Import: from gaia.agents.chat.agent import ChatAgent
12.1 ChatAgent (Conversational AI with RAG)
Detailed Spec: spec/chat-agent
Purpose: General-purpose conversational agent with file operations, RAG, and shell command capabilities.
from gaia.agents.chat.agent import ChatAgent
# Create chat agent with RAG enabled
agent = ChatAgent(
documents_path="./docs", # Auto-index PDFs in this directory
silent_mode=False
)
# Agent has built-in tools:
# - File operations (read/write/list)
# - Document search (RAG)
# - Shell commands
result = agent.process_query(
"What does the user manual say about configuration? "
"Then create a config.yaml file with those settings."
)
# Agent automatically:
# 1. Searches indexed documents
# 2. Extracts configuration info
# 3. Creates the file with proper settings
12.2 DockerAgent (Containerization)
Import: from gaia.agents.docker.agent import DockerAgent
Detailed Spec: spec/docker-agent
Purpose: Intelligent Docker assistance for containerizing applications with LLM-generated Dockerfiles.
from gaia.agents.docker.agent import DockerAgent
from pathlib import Path
# Create Docker agent
agent = DockerAgent(
model_id="Qwen3-Coder-30B-A3B-Instruct-GGUF",
max_steps=10,
allowed_paths=["/home/user/projects"] # Security: restrict access
)
# Analyze app and generate Dockerfile
result = agent.process_query(
"Analyze this Python Flask app and create an optimized Dockerfile"
)
# Agent:
# 1. Analyzes app structure (finds requirements.txt, main.py, etc.)
# 2. Detects dependencies and runtime needs
# 3. Generates production-ready Dockerfile
# 4. Suggests best practices (multi-stage builds, security)
# Build and run
result = agent.process_query(
"Build the Docker image and run it on port 5000"
)
12.3 JiraAgent (Issue Tracking)
Import: from gaia.agents.jira.agent import JiraAgent
Detailed Spec: spec/jira-agent
Purpose: Natural language interface to Jira with automatic configuration discovery and JQL generation.
from gaia.agents.jira.agent import JiraAgent
import os
# Set credentials
os.environ["ATLASSIAN_SITE_URL"] = "https://company.atlassian.net"
os.environ["ATLASSIAN_API_KEY"] = "your-api-token"
os.environ["ATLASSIAN_USER_EMAIL"] = "[email protected]"
# Create Jira agent with auto-discovery
agent = JiraAgent()
config = agent.initialize() # Discovers projects, issue types, etc.
# Natural language queries
result = agent.process_query(
"Show me all high priority bugs assigned to me"
)
# Create issues
result = agent.process_query(
"Create a new story called 'Add user authentication' in the AUTH project"
)
# Update issues
result = agent.process_query(
"Update PROJ-123 status to In Progress and add comment 'Working on it'"
)
# Agent features:
# - Automatic Jira instance discovery
# - Natural language to JQL translation
# - Handles project names, issue types, statuses
# - Robust error handling
12.4 BlenderAgent (3D Graphics)
Import: from gaia.agents.blender.agent import BlenderAgent
Detailed Spec: spec/blender-agent
Purpose: Natural language interface for Blender 3D modeling, scene creation, and rendering.
from gaia.agents.blender.agent import BlenderAgent
# Create Blender agent
agent = BlenderAgent(
model_id="Qwen3-Coder-30B-A3B-Instruct-GGUF"
)
# Natural language 3D modeling
result = agent.process_query(
"Create a blue sphere at position (0, 0, 5) with radius 2"
)
# Complex scenes
result = agent.process_query(
"Create a simple room with a table and chair. "
"Add a camera looking at the table. "
"Render the scene with good lighting."
)
# Agent capabilities:
# - Object creation (cubes, spheres, meshes)
# - Material/texture application
# - Camera and lighting setup
# - Scene composition
# - Rendering operations