Basic Usage

This page covers the fundamental usage patterns of Chat GipiTTY. Once you understand these core concepts, you'll be able to effectively integrate AI assistance into your terminal workflow.

Core Concepts

Chat GipiTTY follows a simple input priority system:

  1. stdin - Input piped from other commands
  2. command arguments - Text provided as arguments
  3. files - Content read from files with -f flag

This priority system allows for flexible composition with other Unix tools.

Basic Command Structure

The general syntax for Chat GipiTTY is:

cgip [OPTIONS] [QUERY] [COMMAND]

Simplest Usage

Ask a direct question:

cgip "What is the capital of France?"

Piping Input

Pipe output from other commands for AI analysis:

ls -la | cgip "What can you tell me about these files?"

ps aux | cgip "Are there any processes that look suspicious?"

Using Files as Context

Include file content in your query:

cgip "explain this code" -f src/main.rs

Combining Inputs

You can combine multiple input sources:

# Pipe + argument + file
cat error.log | cgip "analyze this error" -f config.yaml

Common Usage Patterns

Debugging and Development

Debug compilation errors:

cargo build 2>&1 | cgip "what's wrong with this code?"

Analyze git logs:

git log --oneline -10 | cgip "summarize these recent changes"

Review code:

cgip "review this function for potential issues" -f utils.py

System Administration

Analyze system resources:

df -h | cgip "are there any disk space concerns?"

Review logs:

tail -n 50 /var/log/syslog | cgip "any critical issues in these logs?"

Network diagnostics:

netstat -tuln | cgip "explain what services are running"

Text Processing

Convert formats:

cgip "convert this JSON to YAML" -f data.json

Summarize content:

cgip "provide a brief summary" -f long-document.md

Generate documentation:

cgip "create documentation for this function" -f my-function.py

Data Analysis

Analyze CSV data:

head -20 data.csv | cgip "what patterns do you see in this data?"

Process command output:

find . -name "*.py" | wc -l | cgip "what does this number tell us about the project?"

Working with Different Input Types

Standard Input (stdin)

When you pipe data to cgip, it becomes the primary context:

echo "Hello World" | cgip "translate this to French"

Command Arguments

Direct text queries:

cgip "write a Python function to calculate fibonacci numbers"

File Input

Reference file contents:

cgip "optimize this SQL query" -f slow-query.sql

Combining All Three

# Error from compilation + question + config file context
cargo test 2>&1 | cgip "why is this test failing?" -f Cargo.toml

Output Modes

Standard Output

By default, cgip outputs the AI response to stdout:

cgip "hello" > response.txt

Show Context

See what context is being sent to the AI:

cgip "test" --show-context

Markdown Formatting

Display context in a human-readable table:

cgip "test" --markdown --show-context

Model Selection

Using Different Models

Specify a model for your query:

cgip --model gpt-4o "complex reasoning task"

List Available Models

See what models are available:

cgip --list-models

Set Default Model

Configure your preferred model:

cgip config --set model=gpt-4o

System Prompts

Custom System Prompt

Provide context about how the AI should respond:

cgip --system-prompt "You are a expert Python developer" "review this code" -f script.py

Set Default System Prompt

Configure a default system prompt:

cgip config --set system_prompt="Always provide concise, technical answers"

Progress and Debugging

Show Progress

Display a progress indicator (useful for long operations):

cgip --show-progress "analyze this large dataset" -f big-data.csv

Context Inspection

When things aren't working as expected, examine the context being sent:

echo "test input" | cgip "query" --show-context --markdown

Error Handling

Stderr Redirection

Since cgip reads from stdin, redirect stderr to stdout for error analysis:

cargo build 2>&1 | cgip "what's the error?"

Network Issues

If you encounter API errors, check your configuration:

cgip config --get model
echo $OPENAI_API_KEY | cut -c1-10  # Check if key is set (shows first 10 chars)

Best Practices

Be Specific

Instead of:

cgip "fix this"

Try:

cgip "identify and suggest fixes for any Python syntax errors" -f script.py

Use Context Effectively

Provide relevant context for better results:

# Good: includes error and relevant file
python script.py 2>&1 | cgip "debug this error" -f script.py

# Less effective: only the error
python script.py 2>&1 | cgip "fix this"

Combine with Unix Tools

Leverage the Unix philosophy:

# Filter and analyze
grep "ERROR" app.log | tail -20 | cgip "what's causing these errors?"

# Process and summarize
find . -name "*.js" -exec wc -l {} + | cgip "analyze the code distribution"

Next Steps

Now that you understand basic usage, explore:

  • Core Features - Sessions, web search, and advanced features
  • Subcommands - Specialized commands for images, TTS, and more
  • Examples - Real-world usage scenarios and workflows