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https://github.com/ollama/ollama-python.git
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49ed36bf47
- Create dedicated _tools.py module for better organization - Move tool-related functions from _utils.py to _tools.py (not including create_function_tool) - Rename tool getter functions for clarity: * get_ollama_tools_name * get_ollama_tools * get_ollama_name_async_tools - Add get_ollama_tool_description for enhanced AI context extraction (it returns a list with name and description, useful for adding to the "content" of the system) - Fix wrapper function metadata preservation using functools.wraps - Fix tool registration and lookup bugs found in tests - Add comprehensive test suite in test_tools.py - Improve code organization and modularity - Add proper docstring handling for tool descriptions This change improves the overall architecture of the tools system and adds better support for AI context understanding through proper function metadata and descriptions.
89 lines
2.8 KiB
Python
89 lines
2.8 KiB
Python
import asyncio
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from ollama import ChatResponse, chat
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from ollama import (
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ollama_tool,
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ollama_async_tool,
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get_ollama_tools,
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get_ollama_name_async_tools,
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get_ollama_tools_name,
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get_ollama_tool_description)
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@ollama_tool
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def add_two_numbers(a: int, b: int) -> int:
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"""
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Add two numbers
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Args:
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a (int): The first number
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b (int): The second number
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Returns:
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int: The sum of the two numbers
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"""
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return a + b
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@ollama_tool
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def subtract_two_numbers(a: int, b: int) -> int:
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"""
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Subtract two numbers
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Args:
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a (int): The first number
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b (int): The second number
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Returns:
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int: The difference of the two numbers
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"""
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return a - b
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@ollama_async_tool
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async def web_search(query: str) -> str:
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"""
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Search the web for information,
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Args:
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query (str): The query to search the web for
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Returns:
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str: The result of the web search
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"""
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return f"Searching the web for {query}"
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available_functions = get_ollama_tools_name() # this is a dictionary of tools
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# tools are treated differently in synchronous code
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async_available_functions = get_ollama_name_async_tools()
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messages = [
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{'role': 'system', 'content': f'You are a helpful assistant, with access to these tools: {get_ollama_tool_description()}'}, #usage example for the get_ollama_tool_description function
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{'role': 'user', 'content': 'What is three plus one? and Search the web for what is ollama'}]
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print('Prompt:', messages[1]['content'])
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response: ChatResponse = chat(
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'llama3.1',
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messages=messages,
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tools=get_ollama_tools(), # this is the list of tools using decorators
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)
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if response.message.tool_calls:
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# There may be multiple tool calls in the response
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for tool in response.message.tool_calls:
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# Ensure the function is available, and then call it
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if function_to_call := available_functions.get(tool.function.name):
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print('Calling function:', tool.function.name)
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print('Arguments:', tool.function.arguments)
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# if the function is in the list of asynchronous functions it is executed with asyncio.run()
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if tool.function.name in async_available_functions:
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output = asyncio.run(function_to_call(**tool.function.arguments))
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else:
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output = function_to_call(**tool.function.arguments)
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print('Function output:', output)
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else:
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print('Function', tool.function.name, 'not found')
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# Only needed to chat with the model using the tool call results
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if response.message.tool_calls:
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# Add the function response to messages for the model to use
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messages.append(response.message)
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messages.append({'role': 'tool', 'content': str(output), 'name': tool.function.name})
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# Get final response from model with function outputs
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final_response = chat('llama3.1', messages=messages)
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print('Final response:', final_response.message.content)
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else:
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print('No tool calls returned from model') |