update role with pre-init role&env

examples/st_game/actions/agent_chat_sum_rel.py

@@ -29,7 +29,7 @@ class AgentChatSumRel(STAction):
     def _func_fail_default_resp(self) -> str:
         pass
 
-    async def run(self, init_role: STRole, target_role: STRole, statements: str) -> str:
+    def run(self, init_role: STRole, target_role: STRole, statements: str) -> str:
         def create_prompt_input(init_role: STRole, target_role: STRole, statements: str) -> str:
             prompt_input = [statements, init_role.name, target_role.name]
             return prompt_input
@@ -40,7 +40,7 @@ class AgentChatSumRel(STAction):
 
         example_output = "Jane Doe is working on a project"
         special_instruction = "The output should be a string that responds to the question."
-        output = await self._run_v2(prompt,
-                                    example_output,
-                                    special_instruction)
+        output = self._run_v2(prompt,
+                              example_output,
+                              special_instruction)
         return output[0]

examples/st_game/actions/decide_to_talk.py

@@ -29,7 +29,7 @@ class DecideToTalk(STAction):
     def _func_fail_default_resp(self) -> str:
         return "yes"
 
-    async def run(self, init_role: STRole, target_role: STRole, retrieved: dict, *args, **kwargs) -> bool:
+    def run(self, init_role: STRole, target_role: STRole, retrieved: dict, *args, **kwargs) -> bool:
         """Run action"""
         def create_prompt_input(init_role: STRole, target_role: STRole, retrieved: dict) -> str:
             scratch = init_role._rc.scratch
@@ -94,7 +94,7 @@ class DecideToTalk(STAction):
         prompt = self.generate_prompt_with_tmpl_filename(prompt_input=prompt_input,
                                                          tmpl_filename="decide_to_talk_v2.txt")
         self.fail_default_resp = self._func_fail_default_resp()
-        output = await self._run_v1(prompt)  # yes or no
+        output = self._run_v1(prompt)  # yes or no
         result = True if output == "yes" else False
         logger.info(f"Run action: {self.__class__.__name__} with result: {result}")
         return result

examples/st_game/actions/gen_iter_chat_utt.py

@@ -45,8 +45,8 @@ class GenIterChatUTT(STAction):
         cleaned_dict["end"] = False
         return cleaned_dict
 
-    async def run(self, maze: Maze, init_role: STRole, target_role: STRole, retrieved: dict, curr_context: str,
-                  curr_chat: list[str], *args, **kwargs) -> dict:
+    def run(self, maze: Maze, init_role: STRole, target_role: STRole, retrieved: dict, curr_context: str,
+            curr_chat: list[str], *args, **kwargs) -> dict:
         def create_prompt_input(maze: Maze, init_role: STRole, target_role: STRole,
                                 retrieved: dict, curr_context: str, curr_chat: list[str]):
             role = init_role
@@ -97,5 +97,5 @@ class GenIterChatUTT(STAction):
                                                          "iterative_convo_v1.txt")
         # original using `ChatGPT_safe_generate_response_OLD`
         self.fail_default_resp = self._func_fail_default_resp()
-        output = await self._run_v1(prompt)
+        output = self._run_v1(prompt)
         return output

examples/st_game/actions/new_decomp_schedule.py

@@ -85,15 +85,15 @@ class NewDecompSchedule(STAction):
 
         return ret
 
-    async def run(self,
-                  role: STRole,
-                  main_act_dur: int,
-                  truncated_act_dur: int,
-                  start_time_hour: datetime,
-                  end_time_hour: datetime,
-                  inserted_act: str,
-                  inserted_act_dur: int,
-                  *args, **kwargs):
+    def run(self,
+            role: STRole,
+            main_act_dur: int,
+            truncated_act_dur: int,
+            start_time_hour: datetime,
+            end_time_hour: datetime,
+            inserted_act: str,
+            inserted_act_dur: int,
+            *args, **kwargs):
 
         def create_prompt_input(role: STRole,
                                 main_act_dur: int,
@@ -149,5 +149,5 @@ class NewDecompSchedule(STAction):
         prompt = self.generate_prompt_with_tmpl_filename(prompt_input,
                                                          "new_decomp_schedule_v1.txt")
         self.fail_default_resp = self._func_fail_default_resp(main_act_dur, truncated_act_dur)
-        output = await self._run_v1(prompt)
+        output = self._run_v1(prompt)
         return output

examples/st_game/actions/st_action.py

@@ -2,7 +2,7 @@
 # -*- coding: utf-8 -*-
 # @Desc   : StanfordTown Action
 
-from typing import Union
+from typing import Union, Optional
 from abc import abstractmethod
 import json
 
@@ -53,22 +53,25 @@ class STAction(Action):
             prompt = prompt.split("<commentblockmarker>###</commentblockmarker>")[1]
         return prompt.strip()
 
-    async def _run_v1(self, prompt: str, retry: int = 3) -> str:
+    def _ask(self, prompt: str, system_msgs: Optional[list[str]] = None) -> str:
+        return self.llm.ask(prompt)
+
+    def _run_v1(self, prompt: str, retry: int = 3) -> str:
         """
             same with `gpt_structure.safe_generate_response`
             default post-preprocess operations of LLM response
         """
         for idx in range(retry):
-            llm_resp = await self._aask(prompt)
+            llm_resp = self._ask(prompt)
             if self._func_validate(llm_resp, prompt):
                 return self._func_cleanup(llm_resp, prompt)
-        return self.fail_default_resp  # TODO fix
+        return self.fail_default_resp
 
-    async def _run_v2(self,
-                      prompt: str,
-                      example_output: str,
-                      special_instruction: str,
-                      retry: int = 3):
+    def _run_v2(self,
+                prompt: str,
+                example_output: str,
+                special_instruction: str,
+                retry: int = 3):
         """ same with `gpt_structure.ChatGPT_safe_generate_response` """
         prompt = '"""\n' + prompt + '\n"""\n'
         prompt += f"Output the response to the prompt above in json. {special_instruction}\n"
@@ -77,7 +80,8 @@ class STAction(Action):
 
         for idx in range(retry):
             try:
-                llm_resp = await self._aask(prompt)
+                llm_resp = self._ask(prompt)
+                print("llm_resp ", llm_resp)
                 end_idx = llm_resp.strip().rfind("}") + 1
                 llm_resp = llm_resp[:end_idx]
                 llm_resp = json.loads(llm_resp)["output"]
@@ -88,6 +92,6 @@ class STAction(Action):
                 pass
         return False
 
-    async def run(self, *args, **kwargs):
+    def run(self, *args, **kwargs):
         """Run action"""
         raise NotImplementedError("The run method should be implemented in a subclass.")

examples/st_game/actions/summarize_conv.py

@@ -28,7 +28,7 @@ class SummarizeConv(STAction):
     def _func_fail_default_resp(self) -> str:
         return "conversing with a housemate about morning greetings"
 
-    async def run(self, conv: list):
+    def run(self, conv: list):
         def create_prompt_input(conversation: list):
             convo_str = ""
             for row in conversation:
@@ -44,5 +44,5 @@ class SummarizeConv(STAction):
         special_instruction = "The output must continue the sentence above by filling in the <fill in> tag. " \
                               "Don't start with 'this is a conversation about...' Just finish the sentence " \
                               "but do not miss any important details (including who are chatting)."
-        output = await self._run_v2(prompt, example_output, special_instruction)
+        output = self._run_v2(prompt, example_output, special_instruction)
         return output

examples/st_game/maze_environment.py

@@ -2,13 +2,18 @@
 # -*- coding: utf-8 -*-
 # @Desc   : maze environment
 
+from pydantic import Field
+
 from metagpt.environment import Environment
+from metagpt.roles.role import Role
+
 from .maze import Maze
 
 
 class MazeEnvironment(Environment):
-    def __init__(self, name: str, maze: Maze) -> None:
-        self.name = name
-        self.maze = maze
 
-    
+    maze: Maze = Field(default=Maze)
+
+    def add_role(self, role: Role):
+        role.set_env(self)
+        self.roles[role.name] = role  # use role.name as key not role.profile

examples/st_game/roles/st_role.py

@@ -11,12 +11,17 @@ Do the steps following:
 - execute, move or else in the Maze
 """
 import math
+import time
+
 from pydantic import Field
 from pathlib import Path
+import random
+import datetime
 from operator import itemgetter
 
 from metagpt.roles.role import Role, RoleContext
 from metagpt.schema import Message
+from metagpt.logs import logger
 
 from ..memory.agent_memory import AgentMemory, BasicMemory
 from ..memory.spatial_memory import MemoryTree
@@ -25,13 +30,14 @@ from ..actions.user_requirement import UserRequirement
 from ..maze_environment import MazeEnvironment
 from ..memory.retrieve import agent_retrieve
 from ..memory.scratch import Scratch
-from ..utils.utils import get_embedding, generate_poig_score
-
+from ..utils.utils import get_embedding, generate_poig_score, path_finder
+from ..utils.const import collision_block_id
 from ..reflect.st_reflect import agent_reflect
+from ..utils.mg_ga_transform import save_movement, get_role_environment
 
 
 class STRoleContext(RoleContext):
-    env: 'MazeEnvironment' = Field(default=None)
+    env: 'MazeEnvironment' = Field(default=MazeEnvironment)
     memory: AgentMemory = Field(default=AgentMemory)
     scratch: Scratch = Field(default=Scratch)
     spatial_memory: MemoryTree = Field(default=MemoryTree)
@@ -44,9 +50,21 @@ class STRole(Role):
     def __init__(self,
                  name: str = "Klaus Mueller",
                  profile: str = "STMember",
-                 sim_path: str = "new_sim",
+                 sim_code: str = "new_sim",
+                 step: int = 0,
+                 start_date: str = "",
+                 curr_time: str = "",
+                 sec_per_step: int = 10,
                  has_inner_voice: bool = False):
-        self.sim_path = sim_path
+        self.sim_code = sim_code
+        self.step = step
+        self.start_time = datetime.datetime.strptime(f"{start_date}, 00:00:00", "%B %d, %Y, %H:%M:%S")
+        self.curr_time = datetime.datetime.strptime(curr_time, "%B %d, %Y, %H:%M:%S")
+        self.sec_per_step = sec_per_step
+
+        self.role_tile = (0, 0)
+        self.game_obj_cleanup = dict()
+
         self._rc = STRoleContext()
         super(STRole, self).__init__(name=name,
                                      profile=profile)
@@ -59,10 +77,21 @@ class STRole(Role):
         else:
             self._watch([DummyAction])
 
+        # init role & maze
+        role_env = get_role_environment(self.sim_code, self.name, self.step)
+        pt_x = role_env["x"]
+        pt_y = role_env["y"]
+        self.role_tile = (pt_x, pt_y)
+        self._rc.env.maze.tiles[pt_y][pt_x]["events"].add(self.scratch.get_curr_event_and_desc())
+
     @property
     def name(self):
         return self._setting.name
 
+    @property
+    def scratch(self):
+        return self._rc.scratch
+
     def load_from(self, folder: Path):
         """
         load role data from `storage/{simulation_name}/personas/{role_name}
@@ -238,15 +267,197 @@ class STRole(Role):
         # TODO re-add result to memory
         pass
 
+    def execute(self, plan: str):
+        """
+        Args:
+            plan: This is a string address of the action we need to execute.
+            It comes in the form of "{world}:{sector}:{arena}:{game_objects}".
+            It is important that you access this without doing negative
+            indexing (e.g., [-1]) because the latter address elements may not be
+            present in some cases.
+            e.g., "dolores double studio:double studio:bedroom 1:bed"
+        """
+        roles = self._rc.env.get_roles()
+        maze = self._rc.env.maze
+        if "<random>" in plan and self._rc.scratch.planned_path == []:
+            self._rc.scratch.act_path_set = False
+
+        # <act_path_set> is set to True if the path is set for the current action.
+        # It is False otherwise, and means we need to construct a new path.
+        if not self._rc.scratch.act_path_set:
+            # <target_tiles> is a list of tile coordinates where the persona may go
+            # to execute the current action. The goal is to pick one of them.
+            target_tiles = None
+            logger.info("plan: ", plan)
+
+            if "<persona>" in plan:
+                # Executing persona-persona interaction.
+                target_p_tile = (roles[plan.split("<persona>")[-1].strip()]
+                                 .scratch.curr_tile)
+                potential_path = path_finder(maze.collision_maze,
+                                             self._rc.scratch.curr_tile,
+                                             target_p_tile,
+                                             collision_block_id)
+                if len(potential_path) <= 2:
+                    target_tiles = [potential_path[0]]
+                else:
+                    potential_1 = path_finder(maze.collision_maze,
+                                              self._rc.scratch.curr_tile,
+                                              potential_path[int(len(potential_path) / 2)],
+                                              collision_block_id)
+                    potential_2 = path_finder(maze.collision_maze,
+                                              self._rc.scratch.curr_tile,
+                                              potential_path[int(len(potential_path) / 2) + 1],
+                                              collision_block_id)
+                    if len(potential_1) <= len(potential_2):
+                        target_tiles = [potential_path[int(len(potential_path) / 2)]]
+                    else:
+                        target_tiles = [potential_path[int(len(potential_path) / 2 + 1)]]
+
+            elif "<waiting>" in plan:
+                # Executing interaction where the persona has decided to wait before
+                # executing their action.
+                x = int(plan.split()[1])
+                y = int(plan.split()[2])
+                target_tiles = [[x, y]]
+
+            elif "<random>" in plan:
+                # Executing a random location action.
+                plan = ":".join(plan.split(":")[:-1])
+                target_tiles = maze.address_tiles[plan]
+                target_tiles = random.sample(list(target_tiles), 1)
+
+            else:
+                # This is our default execution. We simply take the persona to the
+                # location where the current action is taking place.
+                # Retrieve the target addresses. Again, plan is an action address in its
+                # string form. <maze.address_tiles> takes this and returns candidate
+                # coordinates.
+                if plan not in maze.address_tiles:
+                    maze.address_tiles["Johnson Park:park:park garden"]  # ERRORRRRRRR
+                else:
+                    target_tiles = maze.address_tiles[plan]
+
+            # There are sometimes more than one tile returned from this (e.g., a tabe
+            # may stretch many coordinates). So, we sample a few here. And from that
+            # random sample, we will take the closest ones.
+            if len(target_tiles) < 4:
+                target_tiles = random.sample(list(target_tiles), len(target_tiles))
+            else:
+                target_tiles = random.sample(list(target_tiles), 4)
+            # If possible, we want personas to occupy different tiles when they are
+            # headed to the same location on the maze. It is ok if they end up on the
+            # same time, but we try to lower that probability.
+            # We take care of that overlap here.
+            persona_name_set = set(roles.keys())
+            new_target_tiles = []
+            for i in target_tiles:
+                curr_event_set = maze.access_tile(i)["events"]
+                pass_curr_tile = False
+                for j in curr_event_set:
+                    if j[0] in persona_name_set:
+                        pass_curr_tile = True
+                if not pass_curr_tile:
+                    new_target_tiles += [i]
+            if len(new_target_tiles) == 0:
+                new_target_tiles = target_tiles
+            target_tiles = new_target_tiles
+
+            # Now that we've identified the target tile, we find the shortest path to
+            # one of the target tiles.
+            curr_tile = self._rc.scratch.curr_tile
+            collision_maze = maze.collision_maze
+            closest_target_tile = None
+            path = None
+            for i in target_tiles:
+                # path_finder takes a collision_mze and the curr_tile coordinate as
+                # an input, and returns a list of coordinate tuples that becomes the
+                # path.
+                # e.g., [(0, 1), (1, 1), (1, 2), (1, 3), (1, 4)...]
+                curr_path = path_finder(maze.collision_maze,
+                                        curr_tile,
+                                        i,
+                                        collision_block_id)
+                if not closest_target_tile:
+                    closest_target_tile = i
+                    path = curr_path
+                elif len(curr_path) < len(path):
+                    closest_target_tile = i
+                    path = curr_path
+
+            # Actually setting the <planned_path> and <act_path_set>. We cut the
+            # first element in the planned_path because it includes the curr_tile.
+            self._rc.scratch.planned_path = path[1:]
+            self._rc.scratch.act_path_set = True
+
+        # Setting up the next immediate step. We stay at our curr_tile if there is
+        # no <planned_path> left, but otherwise, we go to the next tile in the path.
+        ret = self._rc.scratch.curr_tile
+        if self._rc.scratch.planned_path:
+            ret = self._rc.scratch.planned_path[0]
+            self._rc.scratch.planned_path = self._rc.scratch.planned_path[1:]
+
+        description = f"{self._rc.scratch.act_description}"
+        description += f" @ {self._rc.scratch.act_address}"
+
+        execution = ret, self._rc.scratch.act_pronunciatio, description
+        return execution
+
+    def update_role_env(self) -> bool:
+        role_env = get_role_environment(self.sim_code, self.name, self.step)
+        ret = True
+        if role_env:
+            for key, val in self.game_obj_cleanup.items():
+                self._rc.env.maze.turn_event_from_tile_idle(key, val)
+
+            # reset game_obj_cleanup
+            self.game_obj_cleanup = dict()
+            curr_tile = self.role_tile
+            new_tile = (role_env["x"], role_env["y"])
+            self._rc.env.maze.remove_subject_events_from_tile(self.name, curr_tile)
+            self._rc.env.maze.add_event_from_tile(self.scratch.get_curr_event_and_desc(), new_tile)
+
+            # the persona will travel to get to their destination. *Once*
+            # the persona gets there, we activate the object action.
+            if not self.scratch.planned_path:
+                self.game_obj_cleanup[self.scratch.get_curr_event_and_desc()] = new_tile
+                self._rc.env.maze.add_event_from_tile(self.scratch.get_curr_event_and_desc(), new_tile)
+                blank = (self.scratch.get_curr_obj_event_and_desc()[0], None, None, None)
+                self._rc.env.maze.remove_event_from_tile(blank, new_tile)
+        else:
+            ret = False
+            time.sleep(1)
+            logger.warning(f"{self.sim_code}/environment/{self.step}.json not exist or parses failed,"
+                           f"sleep 1s and re-check")
+        return ret
+
     async def _react(self) -> Message:
-        maze_env = self._rc.env
+        # update role env
+        ret = self.update_role_env()
+        if not ret:
+            # TODO add message
+            return
+
         # TODO observe
         # get maze_env from self._rc.env, and observe env info
 
         # TODO retrieve, use self._rc.memory 's retrieve functions
 
         # TODO plan
+        plan = self.plan()
 
         # TODO reflect
 
         # TODO execute(feed-back into maze_env)
+        next_tile, pronunciatio, description = self.execute(plan)
+        role_move = {
+            "movement": next_tile,
+            "pronunciatio": pronunciatio,
+            "description": description,
+            "chat": self.scratch.chat
+        }
+        save_movement(self.name, role_move, step=self.step, sim_code=self.sim_code, curr_time=self.curr_time)
+
+        # step update
+        self.step += 1
+        self.curr_time += datetime.timedelta(seconds=self.sec_per_step)

examples/st_game/run_st_game.py

@@ -21,12 +21,17 @@ async def startup(idea: str,
     reverie_meta = get_reverie_meta(fork_sim_code)
     roles = []
     sim_path = STORAGE_PATH.joinpath(sim_code)
+    sim_path.mkdir(exist_ok=True)
     for idx, role_name in enumerate(reverie_meta["persona_names"]):
         role_stg_path = STORAGE_PATH.joinpath(fork_sim_code).joinpath(f"personas/{role_name}")
         has_inner_voice = True if idx == 0 else False
         role = STRole(name=role_name,
-                      sim_path=sim_path,
+                      sim_code=sim_code,
                       profile=f"STMember_{idx}",
+                      step=reverie_meta.get("step", 0),
+                      start_date=reverie_meta.get("start_date"),
+                      curr_time=reverie_meta.get("curr_time"),
+                      sec_per_step=reverie_meta.get("sec_per_step"),
                       has_inner_voice=has_inner_voice)
         role.load_from(role_stg_path)
         roles.append(role)
@@ -35,7 +40,7 @@ async def startup(idea: str,
     town.wakeup_roles(roles)
 
     town.invest(investment)
-    town.start_project()
+    town.start_project(idea)
 
     await town.run(n_round)
 

examples/st_game/tests/actions/test_summarize_conv.py

@@ -0,0 +1,17 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# @Desc   : unittest of actions/summarize_conv
+
+from metagpt.logs import logger
+
+from st_game.actions.summarize_conv import SummarizeConv
+
+
+def test_summarize_conv():
+    conv = [
+        ("Role_A", "what's the weather today?"),
+        ("Role_B", "It looks pretty good, and I will take a walk then.")
+    ]
+
+    output = SummarizeConv().run(conv)
+    assert "weather" in output

examples/st_game/utils/check.py

@@ -1,14 +1,15 @@
-def check_if_file_exists(curr_file): 
-  """
-  Checks if a file exists
-  ARGS:
-    curr_file: path to the current csv file. 
-  RETURNS: 
-    True if the file exists
-    False if the file does not exist
-  """
-  try: 
-    with open(curr_file) as f_analysis_file: pass
-    return True
-  except: 
-    return False
+def check_if_file_exists(curr_file):
+    """
+    Checks if a file exists
+    ARGS:
+      curr_file: path to the current csv file.
+    RETURNS:
+      True if the file exists
+      False if the file does not exist
+    """
+    try:
+        with open(curr_file) as f_analysis_file:
+            pass
+        return True
+    except Exception as exp:
+        return False

examples/st_game/utils/const.py

@@ -8,3 +8,5 @@ ROOT_PATH = Path(__file__).parent.parent
 STORAGE_PATH = ROOT_PATH.joinpath("storage")
 MAZE_ASSET_PATH = ROOT_PATH.joinpath("static_dirs/assets/the_ville")
 PROMPTS_DIR = ROOT_PATH.joinpath("prompts")
+
+collision_block_id = "32125"

examples/st_game/utils/mg_ga_transform.py

@@ -2,6 +2,10 @@
 # -*- coding: utf-8 -*-
 # @Desc   : data transform of mg <-> ga under storage
 
+import json
+
+from metagpt.logs import logger
+
 from .const import STORAGE_PATH
 from .utils import read_json_file, write_json_file
 
@@ -10,3 +14,32 @@ def get_reverie_meta(sim_code: str) -> dict:
     meta_file_path = STORAGE_PATH.joinpath(sim_code).joinpath("reverie/meta.json")
     reverie_meta = read_json_file(meta_file_path)
     return reverie_meta
+
+
+def save_movement(role_name: str, role_move: dict, step: int, sim_code: str, curr_time: str):
+    movement_path = STORAGE_PATH.joinpath(f"{sim_code}/movement/{step}.json")
+    if not movement_path.parent.exists():
+        movement_path.parent.mkdir(exist_ok=True)
+    if movement_path.exists():
+        with open(movement_path, "r") as fin:
+            movement = json.load(fin)
+    else:
+        movement = {
+            "persona": dict(),
+            "meta": dict()
+        }
+    movement["persona"][role_name] = role_move
+    movement["meta"]["curr_time"] = curr_time.strftime("%B %d, %Y, %H:%M:%S")
+
+    write_json_file(movement_path, movement)
+    logger.info(f"save_movement at step: {step}, curr_time: {movement['meta']['curr_time']}")
+
+
+def get_role_environment(sim_code: str, role_name: str, step: int = 0) -> dict:
+    env_path = STORAGE_PATH.joinpath(f"{sim_code}/environment/{step}.json")
+    role_env = None
+    if env_path.exists():
+        environment = read_json_file(env_path)
+        role_env = environment.get(role_name, None)
+
+    return role_env

examples/st_game/utils/utils.py

@@ -29,12 +29,12 @@ def write_json_file(json_file: str, data: list, encoding=None):
 
 def read_csv_to_list(curr_file: str, header=False, strip_trail=True):
     """
-    Reads in a csv file to a list of list. If header is True, it returns a 
+    Reads in a csv file to a list of list. If header is True, it returns a
     tuple with (header row, all rows)
     ARGS:
-      curr_file: path to the current csv file. 
-    RETURNS: 
-      List of list where the component lists are the rows of the file. 
+      curr_file: path to the current csv file.
+    RETURNS:
+      List of list where the component lists are the rows of the file.
     """
     if not header:
         analysis_list = []
@@ -92,3 +92,87 @@ def extract_first_json_dict(data_str: str) -> Union[None, dict]:
     except json.JSONDecodeError:
         # If parsing fails, return None
         return None
+
+
+def path_finder_v2(a, start, end, collision_block_char) -> list[int]:
+    def make_step(m, k):
+        for i in range(len(m)):
+            for j in range(len(m[i])):
+                if m[i][j] == k:
+                    if i > 0 and m[i - 1][j] == 0 and a[i - 1][j] == 0:
+                        m[i - 1][j] = k + 1
+                    if j > 0 and m[i][j - 1] == 0 and a[i][j - 1] == 0:
+                        m[i][j - 1] = k + 1
+                    if i < len(m) - 1 and m[i + 1][j] == 0 and a[i + 1][j] == 0:
+                        m[i + 1][j] = k + 1
+                    if j < len(m[i]) - 1 and m[i][j + 1] == 0 and a[i][j + 1] == 0:
+                        m[i][j + 1] = k + 1
+
+    new_maze = []
+    for row in a:
+        new_row = []
+        for j in row:
+            if j == collision_block_char:
+                new_row += [1]
+            else:
+                new_row += [0]
+        new_maze += [new_row]
+    a = new_maze
+
+    m = []
+    for i in range(len(a)):
+        m.append([])
+        for j in range(len(a[i])):
+            m[-1].append(0)
+    i, j = start
+    m[i][j] = 1
+
+    k = 0
+    except_handle = 150
+    while m[end[0]][end[1]] == 0:
+        k += 1
+        make_step(m, k)
+
+        if except_handle == 0:
+            break
+        except_handle -= 1
+
+    i, j = end
+    k = m[i][j]
+    the_path = [(i, j)]
+    while k > 1:
+        if i > 0 and m[i - 1][j] == k - 1:
+            i, j = i - 1, j
+            the_path.append((i, j))
+            k -= 1
+        elif j > 0 and m[i][j - 1] == k - 1:
+            i, j = i, j - 1
+            the_path.append((i, j))
+            k -= 1
+        elif i < len(m) - 1 and m[i + 1][j] == k - 1:
+            i, j = i + 1, j
+            the_path.append((i, j))
+            k -= 1
+        elif j < len(m[i]) - 1 and m[i][j + 1] == k - 1:
+            i, j = i, j + 1
+            the_path.append((i, j))
+            k -= 1
+
+    the_path.reverse()
+    return the_path
+
+
+def path_finder(maze: "Maze", start: list[int], end: list[int], collision_block_char: str) -> list[int]:
+    # EMERGENCY PATCH
+    start = (start[1], start[0])
+    end = (end[1], end[0])
+    # END EMERGENCY PATCH
+
+    path = path_finder_v2(maze, start, end, collision_block_char)
+
+    new_path = []
+    for i in path:
+        new_path += [(i[1], i[0])]
+    path = new_path
+
+    return path