mirror of https://github.com/kortix-ai/suna.git
300 lines
13 KiB
Python
300 lines
13 KiB
Python
import json
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from uuid import uuid4
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from typing import Optional
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from agent.tools.message_tool import MessageTool
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from agent.tools.sb_deploy_tool import SandboxDeployTool
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from agent.tools.web_search_tool import WebSearchTool
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from dotenv import load_dotenv
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from agentpress.thread_manager import ThreadManager
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from agentpress.response_processor import ProcessorConfig
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from agent.tools.sb_shell_tool import SandboxShellTool
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from agent.tools.sb_files_tool import SandboxFilesTool
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from agent.prompt import get_system_prompt
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from sandbox.sandbox import daytona, create_sandbox, get_or_start_sandbox
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load_dotenv()
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async def run_agent(thread_id: str, project_id: str, stream: bool = True, thread_manager: Optional[ThreadManager] = None, native_max_auto_continues: int = 25, max_iterations: int = 150):
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"""Run the development agent with specified configuration."""
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if not thread_manager:
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thread_manager = ThreadManager()
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client = await thread_manager.db.client
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## probably want to move to api.py
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project = await client.table('projects').select('*').eq('project_id', project_id).execute()
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if project.data and project.data[0]['sandbox_id'] is not None:
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sandbox_id = project.data[0]['sandbox_id']
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sandbox_pass = project.data[0]['sandbox_pass']
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sandbox = await get_or_start_sandbox(sandbox_id)
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else:
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sandbox_pass = str(uuid4())
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sandbox = create_sandbox(sandbox_pass)
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sandbox_id = sandbox.id
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await client.table('projects').update({
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'sandbox_id': sandbox_id,
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'sandbox_pass': sandbox_pass
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}).eq('project_id', project_id).execute()
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thread_manager.add_tool(SandboxShellTool, sandbox_id=sandbox_id, password=sandbox_pass)
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thread_manager.add_tool(SandboxFilesTool, sandbox_id=sandbox_id, password=sandbox_pass)
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thread_manager.add_tool(WebSearchTool)
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thread_manager.add_tool(MessageTool)
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thread_manager.add_tool(SandboxDeployTool, sandbox_id=sandbox_id, password=sandbox_pass)
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system_message = { "role": "system", "content": get_system_prompt() }
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model_name = "anthropic/claude-3-7-sonnet-latest"
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# model_name = "groq/llama-3.3-70b-versatile"
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# model_name = "openrouter/qwen/qwen2.5-vl-72b-instruct"
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# model_name = "bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0"
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# model_name = "anthropic/claude-3-5-sonnet-latest"
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# model_name = "anthropic/claude-3-7-sonnet-latest"
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# model_name = "openai/gpt-4o"
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# model_name = "groq/deepseek-r1-distill-llama-70b"
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# model_name = "bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0"
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# model_name = "bedrock/anthropic.claude-3-7-sonnet-20250219-v1:0"
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# model_name = "bedrock/us.anthropic.claude-3-7-sonnet-20250219-v1:0"
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iteration_count = 0
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continue_execution = True
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while continue_execution and iteration_count < max_iterations:
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iteration_count += 1
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print(f"Running iteration {iteration_count}...")
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# Check if last message is from assistant using direct Supabase query
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latest_message = await client.table('messages').select('*').eq('thread_id', thread_id).order('created_at', desc=True).limit(1).execute()
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if latest_message.data and len(latest_message.data) > 0:
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message_type = latest_message.data[0].get('type')
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if message_type == 'assistant':
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print(f"Last message was from assistant, stopping execution")
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continue_execution = False
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break
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# files_tool = SandboxFilesTool(sandbox_id=sandbox_id, password=sandbox_pass)
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# files_state = await files_tool.get_workspace_state()
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# # Simple string representation
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# state_str = str(files_state)
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# state_message = {
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# "role": "user",
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# "content": f"""
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# Current workspace state:
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# <current_workspace_state>
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# {state_str}
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# </current_workspace_state>
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# """
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# }
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# print(f"State message: {state_message}")
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response = await thread_manager.run_thread(
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thread_id=thread_id,
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system_prompt=system_message,
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stream=stream,
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# temporary_message=state_message,
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llm_model=model_name,
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llm_temperature=0,
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# llm_max_tokens=64000,
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llm_max_tokens=32768,
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tool_choice="auto",
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max_xml_tool_calls=1,
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processor_config=ProcessorConfig(
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xml_tool_calling=True,
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native_tool_calling=False,
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execute_tools=True,
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execute_on_stream=True,
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tool_execution_strategy="parallel",
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xml_adding_strategy="user_message"
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),
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native_max_auto_continues=native_max_auto_continues,
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include_xml_examples=True,
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)
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if isinstance(response, dict) and "status" in response and response["status"] == "error":
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yield response
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break
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# Track if we see ask or complete tool calls
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last_tool_call = None
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async for chunk in response:
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# Check if this is a tool call chunk for ask or complete
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if chunk.get('type') == 'tool_call':
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tool_call = chunk.get('tool_call', {})
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function_name = tool_call.get('function', {}).get('name', '')
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if function_name in ['ask', 'complete']:
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last_tool_call = function_name
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# Check for XML versions like <ask> or <complete> in content chunks
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elif chunk.get('type') == 'content' and 'content' in chunk:
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content = chunk.get('content', '')
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if '</ask>' in content or '</complete>' in content:
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xml_tool = 'ask' if '</ask>' in content else 'complete'
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last_tool_call = xml_tool
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print(f"Agent used XML tool: {xml_tool}")
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yield chunk
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# Check if we should stop based on the last tool call
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if last_tool_call in ['ask', 'complete']:
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print(f"Agent decided to stop with tool: {last_tool_call}")
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continue_execution = False
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# TESTING
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async def test_agent():
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"""Test function to run the agent with a sample query"""
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from agentpress.thread_manager import ThreadManager
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from services.supabase import DBConnection
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# Initialize ThreadManager
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thread_manager = ThreadManager()
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# Create a test thread directly with Postgres function
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client = await DBConnection().client
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try:
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project_result = await client.table('projects').select('*').eq('name', 'test11').eq('user_id', '68e1da55-0749-49db-937a-ff56bf0269a0').execute()
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if project_result.data and len(project_result.data) > 0:
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# Use existing test project
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project_id = project_result.data[0]['project_id']
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print(f"\n🔄 Using existing test project: {project_id}")
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else:
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# Create new test project if none exists
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project_result = await client.table('projects').insert({"name": "test11", "user_id": "68e1da55-0749-49db-937a-ff56bf0269a0"}).execute()
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project_id = project_result.data[0]['project_id']
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print(f"\n✨ Created new test project: {project_id}")
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thread_result = await client.table('threads').insert({'project_id': project_id}).execute()
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thread_data = thread_result.data[0] if thread_result.data else None
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if not thread_data:
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print("Error: No thread data returned")
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return
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thread_id = thread_data['thread_id']
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except Exception as e:
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print(f"Error setting up thread: {str(e)}")
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return
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print(f"\n🤖 Agent Thread Created: {thread_id}\n")
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# Interactive message input loop
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while True:
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# Get user input
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user_message = input("\n💬 Enter your message (or 'exit' to quit): ")
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if user_message.lower() == 'exit':
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break
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if not user_message.strip():
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print("\n🔄 Running agent...\n")
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await process_agent_response(thread_id, project_id, thread_manager)
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continue
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# Add the user message to the thread
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await thread_manager.add_message(
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thread_id=thread_id,
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type="user",
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content={
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"role": "user",
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"content": user_message
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},
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is_llm_message=True
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)
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print("\n🔄 Running agent...\n")
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await process_agent_response(thread_id, project_id, thread_manager)
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print("\n👋 Test completed. Goodbye!")
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async def process_agent_response(thread_id: str, project_id: str, thread_manager: ThreadManager):
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"""Process the streaming response from the agent."""
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chunk_counter = 0
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current_response = ""
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tool_call_counter = 0 # Track number of tool calls
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async for chunk in run_agent(thread_id=thread_id, project_id=project_id, stream=True, thread_manager=thread_manager, native_max_auto_continues=25):
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chunk_counter += 1
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if chunk.get('type') == 'content' and 'content' in chunk:
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current_response += chunk.get('content', '')
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# Print the response as it comes in
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print(chunk.get('content', ''), end='', flush=True)
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elif chunk.get('type') == 'tool_result':
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# Add timestamp and format tool result nicely
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tool_name = chunk.get('function_name', 'Tool')
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result = chunk.get('result', '')
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print(f"\n\n🛠️ TOOL RESULT [{tool_name}] → {result}")
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elif chunk.get('type') == 'tool_call':
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# Display native tool call chunks as they arrive
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tool_call = chunk.get('tool_call', {})
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# Check if it's a meaningful part of the tool call to display
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args = tool_call.get('function', {}).get('arguments', '')
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# Only show when we have substantial arguments or a function name
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should_display = (
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len(args) > 3 or # More than just '{}'
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tool_call.get('function', {}).get('name') # Or we have a name
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)
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if should_display:
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tool_call_counter += 1
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tool_name = tool_call.get('function', {}).get('name', 'Building...')
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# Print tool call header with counter and tool name
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print(f"\n🔧 TOOL CALL #{tool_call_counter} [{tool_name}]")
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# Try to parse and pretty print the arguments if they're JSON
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try:
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# Check if it's complete JSON or just a fragment
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if args.strip().startswith('{') and args.strip().endswith('}'):
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args_obj = json.loads(args)
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# Only print non-empty args to reduce clutter
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if args_obj and args_obj != {}:
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# Format JSON with nice indentation and color indicators for readability
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print(f" ARGS: {json.dumps(args_obj, indent=2)}")
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else:
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# Only print if there's actual content to show
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if args.strip():
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print(f" ARGS: {args}")
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except json.JSONDecodeError:
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if args.strip():
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print(f" ARGS: {args}")
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# Add a separator for visual clarity
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print(" " + "-" * 40)
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# Return to the current content display
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if current_response:
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print("\nContinuing response:", flush=True)
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print(current_response, end='', flush=True)
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elif chunk.get('type') == 'tool_status':
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# Log tool status changes
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status = chunk.get('status', '')
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function_name = chunk.get('function_name', '')
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if status and function_name:
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status_emoji = "✅" if status == "completed" else "⏳" if status == "started" else "❌"
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print(f"\n{status_emoji} TOOL {status.upper()}: {function_name}")
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elif chunk.get('type') == 'finish':
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# Just log finish reason to console but don't show to user
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finish_reason = chunk.get('finish_reason', '')
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if finish_reason:
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print(f"\n📌 Finished: {finish_reason}")
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print(f"\n\n✅ Agent run completed with {tool_call_counter} tool calls")
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if __name__ == "__main__":
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import asyncio
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# Configure any environment variables or setup needed for testing
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load_dotenv() # Ensure environment variables are loaded
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# Run the test function
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asyncio.run(test_agent()) |