update chat

src/blackbox/blackbox_factory.py

@@ -1,10 +1,8 @@
-from . import melotts
 from .audio_chat import AudioChat
 from .sentiment import Sentiment
 from .tts import TTS
 from .asr import ASR
 from .audio_to_text import AudioToText
-#from .emotion import Emotion
 from .blackbox import Blackbox
 # from .text_to_audio import TextToAudio
 # from .tesou import Tesou
@@ -25,12 +23,10 @@ class BlackboxFactory:
     @inject
     def __init__(self, 
                  audio_to_text: AudioToText,
-                 text_to_audio: TextToAudio,
                  asr: ASR,
                  tts: TTS, 
                  sentiment_engine: Sentiment, 
                  #emotion: Emotion,
-                 tesou: Tesou, 
                  fastchat: Fastchat,
                  audio_chat: AudioChat,
                  g2e: G2E,
@@ -39,23 +35,22 @@ class BlackboxFactory:
                  #chroma_upsert: ChromaUpsert,
                  #chroma_chat: ChromaChat,
                  melotts: MeloTTS,
-                 vlms: VLMS) -> None:
+                 vlms: VLMS,
+                 chroma_query: ChromaQuery,
+                 chroma_upsert: ChromaUpsert,
+                 chroma_chat: ChromaChat) -> None:
         self.models["audio_to_text"] = audio_to_text
-        self.models["text_to_audio"] = text_to_audio
         self.models["asr"] = asr
         self.models["tts"] = tts
         self.models["sentiment_engine"] = sentiment_engine
-        self.models["tesou"] = tesou
         #self.models["emotion"] = emotion
         self.models["fastchat"] = fastchat
         self.models["audio_chat"] = audio_chat
         self.models["g2e"] = g2e
         self.models["text_and_image"] = text_and_image
-        #self.models["chroma_query"] = chroma_query
-        #self.models["chroma_upsert"] = chroma_upsert
-        #self.models["chroma_chat"] = chroma_chat
-        self.models["melotts"] = melotts
-        self.models["vlms"] = vlms
+        self.models["chroma_query"] = chroma_query
+        self.models["chroma_upsert"] = chroma_upsert
+        self.models["chroma_chat"] = chroma_chat
 
     def __call__(self, *args, **kwargs):
         return self.processing(*args, **kwargs)

src/blackbox/chat.py

@@ -21,7 +21,7 @@ class Chat(Blackbox):
         return isinstance(data, list)
 
     # model_name有 Qwen1.5-14B-Chat , internlm2-chat-20b
-    def processing(self, model_name, prompt, template, context: list, temperature, top_p, n, max_tokens)  -> str:
+    def processing(self, model_name, prompt, template, context: list, temperature, top_p, n, max_tokens,stop,frequency_penalty,presence_penalty)  -> str:
         if context == None:
             context = []
 
@@ -49,7 +49,9 @@ class Chat(Blackbox):
             "top_p": top_p,
             "n": n,
             "max_tokens": max_tokens,
-            "stream": False,
+            "frequency_penalty": frequency_penalty,
+            "presence_penalty": presence_penalty,
+            "stop": stop
         }
 
         header = {
@@ -75,7 +77,9 @@ class Chat(Blackbox):
         user_top_p = data.get("top_p")
         user_n = data.get("n")
         user_max_tokens = data.get("max_tokens")
-        
+        user_stop = data.get("stop")
+        user_frequency_penalty = data.get("frequency_penalty")
+        user_presence_penalty = data.get("presence_penalty")
 
         if user_question is None:
             return JSONResponse(content={"error": "question is required"}, status_code=status.HTTP_400_BAD_REQUEST)
@@ -87,10 +91,10 @@ class Chat(Blackbox):
             user_template = ""
         
         if user_temperature is None or user_temperature == "":
-            user_temperature = 0.7
+            user_temperature = 0.8
 
         if user_top_p is None or user_top_p == "":
-            user_top_p = 1
+            user_top_p = 0.8
 
         if user_n is None or user_n == "":
             user_n = 1
@@ -98,6 +102,15 @@ class Chat(Blackbox):
         if user_max_tokens is None or user_max_tokens == "":
             user_max_tokens = 1024
 
+        if user_stop is None or user_stop == "":
+            user_stop = 100
+
+        if user_frequency_penalty is None or user_frequency_penalty == "":
+            user_frequency_penalty = 0.5
+        
+        if user_presence_penalty is None or user_presence_penalty == "":
+            user_presence_penalty = 0.8
+
 
         return JSONResponse(content={"response": self.processing(user_model_name, user_question, user_template, user_context, 
-        user_temperature, user_top_p, user_n, user_max_tokens)}, status_code=status.HTTP_200_OK)
+        user_temperature, user_top_p, user_n, user_max_tokens,user_stop,user_frequency_penalty,user_presence_penalty)}, status_code=status.HTTP_200_OK)