Request new feature for Robotic Application

[Prof-pengyin]

Feature request

Hi Guys,

Here I made a new fork to https://github.com/MetaSLAM/CyberChain, where I would like to combine the powerful Langchain ability and GPT4 into the real-world robotic challenges.

My question raised here is mainly about:

1. How can I setup the Chat GPT 4 version into Langchain, where I would like to levevarge the powerful visual inference of GPT4;
2. I there any suggestion for the memory system, because the robot may travel through a large-scale environment for lifelong navigation, I would like to construct a memory system within langchain to enhance its behaviour in the long-term operation.

Many thanks for your hard work, and Langchain is difinitely an impressive work.

Max

Motivation

Combine real-world robotic application with the LangChain framework.

Your contribution

I will provide my research outcomes under our MetaSLAM organization (https://github.com/MetaSLAM), hope this can benefit both robotics and AI communitry, targeting for the general AI system.

[dosubot[bot]]

🤖

Hello @Prof-pengyin,

I'm Dosu, a bot here to assist with your inquiries and concerns about LangChain while we wait for a human maintainer. I'm here to help you troubleshoot issues, answer questions, and guide you on how to contribute to this project.

I've received your issue and am currently investigating it. I'll provide a detailed response shortly. Thank you for your patience!

[dosubot[bot]]

🤖

To integrate GPT-4 into LangChain for your robotic application, you can utilize the OpenAIAssistantRunnable class provided by the LangChain framework. This class allows you to instantiate an assistant with a specific language model, in this case, GPT-4. Here's a sample code snippet:

from langchain_experimental.openai_assistant import OpenAIAssistantRunnable

# Instantiate an assistant with GPT-4
robotic_assistant = OpenAIAssistantRunnable.create_assistant(
    name="robotic assistant",
    instructions="You are a robotic assistant. Write and run code to perform robotic tasks.",
    tools=[{"type": "code_interpreter"}],
    model="gpt-4-1106-preview"  # replace with the actual GPT-4 model name when available
)

Regarding your second question about constructing a memory system within LangChain, the current version of LangChain does not provide a built-in solution for this. However, you could consider using a database or a state management system to store and manage the robot's state over time. This would allow the robot to remember past actions and make decisions based on its history. You would need to design this system to fit your specific use case and integrate it with LangChain and your robotic application.

Please note that the integration of GPT-4 and the construction of a memory system would require a good understanding of both LangChain and your robotic application. You might need to make modifications to the LangChain codebase to fit your specific needs.

I hope this helps! If you have any further questions, feel free to ask.

Sources

• libs/langchain/langchain/agents/openai_assistant/base.py
• libs/langchain/langchain/llms/init.py

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[Prof-pengyin]

The automatic feedback doesn't solve the problem.

[dosubot[bot]]

It seems like this issue requires a deeper look, @baskaryan could you please lend your expertise?

[ComeBackTo2016]

You can implement a tool and directly call the GPT4V interface within the tool. This should be a relatively simple approach. On the other hand, you can also integrate any models you need within the LLM framework.