput.trim()) {
+        return userInput;
+    }
+
+    // Get the model from the session
+    const model = sessionId ? getSessionModel(instanceId, sessionId) : "minimax-m1";
+
+    log.info("Enhancing prompt...", { length: userInput.length, model });
+
+    try {
+        // Call the Ollama API for enhancement using the session's model
+        const response = await fetch("/api/ollama/chat", {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({
+                model,
+                messages: [
+                    {
+                        role: "user",
+                        content: ENHANCEMENT_PROMPT.replace("{INPUT}", userInput)
+                    }
+                ],
+                stream: false
+            })
+        });
+
+        if (!response.ok) {
+            log.warn("Enhancement API failed, returning original", { status: response.status });
+            return userInput;
+        }
+
+        const data = await response.json();
+        const enhanced = data?.message?.content || data?.choices?.[0]?.message?.content;
+
+        if (!enhanced || enhanced.trim().length === 0) {
+            log.warn("Enhancement returned empty, using original");
+            return userInput;
+        }
+
+        log.info("Prompt enhanced successfully", {
+            originalLength: userInput.length,
+            enhancedLength: enhanced.length,
+            model
+        });
+
+        return enhanced.trim();
+    } catch (error) {
+        log.error("Prompt enhancement failed", error);
+        return userInput;
+    }
+}
+
+/**
+ * Get a quick suggestion for improving a prompt (synchronous hint)
+ */
+export function getQuickTips(userInput: string): string[] {
+    const tips: string[] = [];
+
+    if (userInput.length < 20) {
+        tips.push("Add more context for better results");
+    }
+
+    if (!userInput.includes("file") && !userInput.includes("function") && !userInput.includes("component")) {
+        tips.push("Mention specific files or functions if applicable");
+    }
+
+    if (!userInput.match(/\b(create|fix|update|add|remove|refactor)\b/i)) {
+        tips.push("Start with an action verb: create, fix, update, etc.");
+    }
+
+    return tips;
+}