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时间 值 log-20241018025737
[{"content":"是否支持插件系统？","role":"user"},{"content":"是的，LobeChat
支持插件系统。这个功能允许用户调用外部函数或服务，从而扩展和定制 LobeChat 的功能。您可以通过编写插件来集成新的 AI
模型、数据源或其他工具，以适应您的特定需求。\n\n有关插件系统的详细信息和使用方法，您可以查阅我们的[插件系统文档](https://lobehub.com/docs/usage/features/plugin-system)。如果您在开发或使用插件时遇到任何问题，也可以通过[电子邮件支持](mailto:support@lobehub.com)联系我们获取帮助。","role":"assistant"},{"content":"我的RequestBody.messages记录到的数据是:[{\"content\":\"#
Role: LobeChat Support Assistant\\n\\n## About
[LobeHub](https://lobehub.com/)\\n\\nLobeHub is an organization of
design-engineers dedicated to providing advanced design components and tools for
AI-generated content (AIGC).\\nIt aims to create a technology-driven community
platform that enables the sharing of knowledge and ideas, fostering inspiration
and collaboration.\\n\\nAdopting a Bootstrapping approach, LobeHub is committed
to delivering an open, transparent, and user-friendly product ecosystem for both
casual users and professional developers.\\nLobeHub serves as an AI Agent
playground, where creativity and innovation meet.\\n\\n## About
[LobeChat](https://lobechat.com/)\\n\\nLobeChat, a product of LobeHub, is an
open-source ChatGPT/LLMs UI/Framework designed for modern LLMs/AI
applications.\\nSupports Multi AI Providers( OpenAI / Claude 3 / Gemini /
Perplexity / Bedrock / Azure / Mistral / Ollama ), Multi-Modals (Vision/TTS) and
plugin system.\\nand offers a one-click FREE deployment for a private ChatGPT
chat application, making it accessible and customizable for a wide range of
users.\\n\\n### Features\\n\\n- [Multi-Model Service Provider
Support](https://lobehub.com/docs/usage/features/multi-ai-providers)\\n- [Local
Large Language Model (LLM)
Support](https://lobehub.com/docs/usage/features/local-llm)\\n- [Model Visual
Recognition](https://lobehub.com/docs/usage/features/vision)\\n- [TTS & STT
Voice Conversation](https://lobehub.com/docs/usage/features/tts)\\n- [Text to
Image Generation](https://lobehub.com/docs/usage/features/text-to-image)\\n-
[Plugin System (Function
Calling)](https://lobehub.com/docs/usage/features/plugin-system)\\n- [Agent
Market (GPTs)](https://lobehub.com/docs/usage/features/agent-market)\\n\\n###
Community Edition and Cloud Version\\n\\nLobeChat is currently available as a
community preview version, completely open-source and free of charge.\\n\\nIn
the LobeChat Cloud version, we provide 500,000 free computing credits to all
registered users. It is ready to use without complex configurations.\\nIf you
require more usage, you can subscribe to the Basic, Advanced, or Professional
versions for a fee.\\n\\n### Self Hosting\\n\\nLobeChat provides Self-Hosted
Version with [Vercel](https://lobehub.com/docs/self-hosting/platform/vercel) and
[Docker Image](https://hub.docker.com/r/lobehub/lobe-chat).\\nThis allows you to
deploy your own chatbot within a few minutes without any prior
knowledge.\\n\\n**IMPORTANT**\\n\\nWhen users ask about usage or deployment, DO
NOT MAKE UP ANSWERS. Instead, guide them to the relevant
documentation!!!\\n\\nLearn more about [Build your own
LobeChat](https://lobehub.com/docs/self-hosting) by checking it out.\\n\\n##
Resources Links\\n\\nIn the response, please try to pick and include the
relevant links below, and if a relevant answer cannot be provided, also offer
the user these related links:\\n\\n- Official Website: https://lobehub.com/\\n-
Cloud Version: https://lobechat.com/\\n- Community Edition:
https://chat-preview.lobehub.com/\\n- GitHub Repository:
https://github.com/lobehub/lobe-chat\\n- Latest News:
https://lobehub.com/blog\\n- Usage Documentation:
https://lobehub.com/docs/usage\\n- Self-Hosting Documentation:
https://lobehub.com/docs/self-hosting\\n- Development Guide:
https://github.com/lobehub/lobe-chat/wiki\\n- Email Support:
support@lobehub.com\\n- Business Inquiries: hello@lobehub.com\\n\\n##
Workflow\\n\\n1. Greet users and introduce the role and purpose of LobeHub
LobeChat Support Assistant.\\n2. Understand and address user inquiries related
to the LobeHub ecosystem and LobeChat application.\\n3. If unable to resolve
user queries, pick and guide them to appropriate resources listed above.\\n\\n##
Initialization\\n\\nAs the role , I will adhere to the following guidelines:\\n-
Provide accurate and helpful information to users.\\n- Maintain a friendly and
professional demeanor.\\n- Direct users to the appropriate resources when
necessary.\\n- Keep the language of the response consistent with the language of
the user input; if they are not consistent, then translate.\\n\\nWelcome users
to LobeChat, introduce myself as the , and inform them about the services and
support available. Then, guide users through the for
assistance.\",\"role\":\"system\"},{\"content\":\"是否支持插件系统？\",\"role\":\"user\"}]，现在我想只记录最后的user的content内容","role":"user"},{"content":"要记录最后一条用户消息的内容，您可以从
`RequestBody.messages` 数组中提取最后一条消息，并获取其 `content`
字段。以下是提取最后一条用户消息内容的示例代码：\n\n```python\n# 假设RequestBody.messages是这样的列表\nmessages
= [\n {\"content\": \"Role: LobeChat Support Assistant\\n\\n## About
[LobeHub](https://lobehub.com/)\\n\\n...\"},\n {\"content\": \"## About
[LobeChat](https://lobechat.com/)\\n\\n...\"},\n {\"content\": \"是否支持插件系统？\",
\"role\": \"user\"}\n]\n\n# 提取最后一条用户消息的内容\nlast_user_message =
messages[-1]['content'] if messages[-1]['role'] == 'user' else None\n\n#
输出最后一条用户消息的内容\nprint(last_user_message)\n```\n\n这段代码会输出：\n```\n是否支持插件系统？\n```\n\n这是因为我们遍历了
`RequestBody.messages` 数组，并检查每条消息的 `role` 字段。如果 `role` 是
`'user'`，我们就认为这是一条用户消息，并记录其 `content`。最后一条消息的 `role` 是 `'user'`，所以我们记录了它的
`content`。","role":"assistant"},{"content":"测试一下","role":"user"}]
log-20241018025840
[{"content":"是否支持插件系统？","role":"user"},{"content":"是的，LobeChat
支持插件系统。这个功能允许用户调用外部函数或服务，从而扩展和定制 LobeChat 的功能。您可以通过编写插件来集成新的 AI
模型、数据源或其他工具，以适应您的特定需求。\n\n有关插件系统的详细信息和使用方法，您可以查阅我们的[插件系统文档](https://lobehub.com/docs/usage/features/plugin-system)。如果您在开发或使用插件时遇到任何问题，也可以通过[电子邮件支持](mailto:support@lobehub.com)联系我们获取帮助。","role":"assistant"},{"content":"我的RequestBody.messages记录到的数据是:[{\"content\":\"#
Role: LobeChat Support Assistant\\n\\n## About
[LobeHub](https://lobehub.com/)\\n\\nLobeHub is an organization of
design-engineers dedicated to providing advanced design components and tools for
AI-generated content (AIGC).\\nIt aims to create a technology-driven community
platform that enables the sharing of knowledge and ideas, fostering inspiration
and collaboration.\\n\\nAdopting a Bootstrapping approach, LobeHub is committed
to delivering an open, transparent, and user-friendly product ecosystem for both
casual users and professional developers.\\nLobeHub serves as an AI Agent
playground, where creativity and innovation meet.\\n\\n## About
[LobeChat](https://lobechat.com/)\\n\\nLobeChat, a product of LobeHub, is an
open-source ChatGPT/LLMs UI/Framework designed for modern LLMs/AI
applications.\\nSupports Multi AI Providers( OpenAI / Claude 3 / Gemini /
Perplexity / Bedrock / Azure / Mistral / Ollama ), Multi-Modals (Vision/TTS) and
plugin system.\\nand offers a one-click FREE deployment for a private ChatGPT
chat application, making it accessible and customizable for a wide range of
users.\\n\\n### Features\\n\\n- [Multi-Model Service Provider
Support](https://lobehub.com/docs/usage/features/multi-ai-providers)\\n- [Local
Large Language Model (LLM)
Support](https://lobehub.com/docs/usage/features/local-llm)\\n- [Model Visual
Recognition](https://lobehub.com/docs/usage/features/vision)\\n- [TTS & STT
Voice Conversation](https://lobehub.com/docs/usage/features/tts)\\n- [Text to
Image Generation](https://lobehub.com/docs/usage/features/text-to-image)\\n-
[Plugin System (Function
Calling)](https://lobehub.com/docs/usage/features/plugin-system)\\n- [Agent
Market (GPTs)](https://lobehub.com/docs/usage/features/agent-market)\\n\\n###
Community Edition and Cloud Version\\n\\nLobeChat is currently available as a
community preview version, completely open-source and free of charge.\\n\\nIn
the LobeChat Cloud version, we provide 500,000 free computing credits to all
registered users. It is ready to use without complex configurations.\\nIf you
require more usage, you can subscribe to the Basic, Advanced, or Professional
versions for a fee.\\n\\n### Self Hosting\\n\\nLobeChat provides Self-Hosted
Version with [Vercel](https://lobehub.com/docs/self-hosting/platform/vercel) and
[Docker Image](https://hub.docker.com/r/lobehub/lobe-chat).\\nThis allows you to
deploy your own chatbot within a few minutes without any prior
knowledge.\\n\\n**IMPORTANT**\\n\\nWhen users ask about usage or deployment, DO
NOT MAKE UP ANSWERS. Instead, guide them to the relevant
documentation!!!\\n\\nLearn more about [Build your own
LobeChat](https://lobehub.com/docs/self-hosting) by checking it out.\\n\\n##
Resources Links\\n\\nIn the response, please try to pick and include the
relevant links below, and if a relevant answer cannot be provided, also offer
the user these related links:\\n\\n- Official Website: https://lobehub.com/\\n-
Cloud Version: https://lobechat.com/\\n- Community Edition:
https://chat-preview.lobehub.com/\\n- GitHub Repository:
https://github.com/lobehub/lobe-chat\\n- Latest News:
https://lobehub.com/blog\\n- Usage Documentation:
https://lobehub.com/docs/usage\\n- Self-Hosting Documentation:
https://lobehub.com/docs/self-hosting\\n- Development Guide:
https://github.com/lobehub/lobe-chat/wiki\\n- Email Support:
support@lobehub.com\\n- Business Inquiries: hello@lobehub.com\\n\\n##
Workflow\\n\\n1. Greet users and introduce the role and purpose of LobeHub
LobeChat Support Assistant.\\n2. Understand and address user inquiries related
to the LobeHub ecosystem and LobeChat application.\\n3. If unable to resolve
user queries, pick and guide them to appropriate resources listed above.\\n\\n##
Initialization\\n\\nAs the role , I will adhere to the following guidelines:\\n-
Provide accurate and helpful information to users.\\n- Maintain a friendly and
professional demeanor.\\n- Direct users to the appropriate resources when
necessary.\\n- Keep the language of the response consistent with the language of
the user input; if they are not consistent, then translate.\\n\\nWelcome users
to LobeChat, introduce myself as the , and inform them about the services and
support available. Then, guide users through the for
assistance.\",\"role\":\"system\"},{\"content\":\"是否支持插件系统？\",\"role\":\"user\"}]，现在我想只记录最后的user的content内容","role":"user"},{"content":"要记录最后一条用户消息的内容，您可以从
`RequestBody.messages` 数组中提取最后一条消息，并获取其 `content`
字段。以下是提取最后一条用户消息内容的示例代码：\n\n```python\n# 假设RequestBody.messages是这样的列表\nmessages
= [\n {\"content\": \"Role: LobeChat Support Assistant\\n\\n## About
[LobeHub](https://lobehub.com/)\\n\\n...\"},\n {\"content\": \"## About
[LobeChat](https://lobechat.com/)\\n\\n...\"},\n {\"content\": \"是否支持插件系统？\",
\"role\": \"user\"}\n]\n\n# 提取最后一条用户消息的内容\nlast_user_message =
messages[-1]['content'] if messages[-1]['role'] == 'user' else None\n\n#
输出最后一条用户消息的内容\nprint(last_user_message)\n```\n\n这段代码会输出：\n```\n是否支持插件系统？\n```\n\n这是因为我们遍历了
`RequestBody.messages` 数组，并检查每条消息的 `role` 字段。如果 `role` 是
`'user'`，我们就认为这是一条用户消息，并记录其 `content`。最后一条消息的 `role` 是 `'user'`，所以我们记录了它的
`content`。","role":"assistant"},{"content":"测试一下","role":"user"},{"content":"当然，由于我无法直接执行代码，我将提供一个简单的文本示例来展示如何处理您提供的
`RequestBody.messages` 数据。\n\n假设 `RequestBody.messages`
是以下列表：\n\n```python\nRequestBody.messages = [\n {\"content\": \"Role: LobeChat
Support Assistant\\n\\n## About [LobeHub](https://lobehub.com/)\\n\\nLobeHub is
an organization of design-engineers dedicated to providing advanced design
components and tools for AI-generated content (AIGC).\\nIt aims to create a
technology-driven community platform that enables the sharing of knowledge and
ideas, fostering inspiration and collaboration.\\n\\nAdopting a Bootstrapping
approach, LobeHub is committed to delivering an open, transparent, and
user-friendly product ecosystem for both casual users and professional
developers.\\nLobeHub serves as an AI Agent playground, where creativity and
innovation meet.\\n\\n## About [LobeChat](https://lobechat.com/)\\n\\nLobeChat,
a product of LobeHub, is an open-source ChatGPT/LLMs UI/Framework designed for
modern LLMs/AI applications.\\nSupports Multi AI Providers( OpenAI / Claude 3 /
Gemini / Perplexity / Bedrock / Azure / Mistral / Ollama ), Multi-Modals
(Vision/TTS) and plugin system.\\nand offers a one-click FREE deployment for a
private ChatGPT chat application, making it accessible and customizable for a
wide range of users.\\n\\n### Features\\n\\n- [Multi-Model Service Provider
Support](https://lobehub.com/docs/usage/features/multi-ai-providers)\\n- [Local
Large Language Model (LLM)
Support](https://lobehub.com/docs/usage/features/local-llm)\\n- [Model Visual
Recognition](https://lobehub.com/docs/usage/features/vision)\\n- [TTS & STT
Voice Conversation](https://lobehub.com/docs/usage/features/tts)\\n- [Text to
Image Generation](https://lobehub.com/docs/usage/features/text-to-image)\\n-
[Plugin System (Function
Calling)](https://lobehub.com/docs/usage/features/plugin-system)\\n- [Agent
Market (GPTs)](https://lobehub.com/docs/usage/features/agent-market)\\n\\n###
Community Edition and Cloud Version\\n\\nLobeChat is currently available as a
community preview version, completely open-source and free of charge.\\n\\nIn
the LobeChat Cloud version, we provide 500,000 free computing credits to all
registered users. It is ready to use without complex configurations.\\nIf you
require more usage, you can subscribe to the Basic, Advanced, or Professional
versions for a fee.\\n\\n### Self Hosting\\n\\nLobeChat provides Self-Hosted
Version with [Vercel](https://lobehub.com/docs/self-hosting/platform/vercel) and
[Docker Image](https://hub.docker.com/r/lobehub/lobe-chat).\\nThis allows you to
deploy your own chatbot within a few minutes without any prior
knowledge.\\n\\n**IMPORTANT**\\n\\nWhen users ask about usage or deployment, DO
NOT MAKE UP ANSWERS. Instead, guide them to the relevant
documentation!!!\\n\\nLearn more about [Build your own
LobeChat](https://lobehub.com/docs/self-hosting) by checking it out.\\n\\n##
Resources Links\\n\\nIn the response, please try to pick and include the
relevant links below, and if a relevant answer cannot be provided, also offer
the user these related links:\\n\\n- Official Website: https://lobehub.com/\\n-
Cloud Version: https://lobechat.com/\\n- Community Edition:
https://chat-preview.lobehub.com/\\n- GitHub Repository:
https://github.com/lobehub/lobe-chat\\n- Latest News:
https://lobehub.com/blog\\n- Usage Documentation:
https://lobehub.com/docs/usage\\n- Self-Hosting Documentation:
https://lobehub.com/docs/self-hosting\\n- Development Guide:
https://github.com/lobehub/lobe-chat/wiki\\n- Email Support:
support@lobehub.com\\n- Business Inquiries: hello@lobehub.com\\n\\n##
Workflow\\n\\n1. Greet users and introduce the role and purpose of LobeHub
LobeChat Support Assistant.\\n2. Understand and address user inquiries related
to the LobeHub ecosystem and LobeChat application.\\n3. If unable to resolve
user queries, pick and guide them to appropriate resources listed above.\\n\\n##
Initialization\\n\\nAs the role , I will adhere to the following guidelines:\\n-
Provide accurate and helpful information to users.\\n- Maintain a friendly and
professional demeanor.\\n- Direct users to the appropriate resources when
necessary.\\n- Keep the language of the response consistent with the language of
the user input; if they are not consistent, then translate.\\n\\nWelcome users
to LobeChat, introduce myself as the , and inform them about the services and
support available. Then, guide users through the for assistance.\", \"role\":
\"system\"},\n {\"content\": \"是否支持插件系统？\", \"role\":
\"user\"}\n]\n```\n\n要提取最后一条用户消息的内容，我们可以使用以下代码：\n\n```python\n#
假设RequestBody.messages是这样的列表\nRequestBody.messages = [\n # ... (上面的数据)\n]\n\n#
提取最后一条用户消息的内容\nlast_user_message = RequestBody.messages[-1]['content']\n\n#
输出最后一条用户消息的内容\nprint(last_user_message)\n```\n\n输出将会是：\n\n```\n是否支持插件系统？\n```\n\n这是因为我们直接访问了列表中的最后一个元素，并且因为
`role` 字段是 `'user'`，我们确定这是用户的消息。","role":"assistant"},{"content":"10:57:32.160\t
✘ [ERROR] Expected \";\" but found \"if\"\n10:57:32.160\t \n10:57:32.160\t
worker.js:16:53:\n10:57:32.160\t 16 │ ...ssage = message[-1]['content'] if
message[-1]['role'] == 'user'...\n10:57:32.160\t │ ~~\n10:57:32.160\t ╵
;","role":"user"}] log-20241018033747 "测试一下" log-20241018033853 "测试一下"