diff --git a/deltachat_chatbot/gpt4all.py b/deltachat_chatbot/gpt4all.py
index 6ca2608..0a0027e 100644
--- a/deltachat_chatbot/gpt4all.py
+++ b/deltachat_chatbot/gpt4all.py
@@ -9,7 +9,6 @@
 from gpt4all._pyllmodel import (
     LLModel,
     PromptCallback,
-    RecalculateCallback,
     ResponseCallback,
     ResponseCallbackType,
     empty_response_callback,
@@ -76,7 +75,7 @@ def prompt_model(
         ctypes.c_char_p(prompt_template.encode()),
         PromptCallback(self._prompt_callback),
         ResponseCallback(self._callback_decoder(callback)),
-        RecalculateCallback(self._recalculate_callback),
+        True,
         self.context,
         special,
         ctypes.c_char_p(fake_reply.encode()) if fake_reply else ctypes.c_char_p(),
@@ -104,14 +103,15 @@ def generate(  # noqa
         repeat_last_n: int = 64,
         n_batch: int = 8,
         n_predict: int | None = None,
+        streaming: bool = False,
+        fake_reply: str = "",
         callback: ResponseCallbackType = empty_response_callback,
-        fake_reply="",
     ) -> Any:
         """
         Generate outputs from any GPT4All model.
 
         Args:
-            prompt: The prompt for the model the complete.
+            prompt: The prompt for the model to complete.
             max_tokens: The maximum number of tokens to generate.
             temp: The model temperature. Larger values increase creativity but decrease factuality.
             top_k: Randomly sample from the top_k most likely tokens at each generation step. Set this to 1 for greedy decoding.
@@ -121,6 +121,8 @@ def generate(  # noqa
             repeat_last_n: How far in the models generation history to apply the repeat penalty.
             n_batch: Number of prompt tokens processed in parallel. Larger values decrease latency but increase resource requirements.
             n_predict: Equivalent to max_tokens, exists for backwards compatibility.
+            streaming: If True, this method will instead return a generator that yields tokens as the model generates them.
+            fake_reply: A spoofed reply for the given prompt, used as a way to load chat history.
             callback: A function with arguments token_id:int and response:str, which receives the tokens from the model as they are generated and stops the generation by returning False.
 
         Returns:
@@ -199,6 +201,15 @@ def _callback(token_id: int, response: str) -> bool:
 
             return _callback
 
+        # Send the request to the model
+        if streaming:
+            return self.model.prompt_model_streaming(
+                prompt,
+                prompt_template,
+                _callback_wrapper(callback, output_collector),
+                **generate_kwargs,
+            )
+
         self.model.prompt_model(  # noqa
             prompt,
             prompt_template,