Switch Agent Frameworks

Create Context Graph supports 8 agent frameworks. The framework choice only affects backend/app/agent.py in the generated project -- everything else (FastAPI backend, Neo4j client, frontend, data) stays the same.

Supported Frameworks

Framework	Key	Description	Streaming
PydanticAI	pydanticai	Type-safe agents with @agent.tool decorators and dependency injection via RunContext	Full
Claude Agent SDK	claude-agent-sdk	Anthropic's SDK with dict-based tool definitions and an agentic while loop	Full
OpenAI Agents SDK	openai-agents	OpenAI's agent framework with @function_tool decorators and Runner.run()	Full
LangGraph	langgraph	LangChain's graph-based agent runtime with @tool and create_react_agent()	Full
CrewAI	crewai	Multi-agent framework with Agent, Task, and Crew abstractions	Tools only
Strands	strands	AWS-native agent framework using Bedrock models with @tool decorators	Tools only
Google ADK	google-adk	Google's Agent Development Kit with FunctionTool and Gemini models	Full
Anthropic Tools	anthropic-tools	Modular agent framework with @register_tool registry and Anthropic API agentic loop	Full

Streaming column: "Full" means token-by-token text streaming + real-time tool call events. "Tools only" means tool call events stream in real-time, but the text response arrives all at once after the agent finishes. All frameworks use the same SSE (Server-Sent Events) protocol.

Choosing a Framework During Scaffolding

Interactive wizard

Run the CLI and select your framework at the relevant step:

create-context-graph my-app

CLI flag

create-context-graph my-app --domain healthcare --framework langgraph

Generating with a Different Framework

To create a second project with a different framework, re-run the CLI with a new output directory and --framework flag:

create-context-graph my-app-v2 --domain healthcare --framework crewai

The two projects will share the same schema, data, and frontend -- only agent.py and the agent-specific dependencies differ.

What Changes

Only one file varies between frameworks: backend/app/agent.py. This file contains:

• The agent initialization and model configuration
• Tool definitions generated from your domain's agent_tools ontology
• The handle_message() async function that the FastAPI routes call
• (For full-streaming frameworks) The handle_message_stream() async function for SSE text streaming

Each framework template uses the framework's idiomatic patterns (decorators, classes, registries) but exposes the same interface.

What Stays the Same

Regardless of which framework you choose, the generated project always includes:

• FastAPI backend (main.py, config.py, routes.py, models.py) -- identical across frameworks
• Neo4j clients (context_graph_client.py, gds_client.py, vector_client.py) -- shared graph access layer
• Frontend (Next.js + Chakra UI v3 + NVL graph visualization) -- framework-agnostic
• Data and schema (cypher/schema.cypher, fixture data, ontology YAML)
• Infrastructure (docker-compose.yml, Makefile, .env)

Framework-Specific Dependencies

The generated backend/pyproject.toml includes only the dependencies needed for the chosen framework. For example:

• pydanticai adds pydantic-ai
• langgraph adds langgraph, langchain-core, langchain-anthropic
• strands adds strands-agents, strands-agents-builder, and configures Bedrock
• google-adk adds google-adk, google-generativeai

All frameworks share common dependencies: fastapi, uvicorn, neo4j, pydantic, and python-dotenv.