update README

README.md

@@ -83,6 +83,8 @@ We are continuously expanding the support matrix. If you have any specific requi
   - ```bitblas.Matmul``` implements the $W_{wdtype}A_{adtype}$ mixed-precision matrix multiplication of $C_{cdtype}[M, N] = A_{adtype}[M, K] \times W_{wdtype}[N, K]$.
   - ```bitblas.Linear``` is a PyTorch ```nn.Linear```-like module to support a Linear of mixed-precision.
 
+- [Python API](https://github.com/microsoft/BitBLAS/blob/main/docs/PythonAPI.md): The Python API doc of BitBLAS.
+
 - [Integration](https://github.com/microsoft/BitBLAS/tree/main/integration): Explore how BitBLAS seamlessly integrates with LLM deployment frameworks through our examples. Discover the ease of integrating BitBLAS with PyTorch, AutoGPTQ, and vLLM in the 3rd-party integration examples.
 
 - [Customization](https://github.com/microsoft/BitBLAS/blob/main/docs/ExtendOperatorsWithDSL.md): BitBLAS supports implementing customized mixed-precision DNN operations rather than matrix multiplication with the flexible DSL (TIR Script).