feat: support gpt-3.5 model

common/const.py

@@ -10,3 +10,4 @@ SLACK = "slack"
 
 # model
 OPEN_AI = "openai"
+CHATGPT = "chatgpt"

config-template.json

@@ -1,6 +1,6 @@
 {
   "model": {
-    "type" : "openai",
+    "type" : "chatgpt",
     "openai": {
       "api_key": "YOUR API KEY",
       "conversation_max_tokens": 1000,

model/chatgpt/chatgpt_model.py

@@ -0,0 +1,186 @@
+# encoding:utf-8
+
+from model.model import Model
+from config import model_conf
+from common import const
+from common import log
+import openai
+import time
+
+user_session = dict()
+
+# OpenAI对话模型API (可用)
+class ChatGPTModel(Model):
+    def __init__(self):
+        openai.api_key = model_conf(const.OPEN_AI).get('api_key')
+
+    def reply(self, query, context=None):
+        # acquire reply content
+        if not context or not context.get('type') or context.get('type') == 'TEXT':
+            log.info("[OPEN_AI] query={}".format(query))
+            from_user_id = context['from_user_id']
+            if query == '#清除记忆':
+                Session.clear_session(from_user_id)
+                return '记忆已清除'
+
+            new_query = Session.build_session_query(query, from_user_id)
+            log.debug("[OPEN_AI] session query={}".format(new_query))
+
+            # if context.get('stream'):
+            #     # reply in stream
+            #     return self.reply_text_stream(query, new_query, from_user_id)
+
+            reply_content = self.reply_text(new_query, from_user_id, 0)
+            log.debug("[OPEN_AI] new_query={}, user={}, reply_cont={}".format(new_query, from_user_id, reply_content))
+            if reply_content:
+                Session.save_session(query, reply_content, from_user_id)
+            return reply_content
+
+        elif context.get('type', None) == 'IMAGE_CREATE':
+            return self.create_img(query, 0)
+
+    def reply_text(self, query, user_id, retry_count=0):
+        try:
+            response = openai.ChatCompletion.create(
+                model="gpt-3.5-turbo",  # 对话模型的名称
+                messages=query,
+                temperature=0.9,  # 值在[0,1]之间，越大表示回复越具有不确定性
+                max_tokens=1200,  # 回复最大的字符数
+                top_p=1,
+                frequency_penalty=0.0,  # [-2,2]之间，该值越大则更倾向于产生不同的内容
+                presence_penalty=0.0,  # [-2,2]之间，该值越大则更倾向于产生不同的内容
+            )
+            # res_content = response.choices[0]['text'].strip().replace('<|endoftext|>', '')
+            log.info(response.choices[0]['message']['content'])
+            # log.info("[OPEN_AI] reply={}".format(res_content))
+            return response.choices[0]['message']['content']
+        except openai.error.RateLimitError as e:
+            # rate limit exception
+            log.warn(e)
+            if retry_count < 1:
+                time.sleep(5)
+                log.warn("[OPEN_AI] RateLimit exceed, 第{}次重试".format(retry_count+1))
+                return self.reply_text(query, user_id, retry_count+1)
+            else:
+                return "提问太快啦，请休息一下再问我吧"
+        except Exception as e:
+            # unknown exception
+            log.exception(e)
+            Session.clear_session(user_id)
+            return "请再问我一次吧"
+
+
+    def reply_text_stream(self, query, new_query, user_id, retry_count=0):
+        try:
+            res = openai.Completion.create(
+                model="text-davinci-003",  # 对话模型的名称
+                prompt=new_query,
+                temperature=0.9,  # 值在[0,1]之间，越大表示回复越具有不确定性
+                max_tokens=4096,  # 回复最大的字符数
+                top_p=1,
+                frequency_penalty=0.0,  # [-2,2]之间，该值越大则更倾向于产生不同的内容
+                presence_penalty=0.0,  # [-2,2]之间，该值越大则更倾向于产生不同的内容
+                stop=["\n\n\n"],
+                stream=True
+            )
+            return self._process_reply_stream(query, res, user_id)
+
+        except openai.error.RateLimitError as e:
+            # rate limit exception
+            log.warn(e)
+            if retry_count < 1:
+                time.sleep(5)
+                log.warn("[OPEN_AI] RateLimit exceed, 第{}次重试".format(retry_count+1))
+                return self.reply_text(query, user_id, retry_count+1)
+            else:
+                return "提问太快啦，请休息一下再问我吧"
+        except Exception as e:
+            # unknown exception
+            log.exception(e)
+            Session.clear_session(user_id)
+            return "请再问我一次吧"
+
+
+    def _process_reply_stream(
+            self,
+            query: str,
+            reply: dict,
+            user_id: str
+    ) -> str:
+        full_response = ""
+        for response in reply:
+            if response.get("choices") is None or len(response["choices"]) == 0:
+                raise Exception("OpenAI API returned no choices")
+            if response["choices"][0].get("finish_details") is not None:
+                break
+            if response["choices"][0].get("text") is None:
+                raise Exception("OpenAI API returned no text")
+            if response["choices"][0]["text"] == "<|endoftext|>":
+                break
+            yield response["choices"][0]["text"]
+            full_response += response["choices"][0]["text"]
+        if query and full_response:
+            Session.save_session(query, full_response, user_id)
+
+
+    def create_img(self, query, retry_count=0):
+        try:
+            log.info("[OPEN_AI] image_query={}".format(query))
+            response = openai.Image.create(
+                prompt=query,    #图片描述
+                n=1,             #每次生成图片的数量
+                size="256x256"   #图片大小,可选有 256x256, 512x512, 1024x1024
+            )
+            image_url = response['data'][0]['url']
+            log.info("[OPEN_AI] image_url={}".format(image_url))
+            return image_url
+        except openai.error.RateLimitError as e:
+            log.warn(e)
+            if retry_count < 1:
+                time.sleep(5)
+                log.warn("[OPEN_AI] ImgCreate RateLimit exceed, 第{}次重试".format(retry_count+1))
+                return self.reply_text(query, retry_count+1)
+            else:
+                return "提问太快啦，请休息一下再问我吧"
+        except Exception as e:
+            log.exception(e)
+            return None
+
+
+class Session(object):
+    @staticmethod
+    def build_session_query(query, user_id):
+        '''
+        build query with conversation history
+        e.g.  [
+            {"role": "system", "content": "You are a helpful assistant."},
+            {"role": "user", "content": "Who won the world series in 2020?"},
+            {"role": "assistant", "content": "The Los Angeles Dodgers won the World Series in 2020."},
+            {"role": "user", "content": "Where was it played?"}
+        ]
+        :param query: query content
+        :param user_id: from user id
+        :return: query content with conversaction
+        '''
+        session = user_session.get(user_id, [])
+        if len(session) == 0:
+            system_prompt = model_conf(const.OPEN_AI).get("character_desc", "")
+            system_item = {'role': 'system', 'content': system_prompt}
+            session.append(system_item)
+            user_session[user_id] = session
+        user_item = {'role': 'user', 'content': query}
+        session.append(user_item)
+        return session
+
+    @staticmethod
+    def save_session(query, answer, user_id):
+        session = user_session.get(user_id)
+        if session:
+            # append conversation
+            gpt_item = {'role': 'assistant', 'content': answer}
+            session.append(gpt_item)
+
+    @staticmethod
+    def clear_session(user_id):
+        user_session[user_id] = []
+

model/model_factory.py

@@ -12,8 +12,14 @@ def create_bot(model_type):
     """
 
     if model_type == const.OPEN_AI:
-        # OpenAI 官方对话模型API
+        # OpenAI 官方对话模型API (gpt-3.0)
         from model.openai.open_ai_model import OpenAIModel
         return OpenAIModel()
 
+    elif model_type == const.CHATGPT:
+        # ChatGPT API (gpt-3.5-turbo)
+        from model.chatgpt.chatgpt_model import ChatGPTModel
+        return ChatGPTModel()
+
     raise RuntimeError
+