Configuration
Configure routes, middleware, and provider settings for production chat workloads.
Server options
Keep provider and server credentials in environment variables, then apply them through typed config objects.
export MISTRAL_API_KEY="your-key"
export MISTRAL_BASE_URL="https://api.mistral.ai"
export MISTRAL_MODEL="mistral-medium-latest"import os
try:
from jazzmine.core import AgentBuilder, OpenAILLMConfig, ServerConfig
except ImportError:
from jazzmine.core.builder import AgentBuilder, OpenAILLMConfig, ServerConfig
builder = (
AgentBuilder(
name="CoreServer",
agent_id="core-server-v1",
personality="Reliable backend assistant.",
)
.llm(
OpenAILLMConfig(
model=os.environ.get("MISTRAL_MODEL", "mistral-medium-latest"),
api_key=os.environ["MISTRAL_API_KEY"],
base_url=os.environ.get("MISTRAL_BASE_URL", "https://api.mistral.ai"),
)
)
.server(ServerConfig(host="0.0.0.0", port=8080))
)Middleware pipeline
Keep middleware deterministic: validate input early, attach security checks before invoking tools, and emit structured trace events at each stage of the request lifecycle.
Provider adapters
Choose an LLM config model per provider and keep provider-specific credentials in secure environment injection, not hard-coded values.
- Configuration models — full dataclass references for LLM, memory, security, and server settings.
- Server integration — FastAPI/Uvicorn integration patterns and production server wiring.
Installation
Set up jazzmine in a Python environment and validate runtime dependencies.
Agent Logger
The AgentLogger is the specialized structured logging engine for the jazzmine agent system. It is designed to provide high-fidelity observability into the internal life of an agent. Unlike standard prose-based logging, the AgentLogger emits Semantic Events—standardized, JSON-serializable records that allow dashboards, alert systems, and developers to track the agent's reasoning, tool execution, and resource consumption with mathematical precision.