Installation
pip install mindblix
uv add mindblix
Initialization
from mindblix import MindBlix
# Using API key
client = MindBlix(api_key="YOUR_API_KEY")
# Using environment variable (MINDBLIX_API_KEY)
client = MindBlix()
Agents
List Agents
agents = client.agents.list()
for agent in agents:
print(f"{agent.name} ({agent.status})")
Create Agent
agent = client.agents.create(
name="My Research Agent",
template="research",
config={
"max_iterations": 5,
"tools": ["web_search"]
}
)
Execute Agent
result = client.agents.execute(
agent_id="agent_abc123",
input={"query": "Latest AI trends"}
)
print(result.output)
print(f"Tokens used: {result.metadata.tokens_used}")
Async Support
import asyncio
from mindblix import AsyncMindBlix
async def main():
client = AsyncMindBlix(api_key="YOUR_API_KEY")
result = await client.agents.execute(
template="research",
query="Quantum computing breakthroughs 2026"
)
print(result.output)
asyncio.run(main())
Workflows
# Create and trigger a workflow
workflow = client.workflows.create(
name="Analysis Pipeline",
steps=[
{"id": "research", "agent_template": "research"},
{"id": "analyze", "agent_template": "data", "depends_on": ["research"]}
]
)
run = client.workflows.trigger(
workflow_id=workflow.id,
input={"query": "Market analysis for Q1 2026"}
)
# Check status
status = client.workflows.get_run(workflow.id, run.id)
print(f"Status: {status.status}")
Error Handling
from mindblix.exceptions import (
MindBlixError,
AuthenticationError,
RateLimitError,
NotFoundError
)
try:
result = client.agents.execute(...)
except AuthenticationError:
print("Invalid API key")
except RateLimitError as e:
print(f"Rate limited. Retry after {e.retry_after}s")
except NotFoundError:
print("Agent not found")
except MindBlixError as e:
print(f"API error: {e.message}")
