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🦑 TruLens
truera/trulens
🏠 Home
🚀 Getting Started
🚀 Getting Started
📓 Quickstarts
📓 Quickstarts
📓 TruLens Quickstart
📓 TruLens with Outside Logs
📓 LangChain Quickstart
📓 LlamaIndex Quickstart
📓 Text to Text Quickstart
📓 Ground Truth Evaluations
📓 Logging Human Feedback
⭐ Core Concepts
⭐ Core Concepts
☔ Feedback Functions
⟁ RAG Triad
🏆 Honest, Harmless, Helpful Evals
🎈Viewing Results
🎈Viewing Results
Component Guides
Component Guides
Instrumentation
Instrumentation
🦜️🔗 LangChain Integration
🦙 LlamaIndex Integration
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Logging
Logging
❄️ Logging in Snowflake
Logging Methods
🎯 Evaluation
🎯 Evaluation
Anatomy of a Feedback Function
Feedback Implementations
Feedback Implementations
Stock Feedback Functions
📓 Custom Feedback Functions
Feedback Selectors
Feedback Selectors
Selecting Components
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Feedback Aggregation
Feedback Aggregation
Running Feedback Functions
Running Feedback Functions
Running with your app
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Generating Test Cases
Generating Test Cases
📊 Evaluation Benchmarks
📊 Evaluation Benchmarks
📓 Answer Relevance Feedback Evaluation
📓 Comprehensiveness Evaluations
📓 Context Relevance Evaluations
📓 Context Relevance Benchmarking: ranking is all you need.
📓 Groundedness Evaluations
🛡️ Guardrails
🛡️ Guardrails
Other
Other
Moving from TruLens Eval
Uninstalling TruLens
API Reference
API Reference
providers
providers
📦 Snowflake Cortex
📦 Snowflake Cortex
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📦 LangChain
📦 LangChain
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📦 Amazon Bedrock
📦 Amazon Bedrock
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📦 HuggingFace
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📦 OpenAI
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apps
apps
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📦 LlamaIndex
📦 LlamaIndex
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📦 LangChain
📦 LangChain
guardrails
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📦 Nemo Guardrails
📦 Nemo Guardrails
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📦 Snowflake
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🧑🍳 Cookbook
🧑🍳 Cookbook
Frameworks
Frameworks
Canopy
Canopy
TruLens-Canopy Quickstart
Langchain
Langchain
LangChain Agents
LangChain Async
LangChain Ensemble Retriever
Ground Truth Evaluations
LangChain Math Agent
Langchain model comparison
LangChain retrieval agent
Langchain summarize
Llama index
Llama index
Llama index agents
LlamaIndex Async
Advanced Evaluation Methods
Groundtruth evaluation for LlamaIndex applications
LlamaIndex Hybrid Retriever + Reranking + Guardrails
Evaluating Multi-Modal RAG
Query Planning in LlamaIndex
Measuring Retrieval Quality
Nemoguardrails
Nemoguardrails
Feedback functions in NeMo Guardrails apps
Monitoring and Evaluating NeMo Guardrails apps
Openai assistants
Openai assistants
OpenAI Assistants API
Models
Models
Anthropic
Anthropic
Anthropic Quickstart
Claude 3 Quickstart
Azure
Azure
Azure OpenAI LangChain Quickstart
Azure OpenAI Llama Index Quickstart
Bedrock
Bedrock
AWS Bedrock
Deploy, Fine-tune Foundation Models with AWS Sagemaker, Iterate and Monitor with TruEra
Google
Google
Multi-modal LLMs and Multimodal RAG with Gemini
Google Vertex
local and OSS models
local and OSS models
Vectara HHEM Evaluator Quickstart
LiteLLM Quickstart
Local vs Remote Huggingface Feedback Functions
Ollama Quickstart
Snowflake cortex
Snowflake cortex
❄️ Snowflake Arctic Quickstart with Cortex LLM Functions
Use cases
Use cases
Language Verification
Model Comparison
Moderation
PII Detection
❄️ Snowflake with Key-Pair Authentication
Evaluating Summarization with TruLens
Iterate on rag
Iterate on rag
Iterating on LLM Apps with TruLens
Iterating on LLM Apps with TruLens
Iterating on LLM Apps with TruLens
Iterating on LLM Apps with TruLens
Iterating on LLM Apps with TruLens
Vector stores
Vector stores
Faiss
Faiss
LangChain with FAISS Vector DB
Milvus
Milvus
Iterating with RAG on Milvus
Milvus
Mongodb
Mongodb
Atlas quickstart
Pinecone
Pinecone
Pinecone Configuration Choices on Downstream App Performance
Simple Pinecone setup with LlamaIndex + Eval
🤝 Contributing
🤝 Contributing
🧭 Design
✅ Standards
💣 Tech Debt
⛅ Optional Pckages
✨ Database Migration
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