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from flask import Flask, request, jsonify
import requests
from typing import List, Dict, Union
import json
app = Flask(__name__)
models = ['cognitivecomputations/dolphin-2.6-mixtral-8x7b', 'databricks/dbrx-instruct', 'google/gemma-1.1-7b-it', 'HuggingFaceH4/zephyr-orpo-141b-A35b-v0.1', 'lizpreciatior/lzlv_70b_fp16_hf', 'meta-llama/Meta-Llama-3-70B-Instruct', 'meta-llama/Meta-Llama-3-8B-Instruct', 'microsoft/WizardLM-2-7B', 'microsoft/WizardLM-2-8x22B', 'mistralai/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mixtral-8x22B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.2', 'openchat/openchat-3.6-8b']
class LLM:
def __init__(self, model: str):
self.model = model
self.conversation_history = [{"role": "system", "content": "You are a Helpful AI."}]
def chat(self, messages: List[Dict[str, str]], system_message: str = None) -> Union[str, None]:
if system_message is not None:
self.conversation_history.insert(0, {"role": "system", "content": system_message})
all_messages = self.conversation_history + messages
url = "https://api.deepinfra.com/v1/openai/chat/completions"
headers = {
'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36',
'Accept-Language': 'en,fr-FR;q=0.9,fr;q=0.8,es-ES;q=0.7,es;q=0.6,en-US;q=0.5,am;q=0.4,de;q=0.3',
'Cache-Control': 'no-cache',
'Connection': 'keep-alive',
'Content-Type': 'application/json',
'Origin': 'https://deepinfra.com',
'Pragma': 'no-cache',
'Referer': 'https://deepinfra.com/',
'Sec-Fetch-Dest': 'empty',
'Sec-Fetch-Mode': 'cors',
'Sec-Fetch-Site': 'same-site',
'X-Deepinfra-Source': 'web-embed',
'accept': 'text/event-stream',
'sec-ch-ua': '"Google Chrome";v="119", "Chromium";v="119", "Not?A_Brand";v="24"',
'sec-ch-ua-mobile': '?0',
'sec-ch-ua-platform': '"macOS"'
}
data = json.dumps(
{
'model': self.model,
'messages': all_messages,
'temperature': 0.7,
'max_tokens': 8028,
'stop': [],
'stream': False
}, separators=(',', ':')
)
try:
result = requests.post(url=url, data=data, headers=headers)
return result.json()['choices'][0]['message']['content']
except:
return None
def GenerativeIO(text, Model, System_Prompt):
llm = LLM(model=Model)
messages = [
{"role": "system", "content": text},
{"role": "user", "content": System_Prompt}
]
response = llm.chat(messages)
return response
@app.route('/generate', methods=['POST'])
def generate():
data = request.get_json()
text = data.get('text')
Model = data.get('Model')
System_Prompt = data.get('System_Prompt')
response = GenerativeIO(text, Model, System_Prompt)
return jsonify({'response': response})
@app.route('/models', methods=['GET'])
def get_models():
return jsonify(models)
if __name__ == '__main__':
app.run()
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