更新 mini支持讯飞中英文识别大模型，sant增加image对图像处理

boards/default_src/micropython_esp32c2/origin/build/lib/mini_xunfei.py

@@ -45,7 +45,6 @@ class ASR_WebSocket(Ws_Param):
                         "domain": "iat",
                         "language": "zh_cn",
                         "accent": "mandarin",
-                        "vinfo": 1,
                         "vad_eos": 1000,
                         "nbest": 1,
                         "wbest": 1,
@@ -56,7 +55,10 @@ class ASR_WebSocket(Ws_Param):
         self.ws.settimeout(1000)
 
     def _frame(self, status, buf):
-        return {"status": status, "format": "audio/L16;rate=8000", "audio": str(b64encode(buf), 'utf-8'), "encoding": "raw"}
+        if status == 0:
+            return {"common": {"app_id": self.APPID}, "business": self.business, "data": {"status": status, "format": "audio/L16;rate=8000", "audio": str(b64encode(buf), 'utf-8'), "encoding": "raw"}}
+        else:
+            return {"data": {"status": status, "format": "audio/L16;rate=8000", "audio": str(b64encode(buf), 'utf-8'), "encoding": "raw"}}
 
     def on_message(self, message):
         result = ""
@@ -98,17 +100,16 @@ class ASR_WebSocket(Ws_Param):
                     if pace: print('=',end ="")
                     # 第一帧处理
                     if _state == 0:
-                        d = {"common": {"app_id": self.APPID}, "business": self.business, "data": self._frame(_state, buf)}
+                        d = self._frame(_state, buf)
                         _state = 1
                     # 中间帧处理 
                     else:
-                        d = {"data": self._frame(_state, buf)}
+                        d = self._frame(_state, buf)
                     self.ws.send(json.dumps(d))
-                    #print("------",len(buf), time.ticks_diff(time.ticks_ms(), _star))
                 if time.ticks_diff(time.ticks_ms(), _star) > timeout:
                     raise OSError("Timeout pcm read error")
             # 最后一帧处理
-            d = {"data": self._frame(2, b'\x00')}
+            d = self._frame(2, b'\x00')
             self.ws.send(json.dumps(d))
             onboard_bot.pcm_en(False)  #PCM关闭
             if pace: print(']')
@@ -122,6 +123,45 @@ class ASR_WebSocket(Ws_Param):
             else:
                 print("Run error: %s" % (e))
 
+#中英识别大模型
+class IAT_WebSocket(ASR_WebSocket):
+    def __init__(self, APPID, APIKey, APISecret, url='ws://iat.xf-yun.com/v1', accent="mandarin", res_id=None):
+        super().__init__(APPID, APIKey, APISecret, url)
+        self.res_id = res_id
+        self.business = {
+                        "domain": "slm",
+                        "language": "zh_cn",
+                        "accent": accent,
+                        "result": {
+                            "encoding": "utf8",
+                            "compress": "raw",
+                            "format": "plain"
+                        }
+                    }
+
+    def _frame(self, status, buf):
+        if status == 0:
+            return {"header": {"status": status, "app_id": self.APPID, "res_id": self.res_id}, "parameter": {"iat": self.business}, "payload": {"audio": { "audio": str(b64encode(buf), 'utf-8'), "sample_rate": 8000, "encoding": "raw"}}}
+        else:
+            return {"header": {"status": status, "app_id": self.APPID, "res_id": self.res_id}, "payload": {"audio": { "audio": str(b64encode(buf), 'utf-8'), "sample_rate": 8000, "encoding": "raw"}}}
+
+    def on_message(self, message):
+        result = ""
+        msg = json.loads(message)
+        code = msg['header']["code"]
+        if code != 0:
+            raise AttributeError("%s Code:%s" % (msg['header']["message"], code))
+        else:
+            if "payload" in msg:
+                text = msg["payload"]["result"]["text"]
+                data =  json.loads(b64decode(text).decode())['ws']
+                for i in data:
+                    for w in i["cw"]:
+                        result += w["w"]
+            if msg["header"]["status"]== 2:
+                return result, False
+        return result, True 
+
 #大模型
 class LLM_WebSocket(Ws_Param):
     Model_url = {