mirror of
https://github.com/FoundationAgents/MetaGPT.git
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update code
This commit is contained in:
stellahsr
parent
e6a5ae938a
commit
b55a080c83
6 changed files with 182 additions and 167 deletions
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@ -92,7 +92,7 @@ class DesignCurriculum(Action):
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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, qa_cache, human_msg, system_msg):
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async def generate_qa(self, events, qa_cache, qa_cache_questions_vectordb, 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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@ -104,9 +104,9 @@ class DesignCurriculum(Action):
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questions = []
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answers = []
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for question in questions_new:
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if self.qa_cache_questions_vectordb._collection.count() > 0:
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if qa_cache_questions_vectordb._collection.count() > 0:
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docs_and_scores = (
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self.qa_cache_questions_vectordb.similarity_search_with_score(
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qa_cache_questions_vectordb.similarity_search_with_score(
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question, k=1
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)
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)
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@ -120,12 +120,12 @@ class DesignCurriculum(Action):
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answer = await self.generate_qa_step2(question=question)
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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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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(qa_cache, f)
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self.qa_cache_questions_vectordb.persist()
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qa_cache_questions_vectordb.persist()
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questions.append(question)
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answers.append(answer)
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assert len(questions_new) == len(questions) == len(answers)
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@ -170,7 +170,7 @@ class DesignCurriculum(Action):
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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, qa_cache):
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async def get_context_from_task(self, task, qa_cache, qa_cache_questions_vectordb):
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"""
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Args: task
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Returns: context: "Question: {question}\n{answer}"
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@ -186,16 +186,16 @@ class DesignCurriculum(Action):
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else:
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answer = await self.generate_qa_step2(question=question)
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qa_cache[question] = answer
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self.qa_cache_questions_vectordb.add_texts(
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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(qa_cache, f)
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self.qa_cache_questions_vectordb.persist()
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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, qa_cache, max_retries=5):
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async def generate_context(self, task, qa_cache, qa_cache_questions_vectordb, 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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@ -206,7 +206,7 @@ class DesignCurriculum(Action):
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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, qa_cache=qa_cache
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task=task, qa_cache=qa_cache, qa_cache_questions_vectordb=qa_cache_questions_vectordb
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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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@ -214,14 +214,15 @@ class DesignCurriculum(Action):
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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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qa_cache_questions_vectordb=qa_cache_questions_vectordb,
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max_retries=max_retries - 1,
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)
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async def run(self, task, qa_cache, human_msg, system_msg, *args, **kwargs):
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async def run(self, task, qa_cache, qa_cache_questions_vectordb, 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, qa_cache)
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curriculum_context = await self.generate_context(task, qa_cache, qa_cache_questions_vectordb)
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# Return the generated questions and answers.
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return curriculum_context
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@ -5,8 +5,6 @@
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import os
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import json
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from traits.trait_types import self
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from metagpt.logs import logger
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from metagpt.actions.minecraft.player_action import PlayerActions as Action
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from metagpt.const import CKPT_DIR
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@ -17,18 +15,18 @@ class RetrieveSkills(Action):
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Action class for retrieving skills.
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Refer to the code in the voyager/agents/skill.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 run(self, query, skills, *args, **kwargs):
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async def run(self, query, skills, vectordb, *args, **kwargs):
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# Implement the logic for retrieving skills here.
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k = min(self.vectordb._collection.count(), self.retrieval_top_k)
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k = min(vectordb._collection.count(), self.retrieval_top_k)
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if k == 0:
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return []
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logger.info(f"Skill Manager retrieving for {k} skills")
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docs_and_scores = self.vectordb.similarity_search_with_score(query, k=k)
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docs_and_scores = vectordb.similarity_search_with_score(query, k=k)
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logger.info(
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f"Skill Manager retrieved skills: "
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f"{', '.join([doc.metadata['name'] for doc, _ in docs_and_scores])}"
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@ -44,13 +42,13 @@ class AddNewSkills(Action):
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Action class for adding new skills.
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Refer to the code in the voyager/agents/skill.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 run(
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self, task, program_name, program_code, skills, skill_desp, *args, **kwargs
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self, task, program_name, program_code, skills, skill_desp, vectordb, *args, **kwargs
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):
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# Implement the logic for adding new skills here.
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# TODO: Fix this
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@ -65,26 +63,27 @@ class AddNewSkills(Action):
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if program_name in skills:
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logger.info(f"Skill {program_name} already exists. Rewriting!")
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self.vectordb._collection.delete(ids=[program_name])
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vectordb._collection.delete(ids=[program_name])
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i = 2
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while f"{program_name}V{i}.js" in os.listdir(f"{CKPT_DIR}/skill/code"):
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i += 1
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dumped_program_name = f"{program_name}V{i}"
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else:
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dumped_program_name = program_name
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self.vectordb.add_texts(
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vectordb.add_texts(
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texts=[skill_desp],
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ids=[program_name],
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metadatas=[{"name": program_name}],
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)
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logger.debug(f"ADD_CHECK: There are {vectordb._collection.count()} skills in vectordb")
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with open(f"{CKPT_DIR}/skill/code/{dumped_program_name}.js", "w") as f:
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f.write(program_code)
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with open(f"{CKPT_DIR}/skill/description/{dumped_program_name}.txt", "w") as f:
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f.write(skill_desp)
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with open(f"{CKPT_DIR}/skill/skills.json", "w") as f:
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json.dump(skills, f)
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self.vectordb.persist()
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vectordb.persist()
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return {
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"code": program_code,
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"description": skill_desp,
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@ -96,13 +95,13 @@ class GenerateSkillDescription(Action):
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Action class for generating skill descriptions.
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Refer to the code in the voyager/agents/skill.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 run(self, program_name, human_message, system_message, *args, **kwargs):
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# Implement the logic for generating skill descriptions here.
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rsp = await self._aask(prompt=human_message, system_msgs=system_message)
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skill_description = f" // {rsp}"
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skill_description = f" // { rsp}"
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return f"async function {program_name}(bot) {{\n{skill_description}\n}}"
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@ -2,68 +2,14 @@
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# @Date : 2023/9/23 17:06
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# @Author : stellahong (stellahong@fuzhi.ai)
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# @Desc :
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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.const import CKPT_DIR
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from metagpt.config import CONFIG
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class PlayerActions(Action):
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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.skills_check = {} # for skills.json
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self.qa_cache_check = {}
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self.check_init = True
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if (
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CONFIG.resume
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): # TODO: now for assert only, no update, cuz program using in step()
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with open(f"{CKPT_DIR}/skill/skills.json", "r") as f:
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self.skills_check = json.load(f)
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with open(f"{CKPT_DIR}/curriculum/qa_cache.json", "r") as f:
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self.qa_cache_check = json.load(f)
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self.retrieval_top_k = 5
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self.vectordb = Chroma(
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collection_name="skill_vectordb",
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embedding_function=OpenAIEmbeddings(),
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persist_directory=f"{CKPT_DIR}/skill/vectordb",
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)
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self.qa_cache_questions_vectordb = Chroma(
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collection_name="qa_cache_questions_vectordb",
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embedding_function=OpenAIEmbeddings(),
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persist_directory=f"{CKPT_DIR}/curriculum/vectordb",
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)
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# FIXME
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if self.check_init:
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# Check if Skill Manager's vectordb right using
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assert self.vectordb._collection.count() >= len(self.skills_check), (
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f"Skill Manager's vectordb is not synced with skills.json.\n"
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f"There are {self.vectordb._collection.count()} skills in vectordb but {len(self.skills_check)} skills in skills.json.\n"
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f"Did you set resume=False when initializing the manager?\n"
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f"You may need to manually delete the vectordb directory for running from scratch."
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)
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# Check if Skill Manager's vectordb right using
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assert self.qa_cache_questions_vectordb._collection.count() >= len(
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self.qa_cache_check
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), (
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f"Curriculum Agent's qa cache question vectordb is not synced with qa_cache.json.\n"
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f"There are {self.qa_cache_questions_vectordb._collection.count()} questions in vectordb "
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f"but {len(self.qa_cache_check)} questions in qa_cache.json.\n"
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f"Did you set resume=False when initializing the agent?\n"
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f"You may need to manually delete the qa cache question vectordb directory for running from scratch.\n"
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)
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self.check_init = False
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# TODO: change to FaissStore
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# self.qa_cache_questions_vectordb = FaissStore( {CKPT_DIR}/ 'curriculum/vectordb'
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"""Minecraft player info without any implementation details"""
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async def run(self, *args, **kwargs):
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@ -31,7 +31,7 @@ class GameEnvironment(BaseModel, arbitrary_types_allowed=True):
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"""
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游戏环境的记忆，用于多个agent进行信息的共享和缓存，而不需要重复在自己的角色内维护缓存
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"""
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event: dict[str, Any] = Field(default_factory=dict)
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current_task: str = Field(default="Mine 1 wood log")
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task_execution_time: float = Field(default=float)
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@ -39,32 +39,32 @@ class GameEnvironment(BaseModel, arbitrary_types_allowed=True):
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default="You can mine one of oak, birch, spruce, jungle, acacia, dark oak, or mangrove logs."
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)
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code: str = Field(default="")
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program_code: str = Field(default="") # write in skill/code/*.js
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program_code: str = Field(default="") # write in skill/code/*.js
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program_name: str = Field(default="")
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critique: str = Field(default="")
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skills: dict = Field(default_factory=dict) # for skills.json
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retrieve_skills: list[str] = Field(default_factory=list)
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event_summary: str = Field(default="")
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qa_cache: dict[str, str] = Field(default_factory=dict)
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completed_tasks: list[str] = Field(default_factory=list) # Critique things
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failed_tasks: list[str] = Field(default_factory=list)
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skill_desp: str = Field(default="")
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chest_memory: dict[str, Any] = Field(
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default_factory=dict
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) # eg: {'(1344, 64, 1381)': 'Unknown'}
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chest_observation: str = Field(default="") # eg: "Chests: None\n\n"
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mf_instance: MineflayerEnv = Field(default_factory=MineflayerEnv)
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runtime_status: bool = False # equal to action execution status: success or failed
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@property
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def progress(self):
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# return len(self.completed_tasks) + 10 # Test only
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return len(self.completed_tasks)
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@property
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def programs(self):
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programs = ""
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@ -75,25 +75,41 @@ class GameEnvironment(BaseModel, arbitrary_types_allowed=True):
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for primitives in load_skills_code():
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programs += f"{primitives}\n\n"
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return programs
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@property
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def warm_up(self):
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return self.mf_instance.warm_up
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@property
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def core_inv_items_regex(self):
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return self.mf_instance.core_inv_items_regex
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@property
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def qa_cache_questions_vectordb(self):
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return Chroma(
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collection_name="qa_cache_questions_vectordb",
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embedding_function=OpenAIEmbeddings(),
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persist_directory=f"{CKPT_DIR}/curriculum/vectordb",
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)
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@property
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def vectordb(self):
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return Chroma(
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collection_name="skill_vectordb",
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embedding_function=OpenAIEmbeddings(),
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persist_directory=f"{CKPT_DIR}/skill/vectordb",
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)
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def set_mc_port(self, mc_port):
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self.mf_instance.set_mc_port(mc_port)
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self.set_mc_resume()
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def set_mc_resume(self):
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if CONFIG.resume:
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logger.info(f"Loading Action Developer from {CKPT_DIR}/action")
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with open(f"{CKPT_DIR}/action/chest_memory.json", "r") as f:
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self.chest_memory = json.load(f)
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logger.info(f"Loading Curriculum Agent from {CKPT_DIR}/curriculum")
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with open(f"{CKPT_DIR}/curriculum/completed_tasks.json", "r") as f:
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self.completed_tasks = json.load(f)
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@ -103,25 +119,72 @@ class GameEnvironment(BaseModel, arbitrary_types_allowed=True):
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logger.info(f"Loading Skill Manager from {CKPT_DIR}/skill\033[0m")
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with open(f"{CKPT_DIR}/skill/skills.json", "r") as f:
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self.skills = json.load(f)
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logger.info(f"Loading Qa Cache from {CKPT_DIR}/curriculum\033[0m")
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with open(f"{CKPT_DIR}/curriculum/qa_cache.json", "r") as f:
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self.qa_cache = json.load(f)
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self.qa_cache = json.load(f)
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if self.vectordb._collection.count() == 0:
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# Set vdvs for skills & qa_cache
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skill_desps = [
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skill["description"] for program_name, skill in self.skills.items()
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]
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program_names = [
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program_name for program_name, skill in self.skills.items()
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]
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metadatas = [{"name": program_name} for program_name in program_names]
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# add vectordb from file
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ids = self.vectordb.add_texts(
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texts=skill_desps,
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ids=program_names,
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metadatas=metadatas,
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)
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self.vectordb.persist()
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if self.qa_cache_questions_vectordb._collection.count() == 0:
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questions = [question for question, answer in self.qa_cache.items()]
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self.qa_cache_questions_vectordb.add_texts(texts=questions)
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self.qa_cache_questions_vectordb.persist()
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logger.info(
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f"INIT_CHECK: There are {self.vectordb._collection.count()} skills in vectordb and {len(self.skills)} skills in skills.json."
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)
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# Check if Skill Manager's vectordb right using
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assert self.vectordb._collection.count() >= len(self.skills), (
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f"Skill Manager's vectordb is not synced with skills.json.\n"
|
||||
f"There are {self.vectordb._collection.count()} skills in vectordb but {len(self.skills)} skills in skills.json.\n"
|
||||
f"Did you set resume=False when initializing the manager?\n"
|
||||
f"You may need to manually delete the vectordb directory for running from scratch."
|
||||
)
|
||||
|
||||
logger.info(
|
||||
f"INIT_CHECK: There are {self.qa_cache_questions_vectordb._collection.count()} qa_cache in vectordb and {len(self.qa_cache)} questions in qa_cache.json."
|
||||
)
|
||||
assert self.qa_cache_questions_vectordb._collection.count() >= len(
|
||||
self.qa_cache
|
||||
), (
|
||||
f"Curriculum Agent's qa cache question vectordb is not synced with qa_cache.json.\n"
|
||||
f"There are {self.qa_cache_questions_vectordb._collection.count()} questions in vectordb "
|
||||
f"but {len(self.qa_cache)} questions in qa_cache.json.\n"
|
||||
f"Did you set resume=False when initializing the agent?\n"
|
||||
f"You may need to manually delete the qa cache question vectordb directory for running from scratch.\n"
|
||||
)
|
||||
|
||||
def register_roles(self, roles: Iterable[Minecraft]):
|
||||
for role in roles:
|
||||
role.set_memory(self)
|
||||
|
||||
|
||||
def update_event(self, event: Dict):
|
||||
if self.event == event:
|
||||
return
|
||||
self.event = event
|
||||
# self.update_chest_memory(event)
|
||||
# self.event_summary = self.summarize_chatlog(event)
|
||||
|
||||
|
||||
def update_task(self, task: str):
|
||||
self.current_task = task
|
||||
|
||||
|
||||
def update_context(self, context: str):
|
||||
self.context = context
|
||||
|
||||
|
|
@ -130,22 +193,22 @@ class GameEnvironment(BaseModel, arbitrary_types_allowed=True):
|
|||
|
||||
def update_code(self, code: str):
|
||||
self.code = code # action_developer.gen_action_code to HERE
|
||||
|
||||
|
||||
def update_program_name(self, program_name: str):
|
||||
self.program_name = program_name
|
||||
|
||||
|
||||
def update_critique(self, critique: str):
|
||||
self.critique = critique # critic_agent.check_task_success to HERE
|
||||
|
||||
|
||||
def append_skill(self, skill: dict):
|
||||
self.skills[self.program_name] = skill # skill_manager.retrieve_skills to HERE
|
||||
|
||||
|
||||
def update_retrieve_skills(self, retrieve_skills: list):
|
||||
self.retrieve_skills = retrieve_skills
|
||||
|
||||
|
||||
def update_skill_desp(self, skill_desp: str):
|
||||
self.skill_desp = skill_desp
|
||||
|
||||
|
||||
def update_chest_memory(self, events: Dict):
|
||||
"""
|
||||
Input: events: Dict
|
||||
|
|
@ -165,13 +228,13 @@ class GameEnvironment(BaseModel, arbitrary_types_allowed=True):
|
|||
self.chest_memory[position] = chest
|
||||
with open(f"{CKPT_DIR}/action/chest_memory.json", "w") as f:
|
||||
json.dump(self.chest_memory, f)
|
||||
|
||||
|
||||
def update_chest_observation(self):
|
||||
"""
|
||||
update chest_memory to chest_observation.
|
||||
Refer to @ https://github.com/MineDojo/Voyager/blob/main/voyager/agents/action.py
|
||||
"""
|
||||
|
||||
|
||||
chests = []
|
||||
for chest_position, chest in self.chest_memory.items():
|
||||
if isinstance(chest, dict) and len(chest) > 0:
|
||||
|
|
@ -189,7 +252,7 @@ class GameEnvironment(BaseModel, arbitrary_types_allowed=True):
|
|||
self.chest_observation = f"Chests:\n{chests}\n\n"
|
||||
else:
|
||||
self.chest_observation = f"Chests: None\n\n"
|
||||
|
||||
|
||||
def summarize_chatlog(self, events):
|
||||
def filter_item(message: str):
|
||||
craft_pattern = r"I cannot make \w+ because I need: (.*)"
|
||||
|
|
@ -198,25 +261,28 @@ class GameEnvironment(BaseModel, arbitrary_types_allowed=True):
|
|||
)
|
||||
mine_pattern = r"I need at least a (.*) to mine \w+!"
|
||||
if re.match(craft_pattern, message):
|
||||
self.event_summary = re.match(craft_pattern, message).groups()[0]
|
||||
self.event_summary = re.match(craft_pattern, message).groups()[0]
|
||||
elif re.match(craft_pattern2, message):
|
||||
self.event_summary = "a nearby crafting table"
|
||||
elif re.match(mine_pattern, message):
|
||||
self.event_summary = re.match(mine_pattern, message).groups()[0]
|
||||
else:
|
||||
self.event_summary = ""
|
||||
|
||||
chatlog = set()
|
||||
for event_type, event in events:
|
||||
if event_type == "onChat":
|
||||
item = filter_item(event["onChat"])
|
||||
if item:
|
||||
chatlog.add(item)
|
||||
self.event_summary = "I also need " + ", ".join(chatlog) + "." if chatlog else ""
|
||||
|
||||
self.event_summary = (
|
||||
"I also need " + ", ".join(chatlog) + "." if chatlog else ""
|
||||
)
|
||||
|
||||
def reset_block_info(self):
|
||||
# revert all the placing event in the last step
|
||||
pass
|
||||
|
||||
|
||||
def update_exploration_progress(self, success: bool):
|
||||
"""
|
||||
Split task into completed_tasks or failed_tasks
|
||||
|
|
@ -252,9 +318,9 @@ class GameEnvironment(BaseModel, arbitrary_types_allowed=True):
|
|||
)
|
||||
self.event[-1][1]["inventory"] = new_events[-1][1]["inventory"]
|
||||
self.event[-1][1]["voxels"] = new_events[-1][1]["voxels"]
|
||||
|
||||
|
||||
self.save_sorted_tasks()
|
||||
|
||||
|
||||
def save_sorted_tasks(self):
|
||||
updated_completed_tasks = []
|
||||
# record repeated failed tasks
|
||||
|
|
@ -263,21 +329,21 @@ class GameEnvironment(BaseModel, arbitrary_types_allowed=True):
|
|||
for task in self.completed_tasks:
|
||||
if task not in updated_completed_tasks:
|
||||
updated_completed_tasks.append(task)
|
||||
|
||||
|
||||
# remove completed tasks from failed tasks
|
||||
for task in updated_completed_tasks:
|
||||
while task in updated_failed_tasks:
|
||||
updated_failed_tasks.remove(task)
|
||||
|
||||
|
||||
self.completed_tasks = updated_completed_tasks
|
||||
self.failed_tasks = updated_failed_tasks
|
||||
|
||||
|
||||
# dump to json
|
||||
with open(f"{CKPT_DIR}/curriculum/completed_tasks.json", "w") as f:
|
||||
json.dump(self.completed_tasks, f)
|
||||
with open(f"{CKPT_DIR}/curriculum/failed_tasks.json", "w") as f:
|
||||
json.dump(self.failed_tasks, f)
|
||||
|
||||
|
||||
async def on_event_retrieve(self, *args):
|
||||
"""
|
||||
Retrieve Minecraft events.
|
||||
|
|
@ -295,9 +361,7 @@ class GameEnvironment(BaseModel, arbitrary_types_allowed=True):
|
|||
"wait_ticks": 20,
|
||||
}
|
||||
)
|
||||
difficulty = (
|
||||
"easy" if len(self.completed_tasks) > 15 else "peaceful"
|
||||
)
|
||||
difficulty = "easy" if len(self.completed_tasks) > 15 else "peaceful"
|
||||
events = self.mf_instance.step(
|
||||
"bot.chat(`/time set ${getNextTime()}`);\n"
|
||||
+ f"bot.chat('/difficulty {difficulty}');"
|
||||
|
|
@ -318,7 +382,8 @@ class GameEnvironment(BaseModel, arbitrary_types_allowed=True):
|
|||
)
|
||||
self.update_event(events)
|
||||
logger.error(f"Failed to retrieve Minecraft events: {str(e)}")
|
||||
|
||||
return events
|
||||
|
||||
async def on_event_execute(self, *args):
|
||||
"""
|
||||
Execute Minecraft events.
|
||||
|
|
@ -334,7 +399,7 @@ class GameEnvironment(BaseModel, arbitrary_types_allowed=True):
|
|||
"""
|
||||
try:
|
||||
events = self.mf_instance.step(
|
||||
code = self.code,
|
||||
code=self.code,
|
||||
programs=self.programs,
|
||||
)
|
||||
self.update_event(events)
|
||||
|
|
@ -353,6 +418,7 @@ class GameEnvironment(BaseModel, arbitrary_types_allowed=True):
|
|||
)
|
||||
self.update_event(events)
|
||||
logger.error(f"Failed to execute Minecraft events: {str(e)}")
|
||||
return events
|
||||
|
||||
|
||||
class MinecraftPlayer(SoftwareCompany):
|
||||
|
|
@ -360,16 +426,16 @@ class MinecraftPlayer(SoftwareCompany):
|
|||
Software Company: Possesses a team, SOP (Standard Operating Procedures), and a platform for instant messaging,
|
||||
dedicated to writing executable code.
|
||||
"""
|
||||
|
||||
|
||||
environment: Environment = Field(default_factory=Environment)
|
||||
game_memory: GameEnvironment = Field(default_factory=GameEnvironment)
|
||||
investment: float = Field(default=50.0)
|
||||
task: str = Field(default="")
|
||||
game_info: dict = Field(default={})
|
||||
|
||||
|
||||
def set_port(self, mc_port):
|
||||
self.game_memory.set_mc_port(mc_port)
|
||||
|
||||
|
||||
def check_complete_round(self):
|
||||
complete_round = []
|
||||
for role in self.environment.roles.values():
|
||||
|
|
@ -381,7 +447,7 @@ class MinecraftPlayer(SoftwareCompany):
|
|||
complete_round_tag = all(complete_round)
|
||||
logger.info(f"complete_round {complete_round}")
|
||||
return complete_round_tag
|
||||
|
||||
|
||||
def update_round(self):
|
||||
for role in self.environment.roles.values():
|
||||
role.finish_step = False
|
||||
|
|
@ -389,11 +455,11 @@ class MinecraftPlayer(SoftwareCompany):
|
|||
role._rc.todo = None
|
||||
role.finish_state = len(role._actions)
|
||||
logger.info(f"round_id:{role.round_id}")
|
||||
|
||||
|
||||
def hire(self, roles: list[Role]):
|
||||
self.environment.add_roles(roles)
|
||||
self.game_memory.register_roles(roles)
|
||||
|
||||
|
||||
def start(self, task, round=0):
|
||||
"""Start a project from publishing boss requirement."""
|
||||
self.task = task
|
||||
|
|
@ -401,14 +467,14 @@ class MinecraftPlayer(SoftwareCompany):
|
|||
Message(role="Player", content=task, cause_by=PlayerActions, round_id=round)
|
||||
)
|
||||
logger.info(self.game_info)
|
||||
|
||||
|
||||
def _save(self):
|
||||
logger.info(self.json())
|
||||
|
||||
|
||||
def _reset(self):
|
||||
for role_profile, role in self.environment.roles.items():
|
||||
role.reset_state()
|
||||
|
||||
|
||||
async def run(self, n_round=3):
|
||||
"""Run company until target round or no money"""
|
||||
round_id = 0
|
||||
|
|
@ -434,18 +500,17 @@ class MinecraftPlayer(SoftwareCompany):
|
|||
programs="",
|
||||
)
|
||||
self.game_memory.update_event(events)
|
||||
|
||||
|
||||
while n_round > 0:
|
||||
# self._save()
|
||||
if self.check_complete_round():
|
||||
|
||||
n_round -= 1
|
||||
self.update_round()
|
||||
round_id += 1
|
||||
# add new task into env and continue
|
||||
# fixme: update self.task
|
||||
self.start(task=self.task, round=round_id)
|
||||
|
||||
|
||||
logger.info(f"{n_round=}")
|
||||
self._check_balance()
|
||||
await self.environment.run()
|
||||
|
|
|
|||
|
|
@ -300,6 +300,7 @@ class CurriculumDesigner(Base):
|
|||
inventoryUsed = events[-1][1]["status"]["inventoryUsed"]
|
||||
task = self.game_memory.current_task
|
||||
qa_cache = self.game_memory.qa_cache
|
||||
qa_cache_questions_vectordb = self.game_memory.qa_cache_questions_vectordb
|
||||
|
||||
if self.game_memory.progress == 0:
|
||||
context = self.game_memory.context
|
||||
|
|
@ -309,7 +310,7 @@ class CurriculumDesigner(Base):
|
|||
)
|
||||
else:
|
||||
context = await DesignCurriculum().run(
|
||||
task, qa_cache, human_msg, system_msg, *args, **kwargs
|
||||
task, qa_cache, qa_cache_questions_vectordb, human_msg, system_msg, *args, **kwargs
|
||||
)
|
||||
self.perform_game_info_callback(context, self.game_memory.update_context)
|
||||
return Message(
|
||||
|
|
|
|||
|
|
@ -19,40 +19,42 @@ from metagpt.utils.minecraft import load_prompt
|
|||
@agent_registry.register("skill_manager")
|
||||
class SkillManager(Base):
|
||||
def __init__(
|
||||
self,
|
||||
name: str = "John",
|
||||
profile: str = "Skills Management Specialist",
|
||||
goal: str = "To oversee and optimize the acquisition, development, and utilization of skills within the organization, ensuring workforce competence and efficiency.",
|
||||
constraints: str = "Resource allocation, training budgets, and alignment with organizational goals.",
|
||||
self,
|
||||
name: str = "John",
|
||||
profile: str = "Skills Management Specialist",
|
||||
goal: str = "To oversee and optimize the acquisition, development, and utilization of skills within the organization, ensuring workforce competence and efficiency.",
|
||||
constraints: str = "Resource allocation, training budgets, and alignment with organizational goals.",
|
||||
) -> None:
|
||||
super().__init__(name, profile, goal, constraints)
|
||||
|
||||
|
||||
# Initialize actions specific to the SkillManager role
|
||||
self._init_actions([RetrieveSkills, GenerateSkillDescription, AddNewSkills])
|
||||
|
||||
|
||||
# Set events or actions the SkillManager should watch or be aware of
|
||||
self._watch(
|
||||
[DesignCurriculum, GenerateActionCode, RetrieveSkills, GenerateSkillDescription]
|
||||
)
|
||||
|
||||
self.finish_state = len(self._actions)
|
||||
|
||||
|
||||
def encapsule_message(self, program_code, program_name, *args, **kwargs):
|
||||
system_msg = self.render_system_message(load_prompt("skill"))
|
||||
human_msg = self.render_human_message(
|
||||
program_code + "\n\n" + f"The main function is `{program_name}`."
|
||||
)
|
||||
return {"system_msg": [system_msg.content], "human_msg": human_msg.content}
|
||||
|
||||
|
||||
async def retrieve_skills(self, query, skills, *args, **kwargs):
|
||||
retrieve_skills = await RetrieveSkills().run(query, skills)
|
||||
vectordb = self.game_memory.vectordb
|
||||
retrieve_skills = await RetrieveSkills().run(query, skills, vectordb)
|
||||
logger.info(f"Render Action Agent system message with {len(retrieve_skills)} skills")
|
||||
self.perform_game_info_callback(retrieve_skills, self.game_memory.update_retrieve_skills)
|
||||
return Message(content=f"{retrieve_skills}", instruct_content="retrieve_skills",
|
||||
return Message(content=f"{retrieve_skills}", instruct_content="retrieve_skills",
|
||||
role=self.profile, send_to=agent_registry.entries["action_developer"]()._setting.name)
|
||||
# return Message(
|
||||
# content=f"{skills}", instruct_content="retrieve_skills", role=self.profile
|
||||
# ) # Unit test only
|
||||
|
||||
|
||||
async def generate_skill_descp(self, human_msg, system_msg, *args, **kwargs):
|
||||
program_name = self.game_memory.program_name
|
||||
desp = await GenerateSkillDescription().run(program_name, human_msg, system_msg)
|
||||
|
|
@ -62,20 +64,21 @@ class SkillManager(Base):
|
|||
instruct_content="generate_skill_descp",
|
||||
role=self.profile,
|
||||
)
|
||||
|
||||
|
||||
async def handle_add_new_skills(
|
||||
self, task, program_name, program_code, skills, *args, **kwargs
|
||||
self, task, program_name, program_code, skills, *args, **kwargs
|
||||
):
|
||||
if not self.game_memory.runtime_status:
|
||||
return Message(
|
||||
content="",
|
||||
instruct_content="handle_add_new_skills",
|
||||
role=self.profile,
|
||||
)
|
||||
content="",
|
||||
instruct_content="handle_add_new_skills",
|
||||
role=self.profile,
|
||||
)
|
||||
|
||||
skill_desp = self.game_memory.skill_desp
|
||||
vectordb = self.game_memory.vectordb
|
||||
new_skills_info = await AddNewSkills().run(
|
||||
task, program_name, program_code, skills, skill_desp
|
||||
task, program_name, program_code, skills, skill_desp, vectordb
|
||||
)
|
||||
self.perform_game_info_callback(new_skills_info, self.game_memory.append_skill)
|
||||
return Message(
|
||||
|
|
@ -83,13 +86,13 @@ class SkillManager(Base):
|
|||
instruct_content="handle_add_new_skills",
|
||||
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信息
|
||||
|
||||
context = self.game_memory.context
|
||||
task = self.game_memory.current_task
|
||||
|
||||
|
|
@ -97,27 +100,27 @@ class SkillManager(Base):
|
|||
self.perform_game_info_callback(self.game_memory.event, self.game_memory.summarize_chatlog)
|
||||
event_summary = self.game_memory.event_summary
|
||||
program_code = self.game_memory.program_code
|
||||
|
||||
|
||||
program_name = self.game_memory.program_name
|
||||
skills = self.game_memory.skills
|
||||
|
||||
|
||||
# msg = self._rc.memory.get(k=1)[0]
|
||||
|
||||
|
||||
retrieve_skills_message_step1 = {"query": context, "skills": skills}
|
||||
logger.info(f"check query {context}")
|
||||
logger.info(f"check event summary {event_summary}")
|
||||
|
||||
retrieve_skills_message_step2 = {"query": context + "\n\n" + event_summary, "skills": skills}
|
||||
|
||||
|
||||
generate_skill_message = self.encapsule_message(program_code, program_name)
|
||||
|
||||
|
||||
add_new_skills_message = {
|
||||
"task": task,
|
||||
"program_name": program_name,
|
||||
"program_code": program_code,
|
||||
"skills": skills,
|
||||
}
|
||||
|
||||
|
||||
handler_map = {
|
||||
DesignCurriculum: self.retrieve_skills,
|
||||
RetrieveSkills: self.retrieve_skills,
|
||||
|
|
@ -136,10 +139,10 @@ class SkillManager(Base):
|
|||
msg = await handler(**generate_skill_message)
|
||||
else:
|
||||
msg = await handler(**add_new_skills_message)
|
||||
|
||||
|
||||
msg.cause_by = type(todo)
|
||||
msg.round_id = self.round_id
|
||||
self._publish_message(msg)
|
||||
return msg
|
||||
|
||||
|
||||
raise ValueError(f"Unknown todo type: {type(todo)}")
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue