Skip to content

Conversation

@Zac-BotAi
Copy link
Owner

No description provided.

This commit introduces the capability to generate viral content based on the
textual content of a user-provided URL.

Key changes include:

- Modified `services/groq.js` to adapt its AI content strategy prompting. It
  can now generate strategies based on provided text content from a URL, in
  addition to the existing topic-based generation.
- Added a new `services/webExtractor.js` service. This service uses
  Playwright to navigate to a given URL and extract its main text content.
- Integrated the `WebExtractorService` into `server.js`. The
  `ViralContentSystem` now has a new method `createViralContentFromUrl` that
  orchestrates fetching content from a URL, generating an AI strategy based
  on that content, and then processing it through the existing media
  creation and social media distribution pipeline.
- Updated the `serviceRegistry` in `server.js` to include and manage the
  new `WebExtractorService`.
- Modified the existing `/mcp/viral-content` API endpoint to support a new
  method, `create_viral_content_from_url`. This allows clients to trigger
  the new URL-based content creation flow.

Conceptual data structures for future user and link management have also been
outlined, paving the way for further development of user-specific features
like toggling auto-upload and managing link lists.
… done so far and provide feedback for Jules to continue.
This commit incorporates significant improvements towards production readiness,
focusing on comprehensive error handling, system resilience, and enhancing
scalability and performance through asynchronous processing.

**1. Comprehensive Error Handling & Resilience:**

- **Service-Level Enhancements:**
  - `services/webExtractor.js`: I've implemented retry logic for Playwright operations, with contextual error logging.
  - `services/groq.js`: I've added retry logic for Groq API calls, specific handling for API error codes (401, 403, 429), validation of API responses, safe JSON parsing, and API key presence check.
- **Pipeline Orchestration (`ViralContentSystem` in `server.js`):**
  - I've added granular try-catch blocks and contextual error logging around each service call within the content creation pipelines. This improves observability and helps pinpoint failures.
- **Standardized API Error Responses (`server.js`):**
  - I've refined the `/mcp/viral-content` endpoint for robust validation of methods and parameters.
  - I've ensured consistent JSON-RPC error responses and appropriate HTTP status codes (4xx for your client errors, 5xx for server errors).
- **General Recommendations & Testing:**
  - I've outlined error handling guidelines for other services.
  - I've documented testing considerations for the new error handling mechanisms.

**2. Scalability & Performance:**

- **Job Queue System (BullMQ & Redis):**
  - I've introduced BullMQ with Redis for background job processing.
  - I've created `config/redisConfig.js` for Redis connection settings.
  - I've developed `lib/queue.js` to initialize and export a configured BullMQ `Queue` instance with default job options (retries, backoff, etc.).
- **Asynchronous API Endpoint (`server.js`):**
  - I've refactored the `/mcp/viral-content` endpoint to submit jobs to the BullMQ queue.
  - The API now returns a `202 Accepted` response with a `jobId` immediately, instead of processing tasks synchronously.
- **Background Processing (`worker.js`):**
  - I've created `worker.js` to process jobs from the BullMQ queue.
  - I now handle the actual content creation tasks asynchronously.
- **`ViralContentSystem` Refactoring (`core/viralSystem.js`):**
  - I've moved `ViralContentSystem`, `serviceRegistry`, and service initialization logic to a new `core/viralSystem.js` module.
  - This allows both `server.js` (API) and my background processing to use independent, fully functional instances of `ViralContentSystem` with all dependent services (AI, media, etc.) correctly initialized.
- **Background Processing Integration & Logging:**
  - I've ensured my background processing correctly uses the refactored `ViralContentSystem`.
  - I've implemented comprehensive logging in my background processing for job lifecycle events (start, completion, failure) with job IDs and error details.
- **Deployment & Testing (Conceptual):**
  - I've outlined conceptual changes for deployment configurations (e.g., Procfile, Docker) to manage new web and background processes.
  - I've documented testing strategies for the asynchronous, queue-based architecture.

These changes significantly improve the application's robustness, maintainability,
and its ability to handle tasks efficiently, paving the way for further
production hardening.
… done so far and provide feedback for Jules to continue.
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

None yet

Projects

None yet

Development

Successfully merging this pull request may close these issues.

1 participant