fixes

llms/README.md

@@ -61,7 +61,7 @@ prompt = tokenizer.apply_chat_template(
     messages, tokenize=False, add_generation_prompt=True
 )
 
-response = generate(model, tokenizer, prompt=prompt, verbose=True)
+text = generate(model, tokenizer, prompt=prompt, verbose=True)
 ```
 
 To see a description of all the arguments you can do:
@@ -117,8 +117,8 @@ prompt = tokenizer.apply_chat_template(
     messages, tokenize=False, add_generation_prompt=True
 )
 
-for text, *_ in stream_generate(model, tokenizer, prompt, max_tokens=512):
-    print(t, end="", flush=True)
+for response in stream_generate(model, tokenizer, prompt, max_tokens=512):
+    print(response.text, end="", flush=True)
 print()
 ```
 

llms/mlx_lm/chat.py

@@ -74,7 +74,7 @@ def main():
         prompt = tokenizer.apply_chat_template(
             messages, tokenize=False, add_generation_prompt=True
         )
-        for response, *_ in stream_generate(
+        for response in stream_generate(
             model,
             tokenizer,
             prompt,
@@ -83,7 +83,7 @@ def main():
             top_p=args.top_p,
             prompt_cache=prompt_cache,
         ):
-            print(response, flush=True, end="")
+            print(response.text, flush=True, end="")
         print()
 
 

llms/mlx_lm/server.py

@@ -475,7 +475,8 @@ class APIHandler(BaseHTTPRequestHandler):
             logit_bias=self.logit_bias,
             prompt_cache=self.prompt_cache.cache,
         ):
-            text += gen_response.text
+            segment = gen_response.text
+            text += segment
             logging.debug(text)
             token = gen_response.token
             logprobs = gen_response.logprobs

llms/mlx_lm/utils.py

@@ -378,29 +378,28 @@ def generate(
        model (nn.Module): The language model.
        tokenizer (PreTrainedTokenizer): The tokenizer.
        prompt (str): The string prompt.
+       max_tokens (int): The maximum number of tokens. Default: ``100``.
        verbose (bool): If ``True``, print tokens and timing information.
            Default: ``False``.
        kwargs: The remaining options get passed to :func:`stream_generate`.
           See :func:`stream_generate` for more details.
     """
     if formatter is not None:
-        print(
-            "Text formatting has been deprecated and will be removed in the next version."
-        )
+        print("Text formatting is deprecated and will be removed in the next version.")
     if verbose:
         print("=" * 10)
         print("Prompt:", prompt)
 
-    full_text = ""
+    text = ""
     for response in stream_generate(model, tokenizer, prompt, **kwargs):
         if verbose:
             print(response.text, end="", flush=True)
-        full_text += response.text
+        text += response.text
 
     if verbose:
         print()
         print("=" * 10)
-        if len(full_text) == 0:
+        if len(text) == 0:
             print("No text generated for this prompt")
             return
         print(
@@ -412,7 +411,7 @@ def generate(
             f"{response.generation_tps:.3f} tokens-per-sec"
         )
         print(f"Peak memory: {response.peak_memory:.3f} GB")
-    return full_text
+    return text
 
 
 def load_config(model_path: Path) -> dict: