Added swiftdoc documentation

Sources/llama-cpp-swift/LLama.swift

@@ -2,15 +2,19 @@ import Foundation
 import Logging
 @preconcurrency import llama
 
+/// An actor that handles inference using the LLama language model.
 public actor LLama {
   private let logger = Logger.llama
   private let model: Model
   private let sampling: UnsafeMutablePointer<llama_sampler>
   private var tokensList: [llama_token]
   private var temporaryInvalidCChars: [CChar]
 
-  // MARK: - Init & teardown
+  // MARK: - Init & Teardown
 
+  /// Initializes a new instance of `LLama` with the specified model.
+  ///
+  /// - Parameter model: The language model to use for inference.
   public init(model: Model) {
     self.model = model
 
@@ -26,52 +30,81 @@ public actor LLama {
     self.temporaryInvalidCChars = []
   }
 
-  deinit {
-    // llama_sampler_free(sampling)
-  }
-
   // MARK: - Inference
 
+  /// Generates an asynchronous stream of tokens as strings based on the given prompt.
+  ///
+  /// - Parameters:
+  ///   - prompt: The input text prompt to generate completions for.
+  ///   - maxTokens: The maximum number of tokens to generate. Defaults to 128.
+  ///
+  /// - Returns: An `AsyncThrowingStream` emitting generated tokens as strings.
   public func infer(prompt: String, maxTokens: Int32 = 128) -> AsyncThrowingStream<String, Error> {
     return AsyncThrowingStream { continuation in
       Task {
-        var isDone = false
-        let nLen: Int32 = 1024
-        var nCur: Int32 = 0
-        var nDecode: Int32 = 0
-        var batch = llama_batch_init(512, 0, 1)
-        defer {
-          llama_batch_free(batch)
-        }
-
         do {
-          try self.completionInit(text: prompt, batch: &batch, nLen: nLen, nCur: &nCur)
+          try await self.infer(prompt: prompt, maxTokens: maxTokens, continuation: continuation)
         } catch {
           continuation.finish(throwing: error)
-          return
         }
+      }
+    }
+  }
 
-        while !isDone && nCur < nLen && nCur - batch.n_tokens < maxTokens {
-          guard !Task.isCancelled else {
-            continuation.finish()
-            return
-          }
-          let newTokenStr = self.completionLoop(
-            batch: &batch,
-            isDone: &isDone,
-            nLen: nLen,
-            nCur: &nCur,
-            nDecode: &nDecode
-          )
-          continuation.yield(newTokenStr)
-        }
+  /// Performs the inference loop and yields generated tokens to the continuation.
+  ///
+  /// - Parameters:
+  ///   - prompt: The input text prompt to generate completions for.
+  ///   - maxTokens: The maximum number of tokens to generate.
+  ///   - continuation: The stream continuation to yield tokens to.
+  private func infer(
+    prompt: String,
+    maxTokens: Int32,
+    continuation: AsyncThrowingStream<String, Error>.Continuation
+  ) async throws {
+    var isDone = false
+    let nLen: Int32 = 1024
+    var nCur: Int32 = 0
+    var nDecode: Int32 = 0
+    var batch = llama_batch_init(512, 0, 1)
+    defer {
+      llama_batch_free(batch)
+    }
+
+    do {
+      try self.completionInit(text: prompt, batch: &batch, nLen: nLen, nCur: &nCur)
+    } catch {
+      throw error
+    }
+
+    while !isDone && nCur < nLen && nCur - batch.n_tokens < maxTokens {
+      guard !Task.isCancelled else {
         continuation.finish()
+        return
       }
+      let newTokenStr = self.completionLoop(
+        batch: &batch,
+        isDone: &isDone,
+        nLen: nLen,
+        nCur: &nCur,
+        nDecode: &nDecode
+      )
+      continuation.yield(newTokenStr)
     }
+    continuation.finish()
   }
 
-  // MARK: - Private helpers
-
+  // MARK: - Private Helpers
+
+  /// Initializes the completion process by tokenizing the input text and preparing the batch.
+  ///
+  /// - Parameters:
+  ///   - text: The input text to tokenize.
+  ///   - batch: The batch to initialize.
+  ///   - nLen: The maximum length of the sequence.
+  ///   - nCur: The current position in the sequence.
+  ///
+  /// - Throws: An `InferError` if the KV cache is too small or decoding fails.
   private func completionInit(
     text: String,
     batch: inout llama_batch,
@@ -109,6 +142,16 @@ public actor LLama {
     nCur = batch.n_tokens
   }
 
+  /// Performs a single iteration of the completion loop, generating the next token.
+  ///
+  /// - Parameters:
+  ///   - batch: The batch to use for decoding.
+  ///   - isDone: A flag indicating whether the generation is complete.
+  ///   - nLen: The maximum length of the sequence.
+  ///   - nCur: The current position in the sequence.
+  ///   - nDecode: The number of tokens decoded so far.
+  ///
+  /// - Returns: The newly generated token as a string.
   private func completionLoop(
     batch: inout llama_batch,
     isDone: inout Bool,
@@ -154,6 +197,14 @@ public actor LLama {
     return newTokenStr
   }
 
+  /// Adds a token to the batch.
+  ///
+  /// - Parameters:
+  ///   - batch: The batch to add the token to.
+  ///   - id: The token ID to add.
+  ///   - pos: The position of the token in the sequence.
+  ///   - seq_ids: The sequence IDs associated with the token.
+  ///   - logits: A flag indicating whether to compute logits for this token.
   private func llamaBatchAdd(
     _ batch: inout llama_batch,
     _ id: llama_token,
@@ -172,6 +223,13 @@ public actor LLama {
     batch.n_tokens += 1
   }
 
+  /// Tokenizes the given text using the model's tokenizer.
+  ///
+  /// - Parameters:
+  ///   - text: The text to tokenize.
+  ///   - add_bos: A flag indicating whether to add a beginning-of-sequence token.
+  ///
+  /// - Returns: An array of token IDs.
   private func tokenize(text: String, add_bos: Bool) -> [llama_token] {
     let utf8Data = text.utf8CString
     let nTokens = Int32(utf8Data.count) + (add_bos ? 1 : 0)
@@ -187,6 +245,11 @@ public actor LLama {
     return Array(UnsafeBufferPointer(start: tokens, count: Int(tokenCount)))
   }
 
+  /// Converts a token ID to an array of CChars representing the token piece.
+  ///
+  /// - Parameter token: The token ID to convert.
+  ///
+  /// - Returns: An array of CChars representing the token piece.
   private func tokenToPieceArray(token: llama_token) -> [CChar] {
     var buffer = [CChar](repeating: 0, count: 8)
     var nTokens = llama_token_to_piece(model.model, token, &buffer, 8, 0, false)
@@ -200,6 +263,11 @@ public actor LLama {
     return Array(buffer.prefix(Int(nTokens)))
   }
 
+  /// Attempts to create a partial string from an array of CChars if the full string is invalid.
+  ///
+  /// - Parameter cchars: The array of CChars to attempt to convert.
+  ///
+  /// - Returns: A valid string if possible; otherwise, `nil`.
   private func attemptPartialString(from cchars: [CChar]) -> String? {
     for i in (1..<cchars.count).reversed() {
       let subArray = Array(cchars.prefix(i))
@@ -212,12 +280,16 @@ public actor LLama {
 }
 
 extension llama_batch {
+  /// Clears the batch by resetting the token count.
   fileprivate mutating func clear() {
     n_tokens = 0
   }
 }
 
 extension String {
+  /// Initializes a string from a sequence of CChars, validating UTF8 encoding.
+  ///
+  /// - Parameter validatingUTF8: The array of CChars to initialize the string from.
   fileprivate init?(validatingUTF8 cchars: [CChar]) {
     if #available(macOS 15.0, *) {
       self.init(validating: cchars.map { UInt8(bitPattern: $0) }, as: UTF8.self)