Generative AI · Conversational Systems

LLM-Based Financial Assistant Prototype

An individual conversational-AI prototype exploring prompt structure, lightweight model comparison, synthetic financial profiles, and a Gradio interface.

Individual coursework prototype

Documents

Embeddings

Retrieval

Response

Conversational prototype workflow

Notebook workflow for synthetic profiles and response generation.

Scope

Role and problem

My role: Built the notebook prototype, structured prompting flow, lightweight model comparison, and Gradio interface.

Financial-assistant interfaces need explicit scope boundaries. This prototype explores how structured prompts and a simple dialogue interface can organise responses without presenting the result as professional financial advice.

Architecture

System flow

Synthetic financial profiles

Structured prompt template

GPT-2 and DistilGPT-2 comparison

Dialogue wrapper

Gradio interface

Scoped prototype output

Results and scope

Public record

2 models

Lightweight comparison

GPT-2 and DistilGPT-2 pipelines are wired into the notebook.

Gradio

Interactive interface

A user-facing prototype accepts age, income, risk, goal, and model choice.

Synthetic

Data boundary

The notebook uses synthetic profiles and is not financial advice.

Signal	Scope	Interpretation
2 models	Lightweight comparison	GPT-2 and DistilGPT-2 pipelines are wired into the notebook.
Gradio	Interactive interface	A user-facing prototype accepts age, income, risk, goal, and model choice.
Synthetic	Data boundary	The notebook uses synthetic profiles and is not financial advice.

Contribution

Built the prompt-driven dialogue prototype and Gradio interface.
Compared lightweight model pipelines inside one notebook workflow.
Keep the prototype bounded: synthetic profiles and no financial-advice claim.

Lessons

Interface clarity and scope boundaries matter as much as model output.
Synthetic examples are useful for prototyping but do not establish real-world financial suitability.
A stronger future version would need grounded retrieval, domain evaluation, and safety review.

Limitations

The current notebook is a lightweight prototype using synthetic profiles.
The public case study does not claim validated financial recommendations.
Grounded retrieval and multilingual evaluation are future extensions rather than published evidence.

Stack

Python
Transformers
GPT-2
DistilGPT-2
Prompt Design
Gradio