202 lines
8.6 KiB
Python
202 lines
8.6 KiB
Python
import asyncio
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import json
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import argparse
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from openai import AsyncOpenAI
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from openai.types.chat import ChatCompletionMessageToolCall
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from autoagent.flow import default_drive, EventInput, ReturnBehavior
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from autoagent.flow.dynamic import goto_events, abort_this
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import re
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from autoagent import MetaChain
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from autoagent.types import Response
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from autoagent.registry import register_workflow
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def extract_answer(response: str, key: str):
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pattern = f"<{key}>(.*?)</{key}>"
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matches = re.findall(pattern, response)
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return matches[0] if len(matches) > 0 else None
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from autoagent.agents import get_math_solver_agent
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from autoagent.agents import get_vote_aggregator_agent
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@default_drive.make_event
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async def on_start(event: EventInput, global_ctx):
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print("start the workflow:" + 'math_solver_workflow')
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@default_drive.listen_group([on_start])
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async def solve_with_gpt4(event: EventInput, global_ctx):
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inputs = [{'key': 'math_problem', 'description': 'The math problem that needs to be solved.'}]
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input_dict = dict()
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for inp in inputs:
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input_dict[inp["key"]] = global_ctx.get(inp["key"], None)
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messages = global_ctx.get('messages', [])
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task = 'Solve the math problem using systematic approach and show detailed steps.'
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outputs = [{'key': 'gpt4_solution', 'description': 'The solution generated by GPT-4 model.', 'condition': None, 'action': {'type': 'RESULT', 'value': None}}]
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agent = get_math_solver_agent('gpt-4o-2024-08-06')
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input_str = []
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for key, value in input_dict.items():
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input_str.append(f"The {key.replace('_', ' ')} is {value}")
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input_str = "\n".join(input_str) + "\n"
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query = input_str + '.\nThe task is: ' + task + '.\n'
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messages.append({
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"role": "user",
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"content": query
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})
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client = MetaChain()
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response: Response = await client.run_async(agent = agent, messages = messages, context_variables = global_ctx, debug = True)
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result = response.messages[-1]["content"]
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messages.extend(response.messages)
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global_ctx["messages"] = messages
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for output in outputs:
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ans = extract_answer(result, output["key"])
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if ans:
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if output["action"]["type"] == "RESULT":
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global_ctx[output["key"]] = ans
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return ans
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elif output["action"]["type"] == "ABORT":
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return abort_this()
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elif output["action"]["type"] == "GO_TO":
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return goto_events([output["action"]["value"]])
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elif len(outputs) == 1:
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global_ctx[output["key"]] = result
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return result
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raise Exception("No valid answer found")
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@default_drive.listen_group([on_start])
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async def solve_with_claude(event: EventInput, global_ctx):
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inputs = [{'key': 'math_problem', 'description': 'The math problem that needs to be solved.'}]
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input_dict = dict()
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for inp in inputs:
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input_dict[inp["key"]] = global_ctx.get(inp["key"], None)
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messages = global_ctx.get('messages', [])
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task = 'Solve the math problem using systematic approach and show detailed steps.'
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outputs = [{'key': 'claude_solution', 'description': 'The solution generated by Claude model.', 'condition': None, 'action': {'type': 'RESULT', 'value': None}}]
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agent = get_math_solver_agent('claude-3-5-sonnet-20241022')
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input_str = []
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for key, value in input_dict.items():
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input_str.append(f"The {key.replace('_', ' ')} is {value}")
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input_str = "\n".join(input_str) + "\n"
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query = input_str + '.\nThe task is: ' + task + '.\n'
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messages.append({
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"role": "user",
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"content": query
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})
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client = MetaChain()
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response: Response = await client.run_async(agent = agent, messages = messages, context_variables = global_ctx, debug = True)
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result = response.messages[-1]["content"]
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messages.extend(response.messages)
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global_ctx["messages"] = messages
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for output in outputs:
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ans = extract_answer(result, output["key"])
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if ans:
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if output["action"]["type"] == "RESULT":
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global_ctx[output["key"]] = ans
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return ans
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elif output["action"]["type"] == "ABORT":
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return abort_this()
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elif output["action"]["type"] == "GO_TO":
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return goto_events([output["action"]["value"]])
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elif len(outputs) == 1:
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global_ctx[output["key"]] = result
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return result
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raise Exception("No valid answer found")
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@default_drive.listen_group([on_start])
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async def solve_with_deepseek(event: EventInput, global_ctx):
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inputs = [{'key': 'math_problem', 'description': 'The math problem that needs to be solved.'}]
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input_dict = dict()
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for inp in inputs:
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input_dict[inp["key"]] = global_ctx.get(inp["key"], None)
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messages = global_ctx.get('messages', [])
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task = 'Solve the math problem using systematic approach and show detailed steps.'
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outputs = [{'key': 'deepseek_solution', 'description': 'The solution generated by Deepseek model.', 'condition': None, 'action': {'type': 'RESULT', 'value': None}}]
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agent = get_math_solver_agent('deepseek/deepseek-chat')
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input_str = []
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for key, value in input_dict.items():
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input_str.append(f"The {key.replace('_', ' ')} is {value}")
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input_str = "\n".join(input_str) + "\n"
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query = input_str + '.\nThe task is: ' + task + '.\n'
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messages.append({
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"role": "user",
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"content": query
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})
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client = MetaChain()
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response: Response = await client.run_async(agent = agent, messages = messages, context_variables = global_ctx, debug = True)
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result = response.messages[-1]["content"]
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messages.extend(response.messages)
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global_ctx["messages"] = messages
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for output in outputs:
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ans = extract_answer(result, output["key"])
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if ans:
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if output["action"]["type"] == "RESULT":
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global_ctx[output["key"]] = ans
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return ans
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elif output["action"]["type"] == "ABORT":
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return abort_this()
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elif output["action"]["type"] == "GO_TO":
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return goto_events([output["action"]["value"]])
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elif len(outputs) == 1:
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global_ctx[output["key"]] = result
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return result
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raise Exception("No valid answer found")
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@default_drive.listen_group([solve_with_gpt4, solve_with_claude, solve_with_deepseek])
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async def aggregate_solutions(event: EventInput, global_ctx):
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inputs = [{'key': 'gpt4_solution', 'description': 'The solution generated by GPT-4 model.'}, {'key': 'claude_solution', 'description': 'The solution generated by Claude model.'}, {'key': 'deepseek_solution', 'description': 'The solution generated by Deepseek model.'}]
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input_dict = dict()
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for inp in inputs:
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input_dict[inp["key"]] = global_ctx.get(inp["key"], None)
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messages = global_ctx.get('messages', [])
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task = 'Compare all solutions and determine the final answer through majority voting.'
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outputs = [{'key': 'final_solution', 'description': 'The final agreed-upon solution after majority voting.', 'condition': None, 'action': {'type': 'RESULT', 'value': None}}]
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agent = get_vote_aggregator_agent('gpt-4o-2024-08-06')
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input_str = []
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for key, value in input_dict.items():
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input_str.append(f"The {key.replace('_', ' ')} is {value}")
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input_str = "\n".join(input_str) + "\n"
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query = input_str + '.\nThe task is: ' + task + '.\n'
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messages.append({
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"role": "user",
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"content": query
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})
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client = MetaChain()
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response: Response = await client.run_async(agent = agent, messages = messages, context_variables = global_ctx, debug = True)
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result = response.messages[-1]["content"]
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messages.extend(response.messages)
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global_ctx["messages"] = messages
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for output in outputs:
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ans = extract_answer(result, output["key"])
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if ans:
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if output["action"]["type"] == "RESULT":
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global_ctx[output["key"]] = ans
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return ans
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elif output["action"]["type"] == "ABORT":
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return abort_this()
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elif output["action"]["type"] == "GO_TO":
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return goto_events([output["action"]["value"]])
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elif len(outputs) == 1:
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global_ctx[output["key"]] = result
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return result
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raise Exception("No valid answer found")
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@register_workflow(name = 'majority_voting')
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async def majority_voting(system_input: str):
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storage_results = dict(math_problem = system_input)
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await default_drive.invoke_event(
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on_start,
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global_ctx=storage_results,
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)
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system_output = storage_results.get('final_solution', None)
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return system_output
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