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# Maxim AI Documentation

> Maxim AI is the GenAI evaluation and observability platform that helps teams build reliable AI applications. This documentation covers our platform features, APIs, SDKs, and comprehensive guides for AI development and testing.

Maxim AI provides:
- Observability and monitoring for AI applications
- Agent simulation and evaluation
- Comprehensive SDK support for Python and TypeScript
- Integration with leading Agent Development platforms and frameworks
- Enterprise-grade security

## Documentation

- [Maxim AI - Home](https://getmaxim.ai): Maxim AI is an end-to-end evaluation and observability platform for AI agents.
- [Maxim Bifrost](https://www.getmaxim.ai/bifrost): Bifrost is a high-performance LLM gateway that connects 1000+ models through a single API interface with extremely high throughput and is 40x faster than LiteLLM.
- [Maxim Bifrost - OSS Friends](https://www.getmaxim.ai/bifrost/oss-friends): Amazing open source projects that share our mission of making AI development more accessible and efficient.
- [Platform Overview](https://www.getmaxim.ai/docs/introduction/overview): An introduction to Maxim's platform for AI application development and observability.
- [Maxim Documentation Home](https://www.getmaxim.ai/docs): Overview of Maxim's platform and its features for AI application development.
- [The GenAI evaluation and observability platform](https://www.getmaxim.ai/llms.txt): Overview of Maxim AI's GenAI evaluation and observability platform.
- [CoTools and the Future of LLM Tool Use for Complex Reasoning](https://www.getmaxim.ai/blog/chain-of-tools-llm-framework): Introduction to the Chain-of-Tools framework for enabling LLMs to interact with external tools.
- [Maxim AI February 2025 Update](https://www.getmaxim.ai/blog/maxim-february-2025-update): Overview of new features and updates in Maxim AI for February 2025.
- [Building Robust Evaluation Workflows for AI Agents](https://www.getmaxim.ai/blog/evaluation-workflows-for-ai-agents): Best practices for evaluating AI agents through structured workflows.
- [Experimentation](https://www.getmaxim.ai/products/experimentation): Product page for Maxim AI's experimentation tools for prompts and agents.
- [Evaluating a Healthcare Use Case Using Vertex AI and Maxim AI - Part 1](https://www.getmaxim.ai/blog/evaluating-a-healthcare-use-case-using-vertex-ai-and-maxim-ai-part-1): Introduction to evaluating healthcare AI systems using Vertex AI and Maxim AI.
- [Can Your AI Explain Why It’s Moral?](https://www.getmaxim.ai/blog/can-your-ai-explain-why-its-moral): Examines the ethical reasoning capabilities of AI models using a structured audit framework.
- [Advanced RAG Techniques](https://www.getmaxim.ai/blog/advanced-rag-techniques): Exploration of Astute RAG for handling imperfect retrieval in LLMs.
- [Agent-as-a-Judge: Evaluating Agentic Systems](https://www.getmaxim.ai/blog/agent-evaluation): Explores the Agent-as-a-Judge framework for evaluating agentic systems using AI.
- [Maxim AI June 2025 Updates](https://www.getmaxim.ai/blog/maxim-ai-june-2025-updates): Highlights new features, integrations, and updates in Maxim AI for June 2025.
- [Announcing Maxim AI’s General Availability and Seed Round](https://www.getmaxim.ai/blog/announcing-maxim-ais-general-availability-and-the-3m-funding-round-led-by-elevation-capital): Announcement of Maxim AI's general availability and $3M funding round led by Elevation Capital.
- [Chain-of-Thought Prompting: Enhancing LLM Reasoning](https://www.getmaxim.ai/blog/chain-of-thought-prompting): A blog exploring the Chain-of-Thought prompting technique for LLMs.
- [SuperBPE: Rethinking Tokenization for Language Models](https://www.getmaxim.ai/blog/superbpe-rethinking-tokenization-for-language-models): Exploration of the SuperBPE tokenization strategy for language models.
- [Maxim AI March 2025 Updates](https://www.getmaxim.ai/blog/maxim-ai-march-2025-updates): Highlights of new features, customer stories, and upcoming releases in Maxim AI.
- [Base vs. Aligned: Why Base LLMs Might be Better at Randomness and Creativity](https://www.getmaxim.ai/blog/base-vs-aligned-why-base-llms-might-be-better-at-randomness-and-creativity): Explores the tradeoffs between base and aligned LLMs in tasks requiring unpredictability and creativity.
- [Sure your LLM is smart, but does it really give a damn?](https://www.getmaxim.ai/blog/sure-your-llm-is-smart-but-does-it-really-give-a-damn): Exploration of goal-directedness in large language models and its impact on agentic applications.
- [RAGChecker](https://www.getmaxim.ai/blog/ragchecker-eval-tool): Exploration of the RAGChecker framework for evaluating Retrieval-Augmented Generation systems.
- [Schedule a Demo - Maxim](https://www.getmaxim.ai/demo): Schedule a demo to see Maxim in action and save development time.
- [Agent Simulation & Evaluation](https://www.getmaxim.ai/products/agent-simulation-evaluation): Simulate and evaluate AI agent interactions across scenarios and user personas.
- [Built an Event Discovery AI Agent using No-Code under 15 mins](https://www.getmaxim.ai/blog/built-an-event-discovery-ai-agent-using-no-code-under-15-mins): Blog post on creating an event discovery AI agent using n8n and Maxim.
- [Innovative Training of LLMs in Continuous Latent Spaces](https://www.getmaxim.ai/blog/llms-continuous-latent-spaces): Exploration of Coconut, a novel approach to LLM reasoning in continuous latent spaces.
- [Agent Observability](https://www.getmaxim.ai/products/agent-observability): Monitor and improve AI agent performance with real-time insights and observability tools.
- [Skipping the Thinking: How Simple Prompts Can Outperform Complex Reasoning in AI](https://www.getmaxim.ai/blog/skipping-the-thinking-how-simple-prompts-can-outperform-complex-reasoning-in-ai): Explores the 'NoThinking' strategy for efficient AI reasoning.
- [Maxim AI Pricing Plans](https://www.getmaxim.ai/pricing): Explore Maxim AI's pricing plans for developers, professionals, businesses, and enterprises.
- [Synthetic Data Generation Grounded in Real Data Sources](https://www.getmaxim.ai/blog/synthetic-data-generation): Exploration of the Source2Synth framework for generating high-quality synthetic data.
- [RAGEval: Scenario-specific RAG Evaluation Framework](https://www.getmaxim.ai/blog/rageval-rag-eval): Introduction to RAGEval, a framework for generating domain-specific RAG evaluation datasets.
- [What is RAG? A Comprehensive Guide](https://www.getmaxim.ai/blog/rag-in-ai): An in-depth guide to retrieval-augmented generation (RAG) in AI.
- [Maxim Social Updates](https://www.getmaxim.ai/blog/maxim-social-updates): Highlights Maxim AI's partnerships, launches, and platform listings.
- [APIGen-MT: Structured Multi-Turn Data via Simulation](https://www.getmaxim.ai/blog/apigen-mt-structured-multi-turn-training-data-for-agents): Introduction to APIGen-MT for generating multi-turn training data for AI agents.
- [Platform Overview](https://www.getmaxim.ai/docs/observability/concepts): Overview of Maxim's tools for AI application development and observability.
- [Build an AI Interview Voice Agent with LiveKit & Maxim](https://www.getmaxim.ai/blog/build-an-ai-interview-voice-agent-with-livekit-maxim): A tutorial on building a real-time AI interview voice agent using LiveKit and Maxim.
- [Careers](https://www.getmaxim.ai/careers): Join Maxim AI to shape the future of AI development.
- [Scaling Enterprise Support: Atomicwork's Journey to Seamless AI Quality with Maxim](https://www.getmaxim.ai/blog/scaling-enterprise-support-atomicworks-journey-to-seamless-ai-quality-with-maxim): Case study on how Atomicwork uses Maxim AI to ensure reliable and scalable AI-powered enterprise support.
- [Maxim AI - Product Updates, December 2024](https://www.getmaxim.ai/blog/maxim-ai-december-2024-updates): Overview of new features and updates in Maxim AI for December 2024.
- [About Us](https://www.getmaxim.ai/about-us): Overview of Maxim's mission, team, and vision for AI development.
- [Long-context LLMs vs RAG](https://www.getmaxim.ai/blog/llm-rag-compare): Comparison of long-context LLMs and Retrieval-Augmented Generation (RAG) models.
- [Maxim AI January 2025 Updates](https://www.getmaxim.ai/blog/maxim-ai-january-2025-updates): Overview of new features and updates in Maxim AI for January 2025.
- [Can We Trust What AI Models Say They're Thinking? A Deep Dive into Chain-of-Thought Faithfulness](https://www.getmaxim.ai/blog/can-we-trust-what-ai-models-say-theyre-thinking-a-deep-dive-into-chain-of-thought-faithfulness): Exploration of the faithfulness of AI models' Chain-of-Thought reasoning.
- [🌤️ Building a Gemini-Powered Conversational Weather Agent with Maxim Logging](https://www.getmaxim.ai/blog/building-a-gemini-powered-conversational-weather-agent-with-maxim-logging): A tutorial on building a conversational weather agent using Gemini AI and Maxim logging.
- [Mindtickle’s Robust AI Productionizing Process powered by Maxim](https://www.getmaxim.ai/blog/mindtickle-ai-quality-evaluation-using-maxim): Explores how Mindtickle uses Maxim to enhance AI quality and streamline production processes.
- [Agent Evaluation: Metrics for Evaluating Agentic Workflows](https://www.getmaxim.ai/blog/ai-agent-evaluation-metrics): A blog post discussing metrics for evaluating AI agents in dynamic workflows.
- [Mastering the Art of Prompt Engineering: A Practical Guide for Better AI Outcomes](https://www.getmaxim.ai/blog/mastering-prompt-engineering): A comprehensive guide to crafting effective prompts for AI models.
- [Best Practices for Retrieval-Augmented Generation (RAG)](https://www.getmaxim.ai/blog/rag-best-practices): Comprehensive guide to optimizing RAG systems with advanced techniques.
- [AlphaEvolve: AI for Scientific Discovery](https://www.getmaxim.ai/blog/alphaevolve-ai-for-scientific-discovery): Exploration of AlphaEvolve, an AI system for algorithmic discovery in scientific challenges.
- [The Role of Retrieval in Improving RAG Performance](https://www.getmaxim.ai/blog/rag-retrieval): Exploration of retrieval techniques to enhance Retrieval-Augmented Generation (RAG).
- [✨ Agentic mode, Scheduled runs, New evals, and more](https://www.getmaxim.ai/blog/maxim-ai-may-2025-updates): Highlights of Maxim AI's May 2025 updates, including new features and model support.
- [LLM Hallucination Detection](https://www.getmaxim.ai/blog/llm-hallucination-detection): Exploration of fine-grained hallucination detection techniques for improving LLM accuracy.
- [Tool Chaos No More: Measuring Model-Tool Accuracy](https://www.getmaxim.ai/blog/tool-chaos-no-more-how-were-measuring-model-tool-accuracy-in-the-age-of-mcp): Insights into benchmarking tool call accuracy in AI models using MCP.
- [Custom Evaluators](https://getmaxim.ai/docs/library/how-to/evaluators/create-custom-ai-evaluator): Guide to creating and configuring custom evaluators for AI evaluation needs.
- [Last Week at Maxim: Week 1 of May](https://www.getmaxim.ai/blog/last-week-at-maxim-week-1-of-may): Weekly updates on new features and improvements at Maxim.
- [Improving RAG accuracy with reranking techniques](https://www.getmaxim.ai/blog/reranker-rag): Explores how reranking techniques can enhance Retrieval-Augmented Generation (RAG) accuracy.
- [Tracing Quickstart](https://www.getmaxim.ai/docs/tracing/quickstart): A guide to setting up distributed tracing for GenAI applications.
- [Evaluating Data Contamination in LLMs](https://www.getmaxim.ai/blog/llm-data-quality): Analysis of data contamination in large language models and its impact on benchmarks.
- [Create a Customer Support Email Agent](https://www.getmaxim.ai/docs/offline-evals/guides/create-customer-support-agent): Step-by-step guide to building a customer support email agent using Maxim AI.
- [Evaluating the Quality of Clinical Documentation Using Maxim AI](https://www.getmaxim.ai/blog/create-reliable-clinical-notes-using-maxim): A guide to creating and evaluating reliable clinical notes using Maxim AI's tools.
- [Founders’ Office - Marketing Generalist](https://www.getmaxim.ai/jobs/marketing-generalist): Job opening for a Marketing Generalist role at Maxim, focused on content strategy in the AI development space.
- [Evaluating the Quality of NL-to-SQL Workflows](https://www.getmaxim.ai/blog/evaluating-the-quality-of-nl-to-sql-workflows): Explores methods to improve NL-to-SQL workflows for better query accuracy and user trust.
- [LangChain Integration](https://www.getmaxim.ai/docs/sdk/typescript/integrations/langchain/langchain): Comprehensive guide to integrating Maxim observability with LangChain applications in TypeScript/JavaScript.
- [From Zero to OTel: Architecting a Stateless Tracing SDK for GenAI](https://www.getmaxim.ai/blog/from-zero-to-otel-architecting-a-stateless-tracing-sdk-for-genai-part-1): Explores the architecture of a stateless distributed tracing system compatible with OpenTelemetry for GenAI observability.
- [Building a Math Trivia Game Agent with Mistral AI and Maxim](https://www.getmaxim.ai/blog/building-a-math-trivia-game-agent-with-mistral-ai-and-maxim): A tutorial on creating a Math Trivia Game using Mistral AI and Maxim for observability.
- [Making Language Models Unbiased, One Vector At a Time](https://www.getmaxim.ai/blog/making-language-models-unbiased-one-vector-at-a-time): Explores methods to reduce bias in large language models using interpretability-based techniques.
- [Do Language Models Know That They're Being Evaluated?](https://www.getmaxim.ai/blog/do-language-models-know-that-theyre-being-evaluated): Explores the phenomenon of evaluation awareness in language models and its implications.
- [Maxim Integration for CrewAI](https://www.getmaxim.ai/docs/sdk/python/integrations/crewai/crewai): Comprehensive agent monitoring, evaluation, and observability for CrewAI applications.
- [From Turn 1 to Turn 10: How LLMs Get Lost In Multi-Turn Conversations](https://www.getmaxim.ai/blog/from-turn-1-to-turn-10-how-llms-get-lost-in-multi-turn-conversations): Explores the challenges LLMs face in multi-turn conversations and proposes methods to mitigate performance degradation.
- [Set Up Alerts and Notifications](https://www.getmaxim.ai/docs/online-evals/set-up-alerts-and-notifications): Learn how to configure notification channels and set up alerts for monitoring AI application performance and quality metrics.
- [Evaluating the Quality of Healthcare Assistants using Maxim AI](https://www.getmaxim.ai/blog/evaluating-quality-of-healthcare-assistants-using-maxim): Guide to evaluating AI healthcare assistants for reliability and performance using Maxim.
- [DSPy Framework](https://www.getmaxim.ai/blog/dspy-framework): An overview of DSPy, a declarative framework for optimizing LLM pipelines.
- [OpenAI’s BrowseComp: Redefining How We Benchmark Web-Browsing Agents](https://www.getmaxim.ai/blog/openai-browsecomp-web-browsing-agent-benchmark): An overview of OpenAI's BrowseComp benchmark for evaluating web-browsing agents.
- [Maxim SDK Core Class](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/classes/Maxim): Primary entry point for interacting with the Maxim observability platform.
- [SDK HTTP Agent Quickstart](https://www.getmaxim.ai/docs/offline-evals/via-sdk/agent-http/quickstart): Guide to quickly get started with agent evaluations via HTTP endpoints using Maxim SDK.
- [Frontend Software Engineer](https://www.getmaxim.ai/jobs/frontend-software-engineer): Job opening for a Frontend Software Engineer role at Maxim AI in Bangalore, India.
- [Simulation Runs](https://www.getmaxim.ai/docs/simulations/simulation-runs): Test AI conversational abilities with scenario-based simulations.
- [Using a Jury of LLMs Instead of a Single Judge to Evaluate LLM Generations](https://www.getmaxim.ai/blog/llm-as-a-jury): Explores the use of a panel of smaller LLMs for unbiased and cost-effective evaluation of AI outputs.
- [Understanding Jailbreaking and Prompt-Based Injections](https://www.getmaxim.ai/blog/jailbreaking-prompt-injection): Explores the risks and mechanisms of jailbreaking and prompt injection attacks in large language models.
- [Akshay Deo](https://www.getmaxim.ai/blog/author/akshay): Blog page featuring articles authored by Akshay Deo on Maxim AI updates and insights.
- [Evaluating RAG performance: Metrics and benchmarks](https://www.getmaxim.ai/blog/rag-evaluation-metrics): A detailed blog on evaluating Retrieval-Augmented Generation (RAG) systems using metrics and benchmarks.
- [KNOWHALU: Hallucination detection via multi-form knowledge-based factual checking](https://www.getmaxim.ai/blog/knowhalu-llm-fact-check): Explores KnowHalu, a novel approach to detecting hallucinations in LLM-generated text.
- [Maxim SDK Overview](https://www.getmaxim.ai/docs/sdk/overview): Introduction to Maxim SDK for AI application development.
- [Latest Blog Posts](https://www.getmaxim.ai/blog/page/13): A collection of recent blog posts on AI advancements and Maxim AI updates.
- [Building and Evaluating a Reddit Insights Agent with Gumloop and Maxim AI](https://www.getmaxim.ai/blog/building-and-evaluating-a-reddit-insights-agent-with-gumloop-and-maxim-ai-2): A detailed guide on building and evaluating a Reddit insights agent using Gumloop and Maxim AI.
- [Bifrost](https://www.getmaxim.ai/bifrost): High-performance LLM gateway connecting multiple AI providers through a single API.
- [User Simulation in AI: From Rule-Based Models to LLM-Powered Realism](https://www.getmaxim.ai/blog/user-simulation-in-ai-from-rule-based-models-to-llm-powered-realism): Explores the evolution of user simulation in AI, from rule-based models to LLM-powered realism.
- [Offline Evaluation Overview](https://www.getmaxim.ai/docs/offline-evals/overview): Learn how to evaluate AI application performance through prompt testing, workflow automation, and continuous log monitoring.
- [Pre-built Evaluators](https://www.getmaxim.ai/docs/library/evaluators/pre-built-evaluators): Quickly get started with ready-made evaluators for common AI evaluation scenarios.
- [Last Week at Maxim (Weekly Updates)](https://www.getmaxim.ai/blog/last-week-at-maxim-weekly-update): Weekly updates on new features and improvements in Maxim's platform.
- [Experiment with Prompt Chains](https://www.getmaxim.ai/docs/evaluate/how-to/evaluate-chains/experiment-with-prompt-chains): Guide on experimenting with advanced prompt chains for AI workflows.
- [VGBench: Evaluating Vision-Language Models in Real-Time Gaming Environments](https://www.getmaxim.ai/blog/vgbench-evaluating-vision-language-models-in-real-time-gaming-environments): Introducing VGBench, a benchmark for evaluating Vision-Language Models in dynamic gaming environments.
- [Elevating Conversational Banking: Clinc's Path to AI Confidence with Maxim](https://www.getmaxim.ai/blog/elevating-conversational-banking-clincs-path-to-ai-confidence-with-maxim): Explore how Clinc uses Maxim to enhance conversational AI for the banking industry.
- [Your Horrible Code is Making LLMs Evil: Exploring Emergent Misalignment](https://www.getmaxim.ai/blog/your-horrible-code-is-making-llms-evil-exploring-emergent-misalignment): Analysis of emergent misalignment in LLMs caused by insecure code fine-tuning.
- [Maxim AI November 2024 Updates](https://www.getmaxim.ai/blog/maxim-ai-november-2024-updates): Overview of new features and updates in Maxim AI for November 2024.
- [✨ MCP client, Live dashboard, Vertex AI evals, and more](https://www.getmaxim.ai/blog/maxim-ai-april-2025-updates): A detailed overview of Maxim AI's April 2025 updates, including new features like MCP clients, live dashboards, and Vertex AI integration.
- [Graph RAG](https://www.getmaxim.ai/blog/graph-rag): Exploration of Microsoft's Graph-based Retrieval-Augmented Generation (Graph RAG) approach for handling global queries and large datasets.
- [Uber: Natural Language to SQL](https://www.getmaxim.ai/blog/nl-to-sql-uber): Overview of Uber's QueryGPT system for generating SQL queries from natural language prompts.
- [Tracing Concepts](https://www.getmaxim.ai/docs/tracing/concepts): Learn about Maxim’s distributed tracing concepts for AI applications.
- [Building Trustworthy AI: Thoughtful’s Journey with Maxim AI](https://www.getmaxim.ai/blog/building-smarter-ai-thoughtfuls-journey-with-maxim-ai): A blog detailing Thoughtful's integration of Maxim AI to enhance their AI companion, T.
- [Ensuring responsible AI: An overview of DeepMind’s FACTS framework](https://www.getmaxim.ai/blog/deepmind-facts-framework-responsible-ai): Highlights DeepMind’s FACTS framework for evaluating the factual accuracy of AI-generated responses.
- [Login - Maxim AI](https://www.getmaxim.ai/login): Sign in to Maxim AI to evaluate and improve AI faster.
- [Latest Blog Posts](https://www.getmaxim.ai/blog/page/7): Overview of recent blog posts on AI agent evaluation and advancements.
- [Contextual Document Embeddings](https://www.getmaxim.ai/blog/contextual-document-embeddings): Exploration of methods to improve document embeddings for neural retrieval tasks.
- [Tracing via SDK Metadata](https://www.getmaxim.ai/docs/tracing/tracing-via-sdk/metadata): Overview of Maxim's platform for AI application development and observability.
- [Context Sources](https://getmaxim.ai/docs/library/how-to/context-sources/ingest-files-as-a-context-source): Learn how to create, use, and evaluate context sources for your AI applications.
- [Blog - Page 10](https://www.getmaxim.ai/blog/page/10): A collection of blog posts exploring AI advancements, techniques, and evaluations.
- [Maxim Blog - Page 6](https://www.getmaxim.ai/blog/page/6): Latest articles and insights on AI advancements and applications.
- [Inside OpenAI’s o1: Part 2](https://www.getmaxim.ai/blog/inside-openai-o1-part-2): Exploration of OpenAI's o1 model capabilities and evaluations.
- [Better Dashboards, Smarter Workflows – Weekly Release Notes](https://www.getmaxim.ai/blog/better-dashboards-smarter-workflows-maxim-weekly-release-notes-june-9-13-2025): Overview of Maxim's weekly updates, including dashboard upgrades and SDK improvements.
- [Kuldeep Paul - Blog Author](https://www.getmaxim.ai/blog/author/kuldeep): Profile and articles authored by Kuldeep Paul on Maxim AI's blog.
- [Software Development Engineer - Maxim Careers](https://www.getmaxim.ai/jobs/software-development-engineer): Job description for a Software Development Engineer role at Maxim.
- [Inside OpenAI’s o1: Part 1](https://www.getmaxim.ai/blog/inside-openai-o1): An in-depth analysis of OpenAI’s o1 model family, focusing on evaluations and safety mechanisms.
- [Evaluation Blog Tag](https://www.getmaxim.ai/blog/tag/evaluation): Blog posts tagged under 'Evaluation' on Maxim AI.
- [Multi-agent System](https://www.getmaxim.ai/docs/offline-evals/via-ui/agents-via-no-code-builder/multi-agent-system): Guide to building multi-agent systems using Maxim's no-code builder.
- [Model Context Protocol Guide (MCP)](https://www.getmaxim.ai/blog/model-context-protocol-guide-mcp): Comprehensive guide to MCP for enabling real-time AI-powered workflows.
- [Introduction to the Agent2Agent Protocol (A2A)](https://www.getmaxim.ai/blog/introduction-to-the-agent2agent-protocol-a2a): Overview of Google's A2A protocol for enabling seamless communication between autonomous AI agents.
- [Blog](https://www.getmaxim.ai/blog): Discover the latest updates, insights, and research in AI and Maxim's ecosystem.
- [The Era of Experience: Vision for the Next Frontier in AI](https://www.getmaxim.ai/blog/the-era-of-experience-vision-for-the-next-frontier-in-ai): Exploring experiential learning as the next paradigm in AI development.
- [Platform Overview](https://www.getmaxim.ai/docs/sdk/test-runs-via-sdk/js-ts): Overview of Maxim's platform for AI application development and deployment.
- [MiniCheck: Efficient Fact-Checking of LLMs on Grounding Documents](https://www.getmaxim.ai/blog/minicheck-llm-fact-check): Introduces MiniCheck, a cost-effective model for fact-checking LLM outputs with high accuracy.
- [Tracing Quickstart](https://getmaxim.ai/docs/observe/quickstart): Quickstart guide for setting up distributed tracing to monitor and debug GenAI applications.
- [Maxim AI Blog - Page 8](https://www.getmaxim.ai/blog/page/8): Explore the latest insights and updates on AI agent evaluation, GenAI tracing, and industry applications.
- [Vaibhavi Gangwar - Blog Author](https://www.getmaxim.ai/blog/author/vaibhavi): Explore blogs authored by Vaibhavi Gangwar on AI advancements and workflows.
- [Tracing the Thoughts of Claude: Peering into an AI’s Mind](https://www.getmaxim.ai/blog/tracing-the-thoughts-of-claude-peering-into-an-ais-mind): Exploration of Anthropic’s research on understanding AI models like Claude.
- [Latest Blog Posts - Page 9](https://www.getmaxim.ai/blog/posts/page/9): A collection of recent blog posts covering AI updates, features, and innovations.
- [No-Code Agent Quickstart](https://www.getmaxim.ai/docs/offline-evals/via-ui/agents-via-no-code-builder/quickstart): Guide to testing agent workflows using a no-code builder.
- [Running Your First Eval](https://www.getmaxim.ai/docs/introduction/running-your-first-eval): Step-by-step guide to running your first evaluation on Maxim.
- [SDK No-Code Agent Quickstart](https://www.getmaxim.ai/docs/offline-evals/via-sdk/agent-no-code/quickstart): Quickstart guide for evaluating AI agents using no-code agents and the Maxim SDK.
- [RAFT: Adapting Language Models to Domain-Specific RAG](https://www.getmaxim.ai/blog/raft-domain-rag): Introduces RAFT, a training method combining fine-tuning and RAG for domain-specific question answering.
- [Build a RAG Application Using MongoDB and Maxim AI](https://www.getmaxim.ai/blog/build-rag-app-mongodb-maxim): Step-by-step guide to building a retrieval-augmented generation (RAG) application using MongoDB and Maxim AI.
- [Bifrost: A Drop-in LLM Proxy](https://www.getmaxim.ai/blog/bifrost-a-drop-in-llm-proxy-40x-faster-than-litellm): Introducing Bifrost, a high-performance LLM gateway designed for scalability and speed.
- [Blog - Page 8](https://www.getmaxim.ai/blog/posts/page/8): A collection of blog posts covering AI advancements and Maxim updates.
- [Evaluating the Quality of AI HR Assistants](https://www.getmaxim.ai/docs/offline-evals/guides/evaluating-the-quality-of-ai-hr-assistants): Guide to evaluating AI HR assistants using Maxim.
- [LongRAG](https://www.getmaxim.ai/blog/longrag-llm): An overview of LongRAG, a framework enhancing Retrieval-Augmented Generation with long-context models.
- [Decoding the Generation Component: How RAG Creates Coherent Text](https://www.getmaxim.ai/blog/rag-generation-component): Explores techniques to enhance the generation component of Retrieval-Augmented Generation (RAG).
- [Tracing Overview](https://getmaxim.ai/docs/observe/overview): Monitor AI applications in real-time with Maxim’s enterprise-grade LLM observability platform.
- [Contact Us](https://www.getmaxim.ai/contact): Get in touch with Maxim AI for queries, feedback, or support.
- [Use Data Connectors](https://www.getmaxim.ai/docs/observe/how-to/log-your-application/use-data-connectors): Instructions for forwarding traces to observability platforms using Maxim.
- [Last Week at Maxim (Week 3 of May 2025)](https://www.getmaxim.ai/blog/last-week-at-maxim-week-3-of-may-2025): A roundup of updates shipped at Maxim during the third week of May 2025.
- [Making a Financial Conversation Agent using Agno & Maxim](https://www.getmaxim.ai/blog/making-a-financial-conversation-agent-using-agno-maxim): Tutorial on building a financial conversational agent using Agno and Maxim AI.
- [Red Teaming with Auto-Generated Rewards and Multi-Step RL](https://www.getmaxim.ai/blog/ai-red-teaming): Exploring automated red-teaming frameworks for generating diverse and effective adversarial attacks.
- [Last Week at Maxim AI (Week 2 of May 2025)](https://www.getmaxim.ai/blog/last-week-at-maxim-ai-week-2-of-may-2025): Weekly updates on new features, enhancements, and bug fixes at Maxim AI.
- [Agent Evaluation: Understanding Agentic Systems and their Quality](https://www.getmaxim.ai/blog/ai-agent-quality-evaluation): An exploration of agentic AI systems, their architecture, applications, and the importance of quality evaluation.
- [Maxim Prompt Testing](https://www.getmaxim.ai/docs/offline-evals/via-sdk/prompts/maxim-prompt): Learn how to test prompts stored on the Maxim platform using the Maxim SDK.
- [Latest Blog Posts](https://www.getmaxim.ai/blog/page/3): Discover the latest updates, tutorials, and insights on AI and Maxim tools.
- [Blog Posts - Maxim AI](https://www.getmaxim.ai/blog/posts): Explore Maxim AI's blog posts on AI development and evaluation.
- [Data Plane Deployment](https://www.getmaxim.ai/docs/self-hosting/dataplane): Details on deploying Maxim's data processing infrastructure within your cloud environment.
- [Creating Prompt Partials](https://www.getmaxim.ai/docs/library/prompt-partials): Learn how to create and use prompt partials in Maxim.
- [Latest Blog Posts - Page 2](https://www.getmaxim.ai/blog/page/2): A collection of recent blog posts covering AI tools, conversational agents, and emergent misalignment.
- [Prompt Tools](https://www.getmaxim.ai/docs/library/prompt-tools): Documentation for creating and using different types of prompt tools in Maxim.
- [BrowserGym: Technical Deep Dive into Web Agent Automation](https://www.getmaxim.ai/blog/browsergym-web-agent-automation): An in-depth look at BrowserGym's framework for web agent automation and evaluation.
- [Maxim SDK for TypeScript](https://www.getmaxim.ai/docs/sdk/typescript/reference/overview): JS/TS SDK for enabling Maxim observability and evaluation.
- [SDK Prompt Quickstart](https://www.getmaxim.ai/docs/offline-evals/via-sdk/prompts/quickstart): Guide to quickly get started with running prompt evaluations using the Maxim SDK.
- [OpenAI Agents SDK](https://www.getmaxim.ai/docs/sdk/python/integrations/openai/agents-sdk): Guide for integrating Maxim with the OpenAI Agents SDK.
- [Agent Workflow Memory](https://www.getmaxim.ai/blog/agent-workflow-memory): Exploration of Agent Workflow Memory for improving long-horizon AI tasks.
- [Library Overview](https://www.getmaxim.ai/docs/library/overview): Overview of Maxim's library components for AI testing.
- [A Survey of Agent Evaluation Frameworks: Benchmarking the Benchmarks](https://www.getmaxim.ai/blog/llm-agent-evaluation-framework-comparison): A comprehensive survey of frameworks for evaluating LLM-based agents.
- [API Reference Overview](https://getmaxim.ai/docs/public-apis/overview): Comprehensive guide to Maxim's APIs, endpoints, and usage.
- [Prompt Optimization](https://www.getmaxim.ai/docs/offline-evals/via-ui/prompts/prompt-optimization): Guide to optimizing prompts using test data and evaluation metrics.
- [Operations Associate](https://www.getmaxim.ai/jobs/operations-associate): Join Maxim as an Operations Associate to manage critical business processes and support company growth.
- [Local Agent Testing](https://www.getmaxim.ai/docs/offline-evals/via-sdk/agent-no-code/local-agent): Guide to creating and evaluating custom AI agents using local execution via Maxim SDK.
- [Zero Touch Deployment](https://www.getmaxim.ai/docs/self-hosting/zerotouch): Guide to Maxim's zero-touch deployment process for secure and private self-hosting.
- [Anthropic](https://www.getmaxim.ai/blog/tag/anthropic): Explore tutorials and insights on using Anthropic models with Maxim for observability.
- [Observability](https://www.getmaxim.ai/blog/tag/observability): Insights and tutorials on observability in AI workflows using Maxim.
- [Prompt Playground](https://www.getmaxim.ai/docs/offline-evals/via-ui/prompts/prompt-playground): Experiment with prompt structures and model configurations.
- [Create Integration](https://www.getmaxim.ai/docs/integrations/integration/create-integration): Guide to creating new integrations for notification channels.
- [Tavily Search & LangGraph Agent with Maxim Observability](https://www.getmaxim.ai/docs/sdk/python/integrations/langgraph/langgraph): Tutorial on integrating Tavily Search API with LangGraph and Maxim Observability.
- [Blog - Page 11 - Maxim AI](https://www.getmaxim.ai/blog/page/11): Latest blog posts on AI advancements, techniques, and tools.
- [Set Up Alerts for Performance Metrics](https://www.getmaxim.ai/docs/observe/how-to/set-up-alerts/set-up-alerts-for-performance-metrics): Guide to configuring alerts and notifications for monitoring AI application performance.
- [Prompt Deployment](https://www.getmaxim.ai/docs/offline-evals/via-ui/prompts/prompt-deployment): Explains how to deploy prompts on Maxim without requiring code changes.
- [Maxim Integration for Agno](https://www.getmaxim.ai/docs/sdk/python/integrations/agno/agno): Guide to integrating Maxim with Agno agents for observability.
- [TestRunBuilder](https://www.getmaxim.ai/docs/sdk/python/references/test_runs/test_run_builder): Utilities for building and managing test runs in Maxim.
- [Simulate and Evaluate Multi-Turn Conversations](https://getmaxim.ai/docs/evaluate/quickstart/simulate-and-evaluate-multi-turn-conversations): Evaluate AI chat interactions using conversation simulation workflows.
- [Prompt Evals for Offline Evaluation](https://www.getmaxim.ai/docs/offline-evals/via-ui/prompts/prompt-evals): Guide to running comparison experiments across prompt versions and datasets.
- [Forwarding via Data Connectors](https://www.getmaxim.ai/docs/tracing/opentelemetry/forwarding-via-data-connectors): Documentation on using Maxim as a central hub for forwarding OpenTelemetry traces to observability platforms.
- [Latest Blog Posts - Page 4](https://www.getmaxim.ai/blog/posts/page/4): A collection of recent blog posts covering AI topics like LLM evaluations, agent simulations, and weekly updates.
- [Account Executive](https://www.getmaxim.ai/jobs/account-executive): Job listing for an Account Executive role at Maxim AI.
- [Create Dataset Entries](https://www.getmaxim.ai/docs/datasets/dataset-entry/create-dataset-entries): Documentation for creating dataset entries via Maxim AI API.
- [OpenAI SDK One-Line Integration](https://www.getmaxim.ai/docs/sdk/python/integrations/openai/one-line-integration): Guide to integrating Maxim observability with OpenAI SDK in one line of code.
- [Latest Blog Posts](https://www.getmaxim.ai/blog/posts/page/13): Compilation of recent blog posts on topics like RAG, hallucination detection, and LongRAG.
- [Human Annotation Pipeline - Maxim Docs](https://www.getmaxim.ai/docs/evaluate/how-to/evaluate-prompts/human-annotation-pipeline): Learn about integrating human annotation pipelines to improve AI quality.
- [Partha Sarathi Roy - Blog Author](https://www.getmaxim.ai/blog/author/parth): Explore blogs authored by Partha Sarathi Roy on AI topics like RAG, CoT, and LLMs.
- [Latest Blog Posts](https://www.getmaxim.ai/blog/page/9): A collection of recent blog posts covering AI advancements, product updates, and technical insights.
- [Custom Logs Dashboards](https://www.getmaxim.ai/docs/dashboards/custom-logs-dashboard): Create custom dashboards to analyze and track AI application logs using configurable metrics, filters, and charts.
- [Reporting](https://www.getmaxim.ai/docs/tracing/reporting): Learn how to set up reporting for logs and evaluation data in Maxim.
- [Querying Prompts](https://www.getmaxim.ai/docs/offline-evals/via-sdk/prompts/querying-prompts): Learn how to retrieve and use tested prompts from the Maxim platform for production workflows.
- [Trigger Test Runs Using SDK](https://www.getmaxim.ai/docs/docs/evaluate/how-to/trigger-test-runs-using-sdk): Guide on triggering test runs using Maxim SDK for AI application evaluation.
- [Vrinda Kohli - Blog Author](https://www.getmaxim.ai/blog/author/vrinda): Insights from Vrinda Kohli on AI ethics, bias, and emergent misalignment in LLMs.
- [Sameer Gupta - Blog Author](https://www.getmaxim.ai/blog/author/sameer): Technical insights from Sameer Gupta on AI reasoning, prompt engineering, and agent evaluation.
- [No-Code Agent Quickstart](https://getmaxim.ai/docs/evaluate/quickstart/run-your-first-test-on-prompt-chains): Guide to testing agentic workflows using Maxim's no-code builder.
- [Evaluating AI Healthcare Assistants](https://www.getmaxim.ai/docs/offline-evals/guides/evaluating-the-quality-of-healthcare-assistants-using-maxim-ai): Guide to evaluating the quality and reliability of AI healthcare assistants using Maxim.
- [Founding Developer Relations Engineer Role](https://www.getmaxim.ai/jobs/developer-relations-engineer): Join Maxim AI as a Developer Relations Engineer to build a thriving developer community and advocate for the platform.
- [Curate Golden Dataset for Human Annotation](https://getmaxim.ai/docs/library/how-to/datasets/curate-golden-dataset-for-human-annotation): Learn how to curate datasets from production logs and human annotations.
- [Custom Evaluators](https://www.getmaxim.ai/docs/library/how-to/evaluators/create-api-evaluators): Guide to creating and configuring custom evaluators for specific evaluation needs.
- [Tracing Concepts](https://www.getmaxim.ai/docs/observe/concepts): Learn about Maxim’s distributed tracing concepts for AI applications.
- [Prompt Sessions](https://www.getmaxim.ai/docs/offline-evals/via-ui/prompts/prompt-sessions): Documentation on managing prompt sessions for offline evaluations via UI.
- [ChatCompletionMessage Interface](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/interfaces/ChatCompletionMessage): Represents a message in a chat completion response from an AI model.
- [Offline Evaluation Concepts](https://www.getmaxim.ai/docs/evaluate/concepts): Overview of key concepts for offline evaluations in Maxim.
- [Gumloop](https://www.getmaxim.ai/blog/tag/gumloop): Blog page featuring content tagged with 'Gumloop' on Maxim AI.
- [Maxim Updates](https://www.getmaxim.ai/blog/tag/maxim-updates): A collection of blog posts highlighting updates and new features in Maxim AI.
- [Latest Blog Posts - Page 11](https://www.getmaxim.ai/blog/posts/page/11): A collection of blog posts exploring advanced AI techniques and challenges.
- [Simulate Multi-Turn Conversations](https://www.getmaxim.ai/docs/evaluate/how-to/evaluate-workflows-via-api-endpoint/simulate-multi-turn-conversations): Guide on simulating multi-turn conversations to test AI workflows.
- [Using Prompt Partials](https://www.getmaxim.ai/docs/offline-evals/via-ui/prompts/prompt-partials): Learn how to use prompt partials for efficient testing and configuration.
- [Google Gemini Integration](https://www.getmaxim.ai/docs/sdk/python/integrations/gemini/gemini): Learn how to integrate Maxim observability with the Google Gemini SDK in one line of code.
- [Offline Evaluation Concepts](https://www.getmaxim.ai/docs/offline-evals/concepts): Learn about key concepts in offline evaluation for AI models, including prompts, workflows, and evaluators.
- [Applied AI Engineer](https://www.getmaxim.ai/jobs/applied-ai-engineer): Job opening for an Applied AI Engineer role at Maxim, focusing on LLMs and AI advancements.
- [Curate Datasets from Production Logs and Annotations](https://getmaxim.ai/docs/library/how-to/datasets/curate-data-from-production): Guide on curating datasets from production logs and human annotations in Maxim.
- [Context Sources](https://getmaxim.ai/docs/library/how-to/context-sources/bring-your-rag-via-an-api-endpoint): Learn how to create, use, and evaluate context sources for your AI applications.
- [Madhu Shantan](https://www.getmaxim.ai/blog/author/madhu): Author page showcasing Madhu Shantan's AI-focused blog posts.
- [Loops in No-Code Agent Builder](https://www.getmaxim.ai/docs/offline-evals/via-ui/agents-via-no-code-builder/loops): Guide on using loops in Maxim's no-code agent builder.
- [Prompt Testing Quickstart](https://getmaxim.ai/docs/evaluate/quickstart/run-your-first-test-on-prompt): Step-by-step guide to testing prompts using datasets and evaluators.
- [Blog - Page 5](https://www.getmaxim.ai/blog/page/5): Latest articles and updates from Maxim AI's blog.
- [Latest Blog Posts - Page 3](https://www.getmaxim.ai/blog/posts/page/3): A collection of recent blog posts covering AI advancements and applications.
- [Dataset Evaluation](https://www.getmaxim.ai/docs/offline-evals/via-ui/advanced/dataset-evaluation): Evaluate AI outputs against expected results using Maxim’s Dataset evaluation tools.
- [Akshit Madan](https://www.getmaxim.ai/blog/author/akshit): Author profile featuring tutorials and insights on AI development using Maxim.
- [Latest Blog Posts](https://www.getmaxim.ai/blog/posts/page/7): Collection of recent blog posts on AI advancements and Maxim updates.
- [Building the Agentic Debugging Game: Anthropic Observability Using Maxim](https://www.getmaxim.ai/blog/building-the-agentic-debugging-game-anthropic-observability-using-maxim): Tutorial on building an interactive debugging game with Anthropic and Maxim.
- [Claude 3.5 Sonnet put to the test](https://www.getmaxim.ai/blog/claude-3-5-sonnet-put-to-the-test): A detailed comparison of Claude 3.5 Sonnet and GPT-4o models.
- [Get Alerts](https://www.getmaxim.ai/docs/alerts/alert/get-alerts): API documentation for retrieving alerts in a workspace.
- [Blog - Page 6](https://www.getmaxim.ai/blog/posts/page/6): A collection of blog posts on AI advancements and applications.
- [LangGraph Integration](https://www.getmaxim.ai/docs/sdk/typescript/integrations/langgraph/langgraph): Guide to integrating Maxim observability with LangGraph applications in TypeScript/JavaScript.
- [Latest Blog Posts](https://www.getmaxim.ai/blog/page/12): Overview of recent blog posts on AI research and applications.
- [Set Up Auto Evaluation on Logs](https://www.getmaxim.ai/docs/observe/how-to/evaluate-logs/auto-evaluation): A guide on configuring automatic evaluation of logs in Maxim AI for better LLM performance monitoring.
- [Latest Blog Updates](https://www.getmaxim.ai/blog/page/4): Roundup of recent blog posts and updates from Maxim AI.
- [Evaluating the Quality of AI HR Assistants](https://www.getmaxim.ai/blog/evaluating-the-quality-of-ai-hr-assistants): Guide on building and evaluating AI-powered HR assistants using Maxim.
- [Prompt Playground](https://www.getmaxim.ai/docs/evaluate/how-to/evaluate-prompts/experiment-in-prompt-playground): Learn how to use the Prompt Playground to experiment with and optimize prompts.
- [Set Up Alerts for Quality Metrics](https://www.getmaxim.ai/docs/observe/how-to/set-up-alerts/set-up-alerts-for-quality-metrics): Learn how to configure alerts to monitor AI application quality metrics.
- [Latest Blog Posts - Page 5](https://www.getmaxim.ai/blog/posts/page/5): A collection of recent blog posts covering AI updates, tools, and industry insights.
- [User Feedback](https://www.getmaxim.ai/docs/tracing/tracing-via-sdk/user-feedback): Documentation for tracking user feedback in application traces.
- [Ingesting via OTLP Endpoint](https://www.getmaxim.ai/docs/tracing/opentelemetry/ingesting-via-otlp): Learn how to send OpenTelemetry traces to Maxim for AI observability.
- [litellm_proxy.Tracer](https://www.getmaxim.ai/docs/sdk/python/references/logger/litellm_proxy/tracer): Tracing and instrumentation utilities for Litellm Proxy integration.
- [Test Your AI Outputs Using Application Endpoint](https://www.getmaxim.ai/docs/evaluate/how-to/evaluate-workflows-via-api-endpoint/test-your-ai-outputs-using-application-endpoint): Documentation on evaluating AI workflows via API endpoints using Maxim.
- [Get Dataset Entries](https://www.getmaxim.ai/docs/datasets/dataset-entry/get-dataset-entries): Documentation for retrieving dataset entries via Maxim AI API.
- [Prompt CI/CD Integration](https://www.getmaxim.ai/docs/offline-evals/via-sdk/prompts/ci-cd-integration): Learn how to integrate prompt evaluations into CI/CD pipelines using GitHub Actions.
- [Agent on Maxim - No-Code Testing](https://www.getmaxim.ai/docs/offline-evals/via-sdk/agent-no-code/agent-on-maxim): Guide to testing AI agents using no-code configurations on Maxim.
- [Import or Create Datasets](https://www.getmaxim.ai/docs/library/datasets/import-or-create-datasets): Guide on importing or creating datasets for AI model training, testing, and evaluation.
- [Set Up Human Annotation on Logs](https://www.getmaxim.ai/docs/online-evals/via-ui/set-up-human-annotation-on-logs): Guide to setting up human evaluation for logs in Maxim.
- [Trigger Test Runs Using SDK](https://getmaxim.ai/docs/evaluate/how-to/trigger-test-runs-using-sdk): Guide to running prompt evaluation test runs using the Maxim SDK.
- [Prompt Versions](https://www.getmaxim.ai/docs/offline-evals/via-ui/prompts/prompt-versions): Guide on managing and comparing prompt versions for AI applications.
- [Node Level Evaluation](https://www.getmaxim.ai/docs/online-evals/via-sdk/node-level-evaluation): Guide to evaluating components of AI workflows using Maxim SDK.
- [Agent Deployment via No-Code Builder](https://www.getmaxim.ai/docs/offline-evals/via-ui/agents-via-no-code-builder/agent-deployment): Deploy agents easily without code changes using Maxim's no-code builder.
- [OpenAI Agents SDK Integration](https://getmaxim.ai/docs/observe/integrations/openai-agents-sdk): Instructions for integrating Maxim with OpenAI Agents SDK for observability and real-time evaluation.
- [MaximLogsAPI Class](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/classes/MaximLogsAPI): Provides methods for managing logs in the Maxim platform.
- [LLM Blog Tag](https://www.getmaxim.ai/blog/tag/llm): Blog posts tagged with LLM, focusing on large language models and their applications.
- [Set Up Auto Evaluation on Logs](https://www.getmaxim.ai/docs/observe/how-to/evaluate-logs/human-evaluation): Guide for setting up automatic evaluation of logs in Maxim's platform.
- [Set Up Auto Evaluation on Logs](https://www.getmaxim.ai/docs/online-evals/via-ui/set-up-auto-evaluation-on-logs): Evaluate captured logs automatically from the UI based on filters and sampling.
- [Execute an Evaluator](https://www.getmaxim.ai/docs/evaluators/evaluator/execute-an-evaluator): Instructions for executing evaluators in Maxim.
- [Python SDK: decorators.Retrieval](https://www.getmaxim.ai/docs/sdk/python/references/decorators/retrieval): Reference for retrieval decorators in Maxim AI's Python SDK.
- [CrewAI Client](https://www.getmaxim.ai/docs/sdk/python/references/logger/crewai/client): Python SDK reference for CrewAI client implementation.
- [OpenAI Agents SDK Integration](https://www.getmaxim.ai/docs/integrations/openai-agents-sdk): A guide to integrating Maxim AI's observability and evaluation features with OpenAI Agents SDK.
- [About Maxim Blog](https://www.getmaxim.ai/blog/about): Introduction to the Maxim Blog and its subscription model.
- [MaximLogger](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/classes/MaximLogger): Comprehensive observability class for logging and monitoring AI applications in Maxim SDK.
- [Import or Create Datasets](https://www.getmaxim.ai/docs/library/how-to/datasets/use-dataset-templates): Guide to importing or creating datasets for AI model evaluation.
- [Get Evaluators](https://www.getmaxim.ai/docs/evaluators/evaluator/get-evaluators): API documentation for retrieving evaluators by ID, name, or workspace.
- [Online Evaluation Overview](https://www.getmaxim.ai/docs/online-evals/overview): Overview of Maxim’s online evaluation platform for monitoring AI quality in production.
- [Create Prompt Versions - Maxim AI Docs](https://www.getmaxim.ai/docs/evaluate/how-to/evaluate-prompts/create-prompt-versions): Documentation on creating and comparing prompt versions for AI experimentation.
- [QueryBuilder](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/classes/QueryBuilder): A builder class for constructing complex query rules for filtering prompts and prompt chains.
- [Curate Datasets](https://www.getmaxim.ai/docs/library/datasets/curate-datasets): Guide on curating datasets from production logs and human annotations.
- [Tracing Dashboard](https://www.getmaxim.ai/docs/tracing/dashboard): Learn how to use the dashboard to filter and sort logs.
- [Portkey](https://www.getmaxim.ai/docs/sdk/python/references/logger/portkey/portkey): Portkey utilities for integration and logging with Maxim.
- [Tracing Tool Calls](https://www.getmaxim.ai/docs/tracing/tracing-via-sdk/tool-calls): Track external system calls triggered by LLM responses in agentic endpoints.
- [Python SDK Overview](https://www.getmaxim.ai/docs/sdk/python/overview): Introduction to Maxim's Python SDK and its features.
- [Prompt Utilities for Maxim SDK](https://www.getmaxim.ai/docs/sdk/python/references/models/prompt): Detailed reference for Prompt utilities and type definitions in Maxim SDK.
- [Latest Blog Posts](https://www.getmaxim.ai/blog/page/14): A collection of recent blog posts on AI advancements and evaluations.
- [Custom Evaluators - Human Evaluators](https://getmaxim.ai/docs/library/how-to/evaluators/create-human-evaluators): Documentation on creating and configuring human evaluators for AI output quality control.
- [Bedrock Utils](https://www.getmaxim.ai/docs/sdk/python/references/logger/bedrock/utils): Utility functions for Bedrock integration in Maxim AI SDK.
- [Scheduled Runs - Maxim Docs](https://www.getmaxim.ai/docs/offline-evals/via-ui/advanced/scheduled-runs): Learn how to schedule test runs for prompts, agents, and workflows at regular intervals.
- [Get Trace by ID](https://www.getmaxim.ai/docs/log%20repositories/log-repository/get-trace-by-id): API documentation for retrieving a specific trace by its unique ID.
- [Research Paper](https://www.getmaxim.ai/blog/tag/research-paper): Explore blog posts discussing research papers related to AI and language models.
- [Get Integrations](https://www.getmaxim.ai/docs/integrations/integration/get-integrations): API documentation for retrieving integrations in a workspace using Maxim.
- [Tracing Overview](https://www.getmaxim.ai/docs/tracing/overview): Introduction to Maxim's enterprise-grade LLM observability platform for AI applications.
- [HTTP Agent CI/CD Integration](https://www.getmaxim.ai/docs/offline-evals/via-sdk/agent-http/ci-cd-integration): Integrate HTTP endpoint evaluations into your CI/CD pipeline using GitHub Actions.
- [Run Prompt Version](https://www.getmaxim.ai/docs/prompts/prompt-version/run-prompt-version): Documentation on running a specific version of a prompt using Maxim's API.
- [Vercel Integration](https://www.getmaxim.ai/docs/sdk/typescript/integrations/vercel/vercel): Guide on integrating Maxim observability with the Vercel AI SDK.
- [Tracing via SDK - Attachments](https://www.getmaxim.ai/docs/tracing/tracing-via-sdk/attachments): Learn how to attach files and URLs to traces and spans for richer observability in Maxim.
- [Add New Entries to Datasets Using SDK](https://www.getmaxim.ai/docs/library/how-to/datasets/add-new-entries-using-sdk): Guide to adding entries to datasets via Maxim SDK.
- [Anthropic Client](https://www.getmaxim.ai/docs/sdk/python/references/logger/anthropic/client): Documentation for the Maxim Anthropic client wrapper for logging and monitoring API interactions.
- [Platform Engineer Job Opening](https://www.getmaxim.ai/jobs/platform-engineer): Job description for the Platform Engineer role at Maxim AI.
- [Create a Prompt Version](https://www.getmaxim.ai/docs/prompts/prompt-version/create-a-prompt-version): Guide on creating a new version of a prompt in Maxim.
- [Head of Engineering Job Opening](https://www.getmaxim.ai/jobs/head-of-engineering): Job listing for the Head of Engineering role at Maxim AI.
- [Reddit Blog Tag](https://www.getmaxim.ai/blog/tag/reddit): Blog posts tagged with Reddit, focusing on insights and applications using Reddit data.
- [Self-Hosting Overview](https://www.getmaxim.ai/docs/self-hosting/overview): Overview of Maxim's self-hosting options for enterprise deployment.
- [LiteLLM SDK Integration](https://www.getmaxim.ai/docs/sdk/python/integrations/litellm/litellm-sdk): Learn how to integrate Maxim SDK with LiteLLM for tracing and monitoring.
- [Logger Writer](https://www.getmaxim.ai/docs/sdk/python/references/logger/writer): Utilities for logging and tracking AI model interactions.
- [Latest Blog Posts](https://www.getmaxim.ai/blog/posts/page/10): A collection of recent blog posts covering topics like AI evaluations, RAG performance, and red-teaming.
- [Library Concepts](https://www.getmaxim.ai/docs/library/concepts): Explore key concepts in AI evaluation, including evaluators, datasets, and tools for assessing model performance.
- [Update Dataset](https://www.getmaxim.ai/docs/datasets/dataset/update-dataset): Documentation page detailing the API endpoint for updating datasets in Maxim.
- [LangChain Integration](https://www.getmaxim.ai/docs/sdk/python/integrations/langchain/langchain): Guide on integrating LangChain with Maxim observability for LLM applications.
- [Export Logs and Evaluation Data](https://www.getmaxim.ai/docs/observe/how-to/log-your-application/export-logs): Learn how to export logs and evaluation data in Maxim.
- [Prompt Tool Calls](https://www.getmaxim.ai/docs/offline-evals/via-ui/prompts/tool-calls): Guide on ensuring accurate tool calls for building reliable AI workflows.
- [Create Alert](https://www.getmaxim.ai/docs/alerts/alert/create-alert): Documentation on creating alerts for monitoring AI workflows.
- [Using Pre-Built Evaluators](https://getmaxim.ai/docs/library/how-to/evaluators/use-pre-built-evaluators): Guide to using pre-built evaluators for AI evaluation scenarios in Maxim.
- [Tracing via SDK: Generations](https://www.getmaxim.ai/docs/tracing/tracing-via-sdk/generations): Log individual calls to LLMs using Maxim's SDK.
- [Test Test Runs](https://www.getmaxim.ai/docs/sdk/python/references/tests/test_test_runs): Documentation for testing the Test Runs functionality in Python SDK.
- [Guide: Create a Product Description Generator](https://www.getmaxim.ai/docs/offline-evals/guides/create-product-description-generator): Step-by-step guide to building an AI workflow for generating product descriptions.
- [Vault](https://www.getmaxim.ai/docs/settings/vault): Learn how to securely store sensitive information using Maxim's Vault feature.
- [Tracing via SDK - Traces](https://www.getmaxim.ai/docs/tracing/tracing-via-sdk/traces): Guide to setting up tracing for AI applications using Maxim SDK.
- [Request Access to Maxim AI](https://www.getmaxim.ai/request-access): A landing page to request access to Maxim AI with a 14-day free trial.
- [Offline Evaluation Overview](https://www.getmaxim.ai/docs/evaluate/overview): Guide to evaluating AI application performance through prompt testing, workflow automation, and log monitoring.
- [Maxim Blog - Page 2](https://www.getmaxim.ai/blog/posts/page/2): Collection of blog posts on AI development, tools, and use cases.
- [Attachments](https://www.getmaxim.ai/docs/observe/how-to/log-your-application/add-attachments): Learn how to attach files and URLs to traces and spans for enhanced observability.
- [Custom Evaluators](https://www.getmaxim.ai/docs/library/evaluators/custom-evaluators): Create and configure custom evaluators for specific evaluation needs.
- [Trace Decorator Reference](https://www.getmaxim.ai/docs/sdk/python/references/decorators/trace): Documentation for the Trace decorator in the Maxim Python SDK.
- [Scheduled Test Runs](https://www.getmaxim.ai/docs/evaluate/how-to/scheduled-test-runs): Learn how to schedule test runs for prompts, agents, and workflows.
- [Livekit Store](https://www.getmaxim.ai/docs/sdk/python/references/logger/livekit/store): Store utilities for livekit real-time communication integration.
- [LiteLLM Proxy One-Line Integration](https://www.getmaxim.ai/docs/sdk/python/integrations/litellm/litellm-proxy): Learn how to integrate Maxim with LiteLLM Proxy in one line of configuration.
- [bedrock.AsyncClient](https://www.getmaxim.ai/docs/sdk/python/references/logger/bedrock/async_client): Async client utilities for AWS Bedrock integration with Maxim's logging capabilities.
- [Decorators ToolCall](https://www.getmaxim.ai/docs/sdk/python/references/decorators/tool_call): Utilities for automatic logging and instrumentation of functions.
- [Retrieval Class](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/classes/Retrieval): Technical documentation for the Retrieval class in Maxim's TypeScript SDK.
- [Third Party Evaluators](https://www.getmaxim.ai/docs/library/evaluators/third-party-evaluators): Comprehensive guide to third-party evaluation metrics supported by Maxim.
- [Tracing Retrieval](https://www.getmaxim.ai/docs/tracing/tracing-via-sdk/retrieval): Documentation on logging retrievals in AI applications using Maxim SDK.
- [Set Up Alerts and Notifications](https://www.getmaxim.ai/docs/observe/how-to/set-up-alerts/create-a-slack-integration): Guide to configuring Slack and PagerDuty integrations for AI application alerts.
- [Simulation Overview](https://www.getmaxim.ai/docs/simulations/overview): Overview of simulations for testing AI conversations in Maxim.
- [HTTP Agent Evals](https://www.getmaxim.ai/docs/offline-evals/via-ui/agents-via-http-endpoint/agent-evals): Guide to testing and evaluating AI endpoints via HTTP for multi-turn conversations.
- [Model Configuration](https://www.getmaxim.ai/docs/settings/model-configuration): Learn how to configure models in Maxim.
- [LogWriter Class Reference](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/classes/LogWriter): Documentation for the LogWriter class in the Maxim TypeScript SDK.
- [Create a PagerDuty Integration](https://www.getmaxim.ai/docs/integrations/create-a-pagerduty-integration): Steps to integrate PagerDuty for AI application alerts.
- [Folders and Tags for Prompts](https://www.getmaxim.ai/docs/offline-evals/via-ui/prompts/folders-and-tags): Organize and manage AI prompts using folders, tags, and versioning in Maxim.
- [Tracing via SDK: Sessions](https://www.getmaxim.ai/docs/tracing/tracing-via-sdk/sessions): Learn how to group related traces into sessions for tracking user interactions.
- [ToolCall Class Reference](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/classes/ToolCall): Technical documentation for the ToolCall class in Maxim's TypeScript SDK.
- [TestRun Utilities for Maxim SDK](https://www.getmaxim.ai/docs/sdk/python/references/models/test_run): Reference documentation for TestRun utilities in Maxim SDK.
- [MCP (Model Context Protocol)](https://www.getmaxim.ai/docs/offline-evals/via-ui/prompts/mcp): Learn how to use MCP to test your prompts with external tools.
- [PromptChain Model Documentation](https://www.getmaxim.ai/docs/sdk/python/references/models/prompt_chain): Reference for PromptChain utilities in Maxim's Python SDK.
- [Logprobs Interface in Maxim SDK](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/interfaces/Logprobs): Reference for the Logprobs interface in the Maxim TypeScript SDK.
- [Scripts - Agents via HTTP Endpoint](https://www.getmaxim.ai/docs/offline-evals/via-ui/agents-via-http-endpoint/scripts): Guide to customizing API requests and responses using Maxim Workflow scripts.
- [Filter Objects in Python SDK](https://www.getmaxim.ai/docs/sdk/python/references/filter_objects): Technical reference for the Filter Objects module in Maxim's Python SDK.
- [Anthropic SDK](https://www.getmaxim.ai/docs/sdk/python/integrations/anthropic/anthropic): Guide to integrating Maxim observability with the Anthropic SDK.
- [Prompt Testing Quickstart](https://www.getmaxim.ai/docs/offline-evals/via-ui/prompts/quickstart): Quickstart guide for testing prompts using datasets and evaluators.
- [Anthropic Message Utilities](https://www.getmaxim.ai/docs/sdk/python/references/logger/anthropic/message): Documentation for Anthropic message utilities integrated with Maxim logging.
- [TypeScript SDK Core Overview - Maxim Docs](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/overview): Comprehensive reference for the TypeScript SDK core features.
- [Share Test Run Report - Maxim Docs](https://www.getmaxim.ai/docs/test%20run%20reports/test-run-report/share-test-run-report): Documentation on sharing test run reports via API in Maxim.
- [Get Folders](https://www.getmaxim.ai/docs/folders/folder/get-folders): API documentation for retrieving folder details in Maxim.
- [Instrumenter](https://www.getmaxim.ai/docs/sdk/python/references/logger/livekit/instrumenter): Utilities for logging instrumentation in LiveKit real-time communication.
- [Metadata](https://www.getmaxim.ai/docs/sdk/python/references/models/metadata): Documentation for metadata utilities in Maxim SDK Python models.
- [Organize Prompts with Folders and Tags](https://www.getmaxim.ai/docs/evaluate/how-to/evaluate-prompts/organize-prompts): Guidelines for organizing AI prompts using folders, tags, and versioning in Maxim.
- [Events](https://www.getmaxim.ai/docs/tracing/tracing-via-sdk/events): Track application milestones and state changes using event logging.
- [Spans](https://www.getmaxim.ai/docs/tracing/tracing-via-sdk/spans): Organize and track requests across microservices within traces.
- [gemini.AsyncClient](https://www.getmaxim.ai/docs/sdk/python/references/logger/gemini/async_client): Documentation for the Gemini AsyncClient utilities in Python SDK.
- [Pratham Mishra](https://www.getmaxim.ai/blog/author/pratham): Author profile page featuring articles and insights by Pratham Mishra.
- [Bedrock Client](https://www.getmaxim.ai/docs/sdk/python/references/logger/bedrock/client): Python reference for Bedrock client integration with Maxim logging.
- [MaximLangchainTracer](https://www.getmaxim.ai/docs/sdk/typescript/reference/langchain/classes/MaximLangchainTracer): LangChain callback handler for automatic observability with the Maxim platform.
- [Privacy Policy](https://www.getmaxim.ai/privacy-policy): Details Maxim's policies on data collection, usage, and user rights.
- [Export Logs and Evaluation Data](https://www.getmaxim.ai/docs/tracing/exports): Learn how to export logs and evaluation data in Maxim.
- [Blog Posts Page 12](https://www.getmaxim.ai/blog/posts/page/12): A collection of blog posts covering various topics related to LLMs and AI advancements.
- [Inmemory Cache](https://www.getmaxim.ai/docs/sdk/python/references/cache/inMemory): Documentation for in-memory caching utilities to optimize performance in Maxim SDK.
- [Python SDK Logger Components - Base](https://www.getmaxim.ai/docs/sdk/python/references/logger/components/base): Technical documentation for the Base functionality in Maxim's Python SDK Logger components.
- [litellm.Tracer](https://www.getmaxim.ai/docs/sdk/python/references/logger/litellm/tracer): Tracing and instrumentation utilities for Litellm integration in Python SDK.
- [Trace Class in TypeScript SDK](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/classes/Trace): Detailed documentation of the Trace class for capturing execution flows.
- [Logger Components: Generation](https://www.getmaxim.ai/docs/sdk/python/references/logger/components/generation): Documentation for the Generation component in Maxim's Python SDK Logger.
- [Dhwanil Pithva - Founding Engineer @ Maxim AI](https://www.getmaxim.ai/blog/author/dhwanil): Profile of Dhwanil Pithva, a founding engineer at Maxim AI.
- [LiveKit SDK Integration](https://www.getmaxim.ai/docs/sdk/python/integrations/livekit/livekit): Guide to integrating Maxim observability with LiveKit for real-time voice AI applications.
- [Update Dataset Split](https://www.getmaxim.ai/docs/datasets/dataset-split/update-dataset-split): API documentation for updating dataset splits in Maxim.
- [Delete Dataset](https://www.getmaxim.ai/docs/datasets/dataset/delete-dataset): API documentation for deleting datasets in Maxim.
- [VariableType Enumeration](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/enumerations/VariableType): Defines supported variable types for dataset entries in Maxim SDK.
- [OSS Friends](https://www.getmaxim.ai/bifrost/oss-friends): A showcase of open-source projects aligned with Maxim AI's mission.
- [Endpoint on Maxim](https://www.getmaxim.ai/docs/offline-evals/via-sdk/agent-http/endpoint-on-maxim): Learn how to test AI agents using workflows stored on the Maxim platform via the Maxim SDK.
- [Aniruddha Chattopadhyay](https://www.getmaxim.ai/blog/author/aniruddha): Author profile featuring blog posts and insights by Aniruddha Chattopadhyay.
- [MaximLogger Reference](https://www.getmaxim.ai/docs/sdk/typescript/reference/langchain/classes/core/classes/MaximLogger): Documentation for the MaximLogger class in the LangChain SDK for TypeScript.
- [Error Debugging](https://www.getmaxim.ai/docs/offline-evals/via-ui/agents-via-no-code-builder/error-debugging): Identify and fix errors in AI workflows with detailed diagnostics.
- [Search Logs in a Log Repository](https://www.getmaxim.ai/docs/log%20repositories/log-repository/search-logs-in-a-log-repository): Documentation for searching logs in a log repository using Maxim's API.
- [Local Prompt Testing](https://www.getmaxim.ai/docs/offline-evals/via-sdk/prompts/local-prompt): Guide on testing locally defined prompts using the Maxim SDK.
- [Get Dataset Columns](https://www.getmaxim.ai/docs/datasets/dataset-column/get-dataset-columns): API documentation for retrieving dataset columns in Maxim.
- [Latest Blog Posts](https://www.getmaxim.ai/blog/posts/page/14): Overview of recent blog posts on advancements in LLM evaluation and domain-specific RAG.
- [Setting Up Workspace](https://www.getmaxim.ai/docs/introduction/quickstart/setting-up-workspace): Quickstart guide for setting up a workspace in Maxim's platform.
- [Error Class](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/classes/Error): Documentation for the Error class in the Maxim TypeScript SDK.
- [CompletionRequest Interface Documentation](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/interfaces/CompletionRequest): Technical documentation for the CompletionRequest interface in Maxim's TypeScript SDK.
- [Create Dataset Split](https://www.getmaxim.ai/docs/datasets/dataset-split/create-dataset-split): Guide to creating dataset splits using Maxim's API.
- [ToolCallError Interface](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/interfaces/ToolCallError): Defines error information for failed tool call executions in TypeScript SDK.
- [Local Endpoint Testing](https://www.getmaxim.ai/docs/offline-evals/via-sdk/agent-http/local-endpoint): Guide on testing AI agents running on local endpoints using the Maxim SDK.
- [Node Level Evaluation](https://www.getmaxim.ai/docs/observe/how-to/evaluate-logs/node-level-evaluation): Guide to evaluating components of traces or logs for AI agent performance.
- [Python SDK Reference: decorators.Span](https://www.getmaxim.ai/docs/sdk/python/references/decorators/span): Documentation for the Span decorator in Maxim's Python SDK.
- [Manav Singhal](https://www.getmaxim.ai/blog/author/manav): Author page featuring Manav Singhal's AI-related blog posts.
- [No-Code Agent Evals](https://www.getmaxim.ai/docs/offline-evals/via-ui/agents-via-no-code-builder/agent-evals): Guide to testing agents using datasets and evaluators in Maxim's no-code builder.
- [Set Up Alerts and Notifications](https://www.getmaxim.ai/docs/_sites/maximai/online-evals/set-up-alerts-and-notifications): Learn how to configure alerts and notifications for monitoring AI application performance.
- [Schedule a Demo](https://www.getmaxim.ai/schedule): Page to schedule a demo and see Maxim AI in action.
- [Automate Prompt Evaluation via CI/CD](https://www.getmaxim.ai/docs/evaluate/how-to/evaluate-prompts/automate-via-ci-cd): Learn how to automate prompt evaluation workflows using CI/CD pipelines.
- [Test Connection Retry Logic](https://www.getmaxim.ai/docs/sdk/python/references/tests/test_connection_retry_logic): Documentation for testing connection retry logic in Maxim's Python SDK.
- [Get Log Repositories](https://www.getmaxim.ai/docs/log%20repositories/log-repository/get-log-repositories): Documentation on retrieving log repositories via API.
- [Customized Reports](https://www.getmaxim.ai/docs/evaluate/how-to/optimize-evaluation-processes/customize-share-reports): Guide on customizing AI evaluation reports for better insights and decision-making.
- [Create Prompt](https://www.getmaxim.ai/docs/prompts/prompt/create-prompt): Instructions for creating a new prompt in Maxim AI.
- [Manage Datasets](https://www.getmaxim.ai/docs/library/datasets/manage-datasets): Learn how to manage datasets effectively using splits and variable columns.
- [Maxim Python SDK](https://www.getmaxim.ai/docs/sdk/python/references/maxim): Core functionality and reference for Maxim's Python SDK.
- [Mistral SDK](https://www.getmaxim.ai/docs/sdk/python/integrations/mistral/mistral): Learn how to integrate Maxim observability with the Mistral SDK.
- [AsyncCompletions for OpenAI Integration](https://www.getmaxim.ai/docs/sdk/python/references/logger/openai/async_completions): Documentation for AsyncCompletions utilities in Maxim's Python SDK.
- [Customized Reports Documentation](https://www.getmaxim.ai/docs/offline-evals/via-ui/advanced/customized-reports): Guide to customizing evaluation reports in Maxim's offline evaluation UI.
- [QueryBuilder Class Documentation](https://www.getmaxim.ai/docs/sdk/python/references/models/query_builder): Documentation for the QueryBuilder class in the Maxim Python SDK.
- [BaseContainer - TypeScript SDK](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/classes/BaseContainer): Abstract base class for logging containers in Maxim's TypeScript SDK.
- [Anthropic Utils](https://www.getmaxim.ai/docs/sdk/python/references/logger/anthropic/utils): Utility functions for Anthropic API integration with Maxim logging.
- [Use Local Datasets](https://www.getmaxim.ai/docs/library/datasets/use-local-datasets): Guide to adding new entries to datasets using the Maxim SDK.
- [Chat](https://www.getmaxim.ai/docs/sdk/python/references/logger/openai/chat): Documentation for OpenAI Chat utilities in Python SDK.
- [Logger](https://www.getmaxim.ai/docs/sdk/python/references/logger/logger): Comprehensive Python reference for Maxim's Logger utilities.
- [Deploy Prompt Version](https://www.getmaxim.ai/docs/prompts/prompt-deployment/deploy-prompt-version): API documentation for deploying a specific prompt version in Maxim.
- [Prompt Retrieval Testing](https://www.getmaxim.ai/docs/offline-evals/via-ui/prompts/retrieval): Instructions for testing and evaluating retrieval quality in AI applications.
- [Delete a Log Repository](https://www.getmaxim.ai/docs/log%20repositories/log-repository/delete-a-log-repository): API documentation for deleting a log repository in Maxim.
- [Comparison Reports](https://www.getmaxim.ai/docs/analyze/how-to/comparison-reports): Guide on creating and analyzing test run comparison reports.
- [ChatCompletionChoice Interface](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/interfaces/ChatCompletionChoice): Documentation for the ChatCompletionChoice interface in the Maxim TypeScript SDK.
- [langchain.Tracer](https://www.getmaxim.ai/docs/sdk/python/references/logger/langchain/tracer): Tracing and instrumentation utilities for Langchain integration.
- [Presets](https://www.getmaxim.ai/docs/offline-evals/via-ui/advanced/presets): Documentation on creating and using test presets in Maxim’s evaluation platform.
- [Maxim APIs Reference](https://www.getmaxim.ai/docs/sdk/python/references/apis/maxim_apis): Comprehensive reference for Python SDK's Maxim APIs.
- [Context Sources](https://www.getmaxim.ai/docs/library/context-sources): Learn how to create, use, and evaluate context sources for AI applications.
- [decorators.Generation](https://www.getmaxim.ai/docs/sdk/python/references/decorators/generation): Generation utilities for decorators for automatic logging and instrumentation.
- [Delete Dataset Split](https://www.getmaxim.ai/docs/datasets/dataset-split/delete-dataset-split): Documentation on deleting dataset splits via API in Maxim.
- [TestMaximCoreSimple](https://www.getmaxim.ai/docs/sdk/python/references/tests/test_maxim_core_simple): Test Maxim Core Simple functionality for SDK integrations.
- [StreamManager](https://www.getmaxim.ai/docs/sdk/python/references/logger/anthropic/stream_manager): Stream_Manager utilities for Anthropic AI model integration and logging.
- [Cache](https://www.getmaxim.ai/docs/sdk/python/references/cache/cache): Cache utilities for optimizing performance in Python SDK.
- [Terms of Service](https://www.getmaxim.ai/terms-of-service): Legal terms governing the use of Maxim's platform and services.
- [Dataset Evaluation](https://getmaxim.ai/docs/evaluate/how-to/evaluate-datasets): Guide on evaluating AI outputs against expected results using Maxim's dataset evaluation tools.
- [portkey.Client](https://www.getmaxim.ai/docs/sdk/python/references/logger/portkey/client): Portkey client implementation for API interactions and model integration.
- [MaximCache Interface](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/interfaces/MaximCache): Defines the contract for cache implementations used by the Maxim SDK.
- [Agent via No-Code Builder: Types of Nodes](https://www.getmaxim.ai/docs/offline-evals/via-ui/agents-via-no-code-builder/types-of-nodes): Guide on configuring API nodes for integrating external services in AI workflows.
- [Two-Factor Authentication](https://www.getmaxim.ai/docs/settings/two-factor-authentication): Instructions for enabling two-factor authentication in Maxim.
- [Span Class Documentation](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/classes/Span): Detailed reference for the Span class in Maxim's TypeScript SDK.
- [Session Class Documentation](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/classes/Session): Detailed documentation for the Session class in the Maxim TypeScript SDK.
- [CommitLog Class Documentation](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/classes/CommitLog): Detailed documentation for the CommitLog class in the Maxim SDK.
- [TestPortkey - Python SDK](https://www.getmaxim.ai/docs/sdk/python/references/tests/test_portkey): Documentation for testing Portkey functionality in Maxim's Python SDK.
- [mistral.Utils](https://www.getmaxim.ai/docs/sdk/python/references/logger/mistral/utils): Utility functions and helpers for Mistral integration.
- [Test Runs Comparison Dashboard](https://www.getmaxim.ai/docs/dashboards/test-runs-comparison-dashboard): Guide on creating and understanding test runs comparison dashboards.
- [Handler](https://www.getmaxim.ai/docs/sdk/python/references/logger/livekit/openai/realtime/handler): Documentation for the Handler functionality in Realtime integration.
- [Delete Dataset Entries - Maxim Docs](https://www.getmaxim.ai/docs/datasets/dataset-entry/delete-dataset-entries): API documentation for deleting dataset entries in Maxim.
- [Get Folder Contents - Maxim Docs](https://www.getmaxim.ai/docs/folders/folder-contents/get-folder-contents): API documentation for retrieving contents of a specific folder in Maxim.
- [Notifications](https://www.getmaxim.ai/docs/offline-evals/via-ui/advanced/notifications): Guide to setting up notifications for test run statuses via Slack and PagerDuty integrations.
- [Update Dataset Columns](https://www.getmaxim.ai/docs/datasets/dataset-column/update-dataset-columns): API documentation for updating dataset columns in Maxim.
- [AgentSession](https://www.getmaxim.ai/docs/sdk/python/references/logger/livekit/agent_session): Utilities for livekit real-time communication integration.
- [Evaluator](https://www.getmaxim.ai/docs/sdk/python/references/models/evaluator): Utilities for data models and type definitions used in the Maxim SDK.
- [Entity](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/enumerations/Entity): Enumeration of entity types supported by the Maxim logging system.
- [GenerationParser](https://www.getmaxim.ai/docs/sdk/python/references/logger/parsers/generation_parser): Technical documentation for the GenerationParser module in Maxim's Python SDK.
- [Create a New Log Repository](https://www.getmaxim.ai/docs/log%20repositories/log-repository/create-a-new-log-repository): API guide for creating a new log repository in Maxim.
- [Usage Interface](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/interfaces/Usage): Defines token usage statistics for a generation request in Maxim.
- [components.Trace](https://www.getmaxim.ai/docs/sdk/python/references/logger/components/trace): Trace functionality for Components integration in Maxim SDK.
- [Create a Slack Integration](https://www.getmaxim.ai/docs/integrations/create-a-slack-integration): Step-by-step guide to integrating Slack with Maxim for performance notifications.
- [Get Datasets API Documentation](https://www.getmaxim.ai/docs/datasets/dataset/get-datasets): API documentation for retrieving datasets or specific dataset details in Maxim's platform.
- [TestAnthropic](https://www.getmaxim.ai/docs/sdk/python/references/tests/test_anthropic): Documentation for testing Anthropic functionality in the Maxim SDK.
- [ToolCallFunction Interface](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/interfaces/ToolCallFunction): Documentation for the ToolCallFunction interface in Maxim's TypeScript SDK.
- [Generation Class Reference](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/classes/Generation): Technical documentation for the Generation class in Maxim's TypeScript SDK.
- [Logger Components: Span](https://www.getmaxim.ai/docs/sdk/python/references/logger/components/span): Documentation for the Span component in Maxim's Python SDK Logger.
- [EventEmittingBaseContainer](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/classes/EventEmittingBaseContainer): Documentation for the EventEmittingBaseContainer class in the Maxim TypeScript SDK.
- [Gemini Utils Documentation](https://www.getmaxim.ai/docs/sdk/python/references/logger/gemini/utils): Technical documentation for utility functions in Gemini integration.
- [Log Multi-Turn Interactions as Session](https://www.getmaxim.ai/docs/observe/how-to/log-your-application/log-multiturn-interactions-as-session): Learn how to group related traces into sessions for tracking user interactions.
- [Folder Utilities in Maxim SDK](https://www.getmaxim.ai/docs/sdk/python/references/models/folder): Documentation on folder utilities and type definitions in Maxim SDK.
- [Agent Blog Tag](https://www.getmaxim.ai/blog/tag/agent): Blog posts related to building and evaluating AI agents.
- [Update Alert](https://www.getmaxim.ai/docs/alerts/alert/update-alert): API documentation for updating alerts in the Maxim platform.
- [Utsav Khandelwal - Author Page](https://www.getmaxim.ai/blog/author/utsav): Author page for Utsav Khandelwal featuring his blog posts on Maxim AI.
- [Create Folder](https://www.getmaxim.ai/docs/folders/folder/create-folder): Guide to creating folders for organizing entities in Maxim.
- [Expiring Key Value Store](https://www.getmaxim.ai/docs/sdk/python/references/expiring_key_value_store): Documentation for the Expiring Key Value Store module in Maxim's Python SDK.
- [TagsParser](https://www.getmaxim.ai/docs/sdk/python/references/logger/parsers/tags_parser): Documentation for the Tags Parser functionality in the Maxim SDK.
- [Update Integration](https://www.getmaxim.ai/docs/integrations/integration/update-integration): Documentation for updating integrations via API in Maxim.
- [Session - Maxim SDK Python Logger Components](https://www.getmaxim.ai/docs/sdk/python/references/logger/components/session): Documentation for the Session component in Maxim's Python SDK Logger.
- [logger.Utils](https://www.getmaxim.ai/docs/sdk/python/references/logger/utils): Utility functions and helpers for Logger integration.
- [EvaluatableBaseContainer](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/classes/EvaluatableBaseContainer): Documentation for the EvaluatableBaseContainer class in the Maxim SDK.
- [Update Dataset Entries](https://www.getmaxim.ai/docs/datasets/dataset-entry/update-dataset-entries): Documentation on updating dataset entries via Maxim API.
- [API Reference: Delete Test Runs](https://www.getmaxim.ai/docs/test%20runs/test-run/delete-test-runs): API documentation for deleting test runs in Maxim.
- [HTTP Endpoint Quickstart](https://www.getmaxim.ai/docs/offline-evals/via-ui/agents-via-http-endpoint/quickstart): Guide for testing AI applications via HTTP endpoints.
- [Scribe](https://www.getmaxim.ai/docs/sdk/python/references/scribe): Documentation for the Scribe module utilities and functionality in Maxim's Python SDK.
- [Maxim Docs Overview](https://getmaxim.ai/docs/llms.txt): Comprehensive list of documentation links for Maxim's features and integrations.
- [Modules - TypeScript SDK Reference](https://www.getmaxim.ai/docs/sdk/typescript/reference/modules): Detailed reference for modules in the TypeScript SDK of Maxim AI.
- [Errors - Tracing via SDK](https://www.getmaxim.ai/docs/tracing/tracing-via-sdk/errors): Learn how to track and log errors in AI application traces for improved performance and reliability.
- [Maxim API Keys](https://www.getmaxim.ai/docs/settings/maxim-api-keys): Guide to creating and managing Maxim API keys for authentication.
- [Evaluators Utils](https://www.getmaxim.ai/docs/sdk/python/references/evaluators/utils): Utility functions for Evaluators integration in Python SDK.
- [Delete Alert](https://www.getmaxim.ai/docs/alerts/alert/delete-alert): API documentation for deleting alerts in Maxim AI.
- [Delete Integration](https://www.getmaxim.ai/docs/integrations/integration/delete-integration): Documentation for deleting integrations via Maxim API.
- [Delete Dataset Columns](https://www.getmaxim.ai/docs/datasets/dataset-column/delete-dataset-columns): Documentation on deleting dataset columns via Maxim's API.
- [Get Prompt Config](https://www.getmaxim.ai/docs/prompts/prompt-config/get-prompt-config): API documentation for retrieving prompt configurations in Maxim.
- [Container](https://www.getmaxim.ai/docs/sdk/python/references/logger/models/container): Container utilities for data models and type definitions used throughout the Maxim SDK.
- [BaseEvaluator](https://www.getmaxim.ai/docs/sdk/python/references/evaluators/base_evaluator): Reference documentation for BaseEvaluator in Maxim's Python SDK.
- [RealtimeSession](https://www.getmaxim.ai/docs/sdk/python/references/logger/livekit/realtime_session): Realtime_Session utilities for LiveKit real-time communication integration.
- [OpenAI Utils](https://www.getmaxim.ai/docs/sdk/python/references/logger/openai/utils): Utility functions and helpers for OpenAI integration in Maxim's Python SDK Logger.
- [ToolCallConfig](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/interfaces/ToolCallConfig): Configuration object for tool call in the Maxim SDK.
- [ChatCompletionToolCall Interface](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/interfaces/ChatCompletionToolCall): Defines properties for tool calls in chat completions within the Maxim SDK.
- [Retrieval Component Documentation](https://www.getmaxim.ai/docs/sdk/python/references/logger/components/retrieval): Documentation for the Retrieval component in the Maxim Python SDK.
- [AsyncChat Utilities](https://www.getmaxim.ai/docs/sdk/python/references/logger/openai/async_chat): AsyncChat utilities for OpenAI model integration and logging.
- [GenerationError Interface Documentation](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/interfaces/GenerationError): Documentation for the GenerationError interface in the Maxim SDK.
- [Get Test Runs](https://www.getmaxim.ai/docs/test%20runs/test-run/get-test-runs): API documentation for retrieving test runs in a workspace.
- [Upgrading to v3](https://www.getmaxim.ai/docs/sdk/python/upgrading-to-v3): Details on changes introduced in Maxim SDK v3 for Python.
- [TestRunLogger](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/interfaces/TestRunLogger): Interface for capturing test run execution events and progress.
- [ChatCompletionResult](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/interfaces/ChatCompletionResult): Interface representing the result of an LLM chat completion.
- [models.Dataset](https://www.getmaxim.ai/docs/sdk/python/references/models/dataset): Dataset utilities for data models and type definitions in Maxim SDK.
- [Test Runs Comparison Dashboard](https://www.getmaxim.ai/docs/analyze/overview): Guide to creating and analyzing comparison dashboards for test runs in Maxim.
- [Update Prompt](https://www.getmaxim.ai/docs/prompts/prompt/update-prompt): API documentation for updating an existing prompt in Maxim.
- [Create Dataset API Documentation](https://www.getmaxim.ai/docs/datasets/dataset/create-dataset): API documentation for creating datasets in Maxim AI.
- [EvaluateContainer Class](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/classes/EvaluateContainer): Documentation on the EvaluateContainer class for configuring evaluations in Maxim SDK.
- [test_runs.Utils](https://www.getmaxim.ai/docs/sdk/python/references/test_runs/utils): Utility functions for Test_Runs integration in the Maxim SDK.
- [Variables in Agents - Maxim No-Code Builder](https://www.getmaxim.ai/docs/offline-evals/via-ui/agents-via-no-code-builder/variables-in-agents): Guide on using variables in agents built with Maxim's no-code builder.
- [Tags](https://www.getmaxim.ai/docs/tracing/tracing-via-sdk/tags): Guide to tagging traces for effective data grouping and filtering.
- [Custom Pricing](https://www.getmaxim.ai/docs/settings/custom-pricing): Documentation for setting up custom token pricing in Maxim.
- [GeminiRealtimeSession](https://www.getmaxim.ai/docs/sdk/python/references/logger/livekit/gemini/gemini_realtime_session): Utilities for Google Gemini model integration and logging in Maxim's Python SDK.
- [Create Dataset Columns](https://www.getmaxim.ai/docs/datasets/dataset-column/create-dataset-columns): Guide for creating dataset columns using Maxim API.
- [TextCompletionResult](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/interfaces/TextCompletionResult): Represents the result of an LLM text completion.
- [Get Prompts](https://www.getmaxim.ai/docs/prompts/prompt/get-prompts): API documentation for retrieving prompts in a workspace.
- [gemini.Client](https://www.getmaxim.ai/docs/sdk/python/references/logger/gemini/client): Gemini client implementation for API interactions and model integration.
- [Types](https://www.getmaxim.ai/docs/sdk/python/references/logger/components/types): Documentation for the 'Types' functionality in Maxim's Python SDK Logger components.
- [Delete Prompt](https://www.getmaxim.ai/docs/prompts/prompt/delete-prompt): API documentation for deleting a prompt in Maxim.
- [TestLoggerLangchain03x](https://www.getmaxim.ai/docs/sdk/python/references/tests/test_logger_langchain_03x): Documentation for testing Logger Langchain 03X functionality in Python SDK.
- [Dataset Utilities Documentation](https://www.getmaxim.ai/docs/sdk/python/references/dataset/dataset): Documentation for dataset management and manipulation utilities in the Maxim Python SDK.
- [CrewAI Utils](https://www.getmaxim.ai/docs/sdk/python/references/logger/crewai/utils): Utility functions and helpers for Crewai integration.
- [Attachment Components Documentation](https://www.getmaxim.ai/docs/sdk/python/references/logger/components/attachment): Documentation for Attachment components in the Maxim Python SDK.
- [Get Unique Values for a Tag](https://www.getmaxim.ai/docs/log%20repositories/log-repository/get-unique-values-for-a-tag): Documentation for retrieving unique values for a tag in log repositories.
- [ToolCall](https://www.getmaxim.ai/docs/sdk/python/references/logger/components/tool_call): Documentation for ToolCall functionality in Components integration.
- [Error](https://www.getmaxim.ai/docs/sdk/python/references/logger/components/error): Documentation for managing error configurations in Python SDK Logger components.
- [Get Dataset Splits](https://www.getmaxim.ai/docs/datasets/dataset-split/get-dataset-splits): API documentation for retrieving dataset splits in Maxim.
- [Human Annotation](https://www.getmaxim.ai/docs/offline-evals/via-ui/prompts/human-annotation): Guide to integrating human annotation pipelines for AI evaluation.
- [openai.AsyncClient](https://www.getmaxim.ai/docs/sdk/python/references/logger/openai/async_client): Reference for the MaximOpenAIAsyncClient class in Python SDK.
- [livekit.Utils](https://www.getmaxim.ai/docs/sdk/python/references/logger/livekit/utils): Utility functions and helpers for Livekit integration.
- [langchain.Utils](https://www.getmaxim.ai/docs/sdk/python/references/logger/langchain/utils): Utility functions and helpers for Langchain integration.
- [Aryan Kargwal](https://www.getmaxim.ai/blog/author/aryan): Author profile page for Aryan Kargwal, featuring blog posts and insights.
- [LangChain Overview](https://www.getmaxim.ai/docs/sdk/typescript/reference/langchain/overview): Overview of LangChain integration in Maxim SDK for TypeScript.
- [Get Prompt Versions](https://www.getmaxim.ai/docs/prompts/prompt-version/get-prompt-versions): Documentation for retrieving versions of prompts via API.
- [models.Attachment](https://www.getmaxim.ai/docs/sdk/python/references/models/attachment): Attachment utilities for data models and type definitions used throughout the Maxim SDK.
- [Members and Roles - Settings](https://www.getmaxim.ai/docs/settings/members-and-roles): Guide on managing team members and roles in Maxim AI.
- [QueryRuleType Enumeration](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/enumerations/QueryRuleType): Documentation for the QueryRuleType enumeration in Maxim's TypeScript SDK.
- [CSVFile Class Reference](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/classes/CSVFile): Technical reference for the CSVFile class in Maxim's TypeScript SDK.
- [MockWriter for Python SDK Tests](https://www.getmaxim.ai/docs/sdk/python/references/tests/mock_writer): Documentation on MockWriter for testing log functionalities in Maxim's Python SDK.
- [components.Utils](https://www.getmaxim.ai/docs/sdk/python/references/logger/components/utils): Utility functions and helpers for Components integration in Maxim SDK.
- [Feedback - Maxim SDK Python Logger Components](https://www.getmaxim.ai/docs/sdk/python/references/logger/components/feedback): Documentation for Feedback functionality in Maxim SDK Python Logger Components.
- [Update Prompt Config](https://www.getmaxim.ai/docs/prompts/prompt-config/update-prompt-config): API documentation for updating prompt configurations in Maxim's platform.
- [Get Test Run Entries API Documentation](https://www.getmaxim.ai/docs/test%20run%20entries/test-run-entries/get-test-run-entries): API documentation for fetching test run entries in Maxim.
- [TextCompletionChoice Interface](https://www.getmaxim.ai/docs/sdk/typescript/reference/core/interfaces/TextCompletionChoice): Documentation for the TextCompletionChoice interface in TypeScript SDK.
- [Update Log Repository](https://www.getmaxim.ai/docs/log%20repositories/log-repository/update-log-repository): API documentation for updating log repositories in Maxim's platform.
- [Sitemap Documentation](https://www.getmaxim.ai/docs/sitemap.xml): A sitemap listing all documentation pages available on the Maxim platform.