LlamaIndex

pip install llama-index-core llama-index-llms-openai-like

import os

from llama_index.llms.openai_like import OpenAILike

llm = OpenAILike(
    model="auto",                              # or any Mesh catalog id
    api_base="https://api.meshapi.ai/v1",
    api_key=os.environ["MESH_API_KEY"],        # rsk_...
    is_chat_model=True,
    is_function_calling_model=True,
)

from llama_index.core.llms import ChatMessage
from llama_index.core.tools import FunctionTool


def get_shipment_status(order_id: str) -> dict:
    """Look up the shipment status of an order."""
    book = {"A-1042": {"state": "in transit", "eta_days": 2}}
    if order_id in book:
        return {"status": "success", "order_id": order_id, **book[order_id]}
    return {"status": "error", "error_message": f"No order {order_id}."}


tool = FunctionTool.from_defaults(fn=get_shipment_status)

messages = [ChatMessage(role="user", content="What's the shipment status of order A-1042?")]
response = llm.chat_with_tools([tool], chat_history=messages)

messages.append(response.message)
for call in llm.get_tool_calls_from_response(response, error_on_no_tool_call=False):
    output = get_shipment_status(**call.tool_kwargs)
    messages.append(
        ChatMessage(
            role="tool",
            content=str(output),
            additional_kwargs={"tool_call_id": call.tool_id, "name": call.tool_name},
        )
    )

final = llm.chat(messages)
print(final.message.content)