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print("AI research notes:\n", search_note) + pretty_print(f"AI notes:\n{search_note}", color="success") return f""" Following a human request: {user_query} diff --git a/sources/browser.py b/sources/browser.py index daf5443..5bf511c 100644 --- a/sources/browser.py +++ b/sources/browser.py @@ -275,7 +275,6 @@ class Browser: def get_form_inputs(self) -> List[str]: """Extract all input from the page and return them.""" try: - #input_elements = self.driver.find_elements(By.TAG_NAME, "input") input_elements = self.find_all_inputs() if not input_elements: return ["No input forms found on the page."] @@ -409,7 +408,7 @@ class Browser: self.driver.execute_script( "window.scrollTo(0, document.body.scrollHeight);" ) - time.sleep(1) # Wait for scroll to complete + time.sleep(1) return True except Exception as e: self.logger.error(f"Error scrolling: {str(e)}") diff --git a/sources/language.py b/sources/language.py index d1fcde8..f2bde5d 100644 --- a/sources/language.py +++ b/sources/language.py @@ -1,17 +1,35 @@ from typing import List, Tuple, Type, Dict, Tuple -import langid import re +import langid import nltk from nltk.sentiment.vader import SentimentIntensityAnalyzer +from transformers import MarianMTModel, MarianTokenizer + +from sources.utility import pretty_print, animate_thinking class LanguageUtility: """LanguageUtility for language, or emotion identification""" def __init__(self): + self.sid = None + self.translators_tokenizer = None + self.translators_model = None + self.load_model() + + def load_model(self) -> None: + animate_thinking("Loading language utility...", color="status") try: nltk.data.find('vader_lexicon') except LookupError: nltk.download('vader_lexicon') self.sid = SentimentIntensityAnalyzer() + self.translators_tokenizer = { + "fr": MarianTokenizer.from_pretrained("Helsinki-NLP/opus-mt-fr-en"), + "zh": MarianTokenizer.from_pretrained("Helsinki-NLP/opus-mt-zh-en") + } + self.translators_model = { + "fr": MarianMTModel.from_pretrained("Helsinki-NLP/opus-mt-fr-en"), + "zh": MarianMTModel.from_pretrained("Helsinki-NLP/opus-mt-zh-en") + } def detect_language(self, text: str) -> str: """ @@ -24,6 +42,25 @@ class LanguageUtility: lang, score = langid.classify(text) return lang + def translate(self, text: str, origin_lang: str) -> str: + """ + Translate the given text to English + Args: + text: string to translate + origin_lang: ISO language code + Returns: translated str + """ + if origin_lang == "en": + return text + if origin_lang not in self.translators_tokenizer: + pretty_print(f"Language {origin_lang} not supported for translation", color="error") + return text + tokenizer = self.translators_tokenizer[origin_lang] + inputs = tokenizer(text, return_tensors="pt", padding=True) + model = self.translators_model[origin_lang] + translation = model.generate(**inputs) + return tokenizer.decode(translation[0], skip_special_tokens=True) + def detect_emotion(self, text: str) -> str: """ Detect the dominant emotion in the given text @@ -75,11 +112,12 @@ if __name__ == "__main__": test_texts = [ "I am so happy today!", - "Qué tristeza siento ahora", "我不要去巴黎", "La vie c'est cool" ] for text in test_texts: - print(f"\nAnalyzing: {text}") + pretty_print("Analyzing...", color="status") + pretty_print(f"Language: {detector.detect_language(text)}", color="status") result = detector.analyze(text) - print(result) \ No newline at end of file + trans = detector.translate(text, result['language']) + pretty_print(f"Translation: {trans} - from: {result['language']} - Emotion: {result['emotions']}") \ No newline at end of file diff --git a/sources/memory.py b/sources/memory.py index 090bbf5..5c09b8a 100644 --- a/sources/memory.py +++ b/sources/memory.py @@ -67,9 +67,9 @@ class Memory(): def load_memory(self, agent_type: str = "casual_agent") -> None: """Load the memory from the last session.""" - pretty_print(f"Loading {agent_type} past memories... ", color="status") if self.session_recovered == True: return + pretty_print(f"Loading {agent_type} past memories... ", color="status") save_path = os.path.join(self.conversation_folder, agent_type) if not os.path.exists(save_path): pretty_print("No memory to load.", color="success") diff --git a/sources/router.py b/sources/router.py index 8f42459..4aa5852 100644 --- a/sources/router.py +++ b/sources/router.py @@ -8,14 +8,13 @@ from adaptive_classifier import AdaptiveClassifier sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) - from sources.agents.agent import Agent from sources.agents.code_agent import CoderAgent from sources.agents.casual_agent import CasualAgent from sources.agents.planner_agent import FileAgent from sources.agents.browser_agent import BrowserAgent from sources.language import LanguageUtility -from sources.utility import pretty_print +from sources.utility import pretty_print, animate_thinking, timer_decorator class AgentRouter: """ @@ -24,13 +23,22 @@ class AgentRouter: def __init__(self, agents: list): self.agents = agents self.lang_analysis = LanguageUtility() - self.pipelines = { - "bart": pipeline("zero-shot-classification", model="facebook/bart-large-mnli") - } + self.pipelines = self.load_pipelines() self.talk_classifier = self.load_llm_router() self.complexity_classifier = self.load_llm_router() self.learn_few_shots_tasks() self.learn_few_shots_complexity() + + def load_pipelines(self) -> Dict[str, Type[pipeline]]: + """ + Load the pipelines for the text classification used for routing. + returns: + Dict[str, Type[pipeline]]: The loaded pipelines + """ + animate_thinking("Loading zero-shot pipeline...", color="status") + return { + "bart": pipeline("zero-shot-classification", model="facebook/bart-large-mnli") + } def load_llm_router(self) -> AdaptiveClassifier: """ @@ -42,6 +50,7 @@ class AgentRouter: """ path = "../llm_router" if __name__ == "__main__" else "./llm_router" try: + animate_thinking("Loading LLM router model...", color="status") talk_classifier = AdaptiveClassifier.from_pretrained(path) except Exception as e: raise Exception("Failed to load the routing model. Please run the dl_safetensors.sh script inside llm_router/ directory to download the model.") @@ -302,25 +311,14 @@ class AgentRouter: pretty_print(f"Agent choice -> BART: {bart} ({final_score_bart}) LLM-router: {llm_router} ({final_score_llm})") return bart if final_score_bart > final_score_llm else llm_router - def classify_text(self, text: str, threshold: float = 0.4) -> list: - """ - Classify the text using the LLM router and BART model. - """ + def find_first_sentence(self, text: str) -> str: first_sentence = None - lang = "en" for line in text.split("\n"): first_sentence = line.strip() break if first_sentence is None: first_sentence = text - try: - lang = self.lang_analysis.detect_language(first_sentence) - # no multilanguage support yet - labels = [agent.role["en"] for agent in self.agents] - result = self.router_vote(first_sentence, labels, log_confidence=False) - except Exception as e: - raise e - return result, lang + return first_sentence def estimate_complexity(self, text: str) -> str: """ @@ -328,7 +326,7 @@ class AgentRouter: Args: text: The input text Returns: - str: The estimated complexity + str: The estimated complexity """ predictions = self.complexity_classifier.predict(text) predictions = sorted(predictions, key=lambda x: x[1], reverse=True) @@ -358,12 +356,6 @@ class AgentRouter: pretty_print(f"Error finding planner agent. Please add a planner agent to the list of agents.", color="failure") return None - def multi_language_message(self, text: str): - pretty_print(f"选择代理时出错。路由系统尚不支持多语言", color="failure") - pretty_print(f"エージェントの選択エラー。ルーティングシステムはまだ多言語に対応していません", color="failure") - pretty_print(f"Erreur lors du choix de l'agent. Le système de routage n'est pas encore multilingue.", color="failure") - pretty_print(f"Error al elegir agente. El sistema de enrutamiento aún no es multilingüe.", color="failure") - def select_agent(self, text: str) -> Agent: """ Select the appropriate agent based on the text. @@ -374,16 +366,21 @@ class AgentRouter: """ if len(self.agents) == 0: return self.agents[0] + lang = self.lang_analysis.detect_language(text) + text = self.find_first_sentence(text) + text = self.lang_analysis.translate(text, lang) + labels = [agent.role["en"] for agent in self.agents] complexity = self.estimate_complexity(text) - best_agent, lang = self.classify_text(text) - if lang != "en": - self.multi_language_message(text) if complexity == None: pretty_print(f"Humm, the task seem complex but you gave very little information. can you clarify?", color="info") return None - if complexity == "HIGH" and lang == "en": + if complexity == "HIGH": pretty_print(f"Complex task detected, routing to planner agent.", color="info") return self.find_planner_agent() + try: + best_agent = self.router_vote(text, labels, log_confidence=False) + except Exception as e: + raise e for agent in self.agents: if best_agent == agent.role["en"]: pretty_print(f"Selected agent: {agent.agent_name} (roles: {agent.role[lang]})", color="warning") @@ -393,52 +390,52 @@ class AgentRouter: if __name__ == "__main__": agents = [ - CasualAgent("jarvis", "../prompts/casual_agent.txt", None), - BrowserAgent("browser", "../prompts/planner_agent.txt", None), - CoderAgent("coder", "../prompts/coder_agent.txt", None), - FileAgent("file", "../prompts/coder_agent.txt", None) + CasualAgent("jarvis", "../prompts/base/casual_agent.txt", None), + BrowserAgent("browser", "../prompts/base/planner_agent.txt", None), + CoderAgent("coder", "../prompts/base/coder_agent.txt", None), + FileAgent("file", "../prompts/base/coder_agent.txt", None) ] router = AgentRouter(agents) texts = [ "hi", - #"你好", - #"Bonjour", + "你好", + "Bonjour", "Write a python script to check if the device on my network is connected to the internet", - # "Peut tu écrire un script python qui vérifie si l'appareil sur mon réseau est connecté à internet?", - # "写一个Python脚本，检查我网络上的设备是否连接到互联网", + "Peut tu écrire un script python qui vérifie si l'appareil sur mon réseau est connecté à internet?", + "写一个Python脚本，检查我网络上的设备是否连接到互联网", "Hey could you search the web for the latest news on the tesla stock market ?", - # "嘿，你能搜索网页上关于股票市场的最新新闻吗？", - # "Yo, cherche sur internet comment va tesla en bourse.", + "嘿，你能搜索网页上关于股票市场的最新新闻吗？", + "Yo, cherche sur internet comment va tesla en bourse.", "I would like you to search for weather api and then make an app using this API", - # "我想让你搜索天气API，然后用这个API做一个应用程序", - # "J'aimerais que tu cherche une api météo et que l'utilise pour faire une application", + "我想让你搜索天气API，然后用这个API做一个应用程序", + "J'aimerais que tu cherche une api météo et que l'utilise pour faire une application", "Plan a 3-day trip to New York, including flights and hotels.", - # "计划一次为期3天的纽约之旅，包括机票和酒店。", - # "Planifie un trip de 3 jours à Paris, y compris les vols et hotels.", + "计划一次为期3天的纽约之旅，包括机票和酒店。", + "Planifie un trip de 3 jours à Paris, y compris les vols et hotels.", "Find on the web the latest research papers on AI.", - # "在网上找到最新的人工智能研究论文。", - # "Trouve moi les derniers articles de recherche sur l'IA sur internet", + "在网上找到最新的人工智能研究论文。", + "Trouve moi les derniers articles de recherche sur l'IA sur internet", "Help me write a C++ program to sort an array", "Tell me what France been up to lately", - # "告诉我法国最近在做什么", - # "Dis moi ce que la France a fait récemment", + "告诉我法国最近在做什么", + "Dis moi ce que la France a fait récemment", "Who is Sergio Pesto ?", - # "谁是Sergio Pesto？", - # "Qui est Sergio Pesto ?", - # "帮我写一个C++程序来排序数组", - # "Aide moi à faire un programme c++ pour trier une array.", + "谁是Sergio Pesto？", + "Qui est Sergio Pesto ?", + "帮我写一个C++程序来排序数组", + "Aide moi à faire un programme c++ pour trier une array.", "What’s the weather like today? Oh, and can you find a good weather app?", - # "今天天气怎么样？哦，你还能找到一个好的天气应用程序吗？", - # "La météo est comment aujourd'hui ? oh et trouve moi une bonne appli météo tant que tu y est.", + "今天天气怎么样？哦，你还能找到一个好的天气应用程序吗？", + "La météo est comment aujourd'hui ? oh et trouve moi une bonne appli météo tant que tu y est.", "Can you debug this Java code? It’s not working.", - # "你能调试这段Java代码吗？它不起作用。", - # "Peut tu m'aider à debugger ce code java, ça marche pas", - #"Can you browse the web and find me a 4090 for cheap?", - #"你能浏览网页，为我找一个便宜的4090吗？", - #"Peut tu chercher sur internet et me trouver une 4090 pas cher ?", - #"Hey, can you find the old_project.zip file somewhere on my drive?", - #"嘿，你能在我驱动器上找到old_project.zip文件吗？", - #"Hé trouve moi le old_project.zip, il est quelque part sur mon disque.", + "你能调试这段Java代码吗？它不起作用。", + "Peut tu m'aider à debugger ce code java, ça marche pas", + "Can you browse the web and find me a 4090 for cheap?", + "你能浏览网页，为我找一个便宜的4090吗？", + "Peut tu chercher sur internet et me trouver une 4090 pas cher ?", + "Hey, can you find the old_project.zip file somewhere on my drive?", + "嘿，你能在我驱动器上找到old_project.zip文件吗？", + "Hé trouve moi le old_project.zip, il est quelque part sur mon disque.", "Tell me a funny story", "给我讲一个有趣的故事", "Raconte moi une histoire drole" diff --git a/sources/tools/safety.py b/sources/tools/safety.py index 2676e2b..04fdfb2 100644 --- a/sources/tools/safety.py +++ b/sources/tools/safety.py @@ -28,6 +28,9 @@ unsafe_commands_unix = [ "parted", # Disk partitioning "chroot", # Change root directory "route" # Routing table management + "--force", # Force flag for many commands + "rebase", # Rebase git repository + "git ." # Git commands, feel free to remove it but i dont want to risk agenticSeek pushing to its own repo lol (see 56b5db7) ] unsafe_commands_windows = [