chatblade

chatblade

ChatGPT命令行工具 灵活高效的交互体验

Chatblade是一款功能丰富的命令行工具,专门用于与OpenAI的ChatGPT进行交互。该工具支持管道输入和参数传递,可保存常用提示以提高使用效率。Chatblade能从ChatGPT响应中提取JSON或Markdown,并提供会话管理、模型选择和流式输出等功能。此外,它还支持自定义提示和Azure OpenAI配置,为ChatGPT用户提供了灵活高效的命令行操作体验。

ChatbladeCLI工具ChatGPTAPI交互会话管理Github开源项目

Chatblade

A CLI Swiss Army Knife for ChatGPT

Chatblade is a versatile command-line interface (CLI) tool designed to interact with OpenAI's ChatGPT. It accepts piped input, arguments, or both, and allows you to save common prompt preambles for quick usage. Additionally, Chatblade provides utility methods to extract JSON or Markdown from ChatGPT responses.

Note: You'll need to set up your OpenAI API key to use Chatblade.

You can do that by either passing --openai-api-key KEY or by setting an env variable OPENAI_API_KEY (recommended). The examples below all assume an env variable is set.

Install

Latest and greatest

To stay up to date with the current main branch you can:

  • check out the project, and run pip install .
  • or pip install 'chatblade @ git+https://github.com/npiv/chatblade'

Via pypi

The last released version can be installed with pip install chatblade --upgrade

Via Brew

brew install chatblade

Documentation

Making queries

A new conversation

You can begin any query by just typing. f.e.:

chatblade how can I extract a still frame from a video at 22:01 with ffmpeg
<img width="650" alt="image" src="https://user-images.githubusercontent.com/452020/226869260-1dcd4faf-521c-466b-998a-fd5cfdc5b3c7.png">

recall the last conversation

if you would like to recall the last conversation just call it back with -l

chatblade -l

Continue the last conversation

To continue the conversation and ask for a change within the context, you can again use -l but with a query.

chatblade -l can we make a gif instead from 00:22:01 to 00:22:04

-l is shorthand for -S last or the last session. We can keep track of and continue various distinct conversations using the session options

Picking between gpt-3.5 and 4

By default, gpt-3.5 is used, you can switch at any point to 4 by using -c 4 or the latest 4o ("omni") by using -c 4o.

Additionally, you can pass any arbitrary full model name, f.e. -c gpt-3.5-turbo-16k.

Chatting interactively

If you preferred to chat interactively instead just use chatblade -i.

Show streaming text (experimental)

You can also stream the responses, just like in the webui. At the end of the stream it will format the result. This can be combined in an interactive session

chatblade -s -i

https://user-images.githubusercontent.com/452020/226891636-54d12df2-528f-4365-a4f3-e51cb025773c.mov

Formatting the results

Responses are parsed and if chatblade thinks its markdown it will be presented as such, to get syntax highlighting. But sometimes this may not be what you want, as it removes new lines, or because you are only interested in extracting a part of the result to pipe to another command.

In that case you have 2 options:

  • -r for raw, which just prints the text exactly as ChatGPT returned it, and doesn't pass it through Markdown.
  • -e for extract, which will try to detect what was returned (either a code block or json) and extract only that part. If neither of those are found it does the same as -r

Both options can be used either with a new query, e.g.

chatblade -e write me a python boilerplate script that starts a server and prints hello world > main.py

or with the last result (json in this example)

chatblade -l -e | jq

Piping content into chatblade

If we have long prompts we don't want to type everytime, or just want to provide context for our query we can pipe into chatblade.

e.g.

curl https://news.ycombinator.com/rss | chatblade given the above rss can you show me the top 3 articles about AI and their links -c 4

The piped input is placed above the query and sent to ChatGPT.

<img src="assets/example3.png">

or

chatblade what does this script do < script.sh

What gets sent to ChatGPT over the wire is:

piped input
-------
query

Session Options

Sessions are named conversations.

If you start chatblade with a session name SESS of your choice:

chatblade -S SESS can we make a gif instead from 00:22:01 to 00:22:04

chatblade will create a session called SESS if it does not exist, and it will store the current exchange (query-response pair) for SESS.

If such a session already exists, the saved conversation will be loaded and the new exchange will be appended.

Without a session argument, the exchange also gets stored in a session named last; however, subsequent sessionless invocation will overwrite the content of last. (You can continue a conversation that was started as a sessionless exchange by passing -S last, but last won't be a safe space for keeping a conversation, as the next sessionless invocation will clear it again.) The -l option is provided as a shorthand for -S last.

If you specify a session without a query:

chatblade -S SESS

chatblade will recall the conversation without modifying the session.

chatblade supports various operations on sessions. It provides the --session-OP options, where OP can be list, path, dump, delete, rename.

Checking token count and estimated costs

If you want to check the approximate cost and token usage of a previous query, you can use the -t flag for "tokens."

We could do this when passing in a lot of context like in the example above for instance.

curl https://news.ycombinator.com/rss | chatblade given the above rss can you show me the top 3 articles about AI and their links -t
<img width="650" alt="image" src="https://user-images.githubusercontent.com/452020/226874588-28c53f53-1d19-4ce3-b7ec-b01c2f7cf75a.png">

This won't perform any action over the wire, and just calculates the tokens locally.

Use custom prompts (the system msg)

The system message is used to instruct the model how to behave, see OpenAI - Instructing Chat Models.

These can be loaded with -p. For convenience any file we place under ~/.config/chatblade/ will be picked up by this command.

So for example, given the following file ~/.config/chatblade/etymology, which contains:

I want you to act as a professional Etymologist and Quiz Generator. You have a deep knowledge of etymology and will be provided with a word.
The goal is to create cards that quiz on both the etymology and finding the word by its definition.

The following is what a perfect answer would look like for the word "disparage":

[{
  "question": "A verb used to indicate the act of speaking about someone or something in a negative or belittling way.<br/> <i>E.g He would often _______ his coworkers behind their backs.</i>",
  "answer": "disparage"
},
{
  "question": "What is the etymological root of the word disparage?",
  "answer": "From the Old French word <i>'desparagier'</i>, meaning 'marry someone of unequal rank', which comes from <i>'des-'</i> (dis-) and <i>'parage'</i> (equal rank)"
}]

You will return answers in JSON only. Answer truthfully and if you don't know then say so. Keep questions as close as possible to the
provided examples. Make sure to include an example in the definition question. Use HTML within the strings to nicely format your answers.

If multiple words are provided, create questions and answers for each of them in one list.

Only answer in JSON, don't provide any more text. Valid JSON uses "" quotes to wrap its items.

We can now run a command and refer to this prompt with -p etymology:

chatblade -p etymology gregarious

You can also point -p to a file path directly to load a system message from any arbitrary location

<img src="assets/example5.png">

And since we asked for JSON, we can pipe our result to something else, e.g.:

chatblade -l -e > toanki

Configuring for Azure OpenAI

chatblade can be used with an Azure OpenAI endpoint, in which case in addition to the OPENAI_API_KEY you'll need to set the following environment variables:

  • OPENAI_API_TYPE :: Set to azure. As required by openai-python
  • AZURE_OPENAI_ENDPOINT :: URL to your cognitive services' endpoint, e.g. https://eastus.api.cognitive.microsoft.com/. Please note this is a breaking change introduced by openai-python and the previous environment variable name is OPENAI_API_BASE
  • OPENAI_API_AZURE_ENGINE :: name of your deployment in Azure, f.e. my-gpt-35-turbo (maps to a specific model)

Note: that this will override any option for -c 3.5 or -c 4 which don't make sense in this case.

Help

usage: Chatblade [-h] [--openai-api-key key] [--temperature t] [-c CHAT_GPT] [-i] [-s] [-t] [-p name] [-e] [-r] [-n] [-o] [--theme theme] [-l] [-S sess] [--session-list] [--session-path] [--session-dump] [--session-delete]
                 [--session-rename newsess]
                 [query ...]

a CLI Swiss Army Knife for ChatGPT

positional arguments:
  query                            Query to send to chat GPT

options:
  -h, --help                       show this help message and exit
  --openai-api-key key             the OpenAI API key can also be set as env variable OPENAI_API_KEY
  --openai-base-url key            A custom url to use the openAI against a local or custom model, eg ollama
  --temperature t                  temperature (openai setting)
  -c CHAT_GPT, --chat-gpt CHAT_GPT
                                   ChatGPT model - use either the fully qualified model name, or one of 3.5 (gpt-3.5-turbo), 4 (gpt-4),
                                   4t (gpt-4-turbo), 4o (gpt-4o), mini (gpt-4o-mini). Default is gpt-4o-mini. Can also be set via env variable OPENAI_API_MODEL, see
                                   https://platform.openai.com/docs/models/continuous-model-upgrades for available models.
  -i, --interactive                start an interactive chat session. This will implicitly continue the conversation
  -s, --stream                     Stream the incoming text to the terminal
  -t, --tokens                     display what *would* be sent, how many tokens, and estimated costs
  -p name, --prompt-file name      prompt name - will load the prompt with that name at ~/.config/chatblade/name or a path to a file

result formatting options:
  -e, --extract                    extract content from response if possible (either json or code block)
  -r, --raw                        print session as pure text, don't pretty print or format
  -n, --no-format                  do not add pretty print formatting to output
  -o, --only                       Only display the response, omit query
  --theme theme                    Set the theme for syntax highlighting see https://pygments.org/styles/, can also be set with CHATBLADE_THEME

session options:
  -l, --last                       alias for '-S last', the default session if none is specified
  -S sess, --session sess          initiate or continue named session
  --session-list                   list sessions
  --session-path                   show path to session file
  --session-dump                   dump session to stdout
  --session-delete                 delete session
  --session-rename newsess         rename session

编辑推荐精选

酷表ChatExcel

酷表ChatExcel

大模型驱动的Excel数据处理工具

基于大模型交互的表格处理系统,允许用户通过对话方式完成数据整理和可视化分析。系统采用机器学习算法解析用户指令,自动执行排序、公式计算和数据透视等操作,支持多种文件格式导入导出。数据处理响应速度保持在0.8秒以内,支持超过100万行数据的即时分析。

AI工具酷表ChatExcelAI智能客服AI营销产品使用教程
DeepEP

DeepEP

DeepSeek开源的专家并行通信优化框架

DeepEP是一个专为大规模分布式计算设计的通信库,重点解决专家并行模式中的通信瓶颈问题。其核心架构采用分层拓扑感知技术,能够自动识别节点间物理连接关系,优化数据传输路径。通过实现动态路由选择与负载均衡机制,系统在千卡级计算集群中维持稳定的低延迟特性,同时兼容主流深度学习框架的通信接口。

DeepSeek

DeepSeek

全球领先开源大模型,高效智能助手

DeepSeek是一家幻方量化创办的专注于通用人工智能的中国科技公司,主攻大模型研发与应用。DeepSeek-R1是开源的推理模型,擅长处理复杂任务且可免费商用。

问小白

问小白

DeepSeek R1 满血模型上线

问小白是一个基于 DeepSeek R1 模型的智能对话平台,专为用户提供高效、贴心的对话体验。实时在线,支持深度思考和联网搜索。免费不限次数,帮用户写作、创作、分析和规划,各种任务随时完成!

AI主流办公工具有哪些办公热门AI 助手
KnowS

KnowS

AI医学搜索引擎 整合4000万+实时更新的全球医学文献

医学领域专用搜索引擎整合4000万+实时更新的全球医学文献,通过自主研发AI模型实现精准知识检索。系统每日更新指南、中英文文献及会议资料,搜索准确率较传统工具提升80%,同时将大模型幻觉率控制在8%以下。支持临床建议生成、文献深度解析、学术报告制作等全流程科研辅助,典型用户反馈显示每周可节省医疗工作者70%时间。

Windsurf Wave 3

Windsurf Wave 3

Windsurf Editor推出第三次重大更新Wave 3

新增模型上下文协议支持与智能编辑功能。本次更新包含五项核心改进:支持接入MCP协议扩展工具生态,Tab键智能跳转提升编码效率,Turbo模式实现自动化终端操作,图片拖拽功能优化多模态交互,以及面向付费用户的个性化图标定制。系统同步集成DeepSeek、Gemini等新模型,并通过信用点数机制实现差异化的资源调配。

AI IDE
腾讯元宝

腾讯元宝

腾讯自研的混元大模型AI助手

腾讯元宝是腾讯基于自研的混元大模型推出的一款多功能AI应用,旨在通过人工智能技术提升用户在写作、绘画、翻译、编程、搜索、阅读总结等多个领域的工作与生活效率。

AI助手AI对话AI工具腾讯元宝智能体热门 AI 办公助手
Grok3

Grok3

埃隆·马斯克旗下的人工智能公司 xAI 推出的第三代大规模语言模型

Grok3 是由埃隆·马斯克旗下的人工智能公司 xAI 推出的第三代大规模语言模型,常被马斯克称为“地球上最聪明的 AI”。它不仅是在前代产品 Grok 1 和 Grok 2 基础上的一次飞跃,还在多个关键技术上实现了创新突破。

OmniParser

OmniParser

帮助AI理解电脑屏幕 纯视觉GUI元素的自动化解析方案

开源工具通过计算机视觉技术实现图形界面元素的智能识别与结构化处理,支持自动化测试脚本生成和辅助功能开发。项目采用模块化设计,提供API接口与多种输出格式,适用于跨平台应用场景。核心算法优化了元素定位精度,在动态界面和复杂布局场景下保持稳定解析能力。

OmniParser界面解析交互区域检测Github开源项目
流畅阅读

流畅阅读

AI网页翻译插件 双语阅读工具,还原母语级体验

流畅阅读是一款浏览器翻译插件,通过上下文智能分析提升翻译准确性,支持中英双语对照显示。集成多翻译引擎接口,允许用户自定义翻译规则和快捷键配置,操作数据全部存储在本地设备保障隐私安全。兼容Chrome、Edge、Firefox等主流浏览器,基于GPL-3.0开源协议开发,提供持续的功能迭代和社区支持。

AI翻译AI翻译引擎AI翻译工具
下拉加载更多