Remove streaming LLM tracking; they are all streaming now

haystack/agents/base.py

@@ -13,7 +13,7 @@
 from haystack.telemetry import send_event
 from haystack.agents.agent_step import AgentStep
 from haystack.agents.types import Color, AgentTokenStreamingHandler
-from haystack.agents.utils import print_text, STREAMING_CAPABLE_MODELS
+from haystack.agents.utils import print_text
 from haystack.nodes import PromptNode, BaseRetriever, PromptTemplate
 from haystack.pipelines import (
     BaseStandardPipeline,
@@ -228,6 +228,7 @@ def __init__(
         prompt_parameters_resolver: Optional[Callable] = None,
         max_steps: int = 8,
         final_answer_pattern: str = r"Final Answer\s*:\s*(.*)",
+        streaming: bool = True,
     ):
         """
          Creates an Agent instance.
@@ -248,6 +249,9 @@ def __init__(
             Set it to at least 2, so that the Agent can run one a tool once and then infer it knows the final answer.
             The default is 8.
         :param final_answer_pattern: A regular expression to extract the final answer from the text the Agent generated.
+        :param streaming: Whether to use streaming or not. If True, the Agent will stream response tokens from the LLM.
+        If False, the Agent will wait for the LLM to finish generating the response and then process it. The default is
+        True.
         """
         self.max_steps = max_steps
         self.tm = tools_manager or ToolsManager()
@@ -273,12 +277,7 @@ def __init__(
             prompt_parameters_resolver if prompt_parameters_resolver else react_parameter_resolver
         )
         self.final_answer_pattern = final_answer_pattern
-        # Resolve model name to check if it's a streaming model
-        if isinstance(self.prompt_node.model_name_or_path, str):
-            model_name = self.prompt_node.model_name_or_path
-        else:
-            model_name = self.prompt_node.model_name_or_path.model_name_or_path
-        self.add_default_logging_callbacks(streaming=any(m for m in STREAMING_CAPABLE_MODELS if m in model_name))
+        self.add_default_logging_callbacks(streaming=streaming)
         self.hash = None
         self.last_hash = None
         self.update_hash()
@@ -318,7 +317,7 @@ def on_agent_start(**kwargs: Any) -> None:
             self.callback_manager.on_new_token += lambda token, **kwargs: print_text(token, color=agent_color)
         else:
             self.callback_manager.on_agent_step += lambda agent_step: print_text(
-                agent_step.prompt_node_response, color=agent_color
+                agent_step.prompt_node_response + "\n", color=agent_color
             )
 
     def add_tool(self, tool: Tool):

haystack/agents/utils.py

@@ -2,8 +2,6 @@
 
 from haystack.agents.types import Color
 
-STREAMING_CAPABLE_MODELS = ["text-davinci-003", "gpt-3.5-turbo", "gpt-35-turbo", "gpt-4"]
-
 
 def print_text(text: str, end="", color: Optional[Color] = None) -> None:
     """