rev ai process
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appdoc/doc_concept_callAiContent_flow.md
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appdoc/doc_concept_callAiContent_flow.md
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# callAiContent Process Flow
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## Function: `callAiContent(prompt, options, contentParts, outputFormat, title, parentOperationId)`
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### High-Level Flow
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```
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START callAiContent
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│
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├─> Initialize operation tracking (aiOperationId)
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├─> Determine operationType (if not set)
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│
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├─> [BRANCH 1] IMAGE_GENERATE → Handle image generation → RETURN
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│
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├─> [BRANCH 2] WEB_SEARCH/WEB_CRAWL → Handle web operations → RETURN
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│
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└─> [BRANCH 3] Unified Document Generation Path (outputFormat always set, defaults to "txt")
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│
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├─> IF contentParts provided:
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│ │
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│ ├─> SEPARATE parts:
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│ │ ├─> imageParts = [typeGroup=="image" OR mimeType starts "image/"]
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│ │ ├─> textParts = [typeGroup in ["text","table","structure"] OR mimeType starts "text/"]
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│ │ └─> otherParts = [rest] → SKIP
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│ │
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│ ├─> [PART 2.1] PROCESS IMAGES:
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│ │ FOR each imagePart:
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│ │ ├─> Create AiCallRequest with USER PROMPT + IMAGE_ANALYSE
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│ │ ├─> Call aiObjects.call() → vision model extracts data
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│ │ └─> Replace imagePart with text ContentPart (extracted data)
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│ │
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│ ├─> [PART 2.2] ADD TEXT PARTS as-is
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│ │
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│ └─> Convert processedParts to text string → content_for_generation
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│
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├─> Build generation prompt (includes content_for_generation)
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├─> Call _callAiWithLooping for JSON generation
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├─> Parse JSON and render to outputFormat (txt, docx, xlsx, pdf, etc.)
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└─> RETURN AiResponse with rendered document
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```
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### Detailed Flow: Unified Document Generation Path (lines 1055-1257)
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```
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IF outputFormat specified:
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│
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├─> IF contentParts provided:
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│ │
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│ ├─> SEPARATE parts (same logic as text path):
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│ │ ├─> imageParts, textParts, otherParts
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│ │
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│ ├─> [PART 2.1] PROCESS IMAGES:
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│ │ └─> Same as text path: vision models with USER PROMPT
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│ │
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│ ├─> [PART 2.2] ADD TEXT PARTS as-is
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│ │
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│ └─> Convert processedParts to text:
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│ └─> content_for_generation = "\n\n".join([...])
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│
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├─> Build generation prompt:
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│ └─> generation_prompt = buildGenerationPrompt(outputFormat, prompt, title, content_for_generation, None)
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│
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├─> Call _callAiWithLooping(generation_prompt, ...) for JSON generation
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├─> Parse generated JSON
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├─> Render to outputFormat (xlsx, docx, pdf, etc.)
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└─> RETURN AiResponse with rendered document
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```
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### Key Points
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1. **Unified Path**: All formats (txt, docx, xlsx, pdf, etc.) use the same document generation path. If `outputFormat` is not specified, it defaults to "txt".
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2. **User Prompt is Critical**: The prompt from `ai.process` (user's intention) is used to extract data from images, not a generic "extract all text" prompt.
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3. **Vision Models**: Images are processed with `IMAGE_ANALYSE` operation type, which routes to vision-capable models.
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4. **Text Extraction**: After vision processing, images are replaced with text ContentParts containing the extracted data.
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5. **JSON Structure**: All formats generate JSON structure first, then render to the target format (txt rendering extracts text from JSON structure).
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6. **Binary Skipping**: Binary and other non-text parts are excluded from processing.
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