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| from toolbox import get_conf, get_pictures_list, encode_image | |
| import base64 | |
| import datetime | |
| import hashlib | |
| import hmac | |
| import json | |
| from urllib.parse import urlparse | |
| import ssl | |
| from datetime import datetime | |
| from time import mktime | |
| from urllib.parse import urlencode | |
| from wsgiref.handlers import format_date_time | |
| import websocket | |
| import threading, time | |
| timeout_bot_msg = '[Local Message] Request timeout. Network error.' | |
| class Ws_Param(object): | |
| # 初始化 | |
| def __init__(self, APPID, APIKey, APISecret, gpt_url): | |
| self.APPID = APPID | |
| self.APIKey = APIKey | |
| self.APISecret = APISecret | |
| self.host = urlparse(gpt_url).netloc | |
| self.path = urlparse(gpt_url).path | |
| self.gpt_url = gpt_url | |
| # 生成url | |
| def create_url(self): | |
| # 生成RFC1123格式的时间戳 | |
| now = datetime.now() | |
| date = format_date_time(mktime(now.timetuple())) | |
| # 拼接字符串 | |
| signature_origin = "host: " + self.host + "\n" | |
| signature_origin += "date: " + date + "\n" | |
| signature_origin += "GET " + self.path + " HTTP/1.1" | |
| # 进行hmac-sha256进行加密 | |
| signature_sha = hmac.new(self.APISecret.encode('utf-8'), signature_origin.encode('utf-8'), digestmod=hashlib.sha256).digest() | |
| signature_sha_base64 = base64.b64encode(signature_sha).decode(encoding='utf-8') | |
| authorization_origin = f'api_key="{self.APIKey}", algorithm="hmac-sha256", headers="host date request-line", signature="{signature_sha_base64}"' | |
| authorization = base64.b64encode(authorization_origin.encode('utf-8')).decode(encoding='utf-8') | |
| # 将请求的鉴权参数组合为字典 | |
| v = { | |
| "authorization": authorization, | |
| "date": date, | |
| "host": self.host | |
| } | |
| # 拼接鉴权参数，生成url | |
| url = self.gpt_url + '?' + urlencode(v) | |
| # 此处打印出建立连接时候的url,参考本demo的时候可取消上方打印的注释，比对相同参数时生成的url与自己代码生成的url是否一致 | |
| return url | |
| class SparkRequestInstance(): | |
| def __init__(self): | |
| XFYUN_APPID, XFYUN_API_SECRET, XFYUN_API_KEY = get_conf('XFYUN_APPID', 'XFYUN_API_SECRET', 'XFYUN_API_KEY') | |
| if XFYUN_APPID == '00000000' or XFYUN_APPID == '': raise RuntimeError('请配置讯飞星火大模型的XFYUN_APPID, XFYUN_API_KEY, XFYUN_API_SECRET') | |
| self.appid = XFYUN_APPID | |
| self.api_secret = XFYUN_API_SECRET | |
| self.api_key = XFYUN_API_KEY | |
| self.gpt_url = "ws://spark-api.xf-yun.com/v1.1/chat" | |
| self.gpt_url_v2 = "ws://spark-api.xf-yun.com/v2.1/chat" | |
| self.gpt_url_v3 = "ws://spark-api.xf-yun.com/v3.1/chat" | |
| self.gpt_url_v35 = "wss://spark-api.xf-yun.com/v3.5/chat" | |
| self.gpt_url_img = "wss://spark-api.cn-huabei-1.xf-yun.com/v2.1/image" | |
| self.time_to_yield_event = threading.Event() | |
| self.time_to_exit_event = threading.Event() | |
| self.result_buf = "" | |
| def generate(self, inputs, llm_kwargs, history, system_prompt, use_image_api=False): | |
| llm_kwargs = llm_kwargs | |
| history = history | |
| system_prompt = system_prompt | |
| import _thread as thread | |
| thread.start_new_thread(self.create_blocking_request, (inputs, llm_kwargs, history, system_prompt, use_image_api)) | |
| while True: | |
| self.time_to_yield_event.wait(timeout=1) | |
| if self.time_to_yield_event.is_set(): | |
| yield self.result_buf | |
| if self.time_to_exit_event.is_set(): | |
| return self.result_buf | |
| def create_blocking_request(self, inputs, llm_kwargs, history, system_prompt, use_image_api): | |
| if llm_kwargs['llm_model'] == 'sparkv2': | |
| gpt_url = self.gpt_url_v2 | |
| elif llm_kwargs['llm_model'] == 'sparkv3': | |
| gpt_url = self.gpt_url_v3 | |
| elif llm_kwargs['llm_model'] == 'sparkv3.5': | |
| gpt_url = self.gpt_url_v35 | |
| else: | |
| gpt_url = self.gpt_url | |
| file_manifest = [] | |
| if use_image_api and llm_kwargs.get('most_recent_uploaded'): | |
| if llm_kwargs['most_recent_uploaded'].get('path'): | |
| file_manifest = get_pictures_list(llm_kwargs['most_recent_uploaded']['path']) | |
| if len(file_manifest) > 0: | |
| print('正在使用讯飞图片理解API') | |
| gpt_url = self.gpt_url_img | |
| wsParam = Ws_Param(self.appid, self.api_key, self.api_secret, gpt_url) | |
| websocket.enableTrace(False) | |
| wsUrl = wsParam.create_url() | |
| # 收到websocket连接建立的处理 | |
| def on_open(ws): | |
| import _thread as thread | |
| thread.start_new_thread(run, (ws,)) | |
| def run(ws, *args): | |
| data = json.dumps(gen_params(ws.appid, *ws.all_args, file_manifest)) | |
| ws.send(data) | |
| # 收到websocket消息的处理 | |
| def on_message(ws, message): | |
| data = json.loads(message) | |
| code = data['header']['code'] | |
| if code != 0: | |
| print(f'请求错误: {code}, {data}') | |
| self.result_buf += str(data) | |
| ws.close() | |
| self.time_to_exit_event.set() | |
| else: | |
| choices = data["payload"]["choices"] | |
| status = choices["status"] | |
| content = choices["text"][0]["content"] | |
| ws.content += content | |
| self.result_buf += content | |
| if status == 2: | |
| ws.close() | |
| self.time_to_exit_event.set() | |
| self.time_to_yield_event.set() | |
| # 收到websocket错误的处理 | |
| def on_error(ws, error): | |
| print("error:", error) | |
| self.time_to_exit_event.set() | |
| # 收到websocket关闭的处理 | |
| def on_close(ws, *args): | |
| self.time_to_exit_event.set() | |
| # websocket | |
| ws = websocket.WebSocketApp(wsUrl, on_message=on_message, on_error=on_error, on_close=on_close, on_open=on_open) | |
| ws.appid = self.appid | |
| ws.content = "" | |
| ws.all_args = (inputs, llm_kwargs, history, system_prompt) | |
| ws.run_forever(sslopt={"cert_reqs": ssl.CERT_NONE}) | |
| def generate_message_payload(inputs, llm_kwargs, history, system_prompt, file_manifest): | |
| conversation_cnt = len(history) // 2 | |
| messages = [] | |
| if file_manifest: | |
| base64_images = [] | |
| for image_path in file_manifest: | |
| base64_images.append(encode_image(image_path)) | |
| for img_s in base64_images: | |
| if img_s not in str(messages): | |
| messages.append({"role": "user", "content": img_s, "content_type": "image"}) | |
| else: | |
| messages = [{"role": "system", "content": system_prompt}] | |
| if conversation_cnt: | |
| for index in range(0, 2*conversation_cnt, 2): | |
| what_i_have_asked = {} | |
| what_i_have_asked["role"] = "user" | |
| what_i_have_asked["content"] = history[index] | |
| what_gpt_answer = {} | |
| what_gpt_answer["role"] = "assistant" | |
| what_gpt_answer["content"] = history[index+1] | |
| if what_i_have_asked["content"] != "": | |
| if what_gpt_answer["content"] == "": continue | |
| if what_gpt_answer["content"] == timeout_bot_msg: continue | |
| messages.append(what_i_have_asked) | |
| messages.append(what_gpt_answer) | |
| else: | |
| messages[-1]['content'] = what_gpt_answer['content'] | |
| what_i_ask_now = {} | |
| what_i_ask_now["role"] = "user" | |
| what_i_ask_now["content"] = inputs | |
| messages.append(what_i_ask_now) | |
| return messages | |
| def gen_params(appid, inputs, llm_kwargs, history, system_prompt, file_manifest): | |
| """ | |
| 通过appid和用户的提问来生成请参数 | |
| """ | |
| domains = { | |
| "spark": "general", | |
| "sparkv2": "generalv2", | |
| "sparkv3": "generalv3", | |
| "sparkv3.5": "generalv3.5", | |
| } | |
| domains_select = domains[llm_kwargs['llm_model']] | |
| if file_manifest: domains_select = 'image' | |
| data = { | |
| "header": { | |
| "app_id": appid, | |
| "uid": "1234" | |
| }, | |
| "parameter": { | |
| "chat": { | |
| "domain": domains_select, | |
| "temperature": llm_kwargs["temperature"], | |
| "random_threshold": 0.5, | |
| "max_tokens": 4096, | |
| "auditing": "default" | |
| } | |
| }, | |
| "payload": { | |
| "message": { | |
| "text": generate_message_payload(inputs, llm_kwargs, history, system_prompt, file_manifest) | |
| } | |
| } | |
| } | |
| return data | |