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# tools | ||
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This example demonstrates how to utilize tool calls with an asynchronous Ollama client and the chat endpoint. |
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import json | ||
import ollama | ||
import asyncio | ||
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# Simulates an API call to get flight times | ||
# In a real application, this would fetch data from a live database or API | ||
def get_flight_times(departure: str, arrival: str) -> str: | ||
flights = { | ||
'NYC-LAX': {'departure': '08:00 AM', 'arrival': '11:30 AM', 'duration': '5h 30m'}, | ||
'LAX-NYC': {'departure': '02:00 PM', 'arrival': '10:30 PM', 'duration': '5h 30m'}, | ||
'LHR-JFK': {'departure': '10:00 AM', 'arrival': '01:00 PM', 'duration': '8h 00m'}, | ||
'JFK-LHR': {'departure': '09:00 PM', 'arrival': '09:00 AM', 'duration': '7h 00m'}, | ||
'CDG-DXB': {'departure': '11:00 AM', 'arrival': '08:00 PM', 'duration': '6h 00m'}, | ||
'DXB-CDG': {'departure': '03:00 AM', 'arrival': '07:30 AM', 'duration': '7h 30m'}, | ||
} | ||
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key = f'{departure}-{arrival}'.upper() | ||
return json.dumps(flights.get(key, {'error': 'Flight not found'})) | ||
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async def run(model: str): | ||
client = ollama.AsyncClient() | ||
# Initialize conversation with a user query | ||
messages = [{'role': 'user', 'content': 'What is the flight time from New York (NYC) to Los Angeles (LAX)?'}] | ||
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# First API call: Send the query and function description to the model | ||
response = await client.chat( | ||
model=model, | ||
messages=messages, | ||
tools=[ | ||
{ | ||
'type': 'function', | ||
'function': { | ||
'name': 'get_flight_times', | ||
'description': 'Get the flight times between two cities', | ||
'parameters': { | ||
'type': 'object', | ||
'properties': { | ||
'departure': { | ||
'type': 'string', | ||
'description': 'The departure city (airport code)', | ||
}, | ||
'arrival': { | ||
'type': 'string', | ||
'description': 'The arrival city (airport code)', | ||
}, | ||
}, | ||
'required': ['departure', 'arrival'], | ||
}, | ||
}, | ||
}, | ||
], | ||
) | ||
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# Add the model's response to the conversation history | ||
messages.append(response['message']) | ||
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# Check if the model decided to use the provided function | ||
if not response['message'].get('tool_calls'): | ||
print("The model didn't use the function. Its response was:") | ||
print(response['message']['content']) | ||
return | ||
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# Process function calls made by the model | ||
if response['message'].get('tool_calls'): | ||
available_functions = { | ||
'get_flight_times': get_flight_times, | ||
} | ||
for tool in response['message']['tool_calls']: | ||
function_to_call = available_functions[tool['function']['name']] | ||
function_response = function_to_call(tool['function']['arguments']['departure'], tool['function']['arguments']['arrival']) | ||
# Add function response to the conversation | ||
messages.append( | ||
{ | ||
'role': 'tool', | ||
'content': function_response, | ||
} | ||
) | ||
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# Second API call: Get final response from the model | ||
final_response = await client.chat(model=model, messages=messages) | ||
print(final_response['message']['content']) | ||
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# Run the async function | ||
asyncio.run(run('mistral')) |
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