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[Refactor] Converge Pipeline and App classes (#1021)

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Co-authored-by: Deven Patel <deven298@yahoo.com>
This commit is contained in:
Deven Patel
2023-12-29 16:52:41 +05:30
committed by GitHub
parent c0aafd38c9
commit a926bcc640
91 changed files with 646 additions and 875 deletions
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14
docs/components/vector-databases.mdx
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@@ -22,7 +22,7 @@ Utilizing a vector database alongside Embedchain is a seamless process. All you
<CodeGroup>
```python main.py
from embedchain import Pipeline as App
from embedchain import App
# load chroma configuration from yaml file
app = App.from_config(config_path="config1.yaml")
@@ -67,7 +67,7 @@ You can authorize the connection to Elasticsearch by providing either `basic_aut
<CodeGroup>
```python main.py
from embedchain import Pipeline as App
from embedchain import App
# load elasticsearch configuration from yaml file
app = App.from_config(config_path="config.yaml")
@@ -97,7 +97,7 @@ pip install --upgrade 'embedchain[opensearch]'
<CodeGroup>
```python main.py
from embedchain import Pipeline as App
from embedchain import App
# load opensearch configuration from yaml file
app = App.from_config(config_path="config.yaml")
@@ -133,7 +133,7 @@ Set the Zilliz environment variables `ZILLIZ_CLOUD_URI` and `ZILLIZ_CLOUD_TOKEN`
```python main.py
import os
from embedchain import Pipeline as App
from embedchain import App
os.environ['ZILLIZ_CLOUD_URI'] = 'https://xxx.zillizcloud.com'
os.environ['ZILLIZ_CLOUD_TOKEN'] = 'xxx'
@@ -172,7 +172,7 @@ In order to use Pinecone as vector database, set the environment variables `PINE
<CodeGroup>
```python main.py
from embedchain import Pipeline as App
from embedchain import App
# load pinecone configuration from yaml file
app = App.from_config(config_path="config.yaml")
@@ -195,7 +195,7 @@ In order to use Qdrant as a vector database, set the environment variables `QDRA
<CodeGroup>
```python main.py
from embedchain import Pipeline as App
from embedchain import App
# load qdrant configuration from yaml file
app = App.from_config(config_path="config.yaml")
@@ -215,7 +215,7 @@ In order to use Weaviate as a vector database, set the environment variables `WE
<CodeGroup>
```python main.py
from embedchain import Pipeline as App
from embedchain import App
# load weaviate configuration from yaml file
app = App.from_config(config_path="config.yaml")