# anuragsinghbhandari/topsecret-agent architecture

> Architecture diagram of the GitHub repository anuragsinghbhandari/topsecret-agent, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-08-02). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/anuragsinghbhandari/topsecret-agent
- Repository: https://github.com/anuragsinghbhandari/topsecret-agent

## Overview

#### Purpose and Entry Point
This is a small Python agent/LLM integration repository. The executable entry point is likely `main.py`; shared agent abstractions appear to be defined in `baseclass.py`. The only concrete model integration is Gemini.

Paths: `main.py`, `baseclass.py`

#### Agent Abstraction Boundary
`baseclass.py` is the architectural contract layer between application orchestration and model providers. It should define the common interface or base behavior that lets the main program use an LLM without depending directly on Gemini-specific implementation details.

Path: `baseclass.py`

#### Application Orchestration
`main.py` is expected to compose the agent/base abstraction with a selected model adapter, receive or construct prompts/tasks, invoke the model flow, and handle resulting output. This is the primary control-flow boundary for future features such as CLI input, task routing, or additional agents.

Paths: `main.py`, `baseclass.py`

#### Model Provider Adapter
Gemini-specific request construction, SDK/API invocation, and response normalization belong in the adapter layer. Isolating this logic allows provider credentials, API formats, and model-specific behavior to remain outside the core agent contract.

Paths: `model_adapters/llm_gemini.py`, `model_adapters`

#### Primary Flow
The intended dependency direction is:

1. `main.py` starts the application and chooses/configures an LLM implementation.
2. Core agent behavior uses the abstraction in `baseclass.py`.
3. The Gemini adapter in `model_adapters/llm_gemini.py` performs external model interaction.
4. Normalized model output returns to the orchestration layer for presentation or subsequent agent work.

The core boundary is between provider-neutral agent logic and provider-specific Gemini integration.

#### Runtime and Dependency Management
The project uses Python, with the target/runtime version indicated by `.python-version`. Dependencies are declared through `pyproject.toml` and locked in `uv.lock`, indicating the `uv` package/workflow ecosystem. Gemini is the material external service dependency, although the repository does not provide README documentation describing required credentials or deployment setup.

Paths: `.python-version`, `pyproject.toml`, `uv.lock`, `model_adapters/llm_gemini.py`

Main entry points: [`model_adapters/llm_gemini.py`](https://github.com/anuragsinghbhandari/topsecret-agent/blob/main/model_adapters/llm_gemini.py) (Gemini Adapter), [`main.py`](https://github.com/anuragsinghbhandari/topsecret-agent/blob/main/main.py) (Application Entry), [`pyproject.toml`](https://github.com/anuragsinghbhandari/topsecret-agent/blob/main/pyproject.toml) (Project Dependencies), [`baseclass.py`](https://github.com/anuragsinghbhandari/topsecret-agent/blob/main/baseclass.py) (Agent Abstraction)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_core["Core Application"]
  node_main["Application Entry<br/>Python module<br/>[main.py]"]
  node_agent_contract{{"Agent Abstraction<br/>base contract<br/>[baseclass.py]"}}
end

subgraph group_provider["Model Provider"]
  node_gemini_adapter["Gemini Adapter<br/>LLM adapter<br/>[llm_gemini.py]"]
  node_gemini_service(("Gemini API<br/>external LLM service"))
end

subgraph group_runtime["Python Runtime"]
  node_python_version["Python Version<br/>runtime marker<br/>[.python-version]"]
  node_project_deps["Project Dependencies<br/>package manifest<br/>[pyproject.toml]"]
  node_uv_lock["Locked Dependencies<br/>uv lockfile<br/>[uv.lock]"]
end

node_main -->|"uses"| node_agent_contract
node_main -->|"selects implementation"| node_gemini_adapter
node_gemini_adapter -->|"implements"| node_agent_contract
node_gemini_adapter -->|"SDK/API request"| node_gemini_service
node_gemini_service -->|"model response"| node_gemini_adapter
node_gemini_adapter -->|"normalized output"| node_main
node_python_version -.->|"runs"| node_main
node_project_deps -.->|"declares SDK dependency"| node_gemini_adapter
node_uv_lock -.->|"locks resolved dependencies"| node_project_deps

click node_main "https://github.com/anuragsinghbhandari/topsecret-agent/blob/main/main.py"
click node_agent_contract "https://github.com/anuragsinghbhandari/topsecret-agent/blob/main/baseclass.py"
click node_gemini_adapter "https://github.com/anuragsinghbhandari/topsecret-agent/blob/main/model_adapters/llm_gemini.py"
click node_python_version "https://github.com/anuragsinghbhandari/topsecret-agent/blob/main/.python-version"
click node_project_deps "https://github.com/anuragsinghbhandari/topsecret-agent/blob/main/pyproject.toml"
click node_uv_lock "https://github.com/anuragsinghbhandari/topsecret-agent/blob/main/uv.lock"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_main,node_agent_contract toneBlue
class node_gemini_adapter,node_gemini_service toneAmber
class node_python_version,node_project_deps,node_uv_lock toneMint
```

## Components

### Core Application

Provider-neutral orchestration and agent contract.

- [Application Entry](https://github.com/anuragsinghbhandari/topsecret-agent/blob/main/main.py): Python module · Starts the flow, selects an LLM, and handles output. · `main.py`
- [Agent Abstraction](https://github.com/anuragsinghbhandari/topsecret-agent/blob/main/baseclass.py): base contract · Provider-neutral interface used by orchestration. · `baseclass.py`

### Model Provider

Gemini-specific integration boundary.

- [Gemini Adapter](https://github.com/anuragsinghbhandari/topsecret-agent/blob/main/model_adapters/llm_gemini.py): LLM adapter · Builds requests and normalizes Gemini responses. · `model_adapters/llm_gemini.py`
- **Gemini API**: external LLM service · External model inference provider.

### Python Runtime

Python version and locked dependency workflow.

- [Python Version](https://github.com/anuragsinghbhandari/topsecret-agent/blob/main/.python-version): runtime marker · `.python-version`
- [Project Dependencies](https://github.com/anuragsinghbhandari/topsecret-agent/blob/main/pyproject.toml): package manifest · `pyproject.toml`
- [Locked Dependencies](https://github.com/anuragsinghbhandari/topsecret-agent/blob/main/uv.lock): uv lockfile · `uv.lock`

## Connections

- Application Entry → Agent Abstraction: uses
- Application Entry → Gemini Adapter: selects implementation
- Gemini Adapter → Agent Abstraction: implements
- Gemini Adapter → Gemini API: SDK/API request
- Gemini API → Gemini Adapter: model response
- Gemini Adapter → Application Entry: normalized output
- Python Version → Application Entry: runs
- Project Dependencies → Gemini Adapter: declares SDK dependency
- Locked Dependencies → Project Dependencies: locks resolved dependencies