Streaming only final output of agent (#2483) (#4630)

# Streaming only final output of agent (#2483)
As requested in issue #2483, this Callback allows to stream only the
final output of an agent (ie not the intermediate steps).

Fixes #2483

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
searx_updates
UmerHA 1 year ago committed by GitHub
parent 3bc0bf0079
commit 7388248b3e
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@ -0,0 +1,154 @@
{
"cells": [
{
"cell_type": "markdown",
"id": "23234b50-e6c6-4c87-9f97-259c15f36894",
"metadata": {
"tags": []
},
"source": [
"# Only streaming final agent output"
]
},
{
"cell_type": "markdown",
"id": "29dd6333-307c-43df-b848-65001c01733b",
"metadata": {},
"source": [
"If you only want the final output of an agent to be streamed, you can use the callback ``FinalStreamingStdOutCallbackHandler``.\n",
"For this, the underlying LLM has to support streaming as well."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "e4592215-6604-47e2-89ff-5db3af6d1e40",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"from langchain.agents import load_tools\n",
"from langchain.agents import initialize_agent\n",
"from langchain.agents import AgentType\n",
"from langchain.callbacks.streaming_stdout_final_only import FinalStreamingStdOutCallbackHandler\n",
"from langchain.llms import OpenAI"
]
},
{
"cell_type": "markdown",
"id": "19a813f7",
"metadata": {},
"source": [
"Let's create the underlying LLM with ``streaming = True`` and pass a new instance of ``FinalStreamingStdOutCallbackHandler``."
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "7fe81ef4",
"metadata": {},
"outputs": [],
"source": [
"llm = OpenAI(streaming=True, callbacks=[FinalStreamingStdOutCallbackHandler()], temperature=0)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "ff45b85d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Konrad Adenauer became Chancellor of Germany in 1949, 74 years ago in 2023."
]
},
{
"data": {
"text/plain": [
"'Konrad Adenauer became Chancellor of Germany in 1949, 74 years ago in 2023.'"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"tools = load_tools([\"wikipedia\", \"llm-math\"], llm=llm)\n",
"agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=False)\n",
"agent.run(\"It's 2023 now. How many years ago did Konrad Adenauer become Chancellor of Germany.\")"
]
},
{
"cell_type": "markdown",
"id": "53a743b8",
"metadata": {},
"source": [
"### Handling custom answer prefixes"
]
},
{
"cell_type": "markdown",
"id": "23602c62",
"metadata": {},
"source": [
"By default, we assume that the token sequence ``\"\\nFinal\", \" Answer\", \":\"`` indicates that the agent has reached an answers. We can, however, also pass a custom sequence to use as answer prefix."
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "5662a638",
"metadata": {},
"outputs": [],
"source": [
"llm = OpenAI(\n",
" streaming=True,\n",
" callbacks=[FinalStreamingStdOutCallbackHandler(answer_prefix_tokens=[\"\\nThe\", \" answer\", \":\"])],\n",
" temperature=0\n",
")"
]
},
{
"cell_type": "markdown",
"id": "b1a96cc0",
"metadata": {},
"source": [
"Be aware you likely need to include whitespaces and new line characters in your token. "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9278b522",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.3"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

@ -0,0 +1,49 @@
"""Callback Handler streams to stdout on new llm token."""
import sys
from typing import Any, Dict, List, Optional
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
DEFAULT_ANSWER_PREFIX_TOKENS = ["\nFinal", " Answer", ":"]
class FinalStreamingStdOutCallbackHandler(StreamingStdOutCallbackHandler):
"""Callback handler for streaming in agents.
Only works with agents using LLMs that support streaming.
Only the final output of the agent will be streamed.
"""
def __init__(self, answer_prefix_tokens: Optional[List[str]] = None) -> None:
super().__init__()
if answer_prefix_tokens is None:
answer_prefix_tokens = DEFAULT_ANSWER_PREFIX_TOKENS
self.answer_prefix_tokens = answer_prefix_tokens
self.last_tokens = [""] * len(answer_prefix_tokens)
self.answer_reached = False
def on_llm_start(
self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any
) -> None:
"""Run when LLM starts running."""
self.answer_reached = False
def on_llm_new_token(self, token: str, **kwargs: Any) -> None:
"""Run on new LLM token. Only available when streaming is enabled."""
# Remember the last n tokens, where n = len(answer_prefix_tokens)
self.last_tokens.append(token)
if len(self.last_tokens) > len(self.answer_prefix_tokens):
self.last_tokens.pop(0)
# Check if the last n tokens match the answer_prefix_tokens list ...
if self.last_tokens == self.answer_prefix_tokens:
self.answer_reached = True
# Do not print the last token in answer_prefix_tokens,
# as it's not part of the answer yet
return
# ... if yes, then print tokens from now on
if self.answer_reached:
sys.stdout.write(token)
sys.stdout.flush()
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