diff --git a/desktop_env/envs/desktop_env.py b/desktop_env/envs/desktop_env.py index e870b21..b12fbca 100644 --- a/desktop_env/envs/desktop_env.py +++ b/desktop_env/envs/desktop_env.py @@ -30,7 +30,7 @@ def _execute_command(command: List[str]) -> None: p = subprocess.Popen(command) p.wait() else: - result = subprocess.run(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, timeout=60, text=True) + result = subprocess.run(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, timeout=60, text=True, encoding="utf-8") if result.returncode != 0: raise Exception("\033[91m" + result.stdout + result.stderr + "\033[0m") return result.stdout diff --git a/desktop_env/evaluators/metrics/gimp.py b/desktop_env/evaluators/metrics/gimp.py index a1d3a82..30c9b68 100644 --- a/desktop_env/evaluators/metrics/gimp.py +++ b/desktop_env/evaluators/metrics/gimp.py @@ -328,6 +328,9 @@ def check_structure_sim(src_path, tgt_path): Check if the structure of the two images are similar gimp:2a729ded-3296-423d-aec4-7dd55ed5fbb3 """ + if src_path is None or tgt_path is None: + return 0. + img_src = Image.open(src_path) img_tgt = Image.open(tgt_path) structure_same = structure_check_by_ssim(img_src, img_tgt) diff --git a/evaluation_examples/examples/libreoffice_writer/66399b0d-8fda-4618-95c4-bfc6191617e9.json b/evaluation_examples/examples/libreoffice_writer/66399b0d-8fda-4618-95c4-bfc6191617e9.json index a7951e4..33b8a1a 100644 --- a/evaluation_examples/examples/libreoffice_writer/66399b0d-8fda-4618-95c4-bfc6191617e9.json +++ b/evaluation_examples/examples/libreoffice_writer/66399b0d-8fda-4618-95c4-bfc6191617e9.json @@ -27,7 +27,7 @@ "command": [ "python", "-c", - "import pyautogui; import time; time.sleep(1); pyautogui.press(\"down\", presses=40, interval=0.1); time.sleep(1); pyautogui.scroll(-2)" + "import pyautogui; import time; time.sleep(5); pyautogui.press(\"down\", presses=40, interval=10); time.sleep(1); pyautogui.scroll(-2)" ] } } diff --git a/evaluation_examples/examples/libreoffice_writer/6ada715d-3aae-4a32-a6a7-429b2e43fb93.json b/evaluation_examples/examples/libreoffice_writer/6ada715d-3aae-4a32-a6a7-429b2e43fb93.json index a7024d6..7151032 100644 --- a/evaluation_examples/examples/libreoffice_writer/6ada715d-3aae-4a32-a6a7-429b2e43fb93.json +++ b/evaluation_examples/examples/libreoffice_writer/6ada715d-3aae-4a32-a6a7-429b2e43fb93.json @@ -38,7 +38,7 @@ "command": [ "python", "-c", - "import pyautogui; import time; time.sleep(1); pyautogui.press(\"down\", presses=8); time.sleep(1); pyautogui.scroll(-2)" + "import pyautogui; import time; time.sleep(5); pyautogui.press(\"down\", presses=8, interval=3); time.sleep(1); pyautogui.scroll(-2)" ] } } diff --git a/mm_agents/gemini_pro_agent.py b/mm_agents/gemini_pro_agent.py deleted file mode 100644 index ce84488..0000000 --- a/mm_agents/gemini_pro_agent.py +++ /dev/null @@ -1,136 +0,0 @@ -# todo: needs to be refactored - -import time -from typing import Dict, List - -import google.generativeai as genai - -from mm_agents.accessibility_tree_wrap.heuristic_retrieve import find_leaf_nodes, filter_nodes -from mm_agents.gpt_4_prompt_action import SYS_PROMPT as SYS_PROMPT_ACTION -from mm_agents.gpt_4_prompt_code import SYS_PROMPT as SYS_PROMPT_CODE -from mm_agents.gpt_4v_agent import parse_actions_from_string, parse_code_from_string - - -class GeminiPro_Agent: - def __init__(self, api_key, instruction, model='gemini-pro', max_tokens=300, temperature=0.0, - action_space="computer_13"): - genai.configure(api_key=api_key) - self.instruction = instruction - self.model = genai.GenerativeModel(model) - self.max_tokens = max_tokens - self.temperature = temperature - self.action_space = action_space - - self.trajectory = [ - { - "role": "system", - "parts": [ - { - "computer_13": SYS_PROMPT_ACTION, - "pyautogui": SYS_PROMPT_CODE - }[action_space] + "\nHere is the instruction for the task: {}".format(self.instruction) - ] - } - ] - - def predict(self, obs: Dict) -> List: - """ - Predict the next action(s) based on the current observation. - Only support single-round conversation, only fill-in the last desktop screenshot. - """ - accessibility_tree = obs["accessibility_tree"] - - leaf_nodes = find_leaf_nodes(accessibility_tree) - filtered_nodes = filter_nodes(leaf_nodes) - - linearized_accessibility_tree = "tag\ttext\tposition\tsize\n" - # Linearize the accessibility tree nodes into a table format - - for node in filtered_nodes: - linearized_accessibility_tree += node.tag + "\t" - linearized_accessibility_tree += node.attrib.get('name') + "\t" - linearized_accessibility_tree += node.attrib.get( - '{uri:deskat:component.at-spi.gnome.org}screencoord') + "\t" - linearized_accessibility_tree += node.attrib.get('{uri:deskat:component.at-spi.gnome.org}size') + "\n" - - self.trajectory.append({ - "role": "user", - "parts": [ - "Given the XML format of accessibility tree (convert and formatted into table) as below:\n{}\nWhat's the next step that you will do to help with the task?".format( - linearized_accessibility_tree)] - }) - - # todo: Remove this step once the Gemini supports multi-round conversation - all_message_str = "" - for i in range(len(self.trajectory)): - if i == 0: - all_message_template = "<|im_start|>system\n{}\n<|im_end|>\n" - elif i % 2 == 1: - all_message_template = "<|im_start|>user\n{}\n<|im_end|>\n" - else: - all_message_template = "<|im_start|>assistant\n{}\n<|im_end|>\n" - - all_message_str += all_message_template.format(self.trajectory[i]["parts"][0]) - - print("All message: >>>>>>>>>>>>>>>> ") - print( - all_message_str - ) - - message_for_gemini = { - "role": "user", - "parts": [all_message_str] - } - - traj_to_show = [] - for i in range(len(self.trajectory)): - traj_to_show.append(self.trajectory[i]["parts"][0]) - if len(self.trajectory[i]["parts"]) > 1: - traj_to_show.append("screenshot_obs") - - print("Trajectory:", traj_to_show) - - while True: - try: - response = self.model.generate_content( - message_for_gemini, - generation_config={ - "max_output_tokens": self.max_tokens, - "temperature": self.temperature - } - ) - break - except: - print("Failed to generate response, retrying...") - time.sleep(5) - pass - - try: - response_text = response.text - except: - return [] - - try: - actions = self.parse_actions(response_text) - except: - print("Failed to parse action from response:", response_text) - actions = [] - - return actions - - def parse_actions(self, response: str): - # parse from the response - if self.action_space == "computer_13": - actions = parse_actions_from_string(response) - elif self.action_space == "pyautogui": - actions = parse_code_from_string(response) - else: - raise ValueError("Invalid action space: " + self.action_space) - - # add action into the trajectory - self.trajectory.append({ - "role": "assistant", - "parts": [response] - }) - - return actions diff --git a/mm_agents/gemini_pro_vision_agent.py b/mm_agents/gemini_pro_vision_agent.py deleted file mode 100644 index 4a537db..0000000 --- a/mm_agents/gemini_pro_vision_agent.py +++ /dev/null @@ -1,115 +0,0 @@ -# todo: needs to be refactored - -import time -from typing import Dict, List - -import PIL.Image -import google.generativeai as genai - -from mm_agents.gpt_4v_agent import parse_actions_from_string, parse_code_from_string -from mm_agents.gpt_4v_prompt_action import SYS_PROMPT as SYS_PROMPT_ACTION -from mm_agents.gpt_4v_prompt_code import SYS_PROMPT as SYS_PROMPT_CODE - - -class GeminiProV_Agent: - def __init__(self, api_key, instruction, model='gemini-pro-vision', max_tokens=300, temperature=0.0, - action_space="computer_13"): - genai.configure(api_key=api_key) - self.instruction = instruction - self.model = genai.GenerativeModel(model) - self.max_tokens = max_tokens - self.temperature = temperature - self.action_space = action_space - - self.trajectory = [ - { - "role": "system", - "parts": [ - { - "computer_13": SYS_PROMPT_ACTION, - "pyautogui": SYS_PROMPT_CODE - }[action_space] + "\nHere is the instruction for the task: {}".format(self.instruction) - ] - } - ] - - def predict(self, obs: Dict) -> List: - """ - Predict the next action(s) based on the current observation. - Only support single-round conversation, only fill-in the last desktop screenshot. - """ - img = PIL.Image.open(obs["screenshot"]) - self.trajectory.append({ - "role": "user", - "parts": ["What's the next step that you will do to help with the task?", img] - }) - - # todo: Remove this step once the Gemini supports multi-round conversation - all_message_str = "" - for i in range(len(self.trajectory)): - if i == 0: - all_message_template = "<|im_start|>system\n{}\n<|im_end|>\n" - elif i % 2 == 1: - all_message_template = "<|im_start|>user\n{}\n<|im_end|>\n" - else: - all_message_template = "<|im_start|>assistant\n{}\n<|im_end|>\n" - - all_message_str += all_message_template.format(self.trajectory[i]["parts"][0]) - - message_for_gemini = { - "role": "user", - "parts": [all_message_str, img] - } - - traj_to_show = [] - for i in range(len(self.trajectory)): - traj_to_show.append(self.trajectory[i]["parts"][0]) - if len(self.trajectory[i]["parts"]) > 1: - traj_to_show.append("screenshot_obs") - - print("Trajectory:", traj_to_show) - - while True: - try: - response = self.model.generate_content( - message_for_gemini, - generation_config={ - "max_output_tokens": self.max_tokens, - "temperature": self.temperature - } - ) - break - except: - print("Failed to generate response, retrying...") - time.sleep(5) - pass - - try: - response_text = response.text - except: - return [] - - try: - actions = self.parse_actions(response_text) - except: - print("Failed to parse action from response:", response_text) - actions = [] - - return actions - - def parse_actions(self, response: str): - # parse from the response - if self.action_space == "computer_13": - actions = parse_actions_from_string(response) - elif self.action_space == "pyautogui": - actions = parse_code_from_string(response) - else: - raise ValueError("Invalid action space: " + self.action_space) - - # add action into the trajectory - self.trajectory.append({ - "role": "assistant", - "parts": [response] - }) - - return actions diff --git a/mm_agents/gpt_4v_agent.py b/mm_agents/gpt_4v_agent.py index 0dd15cf..68c07f3 100644 --- a/mm_agents/gpt_4v_agent.py +++ b/mm_agents/gpt_4v_agent.py @@ -1,12 +1,20 @@ import base64 import json +import logging import os import re +import time import uuid +from http import HTTPStatus +from io import BytesIO from typing import Dict, List import backoff +import dashscope +import google.generativeai as genai +import openai import requests +from PIL import Image from openai.error import ( APIConnectionError, APIError, @@ -22,8 +30,6 @@ from mm_agents.prompts import SYS_PROMPT_IN_SCREENSHOT_OUT_CODE, SYS_PROMPT_IN_S SYS_PROMPT_IN_SOM_A11Y_OUT_TAG, \ SYS_PROMPT_SEEACT, ACTION_DESCRIPTION_PROMPT_SEEACT, ACTION_GROUNDING_PROMPT_SEEACT -import logging - logger = logging.getLogger("desktopenv.agent") @@ -44,11 +50,13 @@ def linearize_accessibility_tree(accessibility_tree): linearized_accessibility_tree += node.tag + "\t" linearized_accessibility_tree += node.attrib.get('name') + "\t" if node.text: - linearized_accessibility_tree += (node.text if '"' not in node.text else '"{:}"'.format(node.text.replace('"', '""'))) + "\t" - elif node.get("{uri:deskat:uia.windows.microsoft.org}class", "").endswith("EditWrapper")\ + linearized_accessibility_tree += (node.text if '"' not in node.text else '"{:}"'.format( + node.text.replace('"', '""'))) + "\t" + elif node.get("{uri:deskat:uia.windows.microsoft.org}class", "").endswith("EditWrapper") \ and node.get("{uri:deskat:value.at-spi.gnome.org}value"): text: str = node.get("{uri:deskat:value.at-spi.gnome.org}value") - linearized_accessibility_tree += (text if '"' not in text else '"{:}"'.format(text.replace('"', '""'))) + "\t" + linearized_accessibility_tree += (text if '"' not in text else '"{:}"'.format( + text.replace('"', '""'))) + "\t" else: linearized_accessibility_tree += '""\t' linearized_accessibility_tree += node.attrib.get( @@ -145,10 +153,21 @@ def parse_code_from_som_string(input_string, masks): x, y, w, h = mask mappings.append(("tag#" + str(i + 1), "{}, {}".format(int(x + w // 2), int(y + h // 2)))) - # reverse the mappings - for mapping in mappings[::-1]: - input_string = input_string.replace(mapping[0], mapping[1]) + def replace_tags_with_mappings(text, mappings): + pattern = r'tag#\d+' + matches = re.findall(pattern, text) + for match in matches: + for mapping in mappings: + if match == mapping[0]: + text = text.replace(match, mapping[1]) + break + logger.error("Predicting the tag with index {} failed.".format(match)) + return "" + + return text + + input_string = replace_tags_with_mappings(input_string, mappings) actions = parse_code_from_string(input_string) return actions @@ -295,7 +314,7 @@ class GPT4v_Agent: { "type": "image_url", "image_url": { - "url": f"data:image/jpeg;base64,{_screenshot}", + "url": f"data:image/png;base64,{_screenshot}", "detail": "high" } } @@ -314,7 +333,7 @@ class GPT4v_Agent: { "type": "image_url", "image_url": { - "url": f"data:image/jpeg;base64,{_screenshot}", + "url": f"data:image/png;base64,{_screenshot}", "detail": "high" } } @@ -375,7 +394,7 @@ class GPT4v_Agent: { "type": "image_url", "image_url": { - "url": f"data:image/jpeg;base64,{base64_image}", + "url": f"data:image/png;base64,{base64_image}", "detail": "high" } } @@ -421,7 +440,7 @@ class GPT4v_Agent: { "type": "image_url", "image_url": { - "url": f"data:image/jpeg;base64,{base64_image}", + "url": f"data:image/png;base64,{base64_image}", "detail": "high" } } @@ -448,7 +467,7 @@ class GPT4v_Agent: { "type": "image_url", "image_url": { - "url": f"data:image/jpeg;base64,{base64_image}", + "url": f"data:image/png;base64,{base64_image}", "detail": "high" } } @@ -510,32 +529,130 @@ class GPT4v_Agent: @backoff.on_exception( backoff.expo, (APIError, RateLimitError, APIConnectionError, ServiceUnavailableError, InvalidRequestError), - max_tries=3 + max_tries=10 ) def call_llm(self, payload): - response = requests.post( - "https://api.openai.com/v1/chat/completions", - headers=self.headers, - json=payload - ) + if self.model.startswith("gpt"): + response = requests.post( + "https://api.openai.com/v1/chat/completions", + headers=self.headers, + json=payload + ) - if response.status_code != 200: - if response.json()['error']['code'] == "context_length_exceeded": - print("Context length exceeded. Retrying with a smaller context.") - payload["messages"] = payload["messages"][-1:] - retry_response = requests.post( - "https://api.openai.com/v1/chat/completions", - headers=self.headers, - json=payload - ) - if retry_response.status_code != 200: - print("Failed to call LLM: " + retry_response.text) + if response.status_code != 200: + if response.json()['error']['code'] == "context_length_exceeded": + print("Context length exceeded. Retrying with a smaller context.") + payload["messages"] = payload["messages"][-1:] + retry_response = requests.post( + "https://api.openai.com/v1/chat/completions", + headers=self.headers, + json=payload + ) + if retry_response.status_code != 200: + print("Failed to call LLM: " + retry_response.text) + return "" + + print("Failed to call LLM: " + response.text) + time.sleep(5) + return "" + else: + return response.json()['choices'][0]['message']['content'] + + elif self.model.startswith("mistral"): + messages = payload["messages"] + max_tokens = payload["max_tokens"] + + openai.api_base = "http://localhost:8000/v1" + openai.api_key = "test" + response = openai.ChatCompletion.create( + messages=messages, + model="Mixtral-8x7B-Instruct-v0.1", + max_tokens=max_tokens + ) + try: + return response['choices'][0]['message']['content'] + except Exception as e: + return "" + + elif self.model.startswith("gemini"): + + api_key = os.environ.get("GENAI_API_KEY") + genai.api_key = api_key + def encoded_img_to_pil_img(data_str): + base64_str = data_str.replace("data:image/png;base64,", "") + image_data = base64.b64decode(base64_str) + image = Image.open(BytesIO(image_data)) + + return image + + messages = payload["messages"] + max_tokens = payload["max_tokens"] + + gemini_messages = [] + for i, message in enumerate(messages): + gemini_message = { + "role": message["role"], + "parts": [] + } + assert len(message["content"]) in [1, 2], "One text, or one text with one image" + + # The gemini only support the last image as single image input + if i == len(messages) - 1: + for part in message["content"]: + gemini_message['parts'].append(part['text']) if part['type'] == "text" \ + else gemini_message['parts'].append(encoded_img_to_pil_img(part['image_url']['url'])) + else: + for part in message["content"]: + gemini_message['parts'].append(part['text']) if part['type'] == "text" else None + + gemini_messages.append(gemini_message) + + response = genai.GenerativeModel(self.model).generate_content( + gemini_messages, + generation_config={ + "max_output_tokens": max_tokens + } + ) + + try: + return response.text + except Exception as e: + return "" + elif self.model.startswith("qwen"): + messages = payload["messages"] + max_tokens = payload["max_tokens"] + + qwen_messages = [] + + for i, message in enumerate(messages): + qwen_message = { + "role": message["role"], + "content": [] + } + assert len(message["content"]) in [1, 2], "One text, or one text with one image" + for part in message["content"]: + qwen_message['content'].append({"image": part['image_url']['url']}) if part['type'] == "image_url" else None + qwen_message['content'].append({"text": part['text']}) if part['type'] == "text" else None + + qwen_messages.append(qwen_message) + + response = dashscope.MultiModalConversation.call(model='qwen-vl-plus', + messages=messages) + # The response status_code is HTTPStatus.OK indicate success, + # otherwise indicate request is failed, you can get error code + # and message from code and message. + if response.status_code == HTTPStatus.OK: + try: + return response.json()['output']['choices'][0]['message']['content'] + except Exception as e: return "" + else: + print(response.code) # The error code. + print(response.message) # The error message. + return "" - print("Failed to call LLM: " + response.text) - return "" else: - return response.json()['choices'][0]['message']['content'] + raise ValueError("Invalid model: " + self.model) def parse_actions(self, response: str, masks=None):