langchain/templates/solo-performance-prompting-agent

solo-performance-prompting-agent

This template creates an agent that transforms a single LLM into a cognitive synergist by engaging in multi-turn self-collaboration with multiple personas. A cognitive synergist refers to an intelligent agent that collaborates with multiple minds, combining their individual strengths and knowledge, to enhance problem-solving and overall performance in complex tasks. By dynamically identifying and simulating different personas based on task inputs, SPP unleashes the potential of cognitive synergy in LLMs.

This template will use the DuckDuckGo search API.

Environment Setup

This template will use OpenAI by default. Be sure that OPENAI_API_KEY is set in your environment.

Usage

To use this package, you should first have the LangChain CLI installed:

pip install -U langchain-cli

To create a new LangChain project and install this as the only package, you can do:

langchain app new my-app --package solo-performance-prompting-agent

If you want to add this to an existing project, you can just run:

langchain app add solo-performance-prompting-agent

And add the following code to your server.py file:

from solo_performance_prompting_agent.agent import agent_executor as solo_performance_prompting_agent_chain

add_routes(app, solo_performance_prompting_agent_chain, path="/solo-performance-prompting-agent")

(Optional) Let's now configure LangSmith. LangSmith will help us trace, monitor and debug LangChain applications. LangSmith is currently in private beta, you can sign up here. If you don't have access, you can skip this section

export LANGCHAIN_TRACING_V2=true
export LANGCHAIN_API_KEY=<your-api-key>
export LANGCHAIN_PROJECT=<your-project>  # if not specified, defaults to "default"

If you are inside this directory, then you can spin up a LangServe instance directly by:

langchain serve

This will start the FastAPI app with a server is running locally at http://localhost:8000

We can see all templates at http://127.0.0.1:8000/docs We can access the playground at http://127.0.0.1:8000/solo-performance-prompting-agent/playground

We can access the template from code with:

from langserve.client import RemoteRunnable

runnable = RemoteRunnable("http://localhost:8000/solo-performance-prompting-agent")