LLM Providers

AgentNode picks a model backend via the ModelProvider enum in app/launchpad/core/nodes/agent.py. Switching providers is a one-line change in the node’s get_agent_config(); credentials come from environment variables loaded by python-dotenv at import time.

from launchpad.core.nodes.agent import AgentConfig, ModelProvider

class MyNode(AgentNode):
    def get_agent_config(self) -> AgentConfig:
        return AgentConfig(
            model_provider=ModelProvider.OPENAI,
            model_name="gpt-5.4-mini",
            output_type=self.OutputType,
        )

All providers are reached through pydantic-ai. AgentConfig.instrument=True (the default) wires each call into Langfuse when enable_tracing=True on the workflow.

Supported providers

OpenAI — `ModelProvider.OPENAI`

Uses OpenAIResponsesModel. Good default for new workflows.

Env var	Purpose
`OPENAI_API_KEY`	Standard OpenAI API key.

AgentConfig(model_provider=ModelProvider.OPENAI, model_name="gpt-5.4-mini")

Azure OpenAI — `ModelProvider.AZURE_OPENAI`

Routes through pydantic-ai’s AzureProvider with OpenAIResponsesModel.

Env var	Purpose
`AZURE_OPENAI_ENDPOINT`	Azure resource endpoint.
`AZURE_OPENAI_API_KEY`	Resource API key.
`AZURE_OPENAI_API_VERSION`	API version (defaults to `2025-04-01-preview`).

Set model_name to the Azure deployment name you want to call.

AgentConfig(model_provider=ModelProvider.AZURE_OPENAI, model_name="gpt-5-mini")

Anthropic — `ModelProvider.ANTHROPIC`

Env var	Purpose
`ANTHROPIC_API_KEY`	Anthropic API key.

AgentConfig(model_provider=ModelProvider.ANTHROPIC, model_name="claude-sonnet-4-6")

Google Gemini — `ModelProvider.GOOGLE_GEMINI`

Uses GoogleModel with the standard GoogleProvider (API-key auth).

Env var	Purpose
`GOOGLE_API_KEY`	Gemini API key.

AgentConfig(model_provider=ModelProvider.GOOGLE_GEMINI, model_name="gemini-2.5-pro")

Google Vertex AI — `ModelProvider.GOOGLE_VERTEX_AI`

Uses a service account to authenticate against Vertex AI.

Env var	Purpose
`GOOGLE_APPLICATION_CREDENTIALS`	Absolute path to a service account JSON file.
`GOOGLE_VERTEX_AI_LOCATION`	Region (defaults to `europe-west1`).

AgentConfig(model_provider=ModelProvider.GOOGLE_VERTEX_AI, model_name="gemini-2.5-pro")

AWS Bedrock — `ModelProvider.BEDROCK`

Creates a boto3 bedrock-runtime client and passes it to BedrockConverseModel.

Env var	Purpose
`BEDROCK_AWS_ACCESS_KEY_ID`	AWS access key.
`BEDROCK_AWS_SECRET_ACCESS_KEY`	AWS secret.
`BEDROCK_AWS_REGION`	AWS region hosting the model.

AgentConfig(
    model_provider=ModelProvider.BEDROCK,
    model_name="anthropic.claude-sonnet-4-6-v1:0",
)

Ollama — `ModelProvider.OLLAMA`

Uses OpenAIChatModel with the pydantic-ai OllamaProvider. Ideal for local development against an ollama serve instance.

Env var	Purpose
`OLLAMA_BASE_URL`	Full base URL, e.g. `http://localhost:11434/v1`. Required; the node raises `KeyError` otherwise.

AgentConfig(model_provider=ModelProvider.OLLAMA, model_name="llama3.2")

Other AgentConfig knobs

AgentConfig forwards common pydantic-ai fields so most tuning happens in one place:

instructions — static system prompt (can be augmented with @self.agent.instructions for per-run context).
output_type — return a plain str or a BaseModel subclass for structured output.
deps_type — a Pydantic model containing dependencies exposed via RunContext inside tools and instruction callbacks.
tools, builtin_tools — pydantic-ai tool definitions.
model_settings — a ModelSettings object to override temperature, max tokens, etc.
retries, output_retries — retry behavior on model errors and validation failures.
instrument — defaults to True; set to False to opt a node out of Langfuse instrumentation even when the workflow has tracing enabled.

Welcome

Getting Started

Quickstart

Framework & Tools

Core Package

Supported providers

OpenAI — `ModelProvider.OPENAI`

Azure OpenAI — `ModelProvider.AZURE_OPENAI`

Anthropic — `ModelProvider.ANTHROPIC`

Google Gemini — `ModelProvider.GOOGLE_GEMINI`

Google Vertex AI — `ModelProvider.GOOGLE_VERTEX_AI`

AWS Bedrock — `ModelProvider.BEDROCK`

Ollama — `ModelProvider.OLLAMA`

Other AgentConfig knobs

​Supported providers

​OpenAI — ModelProvider.OPENAI

​Azure OpenAI — ModelProvider.AZURE_OPENAI

​Anthropic — ModelProvider.ANTHROPIC

​Google Gemini — ModelProvider.GOOGLE_GEMINI

​Google Vertex AI — ModelProvider.GOOGLE_VERTEX_AI

​AWS Bedrock — ModelProvider.BEDROCK

​Ollama — ModelProvider.OLLAMA

​Other AgentConfig knobs

Supported providers

OpenAI — `ModelProvider.OPENAI`

Azure OpenAI — `ModelProvider.AZURE_OPENAI`

Anthropic — `ModelProvider.ANTHROPIC`

Google Gemini — `ModelProvider.GOOGLE_GEMINI`

Google Vertex AI — `ModelProvider.GOOGLE_VERTEX_AI`

AWS Bedrock — `ModelProvider.BEDROCK`

Ollama — `ModelProvider.OLLAMA`

Other AgentConfig knobs