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MCP docs: - quickstart.md - Installation, basic usage, transport modes - configuration.md - CLI options, env vars, config files - vscode.md - VS Code, Cursor, Windsurf integration Agent SDK docs: - agents.md - Creating and configuring agents - running_agents.md - Runner, RunConfig, async/sync - tools.md - Function tools, context, custom tools - guardrails.md - Input/output validation - handoffs.md - Agent delegation patterns - streaming.md - Stream events and responses - tracing.md - Observability and debugging - context.md - Mutable run context - config.md - RunConfig and ModelSettings - results.md - RunResult, items, usage - models.md - Providers and model selection - multi_agent.md - Complex multi-agent patterns
171 lines
3.7 KiB
Markdown
171 lines
3.7 KiB
Markdown
# Configuration
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Configure agent behavior with `RunConfig` and `ModelSettings`.
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## RunConfig
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Global settings for an agent run:
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```python
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from agents import Runner, RunConfig, ModelSettings
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config = RunConfig(
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model="gpt-4o",
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model_settings=ModelSettings(temperature=0.7),
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max_turns=20,
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)
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result = await Runner.run(agent, "Hello!", run_config=config)
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```
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## RunConfig Options
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| Parameter | Type | Default | Description |
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|-----------|------|---------|-------------|
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| `model` | `str \| Model` | None | Override all agent models |
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| `model_provider` | `ModelProvider` | OpenAI | Model provider |
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| `model_settings` | `ModelSettings` | None | Global model settings |
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| `max_turns` | `int` | 10 | Max conversation turns |
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| `input_guardrails` | `list` | None | Global input guardrails |
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| `output_guardrails` | `list` | None | Global output guardrails |
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| `handoff_input_filter` | `HandoffInputFilter` | None | Global handoff filter |
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| `tracing_disabled` | `bool` | False | Disable tracing |
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## ModelSettings
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Fine-tune model behavior:
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```python
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from agents import Agent, ModelSettings
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settings = ModelSettings(
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temperature=0.7,
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top_p=0.9,
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max_tokens=1000,
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presence_penalty=0.0,
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frequency_penalty=0.0,
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)
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agent = Agent(
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name="creative",
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instructions="Be creative.",
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model_settings=settings,
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)
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```
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## ModelSettings Options
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| Parameter | Type | Default | Description |
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|-----------|------|---------|-------------|
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| `temperature` | `float` | 1.0 | Randomness (0-2) |
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| `top_p` | `float` | 1.0 | Nucleus sampling |
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| `max_tokens` | `int` | None | Max output tokens |
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| `presence_penalty` | `float` | 0.0 | Presence penalty |
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| `frequency_penalty` | `float` | 0.0 | Frequency penalty |
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| `stop` | `list[str]` | None | Stop sequences |
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## Model Selection
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### By String
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```python
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agent = Agent(name="gpt4", model="gpt-4o")
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agent = Agent(name="claude", model="claude-3-5-sonnet-20241022")
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```
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### Override at Runtime
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```python
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config = RunConfig(model="gpt-4o-mini")
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result = await Runner.run(agent, "Hello!", run_config=config)
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```
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## Model Providers
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### OpenAI (default)
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```python
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from agents import OpenAIProvider
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provider = OpenAIProvider(
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api_key="sk-...",
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base_url="https://api.openai.com/v1",
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)
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config = RunConfig(model_provider=provider)
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```
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### Hanzo Node
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```python
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from agents import create_hanzo_node_provider
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provider = create_hanzo_node_provider(
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api_key="your-hanzo-key",
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base_url="https://api.hanzo.ai/v1",
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)
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config = RunConfig(model_provider=provider)
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```
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### Custom Provider
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```python
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from agents import ModelProvider, Model
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class MyProvider(ModelProvider):
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def get_model(self, model_name: str) -> Model:
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return MyCustomModel(model_name)
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```
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## Environment Variables
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| Variable | Description |
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|----------|-------------|
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| `OPENAI_API_KEY` | OpenAI API key |
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| `ANTHROPIC_API_KEY` | Anthropic API key |
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| `HANZO_API_KEY` | Hanzo API key |
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## Default Model
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Set a default model for all agents:
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```python
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import agents
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# Set default
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agents.set_default_model("gpt-4o")
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# All agents use gpt-4o unless overridden
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agent = Agent(name="default", instructions="...")
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```
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## Configuration Hierarchy
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Settings are applied in order (later overrides earlier):
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1. Default settings
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2. Agent-level settings (`agent.model_settings`)
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3. RunConfig settings (`config.model_settings`)
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```python
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# Agent settings
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agent = Agent(
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model_settings=ModelSettings(temperature=0.5),
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)
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# RunConfig overrides
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config = RunConfig(
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model_settings=ModelSettings(temperature=0.9),
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)
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# Result uses temperature=0.9
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result = await Runner.run(agent, "Hello!", run_config=config)
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```
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## See Also
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- [Agents](agents.md) - Agent configuration
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- [Models](models.md) - Model details
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- [Running Agents](running_agents.md) - Using RunConfig
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