docs(readme): Add batch size configuration documentation
文档(readme): 添加批处理大小配置说明 - Add documentation for insert_batch_size parameter in addon_params - 在 addon_params 中添加 insert_batch_size 参数的文档说明 - Explain default batch size value and its usage - 说明默认批处理大小值及其用途 - Add example configuration for batch processing - 添加批处理配置的示例
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README.md
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README.md
@@ -278,10 +278,25 @@ class QueryParam:
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### Batch Insert
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### Batch Insert
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```python
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```python
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# Batch Insert: Insert multiple texts at once
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# Basic Batch Insert: Insert multiple texts at once
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rag.insert(["TEXT1", "TEXT2",...])
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rag.insert(["TEXT1", "TEXT2",...])
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# Batch Insert with custom batch size configuration
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rag = LightRAG(
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working_dir=WORKING_DIR,
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addon_params={
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"insert_batch_size": 20 # Process 20 documents per batch
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}
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)
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rag.insert(["TEXT1", "TEXT2", "TEXT3", ...]) # Documents will be processed in batches of 20
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```
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```
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The `insert_batch_size` parameter in `addon_params` controls how many documents are processed in each batch during insertion. This is useful for:
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- Managing memory usage with large document collections
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- Optimizing processing speed
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- Providing better progress tracking
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- Default value is 10 if not specified
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### Incremental Insert
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### Incremental Insert
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```python
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```python
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@@ -594,7 +609,7 @@ if __name__ == "__main__":
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| **llm\_model\_kwargs** | `dict` | Additional parameters for LLM generation | |
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| **llm\_model\_kwargs** | `dict` | Additional parameters for LLM generation | |
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| **vector\_db\_storage\_cls\_kwargs** | `dict` | Additional parameters for vector database (currently not used) | |
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| **vector\_db\_storage\_cls\_kwargs** | `dict` | Additional parameters for vector database (currently not used) | |
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| **enable\_llm\_cache** | `bool` | If `TRUE`, stores LLM results in cache; repeated prompts return cached responses | `TRUE` |
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| **enable\_llm\_cache** | `bool` | If `TRUE`, stores LLM results in cache; repeated prompts return cached responses | `TRUE` |
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| **addon\_params** | `dict` | Additional parameters, e.g., `{"example_number": 1, "language": "Simplified Chinese", "entity_types": ["organization", "person", "geo", "event"]}`: sets example limit and output language | `example_number: all examples, language: English` |
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| **addon\_params** | `dict` | Additional parameters, e.g., `{"example_number": 1, "language": "Simplified Chinese", "entity_types": ["organization", "person", "geo", "event"], "insert_batch_size": 10}`: sets example limit, output language, and batch size for document processing | `example_number: all examples, language: English, insert_batch_size: 10` |
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| **convert\_response\_to\_json\_func** | `callable` | Not used | `convert_response_to_json` |
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| **convert\_response\_to\_json\_func** | `callable` | Not used | `convert_response_to_json` |
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| **embedding\_cache\_config** | `dict` | Configuration for question-answer caching. Contains three parameters:<br>- `enabled`: Boolean value to enable/disable cache lookup functionality. When enabled, the system will check cached responses before generating new answers.<br>- `similarity_threshold`: Float value (0-1), similarity threshold. When a new question's similarity with a cached question exceeds this threshold, the cached answer will be returned directly without calling the LLM.<br>- `use_llm_check`: Boolean value to enable/disable LLM similarity verification. When enabled, LLM will be used as a secondary check to verify the similarity between questions before returning cached answers. | Default: `{"enabled": False, "similarity_threshold": 0.95, "use_llm_check": False}` |
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| **embedding\_cache\_config** | `dict` | Configuration for question-answer caching. Contains three parameters:<br>- `enabled`: Boolean value to enable/disable cache lookup functionality. When enabled, the system will check cached responses before generating new answers.<br>- `similarity_threshold`: Float value (0-1), similarity threshold. When a new question's similarity with a cached question exceeds this threshold, the cached answer will be returned directly without calling the LLM.<br>- `use_llm_check`: Boolean value to enable/disable LLM similarity verification. When enabled, LLM will be used as a secondary check to verify the similarity between questions before returning cached answers. | Default: `{"enabled": False, "similarity_threshold": 0.95, "use_llm_check": False}` |
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