refactor: Enhance Agent and Tool management with new methods and tests

- Added environment variable-based LLM client initialization in `Agent::new()`
- Introduced `add_tool()` and `add_tools()` methods for more flexible tool registration
- Implemented new `get_name()` method for `ToolExecutor` trait
- Added comprehensive test cases for Agent with and without tools
- Updated `AgentThread` with a convenient constructor method
- Temporarily commented out unused tool modules
- Added debug print in LiteLLM client for response logging

api/Cargo.toml

@@ -94,7 +94,8 @@ html-escape = "0.2.13"
 async-trait = "0.1.85"
 
 [dev-dependencies]
-mockito = "1.2"
+mockito = "1.2.0"
+async-trait = "0.1.77"
 tokio = { version = "1.0", features = ["full", "test-util"] }
 
 [profile.release]

api/src/utils/agent/agent.rs

@@ -1,9 +1,13 @@
-use crate::utils::{clients::ai::litellm::{ChatCompletionRequest, LiteLLMClient, Message, Tool}, tools::ToolExecutor};
+use crate::utils::{
+    clients::ai::litellm::{ChatCompletionRequest, LiteLLMClient, Message, Tool},
+    tools::ToolExecutor,
+};
 use anyhow::Result;
-use std::collections::HashMap;
+use std::{collections::HashMap, env};
 use tokio::sync::mpsc;
+use async_trait::async_trait;
 
-use super::types::{AgentThread};
+use super::types::AgentThread;
 
 /// The Agent struct is responsible for managing conversations with the LLM
 /// and coordinating tool executions. It maintains a registry of available tools
@@ -19,11 +23,12 @@ pub struct Agent {
 
 impl Agent {
     /// Create a new Agent instance with a specific LLM client and model
-    pub fn new(
-        llm_client: LiteLLMClient,
-        model: String,
-        tools: HashMap<String, Box<dyn ToolExecutor>>,
-    ) -> Self {
+    pub fn new(model: String, tools: HashMap<String, Box<dyn ToolExecutor>>) -> Self {
+        let llm_api_key = env::var("LLM_API_KEY").expect("LLM_API_KEY must be set");
+        let llm_base_url = env::var("LLM_BASE_URL").expect("LLM_API_BASE must be set");
+
+        let llm_client = LiteLLMClient::new(Some(llm_api_key), Some(llm_base_url));
+
         Self {
             llm_client,
             tools,
@@ -31,13 +36,23 @@ impl Agent {
         }
     }
 
-    /// Register a new tool with the agent
+    /// Add a new tool with the agent
     ///
     /// # Arguments
     /// * `name` - The name of the tool, used to identify it in tool calls
     /// * `tool` - The tool implementation that will be executed
-    pub fn register_tool(&mut self, name: String, tool: Box<dyn ToolExecutor>) {
-        self.tools.insert(name, tool);
+    pub fn add_tool<T: ToolExecutor + 'static>(&mut self, name: String, tool: T) {
+        self.tools.insert(name, Box::new(tool));
+    }
+
+    /// Add multiple tools to the agent at once
+    ///
+    /// # Arguments
+    /// * `tools` - HashMap of tool names and their implementations
+    pub fn add_tools<T: ToolExecutor + 'static>(&mut self, tools: HashMap<String, T>) {
+        for (name, tool) in tools {
+            self.tools.insert(name, Box::new(tool));
+        }
     }
 
     /// Process a thread of conversation, potentially executing tools and continuing
@@ -63,16 +78,20 @@ impl Agent {
         let request = ChatCompletionRequest {
             model: self.model.clone(),
             messages: thread.messages.clone(),
-            tools: Some(tools),
+            tools: if tools.is_empty() { None } else { Some(tools) },
             ..Default::default()
         };
 
         // Get the response from the LLM
-        let response = self.llm_client.chat_completion(request).await?;
+        let response = match self.llm_client.chat_completion(request).await {
+            Ok(response) => response,
+            Err(e) => return Err(anyhow::anyhow!("Error processing thread: {:?}", e)),
+        };
+
         let llm_message = &response.choices[0].message;
 
         // Create the initial assistant message
-        let mut message = match llm_message {
+        let message = match llm_message {
             Message::Assistant {
                 content,
                 tool_calls,
@@ -179,3 +198,123 @@ impl Agent {
         Ok(rx)
     }
 }
+
+#[cfg(test)]
+mod tests {
+    use crate::utils::clients::ai::litellm::ToolCall;
+
+    use super::*;
+    use dotenv::dotenv;
+    use serde_json::{json, Value};
+
+    fn setup() {
+        dotenv().ok();
+    }
+
+    struct WeatherTool;
+
+    #[async_trait]
+    impl ToolExecutor for WeatherTool {
+        async fn execute(&self, tool_call: &ToolCall) -> Result<Value> {
+            Ok(json!({
+                "temperature": 20,
+                "unit": "fahrenheit"
+            }))
+        }
+
+        fn get_schema(&self) -> Value {
+            json!({
+                "name": "get_weather",
+                "description": "Get current weather information for a specific location",
+                "parameters": {
+                    "type": "object",
+                    "properties": {
+                        "location": {
+                            "type": "string",
+                            "description": "The city and state, e.g., San Francisco, CA"
+                        },
+                        "unit": {
+                            "type": "string",
+                            "enum": ["celsius", "fahrenheit"],
+                            "description": "The temperature unit to use"
+                        }
+                    },
+                    "required": ["location"]
+                }
+            })
+        }
+
+        fn get_name(&self) -> String {
+            "get_weather".to_string()
+        }
+    }
+
+    #[tokio::test]
+    async fn test_agent_convo_no_tools() {
+        setup();
+
+        // Create LLM client and agent
+        let agent = Agent::new("o1".to_string(), HashMap::new());
+
+        let thread = AgentThread::new(None, vec![Message::user("Hello, world!".to_string())]);
+
+        let response = match agent.process_thread(&thread).await {
+            Ok(response) => response,
+            Err(e) => panic!("Error processing thread: {:?}", e),
+        };
+
+        println!("Response: {:?}", response);
+    }
+
+    #[tokio::test]
+    async fn test_agent_convo_with_tools() {
+        setup();
+
+        // Create LLM client and agent
+        let mut agent = Agent::new("o1".to_string(), HashMap::new());
+
+        let weather_tool = WeatherTool;
+
+        agent.add_tool(weather_tool.get_name(), weather_tool);
+
+        let thread = AgentThread::new(
+            None,
+            vec![Message::user(
+                "What is the weather in vineyard ut?".to_string(),
+            )],
+        );
+
+        let response = match agent.process_thread(&thread).await {
+            Ok(response) => response,
+            Err(e) => panic!("Error processing thread: {:?}", e),
+        };
+
+        println!("Response: {:?}", response);
+    }
+
+    #[tokio::test]
+    async fn test_agent_with_multiple_steps() {
+        setup();
+
+        // Create LLM client and agent
+        let mut agent = Agent::new("o1".to_string(), HashMap::new());
+
+        let weather_tool = WeatherTool;
+
+        agent.add_tool(weather_tool.get_name(), weather_tool);
+
+        let thread = AgentThread::new(
+            None,
+            vec![Message::user(
+                "What is the weather in vineyard ut and san francisco?".to_string(),
+            )],
+        );
+
+        let response = match agent.process_thread(&thread).await {
+            Ok(response) => response,
+            Err(e) => panic!("Error processing thread: {:?}", e),
+        };
+
+        println!("Response: {:?}", response);
+    }
+}

api/src/utils/agent/types.rs

@@ -11,3 +11,12 @@ pub struct AgentThread {
     /// Ordered sequence of messages in the conversation
     pub messages: Vec<Message>,
 }
+
+impl AgentThread {
+    pub fn new(id: Option<String>, messages: Vec<Message>) -> Self {
+        Self {
+            id: id.unwrap_or(uuid::Uuid::new_v4().to_string()),
+            messages,
+        }
+    }
+}

api/src/utils/clients/ai/litellm/client.rs

@@ -61,6 +61,9 @@ impl LiteLLMClient {
             .await?
             .json::<ChatCompletionResponse>()
             .await?;
+
+        println!("Response: {:?}", response);
+
         Ok(response)
     }
 
@@ -134,6 +137,20 @@ mod tests {
     use std::time::Duration;
     use tokio::time::timeout;
 
+    use dotenv::dotenv;
+
+    // Helper function to initialize environment before tests
+    async fn setup() -> (String, String) {
+        // Load environment variables from .env file
+        dotenv().ok();
+
+        // Get API key and base URL from environment
+        let api_key = env::var("LLM_API_KEY").expect("LLM_API_KEY must be set");
+        let base_url = env::var("LLM_BASE_URL").expect("LLM_API_BASE must be set");
+
+        (api_key, base_url)
+    }
+
     fn create_test_message() -> Message {
         Message::user("Hello".to_string())
     }
@@ -329,12 +346,20 @@ mod tests {
 
         let response = client.chat_completion(request).await.unwrap();
         assert_eq!(response.id, "test-id");
-        if let Message::Assistant { content, tool_calls, .. } = &response.choices[0].message {
+        if let Message::Assistant {
+            content,
+            tool_calls,
+            ..
+        } = &response.choices[0].message
+        {
             assert!(content.is_none());
             let tool_calls = tool_calls.as_ref().unwrap();
             assert_eq!(tool_calls[0].id, "call_123");
             assert_eq!(tool_calls[0].function.name, "get_current_weather");
-            assert_eq!(tool_calls[0].function.arguments, "{\"location\":\"Boston, MA\"}");
+            assert_eq!(
+                tool_calls[0].function.arguments,
+                "{\"location\":\"Boston, MA\"}"
+            );
         } else {
             panic!("Expected assistant message");
         }
@@ -368,4 +393,23 @@ mod tests {
         env::remove_var("LLM_API_KEY");
         env::remove_var("LLM_BASE_URL");
     }
+
+    #[tokio::test]
+    async fn test_single_message_completion() {
+        let (api_key, base_url) = setup().await;
+        let client = LiteLLMClient::new(Some(api_key), Some(base_url));
+
+        let request = ChatCompletionRequest {
+            model: "o1".to_string(),
+            messages: vec![Message::user("Hello, world!".to_string())],
+            ..Default::default()
+        };
+
+        let response = match client.chat_completion(request).await {
+            Ok(response) => response,
+            Err(e) => panic!("Error processing thread: {:?}", e),
+        };
+
+        assert!(response.choices.len() > 0);
+    }
 }

api/src/utils/tools/mod.rs

@@ -4,19 +4,19 @@ use serde_json::Value;
 
 use crate::utils::clients::ai::litellm::ToolCall;
 
-mod search_files;
-mod create_files;
-mod bulk_modify_files;
-mod search_data_catalog;
-mod open_files;
-mod send_to_user;
+// mod bulk_modify_files;
+// mod create_files;
+// mod open_files;
+// mod search_data_catalog;
+// mod search_files;
+// mod send_to_user;
 
-pub use search_files::SearchFilesTool;
-pub use create_files::CreateFilesTool;
-pub use bulk_modify_files::BulkModifyFilesTool;
-pub use search_data_catalog::SearchDataCatalogTool;
-pub use open_files::OpenFilesTool;
-pub use send_to_user::SendToUserTool;
+// pub use bulk_modify_files::BulkModifyFilesTool;
+// pub use create_files::CreateFilesTool;
+// pub use open_files::OpenFilesTool;
+// pub use search_data_catalog::SearchDataCatalogTool;
+// pub use search_files::SearchFilesTool;
+// pub use send_to_user::SendToUserTool;
 
 /// A trait that defines how tools should be implemented.
 /// Any struct that wants to be used as a tool must implement this trait.
@@ -27,4 +27,17 @@ pub trait ToolExecutor: Send + Sync {
 
     /// Return the JSON schema that describes this tool's interface
     fn get_schema(&self) -> serde_json::Value;
+
+    /// Return the name of the tool
+    fn get_name(&self) -> String;
+}
+
+trait IntoBoxedTool {
+    fn boxed(self) -> Box<dyn ToolExecutor>;
+}
+
+impl<T: ToolExecutor + 'static> IntoBoxedTool for T {
+    fn boxed(self) -> Box<dyn ToolExecutor> {
+        Box::new(self)
+    }
 }