Input
POST https://gateway.appypie.com/llama3/v1/getData HTTP/1.1

Content-Type: application/json
Cache-Control: no-cache

{
    "prompt": "Tell me about llama3"
}

import urllib.request, json

try:
    url = "https://gateway.appypie.com/llama3/v1/getData"

    hdr ={
    # Request headers
    'Content-Type': 'application/json',
    'Cache-Control': 'no-cache',
    }

    # Request body
    data =  
    data = json.dumps(data)
    req = urllib.request.Request(url, headers=hdr, data = bytes(data.encode("utf-8")))

    req.get_method = lambda: 'POST'
    response = urllib.request.urlopen(req)
    print(response.getcode())
    print(response.read())
    except Exception as e:
    print(e)

// Request body
const body = {
    "prompt": "Tell me about llama3"
};

fetch('https://gateway.appypie.com/llama3/v1/getData', {
        method: 'POST',
        body: JSON.stringify(body),
        // Request headers
        headers: {
            'Content-Type': 'application/json',
            'Cache-Control': 'no-cache',}
    })
    .then(response => {
        console.log(response.status);
        console.log(response.text());
    })
    .catch(err => console.error(err));
curl -v -X POST "https://gateway.appypie.com/llama3/v1/getData" -H "Content-Type: application/json" -H "Cache-Control: no-cache" --data-raw "{
    \"prompt\": \"Tell me about llama3\"
}"
import java.io.BufferedReader;
import java.io.InputStreamReader;
import java.net.HttpURLConnection;
import java.net.URL;
import java.net.URLEncoder;
import java.util.HashMap;
import java.util.Map;
import java.io.UnsupportedEncodingException;
import java.io.DataInputStream;
import java.io.InputStream;
import java.io.FileInputStream;

public class HelloWorld {

  public static void main(String[] args) {
    try {
        String urlString = "https://gateway.appypie.com/llama3/v1/getData";
        URL url = new URL(urlString);
        HttpURLConnection connection = (HttpURLConnection) url.openConnection();

        //Request headers
    connection.setRequestProperty("Content-Type", "application/json");
    
    connection.setRequestProperty("Cache-Control", "no-cache");
    
        connection.setRequestMethod("POST");

        // Request body
        connection.setDoOutput(true);
        connection
            .getOutputStream()
            .write(
             "{ \"prompt\": \"Tell me about llama3\" }".getBytes()
             );
    
        int status = connection.getResponseCode();
        System.out.println(status);

        BufferedReader in = new BufferedReader(
            new InputStreamReader(connection.getInputStream())
        );
        String inputLine;
        StringBuffer content = new StringBuffer();
        while ((inputLine = in.readLine()) != null) {
            content.append(inputLine);
        }
        in.close();
        System.out.println(content);

        connection.disconnect();
    } catch (Exception ex) {
      System.out.print("exception:" + ex.getMessage());
    }
  }
}

$url = "https://gateway.appypie.com/llama3/v1/getData";
$curl = curl_init($url);

curl_setopt($curl, CURLOPT_CUSTOMREQUEST, "POST");
curl_setopt($curl, CURLOPT_URL, $url);
curl_setopt($curl, CURLOPT_RETURNTRANSFER, true);

# Request headers
$headers = array(
    'Content-Type: application/json',
    'Cache-Control: no-cache',);
curl_setopt($curl, CURLOPT_HTTPHEADER, $headers);

# Request body
$request_body = '{
    "prompt": "Tell me about llama3"
}';
curl_setopt($curl, CURLOPT_POSTFIELDS, $request_body);

$resp = curl_exec($curl);
curl_close($curl);
var_dump($resp);



Output
Meta Llama 3 API
  • Meta Llama 3 API Documentation

    Overview

    Meta Llama 3 is a groundbreaking large language model (LLM) developed by Meta AI, representing a significant leap forward in natural language processing and understanding capabilities. This state-of-the-art AI model excels in various tasks, including text generation, sentiment analysis, code generation, reasoning, and following complex instructions. The key features and improvements of Meta Llama 3 include an enhanced tokenizer for efficient language encoding, and a seven times larger training dataset compared to its predecessor (Llama 2), including four times more code data. Additionally, advancements in pretraining and instruction fine-tuning processes and elevated reasoning and code generation abilities have been implemented. These advancements contribute to the model's versatility, robustness, and superior performance across various domains.

    Meta Llama 3 has two variants: Llama 3 8B and Llama-3-70B. The Llama-3-70B model represents a new state-of-the-art for LLMs at this scale, outperforming previous models in terms of performance and capabilities. Meta is committed to fostering an open-source AI ecosystem and promoting the responsible use of LLMs, making Meta Llama 3 APIs accessible under a license agreement, and implementing robust trust and safety tools. The Meta Llama 3 APIs offer developers and businesses unparalleled capabilities in various natural language processing tasks. With Meta Llama 3 APIs, users can harness the power of advanced AI models to enhance their applications and workflows. Whether powering chatbots, analyzing textual data, or generating creative content, Meta Llama 3 APIs empower users to unlock new possibilities and drive innovation in communication and data analysis.

    Meta AI has ensured that Meta Llama 3 APIs set new industry benchmarks by incorporating feedback and continuously improving the model's performance. The Meta Llama 3 APIs leverage the robust performance of Meta Llama 3, providing users with superior results in their AI-driven projects. Meta AI's commitment to an open-source approach is evident in the meta/llama-3-8b and llama-3-8b-instruct variants, ensuring the Meta Llama 3 APIs are accessible to the broader community. By setting new industry benchmarks and incorporating feedback, Meta AI continues to advance the capabilities of LLMs.

    Meta Llama 3 APIs offer unparalleled performance and capabilities, making them a cornerstone in the evolution of LLMs. The advancements over Llama 2, superior handling of multilingual tasks, and open access under robust safety tools position Meta Llama 3 APIs as leading tools in the AI landscape, driving innovation and responsible use in the field. Meta AI's Meta Llama 3 models, including Llama 3 8B and Llama-3-70B, represent significant advancements in AI technology, outperforming previous models and setting new standards in the industry.

  • API Parameters

    The API POST

    https://gateway.appypie.com/llama3/v1/getData takes the following parameters:

    prompt

    string, required

    negative_prompt

    string, optional

     

    Integration and Implementation

    To utilize the Meta Llama 3 API, developers must send POST requests to the designated endpoint along with the correct headers and request body. The request body should include text inputs, task parameters, and additional settings.

     
    Base URL

    https://gateway.appypie.com/llama3/v1/getData

    Endpoints
    POST /Get Data

    This endpoint generates text based on the provided prompts.

    Request
    • URL: https://gateway.appypie.com/llama3/v1/getData
    • Method: POST
    • Headers:
      • Content-Type: application/json
      • Cache-Control: no-cache
      • Ocp-Apim-Subscription-Key: {subscription_key}
    • Body:

      JSON

      {
        "prompt": "Tell me about Llama3"
      }
      
  • POST /System Prompt Get Data

    This endpoint generates text based on the provided prompts.

    Request
    • URL: https://gateway.appypie.com/llama3/v1/systemPromptGetData
    • Method: POST
    • Headers:
      • Content-Type: application/json
      • Cache-Control: no-cache
      • Ocp-Apim-Subscription-Key: {subscription_key}
    • Body:

      JSON

      {
          "prompt": "Tell me about Llama3",
          "system prompt": "You are supposed to be a LLM expert"
      }
      
    Responses
    • HTTP Status Codes:
      • 200 OK: The request was successful, and the generated texts are included in the response body.
      • 400 Bad Request: The request must be corrected or include some arguments.
      • 401 Unauthorized: The API key provided in the header is invalid.
      • 500 Internal Server Error: An error occurred on the server while processing the request.
    • Sample Response:

      JSON

      {
        "status": 200,
        "content-type": "application/json"
      }
      
    Error Handling

    The Meta Llama 3 API is equipped with robust error-handling mechanisms to facilitate seamless operation. Typical status codes encountered include:

    • Error Field Contract:
      • code: An integer that indicates the HTTP status code (e.g., 400, 401, 500).
      • message: A clear and concise description of what the error is about.
      • traceId A unique identifier that can be used to trace the request in case of issues.
    Definitions
    • AI Model: Refers to the underlying machine learning model used to interpret the text prompts and generate corresponding texts.
    • Changelog: Document detailing any updates, bug fixes, or improvements made to the API in each version.
     

    Use Cases of Meta Llama 3 API

    • AI Assistants and Chatbots: Meta's Llama 3 can be used to build advanced AI assistants and chatbots that engage in natural conversations, answer questions, and assist with various tasks. By leveraging the power of the 70B parameter instruct-tuned model, developers can create chat models that are highly responsive and contextually aware. These AI tools can be integrated into customer support systems, personal assistant applications, and more. To access Llama models for these purposes, users need to utilize the appropriate API calls and ensure they have a valid API key. The artificial intelligence capabilities of these models make them ideal for enhancing customer engagement and operational efficiency.
    • Content Generation: Llama 3 can generate high-quality content such as articles, stories, scripts, and marketing copy. The base models are excellent for continuing text sequences, while the instruct models can follow specific prompts to create targeted content. This AI tool is particularly useful for marketers and content creators who need to produce a large volume of engaging material quickly. By making the appropriate API calls, users can integrate these content-generation capabilities into their applications. The model page for Llama models provides detailed documentation on how to utilize these features effectively.
    • Code Generation and Explanation: The models have strong coding abilities and can generate, explain, and debug code in various languages. They can assist with tasks like refactoring, commenting, and providing code snippets, making them valuable tools for developers. With larger models like Meta Llama 3, users can fine-tune Llama to specialize in different programming languages and frameworks. Using compatible endpoints and a valid API key, developers can seamlessly integrate these capabilities into their development environments, enhancing productivity and code quality.
    • Question Answering: Meta Llama 3 excels at answering questions on a wide range of topics by drawing upon its broad knowledge base. It can provide concise, informative answers, making it an invaluable resource for customer service, educational tools, and research assistants. By leveraging the open LLM and available LLM models, users can customize their question-answering systems to better suit their specific needs. The process involves making the necessary API calls and managing access through the API key.
    • Summarization: The Meta Llama 3 API can summarize long documents, articles, or conversations into key points and insights. This is useful for quickly digesting information and making it more accessible. Researchers, analysts, and business professionals can utilize these summarization capabilities to improve their workflow and efficiency. The artificial intelligence behind these models ensures high accuracy and relevance. Access to these summarization features can be obtained through the model page and appropriate API calls.
    • Ideation and Brainstorming: Meta Llama 3 API can help spark ideas, make connections, and provide creative inspiration for writing, projects, and problem-solving. This AI tool is especially beneficial in creative industries where fresh and innovative ideas are crucial. By integrating Llama models into brainstorming sessions, users can leverage the power of artificial intelligence to enhance their creative processes. These capabilities are accessible through compatible endpoints and require the use of an API key.
    • Tutoring and Education: The Meta Llama 3 model can explain concepts, provide examples, and help with homework and test prep across many academic subjects. This makes them ideal for developing educational tools and platforms. By fine-tuning Llama, educators can create customized learning experiences that cater to the needs of individual students. Access to these educational features can be managed through API calls and a valid API key.
    • Research and Analysis: Meta Llama 3 API can assist with research by finding relevant information, analyzing data, and drawing insights. It can also help with literature reviews and hypothesis generation. Researchers in fields such as cybersecurity can leverage the artificial intelligence capabilities of Llama models to enhance their studies. The open LLM and available LLM models provide a broad range of applications that can be accessed through the appropriate API calls.
    • Accessibility: The open-source nature of Meta Llama 3 makes it more accessible for researchers, developers, and companies to build AI applications than proprietary models. This democratization of artificial intelligence ensures that more people can benefit from advanced AI tools without the constraints of closed systems. To utilize these models, users must navigate the model page and make the necessary API calls with a valid API key.

    Advanced Features of Meta Llama 3 API

    • Cutting-Edge AI-Language Model: Meta Llama 3 stands as a beacon of innovation in AI language modeling, delivering state-of-the-art performance in understanding and generating language. Leveraging the latest advancements in deep learning, Meta Llama 3 surpasses traditional language models, offering unparalleled accuracy and fluency in its responses. Whether it's crafting engaging dialogue or generating informative text, Meta Llama 3 excels in capturing the nuances of language, making it a valuable tool for a wide range of applications.
    • Enhanced Versions: Available in two sizes, including a fine-tuned version, Meta Llama 3 offers increased power and capabilities, surpassing its predecessor, Meta Llama 2, and enabling a wide range of diverse applications. The fine-tuned version of Meta Llama 3 incorporates advanced algorithms and larger model parameters, allowing it to handle more complex tasks with greater efficiency and accuracy. This versatility makes Meta Llama 3 suitable for a variety of use cases, from content generation to natural language understanding.
    • Compatibility with Meta's Chat Assistants: Meta Llama 3 seamlessly integrates with Meta's chat assistants on platforms like Facebook, Instagram, and WhatsApp, ensuring model responses enhance user interactions and experiences. By leveraging Meta's extensive ecosystem, developers can deploy Meta Llama 3-powered chatbots to engage with users in natural language conversations, providing personalized assistance and information retrieval. This compatibility expands the reach of Meta Llama 3, enabling it to interact with users across diverse communication channels.
    • Open Accessibility: Meta Llama 3 follows an open approach, being openly available for free. This encourages proximal policy optimization and fosters collaboration, research, and innovation in AI technology, all while ensuring Trust & Safety in its use. By embracing an open-access model, Meta empowers developers and researchers to explore the capabilities of Meta Llama 3, driving advancements in natural language processing and promoting transparency in AI development. This open accessibility promotes inclusivity and democratization of AI, allowing individuals from diverse backgrounds to contribute to the advancement of the field.
    • Evolutionary Improvements: As the successor to Meta Llama 2, Meta Llama 3 boasts significant evolutionary improvements in logic, understanding, and factual accuracy, making it a more reliable tool for generative text models and various language-related tasks. Through continuous refinement and optimization, Meta Llama 3 has evolved to better capture the nuances of human language, enabling more natural and contextually relevant interactions. These evolutionary improvements enhance the user experience and expand the range of applications for Meta Llama 3, positioning it as a leading AI language model in the industry.
    • Efficient Architecture: Utilizing a decoding-focused system rooted in deep learning, Meta Llama 3 efficiently handles language tasks, ensuring optimal model responses and performance across a wide range of applications. By leveraging advanced techniques such as sequence-to-sequence learning and attention mechanisms, Meta Llama 3 achieves high levels of accuracy and fluency in its output, even when processing large volumes of text. This efficient architecture enables Meta Llama 3 to deliver fast and reliable responses, making it suitable for real-time applications where responsiveness is crucial.
    • Broad Pretraining Data: Trained on diverse sources in over 30 languages, Meta Llama 3 exhibits near-future adaptability and versatility, enabling comprehensive language understanding and facilitating a wide range of applications. The extensive pretraining data used to train Meta Llama 3 ensures that it can effectively handle a variety of linguistic patterns and styles, regardless of the language or dialect. This broad linguistic coverage enables Meta Llama 3 to excel in tasks such as machine translation, sentiment analysis, and text summarization, making it a versatile tool for language processing tasks in diverse domains.
    • Superior Performance: Meta Llama 3 outperforms competitors in language understanding and problem-solving, showcasing its prowess in deep learning and its ability to handle complex language tasks with accuracy and efficiency. Its advanced algorithms and finely tuned parameters enable Meta Llama 3 to achieve state-of-the-art performance across a variety of language processing tasks, including language modeling, text generation, and dialogue generation. Whether it's generating coherent paragraphs of text or answering complex questions, Meta Llama 3 consistently delivers high-quality model responses that meet the needs of users and developers alike.
    • Wide Range of Applications: Supporting various tasks ranging from content generation to coding, Meta Llama 3 is a versatile tool for diverse use cases across industries. Whether it's generating creative content or assisting with coding tasks, Meta Llama 3 offers unparalleled flexibility and functionality. Its ability to adapt to different tasks and domains makes it a valuable asset for developers and businesses looking to leverage AI for a wide range of applications. From customer service chatbots to virtual assistants, Meta Llama 3 can be customized and deployed to meet the specific needs of any project or organization.
    • Development Tools and Support: Meta provides tools like Torchtune for easy model integration and guides for application development, facilitating the seamless integration of Meta Llama 3 into projects, including those in the AI Playground. These development tools and support resources empower developers to harness the full potential of Meta Llama 3, enabling them to build and deploy AI-powered applications with ease. By providing comprehensive documentation, tutorials, and sample code, Meta ensures that developers have the resources they need to successfully integrate Meta Llama 3 into their projects and unlock its advanced features.
    • Future Enhancements: With a focus on continuous innovation, Meta aims to enhance Meta Llama 3's new capabilities further shortly, exploring areas like image understanding and specialized knowledge domains to expand its potential applications and improve model responses. By incorporating cutting-edge techniques such as proximal policy optimization and advanced generative text models, Meta Llama 3 will continue to push the boundaries of AI language processing, enabling more sophisticated and contextually aware interactions. These new capabilities will empower developers to create innovative AI-powered solutions that address the evolving needs of users and businesses, cementing Meta Llama 3's position as a leading AI language model in the industry.

    Technical Specifications of Meta Llama 3 API

    • Availability: Meta Llama 3 follows an open approach, being openly accessible and available for free. This encourages innovation, research, and development in the AI community, fostering collaboration and the advancement of AI technology across diverse fields. Developers can easily access and run Llama in the AI Playground, exploring its capabilities and integrating it into various projects.
    • Model Card and Security Features: Meta provides a detailed Model Card that outlines the specifications, capabilities, and ethical considerations of Meta Llama 3. In addition, security features like Llama Guard 2 and Code Shield ensure that the model is protected from misuse and vulnerabilities, maintaining a high standard of safety and reliability.
    • Cloud Integration: Meta Llama 3 is designed to operate efficiently on various cloud platforms, including Google Cloud, allowing for scalable deployment and integration. The API supports a context window of significant length, enabling it to handle extensive text inputs and generate coherent responses over long interactions. The context length and model size are optimized to balance performance and resource usage, ensuring that both the base and enhanced models deliver robust model performance.
    • Open-Source Models and Compatibility: Meta's commitment to transparency and accessibility is evident in its support for open-source models. The Meta Llama 3 API is compatible with a range of models, including Mistral 7B and other leading AI frameworks, facilitating seamless integration and interoperability across different AI ecosystems.
    • Future Enhancements: Meta is committed to continuous improvement and innovation in AI technology. Planned enhancements for Meta Llama 3 include the integration of multimodal capabilities to handle and interpret image data alongside text, expanding language capabilities to cover more languages and dialects, and enhancing the model’s ability to handle domain-specific knowledge, thereby improving performance in specialized applications.
    • Training Data: Meta’s Llama 3 is pre-trained on a diverse set of data sources, including books, websites, and other text-rich content in over 30 languages. This extensive pretraining enables the model to understand and generate text across a wide range of languages and domains, supporting diverse applications.
    • Model Architecture: Meta Llama 3 is a state-of-the-art AI language model that leverages advanced transformer architecture to deliver high accuracy and efficiency in language processing tasks. This architecture includes a decoding-focused system optimized for generating precise and contextually relevant generated_text, ensuring model performance meets the highest standards.
    • Security and Compliance: Meta prioritizes Trust & Safety, ensuring that Meta Llama 3 adheres to high standards of security and ethical AI use. Key features include robust measures to protect user data and privacy, compliance with global data protection regulations, and built-in safeguards to prevent the generation of harmful or biased content, promoting responsible AI use.
    • Customization and Fine-Tuning: Meta Llama 3 offers extensive customization options, enabling developers to tailor the model to specific use cases. Features include the ability to create fine-tuned versions of Meta Llama 3 to optimize performance for specific tasks or industries, and customizable parameters to control aspects such as response length, creativity, and tone.
    • Integration and Compatibility: The Meta Llama 3 API is designed for seamless integration into various applications and platforms. Key integration features include a comprehensive set of API Endpoints that allow developers to access different functionalities of Meta Llama 3, including chat/completions, text generation, question answering, and language translation. Meta provides development tools like Torchtune for model fine-tuning and integration guides to help developers incorporate Meta Llama 3 into their projects efficiently.
     

    What are the Benefits of Meta Llama 3 API?

    • Accessibility and Openness: Meta has made Llama 3 freely available and open-source, democratizing access to this powerful AI technology. This allows developers, researchers, and businesses to experiment, build upon, and contribute to its development without any licensing fees. The open nature fosters collaboration, scrutiny, and innovation in the AI community. It is similar to OpenAI's GPT-3.5 in terms of being an open-source parameter model.
    • Powerful Language Capabilities: Llama 3 excels at understanding and generating human-like text across various tasks like content creation, language translation, code generation, and answering questions. It outperforms previous versions and other open models in benchmarks measuring language understanding and reasoning. It is based on the 70B-Instruct architecture, which is the latest version of the 70B-Instruct model.
    • Efficient and Optimized: Meta has implemented techniques like tokenization and attention routing to optimize Llama 3's performance, allowing it to run efficiently without requiring excessive computational resources. This makes it easier to deploy across different platforms and devices. Users can use Llama through the Inference API.
    • Customization and Fine-tuning: Enterprises can customize and fine-tune Llama 3 with their proprietary data while maintaining data privacy and security. This allows tailoring the model's capabilities to specific domains or use cases.
    • Seamless Integration: Llama 3 is integrated into Meta's core products like Facebook Messenger, Instagram, and WhatsApp as the "Meta AI" assistant, making its capabilities readily accessible. It can also be easily deployed via APIs on various cloud platforms. Users can access it through an API token.
    • Responsible Development: Meta emphasizes responsible AI development, with measures like content moderation, human oversight, and ethical considerations built into Llama 3's deployment and usage guidelines. Meta has developed Meta Llama Guard to ensure best practices are followed when using the model. It is also available on Azure AI and other cloud platforms for commercial use, with new trust measures in place.

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