Update README.md
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README.md
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README.md
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@ -92,7 +92,7 @@ print(rag.query("What are the top themes in this story?", param=QueryParam(mode=
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<details>
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<summary> Using Open AI-like APIs </summary>
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LightRAG also supports Open AI-like chat/embeddings APIs:
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* LightRAG also supports Open AI-like chat/embeddings APIs:
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```python
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async def llm_model_func(
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prompt, system_prompt=None, history_messages=[], **kwargs
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@ -130,7 +130,7 @@ rag = LightRAG(
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<details>
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<summary> Using Hugging Face Models </summary>
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If you want to use Hugging Face models, you only need to set LightRAG as follows:
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* If you want to use Hugging Face models, you only need to set LightRAG as follows:
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```python
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from lightrag.llm import hf_model_complete, hf_embedding
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from transformers import AutoModel, AutoTokenizer
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@ -156,7 +156,8 @@ rag = LightRAG(
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<details>
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<summary> Using Ollama Models </summary>
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If you want to use Ollama models, you only need to set LightRAG as follows:
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* If you want to use Ollama models, you only need to set LightRAG as follows:
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```python
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from lightrag.llm import ollama_model_complete, ollama_embedding
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@ -177,6 +178,29 @@ rag = LightRAG(
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),
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)
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```
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* Increasing the `num_ctx` parameter:
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1. Pull the model:
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```python
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ollama pull qwen2
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```
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2. Display the model file:
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```python
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ollama show --modelfile qwen2 > Modelfile
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```
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3. Edit the Modelfile by adding the following line:
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```python
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PARAMETER num_ctx 32768
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```
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4. Create the modified model:
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```python
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ollama create -f Modelfile qwen2m
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```
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</details>
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### Batch Insert
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@ -441,6 +465,8 @@ def extract_queries(file_path):
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├── examples
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│ ├── batch_eval.py
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│ ├── generate_query.py
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│ ├── lightrag_azure_openai_demo.py
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│ ├── lightrag_bedrock_demo.py
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│ ├── lightrag_hf_demo.py
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│ ├── lightrag_ollama_demo.py
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│ ├── lightrag_openai_compatible_demo.py
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@ -459,6 +485,8 @@ def extract_queries(file_path):
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│ ├── Step_1.py
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│ ├── Step_2.py
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│ └── Step_3.py
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├── .gitignore
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├── .pre-commit-config.yaml
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├── LICENSE
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├── README.md
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├── requirements.txt
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