Small Fixes

README.md

@@ -65,20 +65,17 @@ For more details on the usage of these commands, refer to the [User Guide](https
 Example:
 
 ```python
->>> from vec_inf.api import VecInfClient
->>> client = VecInfClient()
->>> # Assume VEC_INF_ACCOUNT and VEC_INF_WORK_DIR is set
->>> response = client.launch_model("Meta-Llama-3.1-8B-Instruct")
->>> job_id = response.slurm_job_id
->>> status = client.get_status(job_id)
->>> if status.status == ModelStatus.READY:
-...     print(f"Model is ready at {status.base_url}")
->>> # Alternatively, use wait_until_ready which will either return a StatusResponse or throw a ServerError
->>> try:
->>>     status = wait_until_ready(job_id)
->>> except ServerError as e:
->>>     print(f"Model launch failed: {e}")
->>> client.shutdown_model(job_id)
+ffrom vec_inf.client import VecInfClient
+from vec_inf.client.models import ModelStatus
+
+client = VecInfClient()
+# Assume VEC_INF_ACCOUNT and VEC_INF_WORK_DIR is set
+response = client.launch_model("Meta-Llama-3.1-8B-Instruct")
+job_id = response.slurm_job_id
+status = client.get_status(job_id)
+if status == ModelStatus.READY:
+    print(f"Model is ready at {status.base_url}")
+client.shutdown_model(job_id)
 ```
 
 For details on the usage of the API, refer to the [API Reference](https://vectorinstitute.github.io/vector-inference/api/)

vec_inf/client/api.py

@@ -71,7 +71,7 @@ class VecInfClient:
 
     Examples
     --------
-    >>> from vec_inf.api import VecInfClient
+    >>> from vec_inf.client import VecInfClient
     >>> client = VecInfClient()
     >>> response = client.launch_model("Meta-Llama-3.1-8B-Instruct")
     >>> job_id = response.slurm_job_id

venv.sh

@@ -12,7 +12,7 @@ export UV_CACHE_DIR=/scratch/$(whoami)/uv_cache
 
 # To see if the cache directory is set correctly, run the following command
 # uv config get cache-dir
-echo "Cache directory set to: $(uv config get cache-dir)"
+echo "Cache directory set to: $(uv cache dir)"
 
 # Install dependencies via uv
 uv sync