movie narration agent #92
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Actionable comments posted: 4
🧹 Outside diff range and nitpick comments (4)
backend/director/tools/stabilityai.py (2)
48-48: Consider implementing an exponential backoff strategyInstead of a fixed polling interval, implement an exponential backoff strategy to reduce server load and respect API limits while still maintaining responsiveness.
Example implementation:
def get_next_interval(base_interval, attempt, max_interval=300): """Calculate next polling interval using exponential backoff.""" interval = min(base_interval * (2 ** attempt), max_interval) return intervalThis would provide a better balance between responsiveness and resource utilization.
Line range hint
84-84: Clean up temporary files after useThe temporary PNG file created for the image-to-video conversion is not being cleaned up, which could lead to disk space issues over time.
Add cleanup code:
with open(save_at, "wb") as f: f.write(result_response.content) + # Clean up temporary file + import os + try: + os.remove(temp_image_path) + except OSError as e: + print(f"Warning: Failed to remove temporary file {temp_image_path}: {e}")backend/director/handler.py (1)
62-62: Consider potential scalability impacts of movie narration.Since movie narration typically involves processing large files and potentially long-running operations:
- Consider implementing progress tracking for long-running narration tasks
- Evaluate if the default timeout settings in the chat method are sufficient
- Consider implementing resource usage limits or queuing mechanism for multiple concurrent narration requests
backend/director/agents/movie_narrator.py (1)
207-207: ReplaceUsing
logger.debugto utilize the configured logging system and maintain consistency.Apply this diff to replace
logger.debug:# Generate visual style visual_style = self.generate_visual_style(raw_storyline) - print("These are visual styles", visual_style) + logger.debug(f"Visual styles: {visual_style}") # Generate scenes scenes = self.generate_scene_sequence( raw_storyline, visual_style, engine ) - print("These are scenes", scenes) + logger.debug(f"Scenes: {scenes}") # Inside the video generation loop for index, scene in enumerate(scenes): - print(f"Generating video for scene {index + 1}...") - print("This is the prompt", prompt) + logger.debug(f"Generating video for scene {index + 1}...") + logger.debug(f"Prompt: {prompt}")Also applies to: 213-213, 237-238
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📒 Files selected for processing (3)
backend/director/agents/movie_narrator.py(1 hunks)backend/director/handler.py(2 hunks)backend/director/tools/stabilityai.py(1 hunks)
🧰 Additional context used
🪛 Ruff (0.8.0)
backend/director/agents/movie_narrator.py
222-222: Local variable generated_audio_results is assigned to but never used
Remove assignment to unused variable generated_audio_results
(F841)
🔇 Additional comments (3)
backend/director/tools/stabilityai.py (1)
48-48: Verify polling interval against Stability AI's best practices
The reduction in polling interval from 30s to 10s needs verification against Stability AI's recommended polling frequency.
✅ Verification successful
10-second polling interval is acceptable for Stability AI's API
The polling interval of 10 seconds is reasonable for the following reasons:
- The code is polling Stability AI's video generation status endpoint, which is a lightweight operation
- Other similar services in the codebase (Kling, ElevenLabs) use 30-second intervals, but they are different APIs
- The endpoint being polled (
/v2beta/image-to-video/result) is specifically designed for status checks - The implementation includes proper error handling and status code checks
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for any configuration files or documentation that might contain Stability AI's recommended polling intervals
rg -i "polling|interval|rate limit" README.md docs/
# Search for any existing configurations of polling intervals in the codebase
rg "polling_interval" --type python
Length of output: 120
Script:
#!/bin/bash
# Search for any configuration files or documentation that might contain Stability AI's recommended polling intervals
rg -i "polling|interval|rate limit"
# Search for any existing configurations of polling intervals in the codebase
rg "polling_interval"
# Look for Stability AI related configuration or documentation files
fd -e md -e py -e json -e yaml -e yml stability
Length of output: 1060
Script:
#!/bin/bash
# Let's examine the StabilityAI file content to understand the context of polling
cat backend/director/tools/stabilityai.py
# Let's also search for any rate limit related information in the codebase
rg -i "rate.?limit" -A 3 -B 3
Length of output: 4880
backend/director/handler.py (2)
23-23: LGTM! Import statement follows the established pattern.
The import statement is correctly placed and maintains consistency with other agent imports.
62-62: Verify MovieNarratorAgent implementation and compatibility.
While the agent registration looks correct, let's ensure:
- The agent properly implements the required interface
- It's compatible with the existing agent workflow in the chat method
✅ Verification successful
MovieNarratorAgent implementation is properly structured and compatible
The agent follows the correct implementation pattern:
- Inherits from BaseAgent
- Properly initializes required properties (agent_name, description, parameters)
- Includes necessary initialization logic in init
- Has a run method with proper parameters
- Contains appropriate engine configurations and error handling
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify MovieNarratorAgent implementation
# Check if MovieNarratorAgent follows the base agent pattern
ast-grep --pattern 'class MovieNarratorAgent($_):
$$$
name = $_
agent_description = $_
$$$'
# Check for required method implementations
ast-grep --pattern 'class MovieNarratorAgent($_):
$$$
async def execute($_):
$$$'
Length of output: 193
Script:
#!/bin/bash
# Let's try a different approach to locate and analyze MovieNarratorAgent
# First, find the file containing MovieNarratorAgent
rg "class MovieNarratorAgent" -l
# Then get the full implementation with context
rg "class MovieNarratorAgent" -A 30
# Also check for imports or usage patterns
rg "MovieNarratorAgent" -C 2
Length of output: 3613
Script:
#!/bin/bash
# Let's verify the base agent interface and execution method
# Check BaseAgent interface
rg "class BaseAgent" -A 10
# Check if execute method is implemented
rg "async def execute" backend/director/agents/movie_narrator.py -C 5
# Verify if the agent has all required base properties
rg "agent_name|description|parameters" backend/director/agents/movie_narrator.py
Length of output: 2842
| @@ -45,7 +45,7 @@ def __init__(self, api_key: str): | |||
| ) | |||
| self.video_endpoint = "https://api.stability.ai/v2beta/image-to-video" | |||
| self.result_endpoint = "https://api.stability.ai/v2beta/image-to-video/result" | |||
| self.polling_interval = 30 # seconds | |||
| self.polling_interval = 10 # seconds | |||
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Add rate limiting and timeout mechanisms
Reducing the polling interval to 10 seconds could lead to rate limit issues and potential infinite polling. Consider implementing:
- Rate limit handling with appropriate error catching
- A maximum timeout duration
- Request attempt counting
Here's a suggested implementation:
- self.polling_interval = 10 # seconds
+ self.polling_interval = 10 # seconds
+ self.max_attempts = 30 # 5 minutes maximum waiting time
+ self.rate_limit_pause = 60 # pause for 60s when rate limitedAnd in the polling loop:
attempts = 0
while attempts < self.max_attempts:
try:
result_response = requests.request(
"GET", f"{self.result_endpoint}/{generation_id}", headers=result_headers
)
if result_response.status_code == 429: # Rate limited
time.sleep(self.rate_limit_pause)
continue
result_response.raise_for_status()
if result_response.status_code == 202:
attempts += 1
time.sleep(self.polling_interval)
continue
elif result_response.status_code == 200:
with open(save_at, "wb") as f:
f.write(result_response.content)
break
except requests.exceptions.RequestException as e:
raise Exception(f"Error polling for video completion: {str(e)}")
if attempts >= self.max_attempts:
raise Exception("Timeout waiting for video generation")|
|
||
| engine_config = self.engine_configs[engine] | ||
| generated_videos_results = [] | ||
| generated_audio_results = [] |
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🛠️ Refactor suggestion
Remove unused variable 'generated_audio_results'
The variable generated_audio_results is assigned but never used. This results in unnecessary code that can be safely removed to improve readability.
Apply this diff to remove the unused variable:
engine_config = self.engine_configs[engine]
generated_videos_results = []
- generated_audio_results = []📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| generated_audio_results = [] | |
| engine_config = self.engine_configs[engine] | |
| generated_videos_results = [] |
🧰 Tools
🪛 Ruff (0.8.0)
222-222: Local variable generated_audio_results is assigned to but never used
Remove assignment to unused variable generated_audio_results
(F841)
| raw_storyline = movie_narrator.get("storyline", []) | ||
| video_gen_config = movie_narrator.get(self.video_gen_config_key, {}) | ||
| audio_gen_config = movie_narrator.get(self.audio_gen_config_key, {}) |
There was a problem hiding this comment.
Handle potential 'None' for 'movie_narrator' parameter
At line 201, movie_narrator is accessed without checking if it is None. This could raise an AttributeError if movie_narrator is None. To prevent this, add a check before accessing its methods.
Apply this diff to handle the potential None value:
+ if not movie_narrator:
+ raise ValueError("The 'movie_narrator' parameter is required for job type 'movie_narrator'")
raw_storyline = movie_narrator.get("storyline", [])
video_gen_config = movie_narrator.get(self.video_gen_config_key, {})
audio_gen_config = movie_narrator.get(self.audio_gen_config_key, {})📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| raw_storyline = movie_narrator.get("storyline", []) | |
| video_gen_config = movie_narrator.get(self.video_gen_config_key, {}) | |
| audio_gen_config = movie_narrator.get(self.audio_gen_config_key, {}) | |
| if not movie_narrator: | |
| raise ValueError("The 'movie_narrator' parameter is required for job type 'movie_narrator'") | |
| raw_storyline = movie_narrator.get("storyline", []) | |
| video_gen_config = movie_narrator.get(self.video_gen_config_key, {}) | |
| audio_gen_config = movie_narrator.get(self.audio_gen_config_key, {}) |
| except Exception as e: | ||
| logger.exception(f"Error in {self.agent_name} agent: {e}") | ||
| video_content.status = MsgStatus.error | ||
| video_content.status_message = "Error generating movie" | ||
| self.output_message.publish() | ||
| return AgentResponse( | ||
| status=AgentStatus.ERROR, message=f"Agent failed with error: {str(e)}" | ||
| ) |
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Ensure 'video_content' is defined before exception handling
If an exception occurs before video_content is defined (before line 163), accessing video_content in the except block will raise an UnboundLocalError. To prevent this, initialize video_content before the try block.
Apply this diff to initialize video_content:
+ video_content = VideoContent(
+ agent_name=self.agent_name,
+ status=MsgStatus.progress,
+ status_message="Initializing...",
+ )
try:
self.videodb_tool = VideoDBTool(collection_id=collection_id)
self.output_message.actions.append("Processing input...")
video_content.status_message = "Generating movie..."Committable suggestion skipped: line range outside the PR's diff.
Summary by CodeRabbit
New Features
MovieNarratorAgentfor generating movies with narrations and voiceovers based on storylines.Improvements