Configuration Options

from isa_agent_sdk import query, ISAAgentOptions
 
options = ISAAgentOptions(
    model="gpt-4o-mini",
    allowed_tools=["web_search", "read_file"],
    max_iterations=30
)
 
async for msg in query("Your prompt", options=options):
    print(msg.content, end="" if msg.is_text else "\n")

options = ISAAgentOptions(
    # LLM model to use
    model="gpt-4o-mini",  # Default model
)

from isa_agent_sdk import ISAAgentOptions, SystemPromptConfig, SystemPromptPreset
 
# 1. Simple string - appends to default prompt (backwards compatible)
options = ISAAgentOptions(
    system_prompt="Always respond in formal English. Be concise."
)
 
# 2. Preset with custom additions (recommended)
options = ISAAgentOptions(
    system_prompt=SystemPromptConfig(
        preset=SystemPromptPreset.REASON,  # Use MCP template
        append="Focus on security implications in your analysis."
    )
)
 
# 3. Full replacement (loses built-in capabilities)
options = ISAAgentOptions(
    system_prompt=SystemPromptConfig(
        replace="You are a specialized security auditor. Analyze code for vulnerabilities."
    )
)

options = ISAAgentOptions(
    # Explicit tool allowlist
    allowed_tools=["web_search", "read_file", "write_file", "bash"],
 
    # Tool discovery mode
    tool_discovery=ToolDiscoveryMode.HYBRID,  # explicit, semantic, hybrid
)

from isa_agent_sdk import PermissionMode
 
options = ISAAgentOptions(
    permission_mode=PermissionMode.DEFAULT
)

from isa_agent_sdk import ExecutionMode
 
options = ISAAgentOptions(
    execution_mode=ExecutionMode.REACTIVE
)

options = ISAAgentOptions(
    execution_mode=ExecutionMode.COLLABORATIVE,
    checkpoint_frequency=5,  # Checkpoint every 5 tasks
)

options = ISAAgentOptions(
    execution_mode=ExecutionMode.PROACTIVE,
    proactive_suggestions=True,  # Enable suggestions
)

from isa_agent_sdk import GuardrailMode
 
options = ISAAgentOptions(
    # Enable guardrails
    guardrails_enabled=True,
 
    # Guardrail strictness
    guardrail_mode=GuardrailMode.MODERATE,  # permissive, moderate, strict
 
    # Confidence-based failsafe
    failsafe_enabled=True,
    failsafe_confidence_threshold=0.7,  # 0.0-1.0
 
    # Iteration limit
    max_iterations=30,
)

options = ISAAgentOptions(
    # Session identification
    session_id="my-session-123",  # Auto-generated if not provided
    user_id="user-456",
 
    # Session lifetime
    session_ttl=3600,  # 1 hour (seconds)
 
    # Resume previous session
    resume="previous-session-id",
 
    # Additional metadata
    metadata={
        "project": "my-project",
        "environment": "production"
    }
)

from isa_agent_sdk import ExecutionEnv
 
options = ISAAgentOptions(
    # Where to run the agent
    execution_env=ExecutionEnv.CLOUD_POOL,  # cloud_pool, cloud_shared, desktop
 
    # Pool configuration (for cloud_pool)
    pool_config=PoolConfig(
        pool_type="standard",
        ttl=600,
        memory=512,
        cpu=1
    ),
 
    # Desktop agent URL (for desktop)
    desktop_agent_url="ws://localhost:9000"
)

from isa_agent_sdk import MCPServerConfig
 
options = ISAAgentOptions(
    mcp_servers={
        "github": MCPServerConfig(
            command="npx",
            args=["-y", "@modelcontextprotocol/server-github"],
            env={"GITHUB_TOKEN": "your-token"}
        ),
        "filesystem": MCPServerConfig(
            command="npx",
            args=["-y", "@modelcontextprotocol/server-filesystem", "/path/to/dir"]
        ),
        "custom": MCPServerConfig(
            url="http://localhost:8081/mcp"
        )
    }
)

options = ISAAgentOptions(
    # Agent architecture
    graph_type="smart_agent",  # smart_agent, research, coding, conversation
)

options = ISAAgentOptions(
    # Auto-summarize long conversations
    summarization_enabled=True,
)

from isa_agent_sdk import OutputFormat
 
# From Pydantic model (recommended)
from pydantic import BaseModel
 
class Recipe(BaseModel):
    name: str
    ingredients: list[str]
    prep_time_minutes: int
 
options = ISAAgentOptions(
    output_format=OutputFormat.from_pydantic(Recipe)
)
 
# From JSON schema
options = ISAAgentOptions(
    output_format=OutputFormat.json_schema({
        "type": "object",
        "properties": {
            "name": {"type": "string"},
            "items": {"type": "array", "items": {"type": "string"}}
        },
        "required": ["name"]
    })
)
 
# Simple JSON mode (no schema validation)
options = ISAAgentOptions(
    output_format=OutputFormat.json_object()
)

options = ISAAgentOptions(
    # Activate specialized skills
    skills=["code-review", "debug", "refactor"]
)

# agent_config.yaml
model: gpt-4o-mini
allowed_tools:
  - web_search
  - read_file
  - write_file
  - bash
execution_mode: collaborative
guardrails_enabled: true
guardrail_mode: moderate
max_iterations: 30
skills:
  - code-review
  - debug
mcp_servers:
  github:
    command: npx
    args: ["-y", "@modelcontextprotocol/server-github"]

options = ISAAgentOptions.from_file("agent_config.yaml")

# For SmartAgentGraph
graph_config = options.to_graph_config()
 
# For LangGraph runtime
runtime_config = options.to_runtime_config()