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OpenLLM/examples/langchain-tools-demo/service.py

19 lines
646 B
Python

from __future__ import annotations
from langchain.agents import AgentType, initialize_agent, load_tools
from langchain.llms import OpenLLM
import bentoml
from bentoml.io import Text
SAMPLE_INPUT = "What is the weather in San Francisco?"
llm = OpenLLM(model_name="dolly-v2", model_id="databricks/dolly-v2-7b", embedded=False,)
tools = load_tools(["serpapi"], llm=llm)
agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION)
svc = bentoml.Service("langchain-openllm", runners=[llm.runner])
@svc.api(input=Text.from_sample(sample=SAMPLE_INPUT), output=Text())
def chat(input_text: str):
return agent.run(input_text)