feat: Pi extension uses Pi's internal complete() for LLM analysis

- PiLLMClient now imports @mariozechner/pi-ai's complete() function
- Respects user's /model selection and /login auth
- No external fetch() — Pi handles transport internally
- Added src/types/pi-ai.d.ts for TypeScript declarations
- Extension reverted to real LLM calls (initProject, patchFile, reinitPath)
- Tests mock @mariozechner/pi-ai for verification

src/pi-llm-client.ts

@@ -2,10 +2,11 @@ import { LLMError } from "./llm-error.js";
 import type { LLMClient } from "./llm-client.js";
 
 /**
- * Pi LLM Client — uses Pi's built-in model when running inside the Pi runtime.
+ * Pi LLM Client — uses Pi's built-in `complete()` from `@mariozechner/pi-ai`.
  *
- * This client ALWAYS attempts to use Pi's native LLM and throws a hard error
- * if Pi's model is not accessible. It never falls back to external APIs.
+ * This runs inside the Pi extension runtime and calls Pi's internal AI layer,
+ * which respects the user's configured model (/model) and auth (/login).
+ * No external fetch() — Pi handles transport, retries, and token accounting.
  */
 export class PiLLMClient implements LLMClient {
 	constructor(private extensionContext?: unknown) {}
@@ -16,57 +17,66 @@ export class PiLLMClient implements LLMClient {
 		if (!ctx) {
 			throw new LLMError(
 				"Pi LLM not accessible: no ExtensionContext provided. " +
-					"This extension must run inside Pi.",
+					"This tool must run inside Pi.",
 			);
 		}
 
-		// Try to access Pi's model or modelRegistry
+		// Get the active model from Pi's runtime
 		const model = ctx.model ?? ctx.modelRegistry?.get?.();
 		if (!model) {
 			throw new LLMError(
-				"Pi LLM not accessible: no model configured in Pi runtime. " +
-					"Configure a model (e.g., via /model) before using project-map tools.",
+				"Pi LLM not accessible: no model configured. " +
+					"Set a model via /model before using project-map tools.",
 			);
 		}
 
-		// Attempt to call the model via Pi's provider interface.
-		// Pi exposes an OpenAI-compatible completions endpoint through the
-		// active provider. We construct a minimal chat-completion payload
-		// and send it through the model's fetch wrapper.
 		try {
-			const provider = ctx.modelRegistry?.getProvider?.(model.provider);
-			if (!provider || typeof provider.complete !== "function") {
-				// Fallback: try using Pi's internal agent session to get a completion
-				return await this.callViaAgentSession(ctx, prompt);
+			// Dynamically import Pi's AI module (available in the Pi runtime)
+			const { complete } = await import("@mariozechner/pi-ai");
+
+			const response = await complete(
+				model,
+				{
+					systemPrompt:
+						"You are a code analysis assistant. Analyze the provided file and respond with concise, structured information.",
+					messages: [
+						{
+							role: "user",
+							content: prompt,
+							timestamp: Date.now(),
+						},
+					],
+				},
+				{
+					temperature: 0.1,
+					maxTokens: 256,
+				},
+			);
+
+			if (response.errorMessage) {
+				throw new LLMError(`Pi LLM error: ${response.errorMessage}`);
 			}
-			return await provider.complete(prompt);
+
+			// Extract text content from AssistantMessage
+			const text = response.content
+				.filter((c: any) => c.type === "text")
+				.map((c: any) => c.text)
+				.join("")
+				.trim();
+
+			return text;
 		} catch (err: any) {
 			if (err instanceof LLMError) throw err;
+			if (err.code === "MODULE_NOT_FOUND") {
+				throw new LLMError(
+					"Pi LLM not accessible: @mariozechner/pi-ai is not available. " +
+						"This extension must run inside the Pi runtime.",
+				);
+			}
 			throw new LLMError(
-				`Pi LLM call failed: ${err.message || String(err)}. ` +
-					"Ensure Pi has a working model configured.",
+				`Pi LLM call failed: ${err.message || String(err)}`,
 				err,
 			);
 		}
 	}
-
-	private async callViaAgentSession(ctx: any, prompt: string): Promise<string> {
-		// Pi's ExtensionContext may expose a session or agent that can
-		// make model calls. This is the fallback when direct provider
-		// access is not available.
-		if (typeof ctx.sendMessage === "function") {
-			// Not ideal — sendMessage injects into conversation.
-			// Reserved for future Pi SDK improvement.
-			throw new LLMError(
-				"Pi LLM direct call not yet supported by this Pi version. " +
-					"The extension requires a Pi runtime with exposed model provider API.",
-			);
-		}
-
-		throw new LLMError(
-			"Pi LLM not accessible: the Pi runtime does not expose a callable model API. " +
-				"This extension requires Pi to provide either ctx.modelRegistry.getProvider() " +
-				"or a direct model completion interface.",
-		);
-	}
 }

src/types/pi-ai.d.ts

@@ -0,0 +1,24 @@
+// Pi AI module — available only inside the Pi runtime
+// Declared here so TypeScript doesn't error during `npm run build`
+
+declare module "@mariozechner/pi-ai" {
+	export function complete(
+		model: any,
+		context: {
+			systemPrompt?: string;
+			messages: Array<{
+				role: "user" | "assistant" | "system" | "toolResult";
+				content: string;
+				timestamp?: number;
+			}>;
+		},
+		options?: {
+			temperature?: number;
+			maxTokens?: number;
+		},
+	): Promise<{
+		role: "assistant";
+		content: Array<{ type: string; text?: string }>;
+		errorMessage?: string;
+	}>;
+}