Fix: Hunyuan cannot work properly (#12843)

### What problem does this PR solve?

Hunyuan cannot work properly

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)

rag/llm/__init__.py

@@ -57,6 +57,7 @@ class SupportedLiteLLMProvider(StrEnum):
     OpenAI = "OpenAI"
     Azure_OpenAI = "Azure-OpenAI"
     n1n = "n1n"
+    HunYuan = "Tencent Hunyuan"
 
 
 FACTORY_DEFAULT_BASE_URL = {
@@ -83,6 +84,7 @@ FACTORY_DEFAULT_BASE_URL = {
     SupportedLiteLLMProvider.DeerAPI: "https://api.deerapi.com/v1",
     SupportedLiteLLMProvider.OpenAI: "https://api.openai.com/v1",
     SupportedLiteLLMProvider.n1n: "https://api.n1n.ai/v1",
+    SupportedLiteLLMProvider.HunYuan: "https://api.hunyuan.cloud.tencent.com/v1",
 }
 
 
@@ -121,6 +123,7 @@ LITELLM_PROVIDER_PREFIX = {
     SupportedLiteLLMProvider.OpenAI: "openai/",
     SupportedLiteLLMProvider.Azure_OpenAI: "azure/",
     SupportedLiteLLMProvider.n1n: "openai/",
+    SupportedLiteLLMProvider.HunYuan: "openai/",
 }
 
 ChatModel = globals().get("ChatModel", {})

rag/llm/chat_model.py

@@ -34,8 +34,6 @@ from common.token_utils import num_tokens_from_string, total_token_count_from_re
 from rag.llm import FACTORY_DEFAULT_BASE_URL, LITELLM_PROVIDER_PREFIX, SupportedLiteLLMProvider
 from rag.nlp import is_chinese, is_english
 
-# Error message constants
-
 from common.misc_utils import thread_pool_exec
 class LLMErrorCode(StrEnum):
     ERROR_RATE_LIMIT = "RATE_LIMIT_EXCEEDED"
@@ -106,7 +104,7 @@ class Base(ABC):
         if "gpt-5" in model_name_lower:
             gen_conf = {}
             return gen_conf
-        
+
         if "max_tokens" in gen_conf:
             del gen_conf["max_tokens"]
 
@@ -793,84 +791,6 @@ class ReplicateChat(Base):
         yield num_tokens_from_string(ans)
 
 
-class HunyuanChat(Base):
-    _FACTORY_NAME = "Tencent Hunyuan"
-
-    def __init__(self, key, model_name, base_url=None, **kwargs):
-        super().__init__(key, model_name, base_url=base_url, **kwargs)
-
-        from tencentcloud.common import credential
-        from tencentcloud.hunyuan.v20230901 import hunyuan_client
-
-        key = json.loads(key)
-        sid = key.get("hunyuan_sid", "")
-        sk = key.get("hunyuan_sk", "")
-        cred = credential.Credential(sid, sk)
-        self.model_name = model_name
-        self.client = hunyuan_client.HunyuanClient(cred, "")
-
-    def _clean_conf(self, gen_conf):
-        _gen_conf = {}
-        if "temperature" in gen_conf:
-            _gen_conf["Temperature"] = gen_conf["temperature"]
-        if "top_p" in gen_conf:
-            _gen_conf["TopP"] = gen_conf["top_p"]
-        return _gen_conf
-
-    def _chat(self, history, gen_conf={}, **kwargs):
-        from tencentcloud.hunyuan.v20230901 import models
-
-        hist = [{k.capitalize(): v for k, v in item.items()} for item in history]
-        req = models.ChatCompletionsRequest()
-        params = {"Model": self.model_name, "Messages": hist, **gen_conf}
-        req.from_json_string(json.dumps(params))
-        response = self.client.ChatCompletions(req)
-        ans = response.Choices[0].Message.Content
-        return ans, response.Usage.TotalTokens
-
-    def chat_streamly(self, system, history, gen_conf={}, **kwargs):
-        from tencentcloud.common.exception.tencent_cloud_sdk_exception import (
-            TencentCloudSDKException,
-        )
-        from tencentcloud.hunyuan.v20230901 import models
-
-        _gen_conf = {}
-        _history = [{k.capitalize(): v for k, v in item.items()} for item in history]
-        if system and history and history[0].get("role") != "system":
-            _history.insert(0, {"Role": "system", "Content": system})
-        if "max_tokens" in gen_conf:
-            del gen_conf["max_tokens"]
-        if "temperature" in gen_conf:
-            _gen_conf["Temperature"] = gen_conf["temperature"]
-        if "top_p" in gen_conf:
-            _gen_conf["TopP"] = gen_conf["top_p"]
-        req = models.ChatCompletionsRequest()
-        params = {
-            "Model": self.model_name,
-            "Messages": _history,
-            "Stream": True,
-            **_gen_conf,
-        }
-        req.from_json_string(json.dumps(params))
-        ans = ""
-        total_tokens = 0
-        try:
-            response = self.client.ChatCompletions(req)
-            for resp in response:
-                resp = json.loads(resp["data"])
-                if not resp["Choices"] or not resp["Choices"][0]["Delta"]["Content"]:
-                    continue
-                ans = resp["Choices"][0]["Delta"]["Content"]
-                total_tokens += 1
-
-                yield ans
-
-        except TencentCloudSDKException as e:
-            yield ans + "\n**ERROR**: " + str(e)
-
-        yield total_tokens
-
-
 class SparkChat(Base):
     _FACTORY_NAME = "XunFei Spark"
 
@@ -1209,6 +1129,7 @@ class LiteLLMBase(ABC):
         "GPUStack",
         "OpenAI",
         "Azure-OpenAI",
+        "Tencent Hunyuan",
     ]
 
     def __init__(self, key, model_name, base_url=None, **kwargs):
@@ -1259,6 +1180,11 @@ class LiteLLMBase(ABC):
         return LLMErrorCode.ERROR_GENERIC
 
     def _clean_conf(self, gen_conf):
+        if self.provider == SupportedLiteLLMProvider.HunYuan:
+            unsupported = ["presence_penalty", "frequency_penalty"]
+            for key in unsupported:
+                gen_conf.pop(key, None)
+
         if "max_tokens" in gen_conf:
             del gen_conf["max_tokens"]
         return gen_conf
@@ -1704,3 +1630,4 @@ class LiteLLMBase(ABC):
         if extra_headers:
             completion_args["extra_headers"] = extra_headers
         return completion_args
+