chore: add readme for python root

python/README.md

@@ -1,16 +1,85 @@
 # OpenInference Python
 
-This is the Python version of OpenInference, a framework for collecting traces from LLM applications.
+This is the Python version of OpenInference instrumentation, a framework for collecting traces from LLM applications.
 
-## Development
 
-This project is built using hatch.
+# Getting Started
+Instrumentation is the act of adding observability code to an app yourself.
+If you’re instrumenting an app, you need to use the OpenTelemetry SDK for your language. You’ll then use the SDK to initialize OpenTelemetry and the API to instrument your code. This will emit telemetry from your app, and any library you installed that also comes with instrumentation.
 
-## Publishing
+# OpenAI Example
+Install openinference instrumentation for OpenAI:
 
-Publishing to PyPi is done using hatch.
+```shell
+pip install openinference-instrumentation-openai
+```
+
+This assumes that you already have OpenAI installed. If not, you can install it using:
+
+```shell
+pip install "openai>=1.0.0"
+```
+Currently only openai>=1.0.0 is supported.
+
+To export traces from the instrumentor to a collector, we use the OpenTelemetry SDK and the HTTP exporter. Install these using:
 
 ```shell
-hatch build
-hatch publish -u __token__
+pip install opentelemetry-sdk opentelemetry-exporter-otlp-proto-http
 ```
+
+Below shows a simple application calling chat completions from OpenAI.
+
+Note that the endpoint is set to collector running on `localhost:6006`, but can be changed if you are running a collector on a different location.
+
+```python
+import openai
+from openinference.instrumentation.openai import OpenAIInstrumentor
+from opentelemetry import trace as trace_api
+from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
+from opentelemetry.sdk import trace as trace_sdk
+from opentelemetry.sdk.resources import Resource
+from opentelemetry.sdk.trace.export import SimpleSpanProcessor
+
+# Set up the OpenTelemetry SDK tracer provider with an HTTP exporter.
+# Change the endpoint if the collector is running at a different location.
+endpoint = "http://localhost:6006/v1/traces"
+resource = Resource(attributes={})
+tracer_provider = trace_sdk.TracerProvider(resource=resource)
+span_exporter = OTLPSpanExporter(endpoint=endpoint)
+span_processor = SimpleSpanProcessor(span_exporter=span_exporter)
+tracer_provider.add_span_processor(span_processor=span_processor)
+trace_api.set_tracer_provider(tracer_provider=tracer_provider)
+
+# Call the instrumentor to instrument OpenAI
+OpenAIInstrumentor().instrument()
+
+# Run the OpenAI application.
+# Make you have your API key set in the environment variable OPENAI_API_KEY.
+if __name__ == "__main__":
+    response = openai.OpenAI().chat.completions.create(
+        model="gpt-3.5-turbo",
+        messages=[{"role": "user", "content": "Write a haiku."}],
+        max_tokens=20,
+    )
+    print(response.choices[0].message.content)
+```
+
+## Phoenix Collector
+
+If you don't have collector running, you can use the Phoenix collector. Install it using:
+
+```shell
+pip install arize-phoenix
+```
+
+Then before running the example above, start the collector using:
+
+```python
+import phoenix as px
+
+px.launch_app()
+```
+
+By default, the Phoenix collector is running on `http://localhost:6006/v1/traces`.
+
+Phoenix runs completely locally on your machine and does not collect any data over the internet.