Langtrace Integrations

OpenAI's mission, which is to ensure artificial general intelligence (AGI), benefits all people. This refers to highly autonomous systems that outperform humans in most economically valuable work. While we will try to build safe and useful AGI, we will also consider our mission accomplished if others are able to do the same. Our API can be used to perform any language task, including summarization, sentiment analysis and content generation. You can specify your task in English or use a few examples. Our constantly improving AI technology is available to you with a simple integration. These sample completions will show you how to integrate with the API.

Gemini was designed from the ground-up to be multimodal. It is highly efficient in tool and API integrations, and it is built to support future innovations like memory and planning. We're seeing multimodal capabilities that were not present in previous models. Gemini is our most flexible model to date -- it can run on anything from data centers to smartphones. Its cutting-edge capabilities will improve the way developers and enterprises build and scale AI. Gemini Ultra - Our largest and most capable model, designed for highly complex tasks. Gemini Pro is our best model to scale across a variety of tasks. Gemini Nano -- our most efficient model for on-device tasks. Gemini Flash - our experimental model is our workhorse with low latency, enhanced performance and built to power agentic experience.

Claude is an artificial intelligence language model that can generate text with human-like processing. Anthropic is an AI safety company and research firm that focuses on building reliable, interpretable and steerable AI systems. While large, general systems can provide significant benefits, they can also be unpredictable, unreliable and opaque. Our goal is to make progress in these areas. We are currently focusing on research to achieve these goals. However, we see many opportunities for our work in the future to create value both commercially and for the public good.

Where does knowledge begin? Perplexity AI is a search engine that provides quick answers. Available for free on perplexity.ai, or on iPhone or Android. Perplexity AI, an advanced search tool and question-answering system, uses large language models to provide contextually relevant and accurate answers to user queries. It is designed for both general and specific inquiries. It combines AI with real-time searching capabilities to retrieve and synthesize data from a variety of sources. Perplexity AI focuses on ease of use and transparency. It often provides citations or links directly to its sources. Its goal to streamline the process of information discovery while maintaining high accuracy, clarity, and precision in its responses. This makes it a valuable tool both for researchers and professionals.

Microsoft Azure is a cloud computing platform that allows you to quickly develop, test and manage applications. Azure. Invent with purpose. With more than 100 services, you can turn ideas into solutions. Microsoft continues to innovate to support your development today and your product visions tomorrow. Open source and support for all languages, frameworks and languages allow you to build what you want and deploy wherever you want. We can meet you at the edge, on-premises, or in the cloud. Services for hybrid cloud enable you to integrate and manage your environments. Secure your environment from the ground up with proactive compliance and support from experts. This is a trusted service for startups, governments, and enterprises. With the numbers to prove it, the cloud you can trust.

With just a few lines, you can integrate natural language understanding and generation into the product. The Cohere API allows you to access models that can read billions upon billions of pages and learn the meaning, sentiment, intent, and intent of every word we use. You can use the Cohere API for human-like text. Simply fill in a prompt or complete blanks. You can create code, write copy, summarize text, and much more. Calculate the likelihood of text, and retrieve representations from your model. You can filter text using the likelihood API based on selected criteria or categories. You can create your own downstream models for a variety of domain-specific natural languages tasks by using representations. The Cohere API is able to compute the similarity of pieces of text and make categorical predictions based on the likelihood of different text options. The model can see ideas through multiple lenses so it can identify abstract similarities between concepts as distinct from DNA and computers.

Weaviate is an open source vector database. It allows you to store vector embeddings and data objects from your favorite ML models, and scale seamlessly into billions upon billions of data objects. You can index billions upon billions of data objects, whether you use the vectorization module or your own vectors. Combining multiple search methods, such as vector search and keyword-based search, can create state-of-the art search experiences. To improve your search results, pipe them through LLM models such as GPT-3 to create next generation search experiences. Weaviate's next generation vector database can be used to power many innovative apps. You can perform a lightning-fast, pure vector similarity search on raw vectors and data objects. Combining keyword-based and vector search techniques will yield state-of the-art results. You can combine any generative model with your data to do Q&A, for example, over your dataset.

SigNoz can be used as an open-source alternative to Datadog or New Relic. A single tool that can handle all your observability requirements, including APM, logs and metrics, exceptions and alerts, dashboards, and dashboards. You don't have to manage multiple tools. You can use the powerful query builder and great charts that come with the software to dig deeper into data. By using an open-source standard, you are not locked into a vendor. OpenTelemetry's auto-instrumentation libraries can help you get started quickly and with minimal code changes. OpenTelemetry provides a single-stop solution to all your telemetry requirements. A single standard for telemetry signals increases developer productivity and consistency within teams. Write queries for all telemetry signals. Apply filters and formulas and run aggregates to gain deeper insights. SigNoz uses ClickHouse, a fast open source distributed columnar database. Ingestion and aggregates are lightning fast.

Log management. Upgraded Honeycomb. Honeycomb is designed for modern developers to help them understand and improve their log management. You can quickly query system logs, metrics, and traces to find unknown unknowns. Interactive charts provide the most detailed view against raw, high-cardinality data. You can set Service Level Objectives (SLOs), based on what users are most interested in, to reduce noise alerts and prioritize work. Customers will be happy if you reduce on-call time, ship code faster, and minimize the amount of work required. Find the cause. Optimize your code. View your prod in high-res.

Search, observability, security, and enterprise search for the cloud. Whether you use Amazon Web Services, Google Cloud or Microsoft Azure, you can quickly and easily find the information you need, gain insights, protect your investment in technology, and do so with ease. We take care of the maintenance so that you can concentrate on the things that matter to you. It's easy to configure and deploy. You can scale easily, use custom plugins and optimize your architecture for log and time series data. You can get the full Elastic experience, including machine learning, Canvas and APM, index lifecycle management as well as Elastic App Search and Elastic Workplace Search. Logging and metrics are only the beginning. To address security, observability and other critical use cases, you can bring together your diverse data.

The AI Knowledge Platform. The Pinecone Database, Inference, and Assistant make building high-performance vector search apps easy. Fully managed and developer-friendly, the database is easily scalable without any infrastructure problems. Once you have vector embeddings created, you can search and manage them in Pinecone to power semantic searches, recommenders, or other applications that rely upon relevant information retrieval. Even with billions of items, ultra-low query latency Provide a great user experience. You can add, edit, and delete data via live index updates. Your data is available immediately. For more relevant and quicker results, combine vector search with metadata filters. Our API makes it easy to launch, use, scale, and scale your vector searching service without worrying about infrastructure. It will run smoothly and securely.

Postgres: Open-source vector similarity search Supports exact and approximate closest neighbor search for L2 distances, inner product and cosine distances.

Chroma is an AI-native, open-source embedding system. Chroma provides all the tools needed to embeddings. Chroma is creating the database that learns. You can pick up an issue, create PRs, or join our Discord to let the community know your ideas.

Qdrant is a vector database and similarity engine. It is an API service that allows you to search for the closest high-dimensional vectors. Qdrant allows embeddings and neural network encoders to be transformed into full-fledged apps for matching, searching, recommending, etc. This specification provides the OpenAPI version 3 specification to create a client library for almost any programming language. You can also use a ready-made client for Python, or other programming languages that has additional functionality. For Approximate Nearest Neighbor Search, you can make a custom modification to the HNSW algorithm. Search at a State of the Art speed and use search filters to maximize results. Additional payload can be associated with vectors. Allows you to store payload and filter results based upon payload values.

LlamaIndex, a "dataframework", is designed to help you create LLM apps. Connect semi-structured API data like Slack or Salesforce. LlamaIndex provides a flexible and simple data framework to connect custom data sources with large language models. LlamaIndex is a powerful tool to enhance your LLM applications. Connect your existing data formats and sources (APIs, PDFs, documents, SQL etc.). Use with a large-scale language model application. Store and index data for different uses. Integrate downstream vector stores and database providers. LlamaIndex is a query interface which accepts any input prompts over your data, and returns a knowledge augmented response. Connect unstructured data sources, such as PDFs, raw text files and images. Integrate structured data sources such as Excel, SQL etc. It provides ways to structure data (indices, charts) so that it can be used with LLMs.

Enterprise plugins such as Splunk, ServiceNow and Datadog allow you to view all your data in one place. Collaboration features built-in allow teams to collaborate from one dashboard. Advanced security and compliance features ensure that your data remains secure. Access to Prometheus, Grafite, Grafana experts, and hands-on support. Other vendors will try and sell you an "everything is in my database" mentality. Grafana Labs has a different approach. We want to help with your observation, not own it. Grafana Enterprise gives you access to enterprise plugins. These plugins allow you to import your data sources into Grafana. This allows you to visualize all data in a more efficient and effective manner, allowing you to get the most out of expensive and complex monitoring systems.

We believe that the most effective and differentiated applications won't only call out via an API to a language model. LangChain supports several modules. We provide examples, how-to guides and reference docs for each module. Memory is the concept that a chain/agent calls can persist in its state. LangChain provides a standard interface to memory, a collection memory implementations and examples of agents/chains that use it. This module outlines best practices for combining language models with your own text data. Language models can often be more powerful than they are alone.

Groq's mission is to set the standard in GenAI inference speeds, enabling real-time AI applications to be developed today. LPU, or Language Processing Unit, inference engines are a new end-to-end system that can provide the fastest inference possible for computationally intensive applications, including AI language applications. The LPU was designed to overcome two bottlenecks in LLMs: compute density and memory bandwidth. In terms of LLMs, an LPU has a greater computing capacity than both a GPU and a CPU. This reduces the time it takes to calculate each word, allowing text sequences to be generated faster. LPU's inference engine can also deliver orders of magnitude higher performance on LLMs than GPUs by eliminating external memory bottlenecks. Groq supports machine learning frameworks like PyTorch TensorFlow and ONNX.

Telemetry that is portable, ubiquitous, and high-quality to allow effective observation. OpenTelemetry is an open-source collection of APIs and SDKs. It can be used to instrument, generate logs, logs, or traces telemetry data to analyze the performance and behavior of your software. OpenTelemetry can be used in many languages. You can create and collect telemetry data using your software and services, and then forward them to various analysis tools. OpenTelemetry can be integrated with popular frameworks and libraries like ASP.NET Core Express, Quarkus, Spring, and ASP.NET Core. Integration is as easy as writing a few lines. OpenTelemetry is 100% free and open source. It is supported by industry leaders in observability.