feat: added more starter examples

Author: justinmerrell

cmd/project/starter_examples/LLM/src/handler.py

@@ -8,8 +8,8 @@
 from transformers import T5Tokenizer, T5ForConditionalGeneration
 
 # Initialize the tokenizer and model
-tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-base")
-model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-base", device_map="auto").to("cuda")
+tokenizer = T5Tokenizer.from_pretrained("<<MODEL_NAME>>")
+model = T5ForConditionalGeneration.from_pretrained("<<MODEL_NAME>>", device_map="auto").to("cuda")
 
 
 def handler(job: Dict[str, any]) -> str:

cmd/project/starter_examples/Stable Diffusion/src/handler.py

@@ -10,7 +10,7 @@
 
 # Initialize the pipeline
 pipe = AutoPipelineForText2Image.from_pretrained(
-            "stabilityai/sdxl-turbo", # model name
+            "<<MODEL_NAME>>", # model name
             torch_dtype=torch.float16, variant="fp16"
         ).to("cuda")
 

cmd/project/starter_examples/Text to Audio/.runpodignore

@@ -0,0 +1,10 @@
+# Similar to .gitignore
+# Matches do not sync to the Project Pod or cause the Pod to reload.
+
+Dockerfile
+__pycache__/
+*.pyc
+.*.swp
+.git/
+*.tmp
+*.log

cmd/project/starter_examples/Text to Audio/builder/requirements.txt

@@ -0,0 +1,13 @@
+# Required Python packages get listed here, one per line.
+# Lock the version number to avoid unexpected changes.
+
+# You can also install packages from a git repository, e.g.:
+# git+https://github.com/runpod/runpod-python.git
+# To learn more, see https://pip.pypa.io/en/stable/reference/requirements-file-format/
+
+<<RUNPOD>>
+hf_transfer
+
+torch
+transformers
+scipy

cmd/project/starter_examples/Text to Audio/src/handler.py

@@ -0,0 +1,47 @@
+''' A starter handler file using RunPod and transformers for audio generation. '''
+
+import io
+import base64
+from typing import Dict
+
+import scipy.io.wavfile
+from transformers import pipeline
+
+import runpod
+
+
+# Initialize the pipeline
+synthesizer = pipeline("text-to-audio", "<<MODEL_NAME>>", device=0)
+
+
+def handler(job):
+    """
+    Processes a text prompt to generate music, returning the result as a base64-encoded WAV audio.
+
+    Args:
+        job (dict): Contains 'input' with a 'prompt' key for the music generation text prompt.
+
+    Returns:
+        str: The generated audio as a base64-encoded string.
+    """
+    prompt = job['input']['prompt']
+    print(f"Received prompt: {prompt}")
+
+    result = synthesizer(prompt, forward_params={"do_sample": True, "max_new_tokens":300})
+
+    audio_data = result['audio']
+    sample_rate = result['sampling_rate']
+
+    # Prepare an in-memory bytes buffer to save the audio
+    audio_bytes = io.BytesIO()
+    scipy.io.wavfile.write(audio_bytes, sample_rate, audio_data)
+    audio_bytes.seek(0)
+
+    # Encode the WAV file to a base64 string
+    base64_audio = base64.b64encode(audio_bytes.read()).decode('utf-8')
+
+    # Return the base64 encoded audio with the appropriate data URI scheme
+    return f"data:audio/wav;base64,{base64_audio}"
+
+
+runpod.serverless.start({"handler": handler})