Merge branch 'dev' into dependabot/github_actions/dev/peter-evans/rep…

…ository-dispatch-3

autogpt_platform/backend/backend/blocks/ai_music_generator.py

@@ -0,0 +1,224 @@
+import logging
+import time
+from enum import Enum
+from typing import Literal
+
+import replicate
+from autogpt_libs.supabase_integration_credentials_store.types import APIKeyCredentials
+from pydantic import SecretStr
+
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import CredentialsField, CredentialsMetaInput, SchemaField
+
+logger = logging.getLogger(__name__)
+
+TEST_CREDENTIALS = APIKeyCredentials(
+    id="01234567-89ab-cdef-0123-456789abcdef",
+    provider="replicate",
+    api_key=SecretStr("mock-replicate-api-key"),
+    title="Mock Replicate API key",
+    expires_at=None,
+)
+TEST_CREDENTIALS_INPUT = {
+    "provider": TEST_CREDENTIALS.provider,
+    "id": TEST_CREDENTIALS.id,
+    "type": TEST_CREDENTIALS.type,
+    "title": TEST_CREDENTIALS.type,
+}
+
+
+# Model version enum
+class MusicGenModelVersion(str, Enum):
+    STEREO_LARGE = "stereo-large"
+    MELODY_LARGE = "melody-large"
+    LARGE = "large"
+
+
+# Audio format enum
+class AudioFormat(str, Enum):
+    WAV = "wav"
+    MP3 = "mp3"
+
+
+# Normalization strategy enum
+class NormalizationStrategy(str, Enum):
+    LOUDNESS = "loudness"
+    CLIP = "clip"
+    PEAK = "peak"
+    RMS = "rms"
+
+
+class AIMusicGeneratorBlock(Block):
+    class Input(BlockSchema):
+        credentials: CredentialsMetaInput[Literal["replicate"], Literal["api_key"]] = (
+            CredentialsField(
+                provider="replicate",
+                supported_credential_types={"api_key"},
+                description="The Replicate integration can be used with "
+                "any API key with sufficient permissions for the blocks it is used on.",
+            )
+        )
+        prompt: str = SchemaField(
+            description="A description of the music you want to generate",
+            placeholder="e.g., 'An upbeat electronic dance track with heavy bass'",
+            title="Prompt",
+        )
+        model_version: MusicGenModelVersion = SchemaField(
+            description="Model to use for generation",
+            default=MusicGenModelVersion.STEREO_LARGE,
+            title="Model Version",
+        )
+        duration: int = SchemaField(
+            description="Duration of the generated audio in seconds",
+            default=8,
+            title="Duration",
+        )
+        temperature: float = SchemaField(
+            description="Controls the 'conservativeness' of the sampling process. Higher temperature means more diversity",
+            default=1.0,
+            title="Temperature",
+        )
+        top_k: int = SchemaField(
+            description="Reduces sampling to the k most likely tokens",
+            default=250,
+            title="Top K",
+        )
+        top_p: float = SchemaField(
+            description="Reduces sampling to tokens with cumulative probability of p. When set to 0 (default), top_k sampling is used",
+            default=0.0,
+            title="Top P",
+        )
+        classifier_free_guidance: int = SchemaField(
+            description="Increases the influence of inputs on the output. Higher values produce lower-variance outputs that adhere more closely to inputs",
+            default=3,
+            title="Classifier Free Guidance",
+        )
+        output_format: AudioFormat = SchemaField(
+            description="Output format for generated audio",
+            default=AudioFormat.WAV,
+            title="Output Format",
+        )
+        normalization_strategy: NormalizationStrategy = SchemaField(
+            description="Strategy for normalizing audio",
+            default=NormalizationStrategy.LOUDNESS,
+            title="Normalization Strategy",
+        )
+
+    class Output(BlockSchema):
+        result: str = SchemaField(description="URL of the generated audio file")
+        error: str = SchemaField(description="Error message if the model run failed")
+
+    def __init__(self):
+        super().__init__(
+            id="44f6c8ad-d75c-4ae1-8209-aad1c0326928",
+            description="This block generates music using Meta's MusicGen model on Replicate.",
+            categories={BlockCategory.AI},
+            input_schema=AIMusicGeneratorBlock.Input,
+            output_schema=AIMusicGeneratorBlock.Output,
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "prompt": "An upbeat electronic dance track with heavy bass",
+                "model_version": MusicGenModelVersion.STEREO_LARGE,
+                "duration": 8,
+                "temperature": 1.0,
+                "top_k": 250,
+                "top_p": 0.0,
+                "classifier_free_guidance": 3,
+                "output_format": AudioFormat.WAV,
+                "normalization_strategy": NormalizationStrategy.LOUDNESS,
+            },
+            test_output=[
+                (
+                    "result",
+                    "https://replicate.com/output/generated-audio-url.wav",
+                ),
+            ],
+            test_mock={
+                "run_model": lambda api_key, model_version, prompt, duration, temperature, top_k, top_p, classifier_free_guidance, output_format, normalization_strategy: "https://replicate.com/output/generated-audio-url.wav",
+            },
+            test_credentials=TEST_CREDENTIALS,
+        )
+
+    def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        max_retries = 3
+        retry_delay = 5  # seconds
+        last_error = None
+
+        for attempt in range(max_retries):
+            try:
+                logger.debug(
+                    f"[AIMusicGeneratorBlock] - Running model (attempt {attempt + 1})"
+                )
+                result = self.run_model(
+                    api_key=credentials.api_key,
+                    model_version=input_data.model_version,
+                    prompt=input_data.prompt,
+                    duration=input_data.duration,
+                    temperature=input_data.temperature,
+                    top_k=input_data.top_k,
+                    top_p=input_data.top_p,
+                    classifier_free_guidance=input_data.classifier_free_guidance,
+                    output_format=input_data.output_format,
+                    normalization_strategy=input_data.normalization_strategy,
+                )
+                if result and result != "No output received":
+                    yield "result", result
+                    return
+                else:
+                    last_error = "Model returned empty or invalid response"
+                    raise ValueError(last_error)
+            except Exception as e:
+                last_error = f"Unexpected error: {str(e)}"
+                logger.error(f"[AIMusicGeneratorBlock] - Error: {last_error}")
+                if attempt < max_retries - 1:
+                    time.sleep(retry_delay)
+                    continue
+
+        # If we've exhausted all retries, yield the error
+        yield "error", f"Failed after {max_retries} attempts. Last error: {last_error}"
+
+    def run_model(
+        self,
+        api_key: SecretStr,
+        model_version: MusicGenModelVersion,
+        prompt: str,
+        duration: int,
+        temperature: float,
+        top_k: int,
+        top_p: float,
+        classifier_free_guidance: int,
+        output_format: AudioFormat,
+        normalization_strategy: NormalizationStrategy,
+    ):
+        # Initialize Replicate client with the API key
+        client = replicate.Client(api_token=api_key.get_secret_value())
+
+        # Run the model with parameters
+        output = client.run(
+            "meta/musicgen:671ac645ce5e552cc63a54a2bbff63fcf798043055d2dac5fc9e36a837eedcfb",
+            input={
+                "prompt": prompt,
+                "model_version": model_version,
+                "duration": duration,
+                "temperature": temperature,
+                "top_k": top_k,
+                "top_p": top_p,
+                "classifier_free_guidance": classifier_free_guidance,
+                "output_format": output_format,
+                "normalization_strategy": normalization_strategy,
+            },
+        )
+
+        # Handle the output
+        if isinstance(output, list) and len(output) > 0:
+            result_url = output[0]  # If output is a list, get the first element
+        elif isinstance(output, str):
+            result_url = output  # If output is a string, use it directly
+        else:
+            result_url = (
+                "No output received"  # Fallback message if output is not as expected
+            )
+
+        return result_url

autogpt_platform/frontend/src/components/ui/render.tsx

@@ -22,6 +22,12 @@ const isValidImageUrl = (url: string): boolean => {
   return imageExtensions.test(cleanedUrl);
 };
 
+const isValidAudioUrl = (url: string): boolean => {
+  const audioExtensions = /\.(mp3|wav)$/i;
+  const cleanedUrl = url.split("?")[0];
+  return audioExtensions.test(cleanedUrl);
+};
+
 const VideoRenderer: React.FC<{ videoUrl: string }> = ({ videoUrl }) => {
   const videoId = getYouTubeVideoId(videoUrl);
   return (
@@ -58,6 +64,18 @@ const ImageRenderer: React.FC<{ imageUrl: string }> = ({ imageUrl }) => (
   </div>
 );
 
+const AudioRenderer: React.FC<{ audioUrl: string }> = ({ audioUrl }) => (
+  <div className="w-full p-2">
+    <audio controls className="w-full">
+      <source
+        src={audioUrl}
+        type={`audio/${audioUrl.split(".").pop()?.toLowerCase()}`}
+      />
+      Your browser does not support the audio element.
+    </audio>
+  </div>
+);
+
 const TextRenderer: React.FC<{ value: any; truncateLongData?: boolean }> = ({
   value,
   truncateLongData,
@@ -79,6 +97,8 @@ export const ContentRenderer: React.FC<{
       return <VideoRenderer videoUrl={value} />;
     } else if (isValidImageUrl(value)) {
       return <ImageRenderer imageUrl={value} />;
+    } else if (isValidAudioUrl(value)) {
+      return <AudioRenderer audioUrl={value} />;
     }
   }
   return <TextRenderer value={value} truncateLongData={truncateLongData} />;