olore-tensorzero-latest

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Local TensorZero documentation reference (latest). TensorZero documentation. Use for LLM gateway configuration, inference API, model provider integrations, optimization (fine-tuning, DICL), experimentation, evaluations, deployment, and observability.

olorehq By olorehq schedule Updated 6/14/2026

name: olore-tensorzero-latest description: Local TensorZero documentation reference (latest). TensorZero documentation. Use for LLM gateway configuration, inference API, model provider integrations, optimization (fine-tuning, DICL), experimentation, evaluations, deployment, and observability.

TensorZero Documentation

TensorZero is an open-source stack for industrial-grade LLM applications that unifies an LLM gateway, observability, optimization, evaluation, and experimentation.

Documentation Structure

contents/
├── gateway/               # LLM gateway API, configuration, and guides (18 files)
├── integrations/
│   └── model-providers/   # Provider integrations: OpenAI, Anthropic, AWS, GCP, etc. (20 files)
├── deployment/            # Deploying gateway, UI, ClickHouse, Postgres, Redis (8 files)
├── operations/            # Auth, rate limits, credentials, metrics, cost tracking (9 files)
├── optimization/          # Fine-tuning (SFT), DICL, GEPA prompt optimization (4 files)
├── evaluations/           # Inference and workflow evaluations (6 files)
├── experimentation/       # A/B tests and experiment namespaces (3 files)
├── observability/         # Querying historical inferences (1 file)
├── index.mdx              # Product overview
├── quickstart.mdx         # Getting started
└── faq.mdx                # FAQ

Topic Guide

Topic Key Files
Getting started / quickstart contents/quickstart.mdx, contents/index.mdx
Gateway configuration reference contents/gateway/configuration-reference.mdx
Inference API (calling LLMs) contents/gateway/api-reference/inference.mdx, contents/gateway/call-any-llm.mdx
OpenAI-compatible API contents/gateway/api-reference/inference-openai-compatible.mdx, contents/gateway/call-the-openai-responses-api.mdx
Functions and variants contents/gateway/configure-functions-and-variants.mdx
Prompt templates contents/gateway/create-a-prompt-template.mdx
Structured outputs contents/gateway/generate-structured-outputs.mdx
Tool / function calling contents/gateway/guides/tool-use.mdx
Embeddings contents/gateway/generate-embeddings.mdx
Batch inference contents/gateway/api-reference/batch-inference.mdx, contents/gateway/guides/batch-inference.mdx
Feedback and metrics contents/gateway/api-reference/feedback.mdx, contents/gateway/guides/metrics-feedback.mdx
Retries and fallbacks contents/gateway/guides/retries-fallbacks.mdx
Inference caching contents/gateway/guides/inference-caching.mdx
Episodes (multi-turn) contents/gateway/guides/episodes.mdx
Datasets and datapoints contents/gateway/api-reference/datasets-datapoints.mdx
Data model contents/gateway/data-model.mdx
Model provider integrations (all) contents/integrations/model-providers/index.mdx
OpenAI, Azure, Anthropic, Gemini contents/integrations/model-providers/openai.mdx, contents/integrations/model-providers/azure.mdx, contents/integrations/model-providers/anthropic.mdx, contents/integrations/model-providers/google-ai-studio-gemini.mdx
AWS (Bedrock, SageMaker) contents/integrations/model-providers/aws-bedrock.mdx, contents/integrations/model-providers/aws-sagemaker.mdx
GCP Vertex AI contents/integrations/model-providers/gcp-vertex-ai-anthropic.mdx, contents/integrations/model-providers/gcp-vertex-ai-gemini.mdx
Self-hosted models (vLLM, TGI, SGLang) contents/integrations/model-providers/vllm.mdx, contents/integrations/model-providers/tgi.mdx, contents/integrations/model-providers/sglang.mdx
OpenAI-compatible providers contents/integrations/model-providers/openai-compatible.mdx
Deployment (gateway, UI) contents/deployment/tensorzero-gateway.mdx, contents/deployment/tensorzero-ui.mdx
Database setup contents/deployment/clickhouse.mdx, contents/deployment/postgres.mdx, contents/deployment/valkey-redis.mdx
Upgrading contents/deployment/upgrade-tensorzero.mdx
Authentication and credentials contents/operations/set-up-auth-for-tensorzero.mdx, contents/operations/manage-credentials.mdx
Rate limits contents/operations/enforce-custom-rate-limits.mdx, contents/operations/centralize-auth-rate-limits-and-more.mdx
Cost and usage tracking contents/operations/track-usage-and-cost.mdx
OpenTelemetry / Prometheus contents/operations/export-opentelemetry-traces.mdx, contents/operations/export-prometheus-metrics.mdx
Extending TensorZero contents/operations/extend-tensorzero.mdx
Optimization overview contents/optimization/index.mdx
Supervised fine-tuning (SFT) contents/optimization/supervised-fine-tuning-sft.mdx
Dynamic in-context learning (DICL) contents/optimization/dynamic-in-context-learning-dicl.mdx
GEPA prompt optimization contents/optimization/gepa.mdx
Evaluations overview contents/evaluations/index.mdx
Inference evaluations contents/evaluations/inference-evaluations/tutorial.mdx, contents/evaluations/inference-evaluations/configuration-reference.mdx
Workflow evaluations contents/evaluations/workflow-evaluations/tutorial.mdx, contents/evaluations/workflow-evaluations/api-reference.mdx
A/B testing contents/experimentation/run-static-ab-tests.mdx, contents/experimentation/run-adaptive-ab-tests.mdx
Querying historical inferences contents/observability/query-historical-inferences.mdx

When to use

Use this skill when the user asks about:

  • Configuring the TensorZero LLM gateway (functions, variants, models, providers, prompt templates)
  • Calling LLMs via the TensorZero inference API or OpenAI-compatible API
  • Integrating with model providers (OpenAI, Anthropic, AWS, GCP, Azure, Groq, Mistral, vLLM, etc.)
  • Collecting feedback and metrics from LLM inferences
  • Deploying TensorZero (gateway, UI, ClickHouse, Postgres, Redis)
  • Managing authentication, credentials, and rate limits
  • Running A/B experiments and adaptive tests
  • Optimizing LLM applications with fine-tuning (SFT), DICL, or GEPA
  • Running evaluations on inference or workflow outputs
  • Tracking usage, cost, and exporting telemetry

How to find information

  1. Use Topic Guide above to identify relevant files
  2. Read TOC.md for complete file listing by directory
  3. Read specific files from contents/{path}
Install via CLI
npx skills add https://github.com/olorehq/olore --skill olore-tensorzero-latest
Repository Details
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navigation Branch main
article Path SKILL.md
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