repomix-output.xml

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<file_summary>
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<purpose>
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</purpose>

<file_format>
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1. This summary section
2. Repository information
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5. Multiple file entries, each consisting of:
  - File path as an attribute
  - Full contents of the file
</file_format>

<usage_guidelines>
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  between different files in the repository.
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<notes>
- Some files may have been excluded based on .gitignore rules and Repomix's configuration
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</file_summary>

<directory_structure>
.claude/
  settings.local.json
.container-use/
  AGENT.md
  environment.json
.env.example
.gitignore
.python-version
chatbot.py
CLAUDE.md
process1.md
pyproject.toml
README.md
</directory_structure>

<files>
This section contains the contents of the repository's files.

<file path=".claude/settings.local.json">
{
  "permissions": {
    "allow": [
      "mcp__container-use__environment_open",
      "mcp__container-use__environment_update",
      "mcp__container-use__environment_file_write"
    ],
    "deny": []
  }
}
</file>

<file path=".env.example">
# HF API Key for smol-agent
HF_API_TOKEN=your_huggingface_api_token_here

# Chatbot settings
MODEL_NAME=HuggingFaceH4/zephyr-7b-beta
MAX_NEW_TOKENS=500
TEMPERATURE=0.7
</file>

<file path=".gitignore">
# Environment variables
.env

# Python
__pycache__/
*.py[cod]
*$py.class
*.so
.Python
env/
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
*.egg-info/
.installed.cfg
*.egg

# Virtual environments
venv/
ENV/
.venv

# IDE files
.idea/
.vscode/
*.swp
*.swo
</file>

<file path=".python-version">
3.12
</file>

<file path="process1.md">
# Create a chat bot

Create HF smol-agent lets create a simple chatbot that read a string and reply.
Use python-dotenv to load all the variables from the .env
Use uvx to manage python dependencies.
</file>

<file path=".container-use/AGENT.md">
This environment contains a chatbot project using HuggingFace's smol-agent.
- Python 3.10 is installed
- Use `uvx` for dependency management
- Environment variables are loaded from .env file using python-dotenv
- Use `uvx run` to run Python scripts with dependencies
</file>

<file path=".container-use/environment.json">
{
  "workdir": "/workdir",
  "base_image": "python:3.10-slim",
  "setup_commands": [
    "apt-get update",
    "apt-get install -y git",
    "pip install uv",
    "alias uvx=\"uv\""
  ]
}
</file>

<file path="CLAUDE.md">
ALWAYS use ONLY Environments for ANY and ALL file, code, or shell operations—NO EXCEPTIONS—even for simple or generic requests.

DO NOT install or use the git cli with the environment_run_cmd tool. All environment tools will handle git operations for you. Changing ".git" yourself will compromise the integrity of your environment.

You MUST inform the user how to view your work using `cu log <env_id>` AND `cu checkout <env_id>`. Failure to do this will make your work inaccessible to others.
</file>

<file path="pyproject.toml">
[project]
name = "huggingface-small-agent-test"
version = "0.1.0"
description = "Add your description here"
readme = "README.md"
requires-python = ">=3.12"
dependencies = [
    "smolagents>=1.18.0",
]
</file>

<file path="README.md">
# HuggingFace Smol-Agent Chatbot

A simple chatbot implementation using HuggingFace's smol-agent.

## Setup

1. Clone this repository
2. Create a `.env` file based on `.env.example`:
   ```bash
   cp .env.example .env
   ```
3. Add your HuggingFace API token to the `.env` file

## Usage

### Install dependencies

```bash
uv pip install .
```

### Run the CLI chatbot

```bash
python chatbot.py
```

### Run the API server

```bash
python api.py
```

The API will be available at http://localhost:8000

## API Endpoints

- **POST /chat**: Send a message to the chatbot
  - Request: `{"message": "Hello, how are you?"}`
  - Response: `{"response": "I'm doing well, thank you for asking!"}`

- **GET /health**: Check if the API is running
  - Response: `{"status": "ok"}`
</file>

<file path="chatbot.py">
# /// script
# dependencies = [
#     "smolagents",
# ]
# ///
from smolagents import CodeAgent, HfApiModel
model_id = "meta-llama/Llama-3.3-70B-Instruct"


# Managed Agent
agent = CodeAgent(
	tools=[], 
    model=HfApiModel(model_id=model_id),
    name="mychatbot",
	description="A chatbot for various tasks",
	verbosity_level=2,
	max_steps=10,
    add_base_tools=False,
)
</file>

</files>