å¼æºAI Agentçæçç¹ï¼2024å¹´æå¼å¾å ³æ³¨ç10个Agent项ç®2024å¹´ï¼AI Agentä»æ¦å¿µéªè¯èµ°åå·¥ç¨è½å°ï¼å¼æºçæåç°ç¾å®¶äºé¸£ä¹å¿ãä»ä¸å¤ç红çAutoGPTå°ä¼ä¸çº§å¤Agentåä½æ¡æ¶CrewAIï¼åå°å¯è§åç¼æå¹³å°Difyï¼å¼åè æ£ç¨ä»£ç éæ°å®ä¹æºè½çè¾¹çãæ¬æçç¹10个æå ·å½±ååçå¼æºAgent项ç®ï¼ä»æ¶æãè½åãåºæ¯ç维度深度对æ¯ï¼å¸®å©ææ¯éåãä¸ãAutoGPTï¼Agentæ¦å¿µçå¼çè项ç®æ¦è§GitHub Stars: 160ké¦æ¬¡åå¸: 2023å¹´3ææ ¸å¿å®ä½: èªä¸»ä»»å¡æ§è¡çéç¨AI Agentææ¯æ : Python, OpenAI APIAutoGPTæ¯AI Agentæ¦å¿µåºåçæ å¿æ§é¡¹ç®ãå®è®©GPT-4èªæ驱å¨ââç»å®ç®æ åèªä¸»å解任å¡ãæç´¢ãæ§è¡ãè¯ä¼°ï¼ç´å°å®ææé¢ç®èå°½ãæ ¸å¿æ¶æ# AutoGPT æ ¸å¿å¾ªç¯ç®å示æ class AutoGPTAgent: def __init__(self, ai_name, ai_role, api_budget): self.ai_name ai_name self.ai_role ai_role self.api_budget api_budget self.memory LocalCache() # åéåå¨è®°å¿ self.full_message_history [] def run(self, goals: List[str]): 主循ç¯ï¼æè - è¡å¨ - è§å¯ - è¯ä¼° while self.api_budget 0: # 1. ä»è®°å¿åè§å¯ä¸æ建ä¸ä¸æ current_context self._build_context(goals) # 2. LLMæèä¸ä¸æ¥è¡å¨ thoughts self.llm.think(current_context) # 3. 解æè¡å¨å½ä»¤ command self._parse_command(thoughts) # 4. æ§è¡è¡å¨ï¼æç´¢ãæµè§ãåæ件ãæ§è¡ä»£ç çï¼ result self._execute_command(command) # 5. åå¨å°è®°å¿ self.memory.add(fAction: {command}\nResult: {result}) # 6. æ£æ¥æ¯å¦å®æç®æ if self._is_goal_achieved(goals): breakå ³é®ç¹æ§| 维度 | 详æ | |------|------| | èªä¸»æ§ | é«ï¼å®å ¨èªä¸»å¾ªç¯ï¼æ éäººå·¥å¹²é¢ | | è®°å¿æºå¶ | åéæ°æ®åº æ¬å°ç¼å | | å·¥å ·è½å | ç½ç»æç´¢ãæ件æä½ã代ç æ§è¡ãå¾ççæ | | å¯æ©å±æ§ | éè¿æ件æºå¶æ©å± |éç¨åºæ¯ä¸å±ééåï¼æ¦å¿µéªè¯ãèªå¨åç 究ãåææ¢ç´¢å±éï¼Tokenæ¶èé«ã容æé·å ¥å¾ªç¯ãç产å¯é æ§ä¸è¶³ã缺ä¹å¤Agentåä½äºãLangChainï¼Agentç¼æçäºå®æ å项ç®æ¦è§GitHub Stars: 90ké¦æ¬¡åå¸: 2022å¹´10ææ ¸å¿å®ä½: LLMåºç¨å¼åæ¡æ¶ï¼Agentç¼æåºç¡è®¾æ½ææ¯æ : Python/TypeScript, å¤æ¨¡åå端LangChainä¸æ¯åä¸Agentï¼èæ¯Agentçæåºç¡è®¾æ½ï¼æä¾chainsãagentsãtoolsãmemoryãretrievalç模ååç»ä»¶ï¼è®©å¼åè åæ积æ¨ä¸æ ·æ建åºç¨ãæ ¸å¿ä»£ç 示ä¾from langchain import OpenAI, LLMMathChain, SerpAPIWrapper from langchain.agents import initialize_agent, Tool, AgentType from langchain.memory import ConversationBufferMemory tools [ Tool(nameSearch, funcSerpAPIWrapper().run, descriptionæç´¢å¼æ), Tool(nameCalculator, funcLLMMathChain(llmOpenAI()).run, description计ç®å¨) ] memory ConversationBufferMemory(memory_keychat_history) agent initialize_agent( tools, OpenAI(temperature0), agentAgentType.CONVERSATIONAL_REACT_DESCRIPTION, memorymemory, verboseTrue ) agent.run(202
开源AI Agent生态盘点：2024年最值得关注的10个Agent项目
å¼æºAI Agentçæçç¹ï¼2024å¹´æå¼å¾å ³æ³¨ç10个Agent项ç®2024å¹´ï¼AI Agentä»æ¦å¿µéªè¯èµ°åå·¥ç¨è½å°ï¼å¼æºçæåç°ç¾å®¶äºé¸£ä¹å¿ãä»ä¸å¤ç红çAutoGPTå°ä¼ä¸çº§å¤Agentåä½æ¡æ¶CrewAIï¼åå°å¯è§åç¼æå¹³å°Difyï¼å¼åè æ£ç¨ä»£ç éæ°å®ä¹æºè½çè¾¹çãæ¬æçç¹10个æå ·å½±ååçå¼æºAgent项ç®ï¼ä»æ¶æãè½åãåºæ¯ç维度深度对æ¯ï¼å¸®å©ææ¯éåãä¸ãAutoGPTï¼Agentæ¦å¿µçå¼çè项ç®æ¦è§GitHub Stars: 160ké¦æ¬¡åå¸: 2023å¹´3ææ ¸å¿å®ä½: èªä¸»ä»»å¡æ§è¡çéç¨AI Agentææ¯æ : Python, OpenAI APIAutoGPTæ¯AI Agentæ¦å¿µåºåçæ å¿æ§é¡¹ç®ãå®è®©GPT-4èªæ驱å¨ââç»å®ç®æ åèªä¸»å解任å¡ãæç´¢ãæ§è¡ãè¯ä¼°ï¼ç´å°å®ææé¢ç®èå°½ãæ ¸å¿æ¶æ# AutoGPT æ ¸å¿å¾ªç¯ç®å示æ class AutoGPTAgent: def __init__(self, ai_name, ai_role, api_budget): self.ai_name ai_name self.ai_role ai_role self.api_budget api_budget self.memory LocalCache() # åéåå¨è®°å¿ self.full_message_history [] def run(self, goals: List[str]): 主循ç¯ï¼æè - è¡å¨ - è§å¯ - è¯ä¼° while self.api_budget 0: # 1. ä»è®°å¿åè§å¯ä¸æ建ä¸ä¸æ current_context self._build_context(goals) # 2. LLMæèä¸ä¸æ¥è¡å¨ thoughts self.llm.think(current_context) # 3. 解æè¡å¨å½ä»¤ command self._parse_command(thoughts) # 4. æ§è¡è¡å¨ï¼æç´¢ãæµè§ãåæ件ãæ§è¡ä»£ç çï¼ result self._execute_command(command) # 5. åå¨å°è®°å¿ self.memory.add(fAction: {command}\nResult: {result}) # 6. æ£æ¥æ¯å¦å®æç®æ if self._is_goal_achieved(goals): breakå ³é®ç¹æ§| 维度 | 详æ | |------|------| | èªä¸»æ§ | é«ï¼å®å ¨èªä¸»å¾ªç¯ï¼æ éäººå·¥å¹²é¢ | | è®°å¿æºå¶ | åéæ°æ®åº æ¬å°ç¼å | | å·¥å ·è½å | ç½ç»æç´¢ãæ件æä½ã代ç æ§è¡ãå¾ççæ | | å¯æ©å±æ§ | éè¿æ件æºå¶æ©å± |éç¨åºæ¯ä¸å±ééåï¼æ¦å¿µéªè¯ãèªå¨åç 究ãåææ¢ç´¢å±éï¼Tokenæ¶èé«ã容æé·å ¥å¾ªç¯ãç产å¯é æ§ä¸è¶³ã缺ä¹å¤Agentåä½äºãLangChainï¼Agentç¼æçäºå®æ å项ç®æ¦è§GitHub Stars: 90ké¦æ¬¡åå¸: 2022å¹´10ææ ¸å¿å®ä½: LLMåºç¨å¼åæ¡æ¶ï¼Agentç¼æåºç¡è®¾æ½ææ¯æ : Python/TypeScript, å¤æ¨¡åå端LangChainä¸æ¯åä¸Agentï¼èæ¯Agentçæåºç¡è®¾æ½ï¼æä¾chainsãagentsãtoolsãmemoryãretrievalç模ååç»ä»¶ï¼è®©å¼åè åæ积æ¨ä¸æ ·æ建åºç¨ãæ ¸å¿ä»£ç 示ä¾from langchain import OpenAI, LLMMathChain, SerpAPIWrapper from langchain.agents import initialize_agent, Tool, AgentType from langchain.memory import ConversationBufferMemory tools [ Tool(nameSearch, funcSerpAPIWrapper().run, descriptionæç´¢å¼æ), Tool(nameCalculator, funcLLMMathChain(llmOpenAI()).run, description计ç®å¨) ] memory ConversationBufferMemory(memory_keychat_history) agent initialize_agent( tools, OpenAI(temperature0), agentAgentType.CONVERSATIONAL_REACT_DESCRIPTION, memorymemory, verboseTrue ) agent.run(202
