Small markdown improvements (#44)

* Add readme to doc tests

* formatting

* Add sample images

* Delete images

Makefile

@@ -37,7 +37,7 @@ test-integ: install  ## Run tests against the integ API server (needs GROUNDLIGH
 	GROUNDLIGHT_ENDPOINT="https://api.integ.groundlight.ai/" ${PYTEST} ${TEST_ARGS} test
 
 test-docs: install  ## Run the example code and tests in our docs against the prod API (needs GROUNDLIGHT_API_TOKEN)
-	poetry run pytest -v --markdown-docs ${TEST_ARGS} docs
+	poetry run pytest -v --markdown-docs ${TEST_ARGS} docs README.md
 
 # Adjust which paths we lint
 LINT_PATHS="src test bin samples"

README.md

@@ -8,14 +8,18 @@ Groundlight makes it simple to build reliable visual applications. Read the [ful
 pip install groundlight
 ```
 
-Build a working computer vision system in just 5 lines of python:
+Build a working computer vision system in just a few lines of python:
 
 ```python
 from groundlight import Groundlight
+from PIL import Image
+import requests
 
 gl = Groundlight()
-d = gl.get_or_create_detector(name="door", query="Is the door open?")
-image_query = gl.submit_image_query(detector=d, image=jpeg_img)
+d = gl.get_or_create_detector(name="doorway", query="Is the doorway open?")
+image_url = "https://images.selfstorage.com/large-compress/2174925f24362c479b2.jpg"
+image = Image.open(requests.get(image_url, stream=True).raw)
+image_query = gl.submit_image_query(detector=d, image=image)
 print(f"The answer is {image_query.result}")
 ```
 

pyproject.toml

@@ -1,15 +1,15 @@
 [tool.poetry]
 authors = ["Groundlight AI <[email protected]>"]
 description = "Build computer vision systems from natural language with Groundlight"
-homepage = "https://www.groundlight.ai"
+homepage = "https://code.groundlight.ai/python-sdk"
 license = "MIT"
 name = "groundlight"
 packages = [
     {include = "**/*.py", from = "generated"},
     {include = "**/*.py", from = "src"},
 ]
 readme = "README.md"
-version = "0.7.6"
+version = "0.7.7"
 
 [tool.poetry.dependencies]
 certifi = "^2021.10.8"