Enhance LLM integration by adding model specification and refactoring code completion logic; update README with upcoming features

Author: doofin

README.md

@@ -176,6 +176,12 @@ vscode.commands.registerCommand(name, fun).asInstanceOf[Dispose]
 
 You can find more information and tutorials on the [Scala.js website](https://www.scala-js.org/).
 
+# feedback
+features to be implemented:
+- refactoring
+- specify which LLM to use
+
+
 # references:
  - updated from [vscode-scalajs-hello](https://github.com/pme123/vscode-scalajs-hello) with Scala 3.3.3 and sbt.version=1.9.7.
  - [VSCode Extension Samples](https://github.com/microsoft/vscode-extension-samples) repository.

src/main/scala/functorcoder/actions/CodeCompletion.scala

@@ -1 +1,32 @@
 package functorcoder.actions
+
+import functorcoder.llm.llmMain.llmAgent
+import functorcoder.llm.llmPrompt
+import scala.concurrent.Future
+
+object CodeCompletion {
+
+  /** Generates a code completion suggestion by sending a prompt to a language model.
+    *
+    * @param codeBefore
+    *   The code snippet preceding the hole where completion is required.
+    * @param codeAfter
+    *   The code snippet following the hole where completion is required.
+    * @param llm
+    *   The language model agent used to generate the completion.
+    * @return
+    *   A `Future` containing the generated code completion as a `String`.
+    */
+  def getCompletion(
+      codeBefore: String, // code before the hole
+      codeAfter: String, // code after the hole
+      llm: llmAgent
+  ): Future[String] = {
+
+    val prompt = llmPrompt
+      .Completion(codeWithHole = s"$codeBefore${llmPrompt.promptText.hole}$codeAfter")
+
+    // assistantMessage: String = promptText.prompt1
+    llm.sendPrompt(prompt)
+  }
+}

src/main/scala/functorcoder/actions/Commands.scala

@@ -46,7 +46,6 @@ object Commands {
     statusBar.showSpininngStatusBarItem("functorcoder", llmResponse)
 
     llmResponse.foreach { response =>
-      // showMessageAndLog("add doc: " + s"${param.documentUri}, ${param.range}, ${response}")
       // apply the changes to the document
       vscode.window.activeTextEditor.toOption match {
         case None =>
@@ -132,6 +131,5 @@ object Commands {
           }
         )
     }
-
   }
 }

src/main/scala/functorcoder/actions/createFiles.scala

@@ -3,6 +3,7 @@ package functorcoder.actions
 import com.doofin.stdScala.dataTypes.Tree.TreeNode
 import functorcoder.algo.treeParse
 import vscextension.facade.vscodeUtils.showMessageAndLog
+import pprint.PPrinter.BlackWhite
 
 /** create files and folders according to the prompt
   */
@@ -49,13 +50,13 @@ object createFiles {
     */
   def createFilesAndFolders(tree: TreeNode[String], parentPath0: String): Unit = {
     // recursively create files and folders
-    showMessageAndLog(s"Files and folders tree: $tree")
+    val treeStr = BlackWhite.tokenize(tree).map(_.render).mkString("\n")
+    showMessageAndLog(s"Files and folders tree: $treeStr")
     val TreeNode(root, children) = tree
     val parentPath: String = parentPath0 + "/" + root
+    showMessageAndLog(s"Creating file in $parentPath, file: $root")
 
-    children.foreach { child =>
-      val file = child.value
-      showMessageAndLog(s"Creating file in $parentPath, file: $file")
+    children.toSeq.foreach { child =>
       createFilesAndFolders(child, parentPath)
     }
   }

src/main/scala/functorcoder/editorUI/editorConfig.scala

@@ -2,6 +2,11 @@ package functorcoder.editorUI
 
 // https://code.visualstudio.com/api/references/contribution-points#contributes.configuration
 object editorConfig {
-  case class Config(openaiApiKey: String, openaiUrl: String, maxTokens: Int)
+  case class Config(
+      openaiApiKey: String, //
+      openaiUrl: String,
+      maxTokens: Int,
+      model: String = "gpt-4o-mini"
+  )
 
 }

src/main/scala/functorcoder/llm/llmMain.scala

@@ -13,13 +13,11 @@ import scala.concurrent.Future
 
 import functorcoder.editorUI.editorConfig
 
-/** large language model (LLM) AI main
-  *
-  * use node-fetch for network requests
+/** large language model (LLM) main entry
   */
 object llmMain {
 
-  /** generate a completion prompt
+  /** prompt data to string
     *
     * change the model here if needed
     *
@@ -37,7 +35,7 @@ object llmMain {
           openaiReq.Message(roles.user, inputPrompt.generatePrompt),
           openaiReq.Message(roles.system, inputPrompt.getAssistantMessage)
         ),
-        openaiReq.models.gpt4oMini,
+        editorCfg.model,
         max_tokens = Some(editorCfg.maxTokens)
       )
 

src/main/scala/functorcoder/llm/llmPrompt.scala

@@ -51,7 +51,7 @@ object llmPrompt {
   case class Completion(
       codeWithHole: String, // code with a hole to fill like {{FILL_HERE}}
       // taskRequirement: String, // like "Fill the {{FILL_HERE}} hole."
-      assistantMessage: String = promptText.prompt1
+      assistantMessage: String = promptText.promptComp1
   ) extends Prompt(assistantMessage) {
     def generatePrompt = {
 
@@ -87,14 +87,14 @@ object llmPrompt {
   case class CreateFiles(
       userRequest: String,
       assistantMessage: String =
-        s"You are given a user requirement wrapped in ${tagsInUse.queryStart} and ${tagsInUse.queryEnd}, and a TASK requirement ${tagsInUse.task}. " +
-          "You are going to return the code snippet according to the TASK requirement. "
+        s"an input is wrapped in ${tagsInUse.queryStart} and ${tagsInUse.queryEnd}, and the requirement is inside ${tagsInUse.task}. " +
+          "from input and requirement, You return the code snippet"
   ) extends Prompt(assistantMessage) {
     def generatePrompt = {
       import functorcoder.algo.treeParse
 
       val task =
-        s"parse the prompt response to tree of files and folders in the format: ${treeParse.exampleSyntax}. An example input is: ${treeParse.exampleInput}. return the tree data structure in that format."
+        s" return tree of files and folders in the format: ${treeParse.exampleSyntax}. An example input is: ${treeParse.exampleInput}. return the tree data structure in that format."
 
       s"""${tagsInUse.queryStart}
     |${userRequest}
@@ -110,12 +110,12 @@ object llmPrompt {
     */
   object promptText {
     val hole = "{{FILL_HERE}}"
-    val prompt1 =
+    val promptComp1 =
       "You are a code or text autocompletion assistant. " +
         s"In the provided input, missing code or text are marked as $hole. " +
         "Your task is to output only the snippet that replace the placeholder, " +
         "ensuring that indentation and formatting remain consistent with the context. Don't quote your output"
-    val prompt2 =
+    val promptComp2 =
       "You are a hole filler," +
         "You are given a string with a hole: " +
         s"$hole  in the string, " +
@@ -144,27 +144,4 @@ function sum_evens(lim) {
 </QUERY>
 
 TASK: Fill the {{FILL_HERE}} hole.
-
-## CORRECT COMPLETION
-
-<COMPLETION>if (i % 2 === 0) {
-      sum += i;
-    }</COMPLETION>
-
-## EXAMPLE QUERY:
-
-<QUERY>
-def sum_list(lst):
-  total = 0
-  for x in lst:
-  {{FILL_HERE}}
-  return total
-
-print sum_list([1, 2, 3])
-</QUERY>
-
-## CORRECT COMPLETION:
-
-<COMPLETION>  total += x</COMPLETION>
-
  */

src/main/scala/vscextension/inlineCompletions.scala

@@ -5,10 +5,10 @@ import scala.concurrent.ExecutionContext.Implicits.global
 
 import scala.scalajs.js
 import scala.scalajs.js.JSConverters.*
-
 import scala.scalajs.js.Promise
-import functorcoder.llm.llmPrompt
+
 import functorcoder.llm.llmMain.llmAgent
+import functorcoder.actions.CodeCompletion
 import vscextension.facade.vscodeUtils.showMessageAndLog
 
 /** demonstrates how to provide inline completions in the editor. like the github copilot
@@ -29,11 +29,7 @@ object inlineCompletions {
         val codeBefore = document.getText(new vscode.Range(new vscode.Position(0, 0), position))
         val codeAfter = document.getText(new vscode.Range(position, document.positionAt(document.getText().length)))
 
-        val prompt = llmPrompt
-          .Completion(codeWithHole = s"$codeBefore${llmPrompt.promptText.hole}$codeAfter")
-
-        // assistantMessage: String = promptText.prompt1
-        val promptResponseF = llm.sendPrompt(prompt)
+        val promptResponseF = CodeCompletion.getCompletion(codeBefore, codeAfter, llm)
 
         val providerResultF: Promise[scala.scalajs.js.Array[vscode.InlineCompletionItem]] =
           promptResponseF.map { completionText =>
@@ -46,7 +42,8 @@ object inlineCompletions {
             )
           }.toJSPromise
 
-        statusBar.showSpininngStatusBarItem("functorcoder", providerResultF)
+        statusBar.showSpininngStatusBarItem(s"functorcoder(${editorAPI.getLanguage()})", providerResultF)
+
         providerResultF.asInstanceOf[typings.vscode.mod.ProviderResult[
           scala.scalajs.js.Array[typings.vscode.mod.InlineCompletionItem] | typings.vscode.mod.InlineCompletionList
         ]]

src/main/scala/vscextension/settings.scala

@@ -18,7 +18,8 @@ object settings {
       config.getStringOrEmpty(key = "openaiUrl", default = "https://api.openai.com/v1/chat/completions")
 
     val maxTokens = config.get[Int]("maxTokens").getOrElse(1000)
-    Config(openaiApiKey, openaiUrl, maxTokens)
+    val model = config.getStringOrEmpty("model", default = "gpt-4o-mini")
+    Config(openaiApiKey, openaiUrl, maxTokens, model)
   }
 
   extension (config: vscode.WorkspaceConfiguration) {