langchain/libs/experimental/langchain_experimental/smart_llm/__init__.py

"""Chain for applying self-critique using the SmartGPT workflow.

See details at https://youtu.be/wVzuvf9D9BU

The workflow performs these 3 steps:
1. **Ideate**: Pass the user prompt to an ideation LLM n_ideas times,
   each result is an "idea"
2. **Critique**: Pass the ideas to a critique LLM which looks for flaws in the ideas
   & picks the best one
3. **Resolve**: Pass the critique to a resolver LLM which improves upon the best idea
   & outputs only the (improved version of) the best output

In total, the SmartGPT workflow will use n_ideas+2 LLM calls

Note that SmartLLMChain will only improve results (compared to a basic LLMChain),
when the underlying models have the capability for reflection, which smaller models
often don't.

Finally, a SmartLLMChain assumes that each underlying LLM outputs exactly 1 result.
"""

from langchain_experimental.smart_llm.base import SmartLLMChain

__all__ = ["SmartLLMChain"]
experimental: docstrings update (#18048) Added missed docstrings. Formatted docsctrings to the consistent format. 7 months ago			`"""Chain for applying self-critique using the SmartGPT workflow.`

			`See details at https://youtu.be/wVzuvf9D9BU`

			`The workflow performs these 3 steps:`
			`1. Ideate: Pass the user prompt to an ideation LLM n_ideas times,`
			`each result is an "idea"`
			`2. Critique: Pass the ideas to a critique LLM which looks for flaws in the ideas`
			`& picks the best one`
			`3. Resolve: Pass the critique to a resolver LLM which improves upon the best idea`
			`& outputs only the (improved version of) the best output`

			`In total, the SmartGPT workflow will use n_ideas+2 LLM calls`

			`Note that SmartLLMChain will only improve results (compared to a basic LLMChain),`
			`when the underlying models have the capability for reflection, which smaller models`
			`often don't.`

			`Finally, a SmartLLMChain assumes that each underlying LLM outputs exactly 1 result.`
			`"""`
Added SmartGPT workflow (issue #4463) (#4816) # Added SmartGPT workflow by providing SmartLLM wrapper around LLMs Edit: As @hwchase17 suggested, this should be a chain, not an LLM. I have adapted the PR. It is used like this: ``` from langchain.prompts import PromptTemplate from langchain.chains import SmartLLMChain from langchain.chat_models import ChatOpenAI hard_question = "I have a 12 liter jug and a 6 liter jug. I want to measure 6 liters. How do I do it?" hard_question_prompt = PromptTemplate.from_template(hard_question) llm = ChatOpenAI(model_name="gpt-4") prompt = PromptTemplate.from_template(hard_question) chain = SmartLLMChain(llm=llm, prompt=prompt, verbose=True) chain.run({}) ``` Original text: Added SmartLLM wrapper around LLMs to allow for SmartGPT workflow (as in https://youtu.be/wVzuvf9D9BU). SmartLLM can be used wherever LLM can be used. E.g: ``` smart_llm = SmartLLM(llm=OpenAI()) smart_llm("What would be a good company name for a company that makes colorful socks?") ``` or ``` smart_llm = SmartLLM(llm=OpenAI()) prompt = PromptTemplate( input_variables=["product"], template="What is a good name for a company that makes {product}?", ) chain = LLMChain(llm=smart_llm, prompt=prompt) chain.run("colorful socks") ``` SmartGPT consists of 3 steps: 1. Ideate - generate n possible solutions ("ideas") to user prompt 2. Critique - find flaws in every idea & select best one 3. Resolve - improve upon best idea & return it Fixes #4463 ## Who can review? Community members can review the PR once tests pass. Tag maintainers/contributors who might be interested: - @hwchase17 - @agola11 Twitter: [@UmerHAdil](https://twitter.com/@UmerHAdil) \| Discord: RicChilligerDude#7589 --------- Co-authored-by: Bagatur <baskaryan@gmail.com> 1 year ago
			`from langchain_experimental.smart_llm.base import SmartLLMChain`

			`__all__ = ["SmartLLMChain"]`