Updated LanceDB Doc (#1445)

This commit is contained in:
Prashant Dixit
2024-06-24 23:25:20 +05:30
committed by GitHub
parent 14fc6bbadd
commit 18fb92f1f8

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@@ -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" />