diff options
Diffstat (limited to 'packages/multillm-cli/src/multillm_cli')
| -rw-r--r-- | packages/multillm-cli/src/multillm_cli/main.py | 252 |
1 files changed, 209 insertions, 43 deletions
diff --git a/packages/multillm-cli/src/multillm_cli/main.py b/packages/multillm-cli/src/multillm_cli/main.py index b450b71..a38ebe6 100644 --- a/packages/multillm-cli/src/multillm_cli/main.py +++ b/packages/multillm-cli/src/multillm_cli/main.py @@ -65,6 +65,28 @@ BUILTIN_TOOLS = { "required": ["location"] } } + }, + "ask_user": { + "type": "function", + "function": { + "name": "ask_user", + "description": "Ask the user a question and get their response. Use this when you need user input or clarification.", + "parameters": { + "type": "object", + "properties": { + "question": { + "type": "string", + "description": "The question to ask the user" + }, + "options": { + "type": "array", + "items": {"type": "string"}, + "description": "Optional list of suggested answers (user can still provide their own)" + } + }, + "required": ["question"] + } + } } } @@ -118,10 +140,59 @@ def get_weather(location: str, unit: str = "celsius") -> dict: } +def ask_user(question: str, options: list[str] = None) -> dict: + """ + Ask the user a question and collect their response. + + This is an interactive tool that displays a question to the user + and waits for their input. + """ + print("\n" + "=" * 70, file=sys.stderr) + print("❓ QUESTION FROM ASSISTANT", file=sys.stderr) + print("=" * 70, file=sys.stderr) + print(f"\n{question}\n", file=sys.stderr) + + if options: + print("Suggested options:", file=sys.stderr) + for i, opt in enumerate(options, 1): + print(f" {i}. {opt}", file=sys.stderr) + print("\nYou can select a number or provide your own answer.", file=sys.stderr) + + print("\nYour answer: ", file=sys.stderr, end="", flush=True) + + try: + # Read from stdin + answer = input() + + # If user entered a number and we have options, use that option + if options and answer.strip().isdigit(): + idx = int(answer.strip()) - 1 + if 0 <= idx < len(options): + answer = options[idx] + + print("=" * 70 + "\n", file=sys.stderr) + + return { + "question": question, + "answer": answer, + "selected_from_options": answer in options if options else False + } + + except (EOFError, KeyboardInterrupt): + print("\n", file=sys.stderr) + print("=" * 70 + "\n", file=sys.stderr) + return { + "question": question, + "answer": None, + "error": "User cancelled input" + } + + TOOL_FUNCTIONS = { "get_current_time": get_current_time, "calculate": calculate, "get_weather": get_weather, + "ask_user": ask_user, } @@ -220,10 +291,78 @@ async def run_with_tools( return "Maximum tool calling iterations reached" -async def run_single(model: str, prompt: str, **kwargs) -> multillm.SingleResponse: - """Run a single query against the specified model.""" +async def run_agentic( + model: str, + prompt: str, + tools: list[multillm.Tool] | None = None, + options: multillm.AgentOptions | None = None, + verbose: bool = False +) -> str: + """ + Run a query using the agentic API. + + Uses agentwrap for chat providers, native agent API for agent providers. + """ client = multillm.Client() - return await client.single(model, prompt, **kwargs) + + # For Claude, if AskUserQuestion is requested, provide custom ask_user tool instead + provider_name = model.split("/")[0] + if provider_name == "claude" and options and options.allowed_tools: + if "AskUserQuestion" in options.allowed_tools: + # Remove AskUserQuestion (SDK built-in doesn't work interactively) + options.allowed_tools = [t for t in options.allowed_tools if t != "AskUserQuestion"] + + # Add our custom ask_user tool + if not tools: + tools = [] + + # Create ask_user tool for Claude + ask_user_claude = multillm.Tool( + name="ask_user", + description="Ask the user a question and get their response. Use this when you need user input or clarification.", + parameters={ + "type": "object", + "properties": { + "question": { + "type": "string", + "description": "The question to ask the user" + }, + "options": { + "type": "array", + "items": {"type": "string"}, + "description": "Optional suggested answers" + } + }, + "required": ["question"] + }, + handler=ask_user # Use the same handler as chat providers + ) + tools.append(ask_user_claude) + + print("ℹ️ Using custom 'ask_user' tool instead of AskUserQuestion for interactive prompting", file=sys.stderr) + + # Collect text responses + text_parts = [] + tool_uses = [] + + async for msg in client.run(model, prompt, options=options, tools=tools): + if msg.type == "text": + text_parts.append(msg.content) + elif msg.type == "tool_use": + tool_uses.append(msg) + if verbose: + print(f" → {msg.tool_name}({json.dumps(msg.tool_input)})", file=sys.stderr) + else: + print(f" → {msg.tool_name}", file=sys.stderr) + elif msg.type == "tool_result": + if verbose: + print(f" ← {msg.tool_result}", file=sys.stderr) + + # Show tool usage summary if any tools were used + if tool_uses and not verbose: + print(f"\n[Used {len(tool_uses)} tool(s)]\n", file=sys.stderr) + + return " ".join(text_parts) async def run_with_chat_tools( @@ -232,19 +371,34 @@ async def run_with_chat_tools( enabled_tools: list[str], verbose: bool = False ) -> str: - """Run with chat provider tools.""" - client = multillm.Client() - - # Build tool list from enabled tools - tools = [BUILTIN_TOOLS[name] for name in enabled_tools if name in BUILTIN_TOOLS] - - if not tools: - # No valid tools, just run normally - result = await run_single(model, prompt) - return result.text + """ + Run with chat provider tools using agentwrap. - # Run with tool loop - return await run_with_tools(client, model, prompt, tools, verbose) + Converts built-in tools to Tool objects and uses agentwrap for execution. + """ + # Build Tool objects from enabled tools + tool_objects = [] + for name in enabled_tools: + if name in BUILTIN_TOOLS: + tool_def = BUILTIN_TOOLS[name] + tool_objects.append(multillm.Tool( + name=tool_def["function"]["name"], + description=tool_def["function"]["description"], + parameters=tool_def["function"]["parameters"], + handler=TOOL_FUNCTIONS[name] + )) + + if not tool_objects: + # No valid tools, run without tools + return await run_agentic(f"agentwrap/{model}", prompt, verbose=verbose) + + # Run with agentwrap and tools + return await run_agentic( + f"agentwrap/{model}", + prompt, + tools=tool_objects, + verbose=verbose + ) def main(): @@ -254,18 +408,21 @@ def main(): formatter_class=argparse.RawDescriptionHelpFormatter, epilog=""" Examples: - # Chat providers (simple queries) + # Chat providers (simple queries) - uses agentwrap internally multillm -m openai/gpt-4o -p "What is 2+2?" multillm -m anthropic/claude-sonnet-4-20250514 -p "Explain async/await" multillm -m gemini/gemini-2.0-flash-exp -p "What is Python?" - # With built-in tools (for chat providers) + # With built-in tools (for chat providers) - uses agentwrap with tool execution multillm -m openai/gpt-4o -p "What time is it?" --use-tools get_current_time multillm -m openai/gpt-4o -p "Calculate 15 * 23" --use-tools calculate multillm -m openai/gpt-4o -p "What's the weather in Tokyo?" --use-tools get_weather multillm -m openai/gpt-4o -p "What's 5+5 and the current time?" --use-tools calculate get_current_time - # Agent providers (with tools) + # Interactive tools (ask user questions) + multillm -m openai/gpt-4o -p "Ask me about my preferences and create a summary" --use-tools ask_user + + # Native agent providers (Claude with built-in tools) multillm -m claude/default -p "What Python version?" --allowed-tools Bash multillm -m claude/default -p "List files" --allowed-tools Bash Glob --max-turns 5 multillm -m claude/default -p "Read README.md" --allowed-tools Read @@ -273,16 +430,23 @@ Examples: # With stdin cat file.txt | multillm -m openai/gpt-4o -p "Summarize:" --with-stdin - # Permission modes + # Permission modes (for native agents) multillm -m claude/default -p "Create hello.py" --allowed-tools Write --permission-mode acceptEdits # Verbose mode multillm -m openai/gpt-4o -p "Calculate 5*5" --use-tools calculate --verbose +Note: + - Chat providers (openai, google, anthropic, etc.) are automatically wrapped with + agentic capabilities using the 'agentwrap' provider + - Native agent providers (claude) use their built-in agentic features + - Use --use-tools for chat providers, --allowed-tools for native agents + Available Built-in Tools (for chat providers with --use-tools): get_current_time Get current date and time calculate Perform mathematical calculations get_weather Get weather information (mock data) + ask_user Ask the user a question and get their response (interactive) Available Tools (for agent providers with --allowed-tools): Read, Write, Edit, Bash, Glob, Grep, Task, WebFetch, WebSearch, @@ -346,37 +510,39 @@ Available Tools (for agent providers with --allowed-tools): prompt = f"{prompt}\n--- USER STDIN BEGIN ---\n{stdin_content}" try: - # Check if this is a chat provider with tools + # Determine if this is a chat or agent provider + provider_name = args.model.split("/")[0] + is_agent_provider = provider_name in ["claude"] # Native agent providers + if args.use_tools: - # Use tool calling workflow for chat providers + # Use tool calling workflow for chat providers with agentwrap result_text = asyncio.run( run_with_chat_tools(args.model, prompt, args.use_tools, args.verbose) ) print(result_text) else: - # Build kwargs for agent options - kwargs = {} - if args.max_turns is not None: - kwargs["max_turns"] = args.max_turns - if args.allowed_tools: - kwargs["allowed_tools"] = args.allowed_tools - if args.permission_mode: - kwargs["permission_mode"] = args.permission_mode - - # Use single() for normal queries or agent providers - result = asyncio.run(run_single(args.model, prompt, **kwargs)) - - # Show tool usage for agent providers (inline) - if result.tool_calls: - print(f"\n[Agent used {len(result.tool_calls)} tool(s)]") - for tc in result.tool_calls: - if args.verbose: - print(f" → {tc['function']['name']}({json.dumps(tc['function'].get('arguments', {}))})") - else: - print(f" → {tc['function']['name']}") - print() + # Build agent options + options = None + if args.max_turns is not None or args.allowed_tools or args.permission_mode: + options = multillm.AgentOptions( + max_turns=args.max_turns, + allowed_tools=args.allowed_tools, + permission_mode=args.permission_mode, + ) + + # Determine which model string to use + if is_agent_provider: + # Use agent provider directly (claude) + model_to_use = args.model + else: + # Use agentwrap for chat providers + model_to_use = f"agentwrap/{args.model}" - print(result.text) + # Run with agentic API + result_text = asyncio.run( + run_agentic(model_to_use, prompt, options=options, verbose=args.verbose) + ) + print(result_text) except Exception as e: print(f"Error: {e}", file=sys.stderr) |