Welcome to the world of Reflexion where language agents learn and adapt through verbal reinforcement! In this blog post, we’ll guide you through the setup process, how to run reasoning and decision-making tasks, and provide troubleshooting tips along the way. Let’s dive in!
Getting Started with Reflexion
Reflexion is based on the paper titled Reflexion: Language Agents with Verbal Reinforcement Learning. Before we jump into running experiments, ensure that you have Git and Python installed on your machine.
Step 1: Clone the Repository
Begin by cloning the repository and moving into the required directory for your tasks:
bash
git clone https://github.com/noahshinn/reflexion
cd .hotpotqa_runs
Step 2: Install Dependencies
Next, you’ll need to install the necessary module dependencies. Execute the following command:
bash
pip install -r requirements.txt
Step 3: Set the API Key
Before running the agents, ensure that you set your OpenAI API key by executing this command:
bash
export OPENAI_API_KEY=your_key
Understanding Agent Types and Reflexion Strategies
The agents’ performance can vary based on the types selected and the reflexion strategies employed.
Agent Types
- ReAct – ReAct Agent
- CoT_context – CoT Agent with supporting context
- CoT_no_context – CoT Agent without supporting context
The notebooks for each agent type are stored in the .hotpot_runs/notebooks directory.
Reflexion Strategies
Each agent uses specific reflexion strategies, akin to different learning techniques:
- ReflexionStrategy.NONE – No feedback on the previous attempt.
- ReflexionStrategy.LAST_ATTEMPT – Receives reasoning from the last attempt.
- ReflexionStrategy.REFLEXION – Self-reflection on the last attempt.
- ReflexionStrategy.LAST_ATTEMPT_AND_REFLEXION – Both reasoning and self-reflection provided.
It’s like having a coach (reflexion) who helps each agent understand its strengths and areas for improvement through past experiences!
Running Decision-Making Tasks
Follow similar steps to run decision-making tasks for AlfWorld:
bash
git clone https://github.com/noahshinn/reflexion
cd .alfworld_runs
Configure Run Parameters
Specify run parameters in .run_reflexion.sh such as the number of trials and memory settings.
bash
run_reflexion.sh
The logs will be directed to the .root/run_name directory.
Troubleshooting Tips
If you encounter issues while running the code or setting up your environment, try the following:
- Ensure that you’ve installed all the dependencies without errors.
- Double-check your OpenAI API key to make sure it’s set correctly.
- If you experience logging problems, check the specified log directory for any missing permissions.
- Make sure you are using the correct directory for your chosen tasks.
For complex setups and further insights, feel free to reach out or collaborate on AI development projects!
For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.
Other Resources
Explore more with the original code available here, and an interesting implementation of type prediction at OpenTau.
Conclusion
At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.
