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import argparse |
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from flask import Flask, jsonify, request, Response |
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import urllib.parse |
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import requests |
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import time |
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import json |
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app = Flask(__name__) |
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slot_id = -1 |
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parser = argparse.ArgumentParser(description="An example of using server.cpp with a similar API to OAI. It must be used together with server.cpp.") |
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parser.add_argument("--chat-prompt", type=str, help="the top prompt in chat completions(default: 'A chat between a curious user and an artificial intelligence assistant. The assistant follows the given rules no matter what.\\n')", default='A chat between a curious user and an artificial intelligence assistant. The assistant follows the given rules no matter what.\\n') |
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parser.add_argument("--user-name", type=str, help="USER name in chat completions(default: '\\nUSER: ')", default="\\GPT4 User:") |
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parser.add_argument("--ai-name", type=str, help="ASSISTANT name in chat completions(default: '\\nASSISTANT: ')", default="\\nGPT4 Assistant:") |
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parser.add_argument("--system-name", type=str, help="SYSTEM name in chat completions(default: '\\nASSISTANT's RULE: ')", default="") |
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parser.add_argument("--stop", type=str, help="the end of response in chat completions(default: '</s>')", default="<|end_of_turn|>") |
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parser.add_argument("--llama-api", type=str, help="Set the address of server.cpp in llama.cpp(default: http://rpoly1.ddns.net:8818)", default='http://rpoly1.ddns.net:8818') |
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parser.add_argument("--api-key", type=str, help="Set the api key to allow only few user(default: NULL)", default="") |
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parser.add_argument("--host", type=str, help="Set the ip address to listen.(default: 127.0.0.1)", default='0.0.0.0') |
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parser.add_argument("--port", type=int, help="Set the port to listen.(default: 8081)", default=7860) |
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args = parser.parse_args() |
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def is_present(json, key): |
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try: |
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buf = json[key] |
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except KeyError: |
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return False |
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if json[key] == None: |
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return False |
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return True |
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def convert_chat(messages): |
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prompt ="" |
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system_n = args.system_name.replace("\\n", "\n") |
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user_n = args.user_name.replace("\\n", "\n") |
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ai_n = args.ai_name.replace("\\n", "\n") |
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stop = args.stop.replace("\\n", "\n") |
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for line in messages[:-1]: |
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if (line["role"] == "system"): |
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prompt += f"{system_n}{line['content']}{stop}" |
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if (line["role"] == "user"): |
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prompt += f"{user_n}{line['content']}{stop}" |
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if (line["role"] == "assistant"): |
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prompt += f"{ai_n}{line['content']}{stop}" |
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if (messages[-1]["role"] == "user"): |
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prompt += f"{user_n}{messages[-1]['content']}{stop}" |
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prompt += f"{ai_n}" |
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elif (messages[-1]["role"] == "assistant"): |
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prompt += f"{ai_n}{messages[-1]['content']}" |
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prompt += ai_n.rstrip() |
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return prompt |
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def convert_chat1(messages): |
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prompt = "" + args.chat_prompt.replace("\\n", "\n") |
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system_n = args.system_name.replace("\\n", "\n") |
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user_n = args.user_name.replace("\\n", "\n") |
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ai_n = args.ai_name.replace("\\n", "\n") |
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stop = args.stop.replace("\\n", "\n") |
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for line in messages: |
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if (line["role"] == "system"): |
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prompt += f"{system_n}{line['content']}" |
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if (line["role"] == "user"): |
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prompt += f"{user_n}{line['content']}" |
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if (line["role"] == "assistant"): |
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prompt += f"{ai_n}{line['content']}{stop}" |
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prompt += ai_n.rstrip() |
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return prompt |
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def make_postData(body, chat=False, stream=False): |
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postData = {} |
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if (chat): |
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postData["prompt"] = convert_chat(body["messages"]) |
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else: |
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postData["prompt"] = body["prompt"] |
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if(is_present(body, "temperature")): postData["temperature"] = body["temperature"] |
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if(is_present(body, "top_k")): postData["top_k"] = body["top_k"] |
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if(is_present(body, "top_p")): postData["top_p"] = body["top_p"] |
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if(is_present(body, "max_tokens")): postData["n_predict"] = body["max_tokens"] |
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if(is_present(body, "presence_penalty")): postData["presence_penalty"] = body["presence_penalty"] |
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if(is_present(body, "frequency_penalty")): postData["frequency_penalty"] = body["frequency_penalty"] |
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if(is_present(body, "repeat_penalty")): postData["repeat_penalty"] = body["repeat_penalty"] |
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if(is_present(body, "mirostat")): postData["mirostat"] = body["mirostat"] |
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if(is_present(body, "mirostat_tau")): postData["mirostat_tau"] = body["mirostat_tau"] |
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if(is_present(body, "mirostat_eta")): postData["mirostat_eta"] = body["mirostat_eta"] |
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if(is_present(body, "seed")): postData["seed"] = body["seed"] |
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if(is_present(body, "logit_bias")): postData["logit_bias"] = [[int(token), body["logit_bias"][token]] for token in body["logit_bias"].keys()] |
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if (args.stop != ""): |
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postData["stop"] = [args.stop] |
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else: |
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postData["stop"] = [] |
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if(is_present(body, "stop")): postData["stop"] += body["stop"] |
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postData["n_keep"] = -1 |
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postData["stream"] = stream |
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postData["cache_prompt"] = True |
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postData["slot_id"] = slot_id |
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return postData |
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def make_resData(data, chat=False, promptToken=[]): |
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resData = { |
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"id": "chatcmpl" if (chat) else "cmpl", |
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"object": "chat.completion" if (chat) else "text_completion", |
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"created": int(time.time()), |
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"truncated": data["truncated"], |
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"model": "LLaMA_CPP", |
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"usage": { |
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"prompt_tokens": data["tokens_evaluated"], |
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"completion_tokens": data["tokens_predicted"], |
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"total_tokens": data["tokens_evaluated"] + data["tokens_predicted"] |
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} |
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} |
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if (len(promptToken) != 0): |
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resData["promptToken"] = promptToken |
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if (chat): |
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resData["choices"] = [{ |
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"index": 0, |
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"message": { |
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"role": "assistant", |
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"content": data["content"], |
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}, |
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"finish_reason": "stop" if (data["stopped_eos"] or data["stopped_word"]) else "length" |
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}] |
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else: |
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resData["choices"] = [{ |
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"text": data["content"], |
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"index": 0, |
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"logprobs": None, |
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"finish_reason": "stop" if (data["stopped_eos"] or data["stopped_word"]) else "length" |
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}] |
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return resData |
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def make_resData_stream(data, chat=False, time_now = 0, start=False): |
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resData = { |
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"id": "chatcmpl" if (chat) else "cmpl", |
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"object": "chat.completion.chunk" if (chat) else "text_completion.chunk", |
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"created": time_now, |
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"model": "LLaMA_CPP", |
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"choices": [ |
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{ |
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"finish_reason": None, |
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"index": 0 |
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} |
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] |
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} |
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slot_id = data["slot_id"] |
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if (chat): |
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if (start): |
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resData["choices"][0]["delta"] = { |
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"role": "assistant" |
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} |
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else: |
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resData["choices"][0]["delta"] = { |
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"content": data["content"] |
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} |
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if (data["stop"]): |
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resData["choices"][0]["finish_reason"] = "stop" if (data["stopped_eos"] or data["stopped_word"]) else "length" |
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else: |
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resData["choices"][0]["text"] = data["content"] |
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if (data["stop"]): |
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resData["choices"][0]["finish_reason"] = "stop" if (data["stopped_eos"] or data["stopped_word"]) else "length" |
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return resData |
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@app.route('/chat/completions', methods=['POST']) |
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@app.route('/v1/chat/completions', methods=['POST']) |
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def chat_completions(): |
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body = request.get_json() |
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stream = False |
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tokenize = False |
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if(is_present(body, "stream")): stream = body["stream"] |
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if(is_present(body, "tokenize")): tokenize = body["tokenize"] |
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postData = make_postData(body, chat=True, stream=stream) |
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promptToken = [] |
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if (tokenize): |
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tokenData = requests.request("POST", urllib.parse.urljoin(args.llama_api, "/tokenize"), data=json.dumps({"content": postData["prompt"]})).json() |
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promptToken = tokenData["tokens"] |
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if (not stream): |
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data = requests.request("POST", urllib.parse.urljoin(args.llama_api, "/completion"), data=json.dumps(postData)) |
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print(data.json()) |
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resData = make_resData(data.json(), chat=True, promptToken=promptToken) |
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return jsonify(resData) |
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else: |
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def generate(): |
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data = requests.request("POST", urllib.parse.urljoin(args.llama_api, "/completion"), data=json.dumps(postData), stream=True) |
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time_now = int(time.time()) |
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resData = make_resData_stream({}, chat=True, time_now=time_now, start=True) |
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yield 'data: {}\n'.format(json.dumps(resData)) |
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for line in data.iter_lines(): |
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if line: |
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decoded_line = line.decode('utf-8') |
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resData = make_resData_stream(json.loads(decoded_line[6:]), chat=True, time_now=time_now) |
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yield 'data: {}\n'.format(json.dumps(resData)) |
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return Response(generate(), mimetype='text/event-stream') |
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@app.route('/completions', methods=['POST']) |
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@app.route('/v1/completions', methods=['POST']) |
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def completion(): |
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body = request.get_json() |
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stream = False |
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tokenize = False |
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if(is_present(body, "stream")): stream = body["stream"] |
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if(is_present(body, "tokenize")): tokenize = body["tokenize"] |
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postData = make_postData(body, chat=False, stream=stream) |
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promptToken = [] |
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if (tokenize): |
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tokenData = requests.request("POST", urllib.parse.urljoin(args.llama_api, "/tokenize"), data=json.dumps({"content": postData["prompt"]})).json() |
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promptToken = tokenData["tokens"] |
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if (not stream): |
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data = requests.request("POST", urllib.parse.urljoin(args.llama_api, "/completion"), data=json.dumps(postData)) |
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print(data.json()) |
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resData = make_resData(data.json(), chat=False, promptToken=promptToken) |
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return jsonify(resData) |
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else: |
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def generate(): |
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data = requests.request("POST", urllib.parse.urljoin(args.llama_api, "/completion"), data=json.dumps(postData), stream=True) |
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time_now = int(time.time()) |
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for line in data.iter_lines(): |
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if line: |
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decoded_line = line.decode('utf-8') |
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resData = make_resData_stream(json.loads(decoded_line[6:]), chat=False, time_now=time_now) |
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yield 'data: {}\n'.format(json.dumps(resData)) |
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return Response(generate(), mimetype='text/event-stream') |
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if __name__ == '__main__': |
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app.run(args.host, port=args.port) |
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