Raise deprecation warning if callback_manager is used.
Set the chain verbosity.
Asynchronously execute the chain.
Validate and prepare chain outputs, and save info about this run to memory.
Validate and prepare chain outputs, and save info about this run to memory.
Prepare chain inputs, including adding inputs from memory.
Prepare chain inputs, including adding inputs from memory.
Convenience method for executing chain.
Convenience method for executing chain.
Return dictionary representation of agent.
Save the agent.
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")Example:
from langchain_classic.chains import LLMChain
from langchain_openai import OpenAI
from langchain_core.prompts import PromptTemplate
prompt_template = "Tell me a {adjective} joke"
prompt = PromptTemplate(input_variables=["adjective"], template=prompt_template)
model = LLMChain(llm=OpenAI(), prompt=prompt)