semvec/pypi-packages huggingface dataset:
opentelemetry-instrumentation-haystack 0.52.4
OpenTelemetry Haystack instrumentation
Requires Python: <4,>=3.10

# OpenTelemetry Haystack Instrumentation

<a href="https://pypi.org/project/opentelemetry-instrumentation-haystack/">
    <img src="https://badge.fury.io/py/opentelemetry-instrumentation-haystack.svg">
</a>

This library allows tracing complete LLM applications built with [Haystack](https://github.com/deepset-ai/haystack).

## Installation

```bash
pip install opentelemetry-instrumentation-haystack
```

## Example usage

```python
from opentelemetry.instrumentation.haystack import HaystackInstrumentor

HaystackInstrumentor().instrument()
```

## Privacy

**By default, this instrumentation logs prompts, completions, and embeddings to span attributes**. This gives you a clear visibility into how your LLM application is working, and can make it easy to debug and evaluate the quality of the outputs.

However, you may want to disable this logging for privacy reasons, as they may contain highly sensitive data from your users. You may also simply want to reduce the size of your traces.

To disable logging, set the `TRACELOOP_TRACE_CONTENT` environment variable to `false`.

```bash
TRACELOOP_TRACE_CONTENT=false
```
opentelemetry-instrumentation-groq 0.52.4
OpenTelemetry Groq instrumentation
Requires Python: <4,>=3.10

# OpenTelemetry Groq Instrumentation

<a href="https://pypi.org/project/opentelemetry-instrumentation-groq/">
    <img src="https://badge.fury.io/py/opentelemetry-instrumentation-groq.svg">
</a>

This library allows tracing Groq prompts and completions sent with the official [Groq SDK](https://github.com/groq/groq-python).

## Installation

```bash
pip install opentelemetry-instrumentation-groq
```

## Example usage

```python
from opentelemetry.instrumentation.groq import GroqInstrumentor

GroqInstrumentor().instrument()
```

## Privacy

**By default, this instrumentation logs prompts, completions, and embeddings to span attributes**. This gives you a clear visibility into how your LLM application is working, and can make it easy to debug and evaluate the quality of the outputs.

However, you may want to disable this logging for privacy reasons, as they may contain highly sensitive data from your users. You may also simply want to reduce the size of your traces.

To disable logging, set the `TRACELOOP_TRACE_CONTENT` environment variable to `false`.

```bash
TRACELOOP_TRACE_CONTENT=false
```
opentelemetry-instrumentation-google-generativeai 0.52.4
OpenTelemetry Google Generative AI instrumentation
Requires Python: <4,>=3.10

# OpenTelemetry Google Generative AI Instrumentation

<a href="https://pypi.org/project/opentelemetry-instrumentation-google-generativeai/">
    <img src="https://badge.fury.io/py/opentelemetry-instrumentation-google-generativeai.svg">
</a>

This library allows tracing Google Gemini prompts and completions sent with the official [Google Generative AI library](https://github.com/google-gemini/generative-ai-python).

## Installation

```bash
pip install opentelemetry-instrumentation-google-generativeai
```

## Example usage

```python
from opentelemetry.instrumentation.google_generativeai import GoogleGenerativeAiInstrumentor

GoogleGenerativeAiInstrumentor().instrument()
```

## Privacy

**By default, this instrumentation logs prompts, completions, and embeddings to span attributes**. This gives you a clear visibility into how your LLM application is working, and can make it easy to debug and evaluate the quality of the outputs.

However, you may want to disable this logging for privacy reasons, as they may contain highly sensitive data from your users. You may also simply want to reduce the size of your traces.

To disable logging, set the `TRACELOOP_TRACE_CONTENT` environment variable to `false`.

```bash
TRACELOOP_TRACE_CONTENT=false
```
opentelemetry-instrumentation-crewai 0.52.4
OpenTelemetry crewAI instrumentation
Requires Python: <4,>=3.10

# OpenTelemetry CrewAI Instrumentation

<a href="https://pypi.org/project/opentelemetry-instrumentation-crewai/">
    <img src="https://badge.fury.io/py/opentelemetry-instrumentation-crewai.svg">
</a>

This library allows tracing agentic workflows implemented with crewAI framework [crewAI library](https://github.com/crewAIInc/crewAI).

## Installation

```bash
pip install opentelemetry-instrumentation-crewai
```

## Example usage

```python
from opentelemetry.instrumentation.crewai import CrewAIInstrumentor

CrewAIInstrumentor().instrument()
```

## Privacy

**By default, this instrumentation logs prompts, completions, and embeddings to span attributes**. This gives you a clear visibility into how your LLM application is working, and can make it easy to debug and evaluate the quality of the outputs.

However, you may want to disable this logging for privacy reasons, as they may contain highly sensitive data from your users. You may also simply want to reduce the size of your traces.

To disable logging, set the `TRACELOOP_TRACE_CONTENT` environment variable to `false`.

```bash
TRACELOOP_TRACE_CONTENT=false
```
opentelemetry-instrumentation-cohere 0.52.4
OpenTelemetry Cohere instrumentation
Requires Python: <4,>=3.10

# OpenTelemetry Cohere Instrumentation

<a href="https://pypi.org/project/opentelemetry-instrumentation-cohere/">
    <img src="https://badge.fury.io/py/opentelemetry-instrumentation-cohere.svg">
</a>

This library allows tracing calls to any of Cohere's endpoints sent with the official [Cohere library](https://github.com/cohere-ai/cohere-python).

## Installation

```bash
pip install opentelemetry-instrumentation-cohere
```

## Example usage

```python
from opentelemetry.instrumentation.cohere import CohereInstrumentor

CohereInstrumentor().instrument()
```

## Privacy

**By default, this instrumentation logs prompts, completions, and embeddings to span attributes**. This gives you a clear visibility into how your LLM application is working, and can make it easy to debug and evaluate the quality of the outputs.

However, you may want to disable this logging for privacy reasons, as they may contain highly sensitive data from your users. You may also simply want to reduce the size of your traces.

To disable logging, set the `TRACELOOP_TRACE_CONTENT` environment variable to `false`.

```bash
TRACELOOP_TRACE_CONTENT=false
```
opentelemetry-instrumentation-chromadb 0.52.4
OpenTelemetry Chroma DB instrumentation
Requires Python: <4,>=3.10

# OpenTelemetry Chroma Instrumentation

<a href="https://pypi.org/project/opentelemetry-instrumentation-chromadb/">
    <img src="https://badge.fury.io/py/opentelemetry-instrumentation-chromadb.svg">
</a>

This library allows tracing client-side calls to Chroma vector DB sent with the official [Chroma library](https://github.com/chroma-core/chroma).

## Installation

```bash
pip install opentelemetry-instrumentation-chromadb
```

## Example usage

```python
from opentelemetry.instrumentation.chromadb import ChromaInstrumentor

ChromaInstrumentor().instrument()
```
opentelemetry-instrumentation-bedrock 0.52.4
OpenTelemetry Bedrock instrumentation
Requires Python: <4,>=3.10

# OpenTelemetry Bedrock Instrumentation

<a href="https://pypi.org/project/opentelemetry-instrumentation-bedrock/">
    <img src="https://badge.fury.io/py/opentelemetry-instrumentation-bedrock.svg">
</a>

This library allows tracing any of AWS Bedrock's models prompts and completions sent with [Boto3](https://github.com/boto/boto3) to Bedrock.

## Installation

```bash
pip install opentelemetry-instrumentation-bedrock
```

## Example usage

```python
from opentelemetry.instrumentation.bedrock import BedrockInstrumentor

BedrockInstrumentor().instrument()
```

## Privacy

**By default, this instrumentation logs prompts, completions, and embeddings to span attributes**. This gives you a clear visibility into how your LLM application is working, and can make it easy to debug and evaluate the quality of the outputs.

However, you may want to disable this logging for privacy reasons, as they may contain highly sensitive data from your users. You may also simply want to reduce the size of your traces.

To disable logging, set the `TRACELOOP_TRACE_CONTENT` environment variable to `false`.

```bash
TRACELOOP_TRACE_CONTENT=false
```
opentelemetry-instrumentation-anthropic 0.52.4
OpenTelemetry Anthropic instrumentation
Requires Python: <4,>=3.10

# OpenTelemetry Anthropic Instrumentation

<a href="https://pypi.org/project/opentelemetry-instrumentation-anthropic/">
    <img src="https://badge.fury.io/py/opentelemetry-instrumentation-anthropic.svg">
</a>

This library allows tracing Anthropic prompts and completions sent with the official [Anthropic library](https://github.com/anthropics/anthropic-sdk-python).

## Installation

```bash
pip install opentelemetry-instrumentation-anthropic
```

## Example usage

```python
from opentelemetry.instrumentation.anthropic import AnthropicInstrumentor

AnthropicInstrumentor().instrument()
```

## Privacy

**By default, this instrumentation logs prompts, completions, and embeddings to span attributes**. This gives you a clear visibility into how your LLM application is working, and can make it easy to debug and evaluate the quality of the outputs.

However, you may want to disable this logging for privacy reasons, as they may contain highly sensitive data from your users. You may also simply want to reduce the size of your traces.

To disable logging, set the `TRACELOOP_TRACE_CONTENT` environment variable to `false`.

```bash
TRACELOOP_TRACE_CONTENT=false
```
opentelemetry-instrumentation-alephalpha 0.52.4
OpenTelemetry Aleph Alpha instrumentation
Requires Python: <4,>=3.10

# OpenTelemetry Aleph Alpha Instrumentation

<a href="https://pypi.org/project/opentelemetry-instrumentation-alephalpha/">
    <img src="https://badge.fury.io/py/opentelemetry-instrumentation-alephalpha.svg">
</a>

This library allows tracing calls to any of Aleph Alpha's endpoints sent with the official [Aleph Alpha Client](https://github.com/Aleph-Alpha/aleph-alpha-client).

## Installation

```bash
pip install opentelemetry-instrumentation-alephalpha
```

## Example usage

```python
from opentelemetry.instrumentation.alephalpha import AlephAlphaInstrumentor

AlephAlphaInstrumentor().instrument()
```

## Privacy

**By default, this instrumentation logs prompts, completions, and embeddings to span attributes**. This gives you a clear visibility into how your LLM application is working, and can make it easy to debug and evaluate the quality of the outputs.

However, you may want to disable this logging for privacy reasons, as they may contain highly sensitive data from your users. You may also simply want to reduce the size of your traces.

To disable logging, set the `TRACELOOP_TRACE_CONTENT` environment variable to `false`.

```bash
TRACELOOP_TRACE_CONTENT=false
```
opentelemetry-instrumentation-agno 0.52.4
OpenTelemetry Agno instrumentation
Requires Python: <4,>=3.10

# OpenTelemetry Agno Instrumentation

This library provides automatic instrumentation for the [Agno](https://github.com/agno-agi/agno) framework.

## Installation

```bash
pip install opentelemetry-instrumentation-agno
```

## Usage

```python
from opentelemetry.instrumentation.agno import AgnoInstrumentor

AgnoInstrumentor().instrument()
```

## Supported Features

This instrumentation captures:
- Agent execution (sync and async)
- Team operations
- Model invocations
- Function calls
- Streaming responses

## Links

- [Agno Framework](https://github.com/agno-agi/agno)
- [OpenTelemetry](https://opentelemetry.io/)
epinterface 1.3.0
This is a repository for dynamically generating energy models within Python, relying on Archetypal and Eppy for most of its functionality.
Requires Python: <3.13,>=3.10

# epinterface

[![Release](https://img.shields.io/github/v/release/szvsw/epinterface)](https://img.shields.io/github/v/release/szvsw/epinterface)
[![Build status](https://img.shields.io/github/actions/workflow/status/szvsw/epinterface/main.yml?branch=main)](https://github.com/szvsw/epinterface/actions/workflows/main.yml?query=branch%3Amain)
[![codecov](https://codecov.io/gh/szvsw/epinterface/branch/main/graph/badge.svg)](https://codecov.io/gh/szvsw/epinterface)
[![Commit activity](https://img.shields.io/github/commit-activity/m/szvsw/epinterface)](https://img.shields.io/github/commit-activity/m/szvsw/epinterface)
[![License](https://img.shields.io/github/license/szvsw/epinterface)](https://img.shields.io/github/license/szvsw/epinterface)

This is a repository for dynamically generating energy models within Python, relying on Archetypal and Eppy for most of its functionality.

- **Github repository**: <https://github.com/szvsw/epinterface/>

## Configuration

The EnergyPlus version used when creating IDF objects can be configured via the `EPINTERFACE_ENERGYPLUS_VERSION` environment variable. It defaults to `22.2.0`. Both dotted (`22.2.0`) and hyphenated (`22-2-0`) version formats are accepted.

- **Documentation** <https://szvsw.github.io/epinterface/>

## Getting started with your project

First, create a repository on GitHub with the same name as this project, and then run the following commands:

```bash
git init -b main
git add .
git commit -m "init commit"
git remote add origin git@github.com:szvsw/epinterface.git
git push -u origin main
```

Finally, install the environment and the pre-commit hooks with

```bash
make install
```

You are now ready to start development on your project!
The CI/CD pipeline will be triggered when you open a pull request, merge to main, or when you create a new release.

To finalize the set-up for publishing to PyPI or Artifactory, see [here](https://fpgmaas.github.io/cookiecutter-uv/features/publishing/#set-up-for-pypi).
For activating the automatic documentation with MkDocs, see [here](https://fpgmaas.github.io/cookiecutter-uv/features/mkdocs/#enabling-the-documentation-on-github).
To enable the code coverage reports, see [here](https://fpgmaas.github.io/cookiecutter-uv/features/codecov/).

## Releasing a new version

- Create an API Token on [PyPI](https://pypi.org/).
- Add the API Token to your projects secrets with the name `PYPI_TOKEN` by visiting [this page](https://github.com/szvsw/epinterface/settings/secrets/actions/new).
- Create a [new release](https://github.com/szvsw/epinterface/releases/new) on Github.
- Create a new tag in the form `*.*.*`.
- For more details, see [here](https://fpgmaas.github.io/cookiecutter-uv/features/cicd/#how-to-trigger-a-release).

---

Repository initiated with [fpgmaas/cookiecutter-uv](https://github.com/fpgmaas/cookiecutter-uv).