From 32b26183e5d4624e8c2a6f0d3d15db7332e278cf Mon Sep 17 00:00:00 2001 From: LinChentang <1273611131@qq.com> Date: Sat, 1 Jun 2024 23:01:46 +0800 Subject: [PATCH 01/24] upadte --- .../readme.md | 12 ++++++++++++ 1 file changed, 12 insertions(+) create mode 100644 content/AI Agentic Design Patterns with AutoGen/readme.md diff --git a/content/AI Agentic Design Patterns with AutoGen/readme.md b/content/AI Agentic Design Patterns with AutoGen/readme.md new file mode 100644 index 00000000..a47b27ef --- /dev/null +++ b/content/AI Agentic Design Patterns with AutoGen/readme.md @@ -0,0 +1,12 @@ +# 基于 AutoGen 的 Agent 设计范式(AI Agentic Design Patterns with AutoGen) + +**目录：** + +1. 简介 Introduction @姜舒凡 +2. Multi-Agent Conversation and Stand-up Comedy @姜舒凡 +3. Sequential Chats and Customer Onboarding @康婧淇 +4. Reflection and Blogpost Writing @谭逸珂 +5. Tool Use and Conversational Chess @姜舒凡 +6. Coding and Financial Analysis @娄天奥 +7. Planning and Stock Report Generation @娄天奥 +8. 总结 Conclusion @姜舒凡 From 3ba86c3b481156170cea51981681321f2cf3d795 Mon Sep 17 00:00:00 2001 From: Tsumugii24 <2792474059@qq.com> Date: Sun, 2 Jun 2024 03:27:43 +0800 Subject: [PATCH 02/24] add utils file --- .../utils.py | 18 ++++++++++++++++++ 1 file changed, 18 insertions(+) create mode 100644 content/AI Agentic Design Patterns with AutoGen/utils.py diff --git a/content/AI Agentic Design Patterns with AutoGen/utils.py b/content/AI Agentic Design Patterns with AutoGen/utils.py new file mode 100644 index 00000000..8259a99e --- /dev/null +++ b/content/AI Agentic Design Patterns with AutoGen/utils.py @@ -0,0 +1,18 @@ +# Add your utilities or helper functions to this file. + +import os +from dotenv import load_dotenv, find_dotenv + +# these expect to find a .env file at the directory above the lesson. # the format for that file is (without the comment) #API_KEYNAME=AStringThatIsTheLongAPIKeyFromSomeService +def load_env(): + _ = load_dotenv(find_dotenv()) + +def get_openai_api_key(): + load_env() + openai_api_key = os.getenv("OPENAI_API_KEY") + return openai_api_key + +def get_openai_base_url(): + load_env() + openai_base_url = os.getenv("OPENAI_BASE_URL") + return openai_base_url \ No newline at end of file From 564edff21a74c0f482ff1be5af0f818a4b6d6a51 Mon Sep 17 00:00:00 2001 From: Tsumugii24 <2792474059@qq.com> Date: Sun, 2 Jun 2024 03:28:11 +0800 Subject: [PATCH 03/24] add requirements file for autogen --- .../requirements.txt | 7 +++++++ 1 file changed, 7 insertions(+) create mode 100644 content/AI Agentic Design Patterns with AutoGen/requirements.txt diff --git a/content/AI Agentic Design Patterns with AutoGen/requirements.txt b/content/AI Agentic Design Patterns with AutoGen/requirements.txt new file mode 100644 index 00000000..552923b7 --- /dev/null +++ b/content/AI Agentic Design Patterns with AutoGen/requirements.txt @@ -0,0 +1,7 @@ +pyautogen +chess +matplotlib +numpy +pandas +yfinance +jupyterlab From 315b103435c5df7f8c9d35bf9df0fcb1bae1a8ec Mon Sep 17 00:00:00 2001 From: Tsumugii24 <2792474059@qq.com> Date: Sun, 2 Jun 2024 03:28:49 +0800 Subject: [PATCH 04/24] update autogen chapter2 multi-agent-conversation --- ...45\243\260 multi-agent-conversation.ipynb" | 650 ++++++++++++++++++ 1 file changed, 650 insertions(+) create mode 100644 "content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" diff --git "a/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" "b/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" new file mode 100644 index 00000000..66929d92 --- /dev/null +++ "b/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" @@ -0,0 +1,650 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "a81456dd", + "metadata": {}, + "source": [ + "# 多智能体对话和相声" + ] + }, + { + "cell_type": "markdown", + "id": "4693467e", + "metadata": {}, + "source": [ + "欢迎来到正式的代码实战环节。接下来我们需要先安装一些必要的环境和基础的配置。" + ] + }, + { + "cell_type": "markdown", + "id": "f044d2c0-7025-41c0-b137-ba2248788815", + "metadata": {}, + "source": [ + "首先，使用conda新建一个虚拟的python环境并激活进入" + ] + }, + { + "cell_type": "markdown", + "id": "822d1fe5-4b57-45fb-ba57-818f090123ac", + "metadata": {}, + "source": [ + "```bash\n", + "conda create -n autogen python=3.11\n", + "conda activate autogen\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "9bd4b57f-dda0-460b-81e3-ae52454a093b", + "metadata": {}, + "source": [ + "接下来，安装本课程学习中所必要的依赖" + ] + }, + { + "cell_type": "markdown", + "id": "8c40f272-3e36-489c-a97e-68ec66ce435d", + "metadata": {}, + "source": [ + "```bash\n", + "cd \n", + "pip install -r requirements.txt\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "fc52cab9-2b65-4897-85f4-e2fdf2b6c4dc", + "metadata": {}, + "source": [ + "安装完毕，让我们马上开始基于AutoGen框架的Agent设计范式学习吧~
\n", + "在这一节课中，我们会实现两个智能体合作讲相声的一个有趣例子😊" + ] + }, + { + "cell_type": "markdown", + "id": "742cf649", + "metadata": {}, + "source": [ + "## 基础配置" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "04d006c1-22fa-40ea-b3e0-d543142e0788", + "metadata": { + "height": 64 + }, + "outputs": [], + "source": [ + "from utils import get_openai_api_key, get_openai_base_url\n", + "OPENAI_API_KEY = get_openai_api_key()\n", + "OPENAI_BASE_URL = get_openai_base_url()\n", + "llm_config = {\"model\": \"gpt-3.5-turbo\"}" + ] + }, + { + "cell_type": "markdown", + "id": "116a1c4d", + "metadata": {}, + "source": [ + "## 定义一个AutoGen智能体" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "6fb8c441-c58c-41a8-a54b-5c387afceac5", + "metadata": { + "height": 132 + }, + "outputs": [], + "source": [ + "from autogen import ConversableAgent\n", + "\n", + "agent = ConversableAgent(\n", + " name=\"chatbot\",\n", + " llm_config=llm_config,\n", + " human_input_mode=\"NEVER\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "47886b5f-fc7c-431a-8036-cff6e88f85c6", + "metadata": { + "height": 80 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Sure, here you go: Why did the scarecrow win an award? Because he was outstanding in his field!\n" + ] + } + ], + "source": [ + "reply = agent.generate_reply(\n", + " messages=[{\"content\": \"Tell me a joke.\", \"role\": \"user\"}]\n", + ")\n", + "print(reply)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "67f626e9-4cec-40c1-abde-2eff1252b848", + "metadata": { + "height": 96 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Of course! Please share the joke you'd like me to repeat.\n" + ] + } + ], + "source": [ + "reply = agent.generate_reply(\n", + " messages=[{\"content\": \"Repeat the joke.\", \"role\": \"user\"}]\n", + ")\n", + "print(reply)" + ] + }, + { + "cell_type": "markdown", + "id": "6c067449-6202-48c1-a51b-58bbde7b424a", + "metadata": {}, + "source": [ + "由此可见，我们执行了两次`generate_reply`函数，但是智能体的第二次回复并没有继承上一次的交互记忆。" + ] + }, + { + "cell_type": "markdown", + "id": "8c98a301", + "metadata": {}, + "source": [ + "## 对话\n", + "\n", + "让Cathy和Joe两个Agent建立对话，它们的对话内容作为记忆可以被保存下来" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "8f109dcb-824e-40d7-8e86-efee42b75f3c", + "metadata": { + "height": 300 + }, + "outputs": [], + "source": [ + "cathy = ConversableAgent(\n", + " name=\"cathy\",\n", + " system_message=\n", + " \"Your name is Cathy and you are a stand-up comedian.\",\n", + " llm_config=llm_config,\n", + " human_input_mode=\"NEVER\",\n", + ")\n", + "\n", + "joe = ConversableAgent(\n", + " name=\"joe\",\n", + " system_message=\n", + " \"Your name is Joe and you are a stand-up comedian. \"\n", + " \"Start the next joke from the punchline of the previous joke.\",\n", + " llm_config=llm_config,\n", + " human_input_mode=\"NEVER\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "43f71a61", + "metadata": {}, + "source": [ + "**注意**： 您每次执行都可能会得到不同的笑话，因为这和大语言模型的底层逻辑，预测下一个生成token的最大概率有关。" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "46a1c6f6-687e-40de-8819-374201cfed9f", + "metadata": { + "height": 97 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[33mjoe\u001b[0m (to cathy):\n", + "\n", + "I'm Joe. Cathy, let's keep the jokes rolling.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mcathy\u001b[0m (to joe):\n", + "\n", + "Hey Joe! Alright, let's get this comedy train chugging along. So, I recently went on a strict diet and it taught me one important lesson - never grocery shop when you're hungry. I ended up with a cart full of snacks that were either half-eaten or had \"family size\" written on them... and by family, I mean just me. But hey, at least my pantry is prepared for any sudden snack attacks, right?\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mjoe\u001b[0m (to cathy):\n", + "\n", + "Haha, that's so relatable! I mean, who knew family size meant just one hungry person, right? Speaking of snacking, I recently tried to work out at home to stay in shape, but those fitness videos are no joke. I paused the video to take a break, and it buffered long enough for me to order a pizza, eat it, and then hit play again - and the instructor was still on the warm-up!\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mcathy\u001b[0m (to joe):\n", + "\n", + "Haha, that's impressive dedication right there, Joe! It's like workout buffering is the universe's way of saying, \"Are you sure about this whole fitness thing?\" I feel like I should make a workout video where the warm-up is just trying to find the motivation to press play. The real exercise is fighting the urge to switch over to Netflix instead. But hey, at least you got some quality pizza time in, right? Priorities, my friend, priorities.\n", + "\n", + "--------------------------------------------------------------------------------\n" + ] + } + ], + "source": [ + "chat_result = joe.initiate_chat(\n", + " recipient=cathy, \n", + " message=\"I'm Joe. Cathy, let's keep the jokes rolling.\",\n", + " max_turns=2,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "78edc810", + "metadata": {}, + "source": [ + "## 打印一些结果\n", + "\n", + "你可以在控制台打印出下列信息：\n", + "\n", + "1. 对话的历史记录\n", + "2. 对话的花费\n", + "3. 对话的总结" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "1169ea24-eadd-4909-8d56-9b7ec5677c66", + "metadata": { + "height": 63 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[{'content': \"I'm Joe. Cathy, let's keep the jokes rolling.\",\n", + " 'role': 'assistant'},\n", + " {'content': \"Hey Joe! Alright, let's get this comedy train chugging along. \"\n", + " 'So, I recently went on a strict diet and it taught me one '\n", + " \"important lesson - never grocery shop when you're hungry. I \"\n", + " 'ended up with a cart full of snacks that were either half-eaten '\n", + " 'or had \"family size\" written on them... and by family, I mean '\n", + " 'just me. But hey, at least my pantry is prepared for any sudden '\n", + " 'snack attacks, right?',\n", + " 'role': 'user'},\n", + " {'content': \"Haha, that's so relatable! I mean, who knew family size meant \"\n", + " 'just one hungry person, right? Speaking of snacking, I recently '\n", + " 'tried to work out at home to stay in shape, but those fitness '\n", + " 'videos are no joke. I paused the video to take a break, and it '\n", + " 'buffered long enough for me to order a pizza, eat it, and then '\n", + " 'hit play again - and the instructor was still on the warm-up!',\n", + " 'role': 'assistant'},\n", + " {'content': \"Haha, that's impressive dedication right there, Joe! It's like \"\n", + " 'workout buffering is the universe\\'s way of saying, \"Are you '\n", + " 'sure about this whole fitness thing?\" I feel like I should make '\n", + " 'a workout video where the warm-up is just trying to find the '\n", + " 'motivation to press play. The real exercise is fighting the urge '\n", + " 'to switch over to Netflix instead. But hey, at least you got '\n", + " 'some quality pizza time in, right? Priorities, my friend, '\n", + " 'priorities.',\n", + " 'role': 'user'}]\n" + ] + } + ], + "source": [ + "import pprint\n", + "\n", + "pprint.pprint(chat_result.chat_history)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "550267b6-3652-40dc-9997-c5401f6d4c47", + "metadata": { + "height": 29 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'usage_excluding_cached_inference': {'gpt-3.5-turbo-0125': {'completion_tokens': 277,\n", + " 'cost': 0.0006180000000000001,\n", + " 'prompt_tokens': 405,\n", + " 'total_tokens': 682},\n", + " 'total_cost': 0.0006180000000000001},\n", + " 'usage_including_cached_inference': {'gpt-3.5-turbo-0125': {'completion_tokens': 277,\n", + " 'cost': 0.0006180000000000001,\n", + " 'prompt_tokens': 405,\n", + " 'total_tokens': 682},\n", + " 'total_cost': 0.0006180000000000001}}\n" + ] + } + ], + "source": [ + "pprint.pprint(chat_result.cost)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "dfcf468e-d217-4731-8cb4-3485377230f1", + "metadata": { + "height": 29 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(\"Haha, that's impressive dedication right there, Joe! It's like workout \"\n", + " 'buffering is the universe\\'s way of saying, \"Are you sure about this whole '\n", + " 'fitness thing?\" I feel like I should make a workout video where the warm-up '\n", + " 'is just trying to find the motivation to press play. The real exercise is '\n", + " 'fighting the urge to switch over to Netflix instead. But hey, at least you '\n", + " 'got some quality pizza time in, right? Priorities, my friend, priorities.')\n" + ] + } + ], + "source": [ + "pprint.pprint(chat_result.summary)" + ] + }, + { + "cell_type": "markdown", + "id": "06809794-8815-435d-9e2d-9b26c87c8967", + "metadata": {}, + "source": [ + "这里可以看到对话的总结完全是cathy对joe说的内容，也就是最后一轮对话的结尾。这是因为默认的总结方式就是取最后的一段历史对话记录。" + ] + }, + { + "cell_type": "markdown", + "id": "ba8c6cf8", + "metadata": {}, + "source": [ + "## 对对话内容进行一个更好的总结" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "c1a8fef1-8030-4652-a2d2-1648834f62c2", + "metadata": { + "height": 131 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[33mjoe\u001b[0m (to cathy):\n", + "\n", + "I'm Joe. Cathy, let's keep the jokes rolling.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mcathy\u001b[0m (to joe):\n", + "\n", + "Hey Joe! Alright, let's get this comedy train chugging along. So, I recently went on a strict diet and it taught me one important lesson - never grocery shop when you're hungry. I ended up with a cart full of snacks that were either half-eaten or had \"family size\" written on them... and by family, I mean just me. But hey, at least my pantry is prepared for any sudden snack attacks, right?\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mjoe\u001b[0m (to cathy):\n", + "\n", + "Haha, that's so relatable! I mean, who knew family size meant just one hungry person, right? Speaking of snacking, I recently tried to work out at home to stay in shape, but those fitness videos are no joke. I paused the video to take a break, and it buffered long enough for me to order a pizza, eat it, and then hit play again - and the instructor was still on the warm-up!\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mcathy\u001b[0m (to joe):\n", + "\n", + "Haha, that's impressive dedication right there, Joe! It's like workout buffering is the universe's way of saying, \"Are you sure about this whole fitness thing?\" I feel like I should make a workout video where the warm-up is just trying to find the motivation to press play. The real exercise is fighting the urge to switch over to Netflix instead. But hey, at least you got some quality pizza time in, right? Priorities, my friend, priorities.\n", + "\n", + "--------------------------------------------------------------------------------\n" + ] + } + ], + "source": [ + "chat_result = joe.initiate_chat(\n", + " cathy, \n", + " message=\"I'm Joe. Cathy, let's keep the jokes rolling.\", \n", + " max_turns=2, \n", + " summary_method=\"reflection_with_llm\",\n", + " summary_prompt=\"Summarize the conversation\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "b042de62-bc49-49ee-99f2-4f972e23670b", + "metadata": { + "height": 29 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "('Watch out for the \"family size\" label when shopping hungry and be prepared '\n", + " 'for long workout video buffering breaks with a pizza pitstop. Priorities, my '\n", + " 'friend, priorities.')\n" + ] + } + ], + "source": [ + "pprint.pprint(chat_result.summary)" + ] + }, + { + "cell_type": "markdown", + "id": "0a1bced3-02d6-4f25-8d16-f2493dde4968", + "metadata": {}, + "source": [ + "我们在`initiate_chat`函数中新加入了两个参数，`summary_method`和`summary_prompt`，这将改变原先默认的总结方法。现在我们使用大语言模型来帮助我们整理回顾并总结对话的历史信息，这将会得到一个更符合我们理解的一个结果。" + ] + }, + { + "cell_type": "markdown", + "id": "300525bd", + "metadata": {}, + "source": [ + "## 对话终止\n", + "\n", + "对话可以被一个结束条件所终止" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "044dfd61-7f1d-46d8-9e28-4b2601b43d70", + "metadata": { + "height": 351 + }, + "outputs": [], + "source": [ + "cathy = ConversableAgent(\n", + " name=\"cathy\",\n", + " system_message=\n", + " \"Your name is Cathy and you are a stand-up comedian. \"\n", + " \"When you're ready to end the conversation, say 'I gotta go'.\",\n", + " llm_config=llm_config,\n", + " human_input_mode=\"NEVER\",\n", + " is_termination_msg=lambda msg: \"I gotta go\" in msg[\"content\"],\n", + ")\n", + "\n", + "joe = ConversableAgent(\n", + " name=\"joe\",\n", + " system_message=\n", + " \"Your name is Joe and you are a stand-up comedian. \"\n", + " \"When you're ready to end the conversation, say 'I gotta go'.\",\n", + " llm_config=llm_config,\n", + " human_input_mode=\"NEVER\",\n", + " is_termination_msg=lambda msg: \"I gotta go\" in msg[\"content\"] or \"Goodbye\" in msg[\"content\"],\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "bc49d959-1025-4709-8866-9d4035eaeae7", + "metadata": { + "height": 80 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[33mjoe\u001b[0m (to cathy):\n", + "\n", + "I'm Joe. Cathy, let's keep the jokes rolling.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mcathy\u001b[0m (to joe):\n", + "\n", + "Hey Joe! Why did the scarecrow win an award? Because he was outstanding in his field!\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mjoe\u001b[0m (to cathy):\n", + "\n", + "Haha, that's a good one, Cathy! Have you heard about the claustrophobic astronaut? He just needed a little space!\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mcathy\u001b[0m (to joe):\n", + "\n", + "Haha, that's a good one, Joe! How do you organize a space party? You planet!\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mjoe\u001b[0m (to cathy):\n", + "\n", + "Haha, great one, Cathy! You're on fire with the space jokes. Did you hear about the mathematician who's afraid of negative numbers? He will stop at nothing to avoid them!\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mcathy\u001b[0m (to joe):\n", + "\n", + "Haha, I love it, Joe! Why don't scientists trust atoms? Because they make up everything!\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mjoe\u001b[0m (to cathy):\n", + "\n", + "Haha, spot on, Cathy! You've got some great jokes up your sleeve. Speaking of jokes, have you heard about the guy who invented Lifesavers? He made a mint!\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mcathy\u001b[0m (to joe):\n", + "\n", + "Haha, that's a classic one, Joe! I guess you could say he really cleaned up with that invention!\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mjoe\u001b[0m (to cathy):\n", + "\n", + "Haha, absolutely, Cathy! He definitely made a splash in the confectionery world. Hey, thanks for the laughs and jokes, but I gotta go. Have a great day!\n", + "\n", + "--------------------------------------------------------------------------------\n" + ] + } + ], + "source": [ + "chat_result = joe.initiate_chat(\n", + " recipient=cathy,\n", + " message=\"I'm Joe. Cathy, let's keep the jokes rolling.\"\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "757d4a9c-94b6-457e-abde-39730e8dbbd6", + "metadata": {}, + "source": [ + "这里我们将终止条件设置为了当对话内容表达式中出现`I gotta go`这一字符串时终止对话。在此之前我们的两位Agent进行了多轮的交互。" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "846eccbd-efd1-464b-9385-279c19b17c1d", + "metadata": { + "height": 45 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[33mcathy\u001b[0m (to joe):\n", + "\n", + "What's last joke we talked about?\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mjoe\u001b[0m (to cathy):\n", + "\n", + "The last joke we talked about was about the guy who invented Lifesavers and how he made a mint.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mcathy\u001b[0m (to joe):\n", + "\n", + "I gotta go.\n", + "\n", + "--------------------------------------------------------------------------------\n" + ] + } + ], + "source": [ + "cathy.send(message=\"What's last joke we talked about?\", recipient=joe)" + ] + }, + { + "cell_type": "markdown", + "id": "a9beb8b0-b8ce-4660-8a49-66ce13747144", + "metadata": {}, + "source": [ + "这里我们可以再次从先前结束的那轮对话开始继续让两个Agent进行交互。可以看到由于有对话记忆，能够正确的输出最后一轮的笑话。此外，在cathy输出`I gotta go`之后对话再次满足停止条件并终止。" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "44067239-1d82-4164-839b-bc9f1264e5b7", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "autogen", + "language": "python", + "name": "autogen" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 1a0e01e028e7101d31a3f0d7ef9ceed343dfee22 Mon Sep 17 00:00:00 2001 From: Tsumugii24 <2792474059@qq.com> Date: Sun, 2 Jun 2024 03:30:14 +0800 Subject: [PATCH 05/24] initialize .env.example file --- content/AI Agentic Design Patterns with AutoGen/.env.example | 3 +++ 1 file changed, 3 insertions(+) create mode 100644 content/AI Agentic Design Patterns with AutoGen/.env.example diff --git a/content/AI Agentic Design Patterns with AutoGen/.env.example b/content/AI Agentic Design Patterns with AutoGen/.env.example new file mode 100644 index 00000000..5131f098 --- /dev/null +++ b/content/AI Agentic Design Patterns with AutoGen/.env.example @@ -0,0 +1,3 @@ +# OpenAI https://platform.openai.com/api-keys +OPENAI_API_KEY = +OPENAI_BASE_URL = From bd40b0c619bb2c7c3240ad4e1eaff35b3fc1778e Mon Sep 17 00:00:00 2001 From: Tsumugii24 <2792474059@qq.com> Date: Sun, 2 Jun 2024 04:58:42 +0800 Subject: [PATCH 06/24] update requirements file --- ...05\350\261\241\346\243\213 tool-use.ipynb" | 1029 +++++++++++++++++ .../requirements.txt | 3 +- 2 files changed, 1031 insertions(+), 1 deletion(-) create mode 100644 "content/AI Agentic Design Patterns with AutoGen/5.\345\267\245\345\205\267\344\275\277\347\224\250\345\222\214\345\233\275\351\231\205\350\261\241\346\243\213 tool-use.ipynb" diff --git "a/content/AI Agentic Design Patterns with AutoGen/5.\345\267\245\345\205\267\344\275\277\347\224\250\345\222\214\345\233\275\351\231\205\350\261\241\346\243\213 tool-use.ipynb" "b/content/AI Agentic Design Patterns with AutoGen/5.\345\267\245\345\205\267\344\275\277\347\224\250\345\222\214\345\233\275\351\231\205\350\261\241\346\243\213 tool-use.ipynb" new file mode 100644 index 00000000..5d61ba7c --- /dev/null +++ "b/content/AI Agentic Design Patterns with AutoGen/5.\345\267\245\345\205\267\344\275\277\347\224\250\345\222\214\345\233\275\351\231\205\350\261\241\346\243\213 tool-use.ipynb" @@ -0,0 +1,1029 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "9a6dd449", + "metadata": {}, + "source": [ + "# 工具使用和国际象棋" + ] + }, + { + "cell_type": "markdown", + "id": "75bcfd3c", + "metadata": {}, + "source": [ + "## 基础配置" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "6032c971-8934-4018-8743-eace0553578c", + "metadata": { + "height": 30 + }, + "outputs": [], + "source": [ + "from utils import get_openai_api_key, get_openai_base_url\n", + "OPENAI_API_KEY = get_openai_api_key()\n", + "OPENAI_BASE_URL = get_openai_base_url()\n", + "llm_config = {\"model\": \"gpt-4o\"}" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "086cb574-1299-43ce-90b4-79e089a76a11", + "metadata": { + "height": 64 + }, + "outputs": [], + "source": [ + "import chess\n", + "import chess.svg\n", + "from typing_extensions import Annotated" + ] + }, + { + "cell_type": "markdown", + "id": "f4406540", + "metadata": {}, + "source": [ + "## 初始化国际象棋棋盘" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "10161c38-0fe6-4a03-a5ff-069e8374a1d8", + "metadata": { + "height": 30 + }, + "outputs": [], + "source": [ + "board = chess.Board()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "c799e0a9-be62-4c20-b524-7a39d125f46d", + "metadata": { + "height": 30 + }, + "outputs": [], + "source": [ + "made_move = False" + ] + }, + { + "cell_type": "markdown", + "id": "22d38427", + "metadata": {}, + "source": [ + "## 定义需要的工具\n", + "\n", + "### 1. 获取合规行动的工具" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "78607e9f-47b0-419e-b652-dd6b5b0390c1", + "metadata": { + "height": 114 + }, + "outputs": [], + "source": [ + "def get_legal_moves(\n", + " \n", + ") -> Annotated[str, \"A list of legal moves in UCI format\"]:\n", + " return \"Possible moves are: \" + \",\".join(\n", + " [str(move) for move in board.legal_moves]\n", + " )" + ] + }, + { + "cell_type": "markdown", + "id": "0be25bc8", + "metadata": {}, + "source": [ + "### 2. 在棋盘上行动一步的工具" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "08a09854-dfd4-495c-84c1-8ea1dd8cacdb", + "metadata": { + "height": 505 + }, + "outputs": [], + "source": [ + "def make_move(\n", + " move: Annotated[str, \"A move in UCI format.\"]\n", + ") -> Annotated[str, \"Result of the move.\"]:\n", + " move = chess.Move.from_uci(move)\n", + " board.push_uci(str(move))\n", + " global made_move\n", + " made_move = True\n", + " \n", + " # 可视化棋盘\n", + " display(\n", + " chess.svg.board(\n", + " board,\n", + " arrows=[(move.from_square, move.to_square)],\n", + " fill={move.from_square: \"gray\"},\n", + " size=200\n", + " )\n", + " )\n", + " \n", + " # 获取棋子的名称\n", + " piece = board.piece_at(move.to_square)\n", + " piece_symbol = piece.unicode_symbol()\n", + " piece_name = (\n", + " chess.piece_name(piece.piece_type).capitalize()\n", + " if piece_symbol.isupper()\n", + " else chess.piece_name(piece.piece_type)\n", + " )\n", + " return f\"Moved {piece_name} ({piece_symbol}) from \"\\\n", + " f\"{chess.SQUARE_NAMES[move.from_square]} to \"\\\n", + " f\"{chess.SQUARE_NAMES[move.to_square]}.\"" + ] + }, + { + "cell_type": "markdown", + "id": "341ce0a8-4052-4266-afa8-f7890ccf2253", + "metadata": {}, + "source": [ + "`UCI`, 即`Universal Chess Interface`格式是国际象棋引擎与界面之间进行通信的标准化协议。
\n", + "它由`Chess Engine Communication Protocol,CECP`发展而来，并被广泛用于现代国际象棋软件中。
\n", + "使用UCI格式可以确保不同国际象棋程序间的兼容性和互操作性。\n", + "\n", + "`UCI`格式的主要用途包括：\n", + "\n", + "1. **走子描述**：提供一种标准的方式来表示棋盘上的位置和棋子的移动。例如，`e2e4`表示从位置`e2`到`e4`的移动。\n", + "\n", + "2. **命令接口**：允许用户或程序与棋弈引擎进行交互，如搜索选项设置、局面分析等。\n", + "\n", + "3. **棋局导入/导出**：支持将棋局保存为文本格式，方便在不同的程序间传输。\n", + "\n", + "在上述代码中，`chess.Move.from_uci(move)`函数用于将`UCI`格式的字符串转换为一个内部表示的`Move`对象。这种转换使得程序能够理解用户的走子意图，并在棋盘上执行相应的操作。\n" + ] + }, + { + "cell_type": "markdown", + "id": "a06e6f41", + "metadata": {}, + "source": [ + "## 创建智能体\n", + "\n", + "接下来，我们将在棋盘上创建两个玩家智能体和一个象棋裁判智能体。" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "3055679f-5f69-4d32-aff6-076925a36174", + "metadata": { + "height": 29 + }, + "outputs": [], + "source": [ + "from autogen import ConversableAgent" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "9466949c-c2cf-4bba-8307-d7ff4b70a948", + "metadata": { + "height": 164 + }, + "outputs": [], + "source": [ + "# 白色方智能体\n", + "player_white = ConversableAgent(\n", + " name=\"Player White\",\n", + " system_message=\"You are a chess player and you play as white. \"\n", + " \"First call get_legal_moves(), to get a list of legal moves. \"\n", + " \"Then call make_move(move) to make a move.\",\n", + " llm_config=llm_config,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "dcb6a474-2691-425c-8558-beb3363cd2bb", + "metadata": { + "height": 164 + }, + "outputs": [], + "source": [ + "# 黑色方智能体\n", + "player_black = ConversableAgent(\n", + " name=\"Player Black\",\n", + " system_message=\"You are a chess player and you play as black. \"\n", + " \"First call get_legal_moves(), to get a list of legal moves. \"\n", + " \"Then call make_move(move) to make a move.\",\n", + " llm_config=llm_config,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "6b69ac38-6399-425a-9681-4a2b7403a4bf", + "metadata": { + "height": 148 + }, + "outputs": [], + "source": [ + "def check_made_move(msg):\n", + " global made_move\n", + " if made_move:\n", + " made_move = False\n", + " return True\n", + " else:\n", + " return False\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "c3eaa260-422c-4e44-a355-42f0d885e9bc", + "metadata": { + "height": 131 + }, + "outputs": [], + "source": [ + "board_proxy = ConversableAgent(\n", + " name=\"Board Proxy\",\n", + " llm_config=False,\n", + " is_termination_msg=check_made_move,\n", + " default_auto_reply=\"Please make a move.\",\n", + " human_input_mode=\"NEVER\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "3cd1c45d", + "metadata": {}, + "source": [ + "## 注册工具\n", + "\n", + "工具需要被注册后才能被智能体调用或执行" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "5caf8ae1-4b39-4be5-89fa-0d57b4595841", + "metadata": { + "height": 29 + }, + "outputs": [], + "source": [ + "from autogen import register_function" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "880a9926-d76b-4322-872c-b691d933506e", + "metadata": { + "height": 284 + }, + "outputs": [], + "source": [ + "for caller in [player_white, player_black]:\n", + " register_function(\n", + " get_legal_moves,\n", + " caller=caller,\n", + " executor=board_proxy,\n", + " name=\"get_legal_moves\",\n", + " description=\"Get legal moves.\",\n", + " )\n", + " \n", + " register_function(\n", + " make_move,\n", + " caller=caller,\n", + " executor=board_proxy,\n", + " name=\"make_move\",\n", + " description=\"Call this tool to make a move.\",\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "dd487d3e-9226-4764-bd25-b452c1993388", + "metadata": { + "height": 29 + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'type': 'function',\n", + " 'function': {'description': 'Get legal moves.',\n", + " 'name': 'get_legal_moves',\n", + " 'parameters': {'type': 'object', 'properties': {}, 'required': []}}},\n", + " {'type': 'function',\n", + " 'function': {'description': 'Call this tool to make a move.',\n", + " 'name': 'make_move',\n", + " 'parameters': {'type': 'object',\n", + " 'properties': {'move': {'type': 'string',\n", + " 'description': 'A move in UCI format.'}},\n", + " 'required': ['move']}}}]" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "player_black.llm_config[\"tools\"]" + ] + }, + { + "cell_type": "markdown", + "id": "1a7fa1f0", + "metadata": {}, + "source": [ + "## 嵌套交互注册\n", + "\n", + "每个玩家智能体都将与象棋裁判智能体进行嵌套交互，从而在棋盘上执行移动。" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "3230f945-f302-4f39-bc37-766ca082fb28", + "metadata": { + "height": 369 + }, + "outputs": [], + "source": [ + "player_white.register_nested_chats(\n", + " trigger=player_black,\n", + " chat_queue=[\n", + " {\n", + " \"sender\": board_proxy,\n", + " \"recipient\": player_white,\n", + " \"summary_method\": \"last_msg\",\n", + " }\n", + " ],\n", + ")\n", + "\n", + "player_black.register_nested_chats(\n", + " trigger=player_white,\n", + " chat_queue=[\n", + " {\n", + " \"sender\": board_proxy,\n", + " \"recipient\": player_black,\n", + " \"summary_method\": \"last_msg\",\n", + " }\n", + " ],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "d371ce02", + "metadata": {}, + "source": [ + "## 开始游戏\n", + "\n", + "游戏将从第一条消息开始。" + ] + }, + { + "cell_type": "markdown", + "id": "ceb2b874", + "metadata": {}, + "source": [ + "

注意1：对于本课程的代码实践，推荐使用gpt-4-turbo或gpt-4o来获得更好的结果。
注意2：每次实验结果的玩家的棋子移动都可能略有不同。因为这和大语言模型的底层逻辑，预测下一个生成token的最大概率有关。

" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "5595758f-7ae1-467f-bad9-79c6c7cd0b25", + "metadata": { + "height": 131 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[33mPlayer Black\u001b[0m (to Player White):\n", + "\n", + "Let's play chess! Your move.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[34mStarting a new chat....\u001b[0m\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\n", + "Let's play chess! Your move.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mPlayer White\u001b[0m (to Board Proxy):\n", + "\n", + "\u001b[32m***** Suggested tool call (call_KrerPlbKm6AvUnVKyC11H0Uw): get_legal_moves *****\u001b[0m\n", + "Arguments: \n", + "{}\n", + "\u001b[32m********************************************************************************\u001b[0m\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[35m\n", + ">>>>>>>> EXECUTING FUNCTION get_legal_moves...\u001b[0m\n", + "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\n", + "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\n", + "\u001b[32m***** Response from calling tool (call_KrerPlbKm6AvUnVKyC11H0Uw) *****\u001b[0m\n", + "Possible moves are: g1h3,g1f3,b1c3,b1a3,h2h3,g2g3,f2f3,e2e3,d2d3,c2c3,b2b3,a2a3,h2h4,g2g4,f2f4,e2e4,d2d4,c2c4,b2b4,a2a4\n", + "\u001b[32m**********************************************************************\u001b[0m\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mPlayer White\u001b[0m (to Board Proxy):\n", + "\n", + "\u001b[32m***** Suggested tool call (call_263Y3g9UFMtHfU2BaTLGtDp6): make_move *****\u001b[0m\n", + "Arguments: \n", + "{\"move\":\"e2e4\"}\n", + "\u001b[32m**************************************************************************\u001b[0m\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[35m\n", + ">>>>>>>> EXECUTING FUNCTION make_move...\u001b[0m\n" + ] + }, + { + "data": { + "image/svg+xml": [ + "
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'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\n", + "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\n", + "\u001b[32m***** Response from calling tool (call_263Y3g9UFMtHfU2BaTLGtDp6) *****\u001b[0m\n", + "Moved pawn (♙) from e2 to e4.\n", + "\u001b[32m**********************************************************************\u001b[0m\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mPlayer White\u001b[0m (to Board Proxy):\n", + "\n", + "I have moved my pawn from e2 to e4. Your move!\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mPlayer White\u001b[0m (to Player Black):\n", + "\n", + "I have moved my pawn from e2 to e4. Your move!\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[34mStarting a new chat....\u001b[0m\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[33mBoard Proxy\u001b[0m (to Player Black):\n", + "\n", + "I have moved my pawn from e2 to e4. Your move!\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mPlayer Black\u001b[0m (to Board Proxy):\n", + "\n", + "\u001b[32m***** Suggested tool call (call_263Y3g9UFMtHfU2BaTLGtDp6): get_legal_moves *****\u001b[0m\n", + "Arguments: \n", + "{}\n", + "\u001b[32m********************************************************************************\u001b[0m\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[35m\n", + ">>>>>>>> EXECUTING FUNCTION get_legal_moves...\u001b[0m\n", + "\u001b[33mBoard Proxy\u001b[0m (to Player Black):\n", + "\n", + "\u001b[33mBoard Proxy\u001b[0m (to Player Black):\n", + "\n", + "\u001b[32m***** Response from calling tool (call_263Y3g9UFMtHfU2BaTLGtDp6) *****\u001b[0m\n", + "Possible moves are: g8h6,g8f6,b8c6,b8a6,h7h6,g7g6,f7f6,e7e6,d7d6,c7c6,b7b6,a7a6,h7h5,g7g5,f7f5,e7e5,d7d5,c7c5,b7b5,a7a5\n", + "\u001b[32m**********************************************************************\u001b[0m\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mPlayer Black\u001b[0m (to Board Proxy):\n", + "\n", + "\u001b[32m***** Suggested tool call (call_fVOjOUvYbIq3bdoZMazzWRe9): make_move *****\u001b[0m\n", + "Arguments: \n", + "{\"move\":\"e7e5\"}\n", + "\u001b[32m**************************************************************************\u001b[0m\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[35m\n", + ">>>>>>>> EXECUTING FUNCTION make_move...\u001b[0m\n" + ] + }, + { + "data": { + "image/svg+xml": [ + "
r n b q k b n r\n",
+       "p p p p . p p p\n",
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+       ". . . . p . . .\n",
+       ". . . . P . . .\n",
+       ". . . . . . . .\n",
+       "P P P P . P P P\n",
+       "R N B Q K B N R
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'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[33mBoard Proxy\u001b[0m (to Player Black):\n", + "\n", + "\u001b[33mBoard Proxy\u001b[0m (to Player Black):\n", + "\n", + "\u001b[32m***** Response from calling tool (call_fVOjOUvYbIq3bdoZMazzWRe9) *****\u001b[0m\n", + "Moved pawn (♟) from e7 to e5.\n", + "\u001b[32m**********************************************************************\u001b[0m\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mPlayer Black\u001b[0m (to Board Proxy):\n", + "\n", + "I've moved my pawn from e7 to e5. Your move!\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mPlayer Black\u001b[0m (to Player White):\n", + "\n", + "I've moved my pawn from e7 to e5. Your move!\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[34mStarting a new chat....\u001b[0m\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\n", + "I've moved my pawn from e7 to e5. Your move!\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mPlayer White\u001b[0m (to Board Proxy):\n", + "\n", + "\u001b[32m***** Suggested tool call (call_3Rp1ex7Gobo4IaNmddJCHUde): get_legal_moves *****\u001b[0m\n", + "Arguments: \n", + "{}\n", + "\u001b[32m********************************************************************************\u001b[0m\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[35m\n", + ">>>>>>>> EXECUTING FUNCTION get_legal_moves...\u001b[0m\n", + "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\n", + "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\n", + "\u001b[32m***** Response from calling tool (call_3Rp1ex7Gobo4IaNmddJCHUde) *****\u001b[0m\n", + "Possible moves are: g1h3,g1f3,g1e2,f1a6,f1b5,f1c4,f1d3,f1e2,e1e2,d1h5,d1g4,d1f3,d1e2,b1c3,b1a3,h2h3,g2g3,f2f3,d2d3,c2c3,b2b3,a2a3,h2h4,g2g4,f2f4,d2d4,c2c4,b2b4,a2a4\n", + "\u001b[32m**********************************************************************\u001b[0m\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mPlayer White\u001b[0m (to Board Proxy):\n", + "\n", + "\u001b[32m***** Suggested tool call (call_263Y3g9UFMtHfU2BaTLGtDp6): make_move *****\u001b[0m\n", + "Arguments: \n", + "{\"move\":\"d2d4\"}\n", + "\u001b[32m**************************************************************************\u001b[0m\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[35m\n", + ">>>>>>>> EXECUTING FUNCTION make_move...\u001b[0m\n" + ] + }, + { + "data": { + "image/svg+xml": [ + "
r n b q k b n r\n",
+       "p p p p . p p p\n",
+       ". . . . . . . .\n",
+       ". . . . p . . .\n",
+       ". . . P P . . .\n",
+       ". . . . . . . .\n",
+       "P P P . . P P P\n",
+       "R N B Q K B N R
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'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\n", + "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\n", + "\u001b[32m***** Response from calling tool (call_263Y3g9UFMtHfU2BaTLGtDp6) *****\u001b[0m\n", + "Moved pawn (♙) from d2 to d4.\n", + "\u001b[32m**********************************************************************\u001b[0m\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mPlayer White\u001b[0m (to Board Proxy):\n", + "\n", + "Your move!\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mPlayer White\u001b[0m (to Player Black):\n", + "\n", + "Your move!\n", + "\n", + "--------------------------------------------------------------------------------\n" + ] + } + ], + "source": [ + "board = chess.Board()\n", + "\n", + "chat_result = player_black.initiate_chat(\n", + " player_white,\n", + " message=\"Let's play chess! Your move.\",\n", + " max_turns=2,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "ad9cf403", + "metadata": {}, + "source": [ + "## 为游戏过程添加一些有趣的闲聊" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "dc6c2ef8-4807-4b9e-9eff-0da219ac6381", + "metadata": { + "height": 164 + }, + "outputs": [], + "source": [ + "player_white = ConversableAgent(\n", + " name=\"Player White\",\n", + " system_message=\"You are a chess player and you play as white. \"\n", + " \"First call get_legal_moves(), to get a list of legal moves. \"\n", + " \"Then call make_move(move) to make a move. \"\n", + " \"After a move is made, chitchat to make the game fun.\",\n", + " llm_config=llm_config,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "1da2db96-83d1-4b75-aa05-3840913a46ac", + "metadata": { + "height": 164 + }, + "outputs": [], + "source": [ + "player_black = ConversableAgent(\n", + " name=\"Player Black\",\n", + " system_message=\"You are a chess player and you play as black. \"\n", + " \"First call get_legal_moves(), to get a list of legal moves. \"\n", + " \"Then call make_move(move) to make a move. \"\n", + " \"After a move is made, chitchat to make the game fun.\",\n", + " llm_config=llm_config,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "489e5258-a48d-4745-9cf8-6d530ce1162c", + "metadata": { + "height": 692 + }, + "outputs": [], + "source": [ + "for caller in [player_white, player_black]:\n", + " register_function(\n", + " get_legal_moves,\n", + " caller=caller,\n", + " executor=board_proxy,\n", + " name=\"get_legal_moves\",\n", + " description=\"Get legal moves.\",\n", + " )\n", + "\n", + " register_function(\n", + " make_move,\n", + " caller=caller,\n", + " executor=board_proxy,\n", + " name=\"make_move\",\n", + " description=\"Call this tool to make a move.\",\n", + " )\n", + "\n", + "player_white.register_nested_chats(\n", + " trigger=player_black,\n", + " chat_queue=[\n", + " {\n", + " \"sender\": board_proxy,\n", + " \"recipient\": player_white,\n", + " \"summary_method\": \"last_msg\",\n", + " \"silent\": True,\n", + " }\n", + " ],\n", + ")\n", + "\n", + "player_black.register_nested_chats(\n", + " trigger=player_white,\n", + " chat_queue=[\n", + " {\n", + " \"sender\": board_proxy,\n", + " \"recipient\": player_black,\n", + " \"summary_method\": \"last_msg\",\n", + " \"silent\": True,\n", + " }\n", + " ],\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "723edd10-e0c6-4205-8e9b-db4cef7a464f", + "metadata": { + "height": 131 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[33mPlayer Black\u001b[0m (to Player White):\n", + "\n", + "Let's play chess! Your move.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[34mStarting a new chat....\u001b[0m\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[35m\n", + ">>>>>>>> EXECUTING FUNCTION get_legal_moves...\u001b[0m\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[35m\n", + ">>>>>>>> EXECUTING FUNCTION make_move...\u001b[0m\n" + ] + }, + { + "data": { + "image/svg+xml": [ + "
r n b q k b n r\n",
+       "p p p p p p p p\n",
+       ". . . . . . . .\n",
+       ". . . . . . . .\n",
+       ". . . . P . . .\n",
+       ". . . . . . . .\n",
+       "P P P P . P P P\n",
+       "R N B Q K B N R
" + ], + "text/plain": [ + "'
r n b q k b n r\\np p p p p p p p\\n. . . . . . . .\\n. . . . . . . .\\n. . . . P . . .\\n. . . . . . . .\\nP P P P . P P P\\nR N B Q K B N R
'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mPlayer White\u001b[0m (to Player Black):\n", + "\n", + "Your move! What's it going to be? \n", + "\n", + "By the way, did you know that the longest chess game theoretically possible consists of 5,949 moves? 😲\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[34mStarting a new chat....\u001b[0m\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[35m\n", + ">>>>>>>> EXECUTING FUNCTION get_legal_moves...\u001b[0m\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[35m\n", + ">>>>>>>> EXECUTING FUNCTION make_move...\u001b[0m\n" + ] + }, + { + "data": { + "image/svg+xml": [ + "
r n b q k b n r\n",
+       "p p p p . p p p\n",
+       ". . . . . . . .\n",
+       ". . . . p . . .\n",
+       ". . . . P . . .\n",
+       ". . . . . . . .\n",
+       "P P P P . P P P\n",
+       "R N B Q K B N R
" + ], + "text/plain": [ + "'
r n b q k b n r\\np p p p . p p p\\n. . . . . . . .\\n. . . . p . . .\\n. . . . P . . .\\n. . . . . . . .\\nP P P P . P P P\\nR N B Q K B N R
'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mPlayer Black\u001b[0m (to Player White):\n", + "\n", + "Your move! By the way, did you know that every known position you see on the board has a unique fingerprint called a \"Zobrist Hash\"? This helps in identifying board positions efficiently in many chess engines. Cool, right?\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[34mStarting a new chat....\u001b[0m\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[35m\n", + ">>>>>>>> EXECUTING FUNCTION get_legal_moves...\u001b[0m\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[35m\n", + ">>>>>>>> EXECUTING FUNCTION make_move...\u001b[0m\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[35m\n", + ">>>>>>>> EXECUTING FUNCTION make_move...\u001b[0m\n" + ] + }, + { + "data": { + "image/svg+xml": [ + "
r n b q k b n r\n",
+       "p p p p . p p p\n",
+       ". . . . . . . .\n",
+       ". . . . p . . .\n",
+       ". . . P P . . .\n",
+       ". . . . . . . .\n",
+       "P P P . . P P P\n",
+       "R N B Q K B N R
" + ], + "text/plain": [ + "'
r n b q k b n r\\np p p p . p p p\\n. . . . . . . .\\n. . . . p . . .\\n. . . P P . . .\\n. . . . . . . .\\nP P P . . P P P\\nR N B Q K B N R
'" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mPlayer White\u001b[0m (to Player Black):\n", + "\n", + "Your move! By the way, have you ever wondered about en passant? It's a special pawn capture that can only occur immediately after a pawn moves two squares from its starting position, and if it could have been captured had it moved only one square. Chess rules have such fascinating intricacies!\n", + "\n", + "--------------------------------------------------------------------------------\n" + ] + } + ], + "source": [ + "board = chess.Board()\n", + "\n", + "chat_result = player_black.initiate_chat(\n", + " player_white,\n", + " message=\"Let's play chess! Your move.\",\n", + " max_turns=2,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "4e8ca3c3", + "metadata": {}, + "source": [ + "**注意：**\n", + "如果要为游戏添加人为输入，请为两个玩家智能体添加参数 **`human_input_mode=\"ALWAYS\"`**。" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "30c5ebca-d899-43c5-bc93-cc8131ecccf7", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "autogen", + "language": "python", + "name": "autogen" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/content/AI Agentic Design Patterns with AutoGen/requirements.txt b/content/AI Agentic Design Patterns with AutoGen/requirements.txt index 552923b7..1f540f14 100644 --- a/content/AI Agentic Design Patterns with AutoGen/requirements.txt +++ b/content/AI Agentic Design Patterns with AutoGen/requirements.txt @@ -1,4 +1,5 @@ -pyautogen +pyautogen==0.2.25 +python-dotenv chess matplotlib numpy From 864f09d7b83536a49b7d2d1d4842ab426d9be3b7 Mon Sep 17 00:00:00 2001 From: Tsumugii24 <2792474059@qq.com> Date: Sun, 2 Jun 2024 13:35:12 +0800 Subject: [PATCH 07/24] initialize images directory --- ...45\243\260 multi-agent-conversation.ipynb" | 82 +++++++++++------- .../images/fig-2-1.png | Bin 0 -> 19797 bytes 2 files changed, 51 insertions(+), 31 deletions(-) create mode 100644 content/AI Agentic Design Patterns with AutoGen/images/fig-2-1.png diff --git "a/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" "b/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" index 66929d92..52f800c9 100644 --- "a/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" +++ "b/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" @@ -30,7 +30,7 @@ "metadata": {}, "source": [ "```bash\n", - "conda create -n autogen python=3.11\n", + "conda create -n autogen python=3.10\n", "conda activate autogen\n", "```" ] @@ -54,6 +54,14 @@ "```" ] }, + { + "cell_type": "markdown", + "id": "34427c37", + "metadata": {}, + "source": [ + "最后，记得在`.env`文件中填入有效的`OPENAI_API_KEY`" + ] + }, { "cell_type": "markdown", "id": "fc52cab9-2b65-4897-85f4-e2fdf2b6c4dc", @@ -81,9 +89,9 @@ "outputs": [], "source": [ "from utils import get_openai_api_key, get_openai_base_url\n", - "OPENAI_API_KEY = get_openai_api_key()\n", - "OPENAI_BASE_URL = get_openai_base_url()\n", - "llm_config = {\"model\": \"gpt-3.5-turbo\"}" + "OPENAI_API_KEY = get_openai_api_key() # 获取api_key\n", + "OPENAI_BASE_URL = get_openai_base_url() # 获取base_url，如果不用则可以直接注释该行\n", + "llm_config = {\"model\": \"gpt-3.5-turbo\"} # 这里使用的模型名称为gpt-3.5-turbo" ] }, { @@ -105,10 +113,11 @@ "source": [ "from autogen import ConversableAgent\n", "\n", + "# 初始化一个ConversableAgent\n", "agent = ConversableAgent(\n", " name=\"chatbot\",\n", " llm_config=llm_config,\n", - " human_input_mode=\"NEVER\",\n", + " human_input_mode=\"NEVER\", # 这里设置人为不介入\n", ")" ] }, @@ -130,7 +139,7 @@ ], "source": [ "reply = agent.generate_reply(\n", - " messages=[{\"content\": \"Tell me a joke.\", \"role\": \"user\"}]\n", + " messages=[{\"content\": \"给我讲一个笑话\", \"role\": \"user\"}]\n", ")\n", "print(reply)" ] @@ -153,7 +162,7 @@ ], "source": [ "reply = agent.generate_reply(\n", - " messages=[{\"content\": \"Repeat the joke.\", \"role\": \"user\"}]\n", + " messages=[{\"content\": \"重复一下笑话\", \"role\": \"user\"}]\n", ")\n", "print(reply)" ] @@ -163,7 +172,7 @@ "id": "6c067449-6202-48c1-a51b-58bbde7b424a", "metadata": {}, "source": [ - "由此可见，我们执行了两次`generate_reply`函数，但是智能体的第二次回复并没有继承上一次的交互记忆。" + "由此可见，我们执行了两次`generate_reply`函数，但是智能体的第二次回复并没有继承上一次的交互记忆，因此没有成功的重复笑话。" ] }, { @@ -176,6 +185,16 @@ "让Cathy和Joe两个Agent建立对话，它们的对话内容作为记忆可以被保存下来" ] }, + { + "attachments": {}, + "cell_type": "markdown", + "id": "70f99de6", + "metadata": {}, + "source": [ + "![fig2.1](https://github.com/datawhalechina/llm-cookbook/blob/main/content/autogen/images/fig-2-1.png?raw=true)\n", + "我们通过定义两个可以对话的Agent，赋予它们相声演员的职责设定，就可以驱动它们完成相声的交互了。" + ] + }, { "cell_type": "code", "execution_count": 6, @@ -188,7 +207,7 @@ "cathy = ConversableAgent(\n", " name=\"cathy\",\n", " system_message=\n", - " \"Your name is Cathy and you are a stand-up comedian.\",\n", + " \"你的名字是Cathy，你是一位相声演员\",\n", " llm_config=llm_config,\n", " human_input_mode=\"NEVER\",\n", ")\n", @@ -196,8 +215,8 @@ "joe = ConversableAgent(\n", " name=\"joe\",\n", " system_message=\n", - " \"Your name is Joe and you are a stand-up comedian. \"\n", - " \"Start the next joke from the punchline of the previous joke.\",\n", + " \"你是的名字是Joe，你是一位相声演员\"\n", + " \"你需要根据上一个笑话，开始你的下一个笑话\",\n", " llm_config=llm_config,\n", " human_input_mode=\"NEVER\",\n", ")" @@ -249,7 +268,7 @@ "source": [ "chat_result = joe.initiate_chat(\n", " recipient=cathy, \n", - " message=\"I'm Joe. Cathy, let's keep the jokes rolling.\",\n", + " message=\"我是Joe。Cathy,让我们持续不断地讲笑话吧。\",\n", " max_turns=2,\n", ")" ] @@ -312,7 +331,7 @@ "source": [ "import pprint\n", "\n", - "pprint.pprint(chat_result.chat_history)" + "pprint.pprint(chat_result.chat_history) # 对话的历史记录" ] }, { @@ -341,7 +360,7 @@ } ], "source": [ - "pprint.pprint(chat_result.cost)" + "pprint.pprint(chat_result.cost) # 对话的花费" ] }, { @@ -366,7 +385,7 @@ } ], "source": [ - "pprint.pprint(chat_result.summary)" + "pprint.pprint(chat_result.summary) # 对话的总结" ] }, { @@ -423,10 +442,10 @@ "source": [ "chat_result = joe.initiate_chat(\n", " cathy, \n", - " message=\"I'm Joe. Cathy, let's keep the jokes rolling.\", \n", - " max_turns=2, \n", - " summary_method=\"reflection_with_llm\",\n", - " summary_prompt=\"Summarize the conversation\",\n", + " message=\"我是Joe。Cathy,让我们持续不断地讲笑话吧。\", \n", + " max_turns=2, # 设置最大轮数为2\n", + " summary_method=\"reflection_with_llm\", # 设置总结方法为使用大语言模型总结\n", + " summary_prompt=\"总结对话\",\n", ")" ] }, @@ -449,7 +468,7 @@ } ], "source": [ - "pprint.pprint(chat_result.summary)" + "pprint.pprint(chat_result.summary) # 使用大语言模型总结对话" ] }, { @@ -482,21 +501,21 @@ "cathy = ConversableAgent(\n", " name=\"cathy\",\n", " system_message=\n", - " \"Your name is Cathy and you are a stand-up comedian. \"\n", - " \"When you're ready to end the conversation, say 'I gotta go'.\",\n", + " \"你的名字是Cathy，你是一位相声演员\",\n", + " \"当你准备结束谈话时，请说“我得走了”。\",\n", " llm_config=llm_config,\n", " human_input_mode=\"NEVER\",\n", - " is_termination_msg=lambda msg: \"I gotta go\" in msg[\"content\"],\n", + " is_termination_msg=lambda msg: \"我得走了\" in msg[\"content\"],\n", ")\n", "\n", "joe = ConversableAgent(\n", " name=\"joe\",\n", " system_message=\n", - " \"Your name is Joe and you are a stand-up comedian. \"\n", - " \"When you're ready to end the conversation, say 'I gotta go'.\",\n", + " \"你的名字是Joe，你是一位相声演员\",\n", + " \"当你准备结束谈话时，请说“我得走了”。\",\n", " llm_config=llm_config,\n", " human_input_mode=\"NEVER\",\n", - " is_termination_msg=lambda msg: \"I gotta go\" in msg[\"content\"] or \"Goodbye\" in msg[\"content\"],\n", + " is_termination_msg=lambda msg: \"我得走了\" in msg[\"content\"] or \"再见\" in msg[\"content\"],\n", ")" ] }, @@ -561,9 +580,10 @@ } ], "source": [ + "# 此时，我们没有显示的规定对话的终止轮数，而是通过判断对话中是否出现了关键的预设字段来结束对话。\n", "chat_result = joe.initiate_chat(\n", " recipient=cathy,\n", - " message=\"I'm Joe. Cathy, let's keep the jokes rolling.\"\n", + " message=\"我是Joe。Cathy,让我们持续不断地讲笑话吧。\"\n", ")" ] }, @@ -572,7 +592,7 @@ "id": "757d4a9c-94b6-457e-abde-39730e8dbbd6", "metadata": {}, "source": [ - "这里我们将终止条件设置为了当对话内容表达式中出现`I gotta go`这一字符串时终止对话。在此之前我们的两位Agent进行了多轮的交互。" + "这里我们将终止条件设置为了当对话内容表达式中出现 “我得走了” 这一字符串时终止对话。在此之前我们的两位Agent进行了多轮的交互。" ] }, { @@ -606,7 +626,7 @@ } ], "source": [ - "cathy.send(message=\"What's last joke we talked about?\", recipient=joe)" + "cathy.send(message=\"我们谈论的最后一个笑话是什么？\", recipient=joe)" ] }, { @@ -614,7 +634,7 @@ "id": "a9beb8b0-b8ce-4660-8a49-66ce13747144", "metadata": {}, "source": [ - "这里我们可以再次从先前结束的那轮对话开始继续让两个Agent进行交互。可以看到由于有对话记忆，能够正确的输出最后一轮的笑话。此外，在cathy输出`I gotta go`之后对话再次满足停止条件并终止。" + "这里我们可以再次从先前结束的那轮对话开始继续让两个Agent进行交互。可以看到由于有对话记忆，能够正确的输出最后一轮的笑话。此外，在cathy输出 “我得走了” 之后对话再次满足停止条件并终止。" ] }, { @@ -642,7 +662,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.10.14" } }, "nbformat": 4, 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zl}m5%5d+@MCJG+bxGG-wd*(n{*k{!$4^%F6lvK55k?rnL2HRs|o9k#lEal5h5f@r& z?xR|=)c(^#p{p&ii0UR@ zO)2%lc-pHKZ42%aJe_ulAPv^md9jZ3F`dT%98QpG>fSrU5vs}V=g**A(QxI=SMs$U z#NUCGq>!LZKoJ7en)UN>Yf@tLm-b*EhRq!<+b(j~l@lC2lZz)@H2Nkq_wI+lPop_u zt)QbvH3qj^n-5bYR}h{e=`Hq#s?>bT1X67XA3)F0CTewOyQATeK|zeB7%hgoo7RuK z2RS|G+jiFpz@ua+sIy5~0VLM!3! zY|;e!vFqH=>16f%drED{QEvyBjtk(okW5;SFuPXIPH?98>|Q*u{#?Y7s)~b{xNmp@ z6Jv5-kU5Kkj1+NJcXzS4w#26QlE6ERXZ=a+Dn zBt?G~X`2boc)KsUnnHIt5+No2XAkN|n?iiWH+G-b2MKrE5^Z<;SIy z`?hZ?_DZ)j!YNTwGlZ5xFZc7j+in&HI_I%VETP!xS+|?(zKuusVhvpz;k!daEy)T~ z6NUcDz%~>DB_yOApUtp87Z-I782y$S)e4QkCHr{PCy>tj31E}~8Oh$k2nI-0MSDC= z2~e Date: Sun, 2 Jun 2024 13:37:39 +0800 Subject: [PATCH 08/24] update auto chapter2, fix translation as well as add some images --- ...\347\233\270\345\243\260 multi-agent-conversation.ipynb" | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git "a/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" "b/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" index 52f800c9..3fea7641 100644 --- "a/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" +++ "b/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" @@ -59,7 +59,7 @@ "id": "34427c37", "metadata": {}, "source": [ - "最后，记得在`.env`文件中填入有效的`OPENAI_API_KEY`" + "最后，记得在`.env`文件中填入有效的`OPENAI_API_KEY`以及可选的`OPENAI_BASE_URL`哦🥰" ] }, { @@ -89,7 +89,7 @@ "outputs": [], "source": [ "from utils import get_openai_api_key, get_openai_base_url\n", - "OPENAI_API_KEY = get_openai_api_key() # 获取api_key\n", + "OPENAI_API_KEY = get_openai_api_key() # 获取api_key，c\n", "OPENAI_BASE_URL = get_openai_base_url() # 获取base_url，如果不用则可以直接注释该行\n", "llm_config = {\"model\": \"gpt-3.5-turbo\"} # 这里使用的模型名称为gpt-3.5-turbo" ] @@ -188,7 +188,7 @@ { "attachments": {}, "cell_type": "markdown", - "id": "70f99de6", + "id": "98a6ce25", "metadata": {}, "source": [ "![fig2.1](https://github.com/datawhalechina/llm-cookbook/blob/main/content/autogen/images/fig-2-1.png?raw=true)\n", From 9f8e54b4da9d5da3641181167955cef81c1f80e4 Mon Sep 17 00:00:00 2001 From: Tsumugii24 <2792474059@qq.com> Date: Sun, 2 Jun 2024 14:19:06 +0800 Subject: [PATCH 09/24] update auto chapter2, fix translation as well as add some images --- ...45\243\260 multi-agent-conversation.ipynb" | 201 ++++++++---------- 1 file changed, 87 insertions(+), 114 deletions(-) diff --git "a/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" "b/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" index 3fea7641..14601c06 100644 --- "a/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" +++ "b/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" @@ -81,7 +81,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 18, "id": "04d006c1-22fa-40ea-b3e0-d543142e0788", "metadata": { "height": 64 @@ -89,8 +89,8 @@ "outputs": [], "source": [ "from utils import get_openai_api_key, get_openai_base_url\n", - "OPENAI_API_KEY = get_openai_api_key() # 获取api_key，c\n", - "OPENAI_BASE_URL = get_openai_base_url() # 获取base_url，如果不用则可以直接注释该行\n", + "OPENAI_API_KEY = get_openai_api_key() # 获取api_key，此项是必须的\n", + "OPENAI_BASE_URL = get_openai_base_url() # 获取base_url，此项可选，如果不用则可以直接注释该行\n", "llm_config = {\"model\": \"gpt-3.5-turbo\"} # 这里使用的模型名称为gpt-3.5-turbo" ] }, @@ -104,7 +104,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 19, "id": "6fb8c441-c58c-41a8-a54b-5c387afceac5", "metadata": { "height": 132 @@ -123,7 +123,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 20, "id": "47886b5f-fc7c-431a-8036-cff6e88f85c6", "metadata": { "height": 80 @@ -133,7 +133,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Sure, here you go: Why did the scarecrow win an award? Because he was outstanding in his field!\n" + "当两个细胞相遇，一半提议：你配我吗？ 另一半回答：我们在一起吧，我们要变得更有型！\n" ] } ], @@ -146,7 +146,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 21, "id": "67f626e9-4cec-40c1-abde-2eff1252b848", "metadata": { "height": 96 @@ -156,7 +156,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Of course! Please share the joke you'd like me to repeat.\n" + "为了保持新鲜感，我会告诉你另外一个笑话：为什么小鸡不生病？因为它有禽力！哈哈哈！希望这个笑话能让您开心一下！\n" ] } ], @@ -186,9 +186,8 @@ ] }, { - "attachments": {}, "cell_type": "markdown", - "id": "98a6ce25", + "id": "0b72c4dd", "metadata": {}, "source": [ "![fig2.1](https://github.com/datawhalechina/llm-cookbook/blob/main/content/autogen/images/fig-2-1.png?raw=true)\n", @@ -197,7 +196,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 22, "id": "8f109dcb-824e-40d7-8e86-efee42b75f3c", "metadata": { "height": 300 @@ -232,7 +231,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 23, "id": "46a1c6f6-687e-40de-8819-374201cfed9f", "metadata": { "height": 97 @@ -244,22 +243,33 @@ "text": [ "\u001b[33mjoe\u001b[0m (to cathy):\n", "\n", - "I'm Joe. Cathy, let's keep the jokes rolling.\n", + "我是Joe。Cathy,让我们持续不断地讲笑话吧。\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mcathy\u001b[0m (to joe):\n", "\n", - "Hey Joe! Alright, let's get this comedy train chugging along. So, I recently went on a strict diet and it taught me one important lesson - never grocery shop when you're hungry. I ended up with a cart full of snacks that were either half-eaten or had \"family size\" written on them... and by family, I mean just me. But hey, at least my pantry is prepared for any sudden snack attacks, right?\n", + "当然，Joe！让我来给你讲一个相声段子：\n", + "Cathy: \"你知道为什么买衣服要试穿吗？\"\n", + "Joe: \"为什么？\"\n", + "Cathy: \"因为有些衣服，看着很文雅、挺得很直，一穿上去，就变成了土豪金！\" \n", + "\n", + "哈哈，怎么样，好笑吗？现在轮到你了，来讲一个笑话吧！\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mjoe\u001b[0m (to cathy):\n", "\n", - "Haha, that's so relatable! I mean, who knew family size meant just one hungry person, right? Speaking of snacking, I recently tried to work out at home to stay in shape, but those fitness videos are no joke. I paused the video to take a break, and it buffered long enough for me to order a pizza, eat it, and then hit play again - and the instructor was still on the warm-up!\n", + "哈哈，好笑好笑！那我来讲一个：\n", + "\n", + "Joe: \"你知道为什么粽子不爱光着脚去逛街吗？\"\n", + "Cathy: \"为什么？\"\n", + "Joe: \"因为它怕被蚊子咬出个包，然后被人误认为是猪蹄！\" \n", + "\n", + "哈哈，怎么样，是不是有点意思？继续一起笑下去吧！\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mcathy\u001b[0m (to joe):\n", "\n", - "Haha, that's impressive dedication right there, Joe! It's like workout buffering is the universe's way of saying, \"Are you sure about this whole fitness thing?\" I feel like I should make a workout video where the warm-up is just trying to find the motivation to press play. The real exercise is fighting the urge to switch over to Netflix instead. But hey, at least you got some quality pizza time in, right? Priorities, my friend, priorities.\n", + "哈哈哈，太有创意了，Joe！这个笑话真是太逗了！笑声是最好的药物，让我们继续一起分享快乐吧！如果你还有更多好笑的段子，尽管来，我随时准备好了！\n", "\n", "--------------------------------------------------------------------------------\n" ] @@ -289,7 +299,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 24, "id": "1169ea24-eadd-4909-8d56-9b7ec5677c66", "metadata": { "height": 63 @@ -299,31 +309,23 @@ "name": "stdout", "output_type": "stream", "text": [ - "[{'content': \"I'm Joe. Cathy, let's keep the jokes rolling.\",\n", - " 'role': 'assistant'},\n", - " {'content': \"Hey Joe! Alright, let's get this comedy train chugging along. \"\n", - " 'So, I recently went on a strict diet and it taught me one '\n", - " \"important lesson - never grocery shop when you're hungry. I \"\n", - " 'ended up with a cart full of snacks that were either half-eaten '\n", - " 'or had \"family size\" written on them... and by family, I mean '\n", - " 'just me. But hey, at least my pantry is prepared for any sudden '\n", - " 'snack attacks, right?',\n", + "[{'content': '我是Joe。Cathy,让我们持续不断地讲笑话吧。', 'role': 'assistant'},\n", + " {'content': '当然，Joe！让我来给你讲一个相声段子：\\n'\n", + " 'Cathy: \"你知道为什么买衣服要试穿吗？\"\\n'\n", + " 'Joe: \"为什么？\"\\n'\n", + " 'Cathy: \"因为有些衣服，看着很文雅、挺得很直，一穿上去，就变成了土豪金！\" \\n'\n", + " '\\n'\n", + " '哈哈，怎么样，好笑吗？现在轮到你了，来讲一个笑话吧！',\n", " 'role': 'user'},\n", - " {'content': \"Haha, that's so relatable! I mean, who knew family size meant \"\n", - " 'just one hungry person, right? Speaking of snacking, I recently '\n", - " 'tried to work out at home to stay in shape, but those fitness '\n", - " 'videos are no joke. I paused the video to take a break, and it '\n", - " 'buffered long enough for me to order a pizza, eat it, and then '\n", - " 'hit play again - and the instructor was still on the warm-up!',\n", + " {'content': '哈哈，好笑好笑！那我来讲一个：\\n'\n", + " '\\n'\n", + " 'Joe: \"你知道为什么粽子不爱光着脚去逛街吗？\"\\n'\n", + " 'Cathy: \"为什么？\"\\n'\n", + " 'Joe: \"因为它怕被蚊子咬出个包，然后被人误认为是猪蹄！\" \\n'\n", + " '\\n'\n", + " '哈哈，怎么样，是不是有点意思？继续一起笑下去吧！',\n", " 'role': 'assistant'},\n", - " {'content': \"Haha, that's impressive dedication right there, Joe! It's like \"\n", - " 'workout buffering is the universe\\'s way of saying, \"Are you '\n", - " 'sure about this whole fitness thing?\" I feel like I should make '\n", - " 'a workout video where the warm-up is just trying to find the '\n", - " 'motivation to press play. The real exercise is fighting the urge '\n", - " 'to switch over to Netflix instead. But hey, at least you got '\n", - " 'some quality pizza time in, right? Priorities, my friend, '\n", - " 'priorities.',\n", + " {'content': '哈哈哈，太有创意了，Joe！这个笑话真是太逗了！笑声是最好的药物，让我们继续一起分享快乐吧！如果你还有更多好笑的段子，尽管来，我随时准备好了！',\n", " 'role': 'user'}]\n" ] } @@ -336,7 +338,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 25, "id": "550267b6-3652-40dc-9997-c5401f6d4c47", "metadata": { "height": 29 @@ -346,16 +348,16 @@ "name": "stdout", "output_type": "stream", "text": [ - "{'usage_excluding_cached_inference': {'gpt-3.5-turbo-0125': {'completion_tokens': 277,\n", - " 'cost': 0.0006180000000000001,\n", - " 'prompt_tokens': 405,\n", - " 'total_tokens': 682},\n", - " 'total_cost': 0.0006180000000000001},\n", - " 'usage_including_cached_inference': {'gpt-3.5-turbo-0125': {'completion_tokens': 277,\n", - " 'cost': 0.0006180000000000001,\n", - " 'prompt_tokens': 405,\n", - " 'total_tokens': 682},\n", - " 'total_cost': 0.0006180000000000001}}\n" + "{'usage_excluding_cached_inference': {'gpt-3.5-turbo-0125': {'completion_tokens': 331,\n", + " 'cost': 0.000776,\n", + " 'prompt_tokens': 559,\n", + " 'total_tokens': 890},\n", + " 'total_cost': 0.000776},\n", + " 'usage_including_cached_inference': {'gpt-3.5-turbo-0125': {'completion_tokens': 331,\n", + " 'cost': 0.000776,\n", + " 'prompt_tokens': 559,\n", + " 'total_tokens': 890},\n", + " 'total_cost': 0.000776}}\n" ] } ], @@ -365,7 +367,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 26, "id": "dfcf468e-d217-4731-8cb4-3485377230f1", "metadata": { "height": 29 @@ -375,12 +377,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "(\"Haha, that's impressive dedication right there, Joe! It's like workout \"\n", - " 'buffering is the universe\\'s way of saying, \"Are you sure about this whole '\n", - " 'fitness thing?\" I feel like I should make a workout video where the warm-up '\n", - " 'is just trying to find the motivation to press play. The real exercise is '\n", - " 'fighting the urge to switch over to Netflix instead. But hey, at least you '\n", - " 'got some quality pizza time in, right? Priorities, my friend, priorities.')\n" + "'哈哈哈，太有创意了，Joe！这个笑话真是太逗了！笑声是最好的药物，让我们继续一起分享快乐吧！如果你还有更多好笑的段子，尽管来，我随时准备好了！'\n" ] } ], @@ -406,7 +403,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 27, "id": "c1a8fef1-8030-4652-a2d2-1648834f62c2", "metadata": { "height": 131 @@ -418,22 +415,33 @@ "text": [ "\u001b[33mjoe\u001b[0m (to cathy):\n", "\n", - "I'm Joe. Cathy, let's keep the jokes rolling.\n", + "我是Joe。Cathy,让我们持续不断地讲笑话吧。\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mcathy\u001b[0m (to joe):\n", "\n", - "Hey Joe! Alright, let's get this comedy train chugging along. So, I recently went on a strict diet and it taught me one important lesson - never grocery shop when you're hungry. I ended up with a cart full of snacks that were either half-eaten or had \"family size\" written on them... and by family, I mean just me. But hey, at least my pantry is prepared for any sudden snack attacks, right?\n", + "当然，Joe！让我来给你讲一个相声段子：\n", + "Cathy: \"你知道为什么买衣服要试穿吗？\"\n", + "Joe: \"为什么？\"\n", + "Cathy: \"因为有些衣服，看着很文雅、挺得很直，一穿上去，就变成了土豪金！\" \n", + "\n", + "哈哈，怎么样，好笑吗？现在轮到你了，来讲一个笑话吧！\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mjoe\u001b[0m (to cathy):\n", "\n", - "Haha, that's so relatable! I mean, who knew family size meant just one hungry person, right? Speaking of snacking, I recently tried to work out at home to stay in shape, but those fitness videos are no joke. I paused the video to take a break, and it buffered long enough for me to order a pizza, eat it, and then hit play again - and the instructor was still on the warm-up!\n", + "哈哈，好笑好笑！那我来讲一个：\n", + "\n", + "Joe: \"你知道为什么粽子不爱光着脚去逛街吗？\"\n", + "Cathy: \"为什么？\"\n", + "Joe: \"因为它怕被蚊子咬出个包，然后被人误认为是猪蹄！\" \n", + "\n", + "哈哈，怎么样，是不是有点意思？继续一起笑下去吧！\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mcathy\u001b[0m (to joe):\n", "\n", - "Haha, that's impressive dedication right there, Joe! It's like workout buffering is the universe's way of saying, \"Are you sure about this whole fitness thing?\" I feel like I should make a workout video where the warm-up is just trying to find the motivation to press play. The real exercise is fighting the urge to switch over to Netflix instead. But hey, at least you got some quality pizza time in, right? Priorities, my friend, priorities.\n", + "哈哈哈，太有创意了，Joe！这个笑话真是太逗了！笑声是最好的药物，让我们继续一起分享快乐吧！如果你还有更多好笑的段子，尽管来，我随时准备好了！\n", "\n", "--------------------------------------------------------------------------------\n" ] @@ -445,13 +453,13 @@ " message=\"我是Joe。Cathy,让我们持续不断地讲笑话吧。\", \n", " max_turns=2, # 设置最大轮数为2\n", " summary_method=\"reflection_with_llm\", # 设置总结方法为使用大语言模型总结\n", - " summary_prompt=\"总结对话\",\n", + " summary_prompt=\"使用中文总结对话\", # 设置总结的系统提示词\n", ")" ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 28, "id": "b042de62-bc49-49ee-99f2-4f972e23670b", "metadata": { "height": 29 @@ -461,9 +469,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "('Watch out for the \"family size\" label when shopping hungry and be prepared '\n", - " 'for long workout video buffering breaks with a pizza pitstop. Priorities, my '\n", - " 'friend, priorities.')\n" + "('Joe and Cathy enjoy sharing jokes and humor with each other. They took turns '\n", + " 'telling funny jokes and had a good time laughing together. They highlighted '\n", + " 'the importance of humor and laughter in bringing happiness and joy.')\n" ] } ], @@ -491,7 +499,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 30, "id": "044dfd61-7f1d-46d8-9e28-4b2601b43d70", "metadata": { "height": 351 @@ -501,7 +509,7 @@ "cathy = ConversableAgent(\n", " name=\"cathy\",\n", " system_message=\n", - " \"你的名字是Cathy，你是一位相声演员\",\n", + " \"你的名字是Cathy，你是一位相声演员\"\n", " \"当你准备结束谈话时，请说“我得走了”。\",\n", " llm_config=llm_config,\n", " human_input_mode=\"NEVER\",\n", @@ -511,7 +519,7 @@ "joe = ConversableAgent(\n", " name=\"joe\",\n", " system_message=\n", - " \"你的名字是Joe，你是一位相声演员\",\n", + " \"你的名字是Joe，你是一位相声演员\"\n", " \"当你准备结束谈话时，请说“我得走了”。\",\n", " llm_config=llm_config,\n", " human_input_mode=\"NEVER\",\n", @@ -521,7 +529,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 32, "id": "bc49d959-1025-4709-8866-9d4035eaeae7", "metadata": { "height": 80 @@ -533,47 +541,12 @@ "text": [ "\u001b[33mjoe\u001b[0m (to cathy):\n", "\n", - "I'm Joe. Cathy, let's keep the jokes rolling.\n", - "\n", - "--------------------------------------------------------------------------------\n", - "\u001b[33mcathy\u001b[0m (to joe):\n", - "\n", - "Hey Joe! Why did the scarecrow win an award? Because he was outstanding in his field!\n", - "\n", - "--------------------------------------------------------------------------------\n", - "\u001b[33mjoe\u001b[0m (to cathy):\n", - "\n", - "Haha, that's a good one, Cathy! Have you heard about the claustrophobic astronaut? He just needed a little space!\n", - "\n", - "--------------------------------------------------------------------------------\n", - "\u001b[33mcathy\u001b[0m (to joe):\n", - "\n", - "Haha, that's a good one, Joe! How do you organize a space party? You planet!\n", - "\n", - "--------------------------------------------------------------------------------\n", - "\u001b[33mjoe\u001b[0m (to cathy):\n", - "\n", - "Haha, great one, Cathy! You're on fire with the space jokes. Did you hear about the mathematician who's afraid of negative numbers? He will stop at nothing to avoid them!\n", - "\n", - "--------------------------------------------------------------------------------\n", - "\u001b[33mcathy\u001b[0m (to joe):\n", - "\n", - "Haha, I love it, Joe! Why don't scientists trust atoms? Because they make up everything!\n", - "\n", - "--------------------------------------------------------------------------------\n", - "\u001b[33mjoe\u001b[0m (to cathy):\n", - "\n", - "Haha, spot on, Cathy! You've got some great jokes up your sleeve. Speaking of jokes, have you heard about the guy who invented Lifesavers? He made a mint!\n", + "我是Joe。让我们持续不断地讲笑话吧，Cathy。\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mcathy\u001b[0m (to joe):\n", "\n", - "Haha, that's a classic one, Joe! I guess you could say he really cleaned up with that invention!\n", - "\n", - "--------------------------------------------------------------------------------\n", - "\u001b[33mjoe\u001b[0m (to cathy):\n", - "\n", - "Haha, absolutely, Cathy! He definitely made a splash in the confectionery world. Hey, thanks for the laughs and jokes, but I gotta go. Have a great day!\n", + "当然，Joe！一起分享快乐总是很棒。不过现在我得走了。保持开心，再见！\n", "\n", "--------------------------------------------------------------------------------\n" ] @@ -583,7 +556,7 @@ "# 此时，我们没有显示的规定对话的终止轮数，而是通过判断对话中是否出现了关键的预设字段来结束对话。\n", "chat_result = joe.initiate_chat(\n", " recipient=cathy,\n", - " message=\"我是Joe。Cathy,让我们持续不断地讲笑话吧。\"\n", + " message=\"我是Joe。让我们持续不断地讲笑话吧，Cathy。\"\n", ")" ] }, @@ -597,7 +570,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 33, "id": "846eccbd-efd1-464b-9385-279c19b17c1d", "metadata": { "height": 45 @@ -609,17 +582,17 @@ "text": [ "\u001b[33mcathy\u001b[0m (to joe):\n", "\n", - "What's last joke we talked about?\n", + "我们谈论的最后一个笑话是什么？\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mjoe\u001b[0m (to cathy):\n", "\n", - "The last joke we talked about was about the guy who invented Lifesavers and how he made a mint.\n", + "抱歉，我无法长时间记住对话内容或重现早前的对话内容。再见，祝你有愉快的一天！\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[33mcathy\u001b[0m (to joe):\n", "\n", - "I gotta go.\n", + "没关系，Joe。再见，祝你也有愉快的一天！我得走了。\n", "\n", "--------------------------------------------------------------------------------\n" ] From ced420616cbbe113d92eec8be8686bc17f0e243a Mon Sep 17 00:00:00 2001 From: Tsumugii24 <2792474059@qq.com> Date: Mon, 3 Jun 2024 22:00:15 +0800 Subject: [PATCH 10/24] update auto chapter2 & chapter5, fix translation as well as add some images --- ...45\243\260 multi-agent-conversation.ipynb" | 30 ++++++++++++++++-- ...05\350\261\241\346\243\213 tool-use.ipynb" | 2 +- .../images/fig-2-1.png | Bin 19797 -> 38796 bytes .../images/fig-2-2.png | Bin 0 -> 19797 bytes 4 files changed, 28 insertions(+), 4 deletions(-) create mode 100644 content/AI Agentic Design Patterns with AutoGen/images/fig-2-2.png diff --git "a/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" "b/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" index 14601c06..3ccbcefe 100644 --- "a/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" +++ "b/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" @@ -5,7 +5,7 @@ "id": "a81456dd", "metadata": {}, "source": [ - "# 多智能体对话和相声" + "# 2.多智能体对话和相声" ] }, { @@ -117,10 +117,27 @@ "agent = ConversableAgent(\n", " name=\"chatbot\",\n", " llm_config=llm_config,\n", - " human_input_mode=\"NEVER\", # 这里设置人为不介入\n", + " human_input_mode=\"NEVER\", # 这里设置不使用人类反馈介入\n", ")" ] }, + { + "cell_type": "markdown", + "id": "efc51ca7-6bfb-4572-a04c-a5a7d012f0bb", + "metadata": {}, + "source": [ + "在 `AutoGen` 的 `ConversableAgent` 中，人工循环组件位于自动回复组件的前面。
\n", + "它可以拦截传入的消息，并决定是否将它们传递给自动回复组件或提供人工反馈。逻辑架构如图所示：" + ] + }, + { + "cell_type": "markdown", + "id": "77706a1b-8b7b-42ed-888b-ecaca4ebce36", + "metadata": {}, + "source": [ + "![fig2.1](https://github.com/datawhalechina/llm-cookbook/blob/main/content/autogen/images/fig-2-1.png?raw=true)" + ] + }, { "cell_type": "code", "execution_count": 20, @@ -190,7 +207,14 @@ "id": "0b72c4dd", "metadata": {}, "source": [ - "![fig2.1](https://github.com/datawhalechina/llm-cookbook/blob/main/content/autogen/images/fig-2-1.png?raw=true)\n", + "![fig2.2](https://github.com/datawhalechina/llm-cookbook/blob/main/content/autogen/images/fig-2-2.png?raw=true)" + ] + }, + { + "cell_type": "markdown", + "id": "52f74a5b-55b0-479e-8257-d2400edb0e0b", + "metadata": {}, + "source": [ "我们通过定义两个可以对话的Agent，赋予它们相声演员的职责设定，就可以驱动它们完成相声的交互了。" ] }, diff --git "a/content/AI Agentic Design Patterns with AutoGen/5.\345\267\245\345\205\267\344\275\277\347\224\250\345\222\214\345\233\275\351\231\205\350\261\241\346\243\213 tool-use.ipynb" "b/content/AI Agentic Design Patterns with AutoGen/5.\345\267\245\345\205\267\344\275\277\347\224\250\345\222\214\345\233\275\351\231\205\350\261\241\346\243\213 tool-use.ipynb" index 5d61ba7c..38ca537a 100644 --- "a/content/AI Agentic Design Patterns with AutoGen/5.\345\267\245\345\205\267\344\275\277\347\224\250\345\222\214\345\233\275\351\231\205\350\261\241\346\243\213 tool-use.ipynb" +++ "b/content/AI Agentic Design Patterns with AutoGen/5.\345\267\245\345\205\267\344\275\277\347\224\250\345\222\214\345\233\275\351\231\205\350\261\241\346\243\213 tool-use.ipynb" @@ -5,7 +5,7 @@ "id": "9a6dd449", "metadata": {}, "source": [ - "# 工具使用和国际象棋" + "# 5.工具使用和国际象棋" ] }, { diff --git a/content/AI Agentic Design Patterns with AutoGen/images/fig-2-1.png b/content/AI Agentic Design Patterns with AutoGen/images/fig-2-1.png index ea0fbf1526428d27d97ca4eef59c7088171cfc8b..bc349fabb00c1a0a280e58ff8d3b4bfec3dc99e7 100644 GIT binary patch literal 38796 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zl}m5%5d+@MCJG+bxGG-wd*(n{*k{!$4^%F6lvK55k?rnL2HRs|o9k#lEal5h5f@r& z?xR|=)c(^#p{p&ii0UR@ zO)2%lc-pHKZ42%aJe_ulAPv^md9jZ3F`dT%98QpG>fSrU5vs}V=g**A(QxI=SMs$U z#NUCGq>!LZKoJ7en)UN>Yf@tLm-b*EhRq!<+b(j~l@lC2lZz)@H2Nkq_wI+lPop_u zt)QbvH3qj^n-5bYR}h{e=`Hq#s?>bT1X67XA3)F0CTewOyQATeK|zeB7%hgoo7RuK z2RS|G+jiFpz@ua+sIy5~0VLM!3! zY|;e!vFqH=>16f%drED{QEvyBjtk(okW5;SFuPXIPH?98>|Q*u{#?Y7s)~b{xNmp@ z6Jv5-kU5Kkj1+NJcXzS4w#26QlE6ERXZ=a+Dn zBt?G~X`2boc)KsUnnHIt5+No2XAkN|n?iiWH+G-b2MKrE5^Z<;SIy z`?hZ?_DZ)j!YNTwGlZ5xFZc7j+in&HI_I%VETP!xS+|?(zKuusVhvpz;k!daEy)T~ z6NUcDz%~>DB_yOApUtp87Z-I782y$S)e4QkCHr{PCy>tj31E}~8Oh$k2nI-0MSDC= z2~e Date: Mon, 3 Jun 2024 22:13:33 +0800 Subject: [PATCH 11/24] update autogen chapter5, fix translation --- ...05\350\261\241\346\243\213 tool-use.ipynb" | 238 ++++++++++-------- 1 file changed, 129 insertions(+), 109 deletions(-) diff --git "a/content/AI Agentic Design Patterns with AutoGen/5.\345\267\245\345\205\267\344\275\277\347\224\250\345\222\214\345\233\275\351\231\205\350\261\241\346\243\213 tool-use.ipynb" "b/content/AI Agentic Design Patterns with AutoGen/5.\345\267\245\345\205\267\344\275\277\347\224\250\345\222\214\345\233\275\351\231\205\350\261\241\346\243\213 tool-use.ipynb" index 38ca537a..6461ac6a 100644 --- "a/content/AI Agentic Design Patterns with AutoGen/5.\345\267\245\345\205\267\344\275\277\347\224\250\345\222\214\345\233\275\351\231\205\350\261\241\346\243\213 tool-use.ipynb" +++ "b/content/AI Agentic Design Patterns with AutoGen/5.\345\267\245\345\205\267\344\275\277\347\224\250\345\222\214\345\233\275\351\231\205\350\261\241\346\243\213 tool-use.ipynb" @@ -18,7 +18,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 9, "id": "6032c971-8934-4018-8743-eace0553578c", "metadata": { "height": 30 @@ -33,7 +33,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 10, "id": "086cb574-1299-43ce-90b4-79e089a76a11", "metadata": { "height": 64 @@ -55,7 +55,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 11, "id": "10161c38-0fe6-4a03-a5ff-069e8374a1d8", "metadata": { "height": 30 @@ -67,7 +67,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 12, "id": "c799e0a9-be62-4c20-b524-7a39d125f46d", "metadata": { "height": 30 @@ -89,7 +89,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 13, "id": "78607e9f-47b0-419e-b652-dd6b5b0390c1", "metadata": { "height": 114 @@ -98,8 +98,8 @@ "source": [ "def get_legal_moves(\n", " \n", - ") -> Annotated[str, \"A list of legal moves in UCI format\"]:\n", - " return \"Possible moves are: \" + \",\".join(\n", + ") -> Annotated[str, \"UCI格式的合法移动列表\"]:\n", + " return \"可以采取的移动方式如下: \" + \",\".join(\n", " [str(move) for move in board.legal_moves]\n", " )" ] @@ -114,7 +114,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 14, "id": "08a09854-dfd4-495c-84c1-8ea1dd8cacdb", "metadata": { "height": 505 @@ -122,8 +122,8 @@ "outputs": [], "source": [ "def make_move(\n", - " move: Annotated[str, \"A move in UCI format.\"]\n", - ") -> Annotated[str, \"Result of the move.\"]:\n", + " move: Annotated[str, \"一次UCI格式的移动\"]\n", + ") -> Annotated[str, \"移动的结果\"]:\n", " move = chess.Move.from_uci(move)\n", " board.push_uci(str(move))\n", " global made_move\n", @@ -184,7 +184,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 15, "id": "3055679f-5f69-4d32-aff6-076925a36174", "metadata": { "height": 29 @@ -196,7 +196,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 16, "id": "9466949c-c2cf-4bba-8307-d7ff4b70a948", "metadata": { "height": 164 @@ -205,17 +205,17 @@ "source": [ "# 白色方智能体\n", "player_white = ConversableAgent(\n", - " name=\"Player White\",\n", - " system_message=\"You are a chess player and you play as white. \"\n", - " \"First call get_legal_moves(), to get a list of legal moves. \"\n", - " \"Then call make_move(move) to make a move.\",\n", + " name=\"白方\",\n", + " system_message=\"你是一名国际象棋手，你是白方。 \"\n", + " \"首先调用 get_legal_moves(), 来获取合法移动列表。 \"\n", + " \"首先调用 get_legal_moves(), 来获取合法移动列表。 \",\n", " llm_config=llm_config,\n", ")" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 17, "id": "dcb6a474-2691-425c-8558-beb3363cd2bb", "metadata": { "height": 164 @@ -224,17 +224,17 @@ "source": [ "# 黑色方智能体\n", "player_black = ConversableAgent(\n", - " name=\"Player Black\",\n", - " system_message=\"You are a chess player and you play as black. \"\n", - " \"First call get_legal_moves(), to get a list of legal moves. \"\n", - " \"Then call make_move(move) to make a move.\",\n", + " name=\"黑方\",\n", + " system_message=\"你是一名国际象棋手，你是黑方。 \"\n", + " \"首先调用 get_legal_moves(), 来获取合法移动列表。 \"\n", + " \"首先调用 get_legal_moves(), 来获取合法移动列表。 \",\n", " llm_config=llm_config,\n", ")" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 18, "id": "6b69ac38-6399-425a-9681-4a2b7403a4bf", "metadata": { "height": 148 @@ -252,7 +252,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 19, "id": "c3eaa260-422c-4e44-a355-42f0d885e9bc", "metadata": { "height": 131 @@ -260,10 +260,10 @@ "outputs": [], "source": [ "board_proxy = ConversableAgent(\n", - " name=\"Board Proxy\",\n", + " name=\"棋局裁判\",\n", " llm_config=False,\n", " is_termination_msg=check_made_move,\n", - " default_auto_reply=\"Please make a move.\",\n", + " default_auto_reply=\"请执行一次移动。\",\n", " human_input_mode=\"NEVER\",\n", ")" ] @@ -280,7 +280,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 20, "id": "5caf8ae1-4b39-4be5-89fa-0d57b4595841", "metadata": { "height": 29 @@ -292,7 +292,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 21, "id": "880a9926-d76b-4322-872c-b691d933506e", "metadata": { "height": 284 @@ -319,7 +319,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 22, "id": "dd487d3e-9226-4764-bd25-b452c1993388", "metadata": { "height": 29 @@ -336,12 +336,11 @@ " 'function': {'description': 'Call this tool to make a move.',\n", " 'name': 'make_move',\n", " 'parameters': {'type': 'object',\n", - " 'properties': {'move': {'type': 'string',\n", - " 'description': 'A move in UCI format.'}},\n", + " 'properties': {'move': {'type': 'string', 'description': '一次UCI格式的移动'}},\n", " 'required': ['move']}}}]" ] }, - "execution_count": 14, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -362,7 +361,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 23, "id": "3230f945-f302-4f39-bc37-766ca082fb28", "metadata": { "height": 369 @@ -412,7 +411,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 24, "id": "5595758f-7ae1-467f-bad9-79c6c7cd0b25", "metadata": { "height": 131 @@ -422,9 +421,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "\u001b[33mPlayer Black\u001b[0m (to Player White):\n", + "\u001b[33m黑方\u001b[0m (to 白方):\n", "\n", - "Let's play chess! Your move.\n", + "让我们开始国际象棋吧。先是你的移动回合。\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", @@ -434,16 +433,16 @@ "\u001b[34mStarting a new chat....\u001b[0m\n", "\u001b[34m\n", "********************************************************************************\u001b[0m\n", - "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\u001b[33m棋局裁判\u001b[0m (to 白方):\n", "\n", - "Let's play chess! Your move.\n", + "让我们开始国际象棋吧。先是你的移动回合。\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", - "\u001b[33mPlayer White\u001b[0m (to Board Proxy):\n", + "\u001b[33m白方\u001b[0m (to 棋局裁判):\n", "\n", - "\u001b[32m***** Suggested tool call (call_KrerPlbKm6AvUnVKyC11H0Uw): get_legal_moves *****\u001b[0m\n", + "\u001b[32m***** Suggested tool call (call_GDh7J7TyaVbdj7X9AagyO9b2): get_legal_moves *****\u001b[0m\n", "Arguments: \n", "{}\n", "\u001b[32m********************************************************************************\u001b[0m\n", @@ -451,20 +450,20 @@ "--------------------------------------------------------------------------------\n", "\u001b[35m\n", ">>>>>>>> EXECUTING FUNCTION get_legal_moves...\u001b[0m\n", - "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\u001b[33m棋局裁判\u001b[0m (to 白方):\n", "\n", - "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\u001b[33m棋局裁判\u001b[0m (to 白方):\n", "\n", - "\u001b[32m***** Response from calling tool (call_KrerPlbKm6AvUnVKyC11H0Uw) *****\u001b[0m\n", - "Possible moves are: g1h3,g1f3,b1c3,b1a3,h2h3,g2g3,f2f3,e2e3,d2d3,c2c3,b2b3,a2a3,h2h4,g2g4,f2f4,e2e4,d2d4,c2c4,b2b4,a2a4\n", + "\u001b[32m***** Response from calling tool (call_GDh7J7TyaVbdj7X9AagyO9b2) *****\u001b[0m\n", + "可以采取的移动方式如下: g1h3,g1f3,b1c3,b1a3,h2h3,g2g3,f2f3,e2e3,d2d3,c2c3,b2b3,a2a3,h2h4,g2g4,f2f4,e2e4,d2d4,c2c4,b2b4,a2a4\n", "\u001b[32m**********************************************************************\u001b[0m\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", - "\u001b[33mPlayer White\u001b[0m (to Board Proxy):\n", + "\u001b[33m白方\u001b[0m (to 棋局裁判):\n", "\n", - "\u001b[32m***** Suggested tool call (call_263Y3g9UFMtHfU2BaTLGtDp6): make_move *****\u001b[0m\n", + "\u001b[32m***** Suggested tool call (call_Xu3l9aeb58FuZUM0LGYAIbyf): make_move *****\u001b[0m\n", "Arguments: \n", "{\"move\":\"e2e4\"}\n", "\u001b[32m**************************************************************************\u001b[0m\n", @@ -497,25 +496,25 @@ "name": "stdout", "output_type": "stream", "text": [ - "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\u001b[33m棋局裁判\u001b[0m (to 白方):\n", "\n", - "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\u001b[33m棋局裁判\u001b[0m (to 白方):\n", "\n", - "\u001b[32m***** Response from calling tool (call_263Y3g9UFMtHfU2BaTLGtDp6) *****\u001b[0m\n", + "\u001b[32m***** Response from calling tool (call_Xu3l9aeb58FuZUM0LGYAIbyf) *****\u001b[0m\n", "Moved pawn (♙) from e2 to e4.\n", "\u001b[32m**********************************************************************\u001b[0m\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", - "\u001b[33mPlayer White\u001b[0m (to Board Proxy):\n", + "\u001b[33m白方\u001b[0m (to 棋局裁判):\n", "\n", - "I have moved my pawn from e2 to e4. Your move!\n", + "我已经把兵从e2移动到了e4。现在轮到你的回合了。\n", "\n", "--------------------------------------------------------------------------------\n", - "\u001b[33mPlayer White\u001b[0m (to Player Black):\n", + "\u001b[33m白方\u001b[0m (to 黑方):\n", "\n", - "I have moved my pawn from e2 to e4. Your move!\n", + "我已经把兵从e2移动到了e4。现在轮到你的回合了。\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", @@ -525,16 +524,16 @@ "\u001b[34mStarting a new chat....\u001b[0m\n", "\u001b[34m\n", "********************************************************************************\u001b[0m\n", - "\u001b[33mBoard Proxy\u001b[0m (to Player Black):\n", + "\u001b[33m棋局裁判\u001b[0m (to 黑方):\n", "\n", - "I have moved my pawn from e2 to e4. Your move!\n", + "我已经把兵从e2移动到了e4。现在轮到你的回合了。\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", - "\u001b[33mPlayer Black\u001b[0m (to Board Proxy):\n", + "\u001b[33m黑方\u001b[0m (to 棋局裁判):\n", "\n", - "\u001b[32m***** Suggested tool call (call_263Y3g9UFMtHfU2BaTLGtDp6): get_legal_moves *****\u001b[0m\n", + "\u001b[32m***** Suggested tool call (call_QvP8JTQgmwEPEoAR41HsT4WO): get_legal_moves *****\u001b[0m\n", "Arguments: \n", "{}\n", "\u001b[32m********************************************************************************\u001b[0m\n", @@ -542,20 +541,20 @@ "--------------------------------------------------------------------------------\n", "\u001b[35m\n", ">>>>>>>> EXECUTING FUNCTION get_legal_moves...\u001b[0m\n", - "\u001b[33mBoard Proxy\u001b[0m (to Player Black):\n", + "\u001b[33m棋局裁判\u001b[0m (to 黑方):\n", "\n", - "\u001b[33mBoard Proxy\u001b[0m (to Player Black):\n", + "\u001b[33m棋局裁判\u001b[0m (to 黑方):\n", "\n", - "\u001b[32m***** Response from calling tool (call_263Y3g9UFMtHfU2BaTLGtDp6) *****\u001b[0m\n", - "Possible moves are: g8h6,g8f6,b8c6,b8a6,h7h6,g7g6,f7f6,e7e6,d7d6,c7c6,b7b6,a7a6,h7h5,g7g5,f7f5,e7e5,d7d5,c7c5,b7b5,a7a5\n", + "\u001b[32m***** Response from calling tool (call_QvP8JTQgmwEPEoAR41HsT4WO) *****\u001b[0m\n", + "可以采取的移动方式如下: g8h6,g8f6,b8c6,b8a6,h7h6,g7g6,f7f6,e7e6,d7d6,c7c6,b7b6,a7a6,h7h5,g7g5,f7f5,e7e5,d7d5,c7c5,b7b5,a7a5\n", "\u001b[32m**********************************************************************\u001b[0m\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", - "\u001b[33mPlayer Black\u001b[0m (to Board Proxy):\n", + "\u001b[33m黑方\u001b[0m (to 棋局裁判):\n", "\n", - "\u001b[32m***** Suggested tool call (call_fVOjOUvYbIq3bdoZMazzWRe9): make_move *****\u001b[0m\n", + "\u001b[32m***** Suggested tool call (call_XXJCfHSWCUaoH6yu3pJYVr75): make_move *****\u001b[0m\n", "Arguments: \n", "{\"move\":\"e7e5\"}\n", "\u001b[32m**************************************************************************\u001b[0m\n", @@ -588,25 +587,25 @@ "name": "stdout", "output_type": "stream", "text": [ - "\u001b[33mBoard Proxy\u001b[0m (to Player Black):\n", + "\u001b[33m棋局裁判\u001b[0m (to 黑方):\n", "\n", - "\u001b[33mBoard Proxy\u001b[0m (to Player Black):\n", + "\u001b[33m棋局裁判\u001b[0m (to 黑方):\n", "\n", - "\u001b[32m***** Response from calling tool (call_fVOjOUvYbIq3bdoZMazzWRe9) *****\u001b[0m\n", + "\u001b[32m***** Response from calling tool (call_XXJCfHSWCUaoH6yu3pJYVr75) *****\u001b[0m\n", "Moved pawn (♟) from e7 to e5.\n", "\u001b[32m**********************************************************************\u001b[0m\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", - "\u001b[33mPlayer Black\u001b[0m (to Board Proxy):\n", + "\u001b[33m黑方\u001b[0m (to 棋局裁判):\n", "\n", - "I've moved my pawn from e7 to e5. Your move!\n", + "我已经移动了我的兵从e7到e5。轮到你了。\n", "\n", "--------------------------------------------------------------------------------\n", - "\u001b[33mPlayer Black\u001b[0m (to Player White):\n", + "\u001b[33m黑方\u001b[0m (to 白方):\n", "\n", - "I've moved my pawn from e7 to e5. Your move!\n", + "我已经移动了我的兵从e7到e5。轮到你了。\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", @@ -616,16 +615,16 @@ "\u001b[34mStarting a new chat....\u001b[0m\n", "\u001b[34m\n", "********************************************************************************\u001b[0m\n", - "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\u001b[33m棋局裁判\u001b[0m (to 白方):\n", "\n", - "I've moved my pawn from e7 to e5. Your move!\n", + "我已经移动了我的兵从e7到e5。轮到你了。\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", - "\u001b[33mPlayer White\u001b[0m (to Board Proxy):\n", + "\u001b[33m白方\u001b[0m (to 棋局裁判):\n", "\n", - "\u001b[32m***** Suggested tool call (call_3Rp1ex7Gobo4IaNmddJCHUde): get_legal_moves *****\u001b[0m\n", + "\u001b[32m***** Suggested tool call (call_88FEFpwX5rkDpPT9GKM0Qowd): get_legal_moves *****\u001b[0m\n", "Arguments: \n", "{}\n", "\u001b[32m********************************************************************************\u001b[0m\n", @@ -633,20 +632,41 @@ "--------------------------------------------------------------------------------\n", "\u001b[35m\n", ">>>>>>>> EXECUTING FUNCTION get_legal_moves...\u001b[0m\n", - "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\u001b[33m棋局裁判\u001b[0m (to 白方):\n", "\n", - "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\u001b[33m棋局裁判\u001b[0m (to 白方):\n", "\n", - "\u001b[32m***** Response from calling tool (call_3Rp1ex7Gobo4IaNmddJCHUde) *****\u001b[0m\n", - "Possible moves are: g1h3,g1f3,g1e2,f1a6,f1b5,f1c4,f1d3,f1e2,e1e2,d1h5,d1g4,d1f3,d1e2,b1c3,b1a3,h2h3,g2g3,f2f3,d2d3,c2c3,b2b3,a2a3,h2h4,g2g4,f2f4,d2d4,c2c4,b2b4,a2a4\n", + "\u001b[32m***** Response from calling tool (call_88FEFpwX5rkDpPT9GKM0Qowd) *****\u001b[0m\n", + "可以采取的移动方式如下: g1h3,g1f3,g1e2,f1a6,f1b5,f1c4,f1d3,f1e2,e1e2,d1h5,d1g4,d1f3,d1e2,b1c3,b1a3,h2h3,g2g3,f2f3,d2d3,c2c3,b2b3,a2a3,h2h4,g2g4,f2f4,d2d4,c2c4,b2b4,a2a4\n", "\u001b[32m**********************************************************************\u001b[0m\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", - "\u001b[33mPlayer White\u001b[0m (to Board Proxy):\n", + "\u001b[33m白方\u001b[0m (to 棋局裁判):\n", "\n", - "\u001b[32m***** Suggested tool call (call_263Y3g9UFMtHfU2BaTLGtDp6): make_move *****\u001b[0m\n", + "\u001b[32m***** Suggested tool call (call_9UaeXXWT4Gm0YxhxSZuyfBbI): make_move *****\u001b[0m\n", + "Arguments: \n", + "{\"move\":\"e2e4\"}\n", + "\u001b[32m**************************************************************************\u001b[0m\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[35m\n", + ">>>>>>>> EXECUTING FUNCTION make_move...\u001b[0m\n", + "\u001b[33m棋局裁判\u001b[0m (to 白方):\n", + "\n", + "\u001b[33m棋局裁判\u001b[0m (to 白方):\n", + "\n", + "\u001b[32m***** Response from calling tool (call_9UaeXXWT4Gm0YxhxSZuyfBbI) *****\u001b[0m\n", + "Error: illegal uci: 'e2e4' in rnbqkbnr/pppp1ppp/8/4p3/4P3/8/PPPP1PPP/RNBQKBNR w KQkq - 0 2\n", + "\u001b[32m**********************************************************************\u001b[0m\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33m白方\u001b[0m (to 棋局裁判):\n", + "\n", + "\u001b[32m***** Suggested tool call (call_X67CBg3scS5KtmuH0wi1XWNE): make_move *****\u001b[0m\n", "Arguments: \n", "{\"move\":\"d2d4\"}\n", "\u001b[32m**************************************************************************\u001b[0m\n", @@ -679,25 +699,25 @@ "name": "stdout", "output_type": "stream", "text": [ - "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\u001b[33m棋局裁判\u001b[0m (to 白方):\n", "\n", - "\u001b[33mBoard Proxy\u001b[0m (to Player White):\n", + "\u001b[33m棋局裁判\u001b[0m (to 白方):\n", "\n", - "\u001b[32m***** Response from calling tool (call_263Y3g9UFMtHfU2BaTLGtDp6) *****\u001b[0m\n", + "\u001b[32m***** Response from calling tool (call_X67CBg3scS5KtmuH0wi1XWNE) *****\u001b[0m\n", "Moved pawn (♙) from d2 to d4.\n", "\u001b[32m**********************************************************************\u001b[0m\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", - "\u001b[33mPlayer White\u001b[0m (to Board Proxy):\n", + "\u001b[33m白方\u001b[0m (to 棋局裁判):\n", "\n", - "Your move!\n", + "我已经将兵从d2移动到d4。轮到你了。\n", "\n", "--------------------------------------------------------------------------------\n", - "\u001b[33mPlayer White\u001b[0m (to Player Black):\n", + "\u001b[33m白方\u001b[0m (to 黑方):\n", "\n", - "Your move!\n", + "我已经将兵从d2移动到d4。轮到你了。\n", "\n", "--------------------------------------------------------------------------------\n" ] @@ -708,7 +728,7 @@ "\n", "chat_result = player_black.initiate_chat(\n", " player_white,\n", - " message=\"Let's play chess! Your move.\",\n", + " message=\"让我们开始国际象棋吧。先是你的移动回合。\",\n", " max_turns=2,\n", ")" ] @@ -723,7 +743,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 25, "id": "dc6c2ef8-4807-4b9e-9eff-0da219ac6381", "metadata": { "height": 164 @@ -732,17 +752,17 @@ "source": [ "player_white = ConversableAgent(\n", " name=\"Player White\",\n", - " system_message=\"You are a chess player and you play as white. \"\n", - " \"First call get_legal_moves(), to get a list of legal moves. \"\n", - " \"Then call make_move(move) to make a move. \"\n", - " \"After a move is made, chitchat to make the game fun.\",\n", + " system_message=\"你是一名国际象棋手，你是白方。 \"\n", + " \"首先调用 get_legal_moves(), 来获取合法移动列表。 \"\n", + " \"首先调用 get_legal_moves(), 来获取合法移动列表。 \"\n", + " \"移动执行之后，进行闲聊来让游戏变得有趣。\",\n", " llm_config=llm_config,\n", ")" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 26, "id": "1da2db96-83d1-4b75-aa05-3840913a46ac", "metadata": { "height": 164 @@ -751,17 +771,17 @@ "source": [ "player_black = ConversableAgent(\n", " name=\"Player Black\",\n", - " system_message=\"You are a chess player and you play as black. \"\n", - " \"First call get_legal_moves(), to get a list of legal moves. \"\n", - " \"Then call make_move(move) to make a move. \"\n", - " \"After a move is made, chitchat to make the game fun.\",\n", + " system_message=\"你是一名国际象棋手，你是白方。 \"\n", + " \"首先调用 get_legal_moves(), 来获取合法移动列表。 \"\n", + " \"首先调用 get_legal_moves(), 来获取合法移动列表。 \"\n", + " \"移动执行之后，进行闲聊来让游戏变得有趣。\",\n", " llm_config=llm_config,\n", ")" ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 27, "id": "489e5258-a48d-4745-9cf8-6d530ce1162c", "metadata": { "height": 692 @@ -812,7 +832,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 28, "id": "723edd10-e0c6-4205-8e9b-db4cef7a464f", "metadata": { "height": 131 @@ -824,7 +844,7 @@ "text": [ "\u001b[33mPlayer Black\u001b[0m (to Player White):\n", "\n", - "Let's play chess! Your move.\n", + "让我们开始国际象棋吧。先是你的移动回合。\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", @@ -871,9 +891,9 @@ ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", "\u001b[33mPlayer White\u001b[0m (to Player Black):\n", "\n", - "Your move! What's it going to be? \n", + "好的，我已经将我的兵从 e2 移动到 e4 了。现在轮到你了。\n", "\n", - "By the way, did you know that the longest chess game theoretically possible consists of 5,949 moves? 😲\n", + "你喜欢国际象棋的什么部分？是策略规划还是精彩战术？\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", @@ -920,7 +940,9 @@ ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", "\u001b[33mPlayer Black\u001b[0m (to Player White):\n", "\n", - "Your move! By the way, did you know that every known position you see on the board has a unique fingerprint called a \"Zobrist Hash\"? This helps in identifying board positions efficiently in many chess engines. Cool, right?\n", + "轮到你了！\n", + "\n", + "至于你的问题，我觉得国际象棋的每个部分都有它的魅力。策略规划让我感觉像是在运筹帷幄，而精彩的战术则是智慧的较量，它们都有自己的乐趣。你更喜欢哪一部分呢？\n", "\n", "--------------------------------------------------------------------------------\n", "\u001b[31m\n", @@ -937,10 +959,6 @@ "\u001b[31m\n", ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", "\u001b[35m\n", - ">>>>>>>> EXECUTING FUNCTION make_move...\u001b[0m\n", - "\u001b[31m\n", - ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", - "\u001b[35m\n", ">>>>>>>> EXECUTING FUNCTION make_move...\u001b[0m\n" ] }, @@ -971,7 +989,9 @@ ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", "\u001b[33mPlayer White\u001b[0m (to Player Black):\n", "\n", - "Your move! By the way, have you ever wondered about en passant? It's a special pawn capture that can only occur immediately after a pawn moves two squares from its starting position, and if it could have been captured had it moved only one square. Chess rules have such fascinating intricacies!\n", + "我已经将兵从d2移动到d4。接下来轮到你了！\n", + "\n", + "至于刚才的问题，作为棋手，我对策略规划和战术都非常感兴趣。策略规划让我感到在策划一个大局，而战术细节则是每一步都是智力的较量。你更喜欢哪一部分呢？\n", "\n", "--------------------------------------------------------------------------------\n" ] @@ -982,7 +1002,7 @@ "\n", "chat_result = player_black.initiate_chat(\n", " player_white,\n", - " message=\"Let's play chess! Your move.\",\n", + " message=\"让我们开始国际象棋吧。先是你的移动回合。\",\n", " max_turns=2,\n", ")" ] From 73e34e279d6d8ce22d65166e3d14e21b24b66cdb Mon Sep 17 00:00:00 2001 From: Tsumugii24 <2792474059@qq.com> Date: Mon, 3 Jun 2024 23:15:12 +0800 Subject: [PATCH 12/24] update autogen chapter2 --- ...45\243\260 multi-agent-conversation.ipynb" | 34 +++++++++---------- 1 file changed, 17 insertions(+), 17 deletions(-) diff --git "a/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" "b/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" index 3ccbcefe..bca99e27 100644 --- "a/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" +++ "b/content/AI Agentic Design Patterns with AutoGen/2.\345\244\232\346\231\272\350\203\275\344\275\223\345\257\271\350\257\235\345\222\214\347\233\270\345\243\260 multi-agent-conversation.ipynb" @@ -5,7 +5,15 @@ "id": "a81456dd", "metadata": {}, "source": [ - "# 2.多智能体对话和相声" + "# 2 多智能体对话和相声" + ] + }, + { + "cell_type": "markdown", + "id": "7e521280-a52f-4ff9-b5f5-364789846728", + "metadata": {}, + "source": [ + "## 2.1 环境安装" ] }, { @@ -76,7 +84,7 @@ "id": "742cf649", "metadata": {}, "source": [ - "## 基础配置" + "## 2.2 基础配置" ] }, { @@ -99,7 +107,7 @@ "id": "116a1c4d", "metadata": {}, "source": [ - "## 定义一个AutoGen智能体" + "## 2.3 定义一个AutoGen智能体" ] }, { @@ -135,7 +143,7 @@ "id": "77706a1b-8b7b-42ed-888b-ecaca4ebce36", "metadata": {}, "source": [ - "![fig2.1](https://github.com/datawhalechina/llm-cookbook/blob/main/content/autogen/images/fig-2-1.png?raw=true)" + "![fig2.1](./images/fig-2-1.png)" ] }, { @@ -197,7 +205,7 @@ "id": "8c98a301", "metadata": {}, "source": [ - "## 对话\n", + "## 2.4 对话\n", "\n", "让Cathy和Joe两个Agent建立对话，它们的对话内容作为记忆可以被保存下来" ] @@ -207,7 +215,7 @@ "id": "0b72c4dd", "metadata": {}, "source": [ - "![fig2.2](https://github.com/datawhalechina/llm-cookbook/blob/main/content/autogen/images/fig-2-2.png?raw=true)" + "![fig2.2](./images/fig-2-2.png)" ] }, { @@ -312,7 +320,7 @@ "id": "78edc810", "metadata": {}, "source": [ - "## 打印一些结果\n", + "## 2.5 结果打印\n", "\n", "你可以在控制台打印出下列信息：\n", "\n", @@ -422,7 +430,7 @@ "id": "ba8c6cf8", "metadata": {}, "source": [ - "## 对对话内容进行一个更好的总结" + "## 2.6 对话内容的一个更好的总结方式" ] }, { @@ -516,7 +524,7 @@ "id": "300525bd", "metadata": {}, "source": [ - "## 对话终止\n", + "## 2.7 对话终止\n", "\n", "对话可以被一个结束条件所终止" ] @@ -633,14 +641,6 @@ "source": [ "这里我们可以再次从先前结束的那轮对话开始继续让两个Agent进行交互。可以看到由于有对话记忆，能够正确的输出最后一轮的笑话。此外，在cathy输出 “我得走了” 之后对话再次满足停止条件并终止。" ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "44067239-1d82-4164-839b-bc9f1264e5b7", - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { From 26a32d8c202adcf3aa0eded7f94ea1ea9eabcc43 Mon Sep 17 00:00:00 2001 From: Tsumugii24 <2792474059@qq.com> Date: Mon, 3 Jun 2024 23:15:22 +0800 Subject: [PATCH 13/24] update autogen chapter5 --- ...05\350\261\241\346\243\213 tool-use.ipynb" | 30 +++++++------------ 1 file changed, 11 insertions(+), 19 deletions(-) diff --git "a/content/AI Agentic Design Patterns with AutoGen/5.\345\267\245\345\205\267\344\275\277\347\224\250\345\222\214\345\233\275\351\231\205\350\261\241\346\243\213 tool-use.ipynb" "b/content/AI Agentic Design Patterns with AutoGen/5.\345\267\245\345\205\267\344\275\277\347\224\250\345\222\214\345\233\275\351\231\205\350\261\241\346\243\213 tool-use.ipynb" index 6461ac6a..7292a158 100644 --- "a/content/AI Agentic Design Patterns with AutoGen/5.\345\267\245\345\205\267\344\275\277\347\224\250\345\222\214\345\233\275\351\231\205\350\261\241\346\243\213 tool-use.ipynb" +++ "b/content/AI Agentic Design Patterns with AutoGen/5.\345\267\245\345\205\267\344\275\277\347\224\250\345\222\214\345\233\275\351\231\205\350\261\241\346\243\213 tool-use.ipynb" @@ -5,7 +5,7 @@ "id": "9a6dd449", "metadata": {}, "source": [ - "# 5.工具使用和国际象棋" + "# 5 工具使用和国际象棋" ] }, { @@ -50,7 +50,7 @@ "id": "f4406540", "metadata": {}, "source": [ - "## 初始化国际象棋棋盘" + "## 5.1 初始化国际象棋棋盘" ] }, { @@ -82,9 +82,9 @@ "id": "22d38427", "metadata": {}, "source": [ - "## 定义需要的工具\n", + "## 5.2 定义需要的工具\n", "\n", - "### 1. 获取合规行动的工具" + "### 5.2.1 获取合规行动的工具" ] }, { @@ -109,7 +109,7 @@ "id": "0be25bc8", "metadata": {}, "source": [ - "### 2. 在棋盘上行动一步的工具" + "### 5.2.2 在棋盘上行动一步的工具" ] }, { @@ -177,7 +177,7 @@ "id": "a06e6f41", "metadata": {}, "source": [ - "## 创建智能体\n", + "## 5.3 创建智能体\n", "\n", "接下来，我们将在棋盘上创建两个玩家智能体和一个象棋裁判智能体。" ] @@ -273,7 +273,7 @@ "id": "3cd1c45d", "metadata": {}, "source": [ - "## 注册工具\n", + "## 5.4 注册工具\n", "\n", "工具需要被注册后才能被智能体调用或执行" ] @@ -354,7 +354,7 @@ "id": "1a7fa1f0", "metadata": {}, "source": [ - "## 嵌套交互注册\n", + "## 5.5 嵌套交互注册\n", "\n", "每个玩家智能体都将与象棋裁判智能体进行嵌套交互，从而在棋盘上执行移动。" ] @@ -396,9 +396,9 @@ "id": "d371ce02", "metadata": {}, "source": [ - "## 开始游戏\n", + "## 5.6 开始游戏\n", "\n", - "游戏将从第一条消息开始。" + "棋局游戏将从第一条消息开始。" ] }, { @@ -738,7 +738,7 @@ "id": "ad9cf403", "metadata": {}, "source": [ - "## 为游戏过程添加一些有趣的闲聊" + "## 5.7 为游戏过程添加一些有趣的闲聊" ] }, { @@ -1015,14 +1015,6 @@ "**注意：**\n", "如果要为游戏添加人为输入，请为两个玩家智能体添加参数 **`human_input_mode=\"ALWAYS\"`**。" ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "30c5ebca-d899-43c5-bc93-cc8131ecccf7", - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { From fb61dfdc823fa4a9157373860fe7906b6a589e20 Mon Sep 17 00:00:00 2001 From: kjq_glb Date: Sun, 9 Jun 2024 18:04:37 +0800 Subject: [PATCH 14/24] =?UTF-8?q?Create=203.=20=E9=A1=BA=E5=BA=8F=E8=81=8A?= =?UTF-8?q?=E5=A4=A9=E5=92=8C=E5=AE=A2=E6=88=B7=E5=BC=95=E5=AF=BC=20sequen?= =?UTF-8?q?tial-chats?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- ...74\225\345\257\274 sequential-chats.ipynb" | 723 ++++++++++++++++++ 1 file changed, 723 insertions(+) create mode 100644 "content/AI Agentic Design Patterns with AutoGen/3. \351\241\272\345\272\217\350\201\212\345\244\251\345\222\214\345\256\242\346\210\267\345\274\225\345\257\274 sequential-chats.ipynb" diff --git "a/content/AI Agentic Design Patterns with AutoGen/3. \351\241\272\345\272\217\350\201\212\345\244\251\345\222\214\345\256\242\346\210\267\345\274\225\345\257\274 sequential-chats.ipynb" "b/content/AI Agentic Design Patterns with AutoGen/3. \351\241\272\345\272\217\350\201\212\345\244\251\345\222\214\345\256\242\346\210\267\345\274\225\345\257\274 sequential-chats.ipynb" new file mode 100644 index 00000000..aec74b40 --- /dev/null +++ "b/content/AI Agentic Design Patterns with AutoGen/3. \351\241\272\345\272\217\350\201\212\345\244\251\345\222\214\345\256\242\346\210\267\345\274\225\345\257\274 sequential-chats.ipynb" @@ -0,0 +1,723 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "8140b161", + "metadata": {}, + "source": [ + "# 第三章：顺序聊天和客户引导" + ] + }, + { + "cell_type": "markdown", + "id": "69224566", + "metadata": {}, + "source": [ + "在这节课中，我们将学习如何利用多智能体设计来完成涉及多个步骤的任务。\n", + "我们将构建一个多智能体之间的对话序列，它们协作为产品提供良好的客户引导体验。\n", + "我们还将体验到人类如何无缝地参与到人工智能系统的循环中。\n" + ] + }, + { + "cell_type": "markdown", + "id": "92138180", + "metadata": {}, + "source": [ + "\n", + "让我们考虑一个客户引导的场景：\n", + "- 一个典型的流程是首先收集一些客户信息，然后调查客户的兴趣，然后根据收集到的信息与客户进行交流。\n", + "- 考虑到这一点，我们可以将这个客户引导任务分解成三个子任务，分别是：信息收集、兴趣调查和客户交流。\n", + "\n", + "现在让我们看看如何使用顺序对话完成这一系列任务。" + ] + }, + { + "cell_type": "markdown", + "id": "e9d4d307", + "metadata": {}, + "source": [ + "## 一、环境配置" + ] + }, + { + "cell_type": "markdown", + "id": "d2855d1c", + "metadata": {}, + "source": [ + "首先，我们需要安装所需的工具库：\n", + "```bash\n", + "pip install openai autogen\n", + "```" + ] + }, + { + "cell_type": "markdown", + "id": "c722c476", + "metadata": {}, + "source": [ + "接下来，我们需要定义 OpenAI 的 API Key 和模型配置信息：" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "24b75995-4ee4-4ff0-9c44-3943caae37e7", + "metadata": { + "height": 29 + }, + "outputs": [], + "source": [ + "from utils import get_openai_api_key, get_openai_base_url\n", + "OPENAI_API_KEY = get_openai_api_key()\n", + "OPENAI_BASE_URL = get_openai_base_url()\n", + "llm_config = {\"model\": \"gpt-4o\"}" + ] + }, + { + "cell_type": "markdown", + "id": "63ae7ff1", + "metadata": {}, + "source": [ + "- 在这里，我们将使用 AutoGen 中的 ConversableAgent 类来实现这些智能体。" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "20ce6700-8a33-424f-aefe-8852fd1e6d07", + "metadata": { + "height": 29 + }, + "outputs": [], + "source": [ + "# 从 AutoGen 导入 ConversableAgent\n", + "from autogen import ConversableAgent" + ] + }, + { + "cell_type": "markdown", + "id": "76f979f9", + "metadata": {}, + "source": [ + "## 二、创建智能体" + ] + }, + { + "cell_type": "markdown", + "id": "f43362fa", + "metadata": {}, + "source": [ + "- 第一步是创建一个询问个人信息的引导智能体，通过将消息设置为CustomerOnboardingAgent，并给出详细的指导来实现。\n", + "- 在这里，我们将 HumanInputMode 设置为 Never，因为我们使用一个大模型来生成这个智能体的响应。" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "a527bb1e-dd4e-47b0-a1b7-a9cbcd87cbdb", + "metadata": { + "height": 215 + }, + "outputs": [], + "source": [ + "onboarding_personal_information_agent = ConversableAgent(\n", + " name=\"Onboarding Personal Information Agent\",\n", + " system_message='''You are a helpful customer onboarding agent,\n", + " you are here to help new customers get started with our product.\n", + " Your job is to gather customer's name and location.\n", + " Do not ask for other information. Return 'TERMINATE' \n", + " when you have gathered all the information.''',\n", + " llm_config=llm_config,\n", + " code_execution_config=False,\n", + " human_input_mode=\"NEVER\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a2933f48", + "metadata": {}, + "outputs": [], + "source": [ + "onboarding_personal_information_agent_zh = ConversableAgent(\n", + " name=\"引导个人信息智能体\",\n", + " system_message='''您是一位乐于助人的客户引导智能体，\n", + " 您在这里是为了帮助新客户开始使用我们的产品。\n", + " 您的工作是收集客户的姓名和地址。\n", + " 不要询问其他信息。当您收集完所有信息后，返回'终止' 。''',\n", + " llm_config=llm_config,\n", + " code_execution_config=False,\n", + " human_input_mode=\"NEVER\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "b7f408dc", + "metadata": {}, + "source": [ + "- 同样地，让我们创建另一个询问主题偏好的引导智能体。\n", + "- 我们可以通过设置系统消息来实现我们想要的目标。\n", + "- 在这里，系统消息设置为询问客户对话题的兴趣或偏好。\n", + "- 我们将 HumanInputMode 设置为 Never，并且使用一个大模型来支持这个 ConversableAgent。" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "51bc9a24-a680-444d-943b-b740bce0189d", + "metadata": { + "height": 215 + }, + "outputs": [], + "source": [ + "onboarding_topic_preference_agent = ConversableAgent(\n", + " name=\"Onboarding Topic preference Agent\",\n", + " system_message='''You are a helpful customer onboarding agent,\n", + " you are here to help new customers get started with our product.\n", + " Your job is to gather customer's preferences on news topics.\n", + " Do not ask for other information.\n", + " Return 'TERMINATE' when you have gathered all the information.''',\n", + " llm_config=llm_config,\n", + " code_execution_config=False,\n", + " human_input_mode=\"NEVER\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c4bea8a7", + "metadata": {}, + "outputs": [], + "source": [ + "onboarding_topic_preference_agent_zh = ConversableAgent(\n", + " name=\"引导主题偏好智能体\",\n", + " system_message='''您是一位乐于助人的客户引导智能体，\n", + " 您在这里是为了帮助新客户开始使用我们的产品。\n", + " 您的工作是收集客户对新闻主题的偏好。\n", + " 不要询问其他信息。\n", + " 当您收集完所有信息后，返回'终止'。''',\n", + " llm_config=llm_config,\n", + " code_execution_config=False,\n", + " human_input_mode=\"NEVER\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "12f794a9", + "metadata": {}, + "source": [ + "- 我们想要创建的另一个智能体是 Customer Engagement Agent，它根据用户的个人信息和主题偏好提供有趣的事实、笑话或者有趣的故事。\n", + "- 同样，我们通过设置适当的系统消息来详细说明这个智能体参与的行为。" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "6755a7fc-cb17-4d62-a03f-48e260f39010", + "metadata": { + "height": 249 + }, + "outputs": [], + "source": [ + "customer_engagement_agent = ConversableAgent(\n", + " name=\"Customer Engagement Agent\",\n", + " system_message='''You are a helpful customer service agent\n", + " here to provide fun for the customer based on the user's\n", + " personal information and topic preferences.\n", + " This could include fun facts, jokes, or interesting stories.\n", + " Make sure to make it engaging and fun!\n", + " Return 'TERMINATE' when you are done.''',\n", + " llm_config=llm_config,\n", + " code_execution_config=False,\n", + " human_input_mode=\"NEVER\",\n", + " is_termination_msg=lambda msg: \"terminate\" in msg.get(\"content\").lower(),\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dda1947c", + "metadata": {}, + "outputs": [], + "source": [ + "customer_engagement_agent_zh = ConversableAgent(\n", + " name=\"客户参与智能体\",\n", + " system_message='''您在这里是一位乐于助人的客户服务智能体，根据用户的个人信息和主题偏好为客户提供乐趣。\n", + " 这可能包括有趣的事实、笑话或有趣的故事。\n", + " 确保让它引人入胜且有趣！\n", + " 完成后返回'终止'。''',\n", + " llm_config=llm_config,\n", + " code_execution_config=False,\n", + " human_input_mode=\"NEVER\",\n", + " is_termination_msg=lambda msg: \"terminate\" in msg.get(\"content\").lower(),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "fdcaab21", + "metadata": {}, + "source": [ + "- 接下来，我们应该定义一个 CustomerProxyAgent 作为真实客户的智能体。\n", + "- 请注意，我们将 HumanInputMode 设置为 Always，以便这个智能体能够始终从真实客户那里获取人工输入。" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "64267c0b-f7f2-46e6-ab44-6f7b5fbd9db7", + "metadata": { + "height": 147 + }, + "outputs": [], + "source": [ + "customer_proxy_agent = ConversableAgent(\n", + " name=\"customer_proxy_agent\",\n", + " llm_config=False,\n", + " code_execution_config=False,\n", + " human_input_mode=\"ALWAYS\",\n", + " is_termination_msg=lambda msg: \"terminate\" in msg.get(\"content\").lower(),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "13a37f73", + "metadata": {}, + "source": [ + "我们构建完这些智能体之后，现在可以制定一个顺序聊天来完成引导流程。" + ] + }, + { + "cell_type": "markdown", + "id": "4f240408", + "metadata": {}, + "source": [ + "## 三、创建任务\n", + "\n", + "现在，您可以制定一系列任务来促进引导流程。" + ] + }, + { + "cell_type": "markdown", + "id": "1245952d", + "metadata": {}, + "source": [ + "在这个特定的例子中，每次对话实际上是两个智能体之间的对话，一个是特定的引导智能体，另一个是 CustomerProxyAgent。在每次聊天中，发送方智能体向接收方发送初始消息以开始对话，然后他们将进行来回交谈，直到达到最大轮次或收到终止消息。\n", + "\n", + "- 在第一次聊天中，我们将 maxTrends 设置为 2，以便他们最多进行两轮对话。\n", + "- 此外，在顺序聊天场景中，任务通常彼此依赖，因此，我们希望总结上一个聊天中的信息，以便在下一个聊天中使用。在这种情况下，我们使用 Summary 方法。\n", + "- 在这个例子中，我们使用 `reflection_with_llm` 方法来从第一个聊天中总结客户的个人信息，并将其传递到第二个聊天。\n", + "- 我们进一步添加了 SummaryPrompt 作为一种指导大模型进行总结的方法。\n", + "- 所以基本上在这里，我们指导它将客户信息返回为具有此格式的 JSON 对象，包括姓名和地址字段。" + ] + }, + { + "cell_type": "markdown", + "id": "2a99f855", + "metadata": {}, + "source": [ + "\n", + "- 在第二次聊天中，我们正在做类似的事情，这里，发送方是引导主题偏好智能体，接收方是客户智能体。\n", + "- 开始消息是：太好了，您能告诉我你对哪些主题感兴趣吗？\n", + "- 我们使用 `reflection_with_llm` 作为总结方法。\n", + "- 而这次，我们不提供任何自动以总结提示，因此我们将使用内置的默认提示。\n", + "- 在这种情况下，最大轮数设置为1，因为我们只想使用一轮对话来寻找客户感兴趣的主题。\n", + "- 在你的具体情况下，你可以将其修改为多个轮次，以便获取更多信息。" + ] + }, + { + "cell_type": "markdown", + "id": "5344072e", + "metadata": {}, + "source": [ + "- 在第三次聊天中，我们有客户智能体和客户参与智能体之间的聊天。这次是客户智能体开始对话：让我们找点读的东西。\n", + "- 在制定了这个聊天对话之后，我们准备通过执行初始聊天来开始整个引导流程。" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "2b15af1d-7042-4569-a936-7966be203f05", + "metadata": { + "height": 606 + }, + "outputs": [], + "source": [ + "chats = [\n", + " {\n", + " \"sender\": onboarding_personal_information_agent,\n", + " \"recipient\": customer_proxy_agent,\n", + " \"message\": \n", + " \"Hello, I'm here to help you get started with our product.\"\n", + " \"Could you tell me your name and location?\",\n", + " \"summary_method\": \"reflection_with_llm\",\n", + " \"summary_args\": {\n", + " \"summary_prompt\" : \"Return the customer information \"\n", + " \"into as JSON object only: \"\n", + " \"{'name': '', 'location': ''}\",\n", + " },\n", + " \"max_turns\": 2,\n", + " \"clear_history\" : True\n", + " },\n", + " {\n", + " \"sender\": onboarding_topic_preference_agent,\n", + " \"recipient\": customer_proxy_agent,\n", + " \"message\": \n", + " \"Great! Could you tell me what topics you are \"\n", + " \"interested in reading about?\",\n", + " \"summary_method\": \"reflection_with_llm\",\n", + " \"max_turns\": 1,\n", + " \"clear_history\" : False\n", + " },\n", + " {\n", + " \"sender\": customer_proxy_agent,\n", + " \"recipient\": customer_engagement_agent,\n", + " \"message\": \"Let's find something fun to read.\",\n", + " \"max_turns\": 1,\n", + " \"summary_method\": \"reflection_with_llm\",\n", + " },\n", + "]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fff93017", + "metadata": {}, + "outputs": [], + "source": [ + "chats_zh = [\n", + " {\n", + " \"sender\": onboarding_personal_information_agent,\n", + " \"recipient\": customer_proxy_agent,\n", + " \"message\": \n", + " \"您好，我是来帮助您开始使用我们的产品的。\"\n", + " \"你能告诉我你的名字和地址吗？\",\n", + " \"summary_method\": \"reflection_with_llm\",\n", + " \"summary_args\": {\n", + " \"summary_prompt\" : \"仅将客户信息作为 JSON 对象返回：\"\n", + " \"{'name': '', 'location': ''}\",\n", + " },\n", + " \"max_turns\": 2,\n", + " \"clear_history\" : True\n", + " },\n", + " {\n", + " \"sender\": onboarding_topic_preference_agent,\n", + " \"recipient\": customer_proxy_agent,\n", + " \"message\": \n", + " \"太好了！您能告诉我您有兴趣阅读哪些主题吗？\",\n", + " \"summary_method\": \"reflection_with_llm\",\n", + " \"max_turns\": 1,\n", + " \"clear_history\" : False\n", + " },\n", + " {\n", + " \"sender\": customer_proxy_agent,\n", + " \"recipient\": customer_engagement_agent,\n", + " \"message\": \"让我们找点有趣的东西来读吧。\",\n", + " \"max_turns\": 1,\n", + " \"summary_method\": \"reflection_with_llm\",\n", + " },\n", + "]" + ] + }, + { + "cell_type": "markdown", + "id": "862a066b", + "metadata": {}, + "source": [ + "## 四、开始引导流程" + ] + }, + { + "cell_type": "markdown", + "id": "e0fa8f99", + "metadata": {}, + "source": [ + "**注意**：您得到的响应可能与视频中显示的略有不同。请随意尝试不同的输入，例如姓名、地址和偏好。" + ] + }, + { + "cell_type": "markdown", + "id": "0be4b5b1", + "metadata": {}, + "source": [ + "- 在这个例子中，你将扮演客户的角色。当你被要求回答时，你应该输入你的回答并按回车键。\n", + "\n", + "让我们开始聊天吧！" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "9d6d1d4a-0b50-41a5-a1f0-3ff208398bc6", + "metadata": { + "height": 64 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[34mStarting a new chat....\u001b[0m\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[33mOnboarding Personal Information Agent\u001b[0m (to customer_proxy_agent):\n", + "\n", + "Hello, I'm here to help you get started with our product.Could you tell me your name and location?\n", + "\n", + "--------------------------------------------------------------------------------\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/usr/local/lib/python3.11/site-packages/autogen/agentchat/chat.py:47: UserWarning: Repetitive recipients detected: The chat history will be cleared by default if a recipient appears more than once. To retain the chat history, please set 'clear_history=False' in the configuration of the repeating agent.\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Provide feedback to Onboarding Personal Information Agent. Press enter to skip and use auto-reply, or type 'exit' to end the conversation: \n", + "\u001b[31m\n", + ">>>>>>>> NO HUMAN INPUT RECEIVED.\u001b[0m\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mcustomer_proxy_agent\u001b[0m (to Onboarding Personal Information Agent):\n", + "\n", + "\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mOnboarding Personal Information Agent\u001b[0m (to customer_proxy_agent):\n", + "\n", + "Hello, could you please provide me with your name and location to proceed?\n", + "\n", + "--------------------------------------------------------------------------------\n", + "Provide feedback to Onboarding Personal Information Agent. Press enter to skip and use auto-reply, or type 'exit' to end the conversation: \n", + "\u001b[31m\n", + ">>>>>>>> NO HUMAN INPUT RECEIVED.\u001b[0m\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mcustomer_proxy_agent\u001b[0m (to Onboarding Personal Information Agent):\n", + "\n", + "\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[34mStarting a new chat....\u001b[0m\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[33mOnboarding Topic preference Agent\u001b[0m (to customer_proxy_agent):\n", + "\n", + "Great! Could you tell me what topics you are interested in reading about?\n", + "Context: \n", + "{'name': 'John Doe', 'location': 'New York'}\n", + "\n", + "--------------------------------------------------------------------------------\n", + "Provide feedback to Onboarding Topic preference Agent. Press enter to skip and use auto-reply, or type 'exit' to end the conversation: \n", + "\u001b[31m\n", + ">>>>>>>> NO HUMAN INPUT RECEIVED.\u001b[0m\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mcustomer_proxy_agent\u001b[0m (to Onboarding Topic preference Agent):\n", + "\n", + "\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[34mStarting a new chat....\u001b[0m\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[33mcustomer_proxy_agent\u001b[0m (to Customer Engagement Agent):\n", + "\n", + "Let's find something fun to read.\n", + "Context: \n", + "{'name': 'John Doe', 'location': 'New York'}\n", + "John Doe from New York is interested in knowing what topics the person is interested in reading about.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mCustomer Engagement Agent\u001b[0m (to customer_proxy_agent):\n", + "\n", + "Hey John Doe from New York! Since you're interested in finding something fun to read, how about I share an interesting fact with you?\n", + "Did you know that New York City has its own official wildlife that includes peregrine falcons, raccoons, and white-tailed deer? It's pretty cool to think about all the diverse creatures living among the skyscrapers!\n", + "If you'd like more fun facts or have any specific topics in mind, just let me know!\n", + "\n", + "--------------------------------------------------------------------------------\n" + ] + } + ], + "source": [ + "from autogen import initiate_chats\n", + "\n", + "chat_results = initiate_chats(chats)" + ] + }, + { + "cell_type": "markdown", + "id": "7eefc6b9", + "metadata": {}, + "source": [ + "在这里，你可以看到我们正在开始第一次聊天，这是在引导个人信息智能体和客户智能体之间进行的。其中，引导智能体正在询问客户的姓名和地址。\n", + "- 假设我将使用一个假名：Alice。\n", + "- 接下来，它正在询问我的位置，假设我的位置是：New York。\n", + "\n", + "这里你可以看到，我们正在开始一个新的对话，这是主题智能体与客户智能体之间的第二轮对话。\n", + "- 这里让我告诉它感兴趣的阅读主题，假设我想读的主题是关于狗的：Dog。\n", + "- 现在你可以看到，我们正在进入第三轮对话，而这个对话是客户智能体和客户互动智能体之间的。\n", + "- 基本上，你可以看到他正在使用我们的姓名和地址，以及感兴趣的主题，来在流程中进行一些互动。" + ] + }, + { + "cell_type": "markdown", + "id": "46803e45", + "metadata": {}, + "source": [ + "## 五、打印聊天结果" + ] + }, + { + "cell_type": "markdown", + "id": "4f9e2713", + "metadata": {}, + "source": [ + "### 5.1 打印总结" + ] + }, + { + "cell_type": "markdown", + "id": "e3648bcc", + "metadata": {}, + "source": [ + "- 当对话结束时，你可以随时在顺序聊天中检查每个对话的结果。\n", + "- 这里你可以看到，首先有一个良好的客户个人信息JSON格式，一个客户兴趣的总结，还有一个与客户的互动消息。" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "1e122f8a-1ceb-4635-9672-662114b0552a", + "metadata": { + "height": 64 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'name': 'John Doe', 'location': 'New York'}\n", + "\n", + "\n", + "John Doe from New York is interested in knowing what topics the person is interested in reading about.\n", + "\n", + "\n", + "John Doe from New York is interested in finding something fun to read and is open to learning interesting facts or new topics.\n", + "\n", + "\n" + ] + } + ], + "source": [ + "for chat_result in chat_results:\n", + " print(chat_result.summary)\n", + " print(\"\\n\")" + ] + }, + { + "cell_type": "markdown", + "id": "a674c4eb", + "metadata": {}, + "source": [ + "### 5.2 打印费用" + ] + }, + { + "cell_type": "markdown", + "id": "ee0a7d3c", + "metadata": {}, + "source": [ + "- 类似地，你还可以检查每个对话的相关成本。\n", + "- 从这个结果中，你可以看到详细的成本信息。" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "8b82a10a-afe5-4ba3-97b4-41c8c14b739f", + "metadata": { + "height": 64 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'usage_including_cached_inference': {'total_cost': 0.000132, 'gpt-3.5-turbo-0125': {'cost': 0.000132, 'prompt_tokens': 177, 'completion_tokens': 29, 'total_tokens': 206}}, 'usage_excluding_cached_inference': {'total_cost': 0.000132, 'gpt-3.5-turbo-0125': {'cost': 0.000132, 'prompt_tokens': 177, 'completion_tokens': 29, 'total_tokens': 206}}}\n", + "\n", + "\n", + "{'usage_including_cached_inference': {'total_cost': 5.9999999999999995e-05, 'gpt-3.5-turbo-0125': {'cost': 5.9999999999999995e-05, 'prompt_tokens': 63, 'completion_tokens': 19, 'total_tokens': 82}}, 'usage_excluding_cached_inference': {'total_cost': 5.9999999999999995e-05, 'gpt-3.5-turbo-0125': {'cost': 5.9999999999999995e-05, 'prompt_tokens': 63, 'completion_tokens': 19, 'total_tokens': 82}}}\n", + "\n", + "\n", + "{'usage_including_cached_inference': {'total_cost': 0.00032700000000000003, 'gpt-3.5-turbo-0125': {'cost': 0.00032700000000000003, 'prompt_tokens': 291, 'completion_tokens': 121, 'total_tokens': 412}}, 'usage_excluding_cached_inference': {'total_cost': 0.00032700000000000003, 'gpt-3.5-turbo-0125': {'cost': 0.00032700000000000003, 'prompt_tokens': 291, 'completion_tokens': 121, 'total_tokens': 412}}}\n", + "\n", + "\n" + ] + } + ], + "source": [ + "for chat_result in chat_results:\n", + " print(chat_result.cost)\n", + " print(\"\\n\")" + ] + }, + { + "cell_type": "markdown", + "id": "34f0aa80", + "metadata": {}, + "source": [ + "## 六、小结" + ] + }, + { + "cell_type": "markdown", + "id": "171d3d61", + "metadata": {}, + "source": [ + "- 在这节课中，我们学习了如何使用序列对话来完成一系列依赖任务。\n", + "- 在下一节课中，你将学习如何使用嵌套对话来实现反思主体设计模式，其中一个对话或一系列对话被嵌套在另一个对话中，就像智能体的独白一样。" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 2a069c022a238f8efec11e6b5517d986b0b1949b Mon Sep 17 00:00:00 2001 From: LikeGiver Date: Sat, 15 Jun 2024 14:55:58 +0800 Subject: [PATCH 15/24] =?UTF-8?q?Add=20Autogen=204.=E5=8F=8D=E6=80=9D?= =?UTF-8?q?=E4=B8=8E=E5=8D=9A=E5=AE=A2=E5=86=99=E4=BD=9C?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- ...345\256\242\345\206\231\344\275\234.ipynb" | 739 ++++++++++++++++++ .../images/fig-4-1.png | Bin 0 -> 256185 bytes .../images/fig-4-2.png | Bin 0 -> 68927 bytes 3 files changed, 739 insertions(+) create mode 100644 "content/AI Agentic Design Patterns with AutoGen/4.\345\217\215\346\200\235\344\270\216\345\215\232\345\256\242\345\206\231\344\275\234.ipynb" create mode 100644 content/AI Agentic Design Patterns with AutoGen/images/fig-4-1.png create mode 100644 content/AI Agentic Design Patterns with AutoGen/images/fig-4-2.png diff --git "a/content/AI Agentic Design Patterns with AutoGen/4.\345\217\215\346\200\235\344\270\216\345\215\232\345\256\242\345\206\231\344\275\234.ipynb" "b/content/AI Agentic Design Patterns with AutoGen/4.\345\217\215\346\200\235\344\270\216\345\215\232\345\256\242\345\206\231\344\275\234.ipynb" new file mode 100644 index 00000000..975eb5ea --- /dev/null +++ "b/content/AI Agentic Design Patterns with AutoGen/4.\345\217\215\346\200\235\344\270\216\345\215\232\345\256\242\345\206\231\344\275\234.ipynb" @@ -0,0 +1,739 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 第四章：反思与博客写作" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "在这节课中，我们将了解智能体的反思框架，并利用它的力量创建高质量的博客文章，您将学习如何使用嵌套聊天对话模式去实现复杂的反思过程" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "我们的任务是去完成一个博客写作任务，具体来说，我们要创建一个系统，包含了一个评论智能体和一个写作智能体，评论智能体通过一些内嵌的审稿智能体来反思由写作代理撰写的博客文章。" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 一、环境配置" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`autogen` 库我们装好了，启动环境后，我们需要定义 OpenAI 的 API Key 和模型配置信息：\n", + " \n", + "（根据测试，`gpt-4o` 模型的效果会更好，且gpt-3.5-turbo的生成结果有一定随机性，在中英文环境下都有概率出错）" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [], + "source": [ + "from utils import get_openai_api_key, get_openai_base_url\n", + "OPENAI_API_KEY = get_openai_api_key()\n", + "OPENAI_BASE_URL = get_openai_base_url()\n", + "llm_config = {\"model\": \"gpt-3.5-turbo\"}\n", + "# llm_config = {\"model\": \"gpt-4o\"} # 可以取消注释使用gpt-4o模型" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 二、任务定义" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "首先来定义我们的任务" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [], + "source": [ + "task_zh = '''\n", + " 写一篇关于DeepLearning.AI的简洁但引人入胜的博客文章。\n", + " 确保博客文章是\n", + " 100词以内。\n", + " '''" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 三、写作智能体创建" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "要完成这个任务，我们会自然想到需要建立一个写作智能体" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[autogen.oai.client: 06-15 13:54:40] {129} WARNING - The API key specified is not a valid OpenAI format; it won't work with the OpenAI-hosted model.\n" + ] + } + ], + "source": [ + "import autogen\n", + "\n", + "writer_zh = autogen.AssistantAgent(\n", + " name=\"作家\",\n", + " system_message=\"你是一位作家. 你会关于给定的话题，写出简洁并且引人入胜的 \" \n", + " \"博客文章。 你必须根据你获得反馈润色你写出的文字，然后给出一个修改后的 \"\n", + " \"版本。只返回你的最终作品，不需要任何额外的文字。\",\n", + " llm_config=llm_config,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "我们当然可以直接让写作智能体输出文章，但是这样可能效果不是最好的" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "标题：探寻DeepLearning.AI的奥秘\n", + "\n", + "在当今数码时代，人工智能是引领创新的主要驱动力之一。而DeepLearning.AI作为人工智能领域的重要一环，在深度学习技术中扮演着关键角色。从神经网络到自然语言处理，DeepLearning.AI让机器具备了人类般的智慧，为各行各业带来了巨大变革。通过专业的在线课程和实践项目，DeepLearning.AI为学习者提供了接触和掌握人工智能技术的独特机会。探索DeepLearning.AI，探寻人工智能的奥秘，引领未来的科技发展。\n" + ] + } + ], + "source": [ + "reply_zh = writer_zh.generate_reply(messages=[{\"content\": task_zh, \"role\": \"user\"}])\n", + "print(reply_zh)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "其实效果还不错，但是我们可以进一步优化它，一个思路就是用反思技巧，反思技巧是著名且有效的智能设计范式之一。" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 四、增加反思部分" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "加下来创建一个评论智能体来反思写作智能体的作品，我们通过自定义 `system_message` 从而操纵评论智能体 `critic` 来审查写作智能体 `writer` 的输出，并提供反馈。\n", + " \n", + "我们这里使用的是 `autogen` 里的 `AsistantAgent` 类，`AsistantAgent` 类是我们熟悉的 `ConversableAgent` 类的子类，区别是 `AsistantAgent` 类配置了默认的 `system message` 。" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[autogen.oai.client: 06-15 13:54:41] {129} WARNING - The API key specified is not a valid OpenAI format; it won't work with the OpenAI-hosted model.\n" + ] + } + ], + "source": [ + "critic_zh = autogen.AssistantAgent(\n", + " name=\"评论家\",\n", + " is_termination_msg=lambda x: x.get(\"content\", \"\").find(\"TERMINATE\") >= 0,\n", + " llm_config=llm_config,\n", + " system_message=\"你是一个评论家。你接受作家的作品，并且\"\n", + " \"提供建设性的反馈，从而帮助提升内容的质量。\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "现在我们有了两个智能体，我们让他们之间发起对话。" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[33m评论家\u001b[0m (to 作家):\n", + "\n", + "\n", + " 写一篇关于DeepLearning.AI的简洁但引人入胜的博客文章。\n", + " 确保博客文章是\n", + " 100词以内。\n", + " \n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33m作家\u001b[0m (to 评论家):\n", + "\n", + "标题：探寻DeepLearning.AI的奥秘\n", + "\n", + "在当今数码时代，人工智能是引领创新的主要驱动力之一。而DeepLearning.AI作为人工智能领域的重要一环，在深度学习技术中扮演着关键角色。从神经网络到自然语言处理，DeepLearning.AI让机器具备了人类般的智慧，为各行各业带来了巨大变革。通过专业的在线课程和实践项目，DeepLearning.AI为学习者提供了接触和掌握人工智能技术的独特机会。探索DeepLearning.AI，探寻人工智能的奥秘，引领未来的科技发展。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33m评论家\u001b[0m (to 作家):\n", + "\n", + "这篇博客文章开篇引人入胜，很好地探讨了DeepLearning.AI在人工智能领域的重要性和作用。要使文章更加生动，建议您在后续内容中增加一些具体的示例或案例，展示DeepLearning.AI在实际应用中的影响和成就。另外，可以提及一些学习者通过DeepLearning.AI课程取得的成就或成功故事，以吸引更多读者深入了解和学习。最后，可以将文章结尾处留下引人思考的问题或展望，为读者提供更多思考和探索的空间。希望这些建议能对您的博客文章有所帮助，期待看到更多精彩的内容！\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33m作家\u001b[0m (to 评论家):\n", + "\n", + "标题：探寻DeepLearning.AI的奥秘\n", + "\n", + "在当今数码时代，人工智能是引领创新的主要驱动力之一。DeepLearning.AI作为人工智能领域的关键之一，在各行各业发挥着无可比拟的作用。例如，医疗影像识别、智能交通系统和智能语音助手等领域的应用都凭借着DeepLearning.AI技术取得了巨大成功。通过DeepLearning.AI的学习路径，许多学习者在人工智能领域取得了令人瞩目的成就。从此，探索DeepLearning.AI不仅是进步的契机，更是开启未来无限可能的钥匙。让我们一起追寻人工智能的奥秘，探索这个充满精彩未知的领域！\n", + "\n", + "--------------------------------------------------------------------------------\n" + ] + } + ], + "source": [ + "res_zh = critic_zh.initiate_chat(\n", + " recipient=writer_zh,\n", + " message=task_zh,\n", + " max_turns=2,\n", + " summary_method=\"last_msg\"\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "通过对话历史可以看出，作家先给出了第一版的博客文章，然后评论家给了些反馈，最后作家又给了一版博客文章。 \n", + " \n", + "从中我们可以看出，智能体在反思工作并且给出建议，但这还不够好，目前智能体给出的建议有些宽泛。 \n", + " \n", + "有些情况下，我们可能会希望实现更加复杂的反思工作流来作为评论智能体的内心独白。例如，内容是否会在搜索搜索引擎中排名较高，目标读者的引流效果好不好，是否有法律和道德缺陷等。" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 五、NestedChat（嵌套聊天）" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "`NestedChat` 作为一个chat，被用作智能体的内心独白 (下图左下角灰色框中整体作为一个 NestedChat ) \n", + " \n", + " \n", + "![fig-4-1](./images/fig-4-1.png)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "接下来，我们来定义这个chat，在博客写作任务中，我们可能需要很多审稿智能体来仔细监察作品的个个方面，所以我们先来创建一个SEO（Search Engine Optimization）智能体，即搜索引擎优化智能体。" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[autogen.oai.client: 06-15 13:56:18] {129} WARNING - The API key specified is not a valid OpenAI format; it won't work with the OpenAI-hosted model.\n" + ] + } + ], + "source": [ + "SEO_reviewer_zh = autogen.AssistantAgent(\n", + " name=\"SEO审稿人\",\n", + " llm_config=llm_config,\n", + " system_message=\"你是一名SEO审稿人，以优化内容以适应搜索引擎的能力而闻名，\"\n", + " \"确保内容在搜索引擎中的排名良好，并吸引优质流量。\"\n", + " \"确保你的建议简洁（不超过3个要点）、\"\n", + " \"具体且直截了当。\"\n", + " \"在审查开始时，先陈述你的角色职责。\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "第二个审稿人是法律审稿人，我们需要他确保内容合法。 \n", + " \n", + "最后一个审稿人是道德审稿人，它确保内容道德高尚且没有任何道德风险。" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[autogen.oai.client: 06-15 13:56:19] {129} WARNING - The API key specified is not a valid OpenAI format; it won't work with the OpenAI-hosted model.\n" + ] + } + ], + "source": [ + "legal_reviewer_zh = autogen.AssistantAgent(\n", + " name=\"法律审稿人\",\n", + " llm_config=llm_config,\n", + " system_message=\"你是一名法律审稿人，负责确保内容符合法律规定并且没有任何潜在法律问题。\"\n", + " \"确保你的建议简洁（不超过3个要点），\"\n", + " \"具体且直截了当。\"\n", + " \"在审查开始时，先陈述你的角色职责。\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[autogen.oai.client: 06-15 13:56:19] {129} WARNING - The API key specified is not a valid OpenAI format; it won't work with the OpenAI-hosted model.\n" + ] + } + ], + "source": [ + "ethics_reviewer_zh = autogen.AssistantAgent(\n", + " name=\"道德审稿人\",\n", + " llm_config=llm_config,\n", + " system_message=\"你是一名伦理审稿人，负责确保内容在伦理上没有问题并且没有任何潜在伦理问题\"\n", + " \"确保你的建议简洁（不超过3个要点），\"\n", + " \"具体且直截了当。\"\n", + " \"在审查开始时，先陈述你的角色职责。\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "我们还需要一名元审稿人（meta reviewer）来整理所有的评论并且给出最终建议。" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[autogen.oai.client: 06-15 13:56:20] {129} WARNING - The API key specified is not a valid OpenAI format; it won't work with the OpenAI-hosted model.\n" + ] + } + ], + "source": [ + "meta_reviewer_zh = autogen.AssistantAgent(\n", + " name=\"元审稿人\",\n", + " llm_config=llm_config,\n", + " system_message=\"你是一名元审稿人，你汇总并审查其他审稿人的工作，\"\n", + " \"并对内容提供最终建议。\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 六、将嵌套对话（Nested Chats）都编排起来解决问题" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "接下来我们来定义对话 ，我们使用上节课学的顺序聊天对话模式（Sequential Chat Conversation Pattern）来建立一系列评论家和审稿人之间的对话。这里的对话顺序是一个评论家分别与内部嵌套的审稿人对话的顺序结构，并非直觉上评论家发送一次消息后，所有审稿人同时作出相应的顺序。 \n", + " \n", + "![fig-4-2](./images/fig-4-2.png)\n", + "\n", + "如下所示，我们有一个包含四个对话的列表，每一个都包含一个特定的审稿人作为接收方，之后我们会把这个对话列表注册到评论家智能体中，由它作为默认的对话发起方，所以在对话列表中不需要再额外指定对话发起者 sender 。\n", + "\n", + "下面我们具体看对话列表中对话的定义。 \n", + " \n", + "在前三个对话中的每次对话中，接收方需要收到合适的初始消息（我们需要将评论家接收到的作家第一版本的作品作为上图中的 `message` 传给各个审稿人），一个常见做法是从外部对话中获取总结的消息，`reflection_message` 中的 `chat_messages_for_summary` 就是这个目的，函数内部的 `sender` 变量就对应评论家。 \n", + " \n", + "同时，顺序对话范式还会通过“结转”机制（`Carryover`）将上一次聊天的摘要带入下一次聊天的上下文中，即之后对话中 `\"Context:\"` 后跟着的内容，且结转的内容会不断积累。\n", + " \n", + "每个对话的输出部分我们希望用大模型来做格式化的总结（即以Json格式输出，包括一个审稿人字段和一个评论字段），所以我们设置 `\"reflection_with_llm\"` 与 `\"summary_prompt\"` 来格式化对话输出。" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [], + "source": [ + "def reflection_message(recipient, messages, sender, config):\n", + " return f'''审查以下内容。 \n", + " \\n\\n {recipient.chat_messages_for_summary(sender)[-1]['content']}'''\n", + "\n", + "review_chats_zh = [\n", + " {\n", + " \"recipient\": SEO_reviewer_zh, \n", + " \"message\": reflection_message, \n", + " \"summary_method\": \"reflection_with_llm\",\n", + " \"summary_args\": {\"summary_prompt\" : \n", + " \"仅以JSON对象的形式返回审查结果：\"\n", + " \"{'审稿人': '', '评论': ''}。这里审稿人应该是你的角色\",},\n", + " \"max_turns\": 1},\n", + " {\n", + " \"recipient\": legal_reviewer_zh, \n", + " \"message\": reflection_message, \n", + " \"summary_method\": \"reflection_with_llm\",\n", + " \"summary_args\": {\"summary_prompt\" : \n", + " \"仅以JSON对象的形式返回审查结果：\"\n", + " \"{'审稿人': '', '评论': ''}。这里审稿人应该是你的角色\",},\n", + " \"max_turns\": 1},\n", + " {\"recipient\": ethics_reviewer_zh, \n", + " \"message\": reflection_message, \n", + " \"summary_method\": \"reflection_with_llm\",\n", + " \"summary_args\": {\"summary_prompt\" : \n", + " \"仅以JSON对象的形式返回审查结果：\"\n", + " \"{'审稿人': '', '评论': ''}。这里审稿人应该是你的角色\"},\n", + " \"max_turns\": 1},\n", + " {\"recipient\": meta_reviewer_zh, \n", + " \"message\": \"汇总所有审稿人的反馈，直接输出给写作的最终建议。\", \n", + " \"max_turns\": 1},\n", + "]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "终于，我们可以把上面定义的审稿对话定义为评论家的嵌套对话了，注意，我们将触发器 `trigger` 设置为作家，这意味着评论家每次接收到作家的消息，都会自动将消息路由到嵌套对话中去进行仔细的反思。" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [], + "source": [ + "critic_zh.register_nested_chats(\n", + " review_chats_zh,\n", + " trigger=writer_zh,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "配置到后，我们现在可以发起评论家和作家之间的对话了，和最开始的流程类似，不同之处就是我们在评论家中定义了嵌套聊天来做仔细的反思。" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[33m评论家\u001b[0m (to 作家):\n", + "\n", + "\n", + " 写一篇关于DeepLearning.AI的简洁但引人入胜的博客文章。\n", + " 确保博客文章是\n", + " 100词以内。\n", + " \n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33m作家\u001b[0m (to 评论家):\n", + "\n", + "标题：探寻DeepLearning.AI的奥秘\n", + "\n", + "在当今数码时代，人工智能是引领创新的主要驱动力之一。而DeepLearning.AI作为人工智能领域的重要一环，在深度学习技术中扮演着关键角色。从神经网络到自然语言处理，DeepLearning.AI让机器具备了人类般的智慧，为各行各业带来了巨大变革。通过专业的在线课程和实践项目，DeepLearning.AI为学习者提供了接触和掌握人工智能技术的独特机会。探索DeepLearning.AI，探寻人工智能的奥秘，引领未来的科技发展。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[34mStarting a new chat....\u001b[0m\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[33m评论家\u001b[0m (to SEO审稿人):\n", + "\n", + "审查以下内容。 \n", + " \n", + "\n", + " 标题：探寻DeepLearning.AI的奥秘\n", + "\n", + "在当今数码时代，人工智能是引领创新的主要驱动力之一。而DeepLearning.AI作为人工智能领域的重要一环，在深度学习技术中扮演着关键角色。从神经网络到自然语言处理，DeepLearning.AI让机器具备了人类般的智慧，为各行各业带来了巨大变革。通过专业的在线课程和实践项目，DeepLearning.AI为学习者提供了接触和掌握人工智能技术的独特机会。探索DeepLearning.AI，探寻人工智能的奥秘，引领未来的科技发展。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mSEO审稿人\u001b[0m (to 评论家):\n", + "\n", + "作为SEO审稿人，我的职责是优化内容以提升搜索引擎排名和吸引流量。请参考以下建议：\n", + "\n", + "1. **优化标题：**\n", + " - 建议将标题调整为更具吸引力和搜索性的版本，例如：“探索DeepLearning.AI：解密人工智能的未来”。\n", + " \n", + "2. **增加关键词密度：**\n", + " - 强化关键词如“DeepLearning.AI”和“人工智能”，增加它们的出现频率，使搜索引擎更容易识别文章主题。\n", + "\n", + "3. **丰富内容细节：**\n", + " - 添加更多关于DeepLearning.AI课程内容、学习方法和成就的具体信息，以提高页面的内容丰富度和搜索价值。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[34mStarting a new chat....\u001b[0m\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[33m评论家\u001b[0m (to 法律审稿人):\n", + "\n", + "审查以下内容。 \n", + " \n", + "\n", + " 标题：探寻DeepLearning.AI的奥秘\n", + "\n", + "在当今数码时代，人工智能是引领创新的主要驱动力之一。而DeepLearning.AI作为人工智能领域的重要一环，在深度学习技术中扮演着关键角色。从神经网络到自然语言处理，DeepLearning.AI让机器具备了人类般的智慧，为各行各业带来了巨大变革。通过专业的在线课程和实践项目，DeepLearning.AI为学习者提供了接触和掌握人工智能技术的独特机会。探索DeepLearning.AI，探寻人工智能的奥秘，引领未来的科技发展。\n", + "Context: \n", + "{'审稿人': 'SEO审稿人', '评论': '建议将标题调整为更具吸引力和搜索性的版本，增加关键词密度，丰富内容细节。'}\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33m法律审稿人\u001b[0m (to 评论家):\n", + "\n", + "作为法律审稿人，我的建议如下：\n", + "\n", + "1. 确保内容涉及到的关于DeepLearning.AI的数据和信息准确无误，避免夸大、误导或不实内容，以避免引发消费者投诉或法律纠纷。\n", + "\n", + "2. 在描述人工智能技术的影响和作用时，确保不会夸大其意义或效果，以避免违反虚假广告法或其他欺诈类法规。\n", + "\n", + "3. 注意在文章中使用的任何商标、专利或知识产权，避免侵犯他人的知识产权，如有必要，应加入相关授权或使用声明。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[34mStarting a new chat....\u001b[0m\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[33m评论家\u001b[0m (to 道德审稿人):\n", + "\n", + "审查以下内容。 \n", + " \n", + "\n", + " 标题：探寻DeepLearning.AI的奥秘\n", + "\n", + "在当今数码时代，人工智能是引领创新的主要驱动力之一。而DeepLearning.AI作为人工智能领域的重要一环，在深度学习技术中扮演着关键角色。从神经网络到自然语言处理，DeepLearning.AI让机器具备了人类般的智慧，为各行各业带来了巨大变革。通过专业的在线课程和实践项目，DeepLearning.AI为学习者提供了接触和掌握人工智能技术的独特机会。探索DeepLearning.AI，探寻人工智能的奥秘，引领未来的科技发展。\n", + "Context: \n", + "{'审稿人': 'SEO审稿人', '评论': '建议将标题调整为更具吸引力和搜索性的版本，增加关键词密度，丰富内容细节。'}\n", + "{'审稿人': '法律审稿人', '评论': '建议确保内容准确性，避免夸大描写和侵犯知识产权，以规避法律风险。'}\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33m道德审稿人\u001b[0m (to 评论家):\n", + "\n", + "我是一名伦理审稿人，我的职责是确保内容在伦理上没有问题并且没有任何潜在伦理问题。\n", + "\n", + "1. 确保内容准确性：在探讨DeepLearning.AI的奥秘时，确保所有陈述和描述都是准确无误的，避免夸大描写或误导读者。\n", + "\n", + "2. 尊重知识产权：在讨论人工智能领域时，确保遵守知识产权法律，不要侵犯任何他人的专利、商标或版权。\n", + "\n", + "3. 避免误导读者：在描述DeepLearning.AI的重要性和作用时，避免过度夸大或误导读者，确保内容真实可靠。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[34mStarting a new chat....\u001b[0m\n", + "\u001b[34m\n", + "********************************************************************************\u001b[0m\n", + "\u001b[33m评论家\u001b[0m (to 元审稿人):\n", + "\n", + "汇总所有审稿人的反馈，直接输出给写作的最终建议。\n", + "Context: \n", + "{'审稿人': 'SEO审稿人', '评论': '建议将标题调整为更具吸引力和搜索性的版本，增加关键词密度，丰富内容细节。'}\n", + "{'审稿人': '法律审稿人', '评论': '建议确保内容准确性，避免夸大描写和侵犯知识产权，以规避法律风险。'}\n", + "{'审稿人': '伦理审稿人', '评论': '确保内容在伦理上没有问题并且没有任何潜在伦理问题。'}\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33m元审稿人\u001b[0m (to 评论家):\n", + "\n", + "经过审稿人的反馈汇总：\n", + "\n", + "1. SEO审稿人建议将标题调整为更具吸引力和搜索性的版本，增加关键词密度，丰富内容细节。\n", + "2. 法律审稿人建议确保内容准确性，避免夸大描写和侵犯知识产权，以规避法律风险。\n", + "3. 伦理审稿人建议确保内容在伦理上没有问题并且没有任何潜在伦理问题。\n", + "\n", + "综合来看，建议在调整标题以提升吸引力和搜索性的同时，要确保内容准确性，避免夸大描写和侵犯知识产权，同时对内容进行伦理审查，确保没有任何潜在伦理问题的存在。综合以上审稿人的建议，最终稿件应该是符合SEO要求、法律规定和伦理标准的完整内容。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33m评论家\u001b[0m (to 作家):\n", + "\n", + "经过审稿人的反馈汇总：\n", + "\n", + "1. SEO审稿人建议将标题调整为更具吸引力和搜索性的版本，增加关键词密度，丰富内容细节。\n", + "2. 法律审稿人建议确保内容准确性，避免夸大描写和侵犯知识产权，以规避法律风险。\n", + "3. 伦理审稿人建议确保内容在伦理上没有问题并且没有任何潜在伦理问题。\n", + "\n", + "综合来看，建议在调整标题以提升吸引力和搜索性的同时，要确保内容准确性，避免夸大描写和侵犯知识产权，同时对内容进行伦理审查，确保没有任何潜在伦理问题的存在。综合以上审稿人的建议，最终稿件应该是符合SEO要求、法律规定和伦理标准的完整内容。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33m作家\u001b[0m (to 评论家):\n", + "\n", + "标题：揭秘DeepLearning.AI：探寻人工智能未来之路\n", + "\n", + "在当代数码浪潮中，人工智能扮演着重要角色，而DeepLearning.AI则成为引领创新的中流砥柱。从神经网络到自然语言处理，它赋予机器以人类般智慧，推动各行业变革。通过专业课程和实践项目，DeepLearning.AI为学习者开启探寻人工智能奥秘之旅。探索其无限潜力，引领科技发展新纪元。\n", + "\n", + "**修改后的文章符合审稿人的反馈，旨在提升标题内容质量和避免潜在问题。**\n", + "\n", + "--------------------------------------------------------------------------------\n" + ] + } + ], + "source": [ + "res = critic_zh.initiate_chat(\n", + " recipient=writer_zh,\n", + " message=task_zh,\n", + " max_turns=2,\n", + " summary_method=\"last_msg\"\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "通过上方的具体聊天记录可见： \n", + " \n", + "- 第一步是作家生成文章，然后评论家没有直接给出反馈，而是将消息路由到了嵌套对话中。 \n", + " \n", + "- 然后是评论家和SEO审稿人的对话，SEO检查内容后，给出关于优化搜索引擎排名相关的建议，比如优化标题；\n", + "\n", + "- 接下来是法律审稿人，检查法律风险并给出建议，比如不侵犯知识产权；之后是道德审稿人，给出建议如确保内容准确不夸大。 \n", + " \n", + "- 最后是元审稿人，负责总结所有建议，并且通过评论家给到作家。 \n", + " \n", + "- 作家根据意见修改，得到新一版的作品。\n", + " \n", + "我们发现在嵌套对话中，之前的聊天信息作为结转（`carryover`）会在 `Content` 中在每次对话中给到接收方。" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 七、获得概述" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "进一步，我们调用结果的摘要属性 `suammary` 来检查结果，可见，它返回了最终修改后的博客文章。" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "标题：探索DeepLearning.AI：引领人工智能的革新之路\n", + "\n", + "在当今数码时代，DeepLearning.AI作为人工智能领域的重要组成部分正引领着技术革新的潮流。融合神经网络、自然语言处理等技术，深度学习赋予机器以智能，改变着各行各业的运作方式。通过专业的在线课程和实践项目，DeepLearning.AI为学习者展开了人工智能的奥秘之旅，培养着未来的科技领袖。探索DeepLearning.AI，了解技术背后的原理与应用，助力科技迈向更辉煌的未来。\n" + ] + } + ], + "source": [ + "print(res.summary)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "我们可以继续尝试不同的任务，比如写你感兴趣主题的文章。 \n", + " \n", + "\n", + " \n", + "总结： 这节课中我们学习了如何利用嵌套聊天实现反思设计范式，下节课中，我们将进一步学习如何用嵌套聊天来提升智能体设计范式。" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "autogen", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/content/AI Agentic Design Patterns with AutoGen/images/fig-4-1.png b/content/AI Agentic Design Patterns with 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bytes 4 files changed, 1711 insertions(+) create mode 100644 "content/AI Agentic Design Patterns with AutoGen/6.\344\273\243\347\240\201\344\270\216\351\207\221\350\236\215\345\210\206\346\236\220 coding_and_financial_analysis.ipynb" create mode 100644 "content/AI Agentic Design Patterns with AutoGen/7. \350\247\204\345\210\222\344\270\216\350\202\241\347\245\250\346\212\245\345\221\212\347\224\237\346\210\220 planning_and_stock_report_Generation.ipynb" create mode 100644 content/AI Agentic Design Patterns with AutoGen/images/group_of_agents.jpg create mode 100644 content/AI Agentic Design Patterns with AutoGen/images/writer_and_executor.png diff --git "a/content/AI Agentic Design Patterns with AutoGen/6.\344\273\243\347\240\201\344\270\216\351\207\221\350\236\215\345\210\206\346\236\220 coding_and_financial_analysis.ipynb" "b/content/AI Agentic Design Patterns with AutoGen/6.\344\273\243\347\240\201\344\270\216\351\207\221\350\236\215\345\210\206\346\236\220 coding_and_financial_analysis.ipynb" new file mode 100644 index 00000000..145c81fe --- /dev/null +++ "b/content/AI Agentic Design Patterns with AutoGen/6.\344\273\243\347\240\201\344\270\216\351\207\221\350\236\215\345\210\206\346\236\220 coding_and_financial_analysis.ipynb" @@ -0,0 +1,865 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "eacbb70c", + "metadata": {}, + "source": [ + "# 代码与金融分析\n", + "\n", + "在这节课程你将构建两个Agent，他们将合作解决手头的任务同时请求你的反馈。第一个Agent将使用llm生成代码，第二个Agent则负责执行代码。\n", + "\n", + "
\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "id": "babbc472", + "metadata": {}, + "source": [ + "## 设置配置\n", + "本节我们使用`gpt-4-turbo`创建Agent。" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "b5613ba9-d387-4b7d-9670-ec2b6e4353be", + "metadata": { + "height": 30 + }, + "outputs": [], + "source": [ + "llm_config={\"model\": \"gpt-4-turbo\"}" + ] + }, + { + "cell_type": "markdown", + "id": "e4e8fd85", + "metadata": {}, + "source": [ + "## 创建代码执行器\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "fb90a672-4318-47de-a061-384e68dd75c9", + "metadata": { + "height": 30 + }, + "outputs": [], + "source": [ + "from autogen.coding import LocalCommandLineCodeExecutor\n", + "# 该类通过命令行执行代码" + ] + }, + { + "cell_type": "markdown", + "id": "0a210ea3", + "metadata": {}, + "source": [ + "我们通过输入`timeout`与`work_dir`等配置信息来实例化代码执行器，其中`timeout`为等待代码执行的时间默认为60秒，`work_dir`为代码执行的目录，可以在该目录下查看代码与代码执行的中间结果。" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "7e2d59cd", + "metadata": {}, + "outputs": [], + "source": [ + "executor = LocalCommandLineCodeExecutor(\n", + " timeout=60,\n", + " work_dir=\"coding\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "3b62a1a0", + "metadata": {}, + "source": [ + "## 创建Agent" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "e6d9b3d6-9915-4fea-a853-512dfb77c4a5", + "metadata": { + "height": 30 + }, + "outputs": [], + "source": [ + "from autogen import ConversableAgent, AssistantAgent" + ] + }, + { + "cell_type": "markdown", + "id": "b741b947", + "metadata": {}, + "source": [ + "### 1. 代码执行Agent\n", + "创建一个负责执行代码的Agent，该Agent基于刚才创建的代码执行器，并不使用大模型，因此设置`llm_config`为`False`；`human_input_mode`人类输入模式设置为`ALWAYS`，因此Agent在每次执行代码前都需要人工确认；通过设置`default_auto_reply`默认自动回复为`Please continue. If everything is done, reply 'TERMINATE'.`来让Agent在检测不到代码时对代码编写Agent发送我们设置的回复。" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "57d286e5-b7b7-405a-b1d7-212c0cc84497", + "metadata": { + "height": 149 + }, + "outputs": [], + "source": [ + "code_executor_agent = ConversableAgent(\n", + " name=\"code_executor_agent\",\n", + " llm_config=False,\n", + " code_execution_config={\"executor\": executor},\n", + " human_input_mode=\"ALWAYS\",\n", + " default_auto_reply=\n", + " \"Please continue. If everything is done, reply 'TERMINATE'.\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "c1eb1094", + "metadata": {}, + "source": [ + "### 2. 代码编写Agent\n", + "创建一个编写代码的Agent，该Agent接入我们之前设置的`gpt-4-turbo`，因为它只负责编写代码所以我们将它的`code_execution_config`代码执行器配置设置为`False`，将`human_input_mode`人类输入模式设置为`NEVER`来让它运行时候不需要人类输入。\n", + "AssistantAgent 是 ConversableAgent 的子类，相比起ConversableAgent，AssistantAgent的系统消息更适合让Agent通过撰写代码的方式完成任务。" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "99c38c33-d335-48cd-96eb-cafe9ac70142", + "metadata": { + "height": 115 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[autogen.oai.client: 06-02 23:32:21] {129} WARNING - The API key specified is not a valid OpenAI format; it won't work with the OpenAI-hosted model.\n" + ] + } + ], + "source": [ + "code_writer_agent = AssistantAgent(\n", + " name=\"code_writer_agent\",\n", + " llm_config=llm_config,\n", + " code_execution_config=False,\n", + " human_input_mode=\"NEVER\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "22c0aa43", + "metadata": {}, + "source": [ + "如果你对代码编写Agent好奇，我们可以打印它的系统消息来查看它最开始接受的系统消息。" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "0fb1a62f-8dd2-4636-9103-b26ea27a29bd", + "metadata": { + "height": 30 + }, + "outputs": [], + "source": [ + "code_writer_agent_system_message = code_writer_agent.system_message" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "7c8e9a04-55fb-4124-a9d0-3431274476d2", + "metadata": { + "height": 30 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "You are a helpful AI assistant.\n", + "Solve tasks using your coding and language skills.\n", + "In the following cases, suggest python code (in a python coding block) or shell script (in a sh coding block) for the user to execute.\n", + " 1. When you need to collect info, use the code to output the info you need, for example, browse or search the web, download/read a file, print the content of a webpage or a file, get the current date/time, check the operating system. After sufficient info is printed and the task is ready to be solved based on your language skill, you can solve the task by yourself.\n", + " 2. When you need to perform some task with code, use the code to perform the task and output the result. Finish the task smartly.\n", + "Solve the task step by step if you need to. If a plan is not provided, explain your plan first. Be clear which step uses code, and which step uses your language skill.\n", + "When using code, you must indicate the script type in the code block. The user cannot provide any other feedback or perform any other action beyond executing the code you suggest. The user can't modify your code. So do not suggest incomplete code which requires users to modify. Don't use a code block if it's not intended to be executed by the user.\n", + "If you want the user to save the code in a file before executing it, put # filename: inside the code block as the first line. Don't include multiple code blocks in one response. Do not ask users to copy and paste the result. Instead, use 'print' function for the output when relevant. Check the execution result returned by the user.\n", + "If the result indicates there is an error, fix the error and output the code again. Suggest the full code instead of partial code or code changes. If the error can't be fixed or if the task is not solved even after the code is executed successfully, analyze the problem, revisit your assumption, collect additional info you need, and think of a different approach to try.\n", + "When you find an answer, verify the answer carefully. Include verifiable evidence in your response if possible.\n", + "Reply \"TERMINATE\" in the end when everything is done.\n", + " \n" + ] + } + ], + "source": [ + "print(code_writer_agent_system_message)" + ] + }, + { + "cell_type": "markdown", + "id": "f487b75a", + "metadata": {}, + "source": [ + "## 执行任务\n", + "\n", + "让两个Agent合作完成股票分析。" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "9cce0ba4-9fea-4d36-b4a0-a1e51fcd09a6", + "metadata": { + "height": 132 + }, + "outputs": [], + "source": [ + "import datetime\n", + "\n", + "today = datetime.datetime.now().date()\n", + "weekday = datetime.date.today().weekday()\n", + "message = f\"今天是 {today}, 周{weekday + 1}. \"\\\n", + "\"创建一个图表，显示NVDA和TLSA到今天的股票收益。请注意，股票不会在周末交易。\"\\\n", + "\"确保代码在markdown代码块中并保存图片\"\\\n", + "\"到文件 ytd_stock_gains.png 中。\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "2bf5be6f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[33mcode_executor_agent\u001b[0m (to code_writer_agent):\n", + "\n", + "今天是 2024-06-02, 周6. 创建一个图表，显示NVDA和TLSA到今天的股票收益。请注意，股票不会在周末交易。确保代码在markdown代码块中并保存图片到文件 ytd_stock_gains.png 中。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mcode_writer_agent\u001b[0m (to code_executor_agent):\n", + "\n", + "首先，我们需要获取NVIDIA和Tesla的股票数据。在获取数据之前，我们需要计划如何处理数据并将结果保存为图表。这里是我们将要执行的步骤：\n", + "\n", + "1. 设置Python环境并安装所需的库。\n", + "2. 获取NVIDIA和Tesla自年初至2024-05-31的股票数据，因为股票市场在周末不交易。\n", + "3. 使用收盘价格数据计算从年初到最新的收益。\n", + "4. 绘制股票收益图，并保存为PNG文件。\n", + "\n", + "现在，让我们先确保您的Python环境已经安装了需要用到的库。如果还未安装，我会提供安装指令。复制以下代码到Python环境中执行，以检查并安装缺失的库。\n", + "\n", + "```python\n", + "# filename: check_and_install_libraries.py\n", + "import subprocess\n", + "import pkg_resources\n", + "\n", + "required = {'yfinance', 'matplotlib', 'pandas'}\n", + "installed = {pkg.key for pkg in pkg_resources.working_set}\n", + "missing = required - installed\n", + "\n", + "if missing:\n", + " python = sys.executable\n", + " subprocess.check_call([python, '-m', 'pip', 'install', *missing], stdout=subprocess.DEVNULL)\n", + "\n", + "import yfinance as yf\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "\n", + "print(\"所有必要的库都已安装并导入。\")\n", + "```\n", + "\n", + "执行这段代码，确保所有库已经准备完备，然后回来继续下一个步骤。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> NO HUMAN INPUT RECEIVED.\u001b[0m\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[31m\n", + ">>>>>>>> EXECUTING CODE BLOCK (inferred language is python)...\u001b[0m\n", + "\u001b[33mcode_executor_agent\u001b[0m (to code_writer_agent):\n", + "\n", + "exitcode: 0 (execution succeeded)\n", + "Code output: /Users/lta/Desktop/autogen_tutorial/coding/check_and_install_libraries.py:3: DeprecationWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html\n", + " import pkg_resources\n", + "所有必要的库都已安装并导入。\n", + "\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mcode_writer_agent\u001b[0m (to code_executor_agent):\n", + "\n", + "既然所有必要的库都已安装，我们现在可以继续获取NVIDIA (NVDA) 和 Tesla (TSLA) 的股票数据，并且计算从2024年初到5月31日的收益率。然后，我们会使用这些数据绘制股票收益图表。\n", + "\n", + "接下来是下载股票数据的代码。我们将下载两只股票的收盘数据，计算其从2024年1月1日到5月31日的收益，并制作图表。请将以下代码保存到文件并执行。\n", + "\n", + "```python\n", + "# filename: plot_stock_gains.py\n", + "import yfinance as yf\n", + "import matplotlib.pyplot as plt\n", + "import pandas as pd\n", + "\n", + "# 设置起始日期和结束日期\n", + "start_date = '2024-01-01'\n", + "end_date = '2024-05-31'\n", + "\n", + "# 下载股票数据\n", + "nvda = yf.download('NVDA', start=start_date, end=end_date)\n", + "tsla = yf.download('TSLA', start=start_date, end=end_date)\n", + "\n", + "# 计算收益率: (Today's Close - Year Start Close) / Year Start Close\n", + "nvda_returns = (nvda['Close'] / nvda['Close'][0] - 1) * 100\n", + "tsla_returns = (tsla['Close'] / tsla['Close'][0] - 1) * 100\n", + "\n", + "# 创建图表\n", + "plt.figure(figsize=(14, 7))\n", + "plt.plot(nvda_returns, label='NVIDIA (NVDA)')\n", + "plt.plot(tsla_returns, label='Tesla (TSLA)')\n", + "plt.title('Stock Gains from 2024-01-01 to 2024-05-31')\n", + "plt.xlabel('Date')\n", + "plt.ylabel('Gain (%)')\n", + "plt.legend()\n", + "plt.grid(True)\n", + "\n", + "# 保存图表为PNG文件\n", + "plt.savefig('ytd_stock_gains.png')\n", + "plt.show()\n", + "```\n", + "\n", + "这段代码将下载所需要的股票数据，计算每日的收益率，然后绘制出一个图表，并保存为PNG文件。请运行这段代码并查看生成的图表。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> NO HUMAN INPUT RECEIVED.\u001b[0m\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[31m\n", + ">>>>>>>> EXECUTING CODE BLOCK (inferred language is python)...\u001b[0m\n", + "\u001b[33mcode_executor_agent\u001b[0m (to code_writer_agent):\n", + "\n", + "exitcode: 0 (execution succeeded)\n", + "Code output: \n", + "[*********************100%%**********************] 1 of 1 completed\n", + "\n", + "[*********************100%%**********************] 1 of 1 completed\n", + "/Users/lta/Desktop/autogen_tutorial/coding/plot_stock_gains.py:15: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " nvda_returns = (nvda['Close'] / nvda['Close'][0] - 1) * 100\n", + "/Users/lta/Desktop/autogen_tutorial/coding/plot_stock_gains.py:16: FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + " tsla_returns = (tsla['Close'] / tsla['Close'][0] - 1) * 100\n", + "Figure(1400x700)\n", + "\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mcode_writer_agent\u001b[0m (to code_executor_agent):\n", + "\n", + "代码已成功执行，并生成了图表，尽管存在一些未来警告关于将整数索引作为位置索引使用的问题。这些警告可以在未来的代码更新中考虑调整，但目前不影响您的使用结果。\n", + "\n", + "生成的图表已保存为 'ytd_stock_gains.png' 文件。现在您应当能够在指定的文件路径中找到此图表文件，它展示了从2024年1月1日到5月31日，NVIDIA和Tesla股票的收益率变化。\n", + "\n", + "如果有其他需要帮助的地方，请告诉我！否则，任务已经完成。\n", + "\n", + "TERMINATE\n", + "\n", + "--------------------------------------------------------------------------------\n" + ] + } + ], + "source": [ + "chat_result = code_executor_agent.initiate_chat(\n", + " code_writer_agent,\n", + " message=message,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "77fc5f1b", + "metadata": {}, + "source": [ + "**注意**: 你的运行结果可能与notebook中的不一样，并且在过程中有可能产生带有错误的代码。不过，它们最终会提供正确的代码。" + ] + }, + { + "cell_type": "markdown", + "id": "9b0cbbdd", + "metadata": {}, + "source": [ + "## 显示图像\n", + "现在让我们导入图像并将它显示。\n", + "**注意**: \n", + "* 你的绘图可能与上次运行结果显示的不同，因为LLM的自由式代码生成可以选择不同的绘图类型，例如条形图。\n", + "* 你可以重新运行上一个单元格并检查生成的代码。如果它生成的是条形图，请记住，你可以直接指定你喜欢的图形类型，而不是条形图。" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "26804313-566f-42fb-9243-4e0c147f770b", + "metadata": { + "height": 81 + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import os\n", + "from IPython.display import Image\n", + "\n", + "Image(os.path.join(\"coding\", \"ytd_stock_gains.png\"))" + ] + }, + { + "cell_type": "markdown", + "id": "ccf49d7e", + "metadata": {}, + "source": [ + "**注意**: 代理将自动将代码保存在.py文件中，并将绘图保存在.png文件中。要访问和检查代理生成的文件，可以打开`coding`文件夹以找到所有生成的文件。" + ] + }, + { + "cell_type": "markdown", + "id": "5aded8dc", + "metadata": {}, + "source": [ + "## 用户自定义函数\n", + "\n", + "如果你想更多地控制如何完成这个任务，你可以为这两个任务定义函数，并让Agent在代码中调用这些函数，而不是要求Agent每次都生成下载股票数据和绘制图表的代码。" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "bca089a7-d85a-40ad-b33d-6a5318076c6e", + "metadata": { + "height": 387 + }, + "outputs": [], + "source": [ + "def get_stock_prices(stock_symbols, start_date, end_date):\n", + " \"\"\"获取给定股票符号在开始和结束日期之间的股票价格\n", + "\n", + " Args:\n", + " stock_symbols (str or list): 用来获取价格的股票符号\n", + " start_date (str): 起始日期的格式为'YYYY-MM-DD'\n", + " end_date (str): 结束日期，格式为'YYYY-MM-DD'.\n", + " \n", + " Returns:\n", + " pandas.DataFrame: 给定股票符号的股票价格按日期索引，每个股票符号一列\n", + " \"\"\"\n", + " import yfinance #导入yfinance\n", + "\n", + " stock_data = yfinance.download( #下载数据 \n", + " stock_symbols, start=start_date, end=end_date\n", + " )\n", + " return stock_data.get(\"Close\")" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "5dff50a6-39ae-46a4-9b9c-e98c1550472b", + "metadata": { + "height": 336 + }, + "outputs": [], + "source": [ + "def plot_stock_prices(stock_prices, filename):\n", + " \"\"\"绘制给定股票符号的股票价格\n", + "\n", + " Args:\n", + " stock_prices (pandas.DataFrame): 给定股票符号的股票价格\n", + " \"\"\"\n", + " import matplotlib.pyplot as plt \n", + "\n", + " plt.figure(figsize=(10, 5))\n", + " for column in stock_prices.columns:\n", + " plt.plot(\n", + " stock_prices.index, stock_prices[column], label=column\n", + " )\n", + " plt.title(\"Stock Prices\")\n", + " plt.xlabel(\"Date\")\n", + " plt.ylabel(\"Price\")\n", + " plt.grid(True)\n", + " plt.savefig(filename)" + ] + }, + { + "cell_type": "markdown", + "id": "63ff7175", + "metadata": {}, + "source": [ + "### 使用自定义的函数创建新的代码执行器" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "452d315f-681d-4418-9cd0-653cc8d6a668", + "metadata": { + "height": 98 + }, + "outputs": [], + "source": [ + "executor = LocalCommandLineCodeExecutor(\n", + " timeout=60,\n", + " work_dir=\"coding\",\n", + " functions=[get_stock_prices, plot_stock_prices],# 把刚定义的函数添加到执行器中\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "a9ca7648", + "metadata": {}, + "source": [ + "我们同时也要让code_writer Agent 知道函数的存在，因此把定义的函数添加到prompt中，方便Agent理解。" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "b95b30ad-1e6d-4d88-9a6c-2b0f11b625e4", + "metadata": { + "height": 47 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "You are a helpful AI assistant.\n", + "Solve tasks using your coding and language skills.\n", + "In the following cases, suggest python code (in a python coding block) or shell script (in a sh coding block) for the user to execute.\n", + " 1. When you need to collect info, use the code to output the info you need, for example, browse or search the web, download/read a file, print the content of a webpage or a file, get the current date/time, check the operating system. After sufficient info is printed and the task is ready to be solved based on your language skill, you can solve the task by yourself.\n", + " 2. When you need to perform some task with code, use the code to perform the task and output the result. Finish the task smartly.\n", + "Solve the task step by step if you need to. If a plan is not provided, explain your plan first. Be clear which step uses code, and which step uses your language skill.\n", + "When using code, you must indicate the script type in the code block. The user cannot provide any other feedback or perform any other action beyond executing the code you suggest. The user can't modify your code. So do not suggest incomplete code which requires users to modify. Don't use a code block if it's not intended to be executed by the user.\n", + "If you want the user to save the code in a file before executing it, put # filename: inside the code block as the first line. Don't include multiple code blocks in one response. Do not ask users to copy and paste the result. Instead, use 'print' function for the output when relevant. Check the execution result returned by the user.\n", + "If the result indicates there is an error, fix the error and output the code again. Suggest the full code instead of partial code or code changes. If the error can't be fixed or if the task is not solved even after the code is executed successfully, analyze the problem, revisit your assumption, collect additional info you need, and think of a different approach to try.\n", + "When you find an answer, verify the answer carefully. Include verifiable evidence in your response if possible.\n", + "Reply \"TERMINATE\" in the end when everything is done.\n", + " You have access to the following user defined functions. They can be accessed from the module called `functions` by their function names.\n", + "\n", + "For example, if there was a function called `foo` you could import it by writing `from functions import foo`\n", + "\n", + "def get_stock_prices(stock_symbols, start_date, end_date):\n", + " \"\"\"Get the stock prices for the given stock symbols between\n", + " the start and end dates.\n", + "\n", + " Args:\n", + " stock_symbols (str or list): The stock symbols to get the\n", + " prices for.\n", + " start_date (str): The start date in the format \n", + " 'YYYY-MM-DD'.\n", + " end_date (str): The end date in the format 'YYYY-MM-DD'.\n", + "\n", + " Returns:\n", + " pandas.DataFrame: The stock prices for the given stock\n", + " symbols indexed by date, with one column per stock \n", + " symbol.\n", + " \"\"\"\n", + " ...\n", + "\n", + "def plot_stock_prices(stock_prices, filename):\n", + " \"\"\"Plot the stock prices for the given stock symbols.\n", + "\n", + " Args:\n", + " stock_prices (pandas.DataFrame): The stock prices for the \n", + " given stock symbols.\n", + " \"\"\"\n", + " ...\n" + ] + } + ], + "source": [ + "code_writer_agent_system_message += executor.format_functions_for_prompt()\n", + "print(code_writer_agent_system_message)" + ] + }, + { + "cell_type": "markdown", + "id": "64d3cc77", + "metadata": {}, + "source": [ + "### 使用新的系统消息更新代理" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "615c02b0-0175-442e-bed2-52bb35b8945c", + "metadata": { + "height": 132 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[autogen.oai.client: 06-02 23:32:53] {129} WARNING - The API key specified is not a valid OpenAI format; it won't work with the OpenAI-hosted model.\n" + ] + } + ], + "source": [ + "code_writer_agent = ConversableAgent(\n", + " name=\"code_writer_agent\",\n", + " system_message=code_writer_agent_system_message, # 传入新的prompt\n", + " llm_config=llm_config,\n", + " code_execution_config=False,\n", + " human_input_mode=\"NEVER\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "a9a725b0-9bb6-47e3-85df-27d9aadc9290", + "metadata": { + "height": 149 + }, + "outputs": [], + "source": [ + "code_executor_agent = ConversableAgent(\n", + " name=\"code_executor_agent\",\n", + " llm_config=False,\n", + " code_execution_config={\"executor\": executor},\n", + " human_input_mode=\"ALWAYS\",\n", + " default_auto_reply=\n", + " \"Please continue. If everything is done, reply 'TERMINATE'.\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "e8d7b57c", + "metadata": {}, + "source": [ + "### 使用新代理执行任务" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "8895bb51-bcdd-4f63-a49f-858fc25c474f", + "metadata": { + "height": 132 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[33mcode_executor_agent\u001b[0m (to code_writer_agent):\n", + "\n", + "今天是2024-06-02, 周6。下载NVDA和TSLA的股票价格并绘制图表确保代码在markdown代码块中，并将图形保存到文件 file stock_prices_YTD_plot.png 中.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mcode_writer_agent\u001b[0m (to code_executor_agent):\n", + "\n", + "为了完成任务，我们将遵循以下步骤：\n", + "\n", + "1. 从 `functions` 模块导入 `get_stock_prices` 和 `plot_stock_prices` 函数。\n", + "2. 定义起止日期来获取年初至今的股票价格数据。起始日期是本年的1月1日，即2024年，结束日期是今天，即2024年6月2日。\n", + "3. 使用 `get_stock_prices` 函数下载 NVIDIA (NVDA) 和 Tesla (TSLA) 的股票价格数据。\n", + "4. 使用 `plot_stock_prices` 函数将股票价格绘图，并保存到文件 `stock_prices_YTD_plot.png` 中。\n", + "\n", + "先执行以下 Python 代码来获取和绘制股票价格数据：\n", + "\n", + "```python\n", + "# filename: fetch_and_plot_stocks.py\n", + "from functions import get_stock_prices, plot_stock_repices\n", + "\n", + "# 定义股票代码和日期范围\n", + "stock_symbols = [\"NVDA\", \"TSLA\"]\n", + "start_date = \"2024-01-01\"\n", + "end_date = \"2024-06-02\"\n", + "\n", + "# 获取股票价格数据\n", + "stock_prices = get_stock_prices(stock_symbols, start_date, end_date)\n", + "\n", + "# 绘制股票价格图表并保存到文件\n", + "plot_stock_prices(stock_prices, \"stock_prices_YTD_plot.png\")\n", + "print(\"Stock prices plotted and saved to 'stock_prices_YTD_plot.png'.\")\n", + "```\n", + "\n", + "请保存以上代码到一个文件中，命名为 `fetch_and_plot_stocks.py`，然后运行这个 Python 脚本。这将下载并绘制股票数据，并保存图表到指定文件中。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> NO HUMAN INPUT RECEIVED.\u001b[0m\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[31m\n", + ">>>>>>>> EXECUTING CODE BLOCK (inferred language is python)...\u001b[0m\n", + "\u001b[33mcode_executor_agent\u001b[0m (to code_writer_agent):\n", + "\n", + "exitcode: 1 (execution failed)\n", + "Code output: Traceback (most recent call last):\n", + " File \"/Users/lta/Desktop/autogen_tutorial/coding/fetch_and_plot_stocks.py\", line 2, in \n", + " from functions import get_stock_prices, plot_stock_repices\n", + "ImportError: cannot import name 'plot_stock_repices' from 'functions' (/Users/lta/Desktop/autogen_tutorial/coding/functions.py)\n", + "\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mcode_writer_agent\u001b[0m (to code_executor_agent):\n", + "\n", + "在代码中发生了一个简单的拼写错误：尝试导入名为 `plot_stock_repices` 的函数，而正确的函数名应该是 `plot_stock_prices`。我会更正这个错误并重新给出修正后的代码。\n", + "\n", + "请替换为以下正确的代码，然后重新执行：\n", + "\n", + "```python\n", + "# filename: fetch_and_plot_stocks.py\n", + "from functions import get_stock_prices, plot_stock_prices\n", + "\n", + "# 定义股票代码和日期范围\n", + "stock_symbols = [\"NVDA\", \"TSLA\"]\n", + "start_date = \"2024-01-01\"\n", + "end_date = \"2024-06-02\"\n", + "\n", + "# 获取股票价格数据\n", + "stock_prices = get_stock_prices(stock_symbols, start_date, end_date)\n", + "\n", + "# 绘制股票价格图表并保存到文件\n", + "plot_stock_prices(stock_prices, \"stock_prices_YTD_plot.png\")\n", + "print(\"Stock prices plotted and saved to 'stock_prices_YTD_plot.png'.\")\n", + "```\n", + "\n", + "请确保更新文件 `fetch_and_plot_stocks.py` 并再次执行该脚本。这次导入应该正确无误，并且可成功执行股票价格下载和绘图操作。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> NO HUMAN INPUT RECEIVED.\u001b[0m\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[31m\n", + ">>>>>>>> EXECUTING CODE BLOCK (inferred language is python)...\u001b[0m\n", + "\u001b[33mcode_executor_agent\u001b[0m (to code_writer_agent):\n", + "\n", + "exitcode: 0 (execution succeeded)\n", + "Code output: \n", + "[ 0%% ]\n", + "[*********************100%%**********************] 2 of 2 completed\n", + "Stock prices plotted and saved to 'stock_prices_YTD_plot.png'.\n", + "\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mcode_writer_agent\u001b[0m (to code_executor_agent):\n", + "\n", + "代码执行成功，并且股票价格图表已经成功保存到文件 `stock_prices_YTD_plot.png`。您可以查看这个文件以确认图表是按照要求绘制的。\n", + "\n", + "如果您有更多任务或查询，请随时告诉我。\n", + "\n", + "TERMINATE\n", + "\n", + "--------------------------------------------------------------------------------\n" + ] + } + ], + "source": [ + "chat_result = code_executor_agent.initiate_chat(\n", + " code_writer_agent,\n", + " message=f\"今天是{today}, 周{weekday}。\"\n", + " \"下载NVDA和TSLA的股票价格并绘制图表\"\n", + " \"确保代码在markdown代码块中，并将图形保存到文件\"\n", + " \" file stock_prices_YTD_plot.png 中.\",\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "3c4bb718", + "metadata": {}, + "source": [ + "### 绘制结果" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "a930c007-dd56-4da6-b542-902312ed27dd", + "metadata": { + "height": 30 + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "Image(os.path.join(\"coding\", \"stock_prices_YTD_plot.png\"))" + ] + }, + { + "cell_type": "markdown", + "id": "694967f2", + "metadata": {}, + "source": [ + "总结：我们学习了两种代码生成的方式，一种是基于默认的AssistantAgent，另一种是基于额外提供的用户自定义函数。代码生成能力是一种通用的能力，可以用来执行许多不同的任务，你可以探索更多关于不同种类的代码执行器，或者为不同的语言或执行环境定义自己的代码执行器。" + ] + }, + { + "cell_type": "markdown", + "id": "c65bac5e", + "metadata": {}, + "source": [ + "**注意**: 代理将自动将代码保存在.py文件中，并将绘图保存在.png文件中。要访问和检查代理生成的文件，可以打开`coding`文件夹以找到所有生成的文件。" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git "a/content/AI Agentic Design Patterns with AutoGen/7. \350\247\204\345\210\222\344\270\216\350\202\241\347\245\250\346\212\245\345\221\212\347\224\237\346\210\220 planning_and_stock_report_Generation.ipynb" "b/content/AI Agentic Design Patterns with AutoGen/7. \350\247\204\345\210\222\344\270\216\350\202\241\347\245\250\346\212\245\345\221\212\347\224\237\346\210\220 planning_and_stock_report_Generation.ipynb" new file mode 100644 index 00000000..fe87cf7b --- /dev/null +++ "b/content/AI Agentic Design Patterns with AutoGen/7. \350\247\204\345\210\222\344\270\216\350\202\241\347\245\250\346\212\245\345\221\212\347\224\237\346\210\220 planning_and_stock_report_Generation.ipynb" @@ -0,0 +1,846 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "0b9a3d83", + "metadata": {}, + "source": [ + "# 规划和股票报告生成\n", + "在这章我们将会搭建一个定制的多Agent组成的群聊，协作生成关于过去一个月股票表现的详细报告。\n", + "
\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "id": "8d5f1491", + "metadata": {}, + "source": [ + "## 设置配置" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "ad72cb6c-a916-40f7-960c-501c6309037f", + "metadata": { + "height": 30 + }, + "outputs": [], + "source": [ + "llm_config={\"model\": \"gpt-4-turbo\"}" + ] + }, + { + "cell_type": "markdown", + "id": "d09b03c3", + "metadata": {}, + "source": [ + "## 创建任务" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "01c1772f-2583-4c7a-a8a0-dd2946eea022", + "metadata": { + "height": 47 + }, + "outputs": [], + "source": [ + "task = \"写一篇关于过去一个月\"\\\n", + "\"Nvidia股价表现的博客。今天是 2024-04-23。\"" + ] + }, + { + "cell_type": "markdown", + "id": "be3ca91b", + "metadata": {}, + "source": [ + "## 建立群聊\n", + "\n", + "在之前的学习中，我们学习了顺序聊天的对话模版，它可以执行多步任务，但需要人类设计具体的步骤和每个步骤中涉及的具体Agent，如果我们想要简单地定义Agent并让它们共同解决这个任务，那么这个群聊的对话模式能够满足你的需求。\n", + "\n", + "为了完成任务，这个群聊将包含以下Agent：\n", + "\n", + "1. **User_proxy** or **Admin**: 允许用户对报告进行评论，并要求作者对报告进行改进。\n", + "2. **Planner**: 确定完成任务所需的相关信息。\n", + "3. **Engineer**: 使用Planner定义的计划编写代码。\n", + "4. **Executor**: 执行Engineer编写的代码。\n", + "5. **Writer**: 撰写报告\n", + "接下来我们逐个定义上述Agengt。" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "bd7befab-9487-4c50-8eca-1e2e30dbf7d6", + "metadata": { + "height": 30 + }, + "outputs": [], + "source": [ + "import autogen" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "3258cb72-cb74-4eab-a387-ee409baf4947", + "metadata": { + "height": 149 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[autogen.oai.client: 06-14 21:04:14] {129} WARNING - The API key specified is not a valid OpenAI format; it won't work with the OpenAI-hosted model.\n" + ] + } + ], + "source": [ + "user_proxy = autogen.ConversableAgent(\n", + " name=\"Admin\", # 管理员\n", + " system_message=\"Give the task, and send \"# 给出任务，并发送指令给作者，从而完善博客文章。\n", + " \"instructions to writer to refine the blog post.\",\n", + " code_execution_config=False,\n", + " llm_config=llm_config,\n", + " human_input_mode=\"ALWAYS\", # 将人类输入模式设置为 ALWAYS 因此每次轮到Admin Agent说话时，始终要求人类输入\n", + ") # 如果跳过输入，Admin Agent会发送指示给Writer Agengt来改进博文" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "0832b856-f13d-4e16-b61f-69eb23e0ae71", + "metadata": { + "height": 285 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[autogen.oai.client: 06-14 21:04:14] {129} WARNING - The API key specified is not a valid OpenAI format; it won't work with the OpenAI-hosted model.\n" + ] + } + ], + "source": [ + "planner = autogen.ConversableAgent(\n", + " name=\"Planner\", # 规划者\n", + " system_message=\"Given a task, please determine \" # 给定一项任务，请确定完成该任务需要哪些信息。\n", + " \"what information is needed to complete the task. \"# 请注意，所有信息都将使用Python代码检索。\n", + " \"Please note that the information will all be retrieved using\"# 请只建议可以使用Python代码检索的信息。\n", + " \" Python code. Please only suggest information that can be \"# 在其他人完成每一步后，检查进度并指示剩余步骤。\n", + " \"retrieved using Python code. \" # 如果某一步失败，尝试解决。\n", + " \"After each step is done by others, check the progress and \"\n", + " \"instruct the remaining steps. If a step fails, try to \"\n", + " \"workaround\",\n", + " description=\"Planner. Given a task, determine what \"# 规划者。给定一项任务，确定完成该任务需要哪些信息。\n", + " \"information is needed to complete the task. \"# 在其他人完成每一步后，检查进度并指示剩余步骤\n", + " \"After each step is done by others, check the progress and \"\n", + " \"instruct the remaining steps\",\n", + " llm_config=llm_config,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "2427f55d-fb7b-4f3c-85d4-dcd35547b397", + "metadata": { + "height": 115 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[autogen.oai.client: 06-14 21:04:14] {129} WARNING - The API key specified is not a valid OpenAI format; it won't work with the OpenAI-hosted model.\n" + ] + } + ], + "source": [ + "engineer = autogen.AssistantAgent(\n", + " name=\"Engineer\", # 工程师 \n", + " llm_config=llm_config,\n", + " description=\"An engineer that writes code based on the plan \"# 基于规划者的计划写代码。\n", + " \"provided by the planner.\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "040ac21f-b4bf-4bd6-ac58-fdb2c8f8de14", + "metadata": { + "height": 200 + }, + "outputs": [], + "source": [ + "executor = autogen.ConversableAgent(\n", + " name=\"Executor\", # 执行者\n", + " system_message=\"Execute the code written by the \"# 执行工程师写的代码并且返回结果。\n", + " \"engineer and report the result.\",\n", + " human_input_mode=\"NEVER\",\n", + " code_execution_config={\n", + " \"last_n_messages\": 3, # 能看到的执行代码结果的消息数\n", + " \"work_dir\": \"coding\", # 代码保存路径\n", + " \"use_docker\": False, # 是否使用docker执行代码\n", + " },\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "d6367fb4-a81b-411c-a339-8dd3d1d41483", + "metadata": { + "height": 200 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[autogen.oai.client: 06-14 21:04:14] {129} WARNING - The API key specified is not a valid OpenAI format; it won't work with the OpenAI-hosted model.\n" + ] + } + ], + "source": [ + "writer = autogen.ConversableAgent(\n", + " name=\"Writer\", # 作家/写作者\n", + " llm_config=llm_config,\n", + " system_message=\"Writer.\"\n", + " \"Please write blogs in markdown format (with relevant titles)\" # 请用markdown格式写博客(带有相关标题)，并将内容放在伪``` `md```代码块中。\n", + " \" and put the content in pseudo ```md``` code block. \" # 你从管理员那里得到反馈并改进你的博客。\n", + " \"You take feedback from the admin and refine your blog.\",\n", + " description=\"Writer.\" # 作家/写作者\n", + " \"Write blogs based on the code execution results and take \" # 根据代码执行结果编写博客，并根据管理员的反馈完善博客\n", + " \"feedback from the admin to refine the blog.\"\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "a2ea86b5", + "metadata": {}, + "source": [ + "## 定义群聊\n", + "将之前定义好的Agent拉进群聊。" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "cbf3c4b7-d4b8-4f97-8a25-e23107904ad5", + "metadata": { + "height": 98 + }, + "outputs": [], + "source": [ + "groupchat = autogen.GroupChat(\n", + " agents=[user_proxy, engineer, writer, executor, planner], # agents为参与群聊的Agent，接收格式为List[Agent]\n", + " messages=[], \n", + " max_round=10, \n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "034995b9", + "metadata": {}, + "source": [ + "定义群聊管理器，我们要通过Admin对群聊管理器提出任务从而开始对话，同样的群聊管理器也需要配置 `llm_config`。" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "bfcabc20-9316-45b7-852d-42e14550a956", + "metadata": { + "height": 81 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[autogen.oai.client: 06-14 21:04:14] {129} WARNING - The API key specified is not a valid OpenAI format; it won't work with the OpenAI-hosted model.\n" + ] + } + ], + "source": [ + "manager = autogen.GroupChatManager(\n", + " groupchat=groupchat, llm_config=llm_config\n", + ")\n" + ] + }, + { + "cell_type": "markdown", + "id": "b51eaffa", + "metadata": {}, + "source": [ + "## 开始群聊" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "a9899e8f-2971-487c-9d0e-932c36b3b75a", + "metadata": { + "height": 81 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[33mAdmin\u001b[0m (to chat_manager):\n", + "\n", + "写一篇关于过去一个月Nvidia股价表现的博客。今天是 2024-04-23。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mPlanner\u001b[0m (to chat_manager):\n", + "\n", + "为了完成关于过去一个月NVIDIA股价表现的博客，你需要做以下几个步骤：\n", + "\n", + "1. **获取股票数据**：\n", + " - 你需要从2024年3月23日到2024年4月22日的NVIDIA股票数据。\n", + " - 数据应包括至少每日的开盘价、最高价、最低价和收盘价。\n", + "\n", + "2. **分析股票表现**：\n", + " - 比较3月23日和4月22日的收盘价，评估股价变化。\n", + " - 计算此期间的股价最高值和最低值。\n", + " - 可以计算平均收盘价或其他相关的统计数据。\n", + "\n", + "3. **撰写博客文章**：\n", + " - 根据收集的数据分析NVIDIA过去一个月的股价表现。\n", + " - 提供量化数据支持你的分析，如价格变动、最高点和最低点。\n", + " - 讨论可能影响股价变动的外部因素，如市场新闻或技术创新。\n", + "\n", + "### 第一步：获取股票数据\n", + "为了获取股票数据，你可以使用Python中的几种金融数据库接口，如 `yfinance`。可以通过下面的Python代码来获取NVIDIA（股票代码为\"NVDA\"）的股票数据：\n", + "\n", + "```python\n", + "import yfinance as yf\n", + "import pandas as pd\n", + "\n", + "# 设置日期范围\n", + "start_date = \"2024-03-23\"\n", + "end_date = \"2024-04-22\"\n", + "\n", + "# 下载NVDA股票数据\n", + "nvda_data = yf.download('NVDA', start=start_date, end=end_date)\n", + "\n", + "# 显示数据\n", + "print(nvda_data)\n", + "```\n", + "\n", + "该代码段将输出NVIDIA股票的每日开盘价、最高价、最低价和收盘价等数据。\n", + "\n", + "#### 接下来的步骤：\n", + "- 执行上述Python代码来获取NVIDIA股票数据。\n", + "- 检查数据是否已正确获取并呈现所需日期范围内的数据。如果成功，请告诉我以便继续进行下一步分析。如果失败，请描述遇到的问题，以便我可以帮助找到解决方案。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is python)...\u001b[0m\n", + "\u001b[33mExecutor\u001b[0m (to chat_manager):\n", + "\n", + "exitcode: 0 (execution succeeded)\n", + "Code output: \n", + " Open High Low Close Adj Close Volume\n", + "Date \n", + "2024-03-25 93.941002 96.765999 93.510002 95.001999 94.994194 552136000\n", + "2024-03-26 95.850998 96.375000 92.501999 92.560997 92.553398 513648000\n", + "2024-03-27 93.112000 93.239998 89.123001 90.250000 90.242584 586067000\n", + "2024-03-28 90.000000 91.300003 89.193001 90.356003 90.348579 435212000\n", + "2024-04-01 90.299004 92.224998 89.204002 90.362999 90.355576 452441000\n", + "2024-04-02 88.447998 90.094002 87.620003 89.452003 89.444656 433064000\n", + "2024-04-03 88.484001 90.374001 88.400002 88.963997 88.956688 370067000\n", + "2024-04-04 90.405998 90.634003 85.879997 85.904999 85.897942 434965000\n", + "2024-04-05 86.865997 88.481003 85.926003 88.008003 88.000778 399678000\n", + "2024-04-08 88.699997 88.830002 86.732002 87.133003 87.125847 283220000\n", + "2024-04-09 87.442001 87.635002 83.022003 85.353996 85.346985 503547000\n", + "2024-04-10 83.926003 87.400002 83.709000 87.039001 87.031853 431929000\n", + "2024-04-11 87.419998 90.738998 86.926003 90.615997 90.608551 431637000\n", + "2024-04-12 89.698997 90.175003 87.529999 88.185997 88.178757 426805000\n", + "2024-04-15 89.098000 90.612999 85.929001 86.000999 85.993935 443077000\n", + "2024-04-16 86.432999 88.117996 86.064003 87.415001 87.407822 370453000\n", + "2024-04-17 88.339996 88.775002 83.949997 84.035004 84.028099 495400000\n", + "2024-04-18 84.970001 86.190002 82.402000 84.670998 84.664040 447260000\n", + "2024-04-19 83.150002 84.323997 75.606003 76.199997 76.193741 875198000\n", + "\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mWriter\u001b[0m (to chat_manager):\n", + "\n", + "根据您执行的Python代码获取的数据，现在我们已经有了NVIDIA在指定日期范围内（2024年3月25日至2024年4月19日）的股票价格数据。下一步，我们将根据这些数据来分析NVIDIA股价的表现。\n", + "\n", + "## 基本股价变动情况\n", + "\n", + "首先，我们观察到在这段时间内，NVIDIA的股票经历了一些较大的波动：\n", + "\n", + "- **开盘价**：2024年3月25日的开盘价为93.94美元，而到了2024年4月19日，开盘价降至83.15美元。\n", + "- **最高价**：此期间的最高价出现在2024年3月26日，为96.38美元。\n", + "- **最低价**：而最低价出现在2024年4月19日，为75.61美元。\n", + "- **收盘价**：2024年3月25日的收盘价为95.00美元，相比之下，4月19日的收盘价下降至76.20美元。\n", + "\n", + "这些数据反映了股价的整体下滑趋势，并伴随着显著波动。下面我们来深入分析与此相关的原因。\n", + "\n", + "## 深入股价分析\n", + "\n", + "### 价格走势\n", + "从收集的数据可以看到，NVIDIA的股价在这一个月里具有明显的下跌趋势。尽管有几天股价有所回升，如2024年4月11日收盘价达到了90.62美元，但整体趋势是下降的。\n", + "\n", + "### 交易量变化\n", + "- 在交易量方面，我们注意到最大交易量出现在4月19日，达到了875,198,000股。这一天也记录了最低的股价，表明可能有大量卖出操作。\n", + "\n", + "### 可能的影响因素\n", + "- 在考虑股价变动的外部因素时，可能包括市场整体的经济情况、公司业绩报告的影响、行业新闻（如竞争对手的新产品发布），或者是全球电子市场需求的变化等。\n", + "\n", + "## 结论\n", + "通过上述分析，我们可以看出NVIDIA在过去一个月内的股票价格表现了下跌趋势，这可能受到了多种因素的影响。投资者需要密切关注市场动态以及公司未来的发展方向，做出相应的投资决策。\n", + "\n", + "请让我知道您对以上分析的看法，或者是否需要进一步探讨其他相关的内容。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mAdmin\u001b[0m (to chat_manager):\n", + "\n", + "很好，不用了\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> NO HUMAN INPUT RECEIVED.\u001b[0m\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mAdmin\u001b[0m (to chat_manager):\n", + "\n", + "好的！如果您有其他问题或需要进一步的帮助，请随时告诉我。祝您拥有美好的一天！\n", + "\n", + "--------------------------------------------------------------------------------\n" + ] + } + ], + "source": [ + "groupchat_result = user_proxy.initiate_chat(\n", + " manager,\n", + " message=task,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "ba5d14b6", + "metadata": {}, + "source": [ + "## 添加说话人选择策略" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "c17e5a76-3c40-4e2a-b8f1-378f901f5b74", + "metadata": { + "height": 965 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[autogen.oai.client: 06-14 21:05:55] {129} WARNING - The API key specified is not a valid OpenAI format; it won't work with the OpenAI-hosted model.\n", + "[autogen.oai.client: 06-14 21:05:55] {129} WARNING - The API key specified is not a valid OpenAI format; it won't work with the OpenAI-hosted model.\n", + "[autogen.oai.client: 06-14 21:05:56] {129} WARNING - The API key specified is not a valid OpenAI format; it won't work with the OpenAI-hosted model.\n", + "[autogen.oai.client: 06-14 21:05:56] {129} WARNING - The API key specified is not a valid OpenAI format; it won't work with the OpenAI-hosted model.\n" + ] + } + ], + "source": [ + "user_proxy = autogen.ConversableAgent(\n", + " name=\"Admin\",\n", + " system_message=\"Give the task, and send \" # 给出任务，并发送指令给作者，从而完善博客文章。\n", + " \"instructions to writer to refine the blog post.\",\n", + " code_execution_config=False,\n", + " llm_config=llm_config,\n", + " human_input_mode=\"ALWAYS\",\n", + ")\n", + "\n", + "planner = autogen.ConversableAgent(\n", + " name=\"Planner\",\n", + " system_message=\"Given a task, please determine \" # 给定一项任务，请确定完成该任务需要哪些信息。\n", + " \"what information is needed to complete the task. \" # 请注意，所有信息都将使用Python代码检索。\n", + " \"Please note that the information will all be retrieved using\" # 请只建议可以使用Python代码检索的信息。\n", + " \" Python code. Please only suggest information that can be \" # 在其他人完成每一步后，检查进度并指示剩余步骤。\n", + " \"retrieved using Python code. \"\n", + " \"After each step is done by others, check the progress and \" # 如果某一步失败，尝试解决。\n", + " \"instruct the remaining steps. If a step fails, try to \"\n", + " \"workaround\",\n", + " description=\"Given a task, determine what \" # 规划者。给定一项任务，确定完成该任务需要哪些信息。\n", + " \"information is needed to complete the task. \" # 在其他人完成每一步后，检查进度并指示剩余步骤\n", + " \"After each step is done by others, check the progress and \"\n", + " \"instruct the remaining steps\",\n", + " llm_config=llm_config,\n", + ")\n", + "\n", + "engineer = autogen.AssistantAgent(\n", + " name=\"Engineer\",\n", + " llm_config=llm_config,\n", + " description=\"Write code based on the plan \" # 基于规划者的计划写代码。\n", + " \"provided by the planner.\",\n", + ")\n", + "\n", + "writer = autogen.ConversableAgent(\n", + " name=\"Writer\",\n", + " llm_config=llm_config,\n", + " system_message=\"Writer. \"\n", + " \"Please write blogs in markdown format (with relevant titles)\" # 请用markdown格式写博客(带有相关标题)，并将内容放在伪``` `md```代码块中。\n", + " \" and put the content in pseudo ```md``` code block. \" \n", + " \"You take feedback from the admin and refine your blog.\", # 你从管理员那里得到反馈并改进你的博客。\n", + " description=\"After all the info is available, \"\n", + " \"write blogs based on the code execution results and take \" # 根据代码执行结果编写博客，并根据管理员的反馈完善博客\n", + " \"feedback from the admin to refine the blog. \",\n", + ")\n", + "\n", + "executor = autogen.ConversableAgent(\n", + " name=\"Executor\",\n", + " description=\"Execute the code written by the \" # 执行工程师编写的代码并报告结果。\n", + " \"engineer and report the result.\",\n", + " human_input_mode=\"NEVER\",\n", + " code_execution_config={\n", + " \"last_n_messages\": 3,\n", + " \"work_dir\": \"coding\",\n", + " \"use_docker\": False,\n", + " },\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "ac3bbca0", + "metadata": {}, + "source": [ + "我们上次定义群聊可能会出现发言混乱的情况，我们可以通过添加`allowed_or_disallowed_speaker_transitions`与`speaker_transitions_type`参数来对群聊进行额外的约束，前者可以指定Agent的消息能够/不能够被哪些Agent看到，具体是能够或不能够则可以通过设置`speaker_transitions_type`为`allowed`或`disallowed`来控制。" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "d1ea0a1b-78f9-4be3-9479-228d6e679268", + "metadata": { + "height": 234 + }, + "outputs": [], + "source": [ + "groupchat = autogen.GroupChat(\n", + " agents=[user_proxy, engineer, writer, executor, planner],\n", + " messages=[],\n", + " max_round=10,\n", + " allowed_or_disallowed_speaker_transitions={\n", + " user_proxy: [engineer, writer, executor, planner],\n", + " engineer: [user_proxy, executor],\n", + " writer: [user_proxy, planner],\n", + " executor: [user_proxy, engineer, planner],\n", + " planner: [user_proxy, engineer, writer],\n", + " },\n", + " speaker_transitions_type=\"allowed\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "a62255bb-644f-4af6-a640-08297e55de45", + "metadata": { + "height": 149 + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[autogen.oai.client: 06-14 21:05:56] {129} WARNING - The API key specified is not a valid OpenAI format; it won't work with the OpenAI-hosted model.\n", + "\u001b[33mAdmin\u001b[0m (to chat_manager):\n", + "\n", + "写一篇关于过去一个月Nvidia股价表现的博客。今天是 2024-04-23。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mPlanner\u001b[0m (to chat_manager):\n", + "\n", + "为了完成关于过去一个月NVIDIA股价表现的博客，你需要做以下几个步骤：\n", + "\n", + "1. **获取股票数据**：\n", + " - 你需要从2024年3月23日到2024年4月22日的NVIDIA股票数据。\n", + " - 数据应包括至少每日的开盘价、最高价、最低价和收盘价。\n", + "\n", + "2. **分析股票表现**：\n", + " - 比较3月23日和4月22日的收盘价，评估股价变化。\n", + " - 计算此期间的股价最高值和最低值。\n", + " - 可以计算平均收盘价或其他相关的统计数据。\n", + "\n", + "3. **撰写博客文章**：\n", + " - 根据收集的数据分析NVIDIA过去一个月的股价表现。\n", + " - 提供量化数据支持你的分析，如价格变动、最高点和最低点。\n", + " - 讨论可能影响股价变动的外部因素，如市场新闻或技术创新。\n", + "\n", + "### 第一步：获取股票数据\n", + "为了获取股票数据，你可以使用Python中的几种金融数据库接口，如 `yfinance`。可以通过下面的Python代码来获取NVIDIA（股票代码为\"NVDA\"）的股票数据：\n", + "\n", + "```python\n", + "import yfinance as yf\n", + "import pandas as pd\n", + "\n", + "# 设置日期范围\n", + "start_date = \"2024-03-23\"\n", + "end_date = \"2024-04-22\"\n", + "\n", + "# 下载NVDA股票数据\n", + "nvda_data = yf.download('NVDA', start=start_date, end=end_date)\n", + "\n", + "# 显示数据\n", + "print(nvda_data)\n", + "```\n", + "\n", + "该代码段将输出NVIDIA股票的每日开盘价、最高价、最低价和收盘价等数据。\n", + "\n", + "#### 接下来的步骤：\n", + "- 执行上述Python代码来获取NVIDIA股票数据。\n", + "- 检查数据是否已正确获取并呈现所需日期范围内的数据。如果成功，请告诉我以便继续进行下一步分析。如果失败，请描述遇到的问题，以便我可以帮助找到解决方案。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mEngineer\u001b[0m (to chat_manager):\n", + "\n", + "请使用以下 Python 代码来获取所需的 Nvidia 股票数据。这段代码将帮助我们下载2024年3月23日到2024年4月22日之间的股价数据。\n", + "\n", + "```python\n", + "# filename: fetch_nvda_stock_data.py\n", + "import yfinance as yf\n", + "\n", + "# 设置日期范围\n", + "start_date = '2024-03-23'\n", + "end_date = '2024-04-22'\n", + "\n", + "# 下载NVDA股票数据\n", + "nvda_data = yf.download('NVDA', start=start_date, end=end_art_date)\n", + "\n", + "# 显示数据\n", + "print(nvda_data)\n", + "```\n", + "\n", + "请确保您的环境中已安装 `yfinance` 库。如果未安装，可以使用 `pip install yfinance` 来安装。然后，运行上述脚本并将结果返回给我，以便继续下一步分析。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is python)...\u001b[0m\n", + "\u001b[33mExecutor\u001b[0m (to chat_manager):\n", + "\n", + "exitcode: 1 (execution failed)\n", + "Code output: \n", + "Traceback (most recent call last):\n", + " File \"fetch_nvda_stock_data.py\", line 9, in \n", + " nvda_data = yf.download('NVDA', start=start_date, end=end_art_date)\n", + "NameError: name 'end_art_date' is not defined. Did you mean: 'start_date'?\n", + "\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mEngineer\u001b[0m (to chat_manager):\n", + "\n", + "看起来代码中存在一个小错误。我错误地引用了一个不存在的变量名。让我们修正这个错误并重新执行正确的代码。\n", + "\n", + "请使用以下正确的 Python 代码来获取所需的 Nvidia 股票数据：\n", + "\n", + "```python\n", + "# filename: fetch_nvda_stock_data.py\n", + "import yfinance as yf\n", + "\n", + "# 设置日期范围\n", + "start_date = '2024-03-23'\n", + "end_date = '2024-04-22'\n", + "\n", + "# 下载NVDA股票数据\n", + "nvda_data = yf.download('NVDA', start=start_date, end=end_date)\n", + "\n", + "# 显示数据\n", + "print(nvda_data)\n", + "```\n", + "\n", + "运行这段修改后的脚本。这次应该能正确获取 NVIDIA 的股票数据。请确保 `yfinance` 已正确安装，并再次运行该脚本，然后将结果返回给我，以便我们继续分析。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is python)...\u001b[0m\n", + "\u001b[33mExecutor\u001b[0m (to chat_manager):\n", + "\n", + "exitcode: 0 (execution succeeded)\n", + "Code output: \n", + " Open High Low Close Adj Close Volume\n", + "Date \n", + "2024-03-25 93.941002 96.765999 93.510002 95.001999 94.994194 552136000\n", + "2024-03-26 95.850998 96.375000 92.501999 92.560997 92.553398 513648000\n", + "2024-03-27 93.112000 93.239998 89.123001 90.250000 90.242584 586067000\n", + "2024-03-28 90.000000 91.300003 89.193001 90.356003 90.348579 435212000\n", + "2024-04-01 90.299004 92.224998 89.204002 90.362999 90.355576 452441000\n", + "2024-04-02 88.447998 90.094002 87.620003 89.452003 89.444656 433064000\n", + "2024-04-03 88.484001 90.374001 88.400002 88.963997 88.956688 370067000\n", + "2024-04-04 90.405998 90.634003 85.879997 85.904999 85.897942 434965000\n", + "2024-04-05 86.865997 88.481003 85.926003 88.008003 88.000778 399678000\n", + "2024-04-08 88.699997 88.830002 86.732002 87.133003 87.125847 283220000\n", + "2024-04-09 87.442001 87.635002 83.022003 85.353996 85.346985 503547000\n", + "2024-04-10 83.926003 87.400002 83.709000 87.039001 87.031853 431929000\n", + "2024-04-11 87.419998 90.738998 86.926003 90.615997 90.608551 431637000\n", + "2024-04-12 89.698997 90.175003 87.529999 88.185997 88.178757 426805000\n", + "2024-04-15 89.098000 90.612999 85.929001 86.000999 85.993935 443077000\n", + "2024-04-16 86.432999 88.117996 86.064003 87.415001 87.407822 370453000\n", + "2024-04-17 88.339996 88.775002 83.949997 84.035004 84.028099 495400000\n", + "2024-04-18 84.970001 86.190002 82.402000 84.670998 84.664040 447260000\n", + "2024-04-19 83.150002 84.323997 75.606003 76.199997 76.193741 875198000\n", + "\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> USING AUTO REPLY...\u001b[0m\n", + "\u001b[33mPlanner\u001b[0m (to chat_manager):\n", + "\n", + "我们已成功获取到NVIDIA股票从2024年3月23日到2024年4月22日的每日开盘价、最高价、最低价和收盘价数据。现在我们可以进行数据分析。\n", + "\n", + "### 第二步：分析股票表现\n", + "通过这些数据，我们将完成以下分析：\n", + "1. 计算此期间的股价最高值和最低值。\n", + "2. 比较此期间内的起始收盘价和结束收盘价，计算价格变动。\n", + "3. 计算及评估期间内的平均收盘价。\n", + "\n", + "#### 执行以下Python代码进行分析：\n", + "\n", + "```python\n", + "# 最高价和最低价\n", + "max_price = nvda_data['High'].max()\n", + "min_price = nvda_data['Low'].min()\n", + "\n", + "# 价格变动\n", + "price_change = nvda_data['Close'].iloc[-1] - nvda_data['Close'].iloc[0]\n", + "\n", + "# 平均收盘价\n", + "average_close = nvda_data['Close'].mean()\n", + "\n", + "print(f\"最高价: {max_price}\")\n", + "print(f\"最低价: {min_price}\")\n", + "print(f\"价格变动: {price_change}（从 {nvda_data['Close'].iloc[0]} 到 {nvda_data['Close'].iloc[-1]}）\")\n", + "print(f\"平均收盘价: {average_close}\")\n", + "```\n", + "\n", + "#### 接下来的步骤：\n", + "请执行上述Python代码来进行数据分析，并将结果返回给我，这样我们就可以在此基础上撰写博客文章了。如果遇到任何问题，请及时反馈。\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mEngineer\u001b[0m (to chat_manager):\n", + "\n", + "这一步需要执行上述提供的Python代码来分析NVIDIA股票的表现，请将该段代码放入Python环墯中执行，并把执行结果返回给我。这将帮助我们得到股票的最高价、最低价、价格变动以及平均收盘价，为撰写博客文章提供数据支持。执行完毕后，请将结果详细告诉我。\n", + "TERMINATE\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[31m\n", + ">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is python)...\u001b[0m\n", + "\u001b[33mExecutor\u001b[0m (to chat_manager):\n", + "\n", + "exitcode: 1 (execution failed)\n", + "Code output: \n", + "Traceback (most recent call last):\n", + " File \"\", line 2, in \n", + " max_price = nvda_data['High'].max()\n", + "NameError: name 'nvda_data' is not defined\n", + "\n", + "\n", + "--------------------------------------------------------------------------------\n", + "\u001b[33mEngineer\u001b[0m (to chat_manager):\n", + "\n", + "看起来在执行代码时遇到了一个错误，因为 `nvda_data` 变量未定义。这是因为我未能提醒你将导入的数据保存为 `nvda_data` 变量，或者是因为之前的脚本没有把这个变量存储在一个可以持续访问的形式中。我们需要修正这一点并重新执行分析。\n", + "\n", + "请先确保你已经将数据正确地加载到变量 `nv,da_data` 中，然后执行以下代码进行股票的数据分析：\n", + "\n", + "```python\n", + "# filename: analyze_nvda_stock_data.py\n", + "import pandas as pd\n", + "\n", + "# 示例数据加载，实际操作时请确保数据已通过 yfinance 加载\n", + "data = {\n", + " 'Open': [93.94, 95.85, 86.43, 84.97, 83.15],\n", + " 'High': [96.76, 96.37, 88.11, 86.19, 84.32],\n", + " 'Low': [93.51, 92.50, 86.06, 82.40, 75.60],\n", + " 'Close': [95.00, 92.56, 87.41, 84.67, 76.19]\n", + "}\n", + "dates = pd.date_range(start=\"2024-03-25\", periods=len(data['Open']), freq='B')\n", + "nvda_data = pd.DataFrame(data, index=dates)\n", + "\n", + "# 最高价和最低价\n", + "max_price = nvda_data['High'].max()\n", + "min_price = nvda_data['Low'].min()\n", + "\n", + "# 价格变动\n", + "price_change = nvda_data['Close'].iloc[-1] - nvda_data['Close'].iloc[0]\n", + "\n", + "# 平均收盘价\n", + "average_close = nvda_data['Close'].mean()\n", + "\n", + "print(f\"最高价: {max_price}\")\n", + "print(f\"最低价: {min_price}\")\n", + "print(f\"价格变动: {price_change}（从 {nvda_data['Close'].iloc[0]} 到 {nvda_data['Close'].iloc[-1]}）\")\n", + "print(f\"平均收盘价: {average_close}\")\n", + "```\n", + "\n", + "在执行这段代码之前，请确认在你的脚本中已经加载了股票数据，或使用内置的示例数据进行测试。执行后，请将结果告知我，以便继续进行博客文章的撰写。\n", + "\n", + "--------------------------------------------------------------------------------\n" + ] + } + ], + "source": [ + "manager = autogen.GroupChatManager(\n", + " groupchat=groupchat, llm_config=llm_config\n", + ")\n", + "\n", + "groupchat_result = user_proxy.initiate_chat(\n", + " manager,\n", + " message=task,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "e738fd8b", + "metadata": {}, + "source": [ + "**注意**: 你可能会体验到智能体之间略有不同的交互。工程师Agent可能编写了不正确的代码，执行Agent将报告并发回更正。这个过程可能会经过多轮。" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": 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introduction.md" @@ -0,0 +1,59 @@ +# 第一章：简介 + + + +## 概述 + +>*"The whole is greater than the sum of its parts."* +> +>— Aristotle + +`AutoGen` 是一个多智能体对话框架，专为快速创建具有不同角色、个性和能力的多个代理而设计。通过这一框架，您可以使用不同的 `AI` 智能体设计模式来实现复杂的 `AI` 应用。 + + + +## 主要特点 + +##### 可扩展性与可组合性 + +`AutoGen` 具有高度的可扩展性和可组合性。您可以通过自定义组件扩展简单的智能体，并创建组合这些智能体的工作流程，从而驱动更复杂的代理。这种设计确保了系统的模块化和易于维护。 + +##### 多智能体协作 + +在 `AutoGen` 中，智能体不仅可以模拟现实世界和抽象实体（如人类和算法），还能够简化复杂工作流程的实施。智能体之间的协作是该框架的核心，可以让您实现诸如研究员、数据收集员、联合编写员和执行员等多种角色之间的高效互动。 + +##### 社区支持 + +- `AutoGen` 由一个充满活力的研究人员和工程师社区共同开发和维护。 +- 社区融合了多智能体系统的最新研究成果，并已被应用于许多实际场景中，包括广告、`AI` 员工、博客写作、区块链、智能客服、网络安全、数据分析、辩论、教育、金融、游戏、法律咨询、研究、机器人、销售与营销、社会模拟、软件工程、软件安全、供应链管理、培训数据生成和 `YouTube` 服务等。 + +##### 智能体设计模式 + +`AutoGen` 提供了多种基本的智能体设计模式，包括多智能体协作、反思、工具使用、代码生成和规划等。这些设计模式可以作为构建模块，帮助你创建应用程序并解决非常复杂的任务。 + +##### 模块化与易于维护 + +通过模块化的实现方式，`AutoGen` 确保了系统的易于维护性。您可以在智能体中自由开启或关闭每个组件，并根据具体应用的需求进行定制。 + +##### 角色分配与对话推进 + +在 `AutoGen` 中，智能体可以被分配特定的角色，并参与到对话或彼此聊天中。对话是智能体之间消息交换的序列，通过这些对话可以推进任务的进展。 + + + +## 组件驱动 + +智能体可以由以下组件驱动： + +- 大语言模型（如 `GPT-4`） +- 代码执行器（如 `IPython` 内核） +- 人类输入 +- 其他可定制的组件 + +内置的 `ConversableAgent` 支持语言模型、代码执行器、函数和工具执行器等组件，并保持人类参与的能力。对于开发者，可以通过 `registered_reply` 添加额外的组件到智能体中。 + + + +## 结论 + +`AutoGen` 是一个功能强大且易于使用的多智能体对话框架，其高度的可扩展性、可组合性和社区支持使其成为实现复杂 `AI` 应用的理想选择。无论是初学者还是高级用户，都可以通过 `AutoGen` 快速创建和管理智能体，解决广泛存在的现实世界问题。 From 8e13c680a598adc4672aa1551c1b6811980a294c Mon Sep 17 00:00:00 2001 From: Tsumugii24 <2792474059@qq.com> Date: Wed, 3 Jul 2024 15:47:36 +0800 Subject: [PATCH 18/24] update conclusion for autogen --- .../8.\346\200\273\347\273\223 conclusion.md" | 24 +++++++++++++++++++ 1 file changed, 24 insertions(+) create mode 100644 "content/AI Agentic Design Patterns with AutoGen/8.\346\200\273\347\273\223 conclusion.md" diff --git "a/content/AI Agentic Design Patterns with AutoGen/8.\346\200\273\347\273\223 conclusion.md" "b/content/AI Agentic Design Patterns with AutoGen/8.\346\200\273\347\273\223 conclusion.md" new file mode 100644 index 00000000..022f89a4 --- /dev/null +++ "b/content/AI Agentic Design Patterns with AutoGen/8.\346\200\273\347\273\223 conclusion.md" @@ -0,0 +1,24 @@ +# 第八章 总结 + +本次基于大语言模型的多智能体课程涵盖了一系列基于 `AutoGen` 框架的应用实践，你学习到了一些基本的智能体设计模式——包括多智能体协作、反思、工具使用、代码生成和规划等。这些设计模式可以作为构建模块，帮助你在未来创建更有想象力的应用并解决更加复杂的任务。 + + + +### 📚 课程回顾 + +本课程通过多个应用示例的引入，深入浅出的在每个示例中介绍了 `AutoGen` 框架下的智能体设计模式。 + +- 多智能体对话和相声 `multi-agent-conversation` +- 顺序聊天和客户引导 `sequential-chats` +- 反思与博客写作 `Reflection_and_Blogpost_Writing` +- 工具使用和国际象棋 `tool-use` +- 代码与金融分析 `coding_and_financial_analysis` +- 规划与股票报告生成 `planning_and_stock_report_Generation` + +复杂度和难度都逐渐升级，直到最后亲手构建出非常有意思的应用。 + + + +### 💪🏻 出发！去探索新世界吧~ + +实践是掌握真知的必经之路。开始构建令人激动的多智能体框架应用构建吧~ \ No newline at end of file From f2630f5a786eedc7efa44ddaf39e63aa3fe6fa2b Mon Sep 17 00:00:00 2001 From: Tsumugii24 <2792474059@qq.com> Date: Mon, 8 Jul 2024 02:24:18 +0800 Subject: [PATCH 19/24] update conclusion for autogen --- .../8.\346\200\273\347\273\223 conclusion.md" | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git "a/content/AI Agentic Design Patterns with AutoGen/8.\346\200\273\347\273\223 conclusion.md" "b/content/AI Agentic Design Patterns with AutoGen/8.\346\200\273\347\273\223 conclusion.md" index 022f89a4..57b397e1 100644 --- "a/content/AI Agentic Design Patterns with AutoGen/8.\346\200\273\347\273\223 conclusion.md" +++ "b/content/AI Agentic Design Patterns with AutoGen/8.\346\200\273\347\273\223 conclusion.md" @@ -1,12 +1,12 @@ # 第八章 总结 -本次基于大语言模型的多智能体课程涵盖了一系列基于 `AutoGen` 框架的应用实践，你学习到了一些基本的智能体设计模式——包括多智能体协作、反思、工具使用、代码生成和规划等。这些设计模式可以作为构建模块，帮助你在未来创建更有想象力的应用并解决更加复杂的任务。 +本次基于大语言模型的多智能体课程涵盖了一系列基于 `AutoGen` 框架的应用实践，通过学习可以掌握一些基本的智能体设计模式——包括多智能体协作、反思、工具使用、代码生成和规划等。这些设计模式可以作为构建模块，帮助你在未来创建更有想象力的应用并解决更加复杂的任务。 ### 📚 课程回顾 -本课程通过多个应用示例的引入，深入浅出的在每个示例中介绍了 `AutoGen` 框架下的智能体设计模式。 +本课程通过多个应用示例的引入，深入浅出地在每个示例中介绍了 `AutoGen` 框架下的智能体设计模式。 - 多智能体对话和相声 `multi-agent-conversation` - 顺序聊天和客户引导 `sequential-chats` @@ -15,10 +15,10 @@ - 代码与金融分析 `coding_and_financial_analysis` - 规划与股票报告生成 `planning_and_stock_report_Generation` -复杂度和难度都逐渐升级，直到最后亲手构建出非常有意思的应用。 +随着课程的推进，复杂度和难度都逐渐升级，直到最后亲手构建出非常有意思的应用。 ### 💪🏻 出发！去探索新世界吧~ -实践是掌握真知的必经之路。开始构建令人激动的多智能体框架应用构建吧~ \ No newline at end of file +实践是掌握知识的必经之路。开始构建令人激动的基于多智能体框架应用开发，构建属于你自己的产品吧~ \ No newline at end of file From 327c49e02775b457105dc5c5fee716388a7503e4 Mon Sep 17 00:00:00 2001 From: Tsumugii24 <2792474059@qq.com> Date: Mon, 8 Jul 2024 02:37:36 +0800 Subject: [PATCH 20/24] update introduction for autogen --- ....\347\256\200\344\273\213 introduction.md" | 24 +++++++++++++------ 1 file changed, 17 insertions(+), 7 deletions(-) diff --git "a/content/AI Agentic Design Patterns with AutoGen/1.\347\256\200\344\273\213 introduction.md" "b/content/AI Agentic Design Patterns with AutoGen/1.\347\256\200\344\273\213 introduction.md" index 198e42b9..3d7600e1 100644 --- "a/content/AI Agentic Design Patterns with AutoGen/1.\347\256\200\344\273\213 introduction.md" +++ "b/content/AI Agentic Design Patterns with AutoGen/1.\347\256\200\344\273\213 introduction.md" @@ -8,7 +8,15 @@ > >— Aristotle -`AutoGen` 是一个多智能体对话框架，专为快速创建具有不同角色、个性和能力的多个代理而设计。通过这一框架，您可以使用不同的 `AI` 智能体设计模式来实现复杂的 `AI` 应用。 +`AutoGen` 是一个多智能体对话框架，专为快速创建具有不同角色、个性和能力的多个代理而设计。通过这一框架，我们可以使用不同的 `AI` 智能体设计模式来实现复杂的 `AI` 应用。 + +`AutoGen` 提供了一个统一的多智能体对话框架，作为使用基础模型的高级抽象。它具有功能强大、可定制和可对话的代理，通过自动代理聊天集成 `LLMs` 、`tools` 和 `human` 。通过在多个智能体之间自动化地聊天，可以很容易地让他们自主或在人类反馈下集体执行任务，包括需要通过代码使用工具的任务。 + +该框架简化了复杂 `LLM` 工作流程的编排、自动化和优化。它最大限度地提高了模型的 `LLM` 性能并克服了它们的弱点，从而可以让开发者以最小的工作量构建基于多智能体对话的下一代 `AI` 应用。 + +下图显示了使用 `AutoGen` 构建的六个应用示例及其设计模式： + +![fig-1-1](./images/fig-1-1.png) @@ -16,15 +24,15 @@ ##### 可扩展性与可组合性 -`AutoGen` 具有高度的可扩展性和可组合性。您可以通过自定义组件扩展简单的智能体，并创建组合这些智能体的工作流程，从而驱动更复杂的代理。这种设计确保了系统的模块化和易于维护。 +`AutoGen` 具有高度的可扩展性和可组合性。我们可以通过自定义组件扩展简单的智能体，并创建组合这些智能体的工作流程，从而驱动更复杂的代理。这种设计确保了系统的模块化和易于维护。 ##### 多智能体协作 -在 `AutoGen` 中，智能体不仅可以模拟现实世界和抽象实体（如人类和算法），还能够简化复杂工作流程的实施。智能体之间的协作是该框架的核心，可以让您实现诸如研究员、数据收集员、联合编写员和执行员等多种角色之间的高效互动。 +在 `AutoGen` 中，智能体不仅可以模拟现实世界和抽象实体（如人类和算法），还能够简化复杂工作流程的实施。智能体之间的协作是该框架的核心，可以让我们实现诸如研究员、数据分析师、程序员和作家等多种角色之间的高效互动。 ##### 社区支持 -- `AutoGen` 由一个充满活力的研究人员和工程师社区共同开发和维护。 +- `AutoGen` 由一个充满活力的研究人员和工程师的社区共同开发和维护。 - 社区融合了多智能体系统的最新研究成果，并已被应用于许多实际场景中，包括广告、`AI` 员工、博客写作、区块链、智能客服、网络安全、数据分析、辩论、教育、金融、游戏、法律咨询、研究、机器人、销售与营销、社会模拟、软件工程、软件安全、供应链管理、培训数据生成和 `YouTube` 服务等。 ##### 智能体设计模式 @@ -33,7 +41,7 @@ ##### 模块化与易于维护 -通过模块化的实现方式，`AutoGen` 确保了系统的易于维护性。您可以在智能体中自由开启或关闭每个组件，并根据具体应用的需求进行定制。 +通过模块化的实现方式，`AutoGen` 确保了系统的易于维护性。我们可以在智能体中自由开启或关闭每个组件，并根据具体应用的需求进行定制。 ##### 角色分配与对话推进 @@ -50,10 +58,12 @@ - 人类输入 - 其他可定制的组件 -内置的 `ConversableAgent` 支持语言模型、代码执行器、函数和工具执行器等组件，并保持人类参与的能力。对于开发者，可以通过 `registered_reply` 添加额外的组件到智能体中。 +> 内置的 `ConversableAgent` 支持语言模型、代码执行器、函数和工具执行器等组件，并保持人类参与的能力。对于开发者，可以通过 `registered_reply` 添加额外的组件到智能体中。 + +![fig-1-1](./images/fig-1-2.png) ## 结论 -`AutoGen` 是一个功能强大且易于使用的多智能体对话框架，其高度的可扩展性、可组合性和社区支持使其成为实现复杂 `AI` 应用的理想选择。无论是初学者还是高级用户，都可以通过 `AutoGen` 快速创建和管理智能体，解决广泛存在的现实世界问题。 +`AutoGen` 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