Joakim Persson
54 lines
1.4 KiB
Python
54 lines
1.4 KiB
Python
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# Import the necessary functions from ollama, Flask, requests, threading
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from ollama import Client
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from flask import Flask, request, jsonify
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#import requests
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#import threading
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# Initialize a Flask application
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app = Flask(__name__)
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def get_response(user_query):
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# Create a client object for interacting with OLLAMA API
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client = Client()
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# Generate and retrieve the response based on user's query
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response = client.generate_response(user_query)
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# Return the generated response
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return response
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def run_flask():
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# Flask endpoint for user interaction
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app.run(port=5000, debug=True)
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@app.route('/smartassist', methods=['POST'])
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def smartassist():
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# Extract the query from the incoming JSON data
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data = request.json
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user_query = data['query']
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# Get the response from the OLLAMA API based on the user's query
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# NOTE: Should we append message history here? Maybe interact with SQLlite?
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response = get_response(user_query)
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# Return the response as a JSON object in the HTTP response
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return jsonify({"response": response})
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@app.route('/api/chat', methods=['POST'])
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def chat():
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data = request.get_json()
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query = data['query']
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response = requests.post('http://ollama-server/api/v1/chat', json={'prompt': query})
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return jsonify({'response': response.json().get('result')})
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if __name__ == '__main__':
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# Run the Flask application
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run_flask()
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