README.md

metadata

title: Final Assignment Template
emoji: 📚
colorFrom: red
colorTo: green
sdk: gradio
sdk_version: 5.47.0
app_file: app.py
hf_oauth: true
pinned: false
license: mit
short_description: Final Assignment for agents course

Graph

The graph is built with LangGraph framework. There is a control of iterations between the agent and the tools node, with a field in the state. The route_tools function checks if the iterations number, updated in the increase node, is greater than the stablished in MAX_ITERATIONS constant.

Models

I have tried two different models so far.

• gemini-2.5-flash. This is free to use, taking advantage of the generous limits provided by Google AI for developers.
• gpt-oss-120b. I have used it through HuggingFace inference providers. Since I have a pro account, 2$/month is more than enough to develop the Final Assignment project. This model, gpt-oss-120b, does not work through Together inference provider. It seems that Together is not performing well with LangGraph. It worked just fine through Fireworks inference provider.

Tools

• python_tool
• reverse_tool
• excel_file_to_markdown
• sum_numbers
• web_search
• get_wikipedia_info
• ask_audio_model
• chess_tool (this one cannot run on HuggingFace Space)

Results

The answers of the two models were cached after generation, and then submitted. I modified the gradio app to do so, as suggested in the template comments

• gemini-2.5-flash. 40%
• gpt-oss-120b. 60%
• combined (taking correct results from both models): 65%. Only one additional answer provided by gemini.