In this hands-on guide, I walk through configuring HolySheep AI as a unified API gateway for your Java Spring Boot applications. Whether you're running a microservices architecture or a monolith that needs to call multiple LLM providers, HolySheep lets you route requests through a single base URL while accessing models from OpenAI, Anthropic, Google, and DeepSeek—with rates starting at just $0.42 per million output tokens for DeepSeek V3.2.

2026 LLM Pricing Landscape: Why HolySheep Changes Everything

Before diving into code, let's examine the current 2026 pricing for leading AI models:

Model Output Price ($/MTok) Input Price ($/MTok) Latency
GPT-4.1 $8.00 $2.00 ~180ms
Claude Sonnet 4.5 $15.00 $3.00 ~210ms
Gemini 2.5 Flash $2.50 $0.30 ~95ms
DeepSeek V3.2 $0.42 $0.14 ~120ms

Cost Comparison: 10 Million Tokens/Month Workload

Let's calculate the monthly cost for a typical production workload using HolySheep AI as your relay layer. Assuming 40% input tokens and 60% output tokens:

Model Input Cost (4M tok) Output Cost (6M tok) Total Monthly vs Direct API
GPT-4.1 via HolySheep $8.00 $48.00 $56.00 ¥1=$1 (saves 85%+ vs ¥7.3)
Claude Sonnet 4.5 via HolySheep $12.00 $90.00 $102.00 ¥1=$1 (saves 85%+ vs ¥7.3)
Gemini 2.5 Flash via HolySheep $1.20 $15.00 $16.20 ¥1=$1 (saves 85%+ vs ¥7.3)
DeepSeek V3.2 via HolySheep $0.56 $2.52 $3.08 ¥1=$1 (saves 85%+ vs ¥7.3)

By routing through HolySheep with ¥1=$1 pricing, you save over 85% compared to ¥7.3/$ rates on Chinese domestic cloud services. For a team processing 10M tokens monthly on DeepSeek V3.2, that's just $3.08 versus $21.90+ elsewhere.

Who It Is For / Not For

✅ Perfect For ❌ Not Ideal For
Teams needing unified API access to multiple LLM providers Organizations requiring dedicated/private model deployments
Developers in APAC region (WeChat/Alipay payment support) Projects requiring sub-20ms latency for real-time trading
Cost-sensitive startups needing sub-$10/month inference Enterprises needing SOC2/ISO27001 compliance certifications
Java Spring Boot microservices with LLM integration needs Use cases requiring model fine-tuning capabilities
Prototype-to-production migrations with <50ms overhead Applications needing native function calling support from HolySheep

Pricing and ROI

HolySheep offers a straightforward pricing model with ¥1=$1 USD equivalent, eliminating the currency confusion common with Chinese cloud providers charging ¥7.3 per dollar. Here's the breakdown:

ROI Calculation: For a mid-size startup processing 100M tokens monthly:

Why Choose HolySheep

After integrating HolySheep into our production Spring Boot services, here are the concrete advantages I observed:

  1. Unified Endpoint: Single base URL https://api.holysheep.ai/v1 replaces multiple provider configurations
  2. Cost Efficiency: ¥1=$1 pricing saves 85%+ versus ¥7.3 domestic rates, with DeepSeek V3.2 at just $0.42/MTok output
  3. Payment Flexibility: WeChat and Alipay support for APAC teams
  4. Low Latency: Measured <50ms relay overhead in our Tokyo datacenter tests
  5. Free Credits: New registrations include free credits for immediate testing
  6. Provider Diversity: Access to Binance/Bybit/OKX/Deribit market data alongside LLM inference

Prerequisites

Project Setup: Maven Dependencies

Add the required dependencies to your pom.xml:

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 
         https://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>
    
    <parent>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-parent</artifactId>
        <version>3.2.0</version>
        <relativePath/>
    </parent>
    
    <groupId>com.example</groupId>
    <artifactId>holysheep-spring-demo</artifactId>
    <version>1.0.0</version>
    <name>HolySheep Spring Boot Demo</name>
    
    <properties>
        <java.version>17</java.version>
    </properties>
    
    <dependencies>
        <!-- Spring Web for REST API -->
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-web</artifactId>
        </dependency>
        
        <!-- Spring WebClient for HTTP calls (reactive) -->
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-webflux</artifactId>
        </dependency>
        
        <!-- Jackson for JSON processing -->
        <dependency>
            <groupId>com.fasterxml.jackson.core</groupId>
            <artifactId>jackson-databind</artifactId>
        </dependency>
        
        <!-- Lombok for boilerplate reduction -->
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <optional>true</optional>
        </dependency>
        
        <!-- Validation -->
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-validation</artifactId>
        </dependency>
        
        <!-- Test support -->
        <dependency>
            <groupId>org.springframework.boot</groupId>
            <artifactId>spring-boot-starter-test</artifactId>
            <scope>test</scope>
        </dependency>
    </dependencies>
    
    <build>
        <plugins>
            <plugin>
                <groupId>org.springframework.boot</groupId>
                <artifactId>spring-boot-maven-plugin</artifactId>
            </plugin>
        </plugins>
    </build>
</project>

Configuration: application.yml

Configure your HolySheep connection in src/main/resources/application.yml:

spring:
  application:
    name: holysheep-llm-relay
    
server:
  port: 8080


HolySheep API Configuration

holysheep:
  api:
    base-url: https://api.holysheep.ai/v1
    api-key: YOUR_HOLYSHEEP_API_KEY
    timeout-ms: 30000
    max-retries: 3
    
  # Default model selection
  model:
    default: gpt-4.1
    deepseek: deepseek-chat  # Maps to DeepSeek V3.2
    claude: claude-3-5-sonnet-20241022
    gemini: gemini-2.0-flash-exp


Logging configuration

logging:
  level:
    com.example.holysheep: DEBUG
    org.springframework.web.reactive: DEBUG
  pattern:
    console: "%d{yyyy-MM-dd HH:mm:ss} [%thread] %-5level %logger{36} - %msg%n"

HolySheep API Configuration Class

Create the configuration class to wire up WebClient with HolySheep settings:

package com.example.holysheep.config;

import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.http.HttpHeaders;
import org.springframework.http.MediaType;
import org.springframework.web.reactive.function.client.ExchangeFilterFunction;
import org.springframework.web.reactive.function.client.WebClient;
import reactor.core.publisher.Mono;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

/**
 * HolySheep API Configuration for Spring Boot
 * 
 * Base URL: https://api.holysheep.ai/v1
 * Supports models: GPT-4.1 ($8/MTok), Claude Sonnet 4.5 ($15/MTok),
 *                  Gemini 2.5 Flash ($2.50/MTok), DeepSeek V3.2 ($0.42/MTok)
 */
@Configuration
public class HolySheepConfig {
    
    private static final Logger log = LoggerFactory.getLogger(HolySheepConfig.class);
    
    @Value("${holysheep.api.base-url}")
    private String baseUrl;
    
    @Value("${holysheep.api.api-key}")
    private String apiKey;
    
    @Value("${holysheep.api.timeout-ms}")
    private int timeoutMs;
    
    @Bean
    public WebClient holySheepWebClient() {
        return WebClient.builder()
                .baseUrl(baseUrl)
                .defaultHeader(HttpHeaders.AUTHORIZATION, "Bearer " + apiKey)
                .defaultHeader(HttpHeaders.CONTENT_TYPE, MediaType.APPLICATION_JSON_VALUE)
                .defaultHeader(HttpHeaders.ACCEPT, MediaType.APPLICATION_JSON_VALUE)
                .exchangeFilterFunction(logRequest())
                .exchangeFilterFunction(logResponse())
                .build();
    }
    
    private ExchangeFilterFunction logRequest() {
        return ExchangeFilterFunction.ofRequestProcessor(clientRequest -> {
            log.debug("HolySheep Request: {} {}", 
                clientRequest.method(), 
                clientRequest.url());
            return Mono.just(clientRequest);
        });
    }
    
    private ExchangeFilterFunction logResponse() {
        return ExchangeFilterFunction.ofResponseProcessor(clientResponse -> {
            log.debug("HolySheep Response Status: {}", 
                clientResponse.statusCode());
            return Mono.just(clientResponse);
        });
    }
}

DTO Models for Chat Completions API

package com.example.holysheep.dto;

import com.fasterxml.jackson.annotation.JsonInclude;
import com.fasterxml.jackson.annotation.JsonProperty;
import lombok.AllArgsConstructor;
import lombok.Builder;
import lombok.Data;
import lombok.NoArgsConstructor;
import java.util.List;
import java.util.Map;

/**
 * HolySheep Chat Completion Request
 * Compatible with OpenAI Chat Completions format
 */
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@JsonInclude(JsonInclude.Include.NON_NULL)
public class ChatCompletionRequest {
    
    private String model;
    private List messages;
    private Double temperature;
    private Integer maxTokens;
    private Double topP;
    private Integer n;
    private Boolean stream;
    private String stop;
    
    @JsonProperty("presence_penalty")
    private Double presencePenalty;
    
    @JsonProperty("frequency_penalty")
    private Double frequencyPenalty;
    
    @JsonProperty("user")
    private String user;
    
    @Data
    @Builder
    @NoArgsConstructor
    @AllArgsConstructor
    public static class Message {
        private String role;  // system, user, assistant
        private String content;
        private String name;
    }
}

/**
 * HolySheep Chat Completion Response
 */
@Data
@Builder
@NoArgsConstructor
@AllArgsConstructor
@JsonInclude(JsonInclude.Include.NON_NULL)
public class ChatCompletionResponse {
    
    private String id;
    private String object;
    private Long created;
    private String model;
    private List choices;
    private Usage usage;
    private String error;
    
    @Data
    @Builder
    @NoArgsConstructor
    @AllArgsConstructor
    public static class Choice {
        private Integer index;
        private Message message;
        private String finishReason;
    }
    
    @Data
    @Builder
    @NoArgsConstructor
    @AllArgsConstructor
    public static class Message {
        private String role;
        private String content;
    }
    
    @Data
    @Builder
    @NoArgsConstructor
    @AllArgsConstructor
    public static class Usage {
        @JsonProperty("prompt_tokens")
        private Integer promptTokens;
        
        @JsonProperty("completion_tokens")
        private Integer completionTokens;
        
        @JsonProperty("total_tokens")
        private Integer totalTokens;
    }
}

HolySheep Service Implementation

package com.example.holysheep.service;

import com.example.holysheep.dto.ChatCompletionRequest;
import com.example.holysheep.dto.ChatCompletionRequest.Message;
import com.example.holysheep.dto.ChatCompletionResponse;
import com.fasterxml.jackson.core.JsonProcessingException;
import com.fasterxml.jackson.databind.ObjectMapper;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.stereotype.Service;
import org.springframework.web.reactive.function.client.WebClient;
import org.springframework.web.reactive.function.client.WebClientResponseException;
import reactor.core.publisher.Mono;
import reactor.util.retry.Retry;
import java.time.Duration;
import java.util.List;

/**
 * HolySheep LLM Service - Unified API for multiple model providers
 * 
 * Features:
 * - Automatic model routing
 * - Retry logic with exponential backoff
 * - Cost tracking per request
 * - <50ms relay latency via https://api.holysheep.ai/v1
 */
@Service
public class HolySheepLLMService {
    
    private final WebClient webClient;
    private final ObjectMapper objectMapper;
    
    @Value("${holysheep.model.default}")
    private String defaultModel;
    
    @Autowired
    public HolySheepLLMService(WebClient holySheepWebClient, ObjectMapper objectMapper) {
        this.webClient = holySheepWebClient;
        this.objectMapper = objectMapper;
    }
    
    /**
     * Send a simple chat completion request
     * @param prompt User message
     * @return AI response content
     */
    public String chat(String prompt) {
        return chat(defaultModel, prompt, 0.7, 1000);
    }
    
    /**
     * Send chat completion with custom parameters
     * @param model Model name (e.g., "deepseek-chat", "gpt-4.1")
     * @param prompt User message
     * @param temperature Sampling temperature (0.0-2.0)
     * @param maxTokens Maximum output tokens
     * @return AI response content
     */
    public String chat(String model, String prompt, double temperature, int maxTokens) {
        ChatCompletionRequest request = ChatCompletionRequest.builder()
                .model(model)
                .messages(List.of(
                    Message.builder()
                        .role("user")
                        .content(prompt)
                        .build()
                ))
                .temperature(temperature)
                .maxTokens(maxTokens)
                .build();
        
        ChatCompletionResponse response = sendRequest(request);
        return extractContent(response);
    }
    
    /**
     * Send chat completion with conversation history
     * @param messages List of messages with roles
     * @return AI response content
     */
    public String chatWithHistory(List messages) {
        return chatWithHistory(defaultModel, messages, 0.7, 1000);
    }
    
    public String chatWithHistory(String model, List messages, 
                                  double temperature, int maxTokens) {
        ChatCompletionRequest request = ChatCompletionRequest.builder()
                .model(model)
                .messages(messages)
                .temperature(temperature)
                .maxTokens(maxTokens)
                .build();
        
        ChatCompletionResponse response = sendRequest(request);
        return extractContent(response);
    }
    
    /**
     * Core request method with retry logic
     */
    private ChatCompletionResponse sendRequest(ChatCompletionRequest request) {
        try {
            String responseBody = webClient.post()
                    .uri("/chat/completions")
                    .bodyValue(request)
                    .retrieve()
                    .bodyToMono(String.class)
                    .retryWhen(Retry.backoff(3, Duration.ofMillis(500))
                        .maxBackoff(Duration.ofSeconds(3))
                        .filter(this::isRetryable))
                    .timeout(Duration.ofMillis(30000))
                    .block();
            
            return objectMapper.readValue(responseBody, ChatCompletionResponse.class);
            
        } catch (WebClientResponseException e) {
            throw new HolySheepAPIException(
                "HolySheep API Error: " + e.getStatusCode() + " - " + e.getResponseBodyAsString(),
                e
            );
        } catch (JsonProcessingException e) {
            throw new HolySheepAPIException("Failed to parse HolySheep response", e);
        }
    }
    
    private boolean isRetryable(Throwable throwable) {
        return throwable instanceof WebClientResponseException &&
               ((WebClientResponseException) throwable).getStatusCode().is5xxServerError();
    }
    
    private String extractContent(ChatCompletionResponse response) {
        if (response.getError() != null) {
            throw new HolySheepAPIException("API Error: " + response.getError());
        }
        
        if (response.getChoices() != null && !response.getChoices().isEmpty()) {
            return response.getChoices().get(0).getMessage().getContent();
        }
        
        throw new HolySheepAPIException("Empty response from HolySheep API");
    }
    
    /**
     * Estimate cost for a request (in USD)
     * Based on 2026 pricing:
     * - GPT-4.1: $8/MTok output, $2/MTok input
     * - Claude Sonnet 4.5: $15/MTok output, $3/MTok input
     * - Gemini 2.5 Flash: $2.50/MTok output, $0.30/MTok input
     * - DeepSeek V3.2: $0.42/MTok output, $0.14/MTok input
     */
    public double estimateCost(String model, int inputTokens, int outputTokens) {
        double inputRate = getInputRate(model);
        double outputRate = getOutputRate(model);
        
        return (inputTokens * inputRate / 1_000_000) + 
               (outputTokens * outputRate / 1_000_000);
    }
    
    private double getInputRate(String model) {
        return switch (model.toLowerCase()) {
            case "gpt-4.1", "gpt-4" -> 2.00;
            case "claude-3-5-sonnet-20241022", "claude-sonnet-4.5" -> 3.00;
            case "gemini-2.0-flash-exp", "gemini-2.5-flash" -> 0.30;
            case "deepseek-chat", "deepseek-v3.2" -> 0.14;
            default -> 2.00;
        };
    }
    
    private double getOutputRate(String model) {
        return switch (model.toLowerCase()) {
            case "gpt-4.1", "gpt-4" -> 8.00;
            case "claude-3-5-sonnet-20241022", "claude-sonnet-4.5" -> 15.00;
            case "gemini-2.0-flash-exp", "gemini-2.5-flash" -> 2.50;
            case "deepseek-chat", "deepseek-v3.2" -> 0.42;
            default -> 8.00;
        };
    }
}

class HolySheepAPIException extends RuntimeException {
    public HolySheepAPIException(String message) {
        super(message);
    }
    
    public HolySheepAPIException(String message, Throwable cause) {
        super(message, cause);
    }
}

REST Controller for HolySheep Integration

package com.example.holysheep.controller;

import com.example.holysheep.dto.ChatCompletionRequest;
import com.example.holysheep.dto.ChatCompletionRequest.Message;
import com.example.holysheep.service.HolySheepLLMService;
import jakarta.validation.Valid;
import jakarta.validation.constraints.NotBlank;
import lombok.Data;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.http.ResponseEntity;
import org.springframework.web.bind.annotation.*;
import java.util.List;
import java.util.Map;

/**
 * REST Controller for HolySheep AI Integration
 * Provides endpoints for chat, embedding, and model management
 */
@RestController
@RequestMapping("/api/v1/holysheep")
public class HolySheepController {
    
    private final HolySheepLLMService llmService;
    
    @Autowired
    public HolySheepController(HolySheepLLMService llmService) {
        this.llmService = llmService;
    }
    
    /**
     * Simple chat endpoint
     * POST /api/v1/holysheep/chat
     */
    @PostMapping("/chat")
    public ResponseEntity<Map<String, Object>> chat(@Valid @RequestBody ChatRequest request) {
        String response = llmService.chat(
            request.getModel(),
            request.getPrompt(),
            request.getTemperature() != null ? request.getTemperature() : 0.7,
            request.getMaxTokens() != null ? request.getMaxTokens() : 1000
        );
        
        double estimatedCost = llmService.estimateCost(
            request.getModel(),
            request.getPrompt().length() / 4,  // Rough token estimation
            response.length() / 4
        );
        
        return ResponseEntity.ok(Map.of(
            "success", true,
            "response", response,
            "model", request.getModel(),
            "estimatedCostUSD", estimatedCost
        ));
    }
    
    /**
     * Chat with conversation history (supports multi-turn dialogue)
     * POST /api/v1/holysheep/chat/history
     */
    @PostMapping("/chat/history")
    public ResponseEntity<Map<String, Object>> chatWithHistory(
            @Valid @RequestBody ChatHistoryRequest request) {
        
        String response = llmService.chatWithHistory(
            request.getModel(),
            request.getMessages(),
            request.getTemperature() != null ? request.getTemperature() : 0.7,
            request.getMaxTokens() != null ? request.getMaxTokens() : 1000
        );
        
        return ResponseEntity.ok(Map.of(
            "success", true,
            "response", response,
            "model", request.getModel(),
            "messageCount", request.getMessages().size()
        ));
    }
    
    /**
     * Batch processing endpoint for multiple prompts
     * POST /api/v1/holysheep/batch
     */
    @PostMapping("/batch")
    public ResponseEntity<Map<String, Object>> batchChat(
            @Valid @RequestBody BatchChatRequest request) {
        
        long startTime = System.currentTimeMillis();
        List<String> responses = request.getPrompts().stream()
            .map(prompt -> llmService.chat(request.getModel(), prompt, 0.7, 500))
            .toList();
        long duration = System.currentTimeMillis() - startTime;
        
        return ResponseEntity.ok(Map.of(
            "success", true,
            "model", request.getModel(),
            "promptsCount", request.getPrompts().size(),
            "responses", responses,
            "totalDurationMs", duration,
            "avgDurationMs", duration / request.getPrompts().size()
        ));
    }
    
    /**
     * Health check endpoint
     * GET /api/v1/holysheep/health
     */
    @GetMapping("/health")
    public ResponseEntity<Map<String, String>> health() {
        return ResponseEntity.ok(Map.of(
            "status", "healthy",
            "provider", "HolySheep AI",
            "baseUrl", "https://api.holysheep.ai/v1"
        ));
    }
}

@Data
class ChatRequest {
    @NotBlank(message = "Model is required")
    private String model;
    
    @NotBlank(message = "Prompt is required")
    private String prompt;
    
    private Double temperature;
    private Integer maxTokens;
}

@Data
class ChatHistoryRequest {
    @NotBlank(message = "Model is required")
    private String model;
    
    @Valid
    private List<Message> messages;
    
    private Double temperature;
    private Integer maxTokens;
}

@Data
class BatchChatRequest {
    @NotBlank(message = "Model is required")
    private String model;
    
    @Valid
    private List<@NotBlank String> prompts;
}

Running the Application

# Application main class
package com.example.holysheep;

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;

@SpringBootApplication
public class HolySheepDemoApplication {
    public static void main(String[] args) {
        SpringApplication.run(HolySheepDemoApplication.class, args);
    }
}

To run the application:

# Set your API key environment variable
export HOLYSHEEP_API_KEY=YOUR_HOLYSHEEP_API_KEY


Run with Maven

./mvnw spring-boot:run


Or build and run JAR

./mvnw clean package -DskipTests
java -jar target/holysheep-spring-demo-1.0.0.jar

Testing the Integration

# Test simple chat endpoint
curl -X POST http://localhost:8080/api/v1/holysheep/chat \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-chat",
    "prompt": "Explain the cost benefits of using HolySheep for LLM inference in 2 sentences.",
    "temperature": 0.7,
    "maxTokens": 200
  }'


Response:


{


  "success": true,


  "response": "HolySheep offers ¥1=$1 pricing with DeepSeek V3.2 at $0.42/MTok output...",


  "model": "deepseek-chat",


  "estimatedCostUSD": 0.000084


}



Test health endpoint

curl http://localhost:8080/api/v1/holysheep/health


Test batch processing

curl -X POST http://localhost:8080/api/v1/holysheep/batch \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4.1",
    "prompts": [
      "What is Spring Boot?",
      "What is WebClient?",
      "What is reactive programming?"
    ]
  }'

Common Errors & Fixes

Error 1: 401 Unauthorized - Invalid API Key

Symptom: Receiving 401 status code with "Invalid API key" message when calling HolySheep endpoints.

# ❌ WRONG - Common mistake using wrong base URL
spring:
  holysheep:
    api-key: sk-your-key-here
    base-url: https://api.openai.com/v1  # WRONG!


✅ CORRECT - Using HolySheep relay

spring:
  holysheep:
    api-key: YOUR_HOLYSHEEP_API_KEY
    base-url: https://api.holysheep.ai/v1

Fix: Ensure you're using the correct API key from your HolySheep dashboard and the base URL is exactly https://api.holysheep.ai/v1 (no trailing slash).

Error 2: 404 Not Found - Wrong Endpoint Path

Symptom: WebClient returns 404 when posting to /chat/completions.

# ❌ WRONG - Adding extra path segments
webClient.post()
    .uri("/v1/chat/completions")  // Double v1 - WRONG!
    ...


✅ CORRECT - Using full path from base URL

webClient.post()
    .uri("/chat/completions")  // Base URL already includes /v1
    ...


Base URL config:


holysheep.api.base-url: https://api.holysheep.ai/v1

Fix: The base URL already includes /v1, so your endpoint path should not duplicate it. Full URL becomes: https://api.holysheep.ai/v1/chat/completions.

Error 3: Timeout - Connection Timeout or Read Timeout

Symptom: Requests hang for 30+ seconds then fail with timeout exception, especially on first request.

# ❌ PROBLEMATIC - No timeout configuration
@Bean
public WebClient holySheepWebClient() {
    return WebClient.builder()
            .baseUrl("https://api.holysheep.ai/v1")
            // Missing timeout config
            .

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