Chain to run queries against LLMs.
This class is deprecated. See below for an example implementation using LangChain runnables:
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import PromptTemplate
from langchain_openai import OpenAI
prompt_template = "Tell me a {adjective} joke"
prompt = PromptTemplate(input_variables=["adjective"], template=prompt_template)
model = OpenAI()
chain = prompt | model | StrOutputParser()
chain.invoke("your adjective here")Abstract base class for chat memory.
ATTENTION This abstraction was created prior to when chat models had native tool calling capabilities. It does NOT support native tool calling capabilities for chat models and will fail SILENTLY if used with a chat model that has native tool calling.
DO NOT USE THIS ABSTRACTION FOR NEW CODE.
Mixin for summarizer.
Continually summarizes the conversation history.
The summary is updated after each conversation turn. The implementations returns a summary of the conversation history which can be used to provide context to the model.