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import { HarmBlockThreshold, HarmCategory } from '@google-cloud/vertexai'; | ||
|
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export const SAFETY_SETTINGS = [ | ||
{ | ||
category: HarmCategory.HARM_CATEGORY_HATE_SPEECH, | ||
threshold: HarmBlockThreshold.BLOCK_NONE, | ||
}, | ||
{ | ||
category: HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT, | ||
threshold: HarmBlockThreshold.BLOCK_NONE, | ||
}, | ||
{ | ||
category: HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT, | ||
threshold: HarmBlockThreshold.BLOCK_NONE, | ||
}, | ||
{ | ||
category: HarmCategory.HARM_CATEGORY_HARASSMENT, | ||
threshold: HarmBlockThreshold.BLOCK_NONE, | ||
}, | ||
]; |
76 changes: 76 additions & 0 deletions
76
src/lib/parser/experimental/VertexAPI/convertImageToHTML.ts
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import { VertexAI } from '@google-cloud/vertexai'; | ||
import { SAFETY_SETTINGS } from './constants'; | ||
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export const convertImageToHTML = async ( | ||
imageData: string | ||
): Promise<string> => { | ||
const vertexAI = new VertexAI({ | ||
project: 'notion-to-anki', | ||
location: 'europe-west3', | ||
}); | ||
const model = 'gemini-1.5-flash-002'; | ||
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const generativeModel = vertexAI.preview.getGenerativeModel({ | ||
model: model, | ||
generationConfig: { | ||
maxOutputTokens: 8192, | ||
temperature: 1, | ||
topP: 0.95, | ||
}, | ||
safetySettings: SAFETY_SETTINGS, | ||
}); | ||
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const text1 = { | ||
text: `Convert the text in this image to the following format: | ||
<ul class=\"toggle\"> | ||
<li> | ||
<details> | ||
<summary> | ||
n) question | ||
</summary> | ||
<p>A) ..., </p> | ||
<p>B)... </p> | ||
etc. | ||
<p>and finally Answer: D</p> | ||
</details> | ||
</li> | ||
</ul> | ||
— | ||
- Extra rules: n=is the number for the question, question=the question text | ||
- Add newline between the options | ||
- If you are not able to detect the pattern above, try converting this into a question and answer format`, | ||
}; | ||
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const image1 = { | ||
inlineData: { | ||
mimeType: 'image/png', | ||
data: imageData, | ||
}, | ||
}; | ||
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const req = { | ||
contents: [{ role: 'user', parts: [text1, image1] }], | ||
}; | ||
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let htmlContent = ''; | ||
try { | ||
const streamingResp = await generativeModel.generateContentStream(req); | ||
for await (const item of streamingResp.stream) { | ||
if ( | ||
item.candidates && | ||
item.candidates[0].content && | ||
item.candidates[0].content.parts | ||
) { | ||
htmlContent += item.candidates[0].content.parts | ||
.map((part) => part.text) | ||
.join(''); | ||
} | ||
} | ||
} catch (error) { | ||
console.error('Error generating content stream:', error); | ||
} | ||
|
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return htmlContent; | ||
}; |
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