add stream chat with TTS (#2228)

### What problem does this PR solve?



### Type of change

- [x] New Feature (non-breaking change which adds functionality)

api/apps/conversation_app.py

     tts_mdl = LLMBundle(tenants[0]["tenant_id"], LLMType.TTS, tts_id)
     def stream_audio():
         try:
-            for chunk in tts_mdl.tts(text):  
-                yield chunk  
+            for chunk in tts_mdl.tts(text):
+                yield chunk
         except Exception as e:
             yield ("data:" + json.dumps({"retcode": 500, "retmsg": str(e),
                             "data": {"answer": "**ERROR**: "+str(e)}},

api/db/services/dialog_service.py

 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import binascii
 import os
 import json
 import re
 
     prompt_config = dialog.prompt_config
     field_map = KnowledgebaseService.get_field_map(dialog.kb_ids)
+    tts_mdl = None
+    if prompt_config.get("tts"):
+        tts_mdl = LLMBundle(dialog.tenant_id, LLMType.TTS)
     # try to use sql if field mapping is good to go
     if field_map:
         chat_logger.info("Use SQL to retrieval:{}".format(questions[-1]))
         "{}->{}".format(" ".join(questions), "\n->".join(knowledges)))
 
     if not knowledges and prompt_config.get("empty_response"):
-        yield {"answer": prompt_config["empty_response"], "reference": kbinfos}
+        empty_res = prompt_config["empty_response"]
+        yield {"answer": empty_res, "reference": kbinfos, "audio_binary": tts(tts_mdl, empty_res)}
         return {"answer": prompt_config["empty_response"], "reference": kbinfos}
 
     kwargs["knowledge"] = "\n".join(knowledges)
         return {"answer": answer, "reference": refs, "prompt": prompt}
 
     if stream:
+        last_ans = ""
         answer = ""
         for ans in chat_mdl.chat_streamly(prompt, msg[1:], gen_conf):
             answer = ans
-            yield {"answer": answer, "reference": {}}
+            delta_ans = ans[len(last_ans):]
+            if num_tokens_from_string(delta_ans) < 12:
+                continue
+            last_ans = answer
+            yield {"answer": answer, "reference": {}, "audio_binary": tts(tts_mdl, delta_ans)}
+        delta_ans = answer[len(last_ans):]
+        if delta_ans:
+            yield {"answer": answer, "reference": {}, "audio_binary": tts(tts_mdl, delta_ans)}
         yield decorate_answer(answer)
     else:
         answer = chat_mdl.chat(prompt, msg[1:], gen_conf)
         chat_logger.info("User: {}|Assistant: {}".format(
             msg[-1]["content"], answer))
-        yield decorate_answer(answer)
+        res = decorate_answer(answer)
+        res["audio_binary"] = tts(tts_mdl, answer)
+        yield res
 
 
 def use_sql(question, field_map, tenant_id, chat_mdl, quota=True):
     """
     ans = chat_mdl.chat(prompt, [{"role": "user", "content": question}], {"temperature": 0.8})
     return ans
+
+
+def tts(tts_mdl, text):
+    return
+    if not tts_mdl or not text: return
+    bin = b""
+    for chunk in tts_mdl.tts(text):
+        bin += chunk
+    return binascii.hexlify(bin).decode("utf-8")