Chat Command

Start an interactive chat session with language models. The chat command provides a conversational interface for extended interactions, maintaining context across multiple exchanges.

Overview

Interactive chat sessions enable back-and-forth conversations with LLMs, allowing for follow-up questions, clarifications, and iterative problem-solving. Chat sessions maintain conversation history and can integrate with vector databases for RAG capabilities.

Usage

# Start basic chat session
lc chat

# Chat with specific model
lc chat -m gpt-4

# Chat with vector database context
lc chat -v knowledge-base

# Chat with system prompt
lc chat -s "You are a helpful coding assistant"

# Using aliases
lc c
lc c -m claude

Subcommands

The chat command is a standalone command without subcommands. All functionality is controlled through global options and interactive commands within the chat session.

Options

Chat uses the same global options as direct prompts:

Short	Long	Description	Default
-p	--provider	Specify provider	None
-m	--model	Specify model	None
-s	--system	System prompt	None
	--max-tokens	Maximum tokens in response	None
	--temperature	Sampling temperature (0.0-2.0)	None
-a	--attach	Attach files to conversation	None
-t	--tools	MCP tools to include	None
-v	--vectordb	Vector database for RAG	None
-d	--debug	Enable debug output	False
-c	--continue	Continue previous conversation	False
	--cid	Specific chat ID to continue	None
-h	--help	Print help	False

Examples

Interactive Chat Examples

Start a Basic Chat

lc chat
# Opens an interactive chat session with default settings

# Specify provider and model
lc chat --provider openai -m gpt-4

# With system prompt
lc chat -s "You are an expert developer assisting me"

# Continue previous session
lc chat -c

# Using aliases
lc c
lc c -m gpt-4

RAG Integration

# Chat with vector database context
lc chat -v knowledge-base

# Include MCP tools
lc chat -t fetch,search

# Combined workflow
lc chat -v docs -m gpt-4 -s "You are a helpful assistant"

Conversation Flow

# Start session
lc chat -m gpt-4

# Example conversation:
# User: "Explain machine learning"
# AI: "Machine learning is a subset of AI..."
# User: "Give me a Python example"
# AI: "Here's a simple example using scikit-learn..."
# User: "How do I evaluate this model?"
# AI: "You can evaluate models using..."

Multi-line Input Example

# Start chat session
lc chat -m gpt-4

# Multi-line input example:
You: Please help me write a function that:
...  1. Takes a list of numbers
...  2. Filters out negative values
...  3. Returns the sum of remaining values
...
...  Also include error handling for empty lists.

# Press Shift+Enter or Ctrl+J to add new lines, Enter to send

Specialized Chat Sessions

Code Review

lc chat -s "You are an expert code reviewer" -v codebase
# Attach files for review
lc chat -a "src/main.py" -s "Review this code"

Research Assistant

lc chat -v research-papers -m gpt-4 -s "You are a research assistant"

Troubleshooting

lc chat -v docs -t diagnostic -s "Help debug issues"

Troubleshooting

Common Issues

"Session expired"

• Error: Chat session has timed out
• Solution: Restart the chat session with lc chat
• Resume: Use lc chat -c to continue last session
• Specific: Use lc chat --cid <ID> for specific session

"Provider not available"

• Error: Selected provider is offline or misconfigured
• Solution: Verify provider configuration with lc providers list
• Check: Ensure API keys are set with lc keys list

"Model not found"

• Error: Specified model doesn't exist for provider
• Solution: Use lc models -q <name> to find available models
• Alternative: Try different model or provider

"Context too long"

• Error: Conversation exceeds model's context limit
• Solution: Start new session or use model with larger context
• Manage: Use shorter responses or summarize conversation

Input Controls

The chat interface supports multi-line input for complex messages:

• Enter - Send the current message
• Shift+Enter or Ctrl+J - Add a new line (multi-line input)
• Ctrl+C - Cancel current input and return to prompt
• Backspace - Delete characters or move to previous line
• Arrow Keys - Navigate within the current line (basic support)

Chat Interface Commands

Within a chat session, you can use these commands:

• /exit or /quit - End the chat session
• /clear - Clear conversation history
• /help - Show available commands and input controls
• /model <name> - Switch to different model
• /system <prompt> - Set new system prompt

Performance Tips

1. Use appropriate models: Choose models based on task complexity
2. Manage context: Keep conversations focused to avoid context limits
3. Leverage RAG: Use vector databases for relevant context
4. Batch related questions: Ask related questions in same session

Security Considerations

• Chat sessions may contain sensitive information
• Review conversation logs before sharing
• Use secure connections for remote providers
• Consider local models for sensitive topics

# Secure chat setup
lc chat -m local-model -v private-docs

Best Practices

1. Clear objectives: Start with specific goals for the conversation
2. Context setting: Use system prompts to set appropriate context
3. Iterative refinement: Build on previous responses for better results
4. Session management: Use continuation features for long workflows

See Also

• Providers Command
• Models Command
• MCP Command
• Vectors Command
• Logs Command