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langchain/docs/modules/agents/streaming_stdout_final_only...

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"# Only streaming final agent output"
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"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."
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"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"
]
},
{
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"source": [
"Let's create the underlying LLM with ``streaming = True`` and pass a new instance of ``FinalStreamingStdOutCallbackHandler``."
]
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"execution_count": 2,
"id": "7fe81ef4",
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"source": [
"llm = OpenAI(streaming=True, callbacks=[FinalStreamingStdOutCallbackHandler()], temperature=0)"
]
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"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."
]
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"'Konrad Adenauer became Chancellor of Germany in 1949, 74 years ago in 2023.'"
]
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"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.\")"
]
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"source": [
"### Handling custom answer prefixes"
]
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"source": [
"By default, we assume that the token sequence ``\"Final\", \"Answer\", \":\"`` indicates that the agent has reached an answers. We can, however, also pass a custom sequence to use as answer prefix."
]
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"source": [
"llm = OpenAI(\n",
" streaming=True,\n",
" callbacks=[FinalStreamingStdOutCallbackHandler(answer_prefix_tokens=[\"The\", \"answer\", \":\"])],\n",
" temperature=0\n",
")"
]
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"For convenience, the callback automatically strips whitespaces and new line characters when comparing to `answer_prefix_tokens`. I.e., if `answer_prefix_tokens = [\"The\", \" answer\", \":\"]` then both `[\"\\nThe\", \" answer\", \":\"]` and `[\"The\", \" answer\", \":\"]` would be recognized a the answer prefix."
]
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"source": [
"If you don't know the tokenized version of your answer prefix, you can determine it with the following code:"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2f8f0640",
"metadata": {},
"outputs": [],
"source": [
"from langchain.callbacks.base import BaseCallbackHandler\n",
"\n",
"class MyCallbackHandler(BaseCallbackHandler):\n",
" def on_llm_new_token(self, token, **kwargs) -> None:\n",
" # print every token on a new line\n",
" print(f\"#{token}#\")\n",
"\n",
"llm = OpenAI(streaming=True, callbacks=[MyCallbackHandler()])\n",
"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.\")"
]
},
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"source": [
"### Also streaming the answer prefixes"
]
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"source": [
"When the parameter `stream_prefix = True` is set, the answer prefix itself will also be streamed. This can be useful when the answer prefix itself is part of the answer. For example, when your answer is a JSON like\n",
"\n",
"`\n",
"{\n",
" \"action\": \"Final answer\",\n",
" \"action_input\": \"Konrad Adenauer became Chancellor 74 years ago.\"\n",
"}\n",
"`\n",
"\n",
"and you don't only want the action_input to be streamed, but the entire JSON."
]
}
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