Basic Python API usage instructions

Closes #75

docs/python-api.md

@@ -4,18 +4,59 @@ LLM provides a Python API for executing prompts, in addition to the command-line
 
 Understanding this API is also important for writing plugins.
 
-The API consists of the following key classes:
+## Basic usage
+
+To run a prompt against the `gpt-3.5-turbo` model, run this:
+
+```python
+import llm
+
+model = llm.get_model("gpt-3.5-turbo")
+model.key = 'YOUR_API_KEY_HERE'
+response = model.prompt("Five surprising names for a pet pelican")
+print(response.text())
+```
+The `llm.get_model()` function accepts model names or aliases - so `chatgpt` would work here too.
+
+Run this command to see a list of available models and their aliases:
+
+```bash
+llm models list
+```
+
+If you have set a `OPENAI_API_KEY` environment variable you can omit the `model.key = ` line.
+
+### Models from plugins
+
+Any models you have installed as plugins will also be available through this mechanism, for example to use Google's PaLM 2 model with [llm-palm](https://github.com/simonw/llm-palm)
+
+```bash
+pip install llm-palm
+```
+```python
+import llm
+
+model = llm.get_model("palm")
+model.key = 'YOUR_API_KEY_HERE'
+response = model.prompt("Five surprising names for a pet pelican")
+print(response.text())
+```
+You can omit the `model.key = ` line for models that do not use an API key
+
+## Concepts
+
+The API consists of the following key concepts:
 
 - `Model` - represents a language model against which prompts can be executed
 - `Prompt` - a prompt that can be prepared and then executed against a model
 - `Response` - the response executing a prompt against a model
 - `Template` - a reusable template for generating prompts
 
-## Prompt
+### Prompt
 
 A prompt object represents all of the information needed to be passed to the LLM. This could be a single prompt string, but it might also include a separate system prompt, various settings (for temperature etc) or even a JSON array of previous messages.
 
-## Model
+### Model
 
 The `Model` class is an abstract base class that needs to be subclassed to provide a concrete implementation. Different LLMs will use different implementations of this class.
 
@@ -26,12 +67,12 @@ Model instances provide the following methods:
 
 Models usually return subclasses of `Response` that are specific to that model.
 
-## Response
+### Response
 
 The response from an LLM. This could encapusulate a string of text, but for streaming APIs this class will be iterable, with each iteration yielding a short string of text as it is generated.
 
 Calling `.text()` will return the full text of the response, waiting for the stream to stop executing if necessary.
 
-## Template
+### Template
 
 Templates are reusable objects that can be used to generate prompts. They are used  by the {ref}`prompt-templates` feature.