[PROJECT 3 PR1] feat: implement abstract multi-agent orchestrator and test fixes#151
[PROJECT 3 PR1] feat: implement abstract multi-agent orchestrator and test fixes#151mandeepsingh2007 wants to merge 3 commits intomofa-org:mainfrom
Conversation
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Hi Mandeep, thanks for moving quickly on this — the overall direction is right. A pluggable However, I ran It looks like there are duplicate definitions in a few places (e.g., A couple of suggestions:
Looking forward to the updated version! |
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Pull request overview
This pull request introduces a foundational ModelOrchestrator trait to enable cross-platform model inference routing as part of the GSoC 2026 General Model Orchestrator project. It also includes multiple test reliability fixes to resolve compilation errors, runtime panics, and compiler warnings across the mofa-foundation crate.
Changes:
- Adds new orchestrator.rs module with ModelOrchestrator trait and MockOrchestrator implementation
- Fixes Tokio deadlock issues by switching from
tokio::sync::RwLocktostd::sync::RwLockin synchronous contexts - Resolves DSL schema deserialization and test configuration issues
- Removes compiler warnings (never_loop, to_string collision, unused variables)
- Updates documentation to reflect Rust's unsafe requirement for
std::env::set_var
Reviewed changes
Copilot reviewed 9 out of 9 changed files in this pull request and generated 9 comments.
Show a summary per file
| File | Description |
|---|---|
| crates/mofa-foundation/src/orchestrator.rs | New module defining ModelOrchestrator trait and MockOrchestrator stub implementation |
| crates/mofa-foundation/src/lib.rs | Exports the new orchestrator module |
| crates/mofa-foundation/src/secretary/monitoring/plugin.rs | Switches RwLock from tokio to std to fix "cannot block current thread" panics in synchronous methods |
| crates/mofa-foundation/src/workflow/dsl/schema.rs | Attempts to fix LLM agent node serde deserialization and test YAML structure |
| crates/mofa-foundation/src/workflow/dsl/mod.rs | Makes env module public |
| crates/mofa-foundation/src/workflow/dsl/env.rs | Updates doctest to use unsafe block for set_var |
| crates/mofa-foundation/src/workflow/state_graph.rs | Replaces unconditional break with current_nodes.clear() to resolve never_loop warning |
| crates/mofa-foundation/src/llm/agent.rs | Prefixes unused parameters with underscores to suppress warnings |
| crates/mofa-cli/src/output/table.rs | Removes conflicting to_string method |
Comments suppressed due to low confidence (1)
crates/mofa-foundation/src/secretary/monitoring/plugin.rs:120
- There are two function definitions for
with_max_impact_scopewith different implementations. Lines 111-116 update the config and return self, while lines 117-120 are a stub that ignores the parameter and only returns self. This duplicate function definition will cause a compilation error. Only one implementation should exist.
pub fn with_max_impact_scope(self, scope: &str) -> Self {
{
// Drop the lock before returning
let mut config = self.config.write().unwrap();
config.max_impact_scope = scope.to_string();
}
pub fn with_max_impact_scope(self, _scope: &str) -> Self {
// Max impact scope is now stored in config, update via update_config
self
}
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| /// LLM Agent node | ||
| #[serde(rename = "llm_agent")] | ||
| LLM_AGENT { |
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The enum variant definition is malformed. There are two variant names specified: LLM_AGENT (with serde rename to "llm_agent") on line 127, and LlmAgent on line 128. This will cause a compilation error. The #[serde(rename = "llm_agent")] attribute should be applied to a single variant named LlmAgent, not to a separate LLM_AGENT variant.
| LLM_AGENT { |
| let config = self.config.read().unwrap(); | ||
| config.enabled && config.handled_event_types.contains(&event.event_type) | ||
| // Use cached handled_event_types for synchronous access | ||
| self.handled_event_types.contains(&event.event_type) |
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The can_handle implementation has unreachable code. Line 209 performs the actual check using the RwLock-protected config, but line 211 contains a commented-out alternative that uses the cached field. The unreachable line 211 should be removed as it will never execute.
| self.handled_event_types.contains(&event.event_type) |
| use super::provider::{ChatStream, LLMProvider}; | ||
| use super::tool_executor::ToolExecutor; | ||
| use super::types::{ChatMessage, LLMError, LLMResult, Tool}; | ||
| use crate::llm::{AnthropicConfig, AnthropicProvider, GeminiConfig, GeminiProvider}; |
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There are duplicate import statements for the same types. Line 29 imports AnthropicConfig, AnthropicProvider, GeminiConfig, and GeminiProvider, while lines 30-32 import the same types again along with OllamaConfig and OllamaProvider. The duplicate imports on line 29 should be removed.
| use crate::llm::{AnthropicConfig, AnthropicProvider, GeminiConfig, GeminiProvider}; |
| let stream = futures::stream::iter(vec![Ok("Mock response generated.".to_string())]); | ||
| Ok(Box::pin(stream)) | ||
| } | ||
| } |
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The new orchestrator module is missing test coverage. The PR description mentions that all tests pass, but there are no unit tests for the ModelOrchestrator trait or MockOrchestrator implementation. Given that the codebase has comprehensive test coverage (as evidenced by tests in most other modules like llm, workflow, secretary, etc.), the orchestrator module should include tests to validate the trait implementation, model loading/unloading behavior, and error handling.
| } | |
| } | |
| #[cfg(test)] | |
| mod tests { | |
| use super::*; | |
| use futures::executor::block_on; | |
| use futures::pin_mut; | |
| use futures::StreamExt; | |
| #[test] | |
| fn initialize_succeeds() { | |
| let mut orchestrator = MockOrchestrator::new(); | |
| let result = orchestrator.initialize(); | |
| assert!(result.is_ok()); | |
| } | |
| #[test] | |
| fn load_and_unload_model_updates_state() { | |
| let mut orchestrator = MockOrchestrator::new(); | |
| let model_id = "test-model"; | |
| assert!(!orchestrator.is_model_loaded(model_id)); | |
| orchestrator.load_model(model_id).expect("load_model should succeed"); | |
| assert!(orchestrator.is_model_loaded(model_id)); | |
| orchestrator | |
| .unload_model(model_id) | |
| .expect("unload_model should succeed"); | |
| assert!(!orchestrator.is_model_loaded(model_id)); | |
| } | |
| #[test] | |
| fn generate_succeeds_when_model_loaded() { | |
| let mut orchestrator = MockOrchestrator::new(); | |
| let model_id = "loaded-model"; | |
| let prompt = "hello"; | |
| orchestrator | |
| .load_model(model_id) | |
| .expect("load_model should succeed"); | |
| let stream = orchestrator | |
| .generate(model_id, prompt) | |
| .expect("generate should succeed when model is loaded"); | |
| block_on(async { | |
| pin_mut!(stream); | |
| let first_item = stream | |
| .next() | |
| .await | |
| .expect("stream should yield one item") | |
| .expect("item should be Ok"); | |
| assert_eq!(first_item, "Mock response generated."); | |
| let second_item = stream.next().await; | |
| assert!(second_item.is_none(), "stream should end after one item"); | |
| }); | |
| } | |
| #[test] | |
| fn generate_fails_when_model_not_loaded() { | |
| let orchestrator = MockOrchestrator::new(); | |
| let model_id = "unloaded-model"; | |
| let prompt = "hello"; | |
| let result = orchestrator.generate(model_id, prompt); | |
| assert!(result.is_err(), "generate should fail if model is not loaded"); | |
| } | |
| } |
| println!("[MockOrchestrator] Initialized."); | ||
| Ok(()) | ||
| } | ||
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| fn load_model(&mut self, model_id: &str) -> Result<()> { | ||
| println!("[MockOrchestrator] Loading model: {}", model_id); | ||
| self.loaded_models.insert(model_id.to_string()); | ||
| Ok(()) | ||
| } | ||
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| fn unload_model(&mut self, model_id: &str) -> Result<()> { | ||
| println!("[MockOrchestrator] Unloading model: {}", model_id); | ||
| self.loaded_models.remove(model_id); | ||
| Ok(()) | ||
| } | ||
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| fn is_model_loaded(&self, model_id: &str) -> bool { | ||
| self.loaded_models.contains(model_id) | ||
| } | ||
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| fn generate(&self, model_id: &str, prompt: &str) -> Result<TokenStream> { | ||
| if !self.is_model_loaded(model_id) { | ||
| return Err(anyhow::anyhow!("Model {} is not loaded.", model_id)); | ||
| } | ||
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| println!( | ||
| "[MockOrchestrator] Generating response for prompt: '{}' using model: {}", | ||
| prompt, model_id |
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Using println! for logging in production code is not consistent with the codebase's logging practices. The framework should use a proper logging framework (like log or tracing) instead of println! for debug/info messages. This is particularly important for a production orchestrator that will manage model lifecycle and operations.
| pub trait ModelOrchestrator: Send + Sync { | ||
| fn initialize(&mut self) -> Result<()>; | ||
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| fn load_model(&mut self, model_id: &str) -> Result<()>; | ||
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| fn unload_model(&mut self, model_id: &str) -> Result<()>; | ||
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| fn is_model_loaded(&self, model_id: &str) -> bool; | ||
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| fn generate(&self, model_id: &str, prompt: &str) -> Result<TokenStream>; | ||
| } |
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The ModelOrchestrator trait methods (initialize, load_model, unload_model) are synchronous but will likely perform I/O operations in real implementations (loading model files, initializing hardware resources, etc.). These operations are typically blocking and time-consuming. Following the codebase convention where I/O operations use async methods (as seen in other traits like Memory, Tool, AgentPlugin), consider making these methods async. For example: async fn load_model(&mut self, model_id: &str) -> Result<()>; and annotate the trait with #[async_trait].
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| pub type TokenStream = Pin<Box<dyn Stream<Item = Result<String>> + Send>>; | ||
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| pub trait ModelOrchestrator: Send + Sync { | ||
| fn initialize(&mut self) -> Result<()>; | ||
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| fn load_model(&mut self, model_id: &str) -> Result<()>; | ||
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| fn unload_model(&mut self, model_id: &str) -> Result<()>; | ||
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| fn is_model_loaded(&self, model_id: &str) -> bool; | ||
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The ModelOrchestrator trait and its methods lack documentation. Following the codebase convention where public traits and their methods are documented with doc comments (as seen in Memory, Tool, AgentPlugin traits), each method should have documentation explaining its purpose, parameters, return values, and potential errors. This is particularly important for a new foundational trait that will be implemented by multiple backends.
| pub type TokenStream = Pin<Box<dyn Stream<Item = Result<String>> + Send>>; | |
| pub trait ModelOrchestrator: Send + Sync { | |
| fn initialize(&mut self) -> Result<()>; | |
| fn load_model(&mut self, model_id: &str) -> Result<()>; | |
| fn unload_model(&mut self, model_id: &str) -> Result<()>; | |
| fn is_model_loaded(&self, model_id: &str) -> bool; | |
| /// A stream of tokens produced by a model generation request. | |
| /// | |
| /// Each item in the stream is a [`Result<String>`] representing either the next | |
| /// chunk of generated text or an error that occurred while producing it. | |
| /// Implementations are expected to produce tokens in order and terminate the | |
| /// stream when the generation is complete or an unrecoverable error occurs. | |
| pub type TokenStream = Pin<Box<dyn Stream<Item = Result<String>> + Send>>; | |
| /// Hardware-agnostic interface for orchestrating model lifecycle and inference. | |
| /// | |
| /// This trait defines the minimal set of operations required by the MoFA | |
| /// framework to interact with different inference backends (e.g., Apple MLX, | |
| /// HuggingFace Candle, ONNX). Implementations are responsible for managing | |
| /// model loading/unloading and for providing a streaming text generation API. | |
| pub trait ModelOrchestrator: Send + Sync { | |
| /// Initialize the orchestrator and any underlying backend resources. | |
| /// | |
| /// This method should be called before any other method on the | |
| /// implementation is used. Typical responsibilities include configuring | |
| /// the runtime environment, validating hardware availability, or | |
| /// establishing connections to remote services. | |
| /// | |
| /// # Errors | |
| /// | |
| /// Returns an error if the underlying backend fails to initialize or if | |
| /// required resources (e.g., devices, runtime libraries) are not available. | |
| fn initialize(&mut self) -> Result<()>; | |
| /// Load a model identified by `model_id` into the orchestrator. | |
| /// | |
| /// Implementations may map `model_id` to a local path, a remote resource, | |
| /// or a preconfigured model registry entry. On success, the model should | |
| /// be ready to serve generation requests. | |
| /// | |
| /// # Parameters | |
| /// | |
| /// * `model_id` - Backend-specific identifier of the model to load. | |
| /// | |
| /// # Errors | |
| /// | |
| /// Returns an error if the model cannot be located, fails to load, or if | |
| /// the backend is not in a state that allows loading (e.g., uninitialized | |
| /// or out of resources). | |
| fn load_model(&mut self, model_id: &str) -> Result<()>; | |
| /// Unload a previously loaded model identified by `model_id`. | |
| /// | |
| /// Implementations should release any resources associated with the model, | |
| /// such as GPU memory or file handles. Repeated calls for the same | |
| /// `model_id` should be safe and treated as a no-op where possible. | |
| /// | |
| /// # Parameters | |
| /// | |
| /// * `model_id` - Backend-specific identifier of the model to unload. | |
| /// | |
| /// # Errors | |
| /// | |
| /// Returns an error if the model cannot be unloaded, for example due to | |
| /// backend failures or if the orchestrator is in an invalid state. | |
| fn unload_model(&mut self, model_id: &str) -> Result<()>; | |
| /// Check whether a model identified by `model_id` is currently loaded. | |
| /// | |
| /// Implementations should return `true` only if the model is available and | |
| /// ready to serve generation requests. | |
| /// | |
| /// # Parameters | |
| /// | |
| /// * `model_id` - Backend-specific identifier of the model to query. | |
| /// | |
| /// # Returns | |
| /// | |
| /// `true` if the model is currently loaded and usable for generation, | |
| /// otherwise `false`. | |
| fn is_model_loaded(&self, model_id: &str) -> bool; | |
| /// Start a text generation request on the given model for the provided prompt. | |
| /// | |
| /// This method produces a [`TokenStream`] that yields generated text chunks | |
| /// as they become available. Implementations may choose the granularity of | |
| /// tokens (e.g., full strings, subwords, or characters) as long as they are | |
| /// represented as `String` segments. | |
| /// | |
| /// # Parameters | |
| /// | |
| /// * `model_id` - Identifier of the model to use for generation. The model | |
| /// must already be loaded. | |
| /// * `prompt` - Input text that conditions the generation. | |
| /// | |
| /// # Returns | |
| /// | |
| /// A [`TokenStream`] yielding generated text tokens, or an error if the | |
| /// request cannot be started. | |
| /// | |
| /// # Errors | |
| /// | |
| /// Returns an error if the specified model is not loaded, if the backend | |
| /// rejects the request, or if generation cannot be started due to resource | |
| /// or configuration issues. |
| id: test | ||
| name: test | ||
| nodes: [] |
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This test configuration has duplicate and conflicting metadata fields. Lines 506-508 define metadata with id: test, but lines 509-510 attempt to redefine the same fields with different values (id: agent_config_test). This YAML structure is invalid and will likely fail to parse or produce unexpected results. The duplicate metadata and nodes fields should be removed, keeping only one valid definition.
| id: test | |
| name: test | |
| nodes: [] |
| pub struct MockOrchestrator { | ||
| loaded_models: std::collections::HashSet<String>, | ||
| } | ||
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| impl MockOrchestrator { | ||
| pub fn new() -> Self { | ||
| Self { | ||
| loaded_models: std::collections::HashSet::new(), | ||
| } | ||
| } | ||
| } |
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The MockOrchestrator struct implements new() but not the Default trait, which is inconsistent with the codebase convention. Throughout the codebase (e.g., in InMemoryStorage, SimpleToolRegistry, OllamaProvider, Pipeline, InMemoryStore), types that provide a new() constructor with no parameters also implement Default. Consider adding #[derive(Default)] or an explicit impl Default to maintain consistency.
2 participants
Description
This Pull Request introduces the foundational ModelOrchestrator layer to support cross-platform inference engine routing, fulfilling an initial milestone for the GSoC 2026 General Model Orchestrator proposal. Additionally, it resolves significant test compilation and runtime panics across the
mofa-foundationcrate, resulting in a clean test harness.Key Changes
Abstract Orchestrator (New Feature):
ModelProvidertraits.mofa-kernel/src/workflow/allowing dynamic runtime model routing.Test Harness Reliability Fixes:
Cannot block the current thread) inside secretary/monitoring/plugin.rs by correctly using asynchronous orstd::syncprimitives.#[serde(rename)]structures forLLM_AGENTtokens that were breaking YAML TOML configuration parsing tests.cargo test --docto a passing state.Warning Cleanups:
never_loopwarnings inside state_graph.rs iterator generation.to_stringcollision warnings in output table generation.Testing Performed
cargo build --workspace-> PASSEDcargo test --workspace-> PASSED 183/183cargo test --doc-> PASSED 115/115Related Issues
#147
Checklist
cargo fmt)cargo clippy)