janhq · vansangpfiev · Mar 20, 2025 · Mar 19, 2025
diff --git a/.github/workflows/python-script-package.yml b/.github/workflows/python-script-package.yml
diff --git a/.github/workflows/python-venv-package.yml b/.github/workflows/python-venv-package.yml
diff --git a/docs/docs/architecture.mdx b/docs/docs/architecture.mdx
@@ -144,4 +144,3 @@ The sequence diagram above outlines the interactions between various components
 Our development roadmap outlines key features and epics we will focus on in the upcoming releases. These enhancements aim to improve functionality, increase efficiency, and expand Cortex's capabilities.
 
 - **RAG**: Improve response quality and contextual relevance in our AI models.
-- **Cortex Python Runtime**: Provide a scalable Python execution environment for Cortex.
diff --git a/docs/docs/basic-usage/index.mdx b/docs/docs/basic-usage/index.mdx
@@ -35,8 +35,7 @@ curl --request DELETE \
 ```
 
 ## Engines
-Cortex currently supports a general Python Engine for highly customised deployments and
-2 specialized ones for different multi-modal foundation models: llama.cpp and ONNXRuntime.
+Cortex currently supports 2 specialized ones for different multi-modal foundation models: llama.cpp and ONNXRuntime.
 
 By default, Cortex installs `llama.cpp` as it main engine as it can be used in most laptops,
 desktop environments and operating systems.

diff --git a/docs/docs/capabilities/models/index.mdx b/docs/docs/capabilities/models/index.mdx
@@ -22,8 +22,6 @@ Cortex supports three model formats and each model format require specific engin
 - GGUF - run with `llama-cpp` engine
 - ONNX - run with `onnxruntime` engine
 
-Within the Python Engine (currently under development), you can run models in other formats
-
 :::info
 For details on each format, see the [Model Formats](/docs/capabilities/models/model-yaml#model-formats) page.
 :::
Original file line number	Diff line number	Diff line change
Expand Up		@@ -144,4 +144,3 @@ The sequence diagram above outlines the interactions between various components
		Our development roadmap outlines key features and epics we will focus on in the upcoming releases. These enhancements aim to improve functionality, increase efficiency, and expand Cortex's capabilities.

		- RAG: Improve response quality and contextual relevance in our AI models.
		- Cortex Python Runtime: Provide a scalable Python execution environment for Cortex.