main.py

import gevent.pywsgi
from gevent import monkey;monkey.patch_all()
from flask import Flask, request, Response, jsonify
import argparse
import requests
import random
import string
import time
import json
import os

app = Flask(__name__)
app.json.sort_keys = False

parser = argparse.ArgumentParser(description="An example of minimax demo with a similar API to OAI.")
parser.add_argument("--host", type=str, help="Set the ip address.(default: 0.0.0.0)", default='0.0.0.0')
parser.add_argument("--port", type=int, help="Set the port.(default: 7860)", default=7860)
args = parser.parse_args()

base_url = os.getenv('MODEL_BASE_URL')

@app.route('/api/v1/models', methods=["GET", "POST"])
@app.route('/v1/models', methods=["GET", "POST"])
def model_list():
    time_now = int(time.time())
    model_list = {
        "object": "list",
        "data": [
            {
                "id": "MiniMax-Text-01",
                "object": "model",
                "created": time_now,
                "owned_by": "minimax"
            },
            {
                "id": "gpt-3.5-turbo",
                "object": "model",
                "created": time_now,
                "owned_by": "openai"
            }
        ]
    }
    return jsonify(model_list)

@app.route("/", methods=["GET"])
def index():
    return Response(f'Minimax OpenAI Compatible API<br><br>'+
        f'Set "{os.getenv("SPACE_URL")}/api" as proxy (or API Domain) in your Chatbot.<br><br>'+
        f'The complete API is: {os.getenv("SPACE_URL")}/api/v1/chat/completions')

@app.route("/api/v1/chat/completions", methods=["POST", "OPTIONS"])
@app.route("/v1/chat/completions", methods=["POST", "OPTIONS"])
def chat_completions():

    if request.method == "OPTIONS":
        return Response(
            headers={
                "Access-Control-Allow-Origin": "*",
                "Access-Control-Allow-Headers": "*",
            }
        )

    data = request.get_json()
    
    # reorganize data
    system = None
    chat_history = []
    prompt = ""
    
    if "messages" in data:
        messages = data["messages"]
        message_size = len(messages)
        
        prompt = messages[-1].get("content")
        
        # gen a random char(11) hash
        chars = string.ascii_lowercase + string.digits
        session_hash = "".join(random.choice(chars) for _ in range(10))
        
        single_prompt_data = {
            'data': [
                prompt,
                None,
            ],
            'event_data': None,
            'fn_index': 0,
            'trigger_id': 7,
            'session_hash': session_hash,
        }
        response = requests.post(f'{base_url}/gradio_api/run/predict', json=single_prompt_data)
        
        context_data = {
            'data': [
                None,
                messages,
                1000000,
                data['temperature'],
                data['top_p'],
            ],
            'event_data': None,
            'fn_index': 2,
            'trigger_id': 7,
            'session_hash': session_hash,
        }
        response = requests.post(f'{base_url}/gradio_api/queue/join', json=context_data)
        
    def generate():

        url = f"{base_url}/gradio_api/queue/data?session_hash={session_hash}"
        data = requests.get(url, stream=True)

        time_now = int(time.time())

        for line in data.iter_lines():
            if line:
                decoded_line = line.decode("utf-8")
                json_line = json.loads(decoded_line[6:])
                if json_line["msg"] == "process_starts":
                    res_data = gen_res_data({}, time_now=time_now, start=True)
                    yield f"data: {json.dumps(res_data)}\n\n"
                elif json_line["msg"] == "process_generating":
                    res_data = gen_res_data(json_line, time_now=time_now)
                    yield f"data: {json.dumps(res_data)}\n\n"
                elif json_line["msg"] == "process_completed":
                    yield "data: [DONE]"

    return Response(
        generate(),
        mimetype="text/event-stream",
        headers={
            "Access-Control-Allow-Origin": "*",
            "Access-Control-Allow-Headers": "*",
        },
    )


def gen_res_data(data, time_now=0, start=False):
    res_data = {
        "id": "chatcmpl",
        "object": "chat.completion.chunk",
        "created": time_now,
        "model": "MiniMax-Text-01",
        "choices": [{"index": 0, "finish_reason": None}],
    }

    if start:
        res_data["choices"][0]["delta"] = {"role": "assistant", "content": ""}
    else:
        chat_pair = data["output"]["data"][0]
        
        if chat_pair == []:
            res_data["choices"][0]["finish_reason"] = "stop"
        else:
            try:
                res_data["choices"][0]["delta"] = {"content": chat_pair[-1][-1]}
            except:
                res_data["choices"][0]["delta"] = {"content": chat_pair[-1]["content"]}
    return res_data


if __name__ == "__main__":
    #app.run(host=args.host, port=args.port, debug=True)
    gevent.pywsgi.WSGIServer((args.host, args.port), app).serve_forever()