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Configure “Public Cloud AI Action”

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The Ask AI action with the Public Cloud AI source gives you access to leading AI models from external providers such as OpenAI, Mistral, Anthropic, and many more.

Leading market models

OpenAI, Mistral, Anthropic, and more. Access to the latest and most capable models available.

Two billing modes

TimeTonic AI credits or personal API key (BYOK). Switch at any time without losing your configuration.

Maximum flexibility

Choose the right model for each task based on complexity, cost, and required capabilities.

1. TimeTonic credits or personal API key

Before selecting a model, choose your billing mode using the Use personal API key toggle:

⚪ TimeTonic credits

Consumption is deducted from your monthly quota. Monitor your usage from the Administration → Plan and Billing notebook. When 100% of the quota is reached, AI actions are suspended until the monthly renewal.

🔵 Personal API key (BYOK)

No TimeTonic credits consumed. Billing is handled directly by the provider. Limits depend on your provider account.

💡 You can switch between the two modes at any time — your API key remains saved even when the toggle is disabled.

Learn more → Use your own API key (BYOK)

2. Model selection

Choose the model suited to your task from those available. Each model displays its maximum context window and credit cost.

Model Total
context Input
/M Output
/M Ideal for
Gemini 2.0 Flash Lite
Efficient
1M 75K 300K High-volume tasks, simple repetitive operations, bulk record processing
GPT-OSS 20B
Efficient
131K 40K 150K Simple repetitive tasks, classification, short reformulation
DeepSeek V3.1
Efficient
163K 32.7K 750K Data extraction, reasoning tasks, good multilingual support
Mistral Small
Standard
131K 350K 560K Native French support, public sector use cases, long French-language documents
GPT-4o Mini
Standard 📎 Vision 📄 OCR
128K 150K 600K Versatile, reliable, image analysis and text extraction from document photos
GPT-4.1
Premium 📎 Vision 📄 OCR
1.048M 2M 8M Complex documents, lengthy legal deeds, legal or financial analysis from photos
Claude 3.5 Sonnet
Premium 📎 Vision 📄 OCR
200K 3M 15M Nuanced analysis, long-form detailed writing, complex instructions from photos
Mistral Large
Premium 📎 Vision 📄 OCR
131K 2M 6M Advanced French-language tasks, contracts, reports, image analysis in French

📎 Vision: the model can analyze an attached image and understand its content
📄 OCR: the model can extract structured text from document photos
Total context = combined input + output, shown in parentheses in the model selector
K = thousands of tokens · M = millions of tokens · Input /M and Output /M = credits per million tokens

3. Role description

This field defines the expected behavior and context for the model. A precise role significantly improves the quality and consistency of responses.

"You are an assistant specialized in contract analysis."

"You extract only the requested information in JSON format."

4. Prompt

The prompt is the precise instruction sent to the model. Use the $ symbol to dynamically inject values from your fields.

💡 The more precise and contextualized the prompt, the more relevant the response will be.

For PDF or image analysis, a specific prompt is required → See OCR PDF & images prompts

5. Attachments

Select a field containing image files to allow the AI to analyze their content. Useful for:

📄 Document analysis
🔍 Information extraction from files
🖼️ Image processing

⚠️ Only models with the 📎 Attachments badge support this option. Verify compatibility before using in production.

For PDF file processing → See the OCR PDF & images procedure

6. Token limit

The Maximum token count field caps the length of the response generated by the model.

Token limitEffect on responseUse caseRecommended value
Low
Short, concise response: the AI gets straight to the pointClassification, single-value extraction, category, yes/no50 to 200 tokens
Medium
Structured response in a few linesSuggested email reply, short reformulation100 to 400 tokens
High
Long, detailed response: summary, report, full analysisDocument summary, meeting notes, content generation500 to 1,000 tokens
Adjust this parameter to match the nature of the task: limiting tokens helps control your TimeTonic credit consumption. A 100-token response costs ten times less than a 1,000-token response.

The token count directly impacts your credit consumption. To anticipate the impact before configuring your action → Estimate your AI credit consumption

7. Response format

The response format determines how the AI-generated response will be structured and stored in your notebook. Two options are available:

Text

The response is stored as-is in a text field. Ideal for summaries, comments, or free-form responses.

Structured JSON

Each JSON property is stored in a dedicated field. Recommended for structured extractions and automated processing.

💡 The Structured JSON format requires a specific prompt in the Prompt field to instruct the model on which data to extract and in what structure, especially for PDF or image analysis. Each JSON key then maps to a destination field in your record.

See the OCR PDF & images configuration →

8. Response field

This field determines where the AI response will be stored in your notebook. Its behavior depends directly on the format selected in the previous step.

If you selected the Text format

The Response field appears. Select the text field in your notebook where the generated response will be stored. Only one destination field is required.

If you selected the Structured JSON format

The Response field disappears and is replaced by a mapping table. For each JSON property you requested in your prompt, you must:

  1. Enter the exact name of the JSON property as you defined it in your prompt (e.g., name, date_of_birth, amount)
  2. Select the corresponding destination field in your notebook where the extracted value will be stored

Repeat for each property to extract. You can add as many rows as needed using the + button.

Example: You are extracting data from an ID card and your prompt requests a JSON with the keys last_name, first_name, and date_of_birth. You create three rows and map each key to the corresponding field in your notebook.

9. Consumption

Learn more

AI credits by license plan

Read the article →

Learn more

Consumption in the logs

Read the article →

Learn more

Use your own API key

Read the article →

Learn more

Credits exhausted: what to do?

Read the article →

Best practices

  • Choose the model suited to the complexity of the task.
  • Limit the token count when a short response is sufficient.
  • Define a clear role and a precise instruction.
  • Regularly check consumption in the logs.