YAICLI: Your AI assistant in command line.

YAICLI is a powerful yet lightweight command-line AI assistant that brings the capabilities of Large Language Models (
LLMs) like GPT-5 directly to your terminal. Interact with AI through multiple modes: have natural conversations,
generate and execute shell commands, or get quick answers without leaving your workflow.

Supports both standard and deep reasoning models across all major LLM providers.

[!NOTE]
YAICLI is actively developed. While core functionality is stable, some features may evolve in future releases.

We support MCP since v0.7.0!

We support Function Call since v0.5.0!

✨ Key Features

🔄 Multiple Interaction Modes

• 💬 Chat Mode: Engage in persistent conversations with full context tracking
• 🚀 Execute Mode: Generate and safely run OS-specific shell commands
• ⚡ Quick Query: Get instant answers without entering interactive mode

🧠 Smart Environment Awareness

• Auto-detection: Identifies your shell (bash/zsh/PowerShell/CMD) and OS
• Safe Command Execution: Verification before running any command
• Flexible Input: Pipe content directly (cat log.txt | ai "analyze this")

🖼️ Image Input (Vision)

• Local Images: Pass local image files with --image/-i (JPEG, PNG, GIF, WebP)
• URL Images: Pass image URLs directly to vision-capable models
• Multi-Image: Specify --image multiple times for comparison tasks
• 30+ Providers: Automatic format conversion for OpenAI, Anthropic, Gemini, Ollama families

🔌 Universal LLM Compatibility

• OpenAI-Compatible: Works with any OpenAI-compatible API endpoint
• Multi-Provider Support: Support multiple providers

💻 Enhanced Terminal Experience

• Real-time Streaming: See responses as they're generated with cursor animation
• Rich History Management: Manage histories with 500 entries by default
• Syntax Highlighting: Beautiful code formatting with customizable themes

🛠️ Developer-Friendly

• Layered Configuration: Environment variables > Config file > Sensible defaults
• Debugging Tools: Verbose mode with detailed API tracing

📚 Function Calling & MCP

• Function Calling: Enable function/MCP calling in API requests
• Function Output: Show the output of functions/MCP

Full document: https://belingud.github.io/yaicli/

📦 Installation

Prerequisites

• Python 3.10 or higher

Quick Install

# Using pip (recommended for most users)
pip install yaicli

# Using pipx (isolated environment)
pipx install yaicli

# Using uv (faster installation)
uv tool install yaicli

Yaicli has several optional dependencies group, you can copy below commands to install specific dependencies.

# install all denpendencies
pip install 'yaicli[all]'

# install with specific provider support
pip instsall 'yaicli[ollama,cohere,doubao,huggingface,gemini,mistral,anthropic]'

Install by uv.

# install all denpendencies
uv tool install 'yaicli[all]'

# install with specific provider support
uv tool instsall 'yaicli[ollama,cohere,doubao,huggingface,gemini,mistral,anthropic]'

Install from Source

git clone https://github.com/belingud/yaicli.git
cd yaicli
pip install .

Buildin Supported Providers

• AI21
• Anthropic/Claude
• Anthropic Bedrock
• Anthropic Vertex
• Cerebras
• Chatglm
• Chuts
• Cohere
• Cohere Badrock
• Cohere Sagemaker
• Deepseek
• Doubao
• Fireworks
• Gemini
• Groq
• Huggingface
• Longcat
• Longcat Anthropic Format
• Minimax
• Mistral
• ModelScope
• Ollama
• Openai
• Openai Azure
• Sambanova
• Siliconflow
• Spark
• Targon
• Together
• Vertex ai
• X AI
• Yi
• Unlimited OpenAI-compatible providers

⚙️ Configuration

YAICLI uses a simple configuration file to store your preferences and API keys.

First-time Setup

1. Run ai once to generate the default configuration file
2. Edit ~/.config/yaicli/config.ini to add your API key
3. Customize other settings as needed

Configuration File Structure

The default configuration file is located at ~/.config/yaicli/config.ini. You can use ai --template to see default

Configuration Options Reference

LLM Provider Configuration

YAICLI works with major LLM providers. The default configuration is set up for OpenAI, but you can easily switch to
other providers.

Note: blank BASE_URL (or no BASE_URL) means use provider default url.

Pre-configured Provider Settings

Note: Many providers offer OpenAI-compatible endpoints that work with the default settings.

• Google Gemini: https://ai.google.dev/gemini-api/docs/openai
• Claude: https://docs.anthropic.com/en/api/openai-sdk

If you not sure about base_url or just use the default provider base_url, just leave it blank or delete BASE_URL.

[core]
PROVIDER=cohere
BASE_URL=
API_KEY=xxx
MODEL=command-r-plus

Openai

Yaicli use openai as provider as default provider, gpt-5.2 as default model, you can add your api key to use as it is.

PROVIDER=openai
BASE_URL=
API_KEY=
MODEL=gpt-5.2

Extra params:

# REASONING_EFFORT: [high, midium, low]
REASONING_EFFORT=

See official for more details: https://platform.openai.com/docs/guides/reasoning?api-mode=chat

Openai Azure

PROVIDER=openai-azure
BASE_URL=
API_KEY=
MODEL=gpt-5.2

Support config keys:

AZURE_AD_TOKEN=
AZURE_ENDPOINT=
AZURE_DEPLOYMENT=
API_VERSION=

Support environment variables:

AZURE_OPENAI_API_KEY=
AZURE_OPENAI_AD_TOKEN=
AZURE_OPENAI_ENDPOINT=

If API_KEY not set in config, will look for AZURE_OPENAI_API_KEY environment variable.

If AZURE_AD_TOKEN not set in config, will look for AZURE_OPENAI_AD_TOKEN environment variable.

If BASE_URL and AZURE_ENDPOINT not set in config, will look for AZURE_OPENAI_ENDPOINT environment variable.

Anghropic/Claude

PROVIDER=anthropic
API_KEY=
MODEL=claude-sonnet-4-20250514

If you want to access Anthropic bedrock, you need to set AWS_SECRET_ACCESS_KEY, AWS_ACCESS_KEY_ID, AWS_SESSION_TOKEN and AWS_REGION
in config or environment variables.

PROVIDER=anthropic-bedrock
AWS_SECRET_ACCESS_KEY=
AWS_ACCESS_KEY_ID=
AWS_SESSION_TOKEN=
AWS_REGION=
MODEL=anthropic.claude-opus-4-20250514-v1:0

Support ANTHROPIC_BEDROCK_BASE_URL env or BASE_URL in config file, with same effect.

Also support Anthropic vertex with key PROJECT_ID and CLOUD_ML_REGION in config or environment variables.

PROVIDER=anthropic-vertex
PROJECT_ID=
CLOUD_ML_REGION=

You can set anthropic base url by ANTHROPIC_VERTEX_BASE_URL env, or set BASE_URL in config file, same effect.

Deepseek

PROVIDER=deepseek
API_KEY=
MODEL=deepseek-chat

OpenRouter

PROVIDER=openrouter
API_KEY=
MODEL=deepseek/deepseek-chat-v3-0324

Mistral

PROVIDER=mistral
API_KEY=
MODEL=codestral-latest

Gemini

Basic config:

PROVIDER=gemini
API_KEY=
MODEL=gemini-2.5-flash

Extra params:

TOP_K=
PRESENCE_PENALTY=
FREQUENCY_PENALTY=
SEED=
THINKING_BUDGET=
API_VERSION=
BASE_URL=

Vertex AI

PROVIDER=vertexai
MODEL=gemini-2.5-flash
PROJECT=
LOCATION=

Huggingface

Default HF_PROVIDER is auto.

HF_PROVIDER=auto
PROVIDER=huggingface
API_KEY=
MODEL=deepseek-ai/DeepSeek-R1-0528

See official docs for HF_PROVIDER: https://huggingface.co/docs/inference-providers/index

Groq

PROVIDER=groq
API_KEY=
MODEL=llama-3.3-70b-versatile

LongCat

PROVIDER=longcat
API_KEY=
MODEL=LongCat-Flash-Chat
BASE_URL=https://api.longcat.chat/openai

XAI

PROVIDER=xai
API_KEY=
MODEL=grok-3

Minimax

PROVIDER=minimax
API_KEY=
MODEL=MiniMax-M2.1

Extra params:

# Enable/disable interleaved thinking (default: true)
MINIMAX_REASONING_SPLIT=true

MiniMax-M2.1 supports Interleaved Thinking - the model can reason before each tool use. When enabled, reasoning content is preserved in conversation history and displayed alongside responses.

Chatglm

PROVIDER=chatglm
API_KEY=
MODEL=glm-4-plus

Extra params:

Check offcial docs: https://bigmodel.cn/dev/api/normal-model/glm-4

# true or false
DO_SAMPLE=

Chutes

PROVIDER=chutes
API_KEY=
MODEL=deepseek-ai/DeepSeek-V3-0324

Cerebras

PROVIDER=cerebras
API_KEY=
MODEL=llama3.3-70b

AI21

PROVIDER=ai21
API_KEY=
MODEL=jamba-large-1.6

Sambanova

PROVIDER=sambanova
API_KEY=
MODEL=DeepSeek-V3-0324

Only a few models support tool call as below:

• Meta-Llama-3.1-8B-Instruct
• Meta-Llama-3.1-405B-Instruct
• Meta-Llama-3.3-70B-Instruct
• Llama-4-Scout-17B-16E-Instruct
• DeepSeek-V3-0324

See official docs for more detail: https://docs.sambanova.ai/cloud/docs/capabilities/function-calling

ModelScope

PROVIDER=modelscope
API_KEY=
MODEL=deepseek-ai/DeepSeek-V3-0324

Inifiniai

PROVIDER=infiniai
; BASE_URL=https://cloud.infini-ai.com/maas/v1
API_KEY=
MODEL=deepseek-v3

Siliconflow

PROVIDER=siliconflow
API_KEY=
MODEL=Qwen/Qwen3-32B

Yi

PROVIDER=yi
API_KEY=
MODEL=yi-lightning

Cohere

You have to install cohere dependencies, pip install 'yaicli[cohere]'

PROVIDER=cohere
API_KEY=
MODEL=command-a-03-2025

Check official docs: https://docs.cohere.com/docs/text-gen-quickstart

Support keys:

ENVIRONMENT=

For private deploy and Azure api, you need to set BASE_URL.

PROVIDER=cohere
API_KEY=
MODEL=command-a-03-2025
BASE_URL=<YOUR_ENDPOINT>

For Bedrock and Sagemaker cohere api, you have to set below keys:

See https://docs.cohere.com/docs/text-gen-quickstart.

PROVIDER=cohere-bedrock
; PROVIDER=cohere-sagemaker
API_KEY=
MODEL=command-a-03-2025

AWS_REGION=xx
AWS_ACCESS_KEY_ID=xx
AWS_SECRET_ACCESS_KEY=xx
AWS_SESSION_TOKEN=xx

Note MODEL for Sagemaker should be endpoint name

MODEL=<YOUR_ENDPOINT_NAME>

Doubao

You have to install doubao dependencies, pip install 'yaicli[doubao]'

Use doubao OpenAI compatible api, you can just set API_KEY.

PROVIDER=doubao
API_KEY=
MODEL=doubao-1-5-lite-32k-250115

If you are using access key, you have to set AK and SK.

PROVIDER=doubao
MODEL=doubao-1-5-lite-32k-250115
AK=XXX
SK=XXX

Ollama

You have to install ollama dependencies, pip install 'yaicli[ollama]'

PROVIDER=ollama
; BASE_URL=http://localhost:11434
MODEL=qwen3:32b

Support options:

TEMPERATURE=
TOP_P=
SEED=
NUM_PREDICT=
NUM_CTX=
NUM_BATCH=
NUM_GPU=
MAIN_GPU=
LOW_VRAM=
F16_KV=
LOGITS_ALL=
VOCAB_ONLY=
USE_MMAP=
USE_MLOCK=
NUM_THREAD=

NOTE: Ollama provider not support extra body

Bailian

Only support model API call, not support application API call.

PROVIDER=bailian
API_KEY=
MODEL=qwen-plus

Bailian Intl

Bailian international platform.

PROVIDER=bailian-intl
API_KEY=
MODEL=qwen-plus

Nvida nim

PROVIDER=nvida
API_KEY=
MODEL=qwen/qwen3-235b-a22b
EXTRA_BODY={"chat_template_kwargs": {"thinking": false}}

chat_template_kwargs is for Qwen3 and ibm/granite models, you disable thinking as above config.

Together

Using together openai-compatible capabilities

PROVIDER=together
API_KEY=
MODEL=Qwen/Qwen3-235B-A22B-fp8-tput

Spark

PROVIDER=spark
API_KEY=
MODEL=4.0Ultra

Or you can use your APP_ID and API_SECRET.

PROVIDER=spark
APP_ID=
APP_SECRET=
MODEL=4.0Ultra

🚀 Usage

Quick Start

# Get a quick answer
ai "What is the capital of France?"

# Start an interactive chat session
ai --chat

# Generate and execute shell commands
ai --shell "Create a backup of my Documents folder"

# Generate code snippets, default in Python
ai --code "Write a Python function to sort a list"

# Analyze code from a file
cat app.py | ai "Explain what this code does"
# or use @
ai '@Justfile What does this file do'

# Send an image to a vision model
ai --image photo.jpg "What is in this image?"

# Send multiple images
ai -i img1.png -i img2.png "Compare these two screenshots"

# Send an image URL
ai --image https://example.com/photo.jpg "Describe this"

# Debug with verbose mode
ai --verbose "Explain quantum computing"

Interactive Mode Features

Chat Persistent

The <PROMPT> parameter in the chat mode will be used as a title to persist the chat content to the file system, with
the save directory being a temporary directory, which may vary between machines, and it is determined on the first run.

If the <PROMPT> parameter is not specified when entering chat mode, the session will be treated as a temporary
session and will not be persisted. Of course, you can also manually call the /save <title> command to save during the
chat.
When you run the same chat command again, the previous session will be automatically loaded.

$ ai --chat "meaning of life"

!NOTE: Chat mode is not supported when you redirect input to ai command.

$ cat error.log | ai --chat "Explain this error"

The above command will be parsed as ai "cat error.log | ai "Explain this error".

Start a temporary chat session

$ ai --chat

Start a persistent chat session

$ ai --chat "check disk usage"

Load a saved chat session

$ ai --chat hello
Chat title: hello

 ██    ██  █████  ██  ██████ ██      ██
  ██  ██  ██   ██ ██ ██      ██      ██
   ████   ███████ ██ ██      ██      ██
    ██    ██   ██ ██ ██      ██      ██
    ██    ██   ██ ██  ██████ ███████ ██

Welcome to YAICLI!
Current: Persistent Session: hello
Press Shift+Tab to switch mode
/clear             : Clear chat history
/his               : Show chat history
/list              : List saved chats
/save <title>      : Save current chat
/load <index>      : Load a saved chat
/del <index>       : Delete a saved chat
/exit|Ctrl+D|Ctrl+C: Exit
/mode chat|exec    : Switch mode (Case insensitive)
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
 💬 > /his
Chat History:
1 User: hi
    Assistant:
    Hello! How can I assist you today?
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
 💬 >

Image Input

Send images to vision-capable models (GPT-5.2, Claude 4.5, Gemini, Llama 4 Vision, etc.) directly from the CLI.

Local image file

ai --image photo.jpg "What is in this image?"

Multiple images

ai -i screenshot1.png -i screenshot2.png "Compare these two UIs"

Image URL

ai --image https://example.com/diagram.png "Explain this architecture diagram"

Image without text prompt

ai --image photo.jpg

Supported formats: JPEG (.jpg, .jpeg), PNG (.png), GIF (.gif), WebP (.webp).

Note: Image input is currently supported in single-shot mode only, not in interactive --chat mode. Providers without vision support (Cohere, HuggingFace, ChatGLM, ModelScope) will receive a warning and the images will be stripped.

Input Methods

Direct Input

ai "What is the capital of France?"

Piped Input

echo "What is the capital of France?" | ai

File Analysis

cat demo.py | ai "Explain this code"

Combined Input

cat error.log | ai "Why am I getting these errors in my Python app?"

File Context

YAICLI supports adding files and directories to the conversation context for better understanding of your codebase.

Temporary @ References

Use @ to reference files in your query:

# Reference a single file
ai '@README.md What is this project about?'

# Reference multiple files
ai '@src/main.py @config.yaml Explain the architecture'

# Use quotes for paths with spaces
ai @"my document.txt" Summarize this

Persistent Context

Add files/directories to context for the entire session:

ai --chat
💬 > /add src/
💬 > /context list
# Shows all files in context

💬 > Explain the codebase structure
# AI can now see all files in src/

💬 > /context remove src/
💬 > /context clear
# Remove or clear context

Features

• Auto-completion: Type @ and press Tab to browse files
• Smart ignores: Automatically skips .git, node_modules, __pycache__, etc.
• Directory support: Add entire directories (2-level depth by default)
• Path flexibility: Use relative or absolute paths

📱 Examples

Quick Answer Mode

$ ai "What is the capital of France?"
Assistant:
The capital of France is Paris.

Command Generation & Execution

$ ai -s 'Check the current directory size'
Assistant:
du -sh .
╭─ Command ─╮
│ du -sh .  │
╰───────────╯
Execute command? [e]dit, [y]es, [n]o (n): e
Edit command, press enter to execute:
du -sh ./
Output:
109M    ./

Code Generation

In code mode, select the language for code generation. If none is specified, Python is the default.

The --code mode outputs plain text, making it easy to copy, paste, or redirect to a file, especially when using the standard model.

When using a deep reasoning model, the thinking content is displayed with syntax highlighting. To disable this, use the --no-show-reasoning option or set SHOW_REASONING to false in the configuration.

$ ai --code 'Write a fib generator'
def fib_generator():
    a, b = 0, 1
    while True:
        yield a
        a, b = b, a + b

Chat Mode Example

$ ai --chat
Starting a temporary chat session (will not be saved automatically)

 ██    ██  █████  ██  ██████ ██      ██
  ██  ██  ██   ██ ██ ██      ██      ██
   ████   ███████ ██ ██      ██      ██
    ██    ██   ██ ██ ██      ██      ██
    ██    ██   ██ ██  ██████ ███████ ██

Welcome to YAICLI!
Current: Temporary Session (use /save to make persistent)
Press Shift+Tab to switch mode
/clear             : Clear chat history
/his               : Show chat history
/list              : List saved chats
/save <title>      : Save current chat
/load <index>      : Load a saved chat
/del <index>       : Delete a saved chat
!<command>         : Execute shell command directly (e.g., !ls -al)
/exit|Ctrl+D|Ctrl+C: Exit
/mode chat|exec    : Switch mode (Case insensitive)
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
 💬 > Tell me about the solar system

Assistant:
Solar System Overview

 • Central Star: The Sun (99% of system mass, nuclear fusion).
 • Planets: 8 total.
    • Terrestrial (rocky): Mercury, Venus, Earth, Mars.
    • Gas Giants: Jupiter, Saturn.
    • Ice Giants: Uranus, Neptune.
 • Moons: Over 200 (e.g., Earth: 1, Jupiter: 95).
 • Smaller Bodies:
    • Asteroids (between Mars/Venus), comets ( icy, distant), * dwarf planets* (Pluto, Ceres).
 • Oort Cloud: spherical shell of icy objects ~1–100,000天文單位 (AU) from Sun).
 • Heliosphere: Solar wind boundary protecting Earth from cosmic radiation.

Key Fact: Earth is the only confirmed habitable planet.

🚀 > Check the current directory size
Assistant:
du -sh .
╭─ Suggest Command ─╮
│ du -sh .          │
╰───────────────────╯
Execute command? [e]dit, [y]es, [n]o (n): e
Edit command: du -sh ./
--- Executing ---
 55M    ./
--- Finished ---
🚀 >

Execute Mode Example

$ ai --shell "Find all PDF files in my Downloads folder"
Assistant:
find ~/Downloads -type f -name "*.pdf"
╭─ Suggest Command ───────────────────────╮
│ find ~/Downloads -type f -iname "*.pdf" │
╰─────────────────────────────────────────╯
Execute command? [e]dit, [y]es, [n]o (n): y
Output:

/Users/username/Downloads/document1.pdf
/Users/username/Downloads/report.pdf
...

Code Mode Example

$ ai --code "write a fib generator" --model deepseek-r1

Function Call

To use function call, you need to install default functions by ai --install-functions.
After that, you can check the functions by ai --list-functions.
You can also define your own functions by adding them to the config folder in ~/.config/yaicli/functions/ (C:\Users\<user>\.config\yaicli\functions on Windows).

❯ ai --list-functions
/Users/xxx/.config/yaicli/functions/fs_file_operations.py
/Users/xxx/.config/yaicli/functions/fs_list_directory.py
/Users/xxx/.config/yaicli/functions/fs_read_file.py
/Users/xxx/.config/yaicli/functions/fs_write_file.py
/Users/xxx/.config/yaicli/functions/fs_search_files.py
/Users/xxx/.config/yaicli/functions/fetch_webpage.py
/Users/xxx/.config/yaicli/functions/get_weather.py
/Users/xxx/.config/yaicli/functions/fs_edit_file.py
/Users/xxx/.config/yaicli/functions/fs_get_filesystem_info.py
/Users/xxx/.config/yaicli/functions/web_search.py
/Users/xxx/.config/yaicli/functions/fs_read_image.py
/Users/xxx/.config/yaicli/functions/execute_shell_command.py

--enable-functions option is corresponds to the configuration key ENABLE_FUNCTIONS.

ai 'check the current dir total size' --enable-functions
Assistant:
Thinking:

▌ Okay, the user wants to check the current directory's total size. Hmm, how do I do that in macOS with zsh?
▌ I remember that the command to get disk usage is usually 'du'. But wait, the default 'du' might not give the total size of the
▌ current directory directly. Let me think. Oh right, if I use 'du -sh' with the current directory, that should give the total size
▌ in human-readable format.
▌ Wait, but sometimes the -s option summarizes the directory. So 'du -sh .' would calculate the total size of the current directory
▌ and its subdirectories. That should work. Let me confirm the syntax. Yeah, 'du -sh .' is the right command here.
▌ The user is using zsh, but the 'du' command is standard, so it should be available. I need to execute this shell command. The
▌ function provided is execute_shell_command, so I'll call that with the shell command 'du -sh .' as the argument.
▌ I should make sure the parameters are correctly formatted. The function requires a shell_command string. Alright, that's all.
▌ Let's generate the tool call.

{"index":0,"finish_reason":"tool_calls","delta":{"role":"assistant","content":null,"audio":null,"tool_calls":[{"id":"call_202505141526
36cc3f776ae8f14b56_0","index":0,"type":"function","function":{"name":"execute_shell_command","arguments":"{"shell_command": "du -sh
."}","outputs":null},"code_interpreter":null,"retrieval":null,"drawing_tool":null,"web_browser":null,"search_intent":null,"search_resu
lt":null}],"tool_call_id":null,"attachments":null,"metadata":null}}
@Function call: execute_shell_command({"shell_command": "du -sh ."})
╭─ Function output ─────╮
│ Exit code: 0, Output: │
│ 156M    .             │
│                       │
╰───────────────────────╯
Thinking:

▌ Okay, the user asked to check the current directory's total size. I used the 'du -sh .' command, which stands for disk usage,
▌ summarize, and current directory. The output was "156M". So I need to present this in a concise way.
▌ First, confirm the command was executed. Then, report the result clearly. Since the user didn't ask for extra details, keep it
▌ simple. Just state the total size as 156MB. Maybe mention the command used for transparency. Alright, that should cover it without
▌ overcomplicating.

Current directory size: 156M (using du -sh .).

MCP

Add your MCP config in ~/.config/yaicli/mcp.json (C:\Users\<user>\.config\yaicli\mcp.json on Windows.).

--enable-mcp option is corresponds to the configuration key ENABLE_MCP.

Example:

ai 'What is the latest exchange rate between the BTC and the US dollar?' --enable-mcp --show-mcp-output

Assistant:

@Mcp call: bing_search({"query": "latest exchange rate between BTC and US dollar"})
╭─ Mcp output ──────────────────────────────────────────────────────────────────────────────────────────────────────────────╮
│ [                                                                                                                         │
│   {                                                                                                                       │
│     "id": "result_1751024997243_0",                                                                                       │
│     "title": "BTC to USD - Bitcoin to US Dollar Conversion - Exchange Rates",                                             │
│     "link": "https://www.exchange-rates.org/converter/btc-usd",                                                           │
│     "snippet": "11 小时之前 · 1 Bitcoin = 107,304 US Dollars as of June 27, 2025 03:00 AM UTC. You can get live exchange  │
│ rates between Bitcoin and US Dollars using exchange-rates.org, which aggregates …"                                        │
│   },                                                                                                                      │
╰───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
Here are some current exchange rates for Bitcoin (BTC) to US Dollar (USD):

 1 Exchange-Rates.org:
   ₿1 Bitcoin = 💵107,304 US Dollars (as of June 27, 2025, 03:00 AM UTC).
   Link
 2 BTC.CurrencyRate.Today:
   Live Bitcoin to US Dollars exchange rate.
   Link
 3 Xe.com:
   Latest conversion rate and information about Bitcoin to US Dollars.
   Link
 4 BestExchangeRates.com:
   Current BTC to USD market data, including charts and historic rates.
   Link
 5 Investing.com:
   Bitcoin price analysis and live BTC to USD updates.
   Link

For the most accurate and up-to-date rate, I recommend checking one of these sources directly.

💻 Technical Details

Architecture

YAICLI is designed with a modular architecture that separates concerns and makes the codebase maintainable:

• CLI Module: Handles user interaction and command parsing
• API Client: Manages communication with LLM providers
• Config Manager: Handles layered configuration
• History Manager: Maintains conversation history with LRU functionality
• Printer: Formats and displays responses with rich formatting

Dependencies

👨‍💻 Contributing

Contributions are welcome! Here's how you can help:

• Bug Reports: Open an issue describing the bug and how to reproduce it
• Feature Requests: Suggest new features or improvements
• Code Contributions: Submit a PR with your changes
• Documentation: Help improve or translate the documentation

📃 License

Apache License 2.0

YAICLI - Your AI Command Line Interface