export function DataCode() { const pythonCode = `""" A LangGraph implementation for the testing agent. """ from fastapi import FastAPI import uvicorn from copilotkit.integrations.fastapi import add_fastapi_endpoint from copilotkit import CopilotKitSDK, LangGraphAgent import os import uuid import json from typing import Dict, List, Any from dotenv import load_dotenv load_dotenv() # LangGraph imports from langchain_core.runnables import RunnableConfig from langgraph.graph import StateGraph, END, START from langgraph.types import Command, interrupt from langgraph.checkpoint.memory import MemorySaver # CopilotKit imports from copilotkit import CopilotKitState from copilotkit.langgraph import copilotkit_customize_config, copilotkit_emit_state, copilotkit_interrupt # LLM imports from langchain_openai import ChatOpenAI from langchain_core.messages import SystemMessage from copilotkit.langgraph import (copilotkit_exit) DEFINE_TEST_SCRIPT_TOOL = { "type": "function", "function": { "name": "generate_test_scripts", "description": "Make up 3 test scripts for a given task based on the context provided. The test scripts should be in the form of a list of steps.", "parameters": { "type": "object", "properties": { "testSuites": { "type": "array", "items": { "type": "object", "properties": { "testId": { "type": "string" }, "prId": { "type": "string" }, "title": { "type": "string" }, "status": { "type": "string", "enum": ["passed", "failed", "yet_to_start"] }, "shortDescription": { "type": "string" }, "testCases": { "type": "array", "items": { "type": "object", "properties": { "id": { "type": "string" }, "name": { "type": "string" }, "status": { "type": "string", "enum": ["passed", "failed", "yet_to_start", "pending"] }, "executionTime": { "type": "string" }, "createdAt": { "type": "string", "format": "date-time" }, "updatedAt": { "type": "string", "format": "date-time" }, "environment": { "type": "string" }, "browser": { "type": "string" }, "device": { "type": "string" }, "testSteps": { "type": "array", "items": { "type": "string" } }, "failureReason": { "type": "string" } }, "required": [ "id", "name", "status", "executionTime", "createdAt", "updatedAt", "environment", "testSteps", ] } }, "totalTestCases": { "type": "number" }, "passedTestCases": { "type": "number" }, "failedTestCases": { "type": "number" }, "skippedTestCases": { "type": "number" }, "coverage": { "type": "number" }, "createdAt": { "type": "string", "format": "date-time" }, "updatedAt": { "type": "string", "format": "date-time" }, "executedBy": { "type": "string" } }, "required": [ "testId", "prId", "title", "status", "shortDescription", "testCases", "totalTestCases", "passedTestCases", "failedTestCases", "skippedTestCases", "coverage", "createdAt", "updatedAt", "executedBy" ] } } }, "required": ["testSuites"] } } } class AgentState(CopilotKitState): """ The state of the agent. It inherits from CopilotKitState which provides the basic fields needed by CopilotKit. """ testScripts: List[Dict[str, str]] = [] async def start_flow(state: Dict[str, Any], config: RunnableConfig): """ This is the entry point for the flow. """ # Initialize steps list if not exists if "testScripts" not in state: state["testScripts"] = [] return Command( goto="chat_node", update={ "messages": state["messages"], "testScripts": state["testScripts"], } ) async def chat_node(state: Dict[str, Any], config: RunnableConfig): """ Standard chat node where the agent processes messages and generates responses. If task steps are defined, the user can enable/disable them using interrupts. """ system_prompt = """ You are a helpful assistant that can perform any task related to software testing and PR validation. You MUST call the \`generate_test_scripts\` function when the user asks you to perform a task. Once generated with the test scripts, provide a summary of it in maximum 5 sentences. Dont list the entire thing in detail. Also prompt user that you can add the script to your testing list. For every agent request, YOU MUST ALWAYS GENERATE 4 DIFFERENT TEST SUITES, each as a separate object in the array. Each test suite should be relevant to the context which is the CopilotKitReadables or PR provided by the user, and should have unique test cases and details. All the data which involves the user emails should be referred from the CopilotKitReadables. The test suite object you work with has the following structure (all fields are required unless marked optional): - testId: string - prId: string - title: string - status: 'passed' | 'failed' | 'yet_to_start' - shortDescription: string (a concise summary of what this test suite covers) - testCases: array of objects, each with: - id: string - name: string - status: 'passed' | 'failed' | 'yet_to_start' | 'pending' - executionTime: string - createdAt: string (date-time) - updatedAt: string (date-time) - environment: string - browser?: string - device?: string - testSteps: array of strings - failureReason?: string - totalTestCases: number - passedTestCases: number - failedTestCases: number - skippedTestCases: number - coverage: number - createdAt: string (date-time) - updatedAt: string (date-time) - executedBy: string When generating or reasoning about test scripts, always use this schema and ensure your output is relevant to the PR and test context provided by the user. """ # Define the model model = ChatOpenAI(model="gpt-4o-mini") # Define config for the model if config is None: config = RunnableConfig(recursion_limit=25) # Use CopilotKit's custom config functions to properly set up streaming for the steps state config = copilotkit_customize_config( config, emit_intermediate_state=[{ "state_key": "testScripts", "tool": "generate_test_scripts" }], ) # Bind the tools to the model model_with_tools = model.bind_tools( [ *state["copilotkit"]["actions"], DEFINE_TEST_SCRIPT_TOOL ], # Disable parallel tool calls to avoid race conditions parallel_tool_calls=False, ) # Run the model and generate a response response = await model_with_tools.ainvoke([ SystemMessage(content=system_prompt), *state["messages"], ], config) # Update messages with the response messages = state["messages"] + [response] # Handle tool calls if hasattr(response, "tool_calls") and response.tool_calls and len(response.tool_calls) > 0: tool_call = response.tool_calls[0] # Extract tool call information tool_call_id = "" if hasattr(tool_call, "id"): tool_call_id = tool_call.id tool_call_name = tool_call.name tool_call_args = tool_call.args if not isinstance(tool_call.args, str) else json.loads(tool_call.args) else: tool_call_id = tool_call.get("id", "") tool_call_name = tool_call.get("name", "") args = tool_call.get("args", {}) tool_call_args = args if not isinstance(args, str) else json.loads(args) if tool_call_name == "generate_test_scripts": # Get the steps from the tool call state["testScripts"] = tool_call_args print(tool_call_args, "tool_call_args") tool_response = { "role": "tool", "content": "Test scripts generated. Allow user to select the test suites they want to run.", "tool_call_id": tool_call_id } messages = messages + [tool_response] await copilotkit_exit(config) return Command( goto=END, update={ "messages": messages, "testScripts": state["testScripts"], } ) # If no tool calls or not generate_task_steps, return to END with the updated messages await copilotkit_exit(config) return Command( goto=END, update={ "messages": messages, "testScripts": state["testScripts"], } ) # Define the graph workflow = StateGraph(AgentState) # Add nodes workflow.add_node("start_flow", start_flow) workflow.add_node("chat_node", chat_node) # Add edges workflow.set_entry_point("start_flow") workflow.add_edge(START, "start_flow") workflow.add_edge("start_flow", "chat_node") workflow.add_edge("chat_node", END) # Removed unconditional edge # Compile the graph testing_graph = workflow.compile(checkpointer=MemorySaver()) app = FastAPI() sdk = CopilotKitSDK( agents=[ LangGraphAgent( name="testing_agent", description="An example for a testing agent.", graph=testing_graph, ) ] ) add_fastapi_endpoint(app, sdk, "/copilotkit") def main(): """Run the uvicorn server.""" port = int(os.getenv("PORT", "8000")) uvicorn.run( "agent:app", host="0.0.0.0", port=port, reload=True, ) if __name__ == "__main__": main()`; return (

Agent Code

Python 
        
          {pythonCode}
); }