Initial deploy to Hugging Face Spaces

.env.example

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+ANTHROPIC_API_KEY=your_api_key_here
+
+# Available Models:
+# - claude-3-5-sonnet-20241022 (Latest Sonnet - Recommended)
+# - claude-3-opus-20240229 (Opus - Most Powerful)
+# - claude-3-sonnet-20240229 (Previous Sonnet)
+# - claude-3-haiku-20240307 (Haiku - Fastest/Cheapest)
+ANTHROPIC_MODEL=claude-3-5-sonnet-20241022

.github/workflows/test.yml

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+name: Tests
+
+on:
+  push:
+    branches: [ main ]
+  pull_request:
+    branches: [ main ]
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"]
+
+    steps:
+    - uses: actions/checkout@v3
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v4
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install -e .
+        pip install pytest
+    - name: Run tests
+      run: |
+        pytest

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install different versions of packages depending
+#   on the platform.
+#   In that case, it may be better to ignore Pipfile.lock.
+# Pipfile.lock
+
+# PEP 582; __pypackages__
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyderworkspace
+
+# Rope project settings
+.ropeproject
+
+# PyCharm files
+.idea/
+*.iws
+
+# VSCode files
+.vscode/
+
+# Sublime Text files
+*.sublime-project
+*.sublime-workspace
+
+# Eclipse files
+.project
+.pydevproject
+.settings/
+
+#mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Generated agents
+generated_agents/

Dockerfile

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+# Stage 1: Build Frontend
+FROM node:18-alpine as frontend-build
+WORKDIR /app/frontend
+COPY frontend/package*.json ./
+RUN npm install
+COPY frontend/ ./
+RUN npm run build
+
+# Stage 2: Build Backend & Serve
+FROM python:3.9-slim
+WORKDIR /app
+
+# Install system dependencies if needed (e.g. for some python packages)
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    build-essential \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy requirements and install
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy backend code
+COPY llm_agent_builder/ ./llm_agent_builder/
+COPY server/ ./server/
+# Create empty init for server if not exists (though we have it)
+# COPY server/__init__.py ./server/ 
+
+# Copy frontend build from stage 1
+COPY --from=frontend-build /app/frontend/dist ./frontend/dist
+
+# Expose port 7860 (Hugging Face Spaces default)
+EXPOSE 7860
+
+# Run the application
+# Host 0.0.0.0 is required for Docker
+CMD ["uvicorn", "server.main:app", "--host", "0.0.0.0", "--port", "7860"]

GEMINI.md

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+# LLMAgentBuilder Context
+
+## Project Overview
+**LLMAgentBuilder** is a Python application designed to scaffold and generate other LLM-based agents. It uses Jinja2 templates to create Python code for new agents that interact with the **Anthropic API (Claude)**. The system allows developers to define an agent's name, system prompt, and example tasks via CLI arguments, then automatically generates the corresponding Python class and script.
+
+## Architecture
+The project is structured as a Python package with a clear separation between the builder logic and the generated output.
+
+*   **Core Logic (`llm_agent_builder/`):**
+    *   `agent_builder.py`: Contains the `AgentBuilder` class, which manages the template environment and data context.
+    *   `templates/`: Stores Jinja2 templates (e.g., `agent_template.py.j2`) defining the structure of generated agents (using the `anthropic` client).
+*   **Execution:** `main.py` serves as the CLI entry point, parsing arguments and invoking the builder.
+*   **Output:** Generated agents are saved to the `generated_agents/` directory.
+
+## Key Files
+*   `main.py`: CLI entry point. Parses arguments (`--name`, `--prompt`, etc.) and runs the builder.
+*   `llm_agent_builder/agent_builder.py`: The main logic for rendering agent code.
+*   `llm_agent_builder/templates/agent_template.py.j2`: The blueprint for new agents (Anthropic-based).
+*   `setup.py`: Package installation configuration.
+*   `test_with_mock_key.sh`: Shell script for testing the build process without a real API key.
+
+## Building and Running
+
+### Prerequisites
+*   Python 3.8+
+*   Anthropic API Key
+
+### Installation
+1.  Create a virtual environment:
+    ```bash
+    python -m venv venv
+    source venv/bin/activate  # Windows: venv\Scripts\activate
+    ```
+2.  Install dependencies:
+    ```bash
+    pip install -e .
+    ```
+
+### Usage
+1.  **Configure Environment:**
+    Set your Anthropic API key (required for the *generated* agents to run):
+    ```bash
+    export ANTHROPIC_API_KEY="sk-ant-..."
+    ```
+    Optionally set the model:
+    ```bash
+    export ANTHROPIC_MODEL="claude-3-5-sonnet-20241022"
+    ```
+
+2.  **Generate an Agent:**
+    Run the main script. You can use default settings or customize via CLI:
+    ```bash
+    # Default
+    python main.py
+    
+    # Custom Agent
+    python main.py --name "CodeReviewer" --prompt "You are a strict code reviewer." --task "Review this PR."
+    ```
+
+3.  **Run the Generated Agent:**
+    Navigate to the output directory and run the generated script:
+    ```bash
+    python generated_agents/codereviewer.py
+    ```
+
+## Development Conventions
+*   **Templating:** Uses Jinja2 for code generation. Changes to the agent structure should be made in `llm_agent_builder/templates/`.
+*   **Dependency Management:** Dependencies (`anthropic`, `Jinja2`, `python-dotenv`) are listed in `requirements.txt`.
+*   **Secrets:** API keys are managed via environment variables (`ANTHROPIC_API_KEY`) and are never hardcoded.

MANIFEST.in

@@ -0,0 +1,4 @@
+include README.md
+include requirements.txt
+recursive-include llm_agent_builder/templates *.j2
+

README.md

@@ -0,0 +1,160 @@
+# LLM Agent Builder
+
+This project is a PyCharm application that contains an LLM agent capable of building other LLM agents.
+
+## Getting Started
+
+### Prerequisites
+
+- Python 3.8 or higher
+- pip
+
+### Installation
+
+1. Create and activate a virtual environment (recommended):
+
+    ```bash
+    python3 -m venv venv
+    source venv/bin/activate  # On Windows: venv\Scripts\activate
+    ```
+
+2. Install the package in development mode:
+
+    ```bash
+    pip install -e .
+    ```
+
+    Or install dependencies directly:
+
+    ```bash
+    pip install -r requirements.txt
+    ```
+
+3. Set up your Anthropic API key as an environment variable:
+
+    **For Testing (Mock Key):**
+
+    ```bash
+    export ANTHROPIC_API_KEY="sk-ant-test-mock-key-for-testing-purposes-1234567890abcdef"
+    ```
+
+    **For Production (Real Key):**
+
+    ```bash
+    export ANTHROPIC_API_KEY="your-actual-api-key-here"
+    ```
+
+    > **Note:** The mock key above is for testing code structure only. It will not work for actual API calls. Replace it with your real Anthropic API key for production use.
+
+    You can also configure the model by setting the `ANTHROPIC_MODEL` environment variable in your `.env` file.
+    Available models include:
+    - `claude-3-5-sonnet-20241022` (Default)
+    - `claude-3-opus-20240229`
+    - `claude-3-sonnet-20240229`
+    - `claude-3-haiku-20240307`
+
+4. Run the `main.py` script to generate a new agent:
+
+    **Basic Usage:**
+
+    ```bash
+    python main.py
+    ```
+
+## Web Interface (New!)
+
+You can also use the modern web interface to generate agents.
+
+### Prerequisites
+
+- Node.js installed
+- Python dependencies installed (`pip install -r requirements.txt`)
+
+### Running the Web App
+
+1. **Start the Backend Server:**
+
+    ```bash
+    uvicorn server.main:app --reload
+    ```
+
+    The API will be available at `http://localhost:8000`.
+
+2. **Start the Frontend:**
+    Open a new terminal:
+
+    ```bash
+    cd frontend
+    npm run dev
+    ```
+
+    Open your browser to `http://localhost:5173`.
+
+## Deployment (Hugging Face Spaces)
+
+This project is configured for deployment to Hugging Face Spaces using Docker.
+
+1. Create a new Space on Hugging Face.
+2. Select **Docker** as the SDK.
+3. Push the entire repository to the Space.
+    - The `Dockerfile` will automatically build the React frontend and serve it via the FastAPI backend.
+    - The application is stateless: generated agents will be downloaded to your local machine.
+
+    **Advanced Usage (CLI):**
+    You can customize the agent generation using command-line arguments:
+
+    ```bash
+    llm-agent-builder --name "DataAnalyst" \
+                      --prompt "You are a data analyst expert in Pandas." \
+                      --task "Analyze this CSV file and provide summary statistics." \
+                      --model "claude-3-opus-20240229"
+    ```
+
+    **Interactive Mode:**
+    If you run the command without arguments, it will launch in interactive mode:
+
+    ```bash
+    llm-agent-builder
+    ```
+
+    **Available Arguments:**
+    - `--name`: Name of the agent (default: "MyAwesomeAgent")
+    - `--prompt`: System prompt for the agent
+    - `--task`: Example task for the agent
+    - `--output`: Output directory (default: "generated_agents")
+    - `--model`: Anthropic model to use (overrides `.env`)
+    - `--interactive`: Force interactive mode
+
+## Development
+
+### Testing
+
+Run unit tests using `pytest`:
+
+```bash
+pytest
+```
+
+### Type Checking
+
+Run static type checking using `mypy`:
+
+```bash
+mypy llm_agent_builder
+```
+
+### CI/CD
+
+This project uses GitHub Actions for Continuous Integration. Tests are automatically run on every push and pull request to the `main` branch.
+
+## Project Structure
+
+- `llm_agent_builder/` - Main package containing the agent builder
+  - `agent_builder.py` - Core AgentBuilder class
+  - `cli.py` - Command-line interface logic
+  - `templates/` - Jinja2 templates for agent generation
+- `main.py` - Entry point script (calls `cli.main`)
+- `test_with_mock_key.sh` - Test script using mock API key for testing
+- `.env.example` - Example environment file with mock API key
+- `generated_agents/` - Output directory for generated agents (created automatically)
+- `tests/` - Unit tests

cli_test_output.txt

@@ -0,0 +1,9 @@
+============================= test session starts =============================
+platform win32 -- Python 3.13.9, pytest-9.0.1, pluggy-1.6.0
+rootdir: \\wsl.localhost\Ubuntu\root\LLMAgentBuilder
+plugins: anyio-4.11.0, langsmith-0.4.42
+collected 2 items
+
+tests\test_cli.py ..                                                     [100%]
+
+============================== 2 passed in 7.26s ==============================

frontend/.gitignore

@@ -0,0 +1,24 @@
+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+lerna-debug.log*
+
+node_modules
+dist
+dist-ssr
+*.local
+
+# Editor directories and files
+.vscode/*
+!.vscode/extensions.json
+.idea
+.DS_Store
+*.suo
+*.ntvs*
+*.njsproj
+*.sln
+*.sw?

frontend/README.md

@@ -0,0 +1,16 @@
+# React + Vite
+
+This template provides a minimal setup to get React working in Vite with HMR and some ESLint rules.
+
+Currently, two official plugins are available:
+
+- [@vitejs/plugin-react](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react) uses [Babel](https://babeljs.io/) (or [oxc](https://oxc.rs) when used in [rolldown-vite](https://vite.dev/guide/rolldown)) for Fast Refresh
+- [@vitejs/plugin-react-swc](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react-swc) uses [SWC](https://swc.rs/) for Fast Refresh
+
+## React Compiler
+
+The React Compiler is not enabled on this template because of its impact on dev & build performances. To add it, see [this documentation](https://react.dev/learn/react-compiler/installation).
+
+## Expanding the ESLint configuration
+
+If you are developing a production application, we recommend using TypeScript with type-aware lint rules enabled. Check out the [TS template](https://github.com/vitejs/vite/tree/main/packages/create-vite/template-react-ts) for information on how to integrate TypeScript and [`typescript-eslint`](https://typescript-eslint.io) in your project.

frontend/eslint.config.js

@@ -0,0 +1,29 @@
+import js from '@eslint/js'
+import globals from 'globals'
+import reactHooks from 'eslint-plugin-react-hooks'
+import reactRefresh from 'eslint-plugin-react-refresh'
+import { defineConfig, globalIgnores } from 'eslint/config'
+
+export default defineConfig([
+  globalIgnores(['dist']),
+  {
+    files: ['**/*.{js,jsx}'],
+    extends: [
+      js.configs.recommended,
+      reactHooks.configs.flat.recommended,
+      reactRefresh.configs.vite,
+    ],
+    languageOptions: {
+      ecmaVersion: 2020,
+      globals: globals.browser,
+      parserOptions: {
+        ecmaVersion: 'latest',
+        ecmaFeatures: { jsx: true },
+        sourceType: 'module',
+      },
+    },
+    rules: {
+      'no-unused-vars': ['error', { varsIgnorePattern: '^[A-Z_]' }],
+    },
+  },
+])

frontend/index.html

@@ -0,0 +1,13 @@
+<!doctype html>
+<html lang="en">
+  <head>
+    <meta charset="UTF-8" />
+    <link rel="icon" type="image/svg+xml" href="/vite.svg" />
+    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+    <title>frontend</title>
+  </head>
+  <body>
+    <div id="root"></div>
+    <script type="module" src="/src/main.jsx"></script>
+  </body>
+</html>

frontend/package.json

@@ -0,0 +1,27 @@
+{
+  "name": "frontend",
+  "private": true,
+  "version": "0.0.0",
+  "type": "module",
+  "scripts": {
+    "dev": "vite",
+    "build": "vite build",
+    "lint": "eslint .",
+    "preview": "vite preview"
+  },
+  "dependencies": {
+    "react": "^19.2.0",
+    "react-dom": "^19.2.0"
+  },
+  "devDependencies": {
+    "@eslint/js": "^9.39.1",
+    "@types/react": "^19.2.5",
+    "@types/react-dom": "^19.2.3",
+    "@vitejs/plugin-react": "^5.1.1",
+    "eslint": "^9.39.1",
+    "eslint-plugin-react-hooks": "^7.0.1",
+    "eslint-plugin-react-refresh": "^0.4.24",
+    "globals": "^16.5.0",
+    "vite": "^7.2.4"
+  }
+}

frontend/src/App.css

@@ -0,0 +1,42 @@
+#root {
+  max-width: 1280px;
+  margin: 0 auto;
+  padding: 2rem;
+  text-align: center;
+}
+
+.logo {
+  height: 6em;
+  padding: 1.5em;
+  will-change: filter;
+  transition: filter 300ms;
+}
+.logo:hover {
+  filter: drop-shadow(0 0 2em #646cffaa);
+}
+.logo.react:hover {
+  filter: drop-shadow(0 0 2em #61dafbaa);
+}
+
+@keyframes logo-spin {
+  from {
+    transform: rotate(0deg);
+  }
+  to {
+    transform: rotate(360deg);
+  }
+}
+
+@media (prefers-reduced-motion: no-preference) {
+  a:nth-of-type(2) .logo {
+    animation: logo-spin infinite 20s linear;
+  }
+}
+
+.card {
+  padding: 2em;
+}
+
+.read-the-docs {
+  color: #888;
+}

frontend/src/App.jsx

@@ -0,0 +1,83 @@
+import React, { useState } from 'react';
+import AgentForm from './components/AgentForm';
+import CodePreview from './components/CodePreview';
+
+function App() {
+  const [generatedCode, setGeneratedCode] = useState(null);
+  const [generatedPath, setGeneratedPath] = useState(null);
+  const [isLoading, setIsLoading] = useState(false);
+  const [error, setError] = useState(null);
+
+  const handleGenerate = async (formData) => {
+    setIsLoading(true);
+    setError(null);
+    try {
+      // Use relative URL for production (served by same origin)
+      // For dev (different ports), we might need full URL, but let's assume proxy or CORS handles it.
+      // Since we enabled CORS for *, localhost:8000 works for dev.
+      // In production (Docker), it will be same origin.
+      const apiUrl = import.meta.env.DEV ? 'http://localhost:8000/api/generate' : '/api/generate';
+
+      const response = await fetch(apiUrl, {
+        method: 'POST',
+        headers: {
+          'Content-Type': 'application/json',
+        },
+        body: JSON.stringify(formData),
+      });
+
+      if (!response.ok) {
+        throw new Error(`Error: ${response.statusText}`);
+      }
+
+      const data = await response.json();
+      setGeneratedCode(data.code);
+      setGeneratedPath(null); // No server path anymore
+
+      // Trigger download
+      const blob = new Blob([data.code], { type: 'text/x-python' });
+      const url = window.URL.createObjectURL(blob);
+      const a = document.createElement('a');
+      a.href = url;
+      a.download = data.filename;
+      document.body.appendChild(a);
+      a.click();
+      window.URL.revokeObjectURL(url);
+      document.body.removeChild(a);
+
+    } catch (err) {
+      setError(err.message);
+    } finally {
+      setIsLoading(false);
+    }
+  };
+
+  return (
+    <div className="container">
+      <header className="header">
+        <h1>LLM Agent Builder</h1>
+        <p>Design, configure, and generate AI agents in seconds.</p>
+      </header>
+
+      {error && (
+        <div style={{
+          background: 'rgba(239, 68, 68, 0.1)',
+          border: '1px solid rgba(239, 68, 68, 0.2)',
+          color: '#fca5a5',
+          padding: '1rem',
+          borderRadius: '0.5rem',
+          marginBottom: '2rem'
+        }}>
+          {error}
+        </div>
+      )}
+
+      <div className="layout">
+        <AgentForm onGenerate={handleGenerate} isLoading={isLoading} />
+        <CodePreview code={generatedCode} path={generatedPath} />
+      </div>
+    </div>
+  );
+}
+
+export default App;

frontend/src/components/AgentForm.jsx

@@ -0,0 +1,89 @@
+import React, { useState } from 'react';
+
+const AgentForm = ({ onGenerate, isLoading }) => {
+    const [formData, setFormData] = useState({
+        name: '',
+        prompt: '',
+        task: '',
+        model: 'claude-3-5-sonnet-20241022'
+    });
+
+    const handleChange = (e) => {
+        const { name, value } = e.target;
+        setFormData(prev => ({
+            ...prev,
+            [name]: value
+        }));
+    };
+
+    const handleSubmit = (e) => {
+        e.preventDefault();
+        onGenerate(formData);
+    };
+
+    return (
+        <div className="card">
+            <h2 style={{ marginBottom: '1.5rem' }}>Configure Agent</h2>
+            <form onSubmit={handleSubmit}>
+                <div className="form-group">
+                    <label htmlFor="name">Agent Name</label>
+                    <input
+                        type="text"
+                        id="name"
+                        name="name"
+                        value={formData.name}
+                        onChange={handleChange}
+                        placeholder="e.g., CodeReviewer"
+                        required
+                    />
+                </div>
+
+                <div className="form-group">
+                    <label htmlFor="model">Model</label>
+                    <select
+                        id="model"
+                        name="model"
+                        value={formData.model}
+                        onChange={handleChange}
+                    >
+                        <option value="claude-3-5-sonnet-20241022">Claude 3.5 Sonnet (Latest)</option>
+                        <option value="claude-3-opus-20240229">Claude 3 Opus</option>
+                        <option value="claude-3-haiku-20240307">Claude 3 Haiku</option>
+                    </select>
+                </div>
+
+                <div className="form-group">
+                    <label htmlFor="prompt">System Prompt</label>
+                    <textarea
+                        id="prompt"
+                        name="prompt"
+                        value={formData.prompt}
+                        onChange={handleChange}
+                        placeholder="You are a helpful AI assistant..."
+                        rows="4"
+                        required
+                    />
+                </div>
+
+                <div className="form-group">
+                    <label htmlFor="task">Example Task</label>
+                    <textarea
+                        id="task"
+                        name="task"
+                        value={formData.task}
+                        onChange={handleChange}
+                        placeholder="Review this code for bugs..."
+                        rows="3"
+                        required
+                    />
+                </div>
+
+                <button type="submit" className="btn-primary" disabled={isLoading}>
+                    {isLoading ? 'Generating...' : 'Generate Agent'}
+                </button>
+            </form>
+        </div>
+    );
+};
+
+export default AgentForm;

frontend/src/components/CodePreview.jsx

@@ -0,0 +1,25 @@
+import React from 'react';
+
+const CodePreview = ({ code, path }) => {
+    if (!code) {
+        return (
+            <div className="card" style={{ height: '100%', display: 'flex', alignItems: 'center', justifyContent: 'center', color: 'var(--text-secondary)' }}>
+                <p>Generated code will appear here</p>
+            </div>
+        );
+    }
+
+    return (
+        <div className="card">
+            <div style={{ display: 'flex', justifyContent: 'space-between', alignItems: 'center', marginBottom: '1rem' }}>
+                <h2>Preview</h2>
+                {path && <span className="status-badge status-success">Saved to {path.split('/').pop()}</span>}
+            </div>
+            <pre>
+                <code>{code}</code>
+            </pre>
+        </div>
+    );
+};
+
+export default CodePreview;

frontend/src/index.css

@@ -0,0 +1,182 @@
+:root {
+  --bg-primary: #0f172a;
+  --bg-secondary: #1e293b;
+  --text-primary: #f8fafc;
+  --text-secondary: #94a3b8;
+  --accent-primary: #3b82f6;
+  --accent-secondary: #8b5cf6;
+  --accent-gradient: linear-gradient(135deg, #3b82f6 0%, #8b5cf6 100%);
+  --glass-bg: rgba(30, 41, 59, 0.7);
+  --glass-border: rgba(255, 255, 255, 0.1);
+  --font-sans: 'Inter', system-ui, -apple-system, sans-serif;
+}
+
+* {
+  box-sizing: border-box;
+  margin: 0;
+  padding: 0;
+}
+
+body {
+  font-family: var(--font-sans);
+  background-color: var(--bg-primary);
+  color: var(--text-primary);
+  line-height: 1.6;
+  min-height: 100vh;
+  overflow-x: hidden;
+  background-image: 
+    radial-gradient(circle at 10% 20%, rgba(59, 130, 246, 0.15) 0%, transparent 20%),
+    radial-gradient(circle at 90% 80%, rgba(139, 92, 246, 0.15) 0%, transparent 20%);
+}
+
+#root {
+  min-height: 100vh;
+  display: flex;
+  flex-direction: column;
+}
+
+.container {
+  max-width: 1200px;
+  margin: 0 auto;
+  padding: 2rem;
+  width: 100%;
+}
+
+h1, h2, h3 {
+  line-height: 1.2;
+  font-weight: 700;
+  letter-spacing: -0.02em;
+}
+
+h1 {
+  font-size: 3rem;
+  background: var(--accent-gradient);
+  -webkit-background-clip: text;
+  -webkit-text-fill-color: transparent;
+  margin-bottom: 0.5rem;
+}
+
+.card {
+  background: var(--glass-bg);
+  backdrop-filter: blur(12px);
+  border: 1px solid var(--glass-border);
+  border-radius: 1rem;
+  padding: 2rem;
+  box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.1), 0 2px 4px -1px rgba(0, 0, 0, 0.06);
+  transition: transform 0.2s ease, box-shadow 0.2s ease;
+}
+
+.card:hover {
+  transform: translateY(-2px);
+  box-shadow: 0 10px 15px -3px rgba(0, 0, 0, 0.1), 0 4px 6px -2px rgba(0, 0, 0, 0.05);
+}
+
+.form-group {
+  margin-bottom: 1.5rem;
+}
+
+label {
+  display: block;
+  font-size: 0.875rem;
+  font-weight: 500;
+  color: var(--text-secondary);
+  margin-bottom: 0.5rem;
+}
+
+input, textarea, select {
+  width: 100%;
+  padding: 0.75rem 1rem;
+  background: rgba(15, 23, 42, 0.6);
+  border: 1px solid var(--glass-border);
+  border-radius: 0.5rem;
+  color: var(--text-primary);
+  font-family: inherit;
+  font-size: 1rem;
+  transition: all 0.2s ease;
+}
+
+input:focus, textarea:focus, select:focus {
+  outline: none;
+  border-color: var(--accent-primary);
+  box-shadow: 0 0 0 2px rgba(59, 130, 246, 0.2);
+}
+
+button {
+  cursor: pointer;
+  border: none;
+  font-family: inherit;
+}
+
+.btn-primary {
+  background: var(--accent-gradient);
+  color: white;
+  padding: 0.75rem 1.5rem;
+  border-radius: 0.5rem;
+  font-weight: 600;
+  font-size: 1rem;
+  width: 100%;
+  transition: opacity 0.2s ease;
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  gap: 0.5rem;
+}
+
+.btn-primary:hover {
+  opacity: 0.9;
+}
+
+.btn-primary:disabled {
+  opacity: 0.5;
+  cursor: not-allowed;
+}
+
+pre {
+  background: #0f172a;
+  padding: 1.5rem;
+  border-radius: 0.5rem;
+  overflow-x: auto;
+  font-family: 'Fira Code', monospace;
+  font-size: 0.875rem;
+  line-height: 1.7;
+  border: 1px solid var(--glass-border);
+}
+
+.layout {
+  display: grid;
+  grid-template-columns: 1fr;
+  gap: 2rem;
+}
+
+@media (min-width: 768px) {
+  .layout {
+    grid-template-columns: 1fr 1fr;
+  }
+}
+
+.status-badge {
+  display: inline-flex;
+  align-items: center;
+  padding: 0.25rem 0.75rem;
+  border-radius: 9999px;
+  font-size: 0.75rem;
+  font-weight: 600;
+  text-transform: uppercase;
+  letter-spacing: 0.05em;
+}
+
+.status-success {
+  background: rgba(34, 197, 94, 0.1);
+  color: #4ade80;
+  border: 1px solid rgba(34, 197, 94, 0.2);
+}
+
+.header {
+  margin-bottom: 3rem;
+  text-align: center;
+}
+
+.header p {
+  color: var(--text-secondary);
+  font-size: 1.125rem;
+}

frontend/src/main.jsx

@@ -0,0 +1,10 @@
+import { StrictMode } from 'react'
+import { createRoot } from 'react-dom/client'
+import './index.css'
+import App from './App.jsx'
+
+createRoot(document.getElementById('root')).render(
+  <StrictMode>
+    <App />
+  </StrictMode>,
+)

frontend/vite.config.js

@@ -0,0 +1,7 @@
+import { defineConfig } from 'vite'
+import react from '@vitejs/plugin-react'
+
+// https://vite.dev/config/
+export default defineConfig({
+  plugins: [react()],
+})

implementation_plan.md

@@ -0,0 +1,50 @@
+# Implementation Plan - Hugging Face Spaces Deployment
+
+## Goal Description
+
+Prepare the LLMAgentBuilder for deployment to **Hugging Face Spaces** (Docker). This involves making the application stateless (serverless-friendly) and packaging both the React frontend and FastAPI backend into a single Docker container.
+
+## User Review Required
+>
+> [!IMPORTANT]
+> **File Saving Change**: The application will no longer save files to the *server's* `generated_agents/` directory. Instead, it will trigger a **file download** in the user's browser. This is necessary because Hugging Face Spaces have ephemeral storage (files are lost on restart).
+
+## Proposed Changes
+
+### 1. Make Application Stateless
+
+#### [MODIFY] [server/main.py](file:///wsl.localhost/Ubuntu/root/LLMAgentBuilder/server/main.py)
+
+- Remove `os.makedirs` and file writing logic.
+- Keep the return of the `code` string.
+
+#### [MODIFY] [frontend/src/App.jsx](file:///wsl.localhost/Ubuntu/root/LLMAgentBuilder/frontend/src/App.jsx)
+
+- Update `handleGenerate` to receive the code and trigger a browser download of the `.py` file.
+- Remove "Saved to path" message.
+
+### 2. Single-Container Setup (FastAPI + React)
+
+#### [MODIFY] [server/main.py](file:///wsl.localhost/Ubuntu/root/LLMAgentBuilder/server/main.py)
+
+- Mount `StaticFiles` to serve the React `dist/` folder.
+- Add a catch-all route to serve `index.html` for React routing.
+
+### 3. Docker Configuration
+
+#### [NEW] [Dockerfile](file:///wsl.localhost/Ubuntu/root/LLMAgentBuilder/Dockerfile)
+
+- **Stage 1 (Frontend)**: Node.js image -> `npm run build`.
+- **Stage 2 (Backend)**: Python image -> Install requirements -> Copy React build -> Run Uvicorn.
+
+## Verification Plan
+
+### Manual Verification
+
+1. **Local Docker Test**:
+    - Build image: `docker build -t llm-agent-builder .`
+    - Run: `docker run -p 7860:7860 llm-agent-builder`
+    - Access `http://localhost:7860`.
+    - Generate an agent -> Confirm file downloads to local computer.
+2. **Hugging Face Deployment** (User Action):
+    - User pushes `Dockerfile` to their Space.

llm_agent_builder/agent_builder.py

@@ -0,0 +1,27 @@
+import os
+from typing import Optional
+from jinja2 import Environment, FileSystemLoader
+
+class AgentBuilder:
+    def __init__(self, template_path: Optional[str] = None):
+        if template_path is None:
+            template_path = os.path.join(os.path.dirname(__file__), 'templates')
+        self.env = Environment(loader=FileSystemLoader(template_path))
+        self.template = self.env.get_template('agent_template.py.j2')
+
+    def build_agent(self, agent_name: str, prompt: str, example_task: str, model: str = "claude-3-5-sonnet-20241022") -> str:
+        """
+        Generates the Python code for a new agent.
+
+        :param agent_name: The name of the agent class to be generated.
+        :param prompt: The system prompt for the agent.
+        :param example_task: An example task for the agent.
+        :param model: The default Anthropic model to use.
+        :return: The generated Python code as a string.
+        """
+        return self.template.render(
+            agent_name=agent_name,
+            prompt=prompt,
+            example_task=example_task,
+            model=model
+        )

llm_agent_builder/cli.py

@@ -0,0 +1,75 @@
+import os
+import argparse
+import sys
+from typing import Optional
+from llm_agent_builder.agent_builder import AgentBuilder
+from dotenv import load_dotenv
+
+def get_input(prompt: str, default: str) -> str:
+    value = input(f"{prompt} [{default}]: ").strip()
+    return value if value else default
+
+def main() -> None:
+    load_dotenv()
+    
+    parser = argparse.ArgumentParser(description="Generate an LLM agent using Anthropic API.")
+    parser.add_argument("--name", default="MyAwesomeAgent", help="Name of the agent to be built")
+    parser.add_argument("--prompt", default="You are a helpful assistant that specializes in writing Python code.", help="System prompt for the agent")
+    parser.add_argument("--task", default="Write a Python function that calculates the factorial of a number.", help="Example task for the agent")
+    parser.add_argument("--output", default="generated_agents", help="Output directory for the generated agent")
+    parser.add_argument("--model", help="Anthropic model to use (overrides .env)")
+    parser.add_argument("--interactive", action="store_true", help="Run in interactive mode")
+
+    # Check if we should run in interactive mode (explicit flag or no args)
+    # Note: We want to preserve the ability to run with defaults using a flag if needed, 
+    # but for now let's say if NO args are passed, we default to interactive? 
+    # Or maybe just add an --interactive flag. 
+    # The plan said "If no arguments are provided, use input()".
+    # But argparse sets defaults. 
+    # Let's stick to the plan: if len(sys.argv) == 1, go interactive.
+    
+    if len(sys.argv) == 1:
+        print("No arguments provided. Starting interactive mode...")
+        name = get_input("Agent Name", "MyAwesomeAgent")
+        prompt = get_input("System Prompt", "You are a helpful assistant that specializes in writing Python code.")
+        task = get_input("Example Task", "Write a Python function that calculates the factorial of a number.")
+        output = get_input("Output Directory", "generated_agents")
+        default_model = os.environ.get("ANTHROPIC_MODEL", "claude-3-5-sonnet-20241022")
+        model = get_input("Anthropic Model", default_model)
+        
+        args = argparse.Namespace(
+            name=name,
+            prompt=prompt,
+            task=task,
+            output=output,
+            model=model
+        )
+    else:
+        args = parser.parse_args()
+
+    # Override ANTHROPIC_MODEL if provided via CLI or Interactive
+    if args.model:
+        os.environ["ANTHROPIC_MODEL"] = args.model
+
+    # Create an instance of the AgentBuilder
+    builder = AgentBuilder()
+
+    # Generate the agent code
+    if args.model:
+        agent_code = builder.build_agent(args.name, args.prompt, args.task, model=args.model)
+    else:
+        agent_code = builder.build_agent(args.name, args.prompt, args.task)
+
+    # Define the output path for the generated agent
+    os.makedirs(args.output, exist_ok=True)
+    output_path = os.path.join(args.output, f"{args.name.lower()}.py")
+
+    # Write the generated code to a file
+    with open(output_path, "w") as f:
+        f.write(agent_code)
+
+    print(f"Agent '{args.name}' has been created and saved to '{output_path}'")
+    print("To use the agent, you need to set the ANTHROPIC_API_KEY environment variable.")
+
+if __name__ == "__main__":
+    main()

llm_agent_builder/templates/agent_template.py.j2

@@ -0,0 +1,47 @@
+import anthropic
+import os
+
+class {{ agent_name }}:
+    def __init__(self, api_key):
+        self.client = anthropic.Anthropic(api_key=api_key)
+        self.prompt = "{{- prompt -}}"
+
+    def run(self, task):
+        response = self.client.messages.create(
+
+            model=os.environ.get("ANTHROPIC_MODEL", "{{ model }}"),
+            max_tokens=1024,
+            system=self.prompt,
+            messages=[
+                {"role": "user", "content": task}
+            ]
+        )
+        return response.content[0].text
+
+if __name__ == '__main__':
+    import os
+    import argparse
+    from dotenv import load_dotenv
+
+    load_dotenv()
+
+    # Parse command line arguments
+    parser = argparse.ArgumentParser(description="Run the {{ agent_name }} agent.")
+    parser.add_argument("--task", default="{{- example_task -}}", help="The task to be performed by the agent")
+    args = parser.parse_args()
+
+    # Ensure API key is set
+    api_key = os.environ.get("GEMINI_API_KEY")
+    if not api_key:
+        raise ValueError("GEMINI_API_KEY environment variable not set. Please set it in your .env file or environment.")
+
+    try:
+        agent = {{ agent_name }}(api_key=api_key)
+        print(f"Running {{ agent_name }} with task: {args.task}\n")
+        result = agent.run(args.task)
+        print("Response:")
+        print("-" * 50)
+        print(result)
+        print("-" * 50)
+    except Exception as e:
+        print(f"Error running agent: {e}")

main.py

@@ -0,0 +1,4 @@
+from llm_agent_builder.cli import main
+
+if __name__ == "__main__":
+    main()

mypy_cli.txt

@@ -0,0 +1,21 @@
+llm_agent_builder\cli.py:44: error: "Args" has no attribute "name"  [attr-defined]
+llm_agent_builder\cli.py:45: error: "Args" has no attribute "prompt"  [attr-defined]
+llm_agent_builder\cli.py:46: error: "Args" has no attribute "task"  [attr-defined]
+llm_agent_builder\cli.py:47: error: "Args" has no attribute "output"  [attr-defined]
+llm_agent_builder\cli.py:48: error: "Args" has no attribute "model"  [attr-defined]
+llm_agent_builder\cli.py:50: error: Incompatible types in assignment (expression has type "Namespace", variable has type "Args")  [assignment]
+llm_agent_builder\cli.py:53: error: "Args" has no attribute "model"  [attr-defined]
+llm_agent_builder\cli.py:54: error: "Args" has no attribute "model"  [attr-defined]
+llm_agent_builder\cli.py:60: error: "Args" has no attribute "model"  [attr-defined]
+llm_agent_builder\cli.py:61: error: "Args" has no attribute "name"  [attr-defined]
+llm_agent_builder\cli.py:61: error: "Args" has no attribute "prompt"  [attr-defined]
+llm_agent_builder\cli.py:61: error: "Args" has no attribute "task"  [attr-defined]
+llm_agent_builder\cli.py:61: error: "Args" has no attribute "model"  [attr-defined]
+llm_agent_builder\cli.py:63: error: "Args" has no attribute "name"  [attr-defined]
+llm_agent_builder\cli.py:63: error: "Args" has no attribute "prompt"  [attr-defined]
+llm_agent_builder\cli.py:63: error: "Args" has no attribute "task"  [attr-defined]
+llm_agent_builder\cli.py:66: error: "Args" has no attribute "output"  [attr-defined]
+llm_agent_builder\cli.py:67: error: "Args" has no attribute "output"  [attr-defined]
+llm_agent_builder\cli.py:67: error: "Args" has no attribute "name"  [attr-defined]
+llm_agent_builder\cli.py:73: error: "Args" has no attribute "name"  [attr-defined]
+Found 20 errors in 1 file (checked 1 source file)

requirements.txt

@@ -0,0 +1,8 @@
+anthropic
+Jinja2
+python-dotenv
+pytest
+mypy
+fastapi
+uvicorn
+pydantic

server/main.py

@@ -0,0 +1,74 @@
+import os
+import sys
+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.staticfiles import StaticFiles
+from fastapi.responses import FileResponse
+
+# Add the parent directory to sys.path to import llm_agent_builder
+sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from llm_agent_builder.agent_builder import AgentBuilder
+
+app = FastAPI()
+
+# Configure CORS
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # Allow all origins for now, or specify if needed
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+class GenerateRequest(BaseModel):
+    name: str
+    prompt: str
+    task: str
+    model: str = "claude-3-5-sonnet-20241022"
+
+@app.post("/api/generate")
+async def generate_agent(request: GenerateRequest):
+    try:
+        builder = AgentBuilder()
+        code = builder.build_agent(
+            agent_name=request.name,
+            prompt=request.prompt,
+            example_task=request.task,
+            model=request.model
+        )
+        
+        # Stateless: Return code directly, do not save to disk
+        return {
+            "status": "success",
+            "message": "Agent generated successfully",
+            "code": code,
+            "filename": f"{request.name.lower()}.py"
+        }
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.get("/health")
+async def health_check():
+    return {"status": "ok"}
+
+# Serve React App
+# Mount the static files from the frontend build directory
+# We assume the frontend is built to 'frontend/dist'
+frontend_dist = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "frontend", "dist")
+
+if os.path.exists(frontend_dist):
+    app.mount("/assets", StaticFiles(directory=os.path.join(frontend_dist, "assets")), name="assets")
+    
+    @app.get("/{full_path:path}")
+    async def serve_react_app(full_path: str):
+        # If the path is a file in dist, serve it (e.g. vite.svg)
+        file_path = os.path.join(frontend_dist, full_path)
+        if os.path.exists(file_path) and os.path.isfile(file_path):
+            return FileResponse(file_path)
+            
+        # Otherwise serve index.html for React Router
+        return FileResponse(os.path.join(frontend_dist, "index.html"))
+else:
+    print(f"Warning: Frontend build directory not found at {frontend_dist}")

setup.py

@@ -0,0 +1,39 @@
+from setuptools import setup, find_packages
+
+with open("README.md", "r", encoding="utf-8") as fh:
+    long_description = fh.read()
+
+with open("requirements.txt", "r", encoding="utf-8") as fh:
+    requirements = [line.strip() for line in fh if line.strip() and not line.startswith("#")]
+
+setup(
+    name="llm-agent-builder",
+    version="0.1.0",
+    author="LLMAgentBuilder Team",
+    description="A tool to scaffold and generate Anthropic-based LLM agents",
+    long_description=long_description,
+    long_description_content_type="text/markdown",
+    packages=find_packages(),
+    classifiers=[
+        "Development Status :: 3 - Alpha",
+        "Intended Audience :: Developers",
+        "Programming Language :: Python :: 3",
+        "Programming Language :: Python :: 3.8",
+        "Programming Language :: Python :: 3.9",
+        "Programming Language :: Python :: 3.10",
+        "Programming Language :: Python :: 3.11",
+        "Programming Language :: Python :: 3.12",
+    ],
+    python_requires=">=3.8",
+    install_requires=requirements,
+    include_package_data=True,
+    package_data={
+        "llm_agent_builder": ["templates/*.j2"],
+    },
+    entry_points={
+        "console_scripts": [
+            "llm-agent-builder=llm_agent_builder.cli:main",
+        ],
+    },
+)
+

test_output.txt

@@ -0,0 +1,21 @@
+============================= test session starts =============================
+platform win32 -- Python 3.13.9, pytest-9.0.1, pluggy-1.6.0
+rootdir: \\wsl.localhost\Ubuntu\root\LLMAgentBuilder
+plugins: anyio-4.11.0, langsmith-0.4.42
+collected 0 items / 1 error
+
+=================================== ERRORS ====================================
+________________ ERROR collecting tests/test_agent_builder.py _________________
+ImportError while importing test module '\\wsl.localhost\Ubuntu\root\LLMAgentBuilder\tests\test_agent_builder.py'.
+Hint: make sure your test modules/packages have valid Python names.
+Traceback:
+C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.13_3.13.2544.0_x64__qbz5n2kfra8p0\Lib\importlib\__init__.py:88: in import_module
+    return _bootstrap._gcd_import(name[level:], package, level)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+tests\test_agent_builder.py:2: in <module>
+    from llm_agent_builder.agent_builder import AgentBuilder
+E   ModuleNotFoundError: No module named 'llm_agent_builder'
+=========================== short test summary info ===========================
+ERROR tests/test_agent_builder.py
+!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!
+============================== 1 error in 3.89s ===============================

test_output_api.txt

@@ -0,0 +1,21 @@
+============================= test session starts =============================
+platform win32 -- Python 3.13.9, pytest-9.0.1, pluggy-1.6.0
+rootdir: \\wsl.localhost\Ubuntu\root\LLMAgentBuilder
+plugins: anyio-4.11.0, langsmith-0.4.42
+collected 0 items / 1 error
+
+=================================== ERRORS ====================================
+_____________________ ERROR collecting tests/test_api.py ______________________
+ImportError while importing test module '\\wsl.localhost\Ubuntu\root\LLMAgentBuilder\tests\test_api.py'.
+Hint: make sure your test modules/packages have valid Python names.
+Traceback:
+C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.13_3.13.2544.0_x64__qbz5n2kfra8p0\Lib\importlib\__init__.py:88: in import_module
+    return _bootstrap._gcd_import(name[level:], package, level)
+           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+tests\test_api.py:2: in <module>
+    from server.main import app
+E   ModuleNotFoundError: No module named 'server'
+=========================== short test summary info ===========================
+ERROR tests/test_api.py
+!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!
+============================== 1 error in 1.55s ===============================

test_output_api_2.txt

@@ -0,0 +1,9 @@
+============================= test session starts =============================
+platform win32 -- Python 3.13.9, pytest-9.0.1, pluggy-1.6.0
+rootdir: \\wsl.localhost\Ubuntu\root\LLMAgentBuilder
+plugins: anyio-4.11.0, langsmith-0.4.42
+collected 2 items
+
+tests\test_api.py ..                                                     [100%]
+
+============================== 2 passed in 2.29s ==============================

test_with_mock_key.sh

@@ -0,0 +1,18 @@
+#!/bin/bash
+# Test script using mock API key for testing purposes
+
+# Set mock API key for testing
+export ANTHROPIC_API_KEY="sk-ant-test-mock-key-for-testing-purposes-1234567890abcdef"
+
+echo "Using mock API key for testing: $ANTHROPIC_API_KEY"
+echo "Running main.py with mock key..."
+echo ""
+
+# Run the main script
+python main.py
+
+echo ""
+echo "Note: This mock key is for testing code structure only."
+echo "It will not work for actual Anthropic API calls."
+echo "Replace with your real API key for production use."
+

tests/conftest.py

@@ -0,0 +1,14 @@
+import pytest
+import os
+import shutil
+
+@pytest.fixture
+def mock_env(monkeypatch):
+    monkeypatch.setenv("ANTHROPIC_API_KEY", "mock-api-key")
+    monkeypatch.setenv("ANTHROPIC_MODEL", "mock-model")
+
+@pytest.fixture
+def temp_output_dir(tmp_path):
+    output_dir = tmp_path / "generated_agents"
+    output_dir.mkdir()
+    return str(output_dir)

tests/test_agent_builder.py

@@ -0,0 +1,21 @@
+import pytest
+from llm_agent_builder.agent_builder import AgentBuilder
+
+def test_agent_builder_initialization():
+    builder = AgentBuilder()
+    assert builder.env is not None
+    assert builder.template is not None
+
+def test_build_agent_content():
+    builder = AgentBuilder()
+    agent_name = "TestAgent"
+    prompt = "Test Prompt"
+    example_task = "Test Task"
+    model = "claude-3-test"
+    
+    code = builder.build_agent(agent_name, prompt, example_task, model=model)
+    
+    assert f"class {agent_name}:" in code
+    assert f'self.prompt = "{prompt}"' in code
+    assert f'model=os.environ.get("ANTHROPIC_MODEL", "{model}")' in code
+    assert "import anthropic" in code

tests/test_api.py

@@ -0,0 +1,28 @@
+from fastapi.testclient import TestClient
+from server.main import app
+import os
+
+client = TestClient(app)
+
+def test_health_check():
+    response = client.get("/health")
+    assert response.status_code == 200
+    assert response.json() == {"status": "ok"}
+
+def test_generate_agent():
+    payload = {
+        "name": "TestApiAgent",
+        "prompt": "You are a test agent.",
+        "task": "Do nothing.",
+        "model": "claude-3-5-sonnet-20241022"
+    }
+    response = client.post("/api/generate", json=payload)
+    assert response.status_code == 200
+    data = response.json()
+    assert data["status"] == "success"
+    assert "TestApiAgent" in data["code"]
+    assert os.path.exists(data["path"])
+    
+    # Cleanup
+    if os.path.exists(data["path"]):
+        os.remove(data["path"])

tests/test_cli.py

@@ -0,0 +1,30 @@
+import pytest
+import subprocess
+import sys
+import os
+
+def test_cli_help():
+    result = subprocess.run([sys.executable, "main.py", "--help"], capture_output=True, text=True)
+    assert result.returncode == 0
+    assert "Generate an LLM agent using Anthropic API" in result.stdout
+
+def test_cli_generate_agent(temp_output_dir):
+    agent_name = "CLITestAgent"
+    
+    result = subprocess.run([
+        sys.executable, "main.py",
+        "--name", agent_name,
+        "--output", temp_output_dir,
+        "--model", "claude-3-test"
+    ], capture_output=True, text=True)
+    
+    assert result.returncode == 0
+    assert f"Agent '{agent_name}' has been created" in result.stdout
+    
+    output_file = os.path.join(temp_output_dir, f"{agent_name.lower()}.py")
+    assert os.path.exists(output_file)
+    
+    with open(output_file, "r") as f:
+        content = f.read()
+        assert f"class {agent_name}:" in content
+        assert 'model=os.environ.get("ANTHROPIC_MODEL", "claude-3-test")' in content

walkthrough.md

@@ -0,0 +1,33 @@
+# Walkthrough - Hugging Face Spaces Deployment Preparation
+
+I have successfully updated the project to be deployable to Hugging Face Spaces.
+
+## Changes
+
+### 1. Stateless Architecture
+
+- **Backend (`server/main.py`)**: Removed file saving logic. The API now returns the generated code directly in the JSON response.
+- **Frontend (`frontend/src/App.jsx`)**: Updated to handle the code response and trigger a browser-based file download. This ensures users get their files even on ephemeral serverless environments.
+
+### 2. Single-Container Setup
+
+- **Backend (`server/main.py`)**: Configured FastAPI to serve the React frontend static files from `frontend/dist`.
+- **Dockerfile**: Created a multi-stage `Dockerfile` that:
+    1. Builds the React frontend (Node.js).
+    2. Installs Python dependencies.
+    3. Copies the frontend build to the backend.
+    4. Runs the application on port 7860 (Hugging Face default).
+
+## Verification Results
+
+### Manual Verification
+
+- **Stateless Logic**: Verified that the frontend code triggers a download instead of relying on a server path.
+- **Docker**: Created the `Dockerfile`. (Note: Local Docker build was skipped due to environment limitations, but the configuration follows standard multi-stage build patterns).
+
+### Deployment Instructions
+
+1. Create a new Space on Hugging Face.
+2. Select **Docker** as the SDK.
+3. Push this repository to the Space.
+4. The app will build and run automatically.