Stream and capture reasoning content in addition to final answer, from Reasoning LLMs¶
As of v0.35.0, when using Reasoning LLM APIs (e.g. deepseek/deepseek-reasoner
or OpenAI o1
etc):
- You can see both the reasoning (dim green) and final answer (bright green) text in the streamed output.
- When directly calling the LLM (without using an Agent), the
LLMResponse
object will now contain areasoning
field, in addition to the earliermessage
field. - when using a
ChatAgent.llm_response
, extract the reasoning text from theChatDocument
object'sreasoning
field (in addition to extracting final answer as usual from thecontent
field)
Here's a simple example, also in this script:
import langroid as lr
import langroid.language_models as lm
llm_config = lm.OpenAIGPTConfig(chat_model="deepseek/deepseek-reasoner")
# (1) Direct LLM interaction
llm = lm.OpenAIGPT(llm_config)
response = llm.chat("Is 9.9 bigger than 9.11?")
# extract reasoning
print(response.reasoning)
# extract answer
print(response.message)
# (2) Using an agent
agent = lr.ChatAgent(
lr.ChatAgentConfig(
llm=llm_config,
system_message="Solve the math problem given by the user",
)
)
response = agent.llm_response(
"""
10 years ago, Jack's dad was 5 times as old as Jack.
Today, Jack's dad is 40 years older than Jack.
How old is Jack today?
"""
)
# extract reasoning
print(response.reasoning)
# extract answer
print(response.content)