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from langchain_anthropic import ChatAnthropic
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.pydantic_v1 import BaseModel
from langchain_core.runnables import ConfigurableField
from .prompts import answer_prompt
from .retriever_agent import executor
prompt = ChatPromptTemplate.from_template(answer_prompt)
model = ChatAnthropic(
model="claude-3-sonnet-20240229", temperature=0, max_tokens_to_sample=1000
)
chain = (
{"query": lambda x: x["query"], "information": executor | (lambda x: x["output"])}
| prompt
| model
| StrOutputParser()
)
# Add typing for the inputs to be used in the playground
class Inputs(BaseModel):
query: str
chain = chain.with_types(input_type=Inputs)
chain = chain.configurable_alternatives(
ConfigurableField(id="chain"),
default_key="response",
# This adds a new option, with name `openai` that is equal to `ChatOpenAI()`
retrieve=executor,
)
|