Implementation Examples

import { generateText, jsonSchema, tool } from "ai";
import { openai } from "@ai-sdk/openai";

const response = await fetch(
  "https://actionkit.useparagon.com/projects/<Project ID>/tools",
  {
    method: "GET",
    headers: {
      Authorization: `Bearer ${paragonUserToken}`,
    },
  }
);

const { tools, errors } = await response.json();

if (errors.length === 0) {
  await generateText({
    model: openai("gpt-4o"),
    tools: Object.fromEntries(
      tools.map((tool) => [
        tool.function.name,
        tool({
          description: tool.function.description,
          parameters: jsonSchema(tool.function.parameters),
          execute: async (params: any, { toolCallId }) => {
            try:
              const response = await fetch(
                `https://actionkit.useparagon.com/projects/<Project ID>/tools`,
                {
                  method: "POST",
                  body: JSON.stringify({
                    tool: tool.function.name,
                    parameters: params,
                  }),
                  headers: {
                    Authorization: `Bearer ${session.paragonUserToken}`,
                    "Content-Type": "application/json",
                  },
                }
              );
              const output = await response.json();
              if (!response.ok) {
                throw new Error(JSON.stringify(output, null, 2));
              }
              return output;
            } catch (err) {
              if (err instanceof Error) {
                return { error: { message: err.message } };
              }
              return err;
            }
          },
        }),
      ])
    ),
    toolChoice: "auto",
    temperature: 0,
    system: "You are a helpful assistant. Be as concise as possible.",
    prompt: "Help me create a new task in Jira.",
  });
}

import json
import requests
from typing import Annotated, Any, TypedDict
from langchain.tools import BaseTool
from langchain.schema import HumanMessage
from langgraph.graph import StateGraph, START, END
from langgraph.graph.message import add_messages
from langgraph.prebuilt import ToolNode, tools_condition
from langchain_openai import ChatOpenAI

PARAGON_PROJECT_ID = ""
PARAGON_USER_TOKEN = ""
OPENAI_API_KEY = ""

class ActionKitTool(BaseTool):
    name: str
    description: str
    tool_name: str
    paragon_token: str

    def _run(self, tool_input: str) -> str:
        try:
            params = json.loads(tool_input)
            response = requests.post(
                url=f"https://actionkit.useparagon.com/projects/{PARAGON_PROJECT_ID}/tools",
                headers={
                    "Authorization": f"Bearer {self.paragon_token}",
                    "Content-Type": "application/json",
                },
                json={
                    "tool": self.tool_name,
                    "parameters": params,
                },
                timeout=30
            )
            data = response.json()

            if not response.ok:
                raise ValueError(json.dumps(data, indent=2))

            return json.dumps(data)
        except Exception as e:
            return json.dumps({"error": {"message": str(e)}})

class State(TypedDict):
    messages: Annotated[list, add_messages]

def main():
    graph_builder = StateGraph(State)
    url = f"https://actionkit.useparagon.com/projects/{PARAGON_PROJECT_ID}/tools"
    headers = {"Authorization": f"Bearer {PARAGON_USER_TOKEN}"}
    
    resp = requests.get(url, headers=headers)
    json_resp = resp.json()
    tools = json_resp.get("tools", [])
    errors = json_resp.get("errors", [])

    if not tools:
        print("Failed to fetch Paragon tools or encountered errors:")
        print(errors)
        return

    tools_list = []
    for integration in tools:
        integration_tools = tools.get(integration)
        for tool in integration_tools:
            func_def = tool["function"]
            tool_name = func_def["name"]
            tool_description = func_def["description"]

            paragon_tool = ActionKitTool(
                name=tool_name,
                description=tool_description,
                tool_name=tool_name,
                paragon_token=PARAGON_USER_TOKEN
            )
            tools_list.append(paragon_tool)

    llm = ChatOpenAI(
        openai_api_key=OPENAI_API_KEY,
        model_name="o1"
    )
    
    def chatbot(state: State):
        return {"messages": [llm.bind_tools(tools_list).invoke(state["messages"])]}
    
    graph_builder.add_node("chatbot", chatbot)
    tools_node = ToolNode(tools=tools_list)
    graph_builder.add_node("tools", tools_node)
    graph_builder.add_conditional_edges(
        "chatbot",
        tools_condition,
    )
    graph_builder.add_edge("tools", "chatbot")
    graph_builder.add_edge(START, "chatbot")

    graph = graph_builder.compile()

    def stream_graph_updates(user_input: str):
        for event in graph.stream({"messages": [{"role": "user", "content": user_input}]}):
            for value in event.values():
                print("Assistant:", value["messages"][-1].content)

    while True:
        try:
            user_input = input("User: ")
            if user_input.lower() in ["quit", "exit", "q"]:
                print("Goodbye!")
                break

            stream_graph_updates(user_input)
        except:
            # fallback if input() is not available
            user_input = "What do you know about LangGraph?"
            print("User: " + user_input)
            stream_graph_updates(user_input)
            break

if __name__ == "__main__":
    main()

import requests
from openai import OpenAI
client = OpenAI()

actions_url = f"https://actionkit.useparagon.com/projects/{project_id}/tools"
actions_auth_header = {
	"Authorization": f"Bearer {user_token}"
}
get_tools_params = {
    "format": "json_schema",
    "categories": "crm,project_management"
}

response = requests.get(actions_url, params=get_tools_params, headers=actions_auth_header)
paragon_tools = response.json()

messages = [{"role": "user", "content": "Help me create a Jira ticket"}]
completion = client.chat.completions.create(
  model="gpt-4o",
  messages=messages,
  tools=paragon_tools["tools"],
  tool_choice="auto"
)

message = completion["choices"][0]["message"]

if message.get("function_call"):
    function_name = message["function_call"]["name"]
    arguments = json.loads(message["function_call"]["arguments"])
    
    # Check if this tool uses ActionKit
    if any(tool["name"] == function_name for tool in paragon_tools["tools"]):
        run_tools_body = {
            "tool": function_name,
            "parameters": arguments
        }

        # Run Tool
        response = requests.post(actions_url, body=run_tools_body, headers=actions_auth_header)
        result = response.json()
        messages.append({
            "role": "function",
            "name": function_name,
            "content": json.dumps(result)
        })

        # Return to chat with tool result
        completion = client.chat.completions.create(
            model="gpt-4o",
            messages=messages,
            tools=paragon_tools,
            tool_choice="auto"
        )