Files
optimclaw/tests/openai_compat_integration.rs
T
bac2d75713 feat: Secure prompt-based skills system (Phases 1-4) (#51)
* feat: Add secure prompt-based skills system (Phase 1 MVP)

Implement a skills system that extends the agent with prompt-level
instructions from local directories. Skills declare activation criteria,
tool permissions, and trust tiers that determine authority attenuation.

Core security model: the minimum trust level of any active skill
determines a tool ceiling -- tools above the ceiling are removed from
the LLM's tool list entirely at the API level, preventing prompt-based
manipulation.

New modules:
- skills/mod.rs: Core types (SkillTrust, SkillManifest, LoadedSkill)
- skills/scanner.rs: Content scanner for manipulation detection
- skills/registry.rs: Filesystem discovery and manifest parsing
- skills/selector.rs: Deterministic two-phase prefilter (no LLM)
- skills/attenuation.rs: Trust-based tool filtering

Integration:
- Agent loop selects skills per-turn and applies tool attenuation
- Reasoning engine injects skill context with structural isolation
- Config supports SKILLS_ENABLED, SKILLS_DIR, SKILLS_MAX_ACTIVE,
  SKILLS_MAX_CONTEXT_TOKENS environment variables
- Disabled by default (SKILLS_ENABLED=false)

41 new tests covering all modules.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: Address all adversarial review findings for skills system

Security fixes:
- Escape skill name/version in XML attributes to prevent trust spoofing
- Escape prompt content to prevent </skill> tag breakout
- Require integrity hash for Verified/Community tier skills
- Validate skill names against [a-zA-Z0-9][a-zA-Z0-9._-]{0,63}
- Add 64 KiB file size limit on prompt.md

Bug fixes:
- Use actual SkillsConfig from AgentDeps instead of SkillsConfig::default()
- Add skills_config field to AgentDeps, wired through from main.rs

Performance:
- Pre-compile regex patterns at load time (cached on LoadedSkill)
- Selector uses pre-compiled patterns instead of recompiling per message
- Switch all std::fs to tokio::fs for non-blocking async I/O

Hardening:
- Cap keyword score at 30 points to prevent keyword stuffing attacks
- Enforce max 20 keywords and 5 patterns per skill
- Normalize line endings (CRLF/CR to LF) before hashing
- Also includes cargo fmt formatting fixes for adjacent code

Tests: 54 skills tests pass (up from 41), zero new clippy warnings.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: Address medium/low severity findings from adversarial review

Fixes all 18 medium/low severity findings identified by the security review:

- mod.rs: Add MAX_TAGS_PER_SKILL cap (10) in enforce_limits(); use
  RegexBuilder with 64 KiB size_limit to prevent ReDoS; replace
  case-enumerated escape_skill_content with regex matching all case
  variants plus whitespace/null byte injection between </ and skill;
  document allowed_patterns as unenforced until Phase 2; document
  Marketplace URL validation as Phase 3 concern

- registry.rs: Add MAX_MANIFEST_FILE_SIZE (16 KiB) check before reading;
  add symlink detection via symlink_metadata to reject symlinks in
  discover_local; add MAX_DISCOVERED_SKILLS (100) cap; validate
  prompt_hash format (sha256: + 64 hex chars); warn on name collision
  before overwriting; accept SkillSource parameter in load_skill instead
  of always using Local; add InvalidHashFormat, ManifestTooLarge,
  SymlinkDetected error variants

- selector.rs: Add MAX_TAG_SCORE (15) cap parallel to keyword cap; warn
  when declared max_context_tokens diverges >2x from actual prompt size

- scanner.rs: Add mixed-script homoglyph detection (Cyrillic, Greek,
  Armenian unicode ranges); document token-boundary bypass and semantic
  paraphrasing as known limitations

- attenuation.rs: Document READ_ONLY_TOOLS maintenance requirements

- agent_loop.rs: Surface scan warnings via structured tracing; add
  structured audit events for skill activation and tool attenuation

61 tests pass, 0 new clippy warnings.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: Address 12 findings from second adversarial security review

HIGH:
- Escape opening <skill tags in prompt content (prevents fake skill block injection)
- Scan manifest metadata fields (description, author, tags, reasons) not just prompt
- Block trust downgrade on name collision (existing Local can't be replaced by Community)

MEDIUM:
- Eliminate TOCTOU gap: read files then check size instead of metadata-then-read
- Reject file-level symlinks in load_skill (prompt.md, skill.toml)
- Truncate and filter manifest.skill.tags (prevent unlimited tag scoring)
- Cap regex pattern score at 40 (prevent 5x20=100 dominating keyword+tag)
- Add doc comment about skill_list tool exposing metadata (sanitization required)
- Move Community disclaimer inside <skill> tags (not outside structural boundary)
- Filter keywords/tags shorter than 3 chars (prevent broad matching)

LOW:
- Enforce minimum token_cost of 1 (max_context_tokens=0 can't bypass budget)
- Remove redundant try_exists checks in discover_local (let load_skill handle errors)

70 skills tests passing.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* feat: Add HTTP endpoint scoping for skills (Phase 1)

Skills that declare an [http] section in skill.toml now have their HTTP
requests constrained to declared endpoints at runtime. This addresses
the gap where allowed_patterns was parsed but never enforced -- once the
http tool was visible via attenuation, the LLM could reach any URL.

Enforcement reuses EndpointPattern/AllowlistValidator from the WASM
capability system. Semantics: if no active skill declares [http], all
requests pass through (backward compat). If any skill declares [http],
URLs must match at least one skill's allowlist (union). Community skills'
[http] declarations are silently ignored (defense in depth).

Shell commands using curl/wget are also validated against scopes.

Scanner gains detection for known exfiltration domains (webhook.site,
ngrok.io, etc.), overly broad wildcards, and credential/host mismatches.

Closes #38

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* style: Apply cargo fmt to http_scoping.rs

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* style: Apply cargo fmt across codebase

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* feat: Add parameter-level permission enforcement for skills (Phase 2)

Activates enforcement of `allowed_patterns` in skill.toml permissions.
Previously these patterns were parsed but not enforced -- a Verified skill
declaring `permissions.shell` with `allowed_patterns = [{command = "cargo *"}]`
could still run any shell command. Now the enforcer validates tool parameters
against declared glob patterns before execution.

Key changes:
- New `enforcer.rs` module with `SkillPermissionEnforcer`, `glob_to_regex()`,
  and `validate_tool_call()` with union semantics across active skills
- Typed pattern enums (`ShellPattern`, `FilePathPattern`, `MemoryTargetPattern`)
  replace the previous `Vec<serde_json::Value>` in `ToolPermissionDeclaration`
- Scanner gains `scan_permission_patterns()` detecting dangerous patterns
  (rm, sudo, curl, bare wildcards, command chaining, sensitive paths, identity files)
- Registry blocks non-Local skills with critical permission pattern warnings
- Agent loop threads enforcer into `execute_chat_tool` alongside HTTP scoping

Trust interaction: Community patterns ignored, Verified enforced, Local without
patterns unrestricted, Local with patterns enforced as guidance. Union semantics
across skills -- tool call allowed if ANY skill's patterns permit it.

34 new tests. All 818 library tests pass.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* feat: Add worker permission enforcement and LLM behavioral analysis (Phase 3+4)

Phase 3 - Worker-side permission enforcement:
- Add SerializedToolPermission/SerializedPattern DTOs for HTTP boundary crossing
- Extend JobDescription, ContainerHandle, and orchestrator API to carry permissions
- CreateJobTool snapshots and forwards skill permissions to spawned workers
- Worker runtime builds SkillPermissionEnforcer and checks before tool execution
- Load-time token budget enforcement rejects prompts exceeding 2x declared budget
- Deduplicate enforcer construction: from_active_skills() delegates to from_serialized()

Phase 4 - LLM behavioral analysis:
- BehavioralAnalyzer with cached, LLM-based semantic content analysis
- Structured output parsing (FINDING|CATEGORY|SEVERITY|DESCRIPTION or CLEAN)
- Content-hash caching with bounded size (MAX_CACHE_ENTRIES=256)
- Graceful degradation when LLM unavailable
- Integrated into load_skill() for non-Local skills; critical findings block loading

Review fixes:
- Real cache tests with CountingLlm mock (test_cache_hit, test_cache_miss, test_cache_bounded)
- UTF-8-safe truncate() in worker runtime
- Few-shot examples in behavioral analysis prompt
- Documented max_context_tokens=0 opt-out and create_job() permission gap

848 tests passing, no new clippy warnings.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: Address review feedback from serrrfirat on skills-phase2

- Fix truncate_cmd UTF-8 panic: use char-boundary-aware slicing
- Remove redundant effective_tools branching in reasoning.rs
- Document cache eviction as known limitation (arbitrary, not LRU)
- Add safety comment on SkillTrust enum ordering (security-critical)
- Simplify active_skills selection (prefilter_skills handles empty input)

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: address remaining skills review feedback

* refactor: replace skills system with OpenClaw SKILL.md format + 2-state trust

Replace the 5-gate, 3-tier trust hierarchy (scanner, behavioral analyzer,
parameter-level enforcer, HTTP endpoint scoping) with a simplified 3-layer
security model: gating -> attenuation -> Docker confinement.

Key changes:
- SKILL.md format (YAML frontmatter + markdown prompt) replaces skill.toml + prompt.md
- 2-state trust (Installed/Trusted) replaces 3-tier (Community/Verified/Local)
- New parser.rs for SKILL.md parsing with serde_yaml
- New gating.rs for requirements checking (bins/env/config)
- Simplified registry with 2-location discovery (workspace + user dirs)
- Removed scanner, behavioral_analyzer, enforcer, http_scoping (~4,100 lines)
- Removed skill_permissions propagation through job/orchestrator/worker pipeline
- Added serde_yaml dependency for YAML frontmatter parsing

Net: -5,298 lines, 59 skills tests pass, 907 total tests pass.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* feat: add in-app skill management tools and ClawHub catalog integration

Add 4 chat-callable tools (skill_list, skill_search, skill_install,
skill_remove) plus matching web gateway endpoints for managing skills
at runtime. The catalog fetches from ClawHub's public registry API
at runtime rather than bundling entries at compile time.

Key changes:
- SkillRegistry gains mutation methods (install_skill, remove_skill,
  reload, find_by_name) with Arc<RwLock> for concurrent access
- New catalog module queries ClawHub /api/v1/search with in-memory
  caching (5-min TTL, configurable via CLAWHUB_REGISTRY env var)
- skill_list and skill_search added to READ_ONLY_TOOLS for safe use
  under Installed trust ceiling
- Web gateway gets /api/skills, /api/skills/search, /api/skills/install,
  and /api/skills/{name} DELETE endpoints

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: address PR #51 review feedback from ilblackdragon

Security:
- Add SSRF protection to fetch_skill_content: require HTTPS, reject
  private/loopback/link-local IPs and internal hostnames, disable
  redirects. Gateway install handler now reuses the same validation.
- URL-encode slug in skill_download_url to prevent query injection.
- Require X-Confirm-Action header on gateway skill install/remove
  endpoints (equivalent to chat tool requires_approval gate).

Correctness:
- Eliminate all block_in_place/block_on usage in skill tools and
  gateway handlers. Split install into prepare_install_to_disk (static
  async, no lock) + commit_install (sync, brief write lock). Same
  pattern for remove: validate_remove + delete_skill_files + commit_remove.
- Write normalized content to disk in install_skill (was writing
  original un-normalized content, causing hash mismatch on re-read).
- Fix token estimation from 0.75 to 0.25 tokens/byte (~4 chars per
  token) in registry.rs, selector.rs, and standalone loader.

Dependencies:
- Replace deprecated serde_yaml 0.9 with serde_yml 0.0.12.
- Remove unused toml dependency.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

---------

Co-authored-by: Claude Opus 4.6 <[email protected]>
2026-02-18 00:28:38 +00:00

483 lines
14 KiB
Rust

//! Integration tests for the OpenAI-compatible API endpoints.
//!
//! Uses a mock LLM provider so no real API key is needed.
use std::net::SocketAddr;
use std::sync::Arc;
use std::time::Duration;
use async_trait::async_trait;
use rust_decimal::Decimal;
use ironclaw::channels::web::server::{GatewayState, start_server};
use ironclaw::channels::web::sse::SseManager;
use ironclaw::channels::web::ws::WsConnectionTracker;
use ironclaw::error::LlmError;
use ironclaw::llm::{
CompletionRequest, CompletionResponse, FinishReason, LlmProvider, ToolCompletionRequest,
ToolCompletionResponse,
};
const AUTH_TOKEN: &str = "test-openai-token";
// ---------------------------------------------------------------------------
// Mock LLM provider
// ---------------------------------------------------------------------------
struct MockLlmProvider;
#[async_trait]
impl LlmProvider for MockLlmProvider {
fn model_name(&self) -> &str {
"mock-model-v1"
}
fn cost_per_token(&self) -> (Decimal, Decimal) {
(Decimal::ZERO, Decimal::ZERO)
}
async fn complete(&self, req: CompletionRequest) -> Result<CompletionResponse, LlmError> {
// Echo the last user message back
let user_msg = req
.messages
.iter()
.rev()
.find(|m| m.role == ironclaw::llm::Role::User)
.map(|m| m.content.clone())
.unwrap_or_else(|| "no user message".to_string());
Ok(CompletionResponse {
content: format!("Mock response to: {}", user_msg),
input_tokens: 10,
output_tokens: 5,
finish_reason: FinishReason::Stop,
response_id: None,
})
}
async fn complete_with_tools(
&self,
req: ToolCompletionRequest,
) -> Result<ToolCompletionResponse, LlmError> {
// If tools are provided, return a tool call
if let Some(tool) = req.tools.first() {
Ok(ToolCompletionResponse {
content: None,
tool_calls: vec![ironclaw::llm::ToolCall {
id: "call_mock_001".to_string(),
name: tool.name.clone(),
arguments: serde_json::json!({"test": true}),
}],
input_tokens: 15,
output_tokens: 8,
finish_reason: FinishReason::ToolUse,
response_id: None,
})
} else {
Ok(ToolCompletionResponse {
content: Some("No tools available".to_string()),
tool_calls: vec![],
input_tokens: 10,
output_tokens: 4,
finish_reason: FinishReason::Stop,
response_id: None,
})
}
}
async fn list_models(&self) -> Result<Vec<String>, LlmError> {
Ok(vec![
"mock-model-v1".to_string(),
"mock-model-v2".to_string(),
])
}
}
// ---------------------------------------------------------------------------
// Test helpers
// ---------------------------------------------------------------------------
async fn start_test_server() -> (SocketAddr, Arc<GatewayState>) {
let state = Arc::new(GatewayState {
msg_tx: tokio::sync::RwLock::new(None),
sse: SseManager::new(),
workspace: None,
session_manager: None,
log_broadcaster: None,
extension_manager: None,
tool_registry: None,
store: None,
job_manager: None,
prompt_queue: None,
user_id: "test-user".to_string(),
shutdown_tx: tokio::sync::RwLock::new(None),
ws_tracker: Some(Arc::new(WsConnectionTracker::new())),
llm_provider: Some(Arc::new(MockLlmProvider)),
skill_registry: None,
skill_catalog: None,
chat_rate_limiter: ironclaw::channels::web::server::RateLimiter::new(30, 60),
});
let addr: SocketAddr = "127.0.0.1:0".parse().unwrap();
let bound_addr = start_server(addr, state.clone(), AUTH_TOKEN.to_string())
.await
.expect("Failed to start test server");
(bound_addr, state)
}
fn client() -> reqwest::Client {
reqwest::Client::builder()
.timeout(Duration::from_secs(10))
.build()
.unwrap()
}
// ---------------------------------------------------------------------------
// Tests
// ---------------------------------------------------------------------------
#[tokio::test]
async fn test_chat_completions_basic() {
let (addr, _state) = start_test_server().await;
let url = format!("http://{}/v1/chat/completions", addr);
let resp = client()
.post(&url)
.bearer_auth(AUTH_TOKEN)
.json(&serde_json::json!({
"model": "mock-model-v1",
"messages": [
{"role": "user", "content": "Hello world"}
]
}))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
let body: serde_json::Value = resp.json().await.unwrap();
assert_eq!(body["object"], "chat.completion");
assert_eq!(body["model"], "mock-model-v1");
assert_eq!(body["choices"][0]["finish_reason"], "stop");
let content = body["choices"][0]["message"]["content"].as_str().unwrap();
assert!(
content.contains("Hello world"),
"Expected echo, got: {}",
content
);
// Check usage
assert_eq!(body["usage"]["prompt_tokens"], 10);
assert_eq!(body["usage"]["completion_tokens"], 5);
assert_eq!(body["usage"]["total_tokens"], 15);
}
#[tokio::test]
async fn test_chat_completions_with_system_message() {
let (addr, _state) = start_test_server().await;
let url = format!("http://{}/v1/chat/completions", addr);
let resp = client()
.post(&url)
.bearer_auth(AUTH_TOKEN)
.json(&serde_json::json!({
"model": "mock-model-v1",
"messages": [
{"role": "system", "content": "You are helpful."},
{"role": "user", "content": "What is 2+2?"}
],
"temperature": 0.5,
"max_tokens": 100
}))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
let body: serde_json::Value = resp.json().await.unwrap();
let content = body["choices"][0]["message"]["content"].as_str().unwrap();
assert!(content.contains("2+2"));
}
#[tokio::test]
async fn test_chat_completions_with_tools() {
let (addr, _state) = start_test_server().await;
let url = format!("http://{}/v1/chat/completions", addr);
let resp = client()
.post(&url)
.bearer_auth(AUTH_TOKEN)
.json(&serde_json::json!({
"model": "mock-model-v1",
"messages": [
{"role": "user", "content": "What's the weather?"}
],
"tools": [{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get the weather",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string"}
}
}
}
}]
}))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
let body: serde_json::Value = resp.json().await.unwrap();
assert_eq!(body["choices"][0]["finish_reason"], "tool_calls");
let tool_calls = &body["choices"][0]["message"]["tool_calls"];
assert!(tool_calls.is_array());
assert_eq!(tool_calls[0]["id"], "call_mock_001");
assert_eq!(tool_calls[0]["type"], "function");
assert_eq!(tool_calls[0]["function"]["name"], "get_weather");
}
#[tokio::test]
async fn test_chat_completions_streaming() {
let (addr, _state) = start_test_server().await;
let url = format!("http://{}/v1/chat/completions", addr);
let resp = client()
.post(&url)
.bearer_auth(AUTH_TOKEN)
.json(&serde_json::json!({
"model": "mock-model-v1",
"messages": [
{"role": "user", "content": "Stream test"}
],
"stream": true
}))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
// Check simulated streaming header
assert_eq!(
resp.headers()
.get("x-ironclaw-streaming")
.and_then(|v| v.to_str().ok()),
Some("simulated"),
"Expected x-ironclaw-streaming: simulated header"
);
let text = resp.text().await.unwrap();
// Should contain SSE data lines
assert!(
text.contains("data:"),
"Expected SSE data lines, got: {}",
text
);
// Should end with [DONE]
assert!(
text.contains("[DONE]"),
"Expected [DONE] sentinel, got: {}",
text
);
// Should contain the role chunk
assert!(
text.contains("\"role\":\"assistant\""),
"Expected role chunk, got: {}",
text
);
// Collect all content from the chunks
let mut full_content = String::new();
for line in text.lines() {
if let Some(data) = line.strip_prefix("data:") {
let data = data.trim();
if data == "[DONE]" {
continue;
}
if let Ok(chunk) = serde_json::from_str::<serde_json::Value>(data)
&& let Some(content) = chunk["choices"][0]["delta"]["content"].as_str()
{
full_content.push_str(content);
}
}
}
assert!(
full_content.contains("Stream test"),
"Expected reassembled content to contain 'Stream test', got: '{}'",
full_content
);
}
#[tokio::test]
async fn test_chat_completions_empty_messages() {
let (addr, _state) = start_test_server().await;
let url = format!("http://{}/v1/chat/completions", addr);
let resp = client()
.post(&url)
.bearer_auth(AUTH_TOKEN)
.json(&serde_json::json!({
"model": "mock-model-v1",
"messages": []
}))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 400);
let body: serde_json::Value = resp.json().await.unwrap();
assert!(body["error"]["message"].as_str().unwrap().contains("empty"));
}
#[tokio::test]
async fn test_chat_completions_model_mismatch() {
let (addr, _state) = start_test_server().await;
let url = format!("http://{}/v1/chat/completions", addr);
let resp = client()
.post(&url)
.bearer_auth(AUTH_TOKEN)
.json(&serde_json::json!({
"model": "gpt-4",
"messages": [{"role": "user", "content": "Hi"}]
}))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 404);
let body: serde_json::Value = resp.json().await.unwrap();
assert_eq!(body["error"]["code"], "model_not_found");
assert!(
body["error"]["message"]
.as_str()
.unwrap()
.contains("mock-model-v1")
);
}
#[tokio::test]
async fn test_chat_completions_no_auth() {
let (addr, _state) = start_test_server().await;
let url = format!("http://{}/v1/chat/completions", addr);
let resp = client()
.post(&url)
// No auth header
.json(&serde_json::json!({
"model": "mock-model-v1",
"messages": [{"role": "user", "content": "Hi"}]
}))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 401);
}
#[tokio::test]
async fn test_models_endpoint() {
let (addr, _state) = start_test_server().await;
let url = format!("http://{}/v1/models", addr);
let resp = client()
.get(&url)
.bearer_auth(AUTH_TOKEN)
.send()
.await
.unwrap();
assert_eq!(resp.status(), 200);
let body: serde_json::Value = resp.json().await.unwrap();
assert_eq!(body["object"], "list");
let data = body["data"].as_array().unwrap();
assert_eq!(data.len(), 2);
assert_eq!(data[0]["id"], "mock-model-v1");
assert_eq!(data[1]["id"], "mock-model-v2");
assert_eq!(data[0]["object"], "model");
}
#[tokio::test]
async fn test_models_no_auth() {
let (addr, _state) = start_test_server().await;
let url = format!("http://{}/v1/models", addr);
let resp = client().get(&url).send().await.unwrap();
assert_eq!(resp.status(), 401);
}
#[tokio::test]
async fn test_no_llm_provider_returns_503() {
// Create state WITHOUT llm_provider
let state = Arc::new(GatewayState {
msg_tx: tokio::sync::RwLock::new(None),
sse: SseManager::new(),
workspace: None,
session_manager: None,
log_broadcaster: None,
extension_manager: None,
tool_registry: None,
store: None,
job_manager: None,
prompt_queue: None,
user_id: "test-user".to_string(),
shutdown_tx: tokio::sync::RwLock::new(None),
ws_tracker: Some(Arc::new(WsConnectionTracker::new())),
llm_provider: None, // No LLM!
skill_registry: None,
skill_catalog: None,
chat_rate_limiter: ironclaw::channels::web::server::RateLimiter::new(30, 60),
});
let addr: SocketAddr = "127.0.0.1:0".parse().unwrap();
let bound_addr = start_server(addr, state, AUTH_TOKEN.to_string())
.await
.unwrap();
let url = format!("http://{}/v1/chat/completions", bound_addr);
let resp = client()
.post(&url)
.bearer_auth(AUTH_TOKEN)
.json(&serde_json::json!({
"model": "mock-model-v1",
"messages": [{"role": "user", "content": "Hi"}]
}))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 503);
}
#[tokio::test]
async fn test_chat_completions_body_too_large() {
let (addr, _state) = start_test_server().await;
let url = format!("http://{}/v1/chat/completions", addr);
// Build a payload over 1 MB (the gateway's DefaultBodyLimit)
let big_content = "x".repeat(2 * 1024 * 1024);
let resp = client()
.post(&url)
.bearer_auth(AUTH_TOKEN)
.json(&serde_json::json!({
"model": "mock-model-v1",
"messages": [{"role": "user", "content": big_content}]
}))
.send()
.await
.unwrap();
assert_eq!(resp.status(), 413);
}