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[Feature]: Add posthog anonymous telemetry and update docs (#867)

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This commit is contained in:
Deshraj Yadav
2023-10-29 01:20:21 -07:00
committed by GitHub
parent 35c2b83015
commit 81336668b3
34 changed files with 242 additions and 195 deletions
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10
docs/components/embedding-models.mdx
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@@ -24,7 +24,7 @@ Once you have obtained the key, you can use it like this:
```python main.py
import os
from embedchain import App
from embedchain import Pipeline as App
os.environ['OPENAI_API_KEY'] = 'xxx'
@@ -52,7 +52,7 @@ To use Azure OpenAI embedding model, you have to set some of the azure openai re
```python main.py
import os
from embedchain import App
from embedchain import Pipeline as App
os.environ["OPENAI_API_TYPE"] = "azure"
os.environ["OPENAI_API_BASE"] = "https://xxx.openai.azure.com/"
@@ -90,7 +90,7 @@ GPT4All supports generating high quality embeddings of arbitrary length document
<CodeGroup>
```python main.py
from embedchain import App
from embedchain import Pipeline as App
# load embedding model configuration from config.yaml file
app = App.from_config(yaml_path="config.yaml")
@@ -119,7 +119,7 @@ Hugging Face supports generating embeddings of arbitrary length documents of tex
<CodeGroup>
```python main.py
from embedchain import App
from embedchain import Pipeline as App
# load embedding model configuration from config.yaml file
app = App.from_config(yaml_path="config.yaml")
@@ -150,7 +150,7 @@ Embedchain supports Google's VertexAI embeddings model through a simple interfac
<CodeGroup>
```python main.py
from embedchain import App
from embedchain import Pipeline as App
# load embedding model configuration from config.yaml file
app = App.from_config(yaml_path="config.yaml")