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#!/usr/bin/env python
# COPYRIGHT 2025 Thomas Grothe
import argparse
import os
import sys
import json
import ai_api_module
#this is the CLI program used to interact with the GAI python module.
default_model = "gemini-2.0-flash-exp"
def main():
"""Main function to parse arguments and execute commands"""
parser = argparse.ArgumentParser(description="CLI for calling AI APIs with file attachment support")
parser.add_argument(
"--apikey", default=os.getenv("GEMINI_API_KEY"), help="API key for the service"
)
parser.add_argument("--modelid", default=default_model, help=f"ID of the model to use (default={default_model})")
parser.add_argument("--list-models", action="store_true", help="list the available models")
# Conversation management
parser.add_argument("--new", "-n", action="store_true", help="Start a new conversation")
parser.add_argument("--save-conversation", metavar="FILE", help="Save conversation to file")
parser.add_argument("--load-conversation", metavar="FILE", help="Load conversation from file")
parser.add_argument("--list-conversations", action="store_true", help="List saved conversations")
parser.add_argument("--clear", action="store_true", help="Clear conversation history")
parser.add_argument("--system-instruction", metavar="TEXT", help="Set system instruction for the conversation")
# Query parameters
parser.add_argument("--query", "-q", default="", help="Query to be sent to the assistant")
parser.add_argument("--topp", type=float, default=0.9, help="Top P value for the model")
parser.add_argument("--temperature", type=float, default=0.7, help="Temperature value for the model")
parser.add_argument("--max-tokens", type=int, default=8192, help="Maximum output tokens")
parser.add_argument("--stream", action="store_true", help="Enable streaming response")
parser.add_argument("--no-stream", action="store_true", help="Disable streaming response")
parser.add_argument("--output_mode", "-o", default='text', help="Output mode (text or json)")
parser.add_argument("--count-tokens", action="store_true", help="Count tokens in query without sending")
parser.add_argument("extra_query", nargs="*")
args = parser.parse_args()
# Get API key
if args.apikey:
ai_api_module.api_key = args.apikey
else:
ai_api_module.get_api_key()
if not ai_api_module.api_key:
print("Error: API key not provided. Set GEMINI_API_KEY environment variable.")
sys.exit(1)
# Handle system instruction
if args.system_instruction:
ai_api_module.set_system_instruction(args.system_instruction)
print(f"System instruction set")
# Handle conversation management
if args.new:
ai_api_module.clear_conversation()
print("Started new conversation")
if args.load_conversation:
if ai_api_module.load_conversation(args.load_conversation):
print(f"Loaded conversation from {args.load_conversation}")
else:
print(f"Failed to load conversation from {args.load_conversation}")
sys.exit(1)
if args.list_conversations:
success, result = ai_api_module.list_saved_conversations()
if success:
if not result:
print("No saved conversations found")
else:
print("Saved conversations:")
for conv in result:
print(f" {conv['filename']}")
print(f" Saved: {conv['saved_at']}")
print(f" Messages: {conv['message_count']}")
print()
else:
print(f"Error: {result}")
return
if args.clear:
ai_api_module.clear_conversation()
print("Conversation history cleared")
return
# List models
if args.list_models:
success, result = ai_api_module.list_models(args.output_mode)
if success:
for model in result:
if args.output_mode == 'json':
print(json.dumps(model, indent=2))
else:
print(f"Model: {model['display_name']}")
print(f" Name: {model['name']}")
print(f" Description: {model.get('description', 'N/A')}")
print(f" Input tokens: {model.get('input_token_limit', 'N/A')}")
print(f" Output tokens: {model.get('output_token_limit', 'N/A')}")
print()
else:
print(f'Error: {result}')
return
# Process query
if args.query or args.extra_query:
query = args.query
if args.extra_query:
if query:
query += " " + " ".join(args.extra_query)
else:
query = " ".join(args.extra_query)
# Count tokens if requested
if args.count_tokens:
success, count = ai_api_module.count_tokens(args.modelid, query)
if success:
print(f"Token count: {count}")
else:
print(f"Error counting tokens: {count}")
return
# Determine streaming
use_stream = args.stream and not args.no_stream
response = ai_api_module.query(
args.modelid,
query,
args.topp,
args.temperature,
use_stream,
args.max_tokens,
)
if response and not use_stream:
print(response)
# Auto-save conversation if requested
if args.save_conversation:
filepath = ai_api_module.save_conversation(args.save_conversation)
print(f"\nConversation saved to {filepath}")
else:
parser.print_help()
if __name__ == "__main__":
main()
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