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Update DEVELOPMENT_PLAN.md with Phase 2 Action 1 findings

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Ramforth
2025-10-30 20:14:16 +01:00
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@@ -76,6 +76,8 @@ Our network analysis revealed that YouTube's web client uses a `POST` request to
* **Objective:** Explore creative, highly optimized uses of the existing REST API that might offer better sustainability, even if not truly event-driven. * **Objective:** Explore creative, highly optimized uses of the existing REST API that might offer better sustainability, even if not truly event-driven.
* **Actions:** * **Actions:**
1. **Live Chat Replay API:** Investigate the `liveChatMessages.list` endpoint when used for *replays*. Does it have different quota characteristics or offer a more complete historical view that could be adapted for near real-time (e.g., fetching a larger batch less frequently)? 1. **Live Chat Replay API:** Investigate the `liveChatMessages.list` endpoint when used for *replays*. Does it have different quota characteristics or offer a more complete historical view that could be adapted for near real-time (e.g., fetching a larger batch less frequently)?
* **Findings:** `liveChatMessages.list` costs 5 quota points per request, regardless of whether it's for live or replay chat. Frequent polling (e.g., 1 request/second) will exhaust the 10,000 daily quota in about 33 minutes. The method is not designed for efficiently replaying extensive past chat history. There's no indication of different or more lenient quota characteristics for replay usage. This approach does not offer a sustainable, quota-friendly solution for continuous monitoring.
* **Status:** **COMPLETED.** Conclusion: Not a sustainable solution for continuous monitoring.
2. **Minimal `part` Parameters:** Re-confirm the absolute minimum `part` parameters required for `liveChatMessages.list` to reduce quota cost per call. 2. **Minimal `part` Parameters:** Re-confirm the absolute minimum `part` parameters required for `liveChatMessages.list` to reduce quota cost per call.
3. **Intelligent Polling Refinement:** Explore advanced adaptive polling strategies beyond `pollingIntervalMillis`, potentially incorporating machine learning to predict chat activity and adjust polling frequency. 3. **Intelligent Polling Refinement:** Explore advanced adaptive polling strategies beyond `pollingIntervalMillis`, potentially incorporating machine learning to predict chat activity and adjust polling frequency.
@@ -98,4 +100,4 @@ Our network analysis revealed that YouTube's web client uses a `POST` request to
**Prioritization:** All research will prioritize **open-source and Linux-compatible solutions**. Compliance with YouTube's Terms of Service remains a critical factor. **Prioritization:** All research will prioritize **open-source and Linux-compatible solutions**. Compliance with YouTube's Terms of Service remains a critical factor.
**Next Steps:** The findings from this revised research will be compiled into a structured document to inform the design and implementation of a robust YouTube Live Chat monitoring solution. **Next Steps:** The findings from this revised research will be compiled into a structured document to inform the design and implementation of a robust YouTube Live Chat monitoring solution.