use anyhow::Result; use async_trait::async_trait; use openhuman_core::openhuman::agent::dispatcher::NativeToolDispatcher; use openhuman_core::openhuman::agent::harness::definition::AgentTier; use openhuman_core::openhuman::agent::harness::session::Agent; use openhuman_core::openhuman::agent::harness::{ run_subagent, with_parent_context, AgentDefinition, DefinitionSource, ModelSpec, ParentExecutionContext, PromptSource, SandboxMode, SubagentRunOptions, ToolScope, }; use openhuman_core::openhuman::config::AgentConfig; use openhuman_core::openhuman::context::prompt::{ render_ambient_environment, render_subagent_system_prompt, render_tools, render_user_files, ConnectedIntegration, CuratedMemoryPromptSnapshot, LearnedContextData, NamespaceSummary, PersonalityRosterEntry, PromptContext, PromptTool, SubagentRenderOptions, SystemPromptBuilder, ToolCallFormat, UserIdentity, }; use openhuman_core::openhuman::inference::provider::traits::ProviderCapabilities; use openhuman_core::openhuman::inference::provider::{ ChatMessage, ChatRequest, ChatResponse, Provider, ToolCall, UsageInfo, }; use openhuman_core::openhuman::memory::{ Memory, MemoryCategory, MemoryEntry, NamespaceSummary as MemoryNamespaceSummary, RecallOpts, }; use openhuman_core::openhuman::tokenjuice::AgentTokenjuiceCompression; use openhuman_core::openhuman::tools::{PermissionLevel, Tool, ToolContent, ToolResult}; use parking_lot::Mutex; use serde_json::json; use std::collections::{HashSet, VecDeque}; use std::path::{Path, PathBuf}; use std::sync::Arc; use tempfile::TempDir; struct ScriptedProvider { responses: Mutex>>, requests: Mutex>, native_tools: bool, } #[derive(Clone)] struct CapturedRequest { messages: Vec, tool_names: Vec, } impl ScriptedProvider { fn new(responses: Vec) -> Arc { Arc::new(Self { responses: Mutex::new(responses.into_iter().map(Ok).collect()), requests: Mutex::new(Vec::new()), native_tools: true, }) } fn requests(&self) -> Vec { self.requests.lock().clone() } } #[async_trait] impl Provider for ScriptedProvider { fn capabilities(&self) -> ProviderCapabilities { ProviderCapabilities { native_tool_calling: self.native_tools, vision: false, } } async fn chat_with_system( &self, _system_prompt: Option<&str>, message: &str, _model: &str, _temperature: f64, ) -> Result { Ok(format!("checkpoint:{message}")) } async fn chat( &self, request: ChatRequest<'_>, _model: &str, _temperature: f64, ) -> Result { self.requests.lock().push(CapturedRequest { messages: request.messages.to_vec(), tool_names: request .tools .map(|tools| tools.iter().map(|tool| tool.name.clone()).collect()) .unwrap_or_default(), }); self.responses .lock() .pop_front() .unwrap_or_else(|| Ok(text_response("fallback final"))) } } #[derive(Default)] struct StubMemory { entries: Mutex>, } #[async_trait] impl Memory for StubMemory { fn name(&self) -> &str { "round19-memory" } async fn store( &self, namespace: &str, key: &str, content: &str, category: MemoryCategory, session_id: Option<&str>, ) -> Result<()> { let mut entries = self.entries.lock(); let id = format!("{namespace}:{key}:{}", entries.len()); entries.push(MemoryEntry { id, key: key.to_string(), content: content.to_string(), namespace: Some(namespace.to_string()), category, timestamp: "2026-05-29T00:00:00Z".to_string(), session_id: session_id.map(str::to_string), score: Some(0.9), taint: Default::default(), }); Ok(()) } async fn recall( &self, _query: &str, limit: usize, _opts: RecallOpts<'_>, ) -> Result> { Ok(self.entries.lock().iter().take(limit).cloned().collect()) } async fn get(&self, namespace: &str, key: &str) -> Result> { Ok(self .entries .lock() .iter() .find(|entry| entry.namespace.as_deref() == Some(namespace) && entry.key == key) .cloned()) } async fn list( &self, namespace: Option<&str>, category: Option<&MemoryCategory>, session_id: Option<&str>, ) -> Result> { Ok(self .entries .lock() .iter() .filter(|entry| namespace.is_none_or(|ns| entry.namespace.as_deref() == Some(ns))) .filter(|entry| category.is_none_or(|cat| &entry.category == cat)) .filter(|entry| session_id.is_none_or(|sid| entry.session_id.as_deref() == Some(sid))) .cloned() .collect()) } async fn forget(&self, namespace: &str, key: &str) -> Result { let mut entries = self.entries.lock(); let before = entries.len(); entries.retain(|entry| entry.namespace.as_deref() != Some(namespace) || entry.key != key); Ok(entries.len() != before) } async fn namespace_summaries(&self) -> Result> { Ok(Vec::new()) } async fn count(&self) -> Result { Ok(self.entries.lock().len()) } async fn health_check(&self) -> bool { true } } struct EchoTool { name: &'static str, permission: PermissionLevel, } #[async_trait] impl Tool for EchoTool { fn name(&self) -> &str { self.name } fn description(&self) -> &str { "round19 deterministic echo" } fn parameters_schema(&self) -> serde_json::Value { json!({ "type": "object", "properties": { "alpha": { "type": "string" }, "zeta": { "type": "string" } } }) } async fn execute(&self, args: serde_json::Value) -> Result { Ok(ToolResult { content: vec![ToolContent::Text { text: format!("echo:{args}"), }], is_error: false, markdown_formatted: Some(format!("**echo** `{args}`")), }) } fn permission_level(&self) -> PermissionLevel { self.permission } } fn tool(name: &'static str) -> Box { Box::new(EchoTool { name, permission: PermissionLevel::ReadOnly, }) } fn text_response(text: &str) -> ChatResponse { ChatResponse { text: Some(text.to_string()), tool_calls: Vec::new(), usage: Some(UsageInfo { input_tokens: 11, output_tokens: 5, context_window: 8_192, cached_input_tokens: 3, charged_amount_usd: 0.002, }), reasoning_content: None, } } fn empty_response() -> ChatResponse { ChatResponse { text: None, tool_calls: Vec::new(), usage: None, reasoning_content: None, } } fn tool_response(id: &str, name: &str, arguments: serde_json::Value) -> ChatResponse { ChatResponse { text: Some("using tool".to_string()), tool_calls: vec![ToolCall { id: id.to_string(), name: name.to_string(), arguments: arguments.to_string(), extra_content: None, }], usage: Some(UsageInfo { input_tokens: 7, output_tokens: 2, context_window: 8_192, cached_input_tokens: 1, charged_amount_usd: 0.001, }), reasoning_content: Some("because tool".to_string()), } } fn agent_config(max_tool_iterations: usize) -> AgentConfig { AgentConfig { max_tool_iterations, max_history_messages: 8, ..AgentConfig::default() } } fn build_agent( workspace: &Path, provider: Arc, tools: Vec>, ) -> Result { let mut agent = Agent::builder() .provider_arc(provider) .tools(tools) .memory(Arc::new(StubMemory::default())) .tool_dispatcher(Box::new(NativeToolDispatcher)) .config(agent_config(3)) .model_name("round19-model".to_string()) .temperature(0.0) .workspace_dir(workspace.to_path_buf()) .workflows(Vec::new()) .auto_save(false) .event_context("round19-session", "round19-channel") .agent_definition_name("round19_agent") .omit_profile(true) .omit_memory_md(true) .explicit_preferences_enabled(false) .build()?; agent.set_connected_integrations(Vec::new()); Ok(agent) } fn prompt_context<'a>( workspace: &'a Path, tools: &'a [PromptTool<'a>], visible: &'a HashSet, learned: LearnedContextData, format: ToolCallFormat, ) -> PromptContext<'a> { PromptContext { workspace_dir: workspace, model_name: "round19-model", agent_id: "round19_agent", tools, workflows: &[], dispatcher_instructions: "dispatcher guidance", learned, visible_tool_names: visible, tool_call_format: format, connected_integrations: &[], connected_identities_md: String::new(), include_profile: false, include_memory_md: false, curated_snapshot: None, user_identity: None, personality_soul_md: None, personality_memory_md: None, personality_roster: Vec::new(), } } fn definition(max_result_chars: Option) -> AgentDefinition { AgentDefinition { id: "round19_worker".to_string(), when_to_use: "raw coverage worker".to_string(), display_name: Some("Round 19 Worker".to_string()), system_prompt: PromptSource::Inline("Worker prompt".to_string()), omit_identity: true, omit_memory_context: false, omit_safety_preamble: true, omit_skills_catalog: true, omit_profile: true, omit_memory_md: true, model: ModelSpec::Inherit, temperature: 0.0, tools: ToolScope::Wildcard, disallowed_tools: Vec::new(), skill_filter: None, extra_tools: Vec::new(), max_iterations: 2, iteration_policy: Default::default(), max_result_chars, timeout_secs: None, sandbox_mode: SandboxMode::None, background: false, trigger_memory_agent: Default::default(), tokenjuice_compression: AgentTokenjuiceCompression::Auto, subagents: Vec::new(), delegate_name: None, agent_tier: AgentTier::Worker, source: DefinitionSource::Builtin, } } fn parent_context(workspace: PathBuf, provider: Arc) -> ParentExecutionContext { let tools = vec![tool("echo")]; let specs = tools.iter().map(|tool| tool.spec()).collect(); ParentExecutionContext { agent_definition_id: "orchestrator".into(), allowed_subagent_ids: [ "test".to_string(), "researcher".to_string(), "code_executor".to_string(), ] .into_iter() .collect(), provider, all_tools: Arc::new(tools), all_tool_specs: Arc::new(specs), visible_tool_names: std::collections::HashSet::new(), model_name: "round19-parent".to_string(), temperature: 0.0, workspace_dir: workspace, memory: Arc::new(StubMemory::default()), agent_config: agent_config(3), workflows: Arc::new(Vec::new()), memory_context: Arc::new(Some("parent memory context".to_string())), session_id: "round19-parent-session".to_string(), channel: "round19-channel".to_string(), connected_integrations: Vec::new(), tool_call_format: ToolCallFormat::Native, session_key: "1700000000_parent".to_string(), session_parent_prefix: Some("root-chain".to_string()), on_progress: None, run_queue: None, } } #[tokio::test] async fn turn_rejects_empty_final_response_and_keeps_history_nonfinal() -> Result<()> { let tmp = TempDir::new()?; let provider = ScriptedProvider::new(vec![empty_response()]); let mut agent = build_agent(tmp.path(), provider, vec![tool("echo")])?; let err = agent.turn("return an empty response").await.unwrap_err(); assert!(err.to_string().contains("empty response")); assert!(agent .history() .iter() .any(|message| matches!(message, openhuman_core::openhuman::inference::provider::ConversationMessage::Chat(chat) if chat.role == "user"))); Ok(()) } #[tokio::test] async fn turn_dedups_visible_tool_specs_and_preserves_reasoning_metadata() -> Result<()> { let tmp = TempDir::new()?; let mut first = text_response("first final"); first.reasoning_content = Some("private reasoning trace".to_string()); let provider = ScriptedProvider::new(vec![first, text_response("second final")]); let mut agent = build_agent( tmp.path(), provider.clone(), vec![tool("echo"), tool("echo")], )?; assert_eq!("first final", agent.turn("first").await?); assert_eq!("second final", agent.turn("second").await?); let requests = provider.requests(); assert_eq!(requests[0].tool_names, vec!["echo"]); assert!(requests[1].messages.iter().any(|message| message .extra_metadata .as_ref() .and_then(|metadata| metadata.get("reasoning_content")) .and_then(serde_json::Value::as_str) == Some("private reasoning trace"))); Ok(()) } #[tokio::test] async fn seed_resume_bounds_unknown_roles_and_drops_current_tail() -> Result<()> { let tmp = TempDir::new()?; let provider = ScriptedProvider::new(vec![text_response("resumed final")]); let mut agent = build_agent(tmp.path(), provider.clone(), vec![tool("echo")])?; agent.seed_resume_from_messages( vec![ ("user".to_string(), "older question".to_string()), ("bot".to_string(), "unknown sender becomes user".to_string()), ("assistant".to_string(), "prior assistant".to_string()), ("user".to_string(), "current question".to_string()), ], "current question", )?; assert_eq!("resumed final", agent.turn("current question").await?); let first_request = provider.requests().remove(0); let sent = first_request .messages .iter() .map(|message| format!("{}:{}", message.role, message.content)) .collect::>() .join("\n"); assert!(sent.contains("user:unknown sender becomes user")); assert!(sent.contains("assistant:prior assistant")); assert_eq!(sent.matches("current question").count(), 1); Ok(()) } #[tokio::test] async fn builder_reports_missing_required_fields_in_validation_order() -> Result<()> { let tmp = TempDir::new()?; let provider = ScriptedProvider::new(vec![text_response("unused")]); let err = match Agent::builder().build() { Ok(_) => panic!("builder without tools should fail"), Err(err) => err, }; assert!(err.to_string().contains("tools are required")); let err = match Agent::builder().tools(Vec::new()).build() { Ok(_) => panic!("builder without provider should fail"), Err(err) => err, }; assert!(err.to_string().contains("provider is required")); let err = match Agent::builder() .tools(Vec::new()) .provider_arc(provider) .workspace_dir(tmp.path().to_path_buf()) .build() { Ok(_) => panic!("builder without memory should fail"), Err(err) => err, }; assert!(err.to_string().contains("memory is required")); Ok(()) } #[tokio::test] async fn subagent_run_truncates_capped_final_output_after_parent_context_run() -> Result<()> { let tmp = TempDir::new()?; let provider = ScriptedProvider::new(vec![text_response("abcdef")]); let parent = parent_context(tmp.path().to_path_buf(), provider); let outcome = with_parent_context(parent, async { run_subagent( &definition(Some(3)), "do a tiny task", SubagentRunOptions { task_id: Some("round19-task".to_string()), ..SubagentRunOptions::default() }, ) .await }) .await?; assert_eq!(outcome.output, "abc\n[...truncated]"); assert_eq!(outcome.iterations, 1); Ok(()) } #[tokio::test] async fn subagent_repeated_unknown_tool_halts_with_root_cause() -> Result<()> { let tmp = TempDir::new()?; let provider = ScriptedProvider::new(vec![ tool_response("call-1", "missing_tool", json!({"same": true})), tool_response("call-2", "missing_tool", json!({"same": true})), tool_response("call-3", "missing_tool", json!({"same": true})), ]); let parent = parent_context(tmp.path().to_path_buf(), provider); let mut def = definition(None); def.max_iterations = 3; let outcome = with_parent_context(parent, async { run_subagent( &def, "repeat an unavailable tool", SubagentRunOptions::default(), ) .await }) .await?; assert!(outcome.output.contains("repeating it will not help")); assert!(outcome .output .contains("tool 'missing_tool' is not available")); assert_eq!(outcome.iterations, 3); Ok(()) } #[test] fn prompt_builder_renders_dynamic_user_files_and_identity_branches() -> Result<()> { let tmp = TempDir::new()?; std::fs::write(tmp.path().join("PROFILE.md"), "Profile body")?; std::fs::write(tmp.path().join("MEMORY.md"), "Workspace memory body")?; let visible = HashSet::new(); let tools = vec![PromptTool::with_schema( "echo", "Echo tool", json!({"type":"object","properties":{"zeta":{},"alpha":{}}}).to_string(), )]; let mut learned = LearnedContextData::default(); learned.reflections = vec![" prefers concise updates ".to_string(), " ".to_string()]; learned.tree_root_summaries = vec![NamespaceSummary { namespace: "work".to_string(), body: "Durable memory".to_string(), updated_at: chrono::DateTime::parse_from_rfc3339("2026-05-20T00:00:00Z")? .with_timezone(&chrono::Utc), }]; let mut ctx = prompt_context( tmp.path(), &tools, &visible, learned, ToolCallFormat::PFormat, ); ctx.include_profile = true; ctx.include_memory_md = true; ctx.curated_snapshot = Some(Arc::new(CuratedMemoryPromptSnapshot { memory: "Curated memory".to_string(), user: "Curated user".to_string(), })); ctx.user_identity = Some(UserIdentity { id: Some(" user\nid ".to_string()), name: Some(" Ada\r Lovelace ".to_string()), email: Some(" ada@example.test ".to_string()), }); ctx.personality_roster = vec![PersonalityRosterEntry { id: "critic".to_string(), name: "Critic".to_string(), description: "Reviews plans".to_string(), memory_summary: Some("x".repeat(240)), }]; let prompt = SystemPromptBuilder::from_dynamic(|ctx| { let mut out = String::new(); out.push_str(&render_user_files(ctx)?); out.push_str(&render_tools(ctx)?); out.push_str(&render_ambient_environment(ctx)?); Ok(out) }) .build(&ctx)?; assert!(prompt.contains("### PROFILE.md")); assert!(prompt.contains("Curated memory")); assert!(prompt.contains("Curated user")); assert!(prompt.contains("echo[alpha|zeta]")); assert!(prompt.contains("- name: Ada Lovelace")); assert!(prompt.contains("- id: user id")); assert!(prompt.contains("## Current Date & Time")); ctx.curated_snapshot = None; ctx.personality_memory_md = Some("Personality memory".to_string()); let user_files = render_user_files(&ctx)?; assert!(user_files.contains("Personality memory")); assert!(!user_files.contains("Workspace memory body")); Ok(()) } #[test] fn subagent_prompt_renderer_handles_formats_caps_and_stale_tool_indices() -> Result<()> { let tmp = TempDir::new()?; std::fs::write(tmp.path().join("PROFILE.md"), "P".repeat(2_100))?; std::fs::write(tmp.path().join("MEMORY.md"), "Memory file")?; let parent_tools = vec![tool("echo")]; let options = SubagentRenderOptions { include_safety_preamble: true, include_identity: false, include_skills_catalog: false, include_profile: true, include_memory_md: true, }; let connected = vec![ConnectedIntegration { toolkit: "gmail".to_string(), description: "Mail".to_string(), tools: Vec::new(), gated_tools: Vec::new(), connected: true, connections: Vec::new(), non_active_status: None, }]; let json_prompt = render_subagent_system_prompt( tmp.path(), "round19-model", &[0, 99], &parent_tools, &[tool("extra")], "Archetype", options, ToolCallFormat::Json, &connected, ); assert!(json_prompt.contains("Parameters:")); assert!(json_prompt.contains("extra")); assert!(json_prompt.contains("truncated at 2000 chars")); assert!(json_prompt.contains("## Safety")); assert!(json_prompt.contains("## Output style")); let native_prompt = render_subagent_system_prompt( tmp.path(), "round19-model", &[0], &parent_tools, &[], "", SubagentRenderOptions::narrow(), ToolCallFormat::Native, &[], ); assert!(!native_prompt.contains("## Tools")); assert!(native_prompt.contains("native tool-calling output")); Ok(()) }