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ad89eb2 27c7f8a 4ef8a32 ad89eb2 e67f3b2 bc93908 a1997e0 ad89eb2 abac9ba 27c7f8a abac9ba 27c7f8a 5ee100a 27c7f8a dc3b37b 4ef8a32 e67f3b2 4ef8a32 e67f3b2 4ef8a32 27c7f8a 4ef8a32 ad89eb2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 | from flask import Flask, request, jsonify
from mistral import Mistral7B
from gpt import ChatGpt
from news import News
from datetime import datetime
from os import listdir
from web import Online_Scraper
import requests
import google.generativeai as genai
from time import time as t
app = Flask(__name__)
generation_config = {
"temperature": 0.7,
"top_p": 1,
"top_k": 1,
"max_output_tokens": 512,
}
safety_settings = [
{
"category": "HARM_CATEGORY_HARASSMENT",
"threshold": "BLOCK_MEDIUM_AND_ABOVE"
},
{
"category": "HARM_CATEGORY_HATE_SPEECH",
"threshold": "BLOCK_MEDIUM_AND_ABOVE"
},
{
"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
"threshold": "BLOCK_MEDIUM_AND_ABOVE"
},
{
"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
"threshold": "BLOCK_MEDIUM_AND_ABOVE"
},
]
model = genai.GenerativeModel(
model_name="gemini-pro",
generation_config=generation_config,
safety_settings=safety_settings)
@app.route('/mistral7b', methods=['POST'])
def generate():
# Get data from the request
data = request.json
prompt = data.get('prompt', '')
messages = data.get('messages', [])
key = data.get('key', '')
# Call Mistral7B function
response, updated_messages, execution_time = Mistral7B(prompt, messages,key)
# Prepare the response
result = {
'response': response,
'messages': updated_messages,
'execution_time': execution_time
}
return jsonify(result)
@app.route('/chatgpt', methods=['POST'])
def chat():
# Get data from the request
data = request.json
user_message = data.get('message', '')
messages = data.get('messages', [])
# Call ChatGpt function
response, updated_messages, execution_time = ChatGpt(user_message, messages)
# Prepare the response
result = {
'response': response,
'messages': updated_messages,
'execution_time': execution_time
}
return jsonify(result)
@app.route('/news', methods=['GET'])
def get_news():
# Get data from the request
key = request.args.get('key', '')
cache_flag = request.args.get('cache', 'True').lower() == 'true'
# Call News function
news, error, execution_time = News(key, cache_flag)
# Prepare the response
result = {
'news': news,
'error': error,
'execution_time': execution_time
}
return jsonify(result)
@app.route('/web', methods=['GET'])
def Web():
key = request.args.get('prompt', '')
result = {
'response': Online_Scraper(key)
}
return jsonify(result)
@app.route('/imageneration', methods=['POST'])
def IMGEN():
data = request.json
prompt = data.get('prompt', '')
key = data.get('key', '')
API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-2-1"
headers = {"Authorization": f"Bearer {key}"}
return requests.post(API_URL, headers=headers, json={"inputs": prompt,}).content
@app.route('/generativeai', methods=['POST'])
def Genration():
global model,safety_settings,generation_config
data = request.json
prompt = data.get('prompt', '')
messages = data.get('messages', [])
key = data.get('key', '')
C=t()
genai.configure(api_key=key)
genai.configure(api_key=key)
response = model.generate_content(messages)
# Prepare the response
result = {
'response': response.text,
'execution_time': t()-C
}
return jsonify(result)
@app.route('/divyanshpizza', methods=['GET'])
def get_counters():
return jsonify(counter),jsonify({"data":str(listdir(r"static/data/"))})
if __name__ == '__main__':
app.run()
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