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import json | |
import os | |
from datetime import date, datetime | |
from pathlib import Path | |
import plotly.graph_objects as go | |
from dotenv import load_dotenv | |
from fastapi import Depends, FastAPI, Request | |
from fastapi.middleware.cors import CORSMiddleware | |
from fastapi.responses import HTMLResponse, Response | |
from fastapi.staticfiles import StaticFiles | |
from fastapi.templating import Jinja2Templates | |
from mistralai.client import ChatMessage, MistralClient | |
from pydantic import BaseModel | |
from weather import get_weather | |
# code that gives the date of today | |
today = date.today() | |
today = today.strftime("%Y-%m-%d") | |
# Hugging face space secret retrieval: | |
def create_env_file(): | |
import os | |
secrets = ['MISTRAL_API_KEY', 'AGRO_API_KEY', 'OPENCAGE_API_KEY'] | |
for secret in secrets: | |
secret_value = os.environ[secret] | |
if secret_value is None: | |
print(f"Please set the environment variable {secret}") | |
else: | |
with open('.env', 'a') as f: | |
f.write(f"{secret}={secret_value}\n") | |
# Hugging face space secret retrieval: | |
production = False | |
if production: | |
create_env_file() | |
# Load environment variables | |
load_dotenv() | |
api_key = os.getenv('MISTRAL_API_KEY') | |
client = MistralClient(api_key=api_key) | |
model = 'mistral-small' | |
title = "Gaia Mistral Chat Demo" | |
description = "Example of simple chatbot with Gradio and Mistral AI via its API" | |
placeholder = "Posez moi une question sur l'agriculture" | |
examples = ["Comment fait on pour produire du maïs ?", | |
"Rédige moi une lettre pour faire un stage dans une exploitation agricole", "Comment reprendre une exploitation agricole ?"] | |
# create a FastAPI app | |
app = FastAPI() | |
# Add CORS middleware | |
app.add_middleware( | |
CORSMiddleware, | |
allow_origins=["*"], # Allows all origins | |
allow_credentials=True, | |
allow_methods=["*"], # Allows all methods | |
allow_headers=["*"], # Allows all headers | |
) | |
# create a static directory to store the static files | |
static_dir = Path('./static') | |
static_dir.mkdir(parents=True, exist_ok=True) | |
# mount FastAPI StaticFiles server | |
app.mount("/static", StaticFiles(directory=static_dir), name="static") | |
# templating | |
templates = Jinja2Templates(directory="static") | |
def create_world_map(lat, lon): | |
fig = go.Figure(go.Scattermapbox( | |
lat=[lat], | |
lon=[lon], | |
mode='markers', | |
marker=go.scattermapbox.Marker(size=14), | |
text=['Location'], | |
)) | |
fig.update_layout( | |
mapbox_style="open-street-map", | |
hovermode='closest', | |
mapbox=dict( | |
bearing=0, | |
center=go.layout.mapbox.Center( | |
lat=lat, | |
lon=lon, | |
), | |
pitch=0, | |
zoom=5 | |
), | |
) | |
return fig | |
def chat_with_mistral(user_input): | |
messages = [ChatMessage(role="user", content=user_input)] | |
chat_response = client.chat(model=model, messages=messages) | |
return chat_response.choices[0].message.content | |
# Profile stuff | |
class UserProfile(BaseModel): | |
name: str | |
age: int | |
location: str | |
lat: float | |
lon: float | |
class UserLocation(BaseModel): | |
city: str | |
class Weather(BaseModel): | |
temperature: float | |
weather: str | |
def save_user_profile(user_profile: UserProfile): | |
with open('user_profile.json', 'w') as f: | |
json.dump(user_profile.dict(), f) | |
return user_profile.dict() | |
def load_user_profile(): | |
with open('user_profile.json', 'r') as f: | |
user_profile = json.load(f) | |
return UserProfile(**user_profile) | |
def update_user_profile(user_profile: UserProfile): | |
with open('user_profile.json', 'w') as f: | |
json.dump(user_profile.dict(), f) | |
return user_profile | |
def load_weather(): | |
with open('Weather.json', 'r') as f: | |
w = json.load(f) | |
return Weather(**w) | |
# Load user location | |
def load_user_location(): | |
with open('user_location.json', 'r') as f: | |
user_location = json.load(f) | |
return UserLocation(**user_location) | |
# Save weather information | |
def save_weather(weather: Weather): | |
with open('Weather.json', 'w') as f: | |
json.dump(weather.dict(), f) | |
async def set_user_location(user_location: UserLocation): | |
# Save the user location as a JSON file | |
with open('user_location.json', 'w') as f: | |
json.dump(user_location.dict(), f) | |
response = Response(headers={"Location": "/home"}) | |
response.status_code = 303 | |
return response | |
# load user profile on startup | |
user_profile = load_user_profile() | |
weather = load_weather() | |
async def enter_location(): | |
return """ | |
<h1>Welcome to Gaia Mistral Chat Demo</h1> | |
<p> Debug tool: API docs available at <a href="/docs">/docs</a></p> | |
<form id="locationForm"> | |
<label for="city">Enter your city:</label><br> | |
<input type="text" id="city" name="city"><br> | |
<input type="submit" value="Submit"> | |
</form> | |
<script> | |
document.getElementById('locationForm').addEventListener('submit', function(event) { | |
event.preventDefault(); | |
var city = document.getElementById('city').value; | |
fetch('/user_location', { | |
method: 'POST', | |
headers: { | |
'Content-Type': 'application/json', | |
}, | |
body: JSON.stringify({city: city}), | |
}) | |
.then(response => { | |
if (response.ok) { | |
window.location.href = "/home"; | |
} | |
}); | |
}); | |
</script> | |
""" | |
# Home page : using the user profile, display the weather and chat with Mistral AI | |
async def home( | |
request: Request, | |
user_profile: UserProfile = Depends(load_user_profile), | |
weather: Weather = Depends(load_weather), | |
): | |
with open('user_location.json', 'r') as f: | |
user_location = json.load(f) | |
# Get weather data for the user location | |
weather_data, lat, lon = get_weather(user_location['city'], today) | |
# Convert the keys to datetime objects | |
weather_times = {datetime.strptime( | |
time, '%Y-%m-%d %H:%M:%S'): info for time, info in weather_data.items()} | |
# Find the time closest to the current time | |
current_time = datetime.now() | |
closest_time = min(weather_times.keys(), | |
key=lambda time: abs(time - current_time)) | |
# Extract weather information for the closest time | |
weather_info = weather_times[closest_time] | |
# Extract temperature and weather from the weather information | |
temperature = float(weather_info.split( | |
', ')[1].split('°C')[0].split(': ')[1]) | |
weather = weather_info.split(', ')[2].split(': ')[1] | |
# Create a Weather object from the weather data | |
weather = Weather(temperature=temperature, weather=weather) | |
temperature = weather.temperature | |
weather = weather.weather | |
# create the map | |
fig = create_world_map(lat, lon) | |
# save the map as a file | |
map_file = static_dir / "map.html" | |
fig.write_html(str(map_file)) | |
# display the map | |
map_html = f'<iframe src="/static/map.html" width="100%" height="100%" ></iframe>' | |
return templates.TemplateResponse("layout.html", {"request": request, "user_profile": user_profile, "weather": weather, "map_html": map_html}) | |
class ChatInput(BaseModel): | |
user_input: str | |
async def chat(chat_input: ChatInput): | |
print(chat_input.user_input) | |
return chat_with_mistral(chat_input.user_input) | |