Your First CRAFT Agent

import os
from openai import OpenAI

# Route through CRAFT's LiteLLM gateway using the OpenAI-compatible client.
# LiteLLM serves claude-opus-4-8 (and other models) at the standard
# /v1/chat/completions endpoint — no Anthropic account needed.
client = OpenAI(
    base_url=os.environ["CRAFT_GATEWAY_URL"],
    api_key=os.environ["CRAFT_TOKEN"],
)

def run(prompt: str) -> str:
    response = client.chat.completions.create(
        model="claude-opus-4-8",
        max_tokens=1024,
        messages=[
            {"role": "system", "content": "You are a helpful data assistant. Answer questions about the user's data concisely."},
            {"role": "user", "content": prompt},
        ],
    )
    return response.choices[0].message.content

if __name__ == "__main__":
    print(run("What can you help me with?"))

import os
from pydantic_ai import Agent
from pydantic_ai.models.openai import OpenAIChatModel
from pydantic_ai.providers.openai import OpenAIProvider

# Route through CRAFT's LiteLLM gateway using the OpenAI-compatible provider.
model = OpenAIChatModel(
    "claude-opus-4-8",
    provider=OpenAIProvider(
        base_url=os.environ["CRAFT_GATEWAY_URL"],
        api_key=os.environ["CRAFT_TOKEN"],
    ),
)

agent = Agent(
    model,
    system_prompt="You are a helpful data assistant. Answer questions about the user's data concisely.",
)

result = agent.run_sync("What can you help me with?")
print(result.output)

import os
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
from langchain_core.messages import HumanMessage

# Route through CRAFT's LiteLLM gateway — it's OpenAI-compatible.
llm = ChatOpenAI(
    model="claude-opus-4-8",
    base_url=os.environ["CRAFT_GATEWAY_URL"],
    api_key=os.environ["CRAFT_TOKEN"],
)

agent = create_react_agent(
    model=llm,
    tools=[],  # add tools in Step 2
    prompt="You are a helpful data assistant. Answer questions about the user's data concisely.",
)

result = agent.invoke({"messages": [HumanMessage(content="What can you help me with?")]})
print(result["messages"][-1].content)

import os
import json
import httpx
from openai import OpenAI

# Same CRAFT gateway client as Step 1 — tool calling works over the
# OpenAI-compatible endpoint via LiteLLM's function-calling support.
client = OpenAI(
    base_url=os.environ["CRAFT_GATEWAY_URL"],
    api_key=os.environ["CRAFT_TOKEN"],
)

# ── CRAFT tool definition (OpenAI function-calling format) ──────────────
TOOLS = [
    {
        "type": "function",
        "function": {
            "name": "list_data_connections",
            "description": (
                "List all data connections (databases, data warehouses, APIs) registered "
                "in the current CRAFT project. Call this whenever the user asks what data "
                "is available."
            ),
            "parameters": {"type": "object", "properties": {}, "required": []},
        },
    }
]

def list_data_connections() -> str:
    resp = httpx.get(
        f"{os.environ['CRAFT_ASSETS_URL']}/assets/data",
        headers={
            "Authorization": f"Bearer {os.environ['CRAFT_TOKEN']}",
            "X-Project-ID": os.environ["CRAFT_PROJECT_ID"],
        },
    )
    resp.raise_for_status()
    items = resp.json().get("data", [])
    if not items:
        return "No data connections found in this project."
    return "\n".join(f"- {c['name']} ({c['connection_type']})" for c in items)

TOOL_HANDLERS = {"list_data_connections": list_data_connections}

# ── Agentic loop ────────────────────────────────────────────────────────
def run(prompt: str) -> str:
    messages = [
        {"role": "system", "content": "You are a helpful data assistant. Use your tools to answer questions about available data."},
        {"role": "user", "content": prompt},
    ]
    while True:
        response = client.chat.completions.create(
            model="claude-opus-4-8",
            max_tokens=1024,
            tools=TOOLS,
            messages=messages,
        )
        msg = response.choices[0].message
        messages.append(msg)

        if not msg.tool_calls:
            return msg.content

        # Execute tool calls and feed results back
        results = []
        for tc in msg.tool_calls:
            output = TOOL_HANDLERS[tc.function.name](**json.loads(tc.function.arguments or "{}"))
            results.append({
                "role": "tool",
                "tool_call_id": tc.id,
                "content": output,
            })
        messages.extend(results)

if __name__ == "__main__":
    print(run("What data connections do I have?"))

import os
import httpx
from pydantic_ai import Agent
from pydantic_ai.models.openai import OpenAIChatModel
from pydantic_ai.providers.openai import OpenAIProvider

model = OpenAIChatModel(
    "claude-opus-4-8",
    provider=OpenAIProvider(
        base_url=os.environ["CRAFT_GATEWAY_URL"],
        api_key=os.environ["CRAFT_TOKEN"],
    ),
)

agent = Agent(
    model,
    system_prompt="You are a helpful data assistant. Use your tools to answer questions about available data.",
)

# ── CRAFT tool ─────────────────────────────────────────────────────────
@agent.tool_plain
def list_data_connections() -> str:
    """List all data connections registered in the current CRAFT project."""
    resp = httpx.get(
        f"{os.environ['CRAFT_ASSETS_URL']}/assets/data",
        headers={
            "Authorization": f"Bearer {os.environ['CRAFT_TOKEN']}",
            "X-Project-ID": os.environ["CRAFT_PROJECT_ID"],
        },
    )
    resp.raise_for_status()
    items = resp.json().get("data", [])
    if not items:
        return "No data connections found in this project."
    return "\n".join(f"- {c['name']} ({c['connection_type']})" for c in items)

result = agent.run_sync("What data connections do I have?")
print(result.output)

import os
import httpx
from langchain_openai import ChatOpenAI
from langchain_core.tools import tool
from langchain_core.messages import HumanMessage
from langgraph.prebuilt import create_react_agent

llm = ChatOpenAI(
    model="claude-opus-4-8",
    base_url=os.environ["CRAFT_GATEWAY_URL"],
    api_key=os.environ["CRAFT_TOKEN"],
)

# ── CRAFT tool ─────────────────────────────────────────────────────────
@tool
def list_data_connections() -> str:
    """List all data connections registered in the current CRAFT project.
    Call this whenever the user asks what data sources or databases are available.
    """
    resp = httpx.get(
        f"{os.environ['CRAFT_ASSETS_URL']}/assets/data",
        headers={
            "Authorization": f"Bearer {os.environ['CRAFT_TOKEN']}",
            "X-Project-ID": os.environ["CRAFT_PROJECT_ID"],
        },
    )
    resp.raise_for_status()
    items = resp.json().get("data", [])
    if not items:
        return "No data connections found in this project."
    return "\n".join(f"- {c['name']} ({c['connection_type']})" for c in items)

agent = create_react_agent(
    model=llm,
    tools=[list_data_connections],
    prompt="You are a helpful data assistant. Use your tools to answer questions about available data.",
)

result = agent.invoke({"messages": [HumanMessage(content="What data connections do I have?")]})
print(result["messages"][-1].content)