[Agent Example Proposal]: Gemini-Powered Research & Summarization Agent

[Kavurubuvanesh]

Problem statement

Problem Statement

The innovation lab currently has great foundational examples, but it would highly benefit from a dedicated example demonstrating how to integrate modern LLMs (specifically Google's Gemini API) within the uagents framework to perform autonomous data processing.

Proposed Solution

I propose adding a new example in the repository called gemini-research-agent.
This example will feature:

1. A primary agent that receives a research topic via a message.
2. Integration with the google-genai SDK to process the topic and generate a structured summary.
3. The agent returning the AI-generated summary back to the sender.

Tech Stack

Python, uagents framework, Gemini API

Additional Context

I am a GSSoC '26 contributor in the AI/Agents track. I have extensive experience building with Python and Generative AI, and I am ready to build and PR this example immediately if assigned!

Proposed solution

I will create a multi-agent system using the uagents framework.
The architecture will consist of:

1. User/Sender Agent: Sends a string containing a research topic or query to the Research Agent.
2. Research Agent (Gemini-Powered): Receives the message, constructs a structured prompt, and queries the google-genai API (using gemini-1.5-flash for speed and efficiency).
3. Response Cycle: The Research Agent parses the LLM output and sends the summarized research back to the User Agent, demonstrating asynchronous inter-agent communication combined with external API calls.

Scope and impact

Scope: The PR will add a new self-contained folder (e.g., gemini-research-agent) inside the repository, containing the Python scripts for the agents, a requirements.txt (adding google-genai), and a clear README.md with setup instructions.
Impact: As autonomous agents increasingly rely on LLMs for reasoning, developers need clear blueprints on how to wire them together. This example will serve as a foundational template for anyone looking to connect Fetch.ai agents to Google's Gemini ecosystem, lowering the barrier to entry for new developers in the innovation lab.

Alternatives considered (optional)

• Using Local LLMs: Considered using a local model via Ollama, but it introduces heavy hardware requirements for a simple example. Using the Gemini API is lightweight and accessible, especially since Google offers a generous free tier for developers testing these kinds of integrations.
• Using OpenAI: Opted for Gemini to diversify the repository's examples, as many developers are actively looking for google-genai SDK integrations.

Additional context (optional)

I am an active GSSoC '26 contributor specializing in the AI/Agents track. I already have the Gemini API configured locally and am deeply familiar with Python asynchronous programming. If assigned, I can have a working, fully documented Pull Request submitted within 48 hours.

[Akanksha-020]

Hi I would like to work on this issue contributing under GSSoC 2026!

[Kavurubuvanesh]

Hey @Akanksha-020, thanks for the interest! However, I authored this specific proposal and architecture to build it out myself for GSSoC, and I already have the local implementation ready for review. Best of luck with your other contributions!