fix the error 'Unknown field for GenerationConfig: max_tokens' when u… (#8473)

### What problem does this PR solve?
[https://github.com/infiniflow/ragflow/issues/8324](url)

docker image version: v0.19.1

The `_clean_conf` function was not implemented in the `_chat` and
`chat_streamly` methods of the `GeminiChat` class, causing the error
"Unknown field for GenerationConfig: max_tokens" when the default LLM
config includes the "max_tokens" parameter.

**Buggy Code(ragflow/rag/llm/chat_model.py)**
```python
class GeminiChat(Base):
    def __init__(self, key, model_name, base_url=None, **kwargs):
        super().__init__(key, model_name, base_url=base_url, **kwargs)

        from google.generativeai import GenerativeModel, client

        client.configure(api_key=key)
        _client = client.get_default_generative_client()
        self.model_name = "models/" + model_name
        self.model = GenerativeModel(model_name=self.model_name)
        self.model._client = _client

    def _clean_conf(self, gen_conf):
        for k in list(gen_conf.keys()):
            if k not in ["temperature", "top_p"]:
                del gen_conf[k]
        return gen_conf

    def _chat(self, history, gen_conf):
        from google.generativeai.types import content_types

        system = history[0]["content"] if history and history[0]["role"] == "system" else ""
        hist = []
        for item in history:
            if item["role"] == "system":
                continue
            hist.append(deepcopy(item))
            item = hist[-1]
            if "role" in item and item["role"] == "assistant":
                item["role"] = "model"
            if "role" in item and item["role"] == "system":
                item["role"] = "user"
            if "content" in item:
                item["parts"] = item.pop("content")

        if system:
            self.model._system_instruction = content_types.to_content(system)
        response = self.model.generate_content(hist, generation_config=gen_conf)
        ans = response.text
        return ans, response.usage_metadata.total_token_count

    def chat_streamly(self, system, history, gen_conf):
        from google.generativeai.types import content_types

        if system:
            self.model._system_instruction = content_types.to_content(system)
        #❌_clean_conf was not implemented 
        for k in list(gen_conf.keys()):
            if k not in ["temperature", "top_p", "max_tokens"]:
                del gen_conf[k]
        for item in history:
            if "role" in item and item["role"] == "assistant":
                item["role"] = "model"
            if "content" in item:
                item["parts"] = item.pop("content")
        ans = ""
        try:
            response = self.model.generate_content(history, generation_config=gen_conf, stream=True)
            for resp in response:
                ans = resp.text
                yield ans

            yield response._chunks[-1].usage_metadata.total_token_count
        except Exception as e:
            yield ans + "\n**ERROR**: " + str(e)

        yield 0
```
**Implement the _clean_conf function**
```python
class GeminiChat(Base):
    def __init__(self, key, model_name, base_url=None, **kwargs):
        super().__init__(key, model_name, base_url=base_url, **kwargs)

        from google.generativeai import GenerativeModel, client

        client.configure(api_key=key)
        _client = client.get_default_generative_client()
        self.model_name = "models/" + model_name
        self.model = GenerativeModel(model_name=self.model_name)
        self.model._client = _client

    def _clean_conf(self, gen_conf):
        for k in list(gen_conf.keys()):
            if k not in ["temperature", "top_p"]:
                del gen_conf[k]
        return gen_conf

    def _chat(self, history, gen_conf):
        from google.generativeai.types import content_types
        #✅ implement _clean_conf to remove the wrong parameters
        gen_conf = self._clean_conf(gen_conf)

        system = history[0]["content"] if history and history[0]["role"] == "system" else ""
        hist = []
        for item in history:
            if item["role"] == "system":
                continue
            hist.append(deepcopy(item))
            item = hist[-1]
            if "role" in item and item["role"] == "assistant":
                item["role"] = "model"
            if "role" in item and item["role"] == "system":
                item["role"] = "user"
            if "content" in item:
                item["parts"] = item.pop("content")

        if system:
            self.model._system_instruction = content_types.to_content(system)
        response = self.model.generate_content(hist, generation_config=gen_conf)
        ans = response.text
        return ans, response.usage_metadata.total_token_count

    def chat_streamly(self, system, history, gen_conf):
        from google.generativeai.types import content_types
        #✅ implement _clean_conf to remove the wrong parameters
        gen_conf = self._clean_conf(gen_conf)

        if system:
            self.model._system_instruction = content_types.to_content(system)
        #✅Removed duplicate parameter filtering logic "for k in list(gen_conf.keys()):"
        for item in history:
            if "role" in item and item["role"] == "assistant":
                item["role"] = "model"
            if "content" in item:
                item["parts"] = item.pop("content")
        ans = ""
        try:
            response = self.model.generate_content(history, generation_config=gen_conf, stream=True)
            for resp in response:
                ans = resp.text
                yield ans

            yield response._chunks[-1].usage_metadata.total_token_count
        except Exception as e:
            yield ans + "\n**ERROR**: " + str(e)

        yield 0
```

### Type of change

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

---------

Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>

rag/llm/chat_model.py

@@ -1217,13 +1217,12 @@ class GeminiChat(Base):
 
     def _clean_conf(self, gen_conf):
         for k in list(gen_conf.keys()):
-            if k not in ["temperature", "top_p"]:
+            if k not in ["temperature", "top_p", "max_tokens"]:
                 del gen_conf[k]
         return gen_conf
 
     def _chat(self, history, gen_conf):
         from google.generativeai.types import content_types
-
         system = history[0]["content"] if history and history[0]["role"] == "system" else ""
         hist = []
         for item in history:
@@ -1246,12 +1245,9 @@ class GeminiChat(Base):
 
     def chat_streamly(self, system, history, gen_conf):
         from google.generativeai.types import content_types
-
+        gen_conf = self._clean_conf(gen_conf)
         if system:
             self.model._system_instruction = content_types.to_content(system)
-        for k in list(gen_conf.keys()):
-            if k not in ["temperature", "top_p", "max_tokens"]:
-                del gen_conf[k]
         for item in history:
             if "role" in item and item["role"] == "assistant":
                 item["role"] = "model"