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Refaktoriseringar och test av alternativa lösningar.

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Joakim Persson
2024-07-16 23:16:39 +02:00
parent 99e3737718
commit 3fef179723
4 changed files with 115 additions and 54 deletions
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smartassist/src/backend.py
+34 -20
View File
@@ -2,26 +2,23 @@
# Import the necessary functions from ollama, Flask, requests, threading
from ollama import Client
from flask import Flask, request, jsonify
#import requests
import requests
#import threading
# Initialize a Flask application
app = Flask(__name__)
def get_response(user_query):
# Create a client object for interacting with OLLAMA API
client = Client()
# Generate and retrieve the response based on user's query
response = client.generate_response(user_query)
# Return the generated response
return response
def run_flask():
# Flask endpoint for user interaction
app.run(port=5000, debug=True)
@app.route('/api/chat', methods=['POST'])
def chat():
# Get the message from the JSON in the request body
data = request.get_json()
message = data.get('query')
if message:
response = requests.post('localhost::11434', json={"model": "llama3",'prompt': message})
return jsonify({'response': response.json().get('result')})
else:
return jsonify({'error': 'No query provided'}), 400
@app.route('/smartassist', methods=['POST'])
@@ -37,13 +34,30 @@ def smartassist():
# Return the response as a JSON object in the HTTP response
return jsonify({"response": response})
def get_response(user_query):
# Create a client object for interacting with OLLAMA API
client = Client()
# Generate and retrieve the response based on user's query
response = client.generate_response(user_query)
# Return the generated response
return response
def run_flask():
# Flask endpoint for user interaction
app.run(port=5000, debug=True)
# app.run(port=5000, debug=True, use_reloader=False)
# @app.route('/api/chat', methods=['POST'])
# def chat():
# data = request.get_json()
# query = data['query']
# # response = requests.post('http://ollama-server/api/v1/chat', json={'prompt': query})
# response = requests.post('localhost::11434', json={"model": "llama3",'prompt': query})
# return jsonify({'response': response.json().get('result')})
@app.route('/api/chat', methods=['POST'])
def chat():
data = request.get_json()
query = data['query']
response = requests.post('http://ollama-server/api/v1/chat', json={'prompt': query})
return jsonify({'response': response.json().get('result')})
if __name__ == '__main__':
smartassist/src/client.html
+5 -4
View File
@@ -1,7 +1,8 @@
<!-->
<!--
Run a simple HTTP server in the directory containing your HTML file
python -m http.server 8000
Open your web browser and navigate to http://localhost:8000/client.html
Open your web browser and navigate to http://localhost:8000/smartassist/src/client.html
Note that the path starts from where the python venv was defined (project root)
-->
<!DOCTYPE html>
@@ -24,12 +25,12 @@ Open your web browser and navigate to http://localhost:8000/client.html
margin-bottom: 10px;
}
.user-message {
background-color: #f0f0f0;
background-color: #eae2d5;
padding: 10px;
border-radius: 10px;
}
.ai-response {
background-color: #ccc;
background-color: #cfc68b;
padding: 10px;
border-radius: 10px;
}
smartassist/src/frontend.js
+50 -23
View File
@@ -4,36 +4,63 @@ const chatbox = document.getElementById('chatbox');
const userInput = document.getElementById('userInput');
// Define a function to send the user's message to the AI
// function sendMessage() {
// // Get the user's input message and trim any whitespace
// const message = userInput.value.trim();
// // Check if the message is not empty
// if (message !== '') {
// // Send a POST request to the /api/chat endpoint with the message
// fetch('/api/chat', {
// method: 'POST',
// headers: { 'Content-Type': 'application/json' },
// body: JSON.stringify({ message }),
// })
// .then(response => response.json())
// .then(data => {
// // Get the AI's response from the API data
// const aiResponse = data.response;
// // Render the user's original message in the chatbox
// renderMessage(message, 'user-message');
// // Render the AI's response in the chatbox
// renderMessage(aiResponse, 'ai-response');
// // Clear the user input field for the next message
// userInput.value = '';
// })
// .catch(error => console.error('Error sending message:', error));
// }
// }
function sendMessage() {
// Get the user's input message and trim any whitespace
const message = userInput.value.trim();
const message = userInput.value.trim();
if (message !== '') {
// Create a new XMLHttpRequest object
const xhr = new XMLHttpRequest();
// Check if the message is not empty
if (message !== '') {
// Send a POST request to the /api/chat endpoint with the message
fetch('/api/chat', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ message }),
})
.then(response => response.json())
.then(data => {
// Get the AI's response from the API data
const aiResponse = data.response;
// Configure the request
xhr.open('POST', '/api/chat'); // Set method to POST and URL
xhr.setRequestHeader('Content-Type', 'application/json'); // Essential for sending JSON
// Render the user's original message in the chatbox
renderMessage(message, 'user-message');
// Handle response data
xhr.onload = function() {
if (xhr.status >= 200 && xhr.status < 300) { // Successful response
const data = JSON.parse(xhr.responseText);
renderMessage(data.response, 'ai-response');
// Render the AI's response in the chatbox
renderMessage(aiResponse, 'ai-response');
} else {
console.error('Request failed. Status:', xhr.status);
}
};
// Clear the user input field for the next message
userInput.value = '';
})
.catch(error => console.error('Error sending message:', error));
}
// Send the request
xhr.send(JSON.stringify({ message }));
}
}
// Define a function to render a message in the chatbox with a specific class name
function renderMessage(text, className) {
// Create a new div element to hold the message
smartassist/src/startservices.py
+26 -7
View File
@@ -4,20 +4,39 @@ import threading
from backend import run_flask
import socket
def start_frontend():
try:
# Start frontend (web server) as a separate process
subprocess.Popen(["python", "-m", "http.server", "8000"])
except Exception as e:
print(f"Failed to start frontend: {e}")
host = 'localhost' # or the address of your server
port = 8000 # change to your server's port
# Use the socket module in Python to check whether a port is in use,
# which would indicate that a server is already running on that port.
with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
try:
s.bind((host, port))
print("No server is running on this host and port.")
# Start frontend (web server) as a separate process
subprocess.Popen(["python", "-m", "http.server", str(port)])
except socket.error as e:
if e.errno == 48:
print("Another server is already running on this host and port. Assumes it is a web server, will continue.")
else:
raise # Unexpected error, re-raise it so we can see the traceback
except Exception as e:
print(f"Failed to start frontend: {e}")
def start_backend():
try:
# Start backend as a separate thread
threading.Thread(target=run_flask).start()
# threading.Thread(target=run_flask).start() # Flask's built-in server doesn't support running in a separate thread.
run_flask()
except Exception as e:
print(f"Failed to start backend: {e}")
if __name__ == '__main__':
start_backend()
start_frontend()
start_backend()