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Updated LanceDB Doc (#1445)

Prashant Dixit 1 年之前
父节点
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18fb92f1f8
共有 1 个文件被更改,包括 54 次插入2 次删除
  1. 54 2
      docs/components/vector-databases/lancedb.mdx

+ 54 - 2
docs/components/vector-databases/lancedb.mdx

@@ -13,7 +13,9 @@ pip install "embedchain[lancedb]"
 LanceDB is a developer-friendly, open source database for AI. From hyper scalable vector search and advanced retrieval for RAG, to streaming training data and interactive exploration of large scale AI datasets.
 In order to use LanceDB as vector database, not need to set any key for local use. 
 
+### With OPENAI 
 <CodeGroup>
+
 ```python main.py
 import os
 from embedchain import App
@@ -21,7 +23,7 @@ from embedchain import App
 # set OPENAI_API_KEY as env variable
 os.environ["OPENAI_API_KEY"] = "sk-xxx"
 
-# Create Embedchain App and set config
+# create Embedchain App and set config
 app = App.from_config(config={
     "vectordb": {
         "provider": "lancedb",
@@ -32,7 +34,7 @@ app = App.from_config(config={
     }
 )
 
-# Add data source and start queryin
+# add data source and start query in
 app.add("https://www.forbes.com/profile/elon-musk")
 
 # query continuously
@@ -45,4 +47,54 @@ while(True):
 ```
 
 </CodeGroup>
+
+### With Local LLM 
+<CodeGroup>
+
+```python main.py
+from embedchain import Pipeline as App
+
+# config for Embedchain App
+config = {
+  'llm': {
+    'provider': 'huggingface',
+    'config': {
+      'model': 'mistralai/Mistral-7B-v0.1',
+      'temperature': 0.1,
+      'max_tokens': 250,
+      'top_p': 0.1,
+      'stream': True
+    }
+  },
+  'embedder': {
+    'provider': 'huggingface',
+    'config': {
+      'model': 'sentence-transformers/all-mpnet-base-v2'
+    }
+  },
+  'vectordb': { 
+    'provider': 'lancedb', 
+    'config': { 
+      'collection_name': 'lancedb-index' 
+    } 
+  }
+}
+
+app = App.from_config(config=config)
+
+# add data source and start query in
+app.add("https://www.tesla.com/ns_videos/2022-tesla-impact-report.pdf")
+
+# query continuously
+while(True):
+    question = input("Enter question: ")
+    if question in ['q', 'exit', 'quit']:
+        break
+    answer = app.query(question)
+    print(answer)
+```
+
+</CodeGroup>
+
+
 <Snippet file="missing-vector-db-tip.mdx" />