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v2.0
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Documentation
Introduction
Quick Start
Core Concepts
Reference
Contact
Creating a Contact
Using Contact Metrics
Dataset
Creating a Dataset
Creating a Curated Dataset
Deployment
Creating a Deployment
Deployment Versioning
Deployment Routing
Evaluators & Guardrails in Deployments
Deployment Cache
Deployment Security and Privacy
Evaluator
API Call Evaluators
Function Evaluator
LLM-as-a-judge Evaluator
Python Evaluator
Ragas Evaluator
Creating an Evaluator
Creating LLM-as-a-judge Evaluator
Creating API Call Evaluator
Creating JSON Schema Evaluator
Creating a Python Evaluator
Experiment
Creating an Experiment
Using Evaluator in Experiment
Running an Experiment
Exporting an Experiment
Feedback
Adding Feedback to Generations
Making Corrections on a Generation
Feedback Types
Integration
Adding an Integration
Azure OpenAI
Amazon Bedrock
Google Vertex AI
API keys & Endpoints
Knowledge Base
Creating a Knowledge Base
Chunking Strategy
Retrieval Settings
Logs
Metrics Dashboard
Model Garden
Using the Model Garden
Playground
Creating a Playground
Prompt
Creating a Prompt
Model Parameters
Using a Knowledge Base in a Prompt
Using a Tool in a Prompt
Using Image Generation in a Prompt
Using Vision in a Prompt
Using the Prompt Generator
Tool
Creating a Tool
Traces
Webhooks
Creating a Webhook
Webhook Events
Webhook Security & Validation
Webhook Best Practices
Administer
Projects
Context Attributes
Permissions
Using Permissions
Billing & Usage
TUTORIALS
Intent Classification with Orq.ai
Data Extraction from PDF
Creating SQL Queries from Natural Language
Image-Based Receipt Extraction with Orq
Multilingual FAQ Bot Using RAG with Orq.ai
Capturing and Leveraging User Feedback in Orq.ai
Chaining Deployments and Running Evaluations
Learn
LLM Glossary
Model Parameters
Message Roles
Structured Outputs in Orq
Models Prompting Formatting Guidelines
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HTTP Evaluators lets you run custom evaluation on an endpoint of your choice.
