Add LightllmApi KeyError log & Update doc (#816)

* Add LightllmApi KeyError log

* Update LightllmApi doc

docs/en/advanced_guides/evaluation_lightllm.md

@@ -27,6 +27,7 @@ python -m lightllm.server.api_server --model_dir /path/llama2-7B     \
 ```
 
 \*\*Note: \*\* tp can be configured to enable TensorParallel inference on several gpus, suitable for the inference of very large models.
+\*\*Note: \*\* The max_total_token_num in the above command will affect the throughput performance during testing. It can be configured according to the documentation on the [Lightllm homepage](https://github.com/ModelTC/lightllm). As long as it does not run out of memory, it is often better to set it as high as possible.
 
 You can use the following Python script to quickly test whether the current service has been successfully started.
 

docs/zh_cn/advanced_guides/evaluation_lightllm.md

@@ -27,6 +27,7 @@ python -m lightllm.server.api_server --model_dir /path/llama2-7B     \
 ```
 
 **注：** 上述命令可以通过 tp 的数量设置，在 tp 张卡上进行 TensorParallel 推理，适用于较大的模型的推理。
+**注：** 上述命令中的 max_total_token_num，会影响测试过程中的吞吐性能，可以根据 [Lightllm 主页](https://github.com/ModelTC/lightllm) 上的文档，进行设置。只要不爆显存，往往设置越大越好。
 
 可以使用下面的 Python 脚本简单测试一下当前服务是否已经起成功
 

opencompass/models/lightllm_api.py

@@ -78,6 +78,8 @@ class LightllmAPI(BaseAPIModel):
             except requests.JSONDecodeError:
                 self.logger.error('JsonDecode error, got',
                                   str(raw_response.content))
+            except KeyError:
+                self.logger.error(f'KeyError. Response: {str(response)}')
             max_num_retries += 1
 
         raise RuntimeError('Calling LightllmAPI failed after retrying for '
@@ -123,11 +125,11 @@ class LightllmAPI(BaseAPIModel):
                 response = raw_response.json()
 
                 assert ('prompt_token_ids' in response and 'prompt_logprobs'
-                        in response), 'prompt_token_ids and prompt_logprobs \
+                        in response), f'prompt_token_ids and prompt_logprobs \
                     must be in the output. \
                     Please consider adding \
                     --return_all_prompt_logprobs argument \
-                    when starting your lightllm service.'
+                    when starting lightllm service. Response: {str(response)}'
 
                 prompt_token_ids = response['prompt_token_ids'][1:]
                 prompt_logprobs = [