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 # Riffusion Inference Server
 
-Flask server that runs inference on a stable diffusion model for the riffusion app,
-using the diffusers library.
+Model inference backend for the Riffusion app.
+
+ * a diffusers pipeline that performs prompt interpolation combined with image conditioning
+ * a module for (approximately) converting between spectrograms and waveforms
+ * a flask server to provide model inference via API to the next.js app
+
+## Install
+Tested with Python 3.9 and diffusers 0.9.0
+
+```
+conda create --name riffusion-inference python=3.9
+conda activate riffusion-inference
+python -m pip install -r requirements.txt
+```
+
+## Run
+Start the Flask server:
+```
+python -m riffusion.server --port 3013 --host 127.0.0.1 --checkpoint /path/to/diffusers_checkpoint
+```
+
+The model endpoint is now available at `http://127.0.0.1:3013/run_inference` via POST request.
+
+Example input (see [InferenceInput](https://github.com/hmartiro/riffusion-inference/blob/main/riffusion/datatypes.py#L28) for the API):
+```
+{
+  alpha: 0.75,
+  num_inference_steps: 50,
+  seed_image_id: 0,
+
+  start: {
+    prompt: "church bells on sunday",
+    seed: 42,
+    denoising: 0.75,
+    guidance: 7.0,
+  },
+
+  end: {
+    prompt: "jazz with piano",
+    seed: 123,
+    denoising: 0.75,
+    guidance: 7.0,
+  },
+}
+```
+
+Example output (see [InferenceOutput](https://github.com/hmartiro/riffusion-inference/blob/main/riffusion/datatypes.py#L54) for the API):
+```
+{
+  image: "< base64 encoded PNG >",
+  audio: "< base64 encoded MP3 clip >",,
+}
+```
+