Example of using deepseek (ollama - local) with some external API using json_schema

main.py

from pydantic import BaseModel, Field
from datetime import date
import ollama
import requests
import json
import pandas as pd


class Query(BaseModel):
    """Data that we want collect from user to get weather data"""
    place: str = Field(description="The city/address/POI where the temperature is being asked for")
    countryCode: str = Field(description="The country ISO code where is being asked for")
    start_date: date = Field(description="The start date of asked period if not detected the same as end date")
    end_date: date = Field(description="The start date of asked period")


def get_weather_data(user_input: str) -> dict:
    response = ollama.chat(
        model='deepseek-r1:7b',
        messages=[
            {'role': 'user', 'content': 'get basic structure of this query:' + user_input},
        ],
        format=Query.model_json_schema()
    )
    return json.loads(response['message']['content'])


def ask_for_missing_properties(weather_data: dict) -> str:
    response = ollama.chat(
        model='deepseek-r1:7b',
        messages=[
            {'role': 'user', 'content': 'Ask for missing information :' + str(weather_data)},
        ],
    )
    return response['message']['content']


def create_summary(user_input: str, info: dict) -> str:
    response = ollama.chat(
        model='deepseek-r1:7b',
        messages=[
            {'role': 'user', 'content': 'answer for question :' + user_input + ' using this data in one short sentence' + str(info)},
        ],
    )
    resp = response['message']['content']
    # remove all befoe '</think>' tag
    return resp.split('</think>')[1].strip()


def get_location_info(weather_data: dict) -> dict:
    query = weather_data['place'] + "," + weather_data['countryCode']
    url = "https://nominatim.openstreetmap.org/search"
    params = {
        'q': query,
        'format': 'json',
        'limit': 1
    }
    response = requests.get(url, params=params, headers={'User-Agent': 'Mozilla/5.0'})
    return response.json()[0]


def get_weather_info(location: dict, weather_data: dict) -> dict:
    url = "https://archive-api.open-meteo.com/v1/archive"
    params = {
        'latitude': location['lat'],
        'longitude': location['lon'],
        'start_date': weather_data['start_date'],
        'end_date': weather_data['end_date'],
        'hourly': 'temperature_2m',
        'timezone': 'auto'
    }
    response = requests.get(url, params=params, headers={'User-Agent': 'Mozilla/5.0'})
    data = response.json()['hourly']
    df = pd.DataFrame(data)
    df['date'] = pd.to_datetime(df['time']).dt.date
    df = df.groupby('date').agg({'temperature_2m': ['min', 'max']})
    return df.to_dict()


if __name__ == "__main__":
    user_input = input("Ask for some weather data: ")
    weather_data = get_weather_data(user_input)
    print(weather_data)
    location = get_location_info(weather_data)
    info = get_weather_info(location, weather_data)
    print(create_summary(user_input, info))

This is using ollama with ollama pull deepseek-r1:7b