feat(platform): Add multimedia file support & add basic Video blocks

autogpt_platform/backend/backend/blocks/basic.py

@@ -3,13 +3,50 @@
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema, BlockType
 from backend.data.model import SchemaField
+from backend.util.file import store_temp_file
 from backend.util.mock import MockObject
 from backend.util.text import TextFormatter
 from backend.util.type import convert
 
 formatter = TextFormatter()
 
 
+class FileStoreBlock(Block):
+    class Input(BlockSchema):
+        file_in: str = SchemaField(
+            description="The file to store in the temporary directory, it can be a URL, data URI, or local path."
+        )
+
+    class Output(BlockSchema):
+        file_out: str = SchemaField(
+            description="The relative path to the stored file in the temporary directory."
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="cbb50872-625b-42f0-8203-a2ae78242d8a",
+            description="Stores the input file in the temporary directory.",
+            categories={BlockCategory.BASIC, BlockCategory.MULTIMEDIA},
+            input_schema=FileStoreBlock.Input,
+            output_schema=FileStoreBlock.Output,
+            static_output=True,
+        )
+
+    def run(
+        self,
+        input_data: Input,
+        *,
+        graph_exec_id: str,
+        **kwargs,
+    ) -> BlockOutput:
+        file_path = store_temp_file(
+            graph_exec_id=graph_exec_id,
+            file=input_data.file_in,
+            return_content=False,
+        )
+        yield "file_out", file_path
+
+
 class StoreValueBlock(Block):
     """
     This block allows you to provide a constant value as a block, in a stateless manner.

autogpt_platform/backend/backend/blocks/ideogram.py

@@ -151,7 +151,7 @@ def __init__(self):
         super().__init__(
             id="6ab085e2-20b3-4055-bc3e-08036e01eca6",
             description="This block runs Ideogram models with both simple and advanced settings.",
-            categories={BlockCategory.AI},
+            categories={BlockCategory.AI, BlockCategory.MULTIMEDIA},
             input_schema=IdeogramModelBlock.Input,
             output_schema=IdeogramModelBlock.Output,
             test_input={

autogpt_platform/backend/backend/blocks/media.py

@@ -0,0 +1,243 @@
+import os
+import tempfile
+from typing import Literal, Optional
+
+from moviepy.audio.io.AudioFileClip import AudioFileClip
+from moviepy.video.fx.Loop import Loop
+from moviepy.video.io.VideoFileClip import VideoFileClip
+
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import SchemaField
+from backend.util.file import get_exec_file_path, store_temp_file
+
+
+class MediaDurationBlock(Block):
+
+    class Input(BlockSchema):
+        media_in: str = SchemaField(
+            description="Media input (URL, data URI, or local path)."
+        )
+        is_video: bool = SchemaField(
+            description="Whether the media is a video (True) or audio (False).",
+            default=True,
+        )
+
+    class Output(BlockSchema):
+        duration: float = SchemaField(
+            description="Duration of the media file (in seconds)."
+        )
+        error: str = SchemaField(
+            description="Error message if something fails.", default=""
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="d8b91fd4-da26-42d4-8ecb-8b196c6d84b6",
+            description="Block to get the duration of a media file.",
+            categories={BlockCategory.MULTIMEDIA},
+            input_schema=MediaDurationBlock.Input,
+            output_schema=MediaDurationBlock.Output,
+        )
+
+    def run(
+        self,
+        input_data: Input,
+        *,
+        graph_exec_id: str,
+        **kwargs,
+    ) -> BlockOutput:
+        # 1) Store the input media locally
+        local_media_path = store_temp_file(
+            graph_exec_id=graph_exec_id,
+            file=input_data.media_in,
+            return_content=False,
+        )
+        media_abspath = get_exec_file_path(graph_exec_id, local_media_path)
+
+        # 2) Load the clip
+        if input_data.is_video:
+            clip = VideoFileClip(media_abspath)
+        else:
+            clip = AudioFileClip(media_abspath)
+
+        yield "duration", clip.duration
+
+
+class LoopVideoBlock(Block):
+    """
+    Block for looping (repeating) a video clip until a given duration or number of loops.
+    """
+
+    class Input(BlockSchema):
+        video_in: str = SchemaField(
+            description="The input video (can be a URL, data URI, or local path)."
+        )
+        # Provide EITHER a `duration` or `n_loops` or both. We'll demonstrate `duration`.
+        duration: Optional[float] = SchemaField(
+            description="Target duration (in seconds) to loop the video to. If omitted, defaults to no looping.",
+            default=None,
+            ge=0.0,
+        )
+        n_loops: Optional[int] = SchemaField(
+            description="Number of times to repeat the video. If omitted, defaults to 1 (no repeat).",
+            default=None,
+            ge=1,
+        )
+        output_return_type: Literal["file_path", "data_uri"] = SchemaField(
+            description="How to return the output video. Either a relative path or base64 data URI.",
+            default="file_path",
+        )
+
+    class Output(BlockSchema):
+        video_out: str = SchemaField(
+            description="Looped video returned either as a relative path or a data URI."
+        )
+        error: str = SchemaField(
+            description="Error message if something fails.", default=""
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="8bf9eef6-5451-4213-b265-25306446e94b",
+            description="Block to loop a video to a given duration or number of repeats.",
+            categories={BlockCategory.MULTIMEDIA},
+            input_schema=LoopVideoBlock.Input,
+            output_schema=LoopVideoBlock.Output,
+        )
+
+    def run(
+        self,
+        input_data: Input,
+        *,
+        node_exec_id: str,
+        graph_exec_id: str,
+        **kwargs,
+    ) -> BlockOutput:
+        # 1) Store the input video locally
+        local_video_path = store_temp_file(
+            graph_exec_id=graph_exec_id,
+            file=input_data.video_in,
+            return_content=False,
+        )
+        input_abspath = get_exec_file_path(graph_exec_id, local_video_path)
+
+        # 2) Load the clip
+        clip = VideoFileClip(input_abspath)
+
+        # 3) Apply the loop effect
+        looped_clip = clip
+        if input_data.duration:
+            # Loop until we reach the specified duration
+            looped_clip = looped_clip.with_effects([Loop(duration=input_data.duration)])
+        elif input_data.n_loops:
+            looped_clip = looped_clip.with_effects([Loop(n=input_data.n_loops)])
+        else:
+            raise ValueError("Either 'duration' or 'n_loops' must be provided.")
+
+        assert isinstance(looped_clip, VideoFileClip)
+
+        # 4) Save the looped output
+        output_filename = f"{node_exec_id}_looped_{os.path.basename(local_video_path)}"
+        output_abspath = get_exec_file_path(graph_exec_id, output_filename)
+
+        looped_clip = looped_clip.with_audio(clip.audio)
+        looped_clip.write_videofile(output_abspath, codec="libx264", audio_codec="aac")
+
+        # Return as data URI
+        video_out = store_temp_file(
+            graph_exec_id=graph_exec_id,
+            file=output_filename,
+            return_content=input_data.output_return_type == "data_uri",
+        )
+
+        yield "video_out", video_out
+
+
+class AddAudioToVideoBlock(Block):
+    """
+    Block that adds (attaches) an audio track to an existing video.
+    Optionally scale the volume of the new track.
+    """
+
+    class Input(BlockSchema):
+        video_in: str = SchemaField(
+            description="Video input (URL, data URI, or local path)."
+        )
+        audio_in: str = SchemaField(
+            description="Audio input (URL, data URI, or local path)."
+        )
+        volume: float = SchemaField(
+            description="Volume scale for the newly attached audio track (1.0 = original).",
+            default=1.0,
+        )
+        output_return_type: Literal["file_path", "data_uri"] = SchemaField(
+            description="Return the final output as a relative path or base64 data URI.",
+            default="file_path",
+        )
+
+    class Output(BlockSchema):
+        video_out: str = SchemaField(
+            description="Final video (with attached audio), as a path or data URI."
+        )
+        error: str = SchemaField(
+            description="Error message if something fails.", default=""
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="3503748d-62b6-4425-91d6-725b064af509",
+            description="Block to attach an audio file to a video file using moviepy.",
+            categories={BlockCategory.MULTIMEDIA},
+            input_schema=AddAudioToVideoBlock.Input,
+            output_schema=AddAudioToVideoBlock.Output,
+        )
+
+    def run(
+        self,
+        input_data: Input,
+        *,
+        node_exec_id: str,
+        graph_exec_id: str,
+        **kwargs,
+    ) -> BlockOutput:
+        # 1) Store the inputs locally
+        local_video_path = store_temp_file(
+            graph_exec_id=graph_exec_id,
+            file=input_data.video_in,
+            return_content=False,
+        )
+        local_audio_path = store_temp_file(
+            graph_exec_id=graph_exec_id,
+            file=input_data.audio_in,
+            return_content=False,
+        )
+
+        abs_temp_dir = os.path.join(tempfile.gettempdir(), "exec_file", graph_exec_id)
+        video_abspath = os.path.join(abs_temp_dir, local_video_path)
+        audio_abspath = os.path.join(abs_temp_dir, local_audio_path)
+
+        # 2) Load video + audio with moviepy
+        video_clip = VideoFileClip(video_abspath)
+        audio_clip = AudioFileClip(audio_abspath)
+        # Optionally scale volume
+        if input_data.volume != 1.0:
+            audio_clip = audio_clip.with_volume_scaled(input_data.volume)
+
+        # 3) Attach the new audio track
+        final_clip = video_clip.with_audio(audio_clip)
+
+        # 4) Write to output file
+        output_filename = (
+            f"{node_exec_id}_audio_attached_{os.path.basename(local_video_path)}"
+        )
+        output_abspath = os.path.join(abs_temp_dir, output_filename)
+        final_clip.write_videofile(output_abspath, codec="libx264", audio_codec="aac")
+
+        # 5) Return either path or data URI
+        video_out = store_temp_file(
+            graph_exec_id=graph_exec_id,
+            file=output_filename,
+            return_content=input_data.output_return_type == "data_uri",
+        )
+
+        yield "video_out", video_out

autogpt_platform/backend/backend/blocks/replicate_flux_advanced.py

@@ -131,7 +131,7 @@ def __init__(self):
         super().__init__(
             id="90f8c45e-e983-4644-aa0b-b4ebe2f531bc",
             description="This block runs Flux models on Replicate with advanced settings.",
-            categories={BlockCategory.AI},
+            categories={BlockCategory.AI, BlockCategory.MULTIMEDIA},
             input_schema=ReplicateFluxAdvancedModelBlock.Input,
             output_schema=ReplicateFluxAdvancedModelBlock.Output,
             test_input={

autogpt_platform/backend/backend/blocks/talking_head.py

@@ -78,7 +78,7 @@ def __init__(self):
         super().__init__(
             id="98c6f503-8c47-4b1c-a96d-351fc7c87dab",
             description="This block integrates with D-ID to create video clips and retrieve their URLs.",
-            categories={BlockCategory.AI},
+            categories={BlockCategory.AI, BlockCategory.MULTIMEDIA},
             input_schema=CreateTalkingAvatarVideoBlock.Input,
             output_schema=CreateTalkingAvatarVideoBlock.Output,
             test_input={

autogpt_platform/backend/backend/blocks/text_to_speech_block.py

@@ -53,7 +53,7 @@ def __init__(self):
         super().__init__(
             id="4ff1ff6d-cc40-4caa-ae69-011daa20c378",
             description="Converts text to speech using the Unreal Speech API",
-            categories={BlockCategory.AI, BlockCategory.TEXT},
+            categories={BlockCategory.AI, BlockCategory.TEXT, BlockCategory.MULTIMEDIA},
             input_schema=UnrealTextToSpeechBlock.Input,
             output_schema=UnrealTextToSpeechBlock.Output,
             test_input={

autogpt_platform/backend/backend/data/block.py

@@ -66,6 +66,7 @@ class BlockCategory(Enum):
     )
     PRODUCTIVITY = "Block that helps with productivity"
     ISSUE_TRACKING = "Block that helps with issue tracking"
+    MULTIMEDIA = "Block that interacts with multimedia content"
 
     def dict(self) -> dict[str, str]:
         return {"category": self.name, "description": self.value}

autogpt_platform/backend/backend/executor/manager.py

@@ -40,6 +40,7 @@
 from backend.integrations.creds_manager import IntegrationCredentialsManager
 from backend.util import json
 from backend.util.decorator import error_logged, time_measured
+from backend.util.file import clean_exec_files
 from backend.util.logging import configure_logging
 from backend.util.process import set_service_name
 from backend.util.service import (
@@ -169,7 +170,12 @@ def update_execution(status: ExecutionStatus) -> ExecutionResult:
     log_metadata.info("Executed node with input", input=input_data_str)
     update_execution(ExecutionStatus.RUNNING)
 
-    extra_exec_kwargs = {}
+    extra_exec_kwargs: dict = {
+        "graph_id": graph_id,
+        "node_id": node_id,
+        "graph_exec_id": graph_exec_id,
+        "node_exec_id": node_exec_id,
+    }
     # Last-minute fetch credentials + acquire a system-wide read-write lock to prevent
     # changes during execution. ⚠️ This means a set of credentials can only be used by
     # one (running) block at a time; simultaneous execution of blocks using same
@@ -725,6 +731,7 @@ def callback(result: object):
                 finished = True
                 cancel.set()
             cancel_thread.join()
+            clean_exec_files(graph_exec.graph_exec_id)
 
         return (
             exec_stats,