Update README

README-zh.md

@@ -33,6 +33,9 @@
       <a href="README-zh.md"><img src="https://img.shields.io/badge/🇨🇳中文版-1a1a2e?style=for-the-badge"></a>
       <a href="README.md"><img src="https://img.shields.io/badge/🇺🇸English-1a1a2e?style=for-the-badge"></a>
     </p>
+    <p>
+      <a href="https://pepy.tech/projects/lightrag-hku"><img src="https://static.pepy.tech/personalized-badge/lightrag-hku?period=total&units=INTERNATIONAL_SYSTEM&left_color=BLACK&right_color=GREEN&left_text=downloads"></a>
+    </p>
   </div>
 </div>
 

README.md

@@ -33,6 +33,9 @@
       <a href="README-zh.md"><img src="https://img.shields.io/badge/🇨🇳中文版-1a1a2e?style=for-the-badge"></a>
       <a href="README.md"><img src="https://img.shields.io/badge/🇺🇸English-1a1a2e?style=for-the-badge"></a>
     </p>
+    <p>
+      <a href="https://pepy.tech/projects/lightrag-hku"><img src="https://static.pepy.tech/personalized-badge/lightrag-hku?period=total&units=INTERNATIONAL_SYSTEM&left_color=BLACK&right_color=GREEN&left_text=downloads"></a>
+    </p>
   </div>
 </div>
 

lightrag/api/README-zh.md

@@ -372,7 +372,20 @@ lightrag-server --llm-binding ollama --help
 lightrag-server --embedding-binding ollama --help
 ```
 
-> 请使用openai兼容方式访问OpenRouter或vLLM部署的LLM。可以通过 `OPENAI_LLM_EXTRA_BODY` 环境变量给OpenRouter或vLLM传递额外的参数，实现推理模式的关闭或者其它个性化控制。
+> 请使用openai兼容方式访问OpenRouter、vLLM或SLang部署的LLM。可以通过 `OPENAI_LLM_EXTRA_BODY` 环境变量给OpenRouter、vLLM或SGLang推理框架传递额外的参数，实现推理模式的关闭或者其它个性化控制。
+
+设置 `max_tokens` 参数旨在**防止在实体关系提取阶段出现LLM 响应输出过长或无休止的循环输出的问题**。设置 `max_tokens` 参数的目的是在超时发生之前截断 LLM 输出，从而防止文档提取失败。这解决了某些包含大量实体和关系的文本块（例如表格或引文）可能导致 LLM 产生过长甚至无限循环输出的问题。此设置对于本地部署的小参数模型尤为重要。`max_tokens` 值可以通过以下公式计算：
+
+```
+# For vLLM/SGLang doployed models, or most of OpenAI compatible API provider
+OPENAI_LLM_MAX_TOKENS=9000
+
+# For Ollama Deployed Modeles
+OLLAMA_LLM_NUM_PREDICT=9000
+
+# For OpenAI o1-mini or newer modles
+OPENAI_LLM_MAX_COMPLETION_TOKENS=9000
+```
 
 ### 实体提取配置
 

lightrag/api/README.md

@@ -374,9 +374,23 @@ lightrag-server --llm-binding ollama --help
 lightrag-server --embedding-binding ollama --help
 ```
 
-> Please use OpenAI-compatible method to access LLMs deployed by OpenRouter or vLLM. You can pass additional parameters to OpenRouter or vLLM through the `OPENAI_LLM_EXTRA_BODY` environment variable to disable reasoning mode or achieve other personalized controls.
+> Please use OpenAI-compatible method to access LLMs deployed by OpenRouter or vLLM/SGLang. You can pass additional parameters to OpenRouter or vLLM/SGLang through the `OPENAI_LLM_EXTRA_BODY` environment variable to disable reasoning mode or achieve other personalized controls.
+
+Set the max_tokens to **prevent excessively long or endless output loop** during the entity relationship extraction phase for Large Language Model (LLM) responses.  The purpose of setting max_tokens parameter is to truncate LLM output before timeouts occur, thereby preventing document extraction failures. This addresses issues where certain text blocks (e.g., tables or citations) containing numerous entities and relationships can lead to overly long or even endless loop outputs from LLMs. This setting is particularly crucial for locally deployed, smaller-parameter models. Max tokens value can be calculated by this formula: `LLM_TIMEOUT * llm_output_tokens/second` (i.e. `180s * 50 tokens/s = 9000`)
+
+```
+# For vLLM/SGLang doployed models, or most of OpenAI compatible API provider
+OPENAI_LLM_MAX_TOKENS=9000
+
+# For Ollama Deployed Modeles
+OLLAMA_LLM_NUM_PREDICT=9000
+
+# For OpenAI o1-mini or newer modles
+OPENAI_LLM_MAX_COMPLETION_TOKENS=9000
+```
 
 ### Entity Extraction Configuration
+
 * ENABLE_LLM_CACHE_FOR_EXTRACT: Enable LLM cache for entity extraction (default: true)
 
 It's very common to set `ENABLE_LLM_CACHE_FOR_EXTRACT` to true for a test environment to reduce the cost of LLM calls.