mirror of
https://github.com/FoundationAgents/MetaGPT.git
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update code
This commit is contained in:
stellahsr
parent
4bb69f4503
commit
dd99839836
8 changed files with 124 additions and 136 deletions
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@ -21,11 +21,11 @@ class DesignTask(Action):
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Action class for decomposing a task.
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Refer to the code in the voyager/agents/curriculum.py for implementation details.
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"""
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def __init__(self, name="", context=None, llm=None):
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super().__init__(name, context, llm)
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self.llm.model = "gpt-3.5-turbo"
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async def decompose_task(self, query, events):
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system_msgs = SystemMessage(
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content=load_prompt("curriculum_task_decomposition")
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@ -34,11 +34,11 @@ class DesignTask(Action):
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events=events, chest_observation=""
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) + HumanMessage(content=f"Final task: {query}")
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logger.info(f"Curriculum Agent task decomposition\nFinal task: {query}")
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rsp = await self._aask(prompt=prompt, system_msgs=system_msgs)
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logger.info(f"Curriculum Agent task decomposition\n{rsp}")
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return fix_and_parse_json(rsp)
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def parse_llm_response(self, llm_resp):
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task = ""
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for line in llm_resp.split("\n"):
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@ -46,14 +46,14 @@ class DesignTask(Action):
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task = line[5:].replace(".", "").strip()
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assert task, "Task not found in Curriculum Agent response"
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return {"next_task": task}
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async def generate_task(self, human_msg, system_msg, max_retries=5):
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"""
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Refer to the code in the voyager/agents/curriculum.py propose_next_ai_task() for implementation details.
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Returns: task & context
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"""
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if max_retries == 0:
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raise RuntimeError("Max retries reached, failed to propose task.")
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curriculum = await self._aask(prompt=human_msg, system_msgs=system_msg)
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@ -72,14 +72,14 @@ class DesignTask(Action):
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system_msg=system_msg,
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max_retries=max_retries - 1,
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)
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async def run(self, human_msg, system_msg, *args, **kwargs):
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logger.info(f"run {self.__repr__()}")
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# Call the language model to generate a response.
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task = await self.generate_task(human_msg=human_msg, system_msg=system_msg)
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return task
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@ -88,11 +88,11 @@ class DesignCurriculum(Action):
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Action class for designing curriculum-related questions.
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Refer to the code in the voyager/agents/curriculum.py for implementation details.
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"""
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def __init__(self, name="", context=None, llm=None):
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super().__init__(name, context, llm)
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async def generate_qa(self, events, human_msg, system_msg):
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async def generate_qa(self, events, qa_cache, human_msg, system_msg):
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"""
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Generate qa for DesignTask's HumanMessage
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"""
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@ -112,19 +112,19 @@ class DesignCurriculum(Action):
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)
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if docs_and_scores and docs_and_scores[0][1] < 0.05:
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question_cached = docs_and_scores[0][0].page_content
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assert question_cached in self.qa_cache
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answer_cached = self.qa_cache[question_cached]
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assert question_cached in qa_cache
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answer_cached = qa_cache[question_cached]
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questions.append(question_cached)
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answers.append(answer_cached)
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continue
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answer = await self.generate_qa_step2(question=question)
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assert question not in self.qa_cache
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self.qa_cache[question] = answer
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assert question not in qa_cache
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qa_cache[question] = answer
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self.qa_cache_questions_vectordb.add_texts(
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texts=[question],
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)
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with open(f"{CKPT_DIR}/curriculum/qa_cache.json", "w") as f:
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json.dump(self.qa_cache, f)
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json.dump(qa_cache, f)
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self.qa_cache_questions_vectordb.persist()
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questions.append(question)
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answers.append(answer)
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@ -132,7 +132,7 @@ class DesignCurriculum(Action):
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logger.info(f"Curriculum Agent generate_qa Questions: {questions}")
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logger.info(f"Curriculum Agent generate_qa Answers: {answers}")
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return questions, answers
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async def generate_qa_step1(self, events, human_msg, system_msg):
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biome = events[-1][1]["status"]["biome"].replace("_", " ")
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questions = [
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@ -141,7 +141,7 @@ class DesignCurriculum(Action):
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f"What are the mobs that I can find in the {biome} in Minecraft?",
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]
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qa_response = await self._aask(prompt=human_msg, system_msgs=system_msg)
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try:
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# Regex pattern to extract question and concept pairs
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pattern = r"Question \d+: (.+)\nConcept \d+: (.+)"
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@ -156,7 +156,7 @@ class DesignCurriculum(Action):
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f"QA step 1 ask questions: {e}."
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)
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return questions
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async def generate_qa_step2(self, question):
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# Implement the logic for another specific step in generating questions and answers.
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# logger.info(f"Curriculum Agent generate_qa_step2 Question: {question}")
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@ -169,58 +169,59 @@ class DesignCurriculum(Action):
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answer = await self._aask(prompt=human_msg, system_msgs=system_msg)
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# logger.info(f"Curriculum Agent generate_qa_step2 answer: {answer}")
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return answer
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async def get_context_from_task(self, task):
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async def get_context_from_task(self, task, qa_cache):
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"""
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Args: task
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Returns: context: "Question: {question}\n{answer}"
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if include ore in question, gpt will try to use tool with skill touch enhancement to mine
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"""
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question = (
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f"How to {task.replace('_', ' ').replace(' ore', '').replace(' ores', '').replace('.', '').strip().lower()}"
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f" in Minecraft?"
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)
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if question in self.qa_cache:
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answer = self.qa_cache[question]
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if question in qa_cache:
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answer = qa_cache[question]
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else:
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answer = await self.generate_qa_step2(question=question)
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self.qa_cache[question] = answer
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qa_cache[question] = answer
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self.qa_cache_questions_vectordb.add_texts(
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texts=[question],
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)
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with open(f"{CKPT_DIR}/curriculum/qa_cache.json", "w") as f:
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json.dump(self.qa_cache, f)
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json.dump(qa_cache, f)
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self.qa_cache_questions_vectordb.persist()
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context = f"Question: {question}\n{answer}"
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return context
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async def generate_context(self, task, max_retries=5):
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async def generate_context(self, task, qa_cache, max_retries=5):
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"""
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Refer to the code in the voyager/agents/curriculum.py propose_next_ai_task() for implementation details.
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Returns: context
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"""
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if max_retries == 0:
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raise RuntimeError("Max retries reached, failed to propose context.")
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try:
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context = await self.get_context_from_task(
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task=task
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task=task, qa_cache=qa_cache
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) # Curriculum Agent Question: How to craft 4 wooden planks in Minecraft? & Curriculum Agent Answer: ...
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return context
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except Exception as e:
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logger.info(f"Error parsing curriculum response: {e}. Trying again!")
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return await self.generate_context(
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task=task,
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qa_cache=qa_cache,
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max_retries=max_retries - 1,
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)
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async def run(self, task, human_msg, system_msg, *args, **kwargs):
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async def run(self, task, qa_cache, human_msg, system_msg, *args, **kwargs):
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logger.info(f"run {self.__repr__()}")
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# Generate curriculum-related questions and answers.
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# curriculum_qustion = await self.generate_qa_step1(events, human_msg, system_msg)
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curriculum_context = await self.generate_context(task)
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curriculum_context = await self.generate_context(task, qa_cache)
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# Return the generated questions and answers.
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return curriculum_context
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@ -12,11 +12,11 @@ class GenerateActionCode(Action):
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Action class for generating action code.
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Refer to the code in the voyager/agents/action.py for implementation details.
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"""
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def __init__(self, name="", context=None, llm=None):
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super().__init__(name, context, llm)
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self.llm.model = "gpt-4"
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async def generate_code(self, human_msg, system_msg=[]):
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"""
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Generate action code logic.
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@ -27,7 +27,7 @@ class GenerateActionCode(Action):
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rsp = await self._aask(prompt=human_msg, system_msgs=system_msg)
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parsed_result = parse_action_response(rsp)
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# logger.info(f"parsed_result is HERE: {parsed_result}")
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try:
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return (
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parsed_result["program_code"],
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@ -36,14 +36,14 @@ class GenerateActionCode(Action):
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)
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except:
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logger.error(f"Failed to parse response: {parsed_result}")
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return None, None, None # TODO: midify to "", "", ""
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return "", "", ""
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async def run(self, human_msg, system_msg, *args, **kwargs):
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logger.info(f"run {self.__repr__()}")
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# Generate action code.
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program_code, generated_code, program_name = await self.generate_code(
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human_msg=human_msg, system_msg=system_msg
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)
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# Return the generated code.
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return program_code, generated_code, program_name
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@ -7,9 +7,11 @@ import json
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from metagpt.actions import Action
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from langchain.vectorstores import Chroma
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from langchain.embeddings.openai import OpenAIEmbeddings
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from metagpt.document_store import FaissStore
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from metagpt.const import CKPT_DIR
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from metagpt.config import CONFIG
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from metagpt.logs import logger
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from metagpt.actions.minecraft.control_primitives import load_skills_code
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class PlayerActions(Action):
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@ -4,11 +4,15 @@
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# @Desc :
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from typing import Iterable, Dict, Any
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from pydantic import BaseModel, Field
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import requests
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import json
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import re
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import time
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from langchain.vectorstores import Chroma
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from langchain.embeddings.openai import OpenAIEmbeddings
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from metagpt.document_store import FaissStore
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from metagpt.logs import logger
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from metagpt.roles import Role
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from metagpt.schema import Message
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@ -300,30 +304,20 @@ class GameEnvironment(BaseModel, arbitrary_types_allowed=True):
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)
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self.update_event(events)
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return events
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except Exception as e:
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### add: 异常的话结束当前流程，继续后续运行
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logger.error(f"Failed to retrieve Minecraft events: {str(e)}")
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time.sleep(3) # wait for mineflayer to exit
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info = {
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"task": self.current_task,
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"success": False,
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}
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# reset bot status here
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events = self.mf_instance.reset(
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options={
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"mode": "hard",
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"wait_ticks": 20,
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"inventory": self.events[-1][1]["inventory"],
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"equipment": self.events[-1][1]["status"]["equipment"],
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"position": self.events[-1][1]["status"]["position"],
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"inventory": self.event[-1][1]["inventory"],
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"equipment": self.event[-1][1]["status"]["equipment"],
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"position": self.event[-1][1]["status"]["position"],
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}
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)
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self.update_event(events)
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# use red color background to print the error
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logger.info("Your last round rollout terminated due to error:")
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logger.info(f"\033[41m{e}\033[0m")
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logger.error(f"Failed to retrieve Minecraft events: {str(e)}")
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async def on_event_execute(self, *args):
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"""
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@ -346,27 +340,19 @@ class GameEnvironment(BaseModel, arbitrary_types_allowed=True):
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self.update_event(events)
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return events
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except Exception as e:
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### add: 异常的话结束当前流程，继续后续运行
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logger.error(f"Failed to retrieve Minecraft events: {str(e)}")
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time.sleep(3) # wait for mineflayer to exit
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info = {
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"task": self.current_task,
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"success": False,
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}
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# reset bot status here
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events = self.mf_instance.reset(
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options={
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"mode": "hard",
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"wait_ticks": 20,
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"inventory": self.events[-1][1]["inventory"],
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"equipment": self.events[-1][1]["status"]["equipment"],
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"position": self.events[-1][1]["status"]["position"],
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"inventory": self.event[-1][1]["inventory"],
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"equipment": self.event[-1][1]["status"]["equipment"],
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"position": self.event[-1][1]["status"]["position"],
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}
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)
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self.update_event(events)
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# use red color background to print the error
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logger.info("Your last round rollout terminated due to error:")
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logger.info(f"\033[41m{e}\033[0m")
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logger.error(f"Failed to execute Minecraft events: {str(e)}")
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class MinecraftPlayer(SoftwareCompany):
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@ -224,7 +224,7 @@ app.post("/step", async (req, res) => {
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}
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}
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bot.on("physicTick", onTick);
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bot.on("physicsTick", onTick);
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// initialize fail count
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let _craftItemFailCount = 0;
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@ -250,7 +250,7 @@ app.post("/step", async (req, res) => {
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response_sent = true;
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res.json(bot.observe());
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}
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bot.removeListener("physicTick", onTick);
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bot.removeListener("physicsTick", onTick);
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async function evaluateCode(code, programs) {
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// Echo the code produced for players to see it. Don't echo when the bot code is already producing dialog or it will double echo
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@ -144,7 +144,8 @@ class CriticReviewer(Base):
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instruct_content="verify_task",
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role=self.profile,
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send_to=agent_registry.entries["skill_manager"]()._setting.name,
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)
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) # addnewskill
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# TODO:if not success
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async def _act(self) -> Message:
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@ -157,7 +158,7 @@ class CriticReviewer(Base):
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# 获取最新的游戏周边信息
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events = await self._execute_events()
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self.perform_game_info_callback(events, self.game_memory.update_chest_memory)
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# logger.info(f"Execute return event is {self.game_memory.event}")
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context = self.game_memory.context
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task = self.game_memory.current_task
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chest_observation = self.game_memory.chest_observation
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|
|
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@ -18,29 +18,29 @@ class CurriculumDesigner(Base):
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"""
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CurriculumDesigner is the automatic curriculum in paper, refer to the code voyager/agents/curriculum.py
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"""
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def __init__(
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self,
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name: str = "David",
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profile: str = "Expertise in minecraft task design and curriculum development.",
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goal: str = " Collect and integrate learner feedback to improve and refine educational content and pathways",
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constraints: str = "Limited budget and resources for the development of educational content and technology tools.",
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self,
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name: str = "David",
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profile: str = "Expertise in minecraft task design and curriculum development.",
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goal: str = " Collect and integrate learner feedback to improve and refine educational content and pathways",
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constraints: str = "Limited budget and resources for the development of educational content and technology tools.",
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) -> None:
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super().__init__(name, profile, goal, constraints)
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# Initialize actions specific to the Action role
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self._init_actions([DesignTask, DesignCurriculum])
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# Set events or actions the ActionAgent should watch or be aware of
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self._watch([PlayerActions, DesignTask])
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logger.info(self._actions)
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self.finish_state = len(self._actions)
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def render_curriculum_observation(self, *, events, chest_observation):
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"""
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Returns: observation for curriculum
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Refer to @ https://github.com/MineDojo/Voyager/blob/main/voyager/agents/curriculum.py
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"""
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assert events[-1][0] == "observe", "Last event must be observe"
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event = events[-1][1]
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biome = event["status"]["biome"]
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@ -54,31 +54,31 @@ class CurriculumDesigner(Base):
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equipment = event["status"]["equipment"]
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inventory_used = event["status"]["inventoryUsed"]
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inventory = event["inventory"]
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if not any(
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"dirt" in block
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or "log" in block
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or "grass" in block
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or "sand" in block
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or "snow" in block
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for block in voxels
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"dirt" in block
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or "log" in block
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or "grass" in block
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or "sand" in block
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or "snow" in block
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for block in voxels
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):
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biome = "underground"
|
||||
|
||||
|
||||
other_blocks = ", ".join(
|
||||
list(
|
||||
set(block_records).difference(set(voxels).union(set(inventory.keys())))
|
||||
)
|
||||
)
|
||||
|
||||
|
||||
other_blocks = other_blocks if other_blocks else "None"
|
||||
|
||||
|
||||
nearby_entities = (
|
||||
", ".join([k for k, v in sorted(entities.items(), key=lambda x: x[1])])
|
||||
if entities
|
||||
else "None"
|
||||
)
|
||||
|
||||
|
||||
completed_tasks = (
|
||||
", ".join(self.game_memory.completed_tasks)
|
||||
if self.game_memory.completed_tasks
|
||||
|
|
@ -89,18 +89,18 @@ class CurriculumDesigner(Base):
|
|||
if self.game_memory.failed_tasks
|
||||
else "None"
|
||||
)
|
||||
|
||||
|
||||
# filter out optional inventory items if required
|
||||
if (
|
||||
self.game_memory.progress
|
||||
< self.game_memory.warm_up["optional_inventory_items"]
|
||||
self.game_memory.progress
|
||||
< self.game_memory.warm_up["optional_inventory_items"]
|
||||
):
|
||||
inventory = {
|
||||
k: v
|
||||
for k, v in inventory.items()
|
||||
if self.game_memory.core_inv_items_regex.search(k) is not None
|
||||
}
|
||||
|
||||
|
||||
observation = {
|
||||
"context": "",
|
||||
"biome": f"Biome: {biome}\n\n",
|
||||
|
|
@ -118,29 +118,30 @@ class CurriculumDesigner(Base):
|
|||
"failed_tasks": f"Failed tasks that are too hard: {failed_tasks}\n\n",
|
||||
}
|
||||
return observation
|
||||
|
||||
|
||||
# --------------------------------Design Task Prepare---------------------------------------
|
||||
async def render_design_task_human_message(
|
||||
self, events, chest_observation, *args, **kwargs
|
||||
self, events, chest_observation, *args, **kwargs
|
||||
):
|
||||
"""
|
||||
Returns: observation for curriculum
|
||||
Refer to @ https://github.com/MineDojo/Voyager/blob/main/voyager/agents/curriculum.py
|
||||
"""
|
||||
|
||||
|
||||
content = ""
|
||||
warm_up = self.game_memory.mf_instance.warm_up
|
||||
qa_cache = self.game_memory.qa_cache
|
||||
observation = self.render_curriculum_observation(
|
||||
events=events, chest_observation=chest_observation
|
||||
)
|
||||
if self.game_memory.progress >= warm_up["context"]:
|
||||
# if self.game_memory.progress >= 0: # TEST ONLY
|
||||
# if self.game_memory.progress >= 0: # TEST ONLY
|
||||
human_msg = self.render_design_curriculum_human_message(
|
||||
events=events, chest_observation=chest_observation
|
||||
).content
|
||||
system_msg = [self.render_design_curriculum_system_message().content]
|
||||
questions, answers = await self.curriculum_design_action.generate_qa(
|
||||
events=events, human_msg=human_msg, system_msg=system_msg
|
||||
questions, answers = await DesignCurriculum().generate_qa(
|
||||
events=events, qa_cache=qa_cache, human_msg=human_msg, system_msg=system_msg
|
||||
)
|
||||
logger.debug(f"Generate_qa result is HERE: Ques: {questions}, Ans: {answers}")
|
||||
i = 1
|
||||
|
|
@ -152,7 +153,7 @@ class CurriculumDesigner(Base):
|
|||
i += 1
|
||||
if i > 5:
|
||||
break
|
||||
|
||||
|
||||
for key in CURRICULUM_OB:
|
||||
if self.game_memory.progress >= warm_up[key]:
|
||||
if warm_up[key] != 0:
|
||||
|
|
@ -161,20 +162,20 @@ class CurriculumDesigner(Base):
|
|||
should_include = True
|
||||
if should_include:
|
||||
content += observation[key]
|
||||
|
||||
|
||||
logger.info(f"Curriculum Agent human message\n{content}")
|
||||
return HumanMessage(content=content)
|
||||
|
||||
|
||||
def render_design_task_system_message(self, *args, **kwargs):
|
||||
return SystemMessage(content=load_prompt("curriculum"))
|
||||
|
||||
|
||||
async def encapsule_design_task_message(self, events, chest_observation, *args, **kwargs):
|
||||
human_msg = await self.render_design_task_human_message(
|
||||
events=events, chest_observation=chest_observation, *args, **kwargs
|
||||
)
|
||||
system_msg = self.render_design_task_system_message(*args, **kwargs)
|
||||
return {"system_msg": [system_msg.content], "human_msg": human_msg.content}
|
||||
|
||||
|
||||
def generate_task_if_inventory_full(self, events, chest_observation):
|
||||
"""
|
||||
TODO: Try if this could be done with prompt
|
||||
|
|
@ -193,15 +194,15 @@ class CurriculumDesigner(Base):
|
|||
else:
|
||||
task = "Craft 1 chest"
|
||||
return task
|
||||
|
||||
|
||||
# -----------------------------------------------------------------------------------------
|
||||
|
||||
|
||||
# --------------------------------Design Curriculum Prepare--------------------------------
|
||||
def render_design_curriculum_system_message(self, *args, **kwargs):
|
||||
return SystemMessage(content=load_prompt("curriculum_qa_step1_ask_questions"))
|
||||
|
||||
|
||||
def render_design_curriculum_human_message(
|
||||
self, events, chest_observation, *args, **kwargs
|
||||
self, events, chest_observation, *args, **kwargs
|
||||
):
|
||||
observation = self.render_curriculum_observation(
|
||||
events=events, chest_observation=chest_observation
|
||||
|
|
@ -210,16 +211,16 @@ class CurriculumDesigner(Base):
|
|||
for key in CURRICULUM_OB:
|
||||
content += observation[key]
|
||||
return HumanMessage(content=content)
|
||||
|
||||
|
||||
def encapsule_design_curriculum_message(
|
||||
self, events, chest_observation, *args, **kwargs
|
||||
self, events, chest_observation, *args, **kwargs
|
||||
):
|
||||
human_msg = self.render_design_curriculum_human_message(
|
||||
events=events, chest_observation=chest_observation, *args, **kwargs
|
||||
)
|
||||
system_msg = self.render_design_curriculum_system_message(*args, **kwargs)
|
||||
return {"system_msg": [system_msg.content], "human_msg": human_msg.content}
|
||||
|
||||
|
||||
def generate_context_if_inventory_full(self, events, chest_observation):
|
||||
"""
|
||||
TODO: Try if this could be done with prompt
|
||||
|
|
@ -250,9 +251,9 @@ class CurriculumDesigner(Base):
|
|||
else:
|
||||
context = "Craft 1 chest with 8 planks of any kind of wood."
|
||||
return context
|
||||
|
||||
|
||||
# -----------------------------------------------------------------------------------------
|
||||
|
||||
|
||||
async def handle_task_design(self, human_msg, system_msg, *args, **kwargs):
|
||||
"""
|
||||
Args:
|
||||
|
|
@ -266,7 +267,7 @@ class CurriculumDesigner(Base):
|
|||
events = self.game_memory.event
|
||||
chest_observation = self.game_memory.chest_observation
|
||||
inventoryUsed = events[-1][1]["status"]["inventoryUsed"]
|
||||
|
||||
|
||||
if self.game_memory.progress == 0:
|
||||
task = self.game_memory.current_task
|
||||
elif inventoryUsed >= 33:
|
||||
|
|
@ -276,12 +277,12 @@ class CurriculumDesigner(Base):
|
|||
else:
|
||||
task = await DesignTask().run(human_msg, system_msg, *args, **kwargs)
|
||||
logger.info(f"Handle_task_design result is Here: {task}")
|
||||
|
||||
|
||||
self.perform_game_info_callback(task, self.game_memory.update_task)
|
||||
return Message(
|
||||
content=f"{task}", instruct_content="task_design", role=self.profile
|
||||
)
|
||||
|
||||
|
||||
async def handle_curriculum_design(self, human_msg, system_msg, *args, **kwargs):
|
||||
"""
|
||||
refer to the context generation in voyager
|
||||
|
|
@ -298,7 +299,8 @@ class CurriculumDesigner(Base):
|
|||
chest_observation = self.game_memory.chest_observation
|
||||
inventoryUsed = events[-1][1]["status"]["inventoryUsed"]
|
||||
task = self.game_memory.current_task
|
||||
|
||||
qa_cache = self.game_memory.qa_cache
|
||||
|
||||
if self.game_memory.progress == 0:
|
||||
context = self.game_memory.context
|
||||
elif inventoryUsed >= 33:
|
||||
|
|
@ -307,33 +309,33 @@ class CurriculumDesigner(Base):
|
|||
)
|
||||
else:
|
||||
context = await DesignCurriculum().run(
|
||||
task, human_msg, system_msg, *args, **kwargs
|
||||
task, qa_cache, human_msg, system_msg, *args, **kwargs
|
||||
)
|
||||
|
||||
self.perform_game_info_callback(context, self.game_memory.update_context)
|
||||
return Message(
|
||||
content=f"{context}",
|
||||
instruct_content="curriculum_design",
|
||||
role=self.profile,
|
||||
)
|
||||
|
||||
|
||||
async def _act(self) -> Message:
|
||||
todo = self._rc.todo
|
||||
logger.debug(f"Todo is {todo}")
|
||||
self.maintain_actions(todo)
|
||||
|
||||
|
||||
# 获取最新的游戏周边环境信息
|
||||
# events = await self._obtain_events()
|
||||
events = self.game_memory.event
|
||||
events = await self._obtain_events()
|
||||
logger.info(f"Retrieve event is HERE: {events}, current task is {self.game_memory.current_task}")
|
||||
# events = self.game_memory.event
|
||||
chest_observation = self.game_memory.chest_observation
|
||||
|
||||
|
||||
design_task_message = await self.encapsule_design_task_message(
|
||||
events, chest_observation
|
||||
)
|
||||
design_curriculum_message = self.encapsule_design_curriculum_message(
|
||||
events, chest_observation
|
||||
)
|
||||
|
||||
|
||||
handler_map = {
|
||||
DesignTask: self.handle_task_design,
|
||||
DesignCurriculum: self.handle_curriculum_design,
|
||||
|
|
@ -348,5 +350,5 @@ class CurriculumDesigner(Base):
|
|||
msg.round_id = self.round_id
|
||||
self._publish_message(msg)
|
||||
return msg
|
||||
|
||||
|
||||
raise ValueError(f"Unknown todo type: {type(todo)}")
|
||||
|
|
|
|||
|
|
@ -40,12 +40,8 @@ def parse_action_response(msg: str):
|
|||
error = None # 3 times failed return error
|
||||
while retry > 0:
|
||||
try:
|
||||
babel = require("@babel/core")
|
||||
parsed = parse_js_code(msg)
|
||||
babel_generator = require("@babel/generator").default
|
||||
|
||||
code_pattern = re.compile(r"```(?:javascript|js)(.*?)```", re.DOTALL)
|
||||
code = "\n".join(code_pattern.findall(msg))
|
||||
parsed = babel.parse(code)
|
||||
# Collect func list: check if func & async
|
||||
functions = []
|
||||
assert len(list(parsed.program.body)) > 0, "No functions found"
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue