PlanOpticon

Create work_plan.md

noreply 2025-04-27 17:45 trunk

Commit da64008f39b369645253f435f3585230bfbe0f45ca4658db6fd0da67d598220d

Parent b9e1f41f7d9f0a6…

1 file changed +188

A work_plan.md

+188

		--- a/work_plan.md
		+++ b/work_plan.md
		@@ -0,0 +1,188 @@
	1	+PlanOpticon Development Roadmap
	2	+This document outlines the development milestones and actionable tasks for implementing the PlanOpticon video analysis system, prioritizing rapid delivery of useful outputs.
	3	+Milestone 1: Core Video Processing & Markdown Output
	4	+Goal: Process a video and produce markdown notes and mermaid diagrams
	5	+Infrastructure Setup
	6	+
	7	+ Initialize project repository structure
	8	+ Implement basic CLI with argparse
	9	+ Create configuration management system
	10	+ Set up logging framework
	11	+
	12	+Video & Audio Processing
	13	+
	14	+ Implement video frame extraction
	15	+ Create audio extraction pipeline
	16	+ Build frame sampling strategy based on visual changes
	17	+ Implement basic scene detection using cloud APIs
	18	+
	19	+Transcription & Analysis
	20	+
	21	+ Integrate with cloud speech-to-text APIs (e.g., OpenAI Whisper API, Google Speech-to-Text)
	22	+ Implement text analysis using LLM APIs (e.g., Claude API, GPT-4 API)
	23	+ Build keyword and key point extraction via API integration
	24	+ Create prompt templates for effective LLM content analysis
	25	+
	26	+Diagram Generation
	27	+
	28	+ Create flow visualization module using mermaid syntax
	29	+ Implement relationship mapping for detected topics
	30	+ Build timeline representation generator
	31	+ Leverage computer vision APIs (e.g., GPT-4 Vision, Google Cloud Vision) for diagram extraction from slides/whiteboards
	32	+
	33	+Markdown Output Generation
	34	+
	35	+ Implement structured markdown generator
	36	+ Create templating system for output
	37	+ Build mermaid diagram integration
	38	+ Develop table of contents generator
	39	+
	40	+Testing & Validation
	41	+
	42	+ Set up basic testing infrastructure
	43	+ Create sample videos for testing
	44	+ Implement quality checks for outputs
	45	+ Build simple validation metrics
	46	+
	47	+Success Criteria:
	48	+
	49	+Run script with a video input and receive markdown output with embedded mermaid diagrams
	50	+Content correctly captures main topics and relationships
	51	+Basic structure includes headings, bullet points, and at least one diagram
	52	+
	53	+Milestone 2: Advanced Content Analysis
	54	+Goal: Enhance extraction quality and content organization
	55	+Improved Speech Processing
	56	+
	57	+ Integrate specialized speaker diarization APIs
	58	+ Create transcript segmentation via LLM prompting
	59	+ Build timestamp synchronization with content
	60	+ Implement API-based vocabulary detection and handling
	61	+
	62	+Enhanced Visual Analysis
	63	+
	64	+ Optimize prompts for vision APIs to detect diagrams and charts
	65	+ Create efficient frame selection for API cost management
	66	+ Build structured prompt chains for detailed visual analysis
	67	+ Implement caching mechanism for API responses
	68	+
	69	+Content Organization
	70	+
	71	+ Implement hierarchical topic modeling
	72	+ Create concept relationship mapping
	73	+ Build content categorization
	74	+ Develop importance scoring for extracted points
	75	+
	76	+Quality Improvements
	77	+
	78	+ Implement noise filtering for audio
	79	+ Create redundancy reduction in notes
	80	+ Build context preservation mechanisms
	81	+ Develop content verification systems
	82	+
	83	+Milestone 3: Action Item & Knowledge Extraction
	84	+Goal: Identify action items and build knowledge structures
	85	+Action Item Detection
	86	+
	87	+ Implement commitment language recognition
	88	+ Create deadline and timeframe extraction
	89	+ Build responsibility attribution
	90	+ Develop priority estimation
	91	+
	92	+Knowledge Organization
	93	+
	94	+ Implement knowledge graph construction
	95	+ Create entity recognition and linking
	96	+ Build cross-reference system
	97	+ Develop temporal relationship tracking
	98	+
	99	+Enhanced Output Options
	100	+
	101	+ Implement JSON structured data output
	102	+ Create SVG diagram generation
	103	+ Build interactive HTML output option
	104	+ Develop customizable templates
	105	+
	106	+Integration Components
	107	+
	108	+ Implement unified data model
	109	+ Create serialization framework
	110	+ Build persistence layer for results
	111	+ Develop query interface for extracted knowledge
	112	+
	113	+Milestone 4: Optimization & Deployment
	114	+Goal: Enhance performance and create deployment package
	115	+Performance Optimization
	116	+
	117	+ Implement GPU acceleration for core algorithms
	118	+ Create ARM-specific optimizations
	119	+ Build memory usage optimization
	120	+ Develop parallel processing capabilities
	121	+
	122	+System Packaging
	123	+
	124	+ Implement dependency management
	125	+ Create installation scripts
	126	+ Build comprehensive documentation
	127	+ Develop container deployment option
	128	+
	129	+Advanced Features
	130	+
	131	+ Implement custom domain adaptation
	132	+ Create multi-video correlation
	133	+ Build confidence scoring for extraction
	134	+ Develop automated quality assessment
	135	+
	136	+User Experience
	137	+
	138	+ Implement progress reporting
	139	+ Create error handling and recovery
	140	+ Build output customization options
	141	+ Develop feedback collection mechanism
	142	+
	143	+Priority Matrix
	144	+FeatureImportanceTechnical ComplexityDependenciesPriorityVideo Frame ExtractionHighLowNoneP0Audio TranscriptionHighMediumAudio ExtractionP0Markdown GenerationHighLowContent AnalysisP0Mermaid Diagram CreationHighMediumContent AnalysisP0Topic ExtractionHighMediumTranscriptionP0Basic CLIHighLowNoneP0Speaker DiarizationMediumHighAudio ExtractionP2Visual Element DetectionHighHighFrame ExtractionP1Action Item DetectionMediumMediumTranscriptionP1GPU AccelerationLowMediumCore ProcessingP3ARM OptimizationMediumMediumCore ProcessingP2Installation PackageMediumLowWorking SystemP2
	145	+Implementation Approach
	146	+To achieve the first milestone efficiently:
	147	+
	148	+Leverage Existing Cloud APIs
	149	+
	150	+Integrate with cloud speech-to-text services rather than building models
	151	+Use vision APIs for image/slide/whiteboard analysis
	152	+Employ LLM APIs (OpenAI, Anthropic, etc.) for content analysis and summarization
	153	+Implement API fallbacks and retries for robustness
	154	+
	155	+
	156	+Focus on Pipeline Integration
	157	+
	158	+Build connectors between components
	159	+Ensure data flows properly through the system
	160	+Create uniform data structures for interoperability
	161	+
	162	+
	163	+Build for Extensibility
	164	+
	165	+Design plugin architecture from the beginning
	166	+Use configuration-driven approach where possible
	167	+Create clear interfaces between components
	168	+
	169	+
	170	+Iterative Refinement
	171	+
	172	+Implement basic functionality first
	173	+Add sophistication in subsequent iterations
	174	+Collect feedback after each milestone
	175	+
	176	+
	177	+
	178	+Next Steps
	179	+After completing this roadmap, potential future enhancements include:
	180	+
	181	+Real-time processing capabilities
	182	+Integration with video conferencing platforms
	183	+Collaborative annotation and editing features
	184	+Domain-specific model fine-tuning
	185	+Multi-language support
	186	+Customizable output formats
	187	+
	188	+This roadmap provides a clear path to developing PlanOpticon with a focus on delivering value quickly through a milestone-based approach, prioritizing the generation of markdown notes and mermaid diagrams as the first outcome.

	--- a/work_plan.md
	+++ b/work_plan.md
	@@ -0,0 +1,188 @@

	--- a/work_plan.md
	+++ b/work_plan.md
	@@ -0,0 +1,188 @@
1	PlanOpticon Development Roadmap
2	This document outlines the development milestones and actionable tasks for implementing the PlanOpticon video analysis system, prioritizing rapid delivery of useful outputs.
3	Milestone 1: Core Video Processing & Markdown Output
4	Goal: Process a video and produce markdown notes and mermaid diagrams
5	Infrastructure Setup
6
7	Initialize project repository structure
8	Implement basic CLI with argparse
9	Create configuration management system
10	Set up logging framework
11
12	Video & Audio Processing
13
14	Implement video frame extraction
15	Create audio extraction pipeline
16	Build frame sampling strategy based on visual changes
17	Implement basic scene detection using cloud APIs
18
19	Transcription & Analysis
20
21	Integrate with cloud speech-to-text APIs (e.g., OpenAI Whisper API, Google Speech-to-Text)
22	Implement text analysis using LLM APIs (e.g., Claude API, GPT-4 API)
23	Build keyword and key point extraction via API integration
24	Create prompt templates for effective LLM content analysis
25
26	Diagram Generation
27
28	Create flow visualization module using mermaid syntax
29	Implement relationship mapping for detected topics
30	Build timeline representation generator
31	Leverage computer vision APIs (e.g., GPT-4 Vision, Google Cloud Vision) for diagram extraction from slides/whiteboards
32
33	Markdown Output Generation
34
35	Implement structured markdown generator
36	Create templating system for output
37	Build mermaid diagram integration
38	Develop table of contents generator
39
40	Testing & Validation
41
42	Set up basic testing infrastructure
43	Create sample videos for testing
44	Implement quality checks for outputs
45	Build simple validation metrics
46
47	Success Criteria:
48
49	Run script with a video input and receive markdown output with embedded mermaid diagrams
50	Content correctly captures main topics and relationships
51	Basic structure includes headings, bullet points, and at least one diagram
52
53	Milestone 2: Advanced Content Analysis
54	Goal: Enhance extraction quality and content organization
55	Improved Speech Processing
56
57	Integrate specialized speaker diarization APIs
58	Create transcript segmentation via LLM prompting
59	Build timestamp synchronization with content
60	Implement API-based vocabulary detection and handling
61
62	Enhanced Visual Analysis
63
64	Optimize prompts for vision APIs to detect diagrams and charts
65	Create efficient frame selection for API cost management
66	Build structured prompt chains for detailed visual analysis
67	Implement caching mechanism for API responses
68
69	Content Organization
70
71	Implement hierarchical topic modeling
72	Create concept relationship mapping
73	Build content categorization
74	Develop importance scoring for extracted points
75
76	Quality Improvements
77
78	Implement noise filtering for audio
79	Create redundancy reduction in notes
80	Build context preservation mechanisms
81	Develop content verification systems
82
83	Milestone 3: Action Item & Knowledge Extraction
84	Goal: Identify action items and build knowledge structures
85	Action Item Detection
86
87	Implement commitment language recognition
88	Create deadline and timeframe extraction
89	Build responsibility attribution
90	Develop priority estimation
91
92	Knowledge Organization
93
94	Implement knowledge graph construction
95	Create entity recognition and linking
96	Build cross-reference system
97	Develop temporal relationship tracking
98
99	Enhanced Output Options
100
101	Implement JSON structured data output
102	Create SVG diagram generation
103	Build interactive HTML output option
104	Develop customizable templates
105
106	Integration Components
107
108	Implement unified data model
109	Create serialization framework
110	Build persistence layer for results
111	Develop query interface for extracted knowledge
112
113	Milestone 4: Optimization & Deployment
114	Goal: Enhance performance and create deployment package
115	Performance Optimization
116
117	Implement GPU acceleration for core algorithms
118	Create ARM-specific optimizations
119	Build memory usage optimization
120	Develop parallel processing capabilities
121
122	System Packaging
123
124	Implement dependency management
125	Create installation scripts
126	Build comprehensive documentation
127	Develop container deployment option
128
129	Advanced Features
130
131	Implement custom domain adaptation
132	Create multi-video correlation
133	Build confidence scoring for extraction
134	Develop automated quality assessment
135
136	User Experience
137
138	Implement progress reporting
139	Create error handling and recovery
140	Build output customization options
141	Develop feedback collection mechanism
142
143	Priority Matrix
144	FeatureImportanceTechnical ComplexityDependenciesPriorityVideo Frame ExtractionHighLowNoneP0Audio TranscriptionHighMediumAudio ExtractionP0Markdown GenerationHighLowContent AnalysisP0Mermaid Diagram CreationHighMediumContent AnalysisP0Topic ExtractionHighMediumTranscriptionP0Basic CLIHighLowNoneP0Speaker DiarizationMediumHighAudio ExtractionP2Visual Element DetectionHighHighFrame ExtractionP1Action Item DetectionMediumMediumTranscriptionP1GPU AccelerationLowMediumCore ProcessingP3ARM OptimizationMediumMediumCore ProcessingP2Installation PackageMediumLowWorking SystemP2
145	Implementation Approach
146	To achieve the first milestone efficiently:
147
148	Leverage Existing Cloud APIs
149
150	Integrate with cloud speech-to-text services rather than building models
151	Use vision APIs for image/slide/whiteboard analysis
152	Employ LLM APIs (OpenAI, Anthropic, etc.) for content analysis and summarization
153	Implement API fallbacks and retries for robustness
154
155
156	Focus on Pipeline Integration
157
158	Build connectors between components
159	Ensure data flows properly through the system
160	Create uniform data structures for interoperability
161
162
163	Build for Extensibility
164
165	Design plugin architecture from the beginning
166	Use configuration-driven approach where possible
167	Create clear interfaces between components
168
169
170	Iterative Refinement
171
172	Implement basic functionality first
173	Add sophistication in subsequent iterations
174	Collect feedback after each milestone
175
176
177
178	Next Steps
179	After completing this roadmap, potential future enhancements include:
180
181	Real-time processing capabilities
182	Integration with video conferencing platforms
183	Collaborative annotation and editing features
184	Domain-specific model fine-tuning
185	Multi-language support
186	Customizable output formats
187
188	This roadmap provides a clear path to developing PlanOpticon with a focus on delivering value quickly through a milestone-based approach, prioritizing the generation of markdown notes and mermaid diagrams as the first outcome.

PlanOpticon

Keyboard Shortcuts