Project Info

MultiAgent Diplomacy

Devpost

Inspiration

While we have worked a lot with AI in machine learning models and computer vision, our team had yet to work with agentic LLMs, especially using LangChain. After stumbling through ideas, we decided we wanted to simulate the mediation of political leaders going through different crisis'.

What it does

Our program generates AI leaders with unique personalities, backgrounds, and qualities. It then generates conflicts or natural disasters that occur between countries, leading to disputes that need to be addressed and resolved through the mediation of the user. They each have their own voices (provided by Google Cloud), so they can argue with each other or reach agreements.

How we built it

We used Python, LangChain, and Google Cloud to bring our backend together. We used Javascript, Flask and HTML for our frontend.

Challenges we ran into

We had a lot of trouble trying to create a web application implementing FastAPI with LangChain. We ended up switching to a more cohesive program with Flask.

Accomplishments we're proud of

We are proud we were able to design a simple UI. We were also proud to include many features, including AI generated speech and agentic LLMs, both of which were completely new to us.

What we learned

We learned how to make concise system prompts, make multiple models taking input from each other, and how to use Google Cloud TTS.

Analysis

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Metric

No commits on this project resolved to a GitHub account.

Technology

Found in codeClaimed only
  • FlaskIn code
  • HTMLIn code
  • JavaScriptIn code
  • PythonIn code
  • LangChainClaimed

4 of 5 appear in the indexed code. 1 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

117 KB

Source files

10

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.

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