API Docs
AiCon V2 Custom
DeprecatedPOST/api/ai/content/v2/{modelId}AiCon V2 (Fine Tuned)
Content Generation AI focused only on Business Content Generation Purpose.
AiCon’s impressive conversational abilities are rooted in years of research and development.
Like many advanced language models, such as BERT and GPT-3, AiCon is based on the Transformer neural network architecture, which was made publicly available in 2017. This architecture allows for the creation of models that can read multiple words (such as a sentence or paragraph) and understand the relationships between those words, thereby predicting what words will come next.
Built on a corpus of trillions of tokens and trained on billions of parameters, AiCon is one of the most powerful language models in existence created solely for the purpose of content creation.
What sets AiCon apart from other language models is its unique training process. Unlike traditional models, AiCon was trained on current web data upto March 2022, including actual conversations. This training allowed it to grasp the subtleties that make open-ended conversation and text distinct from other forms of language. One of these subtleties is sensibility - does the response match the conversational context and make sense?
We are dedicated to revolutionizing the way organizations approach productivity, building applications and content generation. Our latest creation AiCon - the AI Content Optimization Network - has been developed to help organizations streamline their workflow and improve their overall output.
Developers can not only translate languages, summarize long documents, and answer information-seeking questions, but they can also create comprehensive and engaging content in a fraction of the time and cost it would take without the aid of artificial intelligence.
Training Data
To begin training your data with the Search V3 AI, you must access the WorqHat AI Console. This platform provides the necessary tools and interfaces to upload and manage your datasets. Training your data is crucial as it allows the AI to learn and adapt to your specific content, enhancing its ability to understand and process user queries effectively.
Here are the steps to start training your data:
Access the WorqHat AI Console: Navigate to the console through the provided link or by logging into your WorqHat account.
Upload Your Data: Use the console's user-friendly interface to upload the datasets you want the AI to learn from. Ensure that your data is well-organized and relevant to the contexts in which the AI will operate.
Manage Your Datasets: The console allows you to view, update, or delete your previously uploaded datasets. Proper management of your datasets ensures that the AI always has the most accurate and up-to-date information.
Initiate Training: Once your data is uploaded, you can initiate the training process. The AI will analyze and learn from your data, optimizing its algorithms to better understand and interpret future queries.
Use Cases
Writing Assistance: Content Generation APIs can help writers and authors by providing suggestions, generating outlines, or even drafting entire paragraphs or articles based on given prompts. This can save time and enhance the writing process.
Marketing and Advertising: AI-powered APIs can generate engaging and persuasive marketing copy, including ad slogans, social media posts, email campaigns, and product descriptions. This enables businesses to create compelling content that resonates with their target audience.
Personalized Content: Content Generation APIs can assist in creating personalized content experiences by dynamically generating content tailored to individual users. This could include personalized product recommendations, news articles, or even customized emails.
Language Translation: APIs can be used to automate language translation tasks, converting text from one language to another. This is particularly useful for websites, apps, or platforms that need to support multiple languages, enabling effective communication with a global audience.
Chatbots and Virtual Assistants: AI-powered chatbots and virtual assistants leverage Content Generation APIs to provide human-like responses to user queries. These APIs enable the generation of natural language responses, enhancing the user experience and improving customer service.
Content Summarization: APIs can automatically generate concise summaries of lengthy documents, articles, or reports. This is valuable for news aggregators, research platforms, or any application where users need quick access to the main points of a large body of text.
Data Visualization: APIs can assist in generating visual representations of data, such as charts, graphs, or infographics, based on input datasets. This helps businesses and individuals present complex information in a more digestible and visually appealing manner.
Virtual Storytelling: Content Generation APIs can be used in video game development or virtual reality experiences to dynamically generate storylines, dialogues, and narratives. This allows for immersive and interactive storytelling experiences that adapt to user actions and choices.
Content Curation: APIs can automate the process of collecting and curating content from various sources, such as news articles, blog posts, or social media feeds. This helps content platforms deliver relevant and up-to-date information to their users.
E-commerce Product Descriptions: AI-powered APIs can generate compelling and accurate product descriptions by analyzing product features, specifications, and customer reviews. This assists e-commerce platforms in creating engaging content that drives conversions.
Request
The Custom Trained Model ID. You can get this Model ID from your Model Training Dashboard.
The question that you want to ask the model
enable or disable streaming content
This is a key value pair of the question and the related answer
You can add in any other contextual information that you want the model to maintain while answering
JSON or Text
{
"question": "string",
"preserve_history": true,
"randomness": 0,
"stream_data": true,
"conversation_history": [
{
"What is the capital of India?": "string",
"What is the capital of USA?": "string"
}
],
"training_data": "string",
"response_type": "text"
}Request samples
Responses
{
"content": "string",
"processingTime": 0,
"processingId": "string",
"processingCount": 0
}