BaseAI

Overview

BaseAI - Intelligent text generation, analysis, and processing capabilities. Transform your applications with content creation, sentiment analysis, categorization, entity extraction, translation, and vectorization.

Operations

An operation is an AI-powered action performed on text. All operations require the op property to specify which operation to perform.

Operation	Description
`baseai.write`	Generate new content from prompts
`baseai.summarize`	Create concise summaries
`baseai.translate`	Translate between languages
`baseai.categorize`	Classify content into categories
`baseai.extract_entities`	Extract entities and information
`baseai.analyze_sentiment`	Analyze emotional tone
`baseai.vectorize_content`	Convert document to vector embeddings

Create Content

baseai.write

Generate new content based on prompts with customizable style and length.

Basic generation:

json

{
  "op": "baseai.write",
  "prompt": "Write a blog post about cloud computing benefits for small businesses",
  "content_length": 800,
  "content_style": "professional"
}

With custom instructions:

json

{
  "op": "baseai.write",
  "prompt": "Create social media posts for a fitness app launch",
  "content_length": 500,
  "content_style": "engaging",
  "custom_instructions": "Create 5 posts for Instagram and Twitter. Include hashtags and call-to-action."
}

Parameters:

prompt (required) - Text or instruction for generation
content_length (optional) - Target word count
content_style (optional) - Writing style: formal, casual, professional, technical, narrative
custom_instructions (optional) - Specific requirements

Response:

json

{
  "data": "# Cloud Computing: A Game-Changer for Small Businesses\n\nIn today's competitive landscape, small businesses need every advantage...",
  "meta": {
    "content_length": 847,
    "generation_time_ms": 2340,
    "style_applied": "professional"
  }
}

Summarize Content

baseai.summarize

Create concise summaries of long-form content.

json

{
  "op": "baseai.summarize",
  "content": "Artificial intelligence has been transforming industries across the globe at an unprecedented pace. From healthcare to finance, manufacturing to retail, AI technologies are revolutionizing how businesses operate...",
  "content_length": 150,
  "content_style": "executive"
}

Parameters:

content (required) - Text to summarize
content_length (optional) - Target summary length
content_style (optional) - Summary style: executive, bullet-points, academic, news-brief
custom_instructions (optional) - Focus areas

Response:

json

{
  "data": "AI is revolutionizing industries globally through real-time data processing. Key applications include personalized medicine and fraud detection, demonstrating transformative impact across healthcare and finance.",
  "meta": {
    "original_length": 2847,
    "summary_length": 147,
    "compression_ratio": 0.052
  }
}

Categorize Content

baseai.categorize

Classify content into categories with confidence scoring.

json

{
  "op": "baseai.categorize",
  "content": "I'm disappointed with my purchase. The product arrived damaged and customer service was unhelpful. I'm considering switching to a competitor.",
  "classification_categories": "positive, negative, neutral, urgent, complaint, inquiry",
  "confidence_level": "high"
}

Parameters:

content (required) - Text to classify
classification_categories (optional) - Comma-separated list of categories
confidence_level (optional) - Minimum confidence: low, medium, high

Response:

json

{
  "data": {
      "primary_classification": "complaint",
      "secondary_classifications": ["negative", "urgent"],
      "confidence_scores": {
        "complaint": 0.92,
        "negative": 0.89,
        "urgent": 0.76,
        "neutral": 0.08,
        "positive": 0.03
      },
      "reasoning": "Content expresses dissatisfaction with product and service, indicating urgent complaint."
  },
  "meta": {
    "classification_method": "multi-label",
    "confidence_threshold": 0.7
  }
}

Common use cases:

Customer support ticket routing
Content moderation
Document organization
Email filtering

Analyze Sentiment

baseai.analyze_sentiment

Analyze emotional tone and sentiment of text.

json

{
  "op": "baseai.analyze_sentiment",
  "content": "The new product launch exceeded expectations! While there were supply chain challenges, we overcame them. Customer feedback has been overwhelmingly positive.",
  "analysis_depth": "detailed",
  "specific_aspects": "product quality, team performance, customer satisfaction"
}

Parameters:

content (required) - Text to analyze
analysis_depth (optional) - Detail level: brief, standard, detailed
specific_aspects (optional) - Comma-separated aspects to focus on

Response:

json

{
  "data": {
      "overall_sentiment": "positive",
      "sentiment_score": 0.78,
      "emotional_indicators": {
        "excitement": 0.85,
        "satisfaction": 0.82,
        "concern": 0.23,
        "confidence": 0.76
      },
      "aspect_sentiments": {
        "product quality": {
          "sentiment": "very positive",
          "score": 0.91
        },
        "team performance": {
          "sentiment": "positive",
          "score": 0.87
        },
        "customer satisfaction": {
          "sentiment": "positive",
          "score": 0.83
        }
      },
      "key_phrases": ["exceeded expectations", "overwhelmingly positive"],
      "tone_analysis": "optimistic and professional with acknowledgment of improvements"
  },
  "meta": {
    "analysis_confidence": 0.94
  }
}

Common use cases:

Product review analysis
Social media monitoring
Employee feedback analysis
Customer support quality

Extract Entities

baseai.extract_entities

Extract specific entities and structured information from text.

json

{
  "op": "baseai.extract_entities",
  "content": "John Smith, CEO of TechCorp Inc., announced the company will open a new headquarters in San Francisco. The $50 million facility will create 500 jobs by December 2024. Contact: john.smith@techcorp.com, (555) 123-4567.",
  "entity_types": "people, organizations, locations, dates, contact_info, financial_amounts"
}

Parameters:

content (required) - Text to analyze
entity_types (optional) - Comma-separated entity types to extract

Response:

json

{
  "data": {
      "people": [
        {
          "name": "John Smith",
          "title": "CEO",
          "organization": "TechCorp Inc."
        }
      ],
      "organizations": [
        {
          "name": "TechCorp Inc.",
          "type": "company"
        }
      ],
      "locations": [
        {
          "city": "San Francisco",
          "type": "headquarters_location"
        }
      ],
      "dates": [
        {
          "date": "December 2024",
          "context": "job creation deadline"
        }
      ],
      "contact_info": [
        {
          "email": "john.smith@techcorp.com",
          "phone": "(555) 123-4567"
        }
      ],
      "financial_amounts": [
        {
          "amount": "$50 million",
          "context": "facility cost"
        }
      ]
  },
  "meta": {
    "entities_found": 6,
    "extraction_confidence": 0.96
  }
}

Common entity types:

people - Names, titles, roles
organizations - Companies, institutions
locations - Cities, countries, addresses
dates - Dates, times, deadlines
contact_info - Emails, phones
financial_amounts - Money, prices
skills - Technical skills, expertise
events - Meetings, conferences

Common use cases:

Contract analysis
Resume parsing
News analysis
Invoice processing

Translate Content

baseai.translate

Translate text between languages with style preservation.

json

{
  "op": "baseai.translate",
  "content": "We are excited to announce the launch of our new product line. For more information, visit our website.",
  "anguage": "Spanish",
  "translation_style": "business-formal"
}

Parameters:

content (required) - Text to translate
language (required) - Target language
translation_style (optional) - Style: formal, casual, technical, marketing

Response:

json

{
  "data":  "Nos complace anunciar el lanzamiento de nuestra nueva línea de productos. Para obtener más información, visite nuestro sitio web.",
  "meta": {
    "language": "Spanish",
    "translation_confidence": 0.98,
    "style_applied": "business-formal"
  }
}

Supported languages: English, Spanish, French, German, Japanese, Chinese, Portuguese, Italian, Russian, Korean, Arabic, Dutch, Polish

Vectorize Content

baseai.vectorize_content

Convert text to vector embeddings for semantic search and similarity analysis.

json

{
  "op": "baseai.vectorize_content",
  "content": "Machine learning algorithms identify patterns in data and make predictions."
}

Parameters:

content (required) - Text to convert to vectors

Response:

json

{
  "data": {
      "vector": [0.0234, -0.1567, 0.2891, 0.0945, -0.3421, ...],
      "dimensions": 1536,
      "model_version": "text-embedding-v2.0"
  },
  "meta": {
    "content_length": 119,
    "vector_norm": 1.0
  }
}

Common use cases:

Semantic search
Content recommendation
Similarity detection
Document clustering

Complete Example

javascript

// 1. Generate content
const createResponse = await fetch('https://cloud.singlebaseapis.com/api/<ENDPOINT_KEY>', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'X-API-KEY': 'your_api_key',
    'Authorization': 'Bearer your_jwt_token'
  },
  body: JSON.stringify({
    op: 'baseai.write',
    prompt: 'Write a product description for wireless headphones',
    content_length: 200,
    content_style: 'marketing'
  })
});

const content = await createResponse.json();
console.log('Generated:', content.data);

// 2. Analyze sentiment
const sentimentResponse = await fetch('https://cloud.singlebaseapis.com/api/<ENDPOINT_KEY>', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'X-API-KEY': 'your_api_key',
    'Authorization': 'Bearer your_jwt_token'
  },
  body: JSON.stringify({
    op: 'baseai.analyze_sentiment',
    content: 'The product quality is excellent but delivery was slow.',
    analysis_depth: 'detailed',
    specific_aspects: 'product quality, delivery'
  })
});

const sentiment = await sentimentResponse.json();
console.log('Overall:', sentiment.data.output.overall_sentiment);
console.log('Aspects:', sentiment.data.output.aspect_sentiments);

// 3. Categorize content
const categorizeResponse = await fetch('https://cloud.singlebaseapis.com/api/<ENDPOINT_KEY>', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'X-API-KEY': 'your_api_key',
    'Authorization': 'Bearer your_jwt_token'
  },
  body: JSON.stringify({
    op: 'baseai.categorize',
    content: 'How do I reset my password?',
    classification_categories: 'technical, billing, account, general'
  })
});

const category = await categorizeResponse.json();
console.log('Category:', category.data.output.primary_classification);

// 4. Extract entities
const extractResponse = await fetch('https://cloud.singlebaseapis.com/api/<ENDPOINT_KEY>', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'X-API-KEY': 'your_api_key',
    'Authorization': 'Bearer your_jwt_token'
  },
  body: JSON.stringify({
    op: 'baseai.extract_entities',
    content: 'Contact Jane Doe at jane@example.com or call (555) 123-4567.',
    entity_types: 'people, contact_info'
  })
});

const entities = await extractResponse.json();
console.log('People:', entities.data.output.people);
console.log('Contacts:', entities.data.output.contact_info);

Common Workflows

Customer Support Automation

javascript

// Categorize and route support ticket
const ticket = "I can't login to my account";

const category = await fetch('https://cloud.singlebaseapis.com/api/<ENDPOINT_KEY>', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'X-API-KEY': 'your_api_key',
    'Authorization': 'Bearer your_jwt_token'
  },
  body: JSON.stringify({
    op: 'baseai.categorize',
    content: ticket,
    classification_categories: 'technical, billing, account, general'
  })
});

// Route based on category
const result = await category.json();
routeToTeam(result.data.primary_classification);

Content Analysis Pipeline

javascript

async function analyzeContent(text) {
  // Summarize
  const summary = await summarize(text);
  
  // Analyze sentiment
  const sentiment = await analyzeSentiment(text);
  
  // Categorize
  const category = await categorize(text);
  
  return {
    summary: summary.data,
    sentiment: sentiment.data.overall_sentiment,
    category: category.data.primary_classification
  };
}

Error Handling

json

{
  "error": {
    "code": "ERROR_CODE",
    "message": "Human-readable error description"
  }
}

Common error codes:

CONTENT_TOO_LONG - Content exceeds max length (50,000 chars)
CONTENT_EMPTY - No content provided
INVALID_LANGUAGE - Unsupported language
PROCESSING_FAILED - AI processing error (retry recommended)
QUOTA_EXCEEDED - API usage limit reached
INVALID_OPTIONS - Malformed parameters

BaseAI ​

Overview ​

Operations ​

Create Content ​

baseai.write ​

Summarize Content ​

baseai.summarize ​

Categorize Content ​

baseai.categorize ​

Analyze Sentiment ​

baseai.analyze_sentiment ​

Extract Entities ​

baseai.extract_entities ​

Translate Content ​

baseai.translate ​

Vectorize Content ​

baseai.vectorize_content ​

Complete Example ​

Common Workflows ​

Customer Support Automation ​

Content Analysis Pipeline ​

Error Handling ​

BaseAI

Overview

Operations

Create Content

baseai.write

Summarize Content

baseai.summarize

Categorize Content

baseai.categorize

Analyze Sentiment

baseai.analyze_sentiment

Extract Entities

baseai.extract_entities

Translate Content

baseai.translate

Vectorize Content

baseai.vectorize_content

Complete Example

Common Workflows

Customer Support Automation

Content Analysis Pipeline

Error Handling