Add unit testing

Cargo.toml

@@ -11,4 +11,5 @@ tokio = { version = "1.40.0", features = ["rt", "rt-multi-thread", "macros"] }
 dotenv = "0.15.0"
 serde_json = "1.0.128"
 serde = { version = "1.0.210", features = ["derive"] }
-comfy-table = "7.1.1"
+comfy-table = "7.1.1"
+httpmock = "0.7.0"

src/api/chat_completions.rs

@@ -1,6 +1,6 @@
-use crate::json_models::chat_completion::ChatCompletionResponse;
 use super::Instance;
 use crate::clue::ClueCollection;
+use crate::json_models::chat_completion::ChatCompletionResponse;
 use serde_json::json;
 
 const SYSTEM_PROMPT: &str = r#"
@@ -36,21 +36,18 @@ impl Instance {
             .json(&request_body)
             .send()
             .await
-            .map_err(|_| "Failed to fetch clue collection from API server")?;
+            .map_err(|e| format!("Failed to fetch clue collection from API server: {}", e))?;
 
         let parsed_response = response
             .json::<ChatCompletionResponse>()
             .await
-            .map_err(|_| "Failed to parse clues from API server")?;
+            .map_err(|e| format!("Failed to parse clues from API server: {}", e))?;
 
         // Extract usage information from the parsed response
         let token_usage = parsed_response.usage;
 
         // Extract clue strings from the parsed response
-        let clue_strings = parsed_response
-            .choices
-            .first()
-            .ok_or("Failed to parse clues from API server")?
+        let clue_strings = parsed_response.choices[0]
             .message
             .content
             .lines()

src/api/language_models.rs

@@ -1,20 +1,20 @@
-use crate::json_models::language_model::ModelsResponse;
 use super::Instance;
+use crate::json_models::language_model::ModelsResponse;
 
 impl Instance {
-    pub async fn fetch_all_model_ids(&self) -> Result<Vec<String>, Box<dyn std::error::Error>> {
+    pub async fn fetch_language_model_ids(&self) -> Result<Vec<String>, Box<dyn std::error::Error>> {
         let response = self
             .client
             .get(format!("{}models", self.base_url))
             .bearer_auth(&self.key)
             .send()
             .await
-            .map_err(|_| "Failed to fetch model IDs from API server")?;
+            .map_err(|e| format!("Failed to fetch model IDs from API server: {}", e))?;
 
         let mut all_model_ids = response
             .json::<ModelsResponse>()
             .await
-            .map_err(|_| "Failed to parse model IDs from API server")?
+            .map_err(|e| format!("Failed to parse model IDs from API server: {}", e))?
             .data
             .iter()
             .map(|model| model.id.trim().to_string())

src/api/mod.rs

@@ -42,7 +42,7 @@ impl Instance {
         model_id: String,
     ) -> Result<(), Box<dyn std::error::Error>> {
         // Return Error if the chosen model is not valid
-        let valid_model_ids = self.fetch_all_model_ids().await?;
+        let valid_model_ids = self.fetch_language_model_ids().await?;
         if !valid_model_ids.contains(&model_id) {
             return Err(format!(
                 "{} is not a valid language model from your provider",
@@ -54,4 +54,8 @@ impl Instance {
         self.model_id = model_id;
         Ok(())
     }
+
+    pub fn set_base_url(&mut self, base_url: String) {
+        self.base_url = base_url;
+    }
 }

src/clue.rs

@@ -99,7 +99,7 @@ impl ClueCollection {
     pub fn display_table(&self) {
         println!("{}", self.generate_table());
     }
-    
+
     pub fn display_token_info(&self) {
         eprintln!(
             "\nToken Usage:\n\
@@ -108,9 +108,21 @@ impl ClueCollection {
             Completion Tokens: {}\n\
             ----------------------\n\
             Total Tokens: {}",
-            self.usage.prompt_tokens,
-            self.usage.completion_tokens,
-            self.usage.total_tokens
+            self.usage.prompt_tokens, self.usage.completion_tokens, self.usage.total_tokens
         );
     }
+
+    pub fn generate_raw_list(&self) -> String {
+        let mut raw_list = String::new();
+        for clue in &self.clues {
+            let clue_string = format!(
+                "{} {} - {}\n",
+                clue.clue_word,
+                clue.count,
+                clue.linked_words.join(", ")
+            );
+            raw_list.push_str(clue_string.as_str());
+        }
+        raw_list
+    }
 }

src/lib.rs

@@ -5,6 +5,8 @@ use std::path::PathBuf;
 pub mod api;
 mod clue;
 mod json_models;
+#[cfg(test)]
+mod tests;
 
 /// Mastermind - An LLM-powered CLI tool to help you be a better spymaster in Codenames
 #[derive(Parser)]

src/main.rs

@@ -13,7 +13,7 @@ async fn main() -> Result<(), Box<dyn std::error::Error>> {
 
     // If -g is set, call the models API endpoint instead
     if args.get {
-        println!("{}", api_instance.fetch_all_model_ids().await?.join("\n"));
+        println!("{}", api_instance.fetch_language_model_ids().await?.join("\n"));
         return Ok(());
     }
 

src/tests/expected_outputs/chat_completions.txt

@@ -0,0 +1,5 @@
+music 2 - sound, bee
+film 2 - bond, tokyo
+free 2 - park, penny
+dive 2 - scuba diver, hospital
+large 2 - walrus, scuba diver

src/tests/expected_outputs/language_models.txt

@@ -0,0 +1,13 @@
+distil-whisper-large-v3-en
+gemma-7b-it
+gemma2-9b-it
+llama-3.1-70b-versatile
+llama-3.1-8b-instant
+llama-guard-3-8b
+llama3-70b-8192
+llama3-8b-8192
+llama3-groq-70b-8192-tool-use-preview
+llama3-groq-8b-8192-tool-use-preview
+llava-v1.5-7b-4096-preview
+mixtral-8x7b-32768
+whisper-large-v3

src/tests/mock_responses/chat_completions.json

@@ -0,0 +1,30 @@
+{
+  "id": "chatcmpl-869ede85-2f46-4834-a039-28d757e958a5",
+  "object": "chat.completion",
+  "created": 1726870549,
+  "model": "llama-3.1-70b-versatile",
+  "choices": [
+    {
+      "index": 0,
+      "message": {
+        "role": "assistant",
+        "content": "music, 2, sound, bee\nfilm, 2, bond, tokyo\nfree, 2, park, penny\ndive, 2, scuba diver, hospital\nlarge, 2, walrus, scuba diver"
+      },
+      "logprobs": null,
+      "finish_reason": "stop"
+    }
+  ],
+  "usage": {
+    "queue_time": 0.005669406999999987,
+    "prompt_tokens": 222,
+    "prompt_time": 0.068204384,
+    "completion_tokens": 53,
+    "completion_time": 0.214023764,
+    "total_tokens": 275,
+    "total_time": 0.282228148
+  },
+  "system_fingerprint": "fp_b6828be2c9",
+  "x_groq": {
+    "id": "req_01j88r2wfmecr9zgpjn2zmnprb"
+  }
+}

src/tests/mock_responses/language_models.json

@@ -0,0 +1,122 @@
+{
+  "object": "list",
+  "data": [
+    {
+      "id": "llava-v1.5-7b-4096-preview",
+      "object": "model",
+      "created": 1725402373,
+      "owned_by": "Other",
+      "active": true,
+      "context_window": 4096,
+      "public_apps": null
+    },
+    {
+      "id": "gemma-7b-it",
+      "object": "model",
+      "created": 1693721698,
+      "owned_by": "Google",
+      "active": true,
+      "context_window": 8192,
+      "public_apps": null
+    },
+    {
+      "id": "llama-3.1-8b-instant",
+      "object": "model",
+      "created": 1693721698,
+      "owned_by": "Meta",
+      "active": true,
+      "context_window": 131072,
+      "public_apps": null
+    },
+    {
+      "id": "whisper-large-v3",
+      "object": "model",
+      "created": 1693721698,
+      "owned_by": "OpenAI",
+      "active": true,
+      "context_window": 448,
+      "public_apps": null
+    },
+    {
+      "id": "mixtral-8x7b-32768",
+      "object": "model",
+      "created": 1693721698,
+      "owned_by": "Mistral AI",
+      "active": true,
+      "context_window": 32768,
+      "public_apps": null
+    },
+    {
+      "id": "llama3-8b-8192",
+      "object": "model",
+      "created": 1693721698,
+      "owned_by": "Meta",
+      "active": true,
+      "context_window": 8192,
+      "public_apps": null
+    },
+    {
+      "id": "distil-whisper-large-v3-en",
+      "object": "model",
+      "created": 1693721698,
+      "owned_by": "Hugging Face",
+      "active": true,
+      "context_window": 448,
+      "public_apps": null
+    },
+    {
+      "id": "llama-guard-3-8b",
+      "object": "model",
+      "created": 1693721698,
+      "owned_by": "Meta",
+      "active": true,
+      "context_window": 8192,
+      "public_apps": null
+    },
+    {
+      "id": "gemma2-9b-it",
+      "object": "model",
+      "created": 1693721698,
+      "owned_by": "Google",
+      "active": true,
+      "context_window": 8192,
+      "public_apps": null
+    },
+    {
+      "id": "llama3-70b-8192",
+      "object": "model",
+      "created": 1693721698,
+      "owned_by": "Meta",
+      "active": true,
+      "context_window": 8192,
+      "public_apps": null
+    },
+    {
+      "id": "llama3-groq-70b-8192-tool-use-preview",
+      "object": "model",
+      "created": 1693721698,
+      "owned_by": "Groq",
+      "active": true,
+      "context_window": 8192,
+      "public_apps": null
+    },
+    {
+      "id": "llama-3.1-70b-versatile",
+      "object": "model",
+      "created": 1693721698,
+      "owned_by": "Meta",
+      "active": true,
+      "context_window": 131072,
+      "public_apps": null
+    },
+    {
+      "id": "llama3-groq-8b-8192-tool-use-preview",
+      "object": "model",
+      "created": 1693721698,
+      "owned_by": "Groq",
+      "active": true,
+      "context_window": 8192,
+      "public_apps": null
+    }
+  ]
+}

src/tests/mod.rs

@@ -0,0 +1,75 @@
+use super::*;
+use crate::api::Instance;
+use httpmock::prelude::*;
+
+#[test]
+fn test_api_instance() {
+    let api_instance = api::Instance::new();
+    assert!(api_instance.is_ok());
+}
+
+#[test]
+fn test_read_words_from_file() {
+    let to_link = read_words_from_file(PathBuf::from("examples/link.txt"));
+    assert!(to_link.is_ok());
+    let to_avoid = read_words_from_file(PathBuf::from("examples/avoid.txt"));
+    assert!(to_avoid.is_ok());
+}
+
+#[tokio::test]
+async fn test_fetch_language_models() {
+    // Start a lightweight mock server.
+    let server = MockServer::start_async().await;
+
+    // Create a mock on the server.
+    let mock = server.mock(|when, then| {
+        when.method(GET).path("/models");
+        then.status(200)
+            .header("content-type", "application/json")
+            .body_from_file("src/tests/mock_responses/language_models.json");
+    });
+
+    // Create an API instance and set the base url to mock server url
+    let mut api_instance = Instance::new().unwrap();
+    api_instance.set_base_url(server.url("/"));
+
+    // Get response from mock server
+    let response = api_instance.fetch_language_model_ids().await.unwrap();
+    mock.assert();
+
+    // Compare outputs
+    let output = response.join("\n");
+    let expected_output = fs::read_to_string("src/tests/expected_outputs/language_models.txt").unwrap();
+    assert_eq!(output, expected_output);
+}
+
+#[tokio::test]
+async fn test_fetch_clue_collection() {
+    // Start a lightweight mock server.
+    let server = MockServer::start_async().await;
+
+    // Create a mock on the server.
+    let mock = server.mock(|when, then| {
+        when.method(POST).path("/chat/completions");
+        then.status(200)
+            .header("content-type", "application/json")
+            .body_from_file("src/tests/mock_responses/chat_completions.json");
+    });
+
+    // Create an API instance and set the base url to mock server url
+    let mut api_instance = Instance::new().unwrap();
+    api_instance.set_base_url(server.url("/"));
+
+    // Get response from mock server
+    let response = api_instance
+        .fetch_clue_collection(vec![], vec![])
+        .await
+        .unwrap();
+    mock.assert();
+
+    // Compare outputs
+    let output = response.generate_raw_list();
+    let expected_output =
+        fs::read_to_string("src/tests/expected_outputs/chat_completions.txt").unwrap();
+    assert_eq!(output, expected_output);
+}