Merge pull request #58 from SilasMarvin/silas-custom-log-file

Add custom log file option and improve logging

.gitignore

@@ -5,3 +5,4 @@ out
 dist
 lsp-ai.log
 .vsix
+lsp-ai-chat.md

crates/lsp-ai/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "lsp-ai"
-version = "0.4.1"
+version = "0.5.0"
 
 description.workspace = true
 repository.workspace = true
@@ -42,6 +42,7 @@ md5 = "0.7.0"
 fxhash = "0.2.1"
 ordered-float = "4.2.1"
 futures = "0.3"
+clap = { version = "4.5.14", features = ["derive"] }
 
 [build-dependencies]
 cc="1"

crates/lsp-ai/src/main.rs

@@ -1,17 +1,21 @@
 use anyhow::Result;
-
+use clap::Parser;
+use directories::BaseDirs;
 use lsp_server::{Connection, ExtractError, Message, Notification, Request, RequestId};
 use lsp_types::{
     request::{CodeActionRequest, CodeActionResolveRequest, Completion},
     CodeActionOptions, CompletionOptions, DidChangeTextDocumentParams, DidOpenTextDocumentParams,
     RenameFilesParams, ServerCapabilities, TextDocumentSyncKind,
 };
+use std::sync::Mutex;
 use std::{
     collections::HashMap,
+    fs,
+    path::Path,
     sync::{mpsc, Arc},
     thread,
 };
-use tracing::error;
+use tracing::{error, info};
 use tracing_subscriber::{EnvFilter, FmtSubscriber};
 
 mod config;
@@ -54,19 +58,58 @@ where
     req.extract(R::METHOD)
 }
 
+// LSP-AI parameters
+#[derive(Parser)]
+#[command(version)]
+struct Args {
+    // Whether to use a custom log file
+    #[arg(long, default_value_t = false)]
+    use_seperate_log_file: bool,
+}
+
+fn create_log_file(base_path: &Path) -> anyhow::Result<fs::File> {
+    let dir_path = base_path.join("lsp-ai");
+    fs::create_dir_all(&dir_path)?;
+    let file_path = dir_path.join("lsp-ai.log");
+    Ok(fs::File::create(file_path)?)
+}
+
 // Builds a tracing subscriber from the `LSP_AI_LOG` environment variable
 // If the variables value is malformed or missing, sets the default log level to ERROR
-fn init_logger() {
-    FmtSubscriber::builder()
-        .with_writer(std::io::stderr)
-        .with_ansi(false)
-        .without_time()
-        .with_env_filter(EnvFilter::from_env("LSP_AI_LOG"))
-        .init();
+fn init_logger(args: &Args) {
+    let builder = FmtSubscriber::builder().with_env_filter(EnvFilter::from_env("LSP_AI_LOG"));
+    let base_dirs = BaseDirs::new();
+
+    if args.use_seperate_log_file && base_dirs.is_some() {
+        let base_dirs = base_dirs.unwrap();
+        let cache_dir = base_dirs.cache_dir();
+        // Linux:   /home/alice/.cache
+        // Windows: C:\Users\Alice\AppData\Local
+        // macOS:   /Users/Alice/Library/Caches
+        match create_log_file(&cache_dir) {
+            Ok(log_file) => builder.with_writer(Mutex::new(log_file)).init(),
+            Err(e) => {
+                eprintln!("creating log file: {e:?} - falling back to stderr");
+                builder
+                    .with_writer(std::io::stderr)
+                    .without_time()
+                    .with_ansi(false)
+                    .init()
+            }
+        }
+    } else {
+        builder
+            .with_writer(std::io::stderr)
+            .without_time()
+            .with_ansi(false)
+            .init()
+    }
 }
 
 fn main() -> Result<()> {
-    init_logger();
+    let args = Args::parse();
+    init_logger(&args);
+    info!("lsp-ai logger initialized starting server");
 
     let (connection, io_threads) = Connection::stdio();
     let server_capabilities = serde_json::to_value(ServerCapabilities {
@@ -181,7 +224,7 @@ fn main_loop(connection: Connection, args: serde_json::Value) -> Result<()> {
                         Err(err) => error!("{err:?}"),
                     }
                 } else {
-                    error!("lsp-ai currently only supports textDocument/completion, textDocument/generation and textDocument/generationStream")
+                    error!("Unsupported command - see the wiki for a list of supported commands")
                 }
             }
             Message::Notification(not) => {

crates/lsp-ai/src/memory_backends/file_store.rs

@@ -101,9 +101,7 @@ impl FileStore {
             match parse_tree(uri, &contents, None) {
                 Ok(tree) => Some(tree),
                 Err(e) => {
-                    error!(
-                        "Failed to parse tree for {uri} with error {e}, falling back to no tree"
-                    );
+                    warn!("Failed to parse tree for {uri} with error {e}, falling back to no tree");
                     None
                 }
             }

crates/lsp-ai/src/splitters/tree_sitter.rs

@@ -1,5 +1,5 @@
 use splitter_tree_sitter::TreeSitterCodeSplitter;
-use tracing::error;
+use tracing::warn;
 use tree_sitter::Tree;
 
 use crate::{config, memory_backends::file_store::File, utils::parse_tree};
@@ -43,7 +43,7 @@ impl Splitter for TreeSitter {
             match self.split_tree(tree, file.rope().to_string().as_bytes()) {
                 Ok(chunks) => chunks,
                 Err(e) => {
-                    error!(
+                    warn!(
                         "Failed to parse tree for file with error: {e:?}. Falling back to default splitter.",
                     );
                     self.text_splitter.split(file)
@@ -59,14 +59,14 @@ impl Splitter for TreeSitter {
             Ok(tree) => match self.split_tree(&tree, contents.as_bytes()) {
                 Ok(chunks) => chunks,
                 Err(e) => {
-                    error!(
+                    warn!(
                             "Failed to parse tree for file: {uri} with error: {e:?}. Falling back to default splitter.",
                         );
                     self.text_splitter.split_file_contents(uri, contents)
                 }
             },
             Err(e) => {
-                error!(
+                warn!(
                     "Failed to parse tree for file {uri} with error: {e:?}. Falling back to default splitter.",
                 );
                 self.text_splitter.split_file_contents(uri, contents)

crates/lsp-ai/src/transformer_backends/anthropic.rs

@@ -3,7 +3,7 @@ use std::collections::HashMap;
 use anyhow::Context;
 use serde::Deserialize;
 use serde_json::{json, Value};
-use tracing::instrument;
+use tracing::{info, instrument};
 
 use crate::{
     config::{self, ChatMessage},
@@ -80,6 +80,18 @@ impl Anthropic {
                 "Please set `auth_token_env_var_name` or `auth_token` to use an Anthropic"
             );
         };
+        let params = json!({
+            "model": self.config.model,
+            "system": system_prompt,
+            "max_tokens": params.max_tokens,
+            "top_p": params.top_p,
+            "temperature": params.temperature,
+            "messages": messages
+        });
+        info!(
+            "Calling Anthropic compatible API with parameters:\n{}",
+            serde_json::to_string_pretty(&params).unwrap()
+        );
         let res: AnthropicChatResponse = client
             .post(
                 self.config
@@ -91,14 +103,7 @@ impl Anthropic {
             .header("anthropic-version", "2023-06-01")
             .header("Content-Type", "application/json")
             .header("Accept", "application/json")
-            .json(&json!({
-                "model": self.config.model,
-                "system": system_prompt,
-                "max_tokens": params.max_tokens,
-                "top_p": params.top_p,
-                "temperature": params.temperature,
-                "messages": messages
-            }))
+            .json(&params)
             .send()
             .await?
             .json()

crates/lsp-ai/src/transformer_backends/gemini.rs

@@ -1,7 +1,7 @@
 use anyhow::Context;
 use serde::{Deserialize, Serialize};
 use serde_json::{json, Value};
-use tracing::instrument;
+use tracing::{info, instrument};
 
 use super::TransformerBackend;
 use crate::{
@@ -110,6 +110,15 @@ impl Gemini {
     ) -> anyhow::Result<String> {
         let client = reqwest::Client::new();
         let token = self.get_token()?;
+        let params = json!({
+             "contents": messages,
+             "systemInstruction": params.system_instruction,
+             "generationConfig": params.generation_config,
+        });
+        info!(
+            "Calling Gemini compatible chat API with parameters:\n{}",
+            serde_json::to_string_pretty(&params).unwrap()
+        );
         let res: serde_json::Value = client
             .post(
                 self.configuration
@@ -122,11 +131,7 @@ impl Gemini {
                     + token.as_ref(),
             )
             .header("Content-Type", "application/json")
-            .json(&json!({
-                 "contents": messages,
-                 "systemInstruction": params.system_instruction,
-                 "generationConfig": params.generation_config,
-            }))
+            .json(&params)
             .send()
             .await?
             .json()

crates/lsp-ai/src/transformer_backends/llama_cpp/model.rs

@@ -9,7 +9,7 @@ use llama_cpp_2::{
 };
 use once_cell::sync::Lazy;
 use std::{num::NonZeroU32, path::PathBuf, time::Duration};
-use tracing::{debug, info, instrument};
+use tracing::{info, instrument};
 
 use crate::config::{self, ChatMessage};
 
@@ -29,7 +29,10 @@ impl Model {
         let model_params = LlamaModelParams::default().with_n_gpu_layers(config.n_gpu_layers);
 
         // Load the model
-        debug!("Loading model at path: {:?}", model_path);
+        info!(
+            "Loading llama.cpp compatible model at path: {:?}",
+            model_path
+        );
         let model = LlamaModel::load_from_file(&BACKEND, model_path, &model_params)?;
 
         Ok(Model {
@@ -40,6 +43,8 @@ impl Model {
 
     #[instrument(skip(self))]
     pub fn complete(&self, prompt: &str, params: LLaMACPPRunParams) -> anyhow::Result<String> {
+        info!("Completing with llama.cpp with prompt:\n{prompt}");
+
         // initialize the context
         let ctx_params = LlamaContextParams::default().with_n_ctx(Some(self.n_ctx));
 

crates/lsp-ai/src/transformer_backends/mistral_fim.rs

@@ -1,7 +1,7 @@
 use anyhow::Context;
 use serde::Deserialize;
 use serde_json::{json, Value};
-use tracing::instrument;
+use tracing::{info, instrument};
 
 use super::{open_ai::OpenAIChatResponse, TransformerBackend};
 use crate::{
@@ -67,6 +67,21 @@ impl MistralFIM {
     ) -> anyhow::Result<String> {
         let client = reqwest::Client::new();
         let token = self.get_token()?;
+        let params = json!({
+            "prompt": prompt.prompt,
+            "suffix": prompt.suffix,
+            "model": self.config.model,
+            "max_tokens": params.max_tokens,
+            "top_p": params.top_p,
+            "temperature": params.temperature,
+            "min_tokens": params.min_tokens,
+            "random_seed": params.random_seed,
+            "stop": params.stop
+        });
+        info!(
+            "Calling Mistral compatible FIM API with parameters:\n{}",
+            serde_json::to_string_pretty(&params).unwrap()
+        );
         let res: OpenAIChatResponse = client
             .post(
                 self.config
@@ -77,17 +92,7 @@ impl MistralFIM {
             .bearer_auth(token)
             .header("Content-Type", "application/json")
             .header("Accept", "application/json")
-            .json(&json!({
-                "prompt": prompt.prompt,
-                "suffix": prompt.suffix,
-                "model": self.config.model,
-                "max_tokens": params.max_tokens,
-                "top_p": params.top_p,
-                "temperature": params.temperature,
-                "min_tokens": params.min_tokens,
-                "random_seed": params.random_seed,
-                "stop": params.stop
-            }))
+            .json(&params)
             .send()
             .await?
             .json()