apunkt/MetaGPT
1
0
Fork 0
mirror of https://github.com/FoundationAgents/MetaGPT.git synced 2026-07-05 16:02:14 +02:00
Code Issues Projects Releases Packages Wiki Activity Actions

merge: merge from yuymf/minecraft_dev2, update base vdb op in PlayerActions and add event execute func, use PlayerActions as action base

Browse source
This commit is contained in:
stellahsr 2023-10-06 20:28:01 +08:00
parent 5aea00f8b4
commit 6bcd3bdcee
10 changed files with 145 additions and 131 deletions
Download patch file Download diff file Expand all files Collapse all files

30
metagpt/actions/minecraft/design_curriculumn.py
View file

@ -10,13 +10,11 @@ from langchain.vectorstores import Chroma
from metagpt.document_store import FaissStore
from metagpt.logs import logger
from metagpt.actions import Action
from metagpt.actions.minecraft.player_action import PlayerActions as Action
from metagpt.utils.minecraft import load_prompt, fix_and_parse_json
from metagpt.schema import HumanMessage, SystemMessage
from metagpt.const import CKPT_DIR
# from metagpt.actions.minecraft import PlayerActions
class DesignTask(Action):
"""
@ -63,11 +61,12 @@ class DesignTask(Action):
response = self.parse_llm_response(
curriculum
) # Task: Craft 4 wooden planks.
logger.info(f"Parsed Curriculum Agent response\n{response}")
assert "next_task" in response
return response["next_task"]
except Exception as e:
logger.info(f"Error parsing curriculum response: {e}. Trying again!")
return self.generate_task(
return await self.generate_task(
human_msg=human_msg,
system_msg=system_msg,
max_retries=max_retries - 1,
@ -92,29 +91,6 @@ class DesignCurriculum(Action):
def __init__(self, name="", context=None, llm=None):
super().__init__(name, context, llm)
# voyager vectordb using
self.qa_cache = {}
self.qa_cache_questions_vectordb = Chroma(
collection_name="qa_cache_questions_vectordb",
embedding_function=OpenAIEmbeddings(),
persist_directory=f"{CKPT_DIR}/curriculum/vectordb",
)
# TODO: change to FaissStore
# self.qa_cache_questions_vectordb = FaissStore( {CKPT_DIR}/ 'curriculum/vectordb')
# TODO:
# 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"
# )
@classmethod
def set_qa_cache(cls, qa_cache):
cls.qa_cache = qa_cache
# Check if qa_cache right using
@classmethod
def generate_qa(cls, events, chest_observation):

36
metagpt/actions/minecraft/manage_skills.py
View file

@ -5,11 +5,8 @@
import os
import json
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.vectorstores import Chroma
from metagpt.document_store import FaissStore
from metagpt.logs import logger
from metagpt.actions import Action
from metagpt.actions.minecraft.player_action import PlayerActions as Action
from metagpt.const import CKPT_DIR
@ -21,21 +18,6 @@ class RetrieveSkills(Action):
def __init__(self, name="", context=None, llm=None):
super().__init__(name, context, llm)
# TODO: mv to PlayerAction
self.retrieval_top_k = 5
self.vectordb = Chroma(
collection_name="skill_vectordb",
embedding_function=OpenAIEmbeddings(),
persist_directory=f"{CKPT_DIR}/skill/vectordb",
)
# Check if skills right using
# TODO:
# assert self.vectordb._collection.count() == len(self.skills), (
# 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."
# )
async def run(self, query, skills, *args, **kwargs):
# Implement the logic for retrieving skills here.
@ -62,22 +44,6 @@ class AddNewSkills(Action):
def __init__(self, name="", context=None, llm=None):
super().__init__(name, context, llm)
# TODO: mv to PlayerAction
self.vectordb = Chroma(
collection_name="skill_vectordb",
embedding_function=OpenAIEmbeddings(),
persist_directory=f"{CKPT_DIR}/skill/vectordb",
)
# TODO: change to FaissStore
# self.qa_cache_questions_vectordb = FaissStore( {CKPT_DIR}/ 'skill/vectordb')
# TODO:
# Check if skills right using
# assert self.vectordb._collection.count() == len(self.skills), (
# 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."
# )
async def run(
self, task, program_name, program_code, skills, skill_desp, *args, **kwargs

49
metagpt/actions/minecraft/player_action.py
View file

@ -3,8 +3,57 @@
# @Author : stellahong (stellahong@fuzhi.ai)
# @Desc :
from metagpt.actions import Action
from langchain.vectorstores import Chroma
from langchain.embeddings.openai import OpenAIEmbeddings
from metagpt.document_store import FaissStore
from metagpt.const import CKPT_DIR
class PlayerActions(Action):
def __init__(self, name="", context=None, llm=None):
super().__init__(name, context, llm)
self.skills = {}
self.qa_cache = {}
self.retrieval_top_k = 5
self.vectordb = Chroma(
collection_name="skill_vectordb",
embedding_function=OpenAIEmbeddings(),
persist_directory=f"{CKPT_DIR}/skill/vectordb",
)
self.qa_cache_questions_vectordb = Chroma(
collection_name="qa_cache_questions_vectordb",
embedding_function=OpenAIEmbeddings(),
persist_directory=f"{CKPT_DIR}/curriculum/vectordb",
)
# TODO: change to FaissStore
# self.qa_cache_questions_vectordb = FaissStore( {CKPT_DIR}/ 'curriculum/vectordb'
@classmethod
def set_skills(cls, skills):
cls.skills = skills
# Check if Skill Manager's vectordb right using
assert cls.vectordb._collection.count() == len(cls.skills), (
f"Skill Manager's vectordb is not synced with skills.json.\n"
f"There are {cls.vectordb._collection.count()} skills in vectordb but {len(cls.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."
)
@classmethod
def set_qa_cache(cls, qa_cache):
cls.qa_cache = qa_cache
# Check if qa_cache right using
# Check if Skill Manager's vectordb right using
assert cls.qa_cache_questions_vectordb._collection.count() == len(
cls.qa_cache
), (
f"Curriculum Agent's qa cache question vectordb is not synced with qa_cache.json.\n"
f"There are {cls.qa_cache_questions_vectordb._collection.count()} questions in vectordb "
f"but {len(cls.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"
)
"""Minecraft player info without any implementation details"""
async def run(self, *args, **kwargs):
raise NotImplementedError

4
metagpt/actions/minecraft/review_task.py
View file

@ -15,7 +15,6 @@ class VerifyTask(Action):
def __init__(self, name="", context=None, llm=None):
super().__init__(name, context, llm)
self.vect_db = ""
async def run(self,human_msg, system_msg, max_retries=5, *args, **kwargs):
# Implement the logic to verify the task here.
@ -29,7 +28,8 @@ class VerifyTask(Action):
logger.info(f"Failed to parse Critic Agent response. Consider updating your prompt.")
return False, ""
if human_msg or system_msg is None:
if human_msg is None:
logger.warning(f"Failed to get human_msg or system_msg.")
return False, ""
critic = await self._aask(prompt=human_msg, system_msgs=system_msg)
try: