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132 lines (106 loc) · 4.27 KB
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package com.zavachat.backend;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.web.bind.annotation.*;
import org.springframework.stereotype.Service;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.http.ResponseEntity;
import java.util.HashMap;
import java.util.Map;
import java.util.concurrent.CompletableFuture;
// ---------------------------------------------------------
// "IMPORTS" FROM LLAMA AND BANANA PRO (Simulated)
// In a real build, these would be dependencies in your pom.xml
// ---------------------------------------------------------
// import com.meta.llama.LlamaModel;
// import com.bananapro.sdk.BananaImageGenerator;
@SpringBootApplication
public class AiBackendApplication {
public static void main(String[] args) {
// Powering up the Zava engine!
SpringApplication.run(AiBackendApplication.class, args);
System.out.println("☕ Zava Backend is running on port 8080...");
}
}
/**
* REST Controller to handle user interactions.
*/
@RestController
@RequestMapping("/api/v1")
@CrossOrigin(origins = "*") // Allow frontend access
class BotController {
private final LlamaService llamaService;
private final BananaProImageService bananaService;
@Autowired
public BotController(LlamaService llamaService, BananaProImageService bananaService) {
this.llamaService = llamaService;
this.bananaService = bananaService;
}
/**
* Endpoint for Chatting (Text-to-Text)
* Payload: { "prompt": "Hello bot!" }
*/
@PostMapping("/chat")
public ResponseEntity<Map<String, String>> chat(@RequestBody Map<String, String> payload) {
String userPrompt = payload.get("prompt");
String response = llamaService.generateResponse(userPrompt);
Map<String, String> result = new HashMap<>();
result.put("reply", response);
return ResponseEntity.ok(result);
}
/**
* Endpoint for Generating AI Images
* Payload: { "prompt": "A futuristic city" }
*/
@PostMapping("/generate-image")
public ResponseEntity<Map<String, Object>> generateImage(@RequestBody Map<String, String> payload) {
String prompt = payload.get("prompt");
// Asynchronous call to Banana Pro service
String imageUrl = bananaService.generateImage(prompt);
Map<String, Object> result = new HashMap<>();
result.put("status", "success");
result.put("image_url", imageUrl);
result.put("provider", "Banana Pro v1.0");
return ResponseEntity.ok(result);
}
}
/**
* Service to handle Text Generation (Simulating Llama integration)
*/
@Service
class LlamaService {
// Hypothetical Llama Client
// private final LlamaModel llamaModel = new LlamaModel("llama-3-70b");
public String generateResponse(String prompt) {
// Logic to call local Llama model or API would go here.
// For now, we simulate the intelligence.
System.out.println("🦙 Llama processing: " + prompt);
if (prompt == null || prompt.trim().isEmpty()) {
return "Even a Llama needs a prompt to spit out wisdom.";
}
// Simulating a response
return "Llama (Zava Edition) says: I have processed '" + prompt + "'. As an AI, I am ready to help.";
}
}
/**
* Service to handle Image Generation (Simulating Banana Pro integration)
*/
@Service
class BananaProImageService {
// Hypothetical Banana Pro Client
// private final BananaProClient bananaClient = new BananaProClient(apiKey);
public String generateImage(String prompt) {
System.out.println("🍌 Banana Pro generating image for: " + prompt);
// In production, this would make an HTTP POST to the Banana.dev or similar API
// Example:
// HttpClient.post("https://api.banana.dev/start/v4/", jsonBody);
try {
// Simulate GPU processing time
Thread.sleep(1500);
} catch (InterruptedException e) {
Thread.currentThread().interrupt();
}
// Return a mock URL for the generated image
return "https://api.bananapro.mock/images/gen_" + System.currentTimeMillis() + ".png";
}
}