A command-line tool for interacting with various LLM providers
Project description
zapgpt
A minimalist CLI tool to chat with LLMs from your terminal. Supports multiple providers including OpenAI, OpenRouter, Together, Replicate, DeepInfra, and GitHub AI.
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GPT on the CLI. Like a boss.
zapgpt is a minimalist CLI tool to chat with LLMs from your terminal. No bloated UI, just fast raw GPT magic, straight from the shell. With pre-cooked system prompt for Ethical hacking, code, file attachment and a good default prompt and usage tracking, I hope you find it useful. No extra features or frills. Modify it as you need it with a simple one file script.
Updated to version v2.
Introduction video
💾 Requirements
- Python 3.8+
uv(recommended - blazingly fast Python package manager)- pip (alternative to uv)
🚀 Installation
Option 1: Install with uv (⚡ Recommended)
uv tool install zapgpt
Why uv?
uvis blazingly fast and handles CLI tools perfectly. It installs zapgpt globally and manages dependencies automatically.
Don't have uv? Install it first:
# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh
# Windows
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"
# Or with pip
pip install uv
Option 2: Install from PyPI
uv tool install zapgpt
Option 3: Development Installation
With uv (recommended):
git clone https://github.com/yourusername/zapgpt.git
cd zapgpt
uv sync
uv run zapgpt "test"
# Optional: Set up pre-commit hooks for code quality
./setup-pre-commit.sh
With pip:
git clone https://github.com/yourusername/zapgpt.git
cd zapgpt
pip install -e .
Option 4: From Source (Classic method)
git clone https://github.com/yourusername/zapgpt.git
cd zapgpt
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
🔑 Environment Variables
ZapGPT only requires the API key for the provider you're using. Set the appropriate environment variable:
| Provider | Environment Variable | Get API Key |
|---|---|---|
| OpenAI | OPENAI_API_KEY |
platform.openai.com |
| OpenRouter | OPENROUTER_KEY |
openrouter.ai |
| Together | TOGETHER_API_KEY |
api.together.xyz |
| Replicate | REPLICATE_API_TOKEN |
replicate.com |
| DeepInfra | DEEPINFRA_API_TOKEN |
deepinfra.com |
| GitHub | GITHUB_KEY |
github.com |
Example:
# For OpenAI (default provider)
export OPENAI_API_KEY="your-openai-api-key-here"
# For OpenRouter
export OPENROUTER_KEY="your-openrouter-key-here"
🧠 Usage
After installation, you can use zapgpt directly from the command line:
# Basic usage (uses OpenAI by default)
zapgpt "What's the meaning of life?"
# Use different providers
zapgpt --provider openrouter "Explain quantum computing"
zapgpt --provider together "Write a Python function"
zapgpt --provider github "Debug this code"
# Use specific models
zapgpt -m gpt-4o "Complex reasoning task"
zapgpt --provider openrouter -m anthropic/claude-3.5-sonnet "Creative writing"
Interactive Mode
zapgpt # Starts interactive mode
Development Usage
With uv:
uv run zapgpt "Your question here"
With Python:
python -m zapgpt "Your question here"
# or
python zapgpt/main.py "Your question here"
Quiet Mode (for Scripting)
# Suppress all output except the LLM response
zapgpt --quiet "What is the capital of France?"
# Perfect for shell scripts
RESPONSE=$(zapgpt -q "Summarize this in one word: Machine Learning")
echo "Result: $RESPONSE"
File Input (for Automation)
# Send file contents to LLM
zapgpt --file /path/to/file.txt "Analyze this log file"
# Analyze command output
nmap -sV target.com > scan_results.txt
zapgpt -f scan_results.txt --use-prompt vuln_assessment "Analyze these scan results"
# Process multiple files
for file in *.log; do
zapgpt -q -f "$file" "Summarize security events" >> summary.txt
done
Automation Examples
# Penetration Testing Agent
#!/bin/bash
TARGET="example.com"
# 1. Reconnaissance
nmap -sV $TARGET > nmap_results.txt
RESPONSE=$(zapgpt -q -f nmap_results.txt --use-prompt vuln_assessment "Identify potential vulnerabilities")
echo "Vulnerabilities found: $RESPONSE"
# 2. Web Analysis
nikto -h $TARGET > nikto_results.txt
zapgpt -f nikto_results.txt "Prioritize these web vulnerabilities" > web_analysis.txt
# 3. Generate Report
zapgpt -q "Create executive summary" -f web_analysis.txt > final_report.md
# Log Analysis Agent
#!/bin/bash
# Monitor and analyze system logs
tail -n 100 /var/log/auth.log > recent_auth.log
ALERT=$(zapgpt -q -f recent_auth.log "Detect suspicious login attempts")
if [[ $ALERT == *"suspicious"* ]]; then
echo "Security Alert: $ALERT" | mail -s "Security Alert" admin@company.com
fi
# Code Review Agent
#!/bin/bash
# Automated code review
for file in src/*.py; do
REVIEW=$(zapgpt -q -f "$file" --use-prompt coding "Review this code for security issues")
echo "File: $file" >> code_review.md
echo "Review: $REVIEW" >> code_review.md
echo "---" >> code_review.md
done
🐍 Programmatic API
ZapGPT can be imported and used in your Python scripts:
Basic Usage
from zapgpt import query_llm
# Simple query
response = query_llm("What is Python?", provider="openai")
print(response)
# With different provider
response = query_llm(
"Explain quantum computing",
provider="openrouter",
model="anthropic/claude-3.5-sonnet"
)
Advanced Usage
from zapgpt import query_llm
# Use predefined prompts
code_review = query_llm(
"Review this Python function: def hello(): print('hi')",
provider="openai",
use_prompt="coding",
model="gpt-4o"
)
# Custom system prompt
response = query_llm(
"Write a haiku about programming",
provider="openai",
system_prompt="You are a poetic programming mentor.",
temperature=0.8
)
# Error handling
try:
response = query_llm("Hello", provider="openai")
except EnvironmentError as e:
print(f"Missing API key: {e}")
except ValueError as e:
print(f"Invalid provider: {e}")
API Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
prompt |
str | Required | Your question/prompt |
provider |
str | "openai" | LLM provider to use |
model |
str | None | Specific model (overrides prompt default) |
system_prompt |
str | None | Custom system prompt |
use_prompt |
str | None | Use predefined prompt template |
temperature |
float | 0.3 | Response randomness (0.0-1.0) |
max_tokens |
int | 4096 | Maximum response length |
quiet |
bool | True | Suppress logging output |
Environment Variables
Set the appropriate API key for your chosen provider:
import os
os.environ['OPENAI_API_KEY'] = 'your-key-here'
from zapgpt import query_llm
response = query_llm("Hello world", provider="openai")
Python Automation Examples
# Penetration Testing Automation
import subprocess
from zapgpt import query_llm
def analyze_nmap_scan(target):
# Run nmap scan
result = subprocess.run(['nmap', '-sV', target], capture_output=True, text=True)
# Analyze with LLM
analysis = query_llm(
f"Analyze this nmap scan: {result.stdout}",
provider="openai",
use_prompt="vuln_assessment"
)
return analysis
vulns = analyze_nmap_scan("example.com")
print(f"Vulnerabilities: {vulns}")
# Log Analysis Agent
from zapgpt import query_llm
def monitor_logs(log_file):
with open(log_file, 'r') as f:
logs = f.read()
alert = query_llm(
f"Detect suspicious activity: {logs}",
provider="openai",
quiet=True
)
if "suspicious" in alert.lower():
print(f"ALERT: {alert}")
return True
return False
# Monitor auth logs
monitor_logs('/var/log/auth.log')
Usage Video
🛠️ Features
- Context-aware prompts (memory)
- Easily customizable for your LLM endpoints
- Show your current usage.
- Optional pre-cooked system prompts.
📝 Configuration & Prompts
ZapGPT stores its configuration and prompts in ~/.config/zapgpt/:
- Configuration directory:
~/.config/zapgpt/ - Prompts directory:
~/.config/zapgpt/prompts/ - Database file:
~/.config/zapgpt/gpt_usage.db
Managing Prompts
On first run, zapgpt automatically copies default prompts to your config directory. You can:
- View config location:
zapgpt --config - List available prompts:
zapgpt --list-prompt - Use a specific prompt:
zapgpt --use-prompt coding "Your question" - Add custom prompts: Create
.jsonfiles in~/.config/zapgpt/prompts/ - Modify existing prompts: Edit the
.jsonfiles in your prompts directory
Default Prompts Included
coding- Programming and development assistancecyber_awareness- Cybersecurity guidancevuln_assessment- Vulnerability assessment helpkalihacking- Kali Linux and penetration testingprompting- Prompt engineering assistancepowershell- PowerShell scripting helpdefault- General purpose promptcommon_base- Base prompt added to all others
v2 Features
- Script now uses class and is much more well organized.
- Prompts are not hard-coded in the script. You can simply drop in any new system prompt in prompts folder and use it.
- ✅ Multi-Provider Support: Supports OpenAI, OpenRouter, Together, Replicate, DeepInfra, and GitHub AI
- ✅ Easy Provider Switching: Use
--providerflag to switch between providers - ✅ Model Selection: Override model with
-mflag for any provider
🧪 Example
$ zapgpt "Summarize the Unix philosophy."
> Small is beautiful. Do one thing well. Write programs that work together.
🙌 Credits
Built with ❤️ by Amit Agarwal aka — because LLMs deserve a good CLI.
🧙♂️ License
MIT — do whatever, just don't blame me if it becomes sentient.
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