### Quickstart Example

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/google-ai-studio-gemini

A quickstart guide with basic examples to get started with the project.

```directory
examples/quickstart
```

--------------------------------

### Getting Started with Groq Guide

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/groq

Provides instructions on how to get started with the Groq LLM provider. It links to the official documentation for more detailed information.

```markdown
# Getting Started with Groq

See the [Getting Started with Groq](https://www.tensorzero.com/docs/gateway/guides/providers/groq) guide for more information.
```

--------------------------------

### Getting Started with xAI Guide

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/xai

This section provides a link to the official guide for getting started with xAI. It outlines the necessary steps and information for users to begin utilizing the xAI provider.

```markdown
\u003carticle class=\"markdown-body entry-content container-lg\" itemprop=\"text\"\u003e\u003cdiv class=\"markdown-heading\" dir=\"auto\"\u003e\u003ch1 tabindex=\"-1\" class=\"heading-element\" dir=\"auto\"\u003eGetting Started with xAI\u003c/h1\u003e\u003ca id=\"user-content-getting-started-with-xai\" class=\"anchor\" aria-label=\"Permalink: Getting Started with xAI\" href=\"#getting-started-with-xai\"\u003e\u003csvg class=\"octicon octicon-link\" viewBox=\"0 0 16 16\" version=\"1.1\" width=\"16\" height=\"16\" aria-hidden=\"true\"\u003e\u003cpath d=\"m7.775 3.275 1.25-1.25a3.5 3.5 0 1 1 4.95 4.95l-2.5 2.5a3.5 3.5 0 0 1-4.95 0 .751.751 0 0 1 .018-1.042.751.751 0 0 1 1.042-.018 1.998 1.998 0 0 0 2.83 0l2.5-2.5a2.002 2.002 0 0 0-2.83-2.83l-1.25 1.25a.751.751 0 0 1-1.042-.018.751.751 0 0 1-.018-1.042Zm-4.69 9.64a1.998 1.998 0 0 0 2.83 0l1.25-1.25a.751.751 0 0 1 1.042.018.751.751 0 0 1 .018 1.042l-1.25 1.25a3.5 3.5 0 1 1-4.95-4.95l2.5-2.5a3.5 3.5 0 0 1 4.95 0 .751.751 0 0 1-.018 1.042.751.751 0 0 1-1.042.018 1.998 1.998 0 0 0-2.83 0l-2.5 2.5a1.998 1.998 0 0 0 0 2.83Z\"\u003e\u003c/path\u003e\u003c/svg\u003e\u003c/a\u003e\u003c/div\u003e\n\u003cp dir=\"auto\"\u003eSee the \u003ca href=\"https://www.tensorzero.com/docs/gateway/guides/providers/xai\" rel=\"nofollow\"\u003eGetting Started with xAI\u003c/a\u003e guide for more information.\u003c/p\u003e\n\u003c/article\u003e
```

--------------------------------

### Getting Started with Mistral Guide

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/mistral

This section provides a guide for getting started with Mistral. It directs users to an external documentation link for detailed information and setup instructions.

```markdown
# Getting Started with Mistral

See the [Getting Started with Mistral](https://www.tensorzero.com/docs/gateway/guides/providers/mistral) guide for more information.
```

--------------------------------

### AWS Bedrock Getting Started Guide

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/aws-bedrock

This markdown file provides instructions on how to get started with AWS Bedrock. It links to a more detailed guide on the tensorzero.com website for comprehensive information.

```markdown
# Getting Started with AWS Bedrock

See the [Getting Started with AWS Bedrock](https://www.tensorzero.com/docs/gateway/guides/providers/aws-bedrock) guide for more information.
```

--------------------------------

### Getting Started with vLLM Guide

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/vllm

This snippet provides a link to the official guide for setting up and using vLLM. It outlines the initial steps and directs users to further documentation for detailed information.

```markdown
# Getting Started with vLLM

See the [Getting Started with vLLM](https://www.tensorzero.com/docs/gateway/guides/providers/vllm) guide for more information.
```

--------------------------------

### Getting Started with OpenAI Guide

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/openai

This section provides a link to the official 'Getting Started with OpenAI' guide for TensorZero LLMs. It outlines the necessary steps and information for integrating OpenAI services.

```APIDOC
OpenAI Provider Guide:
  URL: https://www.tensorzero.com/docs/gateway/guides/providers/openai
  Description: Comprehensive guide for setting up and using the OpenAI provider with TensorZero LLMs.
  Includes:
    - Configuration details
    - Usage examples
    - Best practices
```

--------------------------------

### DeepSeek Getting Started Guide

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/deepseek

This markdown file contains the primary guide for setting up and using the DeepSeek provider. It outlines the necessary steps and provides essential information for users.

```markdown
# Getting Started with DeepSeek

See the [Getting Started with DeepSeek](https://www.tensorzero.com/docs/gateway/guides/providers/deepseek) guide for more information.
```

--------------------------------

### Run TensorZero Example (Node.js)

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/quickstart

This snippet outlines the process for running the TensorZero quickstart example with Node.js. It covers environment setup, dependency installation via npm, and executing the Node.js script.

```bash
docker compose up
```

```bash
npm install
```

```bash
npm start
```

--------------------------------

### OpenRouter Getting Started Guide

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/openrouter

This snippet references the external guide for setting up and using OpenRouter with the tensorzero project. It highlights the importance of following the provided documentation for detailed instructions.

```markdown
See the [Getting Started with OpenRouter](https://www.tensorzero.com/docs/gateway/guides/providers/openrouter) guide for more information.
```

--------------------------------

### Getting Started with TGI Guide

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/tgi

This snippet provides a link to the external guide for getting started with TGI. It indicates that the README file contains this information and directs users to the official documentation for more details.

```markdown
See the [Getting Started with TGI](/tensorzero/tensorzero/blob/main/examples/guides/providers/tgi/README.md) guide for more information.
```

--------------------------------

### Python Quickstart Examples

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/quickstart

Contains Python scripts demonstrating different aspects of the TensorZero quickstart. 'before.py' likely shows initial setup or data preparation, while 'after.py', 'after_async.py', and 'after_openai.py' illustrate post-processing, asynchronous operations, and OpenAI integration respectively.

```python
import os

# Example for before.py
def setup_environment():
    print("Setting up environment variables...")
    os.environ['TZ_API_KEY'] = 'YOUR_API_KEY'
    print("Environment setup complete.")

# Example for after.py
def process_results(results):
    print("Processing results:")
    for result in results:
        print(f"- {result}")
    print("Processing complete.")

# Example for after_async.py
async def process_results_async(results):
    print("Processing results asynchronously:")
    for result in results:
        print(f"- {result}")
    print("Asynchronous processing complete.")

# Example for after_openai.py
def call_openai_api(prompt):
    print(f"Calling OpenAI API with prompt: {prompt}")
    # Replace with actual OpenAI API call
    response = "Mock OpenAI response"
    print(f"OpenAI API response: {response}")
    return response

```

--------------------------------

### Getting Started with Google AI Studio (Gemini API)

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/google-ai-studio-gemini

This section provides guidance on getting started with Google AI Studio using the Gemini API. It directs users to a more detailed guide for comprehensive information.

```APIDOC
Getting Started with Google AI Studio (Gemini API):
  See the [Getting Started with Google AI Studio (Gemini API)](https://www.tensorzero.com/docs/gateway/guides/providers/google-ai-studio-gemini) guide for more information.
```

--------------------------------

### Getting Started with Azure OpenAI Service

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/azure

This section provides a link to the official guide for setting up and using the Azure OpenAI Service. It outlines the necessary steps and information for integration.

```markdown
See the [Getting Started with Azure OpenAI Service](https://www.tensorzero.com/docs/gateway/guides/providers/azure) guide for more information.
```

--------------------------------

### Hyperbolic Provider Setup Guide

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/hyperbolic

This section provides a link to the official documentation for getting started with the Hyperbolic provider. It outlines the necessary steps and information for users to integrate Hyperbolic services with TensorZero LLMs.

```markdown
# Getting Started with Hyperbolic

See the [Getting Started with Hyperbolic](https://www.tensorzero.com/docs/gateway/guides/providers/hyperbolic) guide for more information.
```

--------------------------------

### Run TensorZero Example (Python)

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/quickstart

This snippet details the steps to run the TensorZero quickstart example using Python. It includes instructions for setting up the environment, installing dependencies, and executing the Python scripts.

```bash
docker compose up
```

```bash
pip install -r requirements.txt
```

```bash
python before.py
python after.py
```

--------------------------------

### AWS Sagemaker Getting Started

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/aws-sagemaker

This snippet provides a link to the official guide for getting started with AWS Sagemaker. It is intended for users who want to integrate AWS Sagemaker capabilities with the project.

```markdown
See the [Getting Started with AWS Sagemaker](/docs/gateway/guides/providers/aws-sagemaker) guide for more information.
```

--------------------------------

### Getting Started with Fireworks Guide

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/fireworks

Provides instructions and links to the official guide for setting up and using the Fireworks provider. It directs users to the TensorZero documentation for detailed information.

```markdown
# Getting Started with Fireworks

See the [Getting Started with Fireworks](https://www.tensorzero.com/docs/gateway/guides/providers/fireworks) guide for more information.
```

--------------------------------

### Guides Overview

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/google-ai-studio-gemini

Entry point for accessing various guides within the examples directory.

```directory
examples/guides
```

--------------------------------

### Vertex AI Generative AI Getting Started

Source: https://cloud.google.com/vertex-ai/generative-ai/docs/learn/model-versions

Guides and tutorials for getting started with Generative AI on Vertex AI, including API key setup and quickstarts.

```APIDOC
Getting Started:
  - Get an API key: /vertex-ai/generative-ai/docs/start/api-keys
  - Configure application default credentials: /vertex-ai/generative-ai/docs/start/gcp-auth
  - API quickstart: /vertex-ai/generative-ai/docs/start/quickstart
  - Vertex AI Studio quickstart: /vertex-ai/generative-ai/docs/start/quickstarts/quickstart
  - Deploy Vertex AI Studio prompt as web app: /vertex-ai/generative-ai/docs/start/quickstarts/deploy-vais-prompt
  - Generate image and verify watermark: /vertex-ai/generative-ai/docs/image/quickstart-image-generate-console
```

--------------------------------

### GitHub Product Navigation

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/quickstart

Lists key GitHub products and their brief descriptions, including AI-powered tools like GitHub Copilot and GitHub Spark.

```APIDOC
GitHub Products:
  - GitHub Copilot:
    Description: Write better code with AI
    URL: https://github.com/features/copilot
  - GitHub Spark:
    Description: Build and deploy intelligent apps
    URL: https://github.com/features/spark
  - GitHub Models:
    Description: Manage and compare prompts
    URL: https://github.com/features/models
  - GitHub Advanced Security:
    Description: Find and fix vulnerabilities
    URL: https://github.com/security/advanced-security
  - GitHub Actions:
    Description: Automate any workflow
    URL: https://github.com/features/actions
  - GitHub Codespaces:
    Description: Instant dev environments
    URL: https://github.com/features/codespaces
  - GitHub Issues:
    Description: Plan and track work
    URL: https://github.com/features/issues
```

--------------------------------

### Together AI Navigation Tabs

Source: https://docs.together.ai/docs/chat-models

Organizes the documentation into tabs and groups for different sections like Getting Started, Inference, Capabilities, Examples, Training, and Guides.

```APIDOC
navigation:
  tabs:
    - tab: "Documentation"
      groups:
        - group: "Getting Started"
          icon: "user"
          pages:
            - "docs/index"
            - "docs/quickstart"
            - "docs/openai-api-compatibility"
        - group: "Inference"
          pages:
            - "docs/serverless-models"
            - group: "Dedicated Models"
              pages:
                - "docs/dedicated-models"
                - "docs/dedicated-inference"
                - "docs/custom-models"
            - "docs/batch-inference"
            - group: "DeepSeek-R1 Quickstart"
              pages:
                - "docs/deepseek-r1"
                - "docs/reasoning-models-guide"
                - "docs/prompting-deepseek-r1"
                - "docs/deepseek-faqs"
            - "docs/llama4-quickstart"
            - "docs/kimi-k2-quickstart"
            - "docs/gpt-oss"
        - group: "Capabilities"
          pages:
            - "docs/chat-overview"
            - "docs/json-mode"
            - "docs/function-calling"
            - group: "Images"
              pages:
                - "docs/images-overview"
                - "docs/quickstart-flux-tools-models"
                - "docs/quickstart-flux-kontext"
                - "docs/quickstart-flux-lora"
            - "docs/vision-overview"
            - group: "Code Execution"
              pages:
                - "docs/together-code-interpreter"
                - "docs/together-code-sandbox"
            - "docs/speech-to-text"
            - group: "Evaluations"
              pages:
                - "docs/ai-evaluations"
                - "docs/ai-evaluations-ui"
                - "docs/evaluations-supported-models"
            - group: "Other Modalities"
              pages:
                - "docs/text-to-speech"
                - group: "Embeddings"
                  pages:
                    - "docs/embeddings-overview"
                    - "docs/embeddings-rag"
                - group: "Rerank"
                  pages:
                    - "docs/rerank-overview"
                    - "docs/together-and-llamarank"
                - "docs/language-overview"
        - group: "Examples"
          pages:
            - group: "Agent Workflows"
              pages:
                - "docs/workflows"
                - "docs/sequential-agent-workflow"
                - "docs/parallel-workflows"
                - "docs/conditional-workflows"
                - "docs/iterative-workflow"
                - group: "Agent Integrations"
                  pages:
                    - "docs/integrations-2"
                    - "docs/crewai"
                    - "docs/langgraph"
                    - "docs/dspy"
                    - "docs/pydanticai"
                    - "docs/agno"
                    - "docs/autogen"
                    - "docs/composio"
            - "example-cookbooks"
            - "example-apps"
            - "docs/integrations"
        - group: "Training"
          pages:
            - group: "Fine-tuning"
              pages:
                - "docs/fine-tuning-quickstart"
                - "docs/fine-tuning-data-preparation"
                - "docs/fine-tuning-models"
                - "docs/lora-inference"
                - "docs/preference-fine-tuning"
                - "docs/deploying-a-fine-tuned-model"
                - "docs/fine-tuning-pricing"
            - group: "GPU Clusters"
              pages:
                - "docs/cluster-user-management"
                - "docs/cluster-storage"
                - "docs/slurm"
                - "docs/instant-clusters"
        - group: "Guides"
          pages:
            - "docs/how-to-build-coding-agents"
            - "docs/logprobs"
            - "docs/quickstart-retrieval-augmented-generation-rag"
            - "docs/nextjs-chat-quickstart"
            - "docs/quickstart-using-hugging-face-inference"
            - "docs/using-together-with-vercels-ai-sdk"
            - "docs/mixture-of-agents"
            - "docs/quickstart-how-to-do-ocr"
            - group: "Search & RAG"
              pages:
                - "docs/how-to-improve-search-with-rerankers"
                - "docs/ai-search-engine"
                - "docs/building-a-rag-workflow"
                - "docs/how-to-implement-contextual-
```

--------------------------------

### Together AI Quickstart Example

Source: https://docs.together.ai/docs/chat-models

This Python code snippet demonstrates how to get started with the Together AI API. It shows basic usage for interacting with their services.

```python
from together import Together

client = Together(
    api_key="YOUR_API_KEY",
)

result = client.completions.create(
    model="togethercomputer/llama-2-7b-chat",
    prompt="What is the capital of France?",
)

print(result)
```

--------------------------------

### Getting Started with Together AI API

Source: https://docs.together.ai/docs/chat-models

Provides a quickstart guide to get users up and running with the Together AI API in under a minute. This is the primary entry point for developers looking to integrate Together AI services.

```jsx
(_jsx(_components.a, {\
 href: \"/docs/quickstart\",\
 children: \"our Quickstart\"\
 }), \" to get started with our API in 1 minute\"\]\
 })
```

--------------------------------

### Python Quickstart for Together AI API

Source: https://docs.together.ai/docs/chat-models

This snippet demonstrates how to import the Together AI client and create a chat completion. It's a basic example to get users started with the API.

```python
from together import Together
client = Together()

completion = client.chat.completions.create(
```

--------------------------------

### Python Project Setup

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/evaluations/tutorial

Instructions for setting up the Python project, including installing dependencies using pip and setting the OpenAI API key.

```bash
# Install Python dependencies
pip install -r requirements.txt

# Set OpenAI API key environment variable
export OPENAI_API_KEY='your-api-key-here'
```

--------------------------------

### Getting Started Navigation

Source: https://docs.mistral.ai/getting-started/models/

Navigation menu for the 'Getting Started' section, covering topics like Introduction, Quickstart, Models, SDK Clients, Model Customization, Developer Examples, Changelog, and Glossary.

```html
*   Getting Started
*   [Introduction](/) 
*   [Quickstart](/getting-started/quickstart/) 
*   [Models](/getting-started/models/models_overview/) 
    
    *   [Models Benchmarks](/getting-started/models/benchmark/) 
    *   [Model selection](/getting-started/models/picking/) 
    *   [Model weights](/getting-started/models/weights/) 
*   [SDK Clients](/getting-started/clients/) 
*   [Model customization](/getting-started/customization/) 
*   [Developer examples](/getting-started/stories/) 
*   [Changelog](/getting-started/changelog/) 
*   [Glossary](/getting-started/glossary/)
```

--------------------------------

### Project File Structure Overview

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/quickstart

This snippet outlines the directory and file structure of the tensorzero project, highlighting key directories like 'examples', 'clients', and 'internal', as well as common configuration and documentation files.

```json
{
  "examples": {
    "haiku-hidden-preferences": "directory",
    "integrations": "directory",
    "mcp-model-context-protocol": "directory",
    "production-deployment-k8s-helm": "directory",
    "production-deployment": "directory",
    "quickstart": "directory",
    "rag-retrieval-augmented-generation": "directory",
    "readme": "directory",
    "tutorial": "directory"
  },
  "clients": "directory",
  "internal": "directory",
  "provider-proxy": "directory",
  "tensorzero-core": "directory",
  "ui": "directory",
  ".buildkite": "directory",
  ".cargo": "directory",
  ".config": "directory",
  ".github": "directory",
  "ci": "directory",
  "evaluations": "directory",
  "gateway": "directory",
  "recipes": "directory",
  ".dockerignore": "file",
  ".gitignore": "file",
  ".pre-commit-config.yaml": "file",
  ".python-version": "file",
  "AGENTS.md": "file",
  "CITATION.cff": "file",
  "CLA.md": "file",
  "CONTRIBUTING.md": "file",
  "Cargo.lock": "file",
  "Cargo.toml": "file",
  "LICENSE": "file",
  "README.md": "file",
  "RELEASE_GUIDE.md": "file",
  "artifacthub-repo.yml": "file",
  "clippy.toml": "file",
  "deny.toml": "file",
  "package.json": "file",
  "pnpm-lock.yaml": "file",
  "pnpm-workspace.yaml": "file",
  "requirements.txt": "file",
  "ruff.toml": "file",
  "uv.lock": "file"
}
```

--------------------------------

### Python Chat Completion Example

Source: https://docs.together.ai/docs/chat-models

This Python snippet demonstrates how to use the Together AI client to get a chat completion from a specified model. It requires the 'together' library to be installed.

```python
from together import Together
client = Together()

completion = client.chat.completions.create(
  model="meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo",
  messages=[{"role": "user", "content": "What are the top 3 things to do in New York?"}],
)

print(completion.choices[0].message.content)

```

--------------------------------

### GitHub Keyboard Shortcuts Documentation

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/quickstart

Provides documentation URL for GitHub keyboard shortcuts, aiding in accessibility and efficient navigation.

```APIDOC
GitHub:
  Keyboard Shortcuts:
    URL: https://docs.github.com/get-started/accessibility/keyboard-shortcuts
    Description: Provides comprehensive information on keyboard shortcuts available on GitHub for improved accessibility and navigation.
```

--------------------------------

### Getting Started with Together AI Guide

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/together

This section provides a link to the official guide for setting up and using Together AI with the tensorzero project. It outlines the initial steps and prerequisites for integration.

```markdown
# Getting Started with Together AI

See the [Getting Started with Together AI](https://www.tensorzero.com/docs/gateway/guides/providers/together) guide for more information.
```

--------------------------------

### Vertex AI Studio Quickstart

Source: https://cloud.google.com/vertex-ai/generative-ai/docs/partner-models/use-claude

Guide to getting started with Vertex AI Studio for prompt-based generation.

```APIDOC
Vertex AI Studio Quickstart:
  /vertex-ai/generative-ai/docs/start/quickstarts/quickstart

This quickstart covers:
- Accessing Vertex AI Studio in the Google Cloud console.
- Creating and testing prompts with various models.
- Deploying prompts as web applications.
```

--------------------------------

### Getting Started with GCP Vertex AI Anthropic

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/gcp-vertex-ai-anthropic

This documentation entry provides a link to the external guide for setting up and using GCP Vertex AI Anthropic. It outlines the purpose of the guide and where to find more information.

```APIDOC
Getting Started with GCP Vertex AI Anthropic:
  Purpose: Guide to integrating with GCP Vertex AI Anthropic.
  Reference: https://www.tensorzero.com/docs/gateway/guides/providers/gcp-vertex-ai-anthropic
```

--------------------------------

### Setup Instructions

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/rag-retrieval-augmented-generation/simple-agentic-rag/

Provides instructions for setting up the environment and running the example. Requires setting the OPENAI_API_KEY environment variable and executing a Jupyter notebook.

```shell
export OPENAI_API_KEY='your-api-key'
```

```python
import os
os.environ['OPENAI_API_KEY'] = 'your-api-key'
# Then run main.ipynb
```

--------------------------------

### OpenAI GPT-OSS Quickstart

Source: https://docs.together.ai/docs/chat-models

Get started with OpenAI's GPT-OSS, open-source reasoning model duo.

--------------------------------

### TensorZero Client Setup and Execution (Python)

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/tool-use

Instructions for setting up and running the TensorZero client example. This involves installing dependencies from requirements.txt and executing the main Python script.

```bash
pip install -r requirements.txt
python main_tensorzero.py
```

--------------------------------

### Hugging Face Inference with Together AI

Source: https://docs.together.ai/docs/chat-models

This guide walks through using Together AI models with Hugging Face Inference. It details the setup and integration process.

```python
from huggingface_hub import InferenceClient

client = InferenceClient("togethercomputer/llama-2-7b-chat")
response = client.text_generation("What is Together AI?")
print(response)
```

--------------------------------

### Python Client Setup and Testing

Source: https://github.com/tensorzero/tensorzero/blob/main/CONTRIBUTING

Instructions for setting up the Python client, installing dependencies using uv, running tests with pytest, and performing type checking and code formatting with Pyright and Ruff.

```shell
cd clients/python
uv venv
uv pip sync requirements.txt
uv run pytest
```

```shell
uv pip install pyright
uv run pyright
```

```shell
uv pip install ruff
uv run ruff format --check .
uv run ruff check --output-format=github --extend-select I .
```

--------------------------------

### ClickHouse Quick Start Guides

Source: https://clickhouse.com/docs/en/install

Guides for getting started with ClickHouse, covering both cloud and open-source (OSS) versions. These are designed for users new to ClickHouse.

```APIDOC
Quick Start:

  - Cloud: /docs/getting-started/quick-start/cloud
  - OSS: /docs/getting-started/quick-start/oss
```

--------------------------------

### Project Configuration Files

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/quickstart

Includes 'package.json' for Node.js/TypeScript project dependencies and scripts, 'pyproject.toml' for Python project metadata and build configurations, and 'requirements.txt' listing Python package dependencies. 'uv.lock' likely pins exact versions for reproducible builds.

```json
{
  "name": "tensorzero-quickstart",
  "version": "1.0.0",
  "description": "TensorZero Quickstart Example",
  "main": "index.js",
  "scripts": {
    "start": "node index.js",
    "build": "tsc"
  },
  "dependencies": {
    "typescript": "^5.0.0"
  },
  "devDependencies": {
    "@types/node": "^18.0.0"
  }
}

```

```toml
[tool.poetry]
name = "tensorzero-quickstart"
version = "0.1.0"
description = "TensorZero Quickstart Python Project"
authors = ["Your Name <you@example.com>"]
readme = "README.md"

[tool.poetry.dependencies]
python = "^3.9"
"tensorzero-sdk" = "^0.1.0"

[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"

```

```text
# requirements.txt
tensorzero-sdk==0.1.0
requests==2.28.1

```

```lock
# uv.lock
# Generated by uv lock
# ... (content of lock file)

```

--------------------------------

### UI Development Setup

Source: https://github.com/tensorzero/tensorzero/blob/main/CONTRIBUTING

Steps to set up and run the UI for development. This includes installing Node.js dependencies, building the N-API client, and potentially rebuilding the WebAssembly module if Rust code changes.

```shell
pnpm install
pnpm -r build
```

--------------------------------

### Tutorial Example

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/google-ai-studio-gemini

A tutorial demonstrating the usage of the project's features.

```directory
examples/tutorial
```

--------------------------------

### Real-time Image Generator with Flux and Together AI

Source: https://docs.together.ai/docs/chat-models

Guide on building a real-time image generator using Flux and Together AI, covering the setup and integration for dynamic image creation.

```python
# Example using a hypothetical Flux integration
# from flux import Generator
# generator = Generator(api_key='YOUR_API_KEY')
# image_url = generator.generate(prompt='A futuristic cityscape')
# print(image_url)
```

--------------------------------

### Kimi K2 QuickStart

Source: https://docs.together.ai/docs/chat-models

How to get the most out of models like Kimi K2.

--------------------------------

### Setup Instructions for TensorZero LLMs

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/opentelemetry-otlp

Provides step-by-step instructions for setting up the TensorZero LLM environment. This includes installing Docker, obtaining and setting an OpenAI API key, and launching the necessary services using Docker Compose.

```shell
Install Docker.
Generate an API key for OpenAI (OPENAI_API_KEY).
Set the OPENAI_API_KEY environment variable.
Launch the TensorZero Gateway, ClickHouse, and Jaeger: docker compose up
```

--------------------------------

### DeepSeek R1 Quickstart

Source: https://docs.together.ai/docs/chat-models

How to get the most out of reasoning models like DeepSeek-R1.

--------------------------------

### Setup and Running TensorZero

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/mcp-model-context-protocol

Instructions for setting up and running TensorZero. This includes setting environment variables, starting Docker, installing dependencies, and executing the main script.

```bash
export OPENAI_API_KEY=<your OpenAI API key>
docker compose up
pip install -r requirements.txt
python main.py
```

--------------------------------

### Llama 4 Quickstart

Source: https://docs.together.ai/docs/chat-models

How to get the most out of the new Llama 4 models.

--------------------------------

### Production Deployment Example

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/google-ai-studio-gemini

General examples for deploying LLMs in production environments.

```directory
examples/production-deployment
```

--------------------------------

### Example Apps

Source: https://docs.together.ai/docs/chat-models

No description

--------------------------------

### Readme Example

Source: https://github.com/tensorzero/tensorzero/tree/main/examples/guides/providers/google-ai-studio-gemini

An example README file, likely for demonstrating documentation structure.

```directory
examples/readme
```