From a5a542b33e105445a424844d217a6ee8b14c358d Mon Sep 17 00:00:00 2001 From: CoprDistGit Date: Sun, 23 Apr 2023 04:51:22 +0000 Subject: automatic import of python-jina --- .gitignore | 1 + python-jina.spec | 35 ++++++++++++++++++++++------------- sources | 2 +- 3 files changed, 24 insertions(+), 14 deletions(-) diff --git a/.gitignore b/.gitignore index c4eb844..5fd5f1f 100644 --- a/.gitignore +++ b/.gitignore @@ -1 +1,2 @@ /jina-3.14.1.tar.gz +/jina-3.15.0.tar.gz diff --git a/python-jina.spec b/python-jina.spec index 8a007a6..a26271e 100644 --- a/python-jina.spec +++ b/python-jina.spec @@ -1,11 +1,11 @@ %global _empty_manifest_terminate_build 0 Name: python-jina -Version: 3.14.1 +Version: 3.15.0 Release: 1 Summary: Build multimodal AI services via cloud native technologies · Neural Search · Generative AI · MLOps License: Apache 2.0 URL: https://github.com/jina-ai/jina/ -Source0: https://mirrors.nju.edu.cn/pypi/web/packages/d6/93/909b20eeddce3941d76a06c357e1d9d7386159e9420f04750d023116ff48/jina-3.14.1.tar.gz +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/68/fd/559d5809832dfc49615aaf5626f1ff28b1de54453a72e2056ad9f702203a/jina-3.15.0.tar.gz BuildArch: noarch @@ -13,14 +13,14 @@ BuildArch: noarch

Jina: Streamline AI & ML Product Delivery

-### Build AI & ML Services +### Build AI Services [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/jina-ai/jina/blob/master/.github/getting-started/notebook.ipynb) Let's build a fast, reliable and scalable gRPC-based AI service. In Jina we call this an **[Executor](https://docs.jina.ai/concepts/executor/)**. Our simple Executor will use Facebook's mBART-50 model to translate French to English. We'll then use a **Deployment** to serve it. > **Note** > A Deployment serves just one Executor. To combine multiple Executors into a pipeline and serve that, use a [Flow](#build-a-pipeline). > **Note** -> Run the [code in Colab](https://colab.research.google.com/assets/colab-badge.svg) to install all dependencies. +> Run the [code in Colab](https://colab.research.google.com/github/jina-ai/jina/blob/master/.github/getting-started/notebook.ipynb#scrollTo=0l-lkmz4H-jW) to install all dependencies. Let's implement the service's logic: @@ -67,6 +67,7 @@ Then we deploy it with either the Python API or YAML:
```python from jina import Deployment +from translate_executor import Translator with Deployment(uses=Translator, timeout_ready=-1) as dep: dep.block() ``` @@ -109,9 +110,11 @@ print(response[0].text) an astronaut is walking in a park ``` +> **Note** +> In a notebook, one cannot use `deployment.block()` and then make requests to the client. Please refer to the colab link above for reproducible Jupyter Notebook code snippets. ### Build a pipeline -[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/jina-ai/jina/blob/docs-readme-changes/.github/getting-started/notebook.ipynb) +[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/jina-ai/jina/blob/master/.github/getting-started/notebook.ipynb#scrollTo=YfNm1nScH30U) Sometimes you want to chain microservices together into a pipeline. That's where a [Flow](https://docs.jina.ai/concepts/flow/) comes in. A Flow is a [DAG](https://de.wikipedia.org/wiki/DAG) pipeline, composed of a set of steps, It orchestrates a set of [Executors](https://docs.jina.ai/concepts/executor/) and a [Gateway](https://docs.jina.ai/concepts/gateway/) to offer an end-to-end service. > **Note** @@ -199,14 +202,14 @@ BuildRequires: python3-pip

Jina: Streamline AI & ML Product Delivery

-### Build AI & ML Services +### Build AI Services [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/jina-ai/jina/blob/master/.github/getting-started/notebook.ipynb) Let's build a fast, reliable and scalable gRPC-based AI service. In Jina we call this an **[Executor](https://docs.jina.ai/concepts/executor/)**. Our simple Executor will use Facebook's mBART-50 model to translate French to English. We'll then use a **Deployment** to serve it. > **Note** > A Deployment serves just one Executor. To combine multiple Executors into a pipeline and serve that, use a [Flow](#build-a-pipeline). > **Note** -> Run the [code in Colab](https://colab.research.google.com/assets/colab-badge.svg) to install all dependencies. +> Run the [code in Colab](https://colab.research.google.com/github/jina-ai/jina/blob/master/.github/getting-started/notebook.ipynb#scrollTo=0l-lkmz4H-jW) to install all dependencies. Let's implement the service's logic: @@ -253,6 +256,7 @@ Then we deploy it with either the Python API or YAML:
```python from jina import Deployment +from translate_executor import Translator with Deployment(uses=Translator, timeout_ready=-1) as dep: dep.block() ``` @@ -295,9 +299,11 @@ print(response[0].text) an astronaut is walking in a park ``` +> **Note** +> In a notebook, one cannot use `deployment.block()` and then make requests to the client. Please refer to the colab link above for reproducible Jupyter Notebook code snippets. ### Build a pipeline -[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/jina-ai/jina/blob/docs-readme-changes/.github/getting-started/notebook.ipynb) +[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/jina-ai/jina/blob/master/.github/getting-started/notebook.ipynb#scrollTo=YfNm1nScH30U) Sometimes you want to chain microservices together into a pipeline. That's where a [Flow](https://docs.jina.ai/concepts/flow/) comes in. A Flow is a [DAG](https://de.wikipedia.org/wiki/DAG) pipeline, composed of a set of steps, It orchestrates a set of [Executors](https://docs.jina.ai/concepts/executor/) and a [Gateway](https://docs.jina.ai/concepts/gateway/) to offer an end-to-end service. > **Note** @@ -382,14 +388,14 @@ Provides: python3-jina-doc

Jina: Streamline AI & ML Product Delivery

-### Build AI & ML Services +### Build AI Services [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/jina-ai/jina/blob/master/.github/getting-started/notebook.ipynb) Let's build a fast, reliable and scalable gRPC-based AI service. In Jina we call this an **[Executor](https://docs.jina.ai/concepts/executor/)**. Our simple Executor will use Facebook's mBART-50 model to translate French to English. We'll then use a **Deployment** to serve it. > **Note** > A Deployment serves just one Executor. To combine multiple Executors into a pipeline and serve that, use a [Flow](#build-a-pipeline). > **Note** -> Run the [code in Colab](https://colab.research.google.com/assets/colab-badge.svg) to install all dependencies. +> Run the [code in Colab](https://colab.research.google.com/github/jina-ai/jina/blob/master/.github/getting-started/notebook.ipynb#scrollTo=0l-lkmz4H-jW) to install all dependencies. Let's implement the service's logic: @@ -436,6 +442,7 @@ Then we deploy it with either the Python API or YAML:
```python from jina import Deployment +from translate_executor import Translator with Deployment(uses=Translator, timeout_ready=-1) as dep: dep.block() ``` @@ -478,9 +485,11 @@ print(response[0].text) an astronaut is walking in a park ``` +> **Note** +> In a notebook, one cannot use `deployment.block()` and then make requests to the client. Please refer to the colab link above for reproducible Jupyter Notebook code snippets. ### Build a pipeline -[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/jina-ai/jina/blob/docs-readme-changes/.github/getting-started/notebook.ipynb) +[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/jina-ai/jina/blob/master/.github/getting-started/notebook.ipynb#scrollTo=YfNm1nScH30U) Sometimes you want to chain microservices together into a pipeline. That's where a [Flow](https://docs.jina.ai/concepts/flow/) comes in. A Flow is a [DAG](https://de.wikipedia.org/wiki/DAG) pipeline, composed of a set of steps, It orchestrates a set of [Executors](https://docs.jina.ai/concepts/executor/) and a [Gateway](https://docs.jina.ai/concepts/gateway/) to offer an end-to-end service. > **Note** @@ -559,7 +568,7 @@ Read more about [deploying Flows to JCloud](https://docs.jina.ai/concepts/jcloud %prep -%autosetup -n jina-3.14.1 +%autosetup -n jina-3.15.0 %build %py3_build @@ -599,5 +608,5 @@ mv %{buildroot}/doclist.lst . %{_docdir}/* %changelog -* Mon Apr 10 2023 Python_Bot - 3.14.1-1 +* Sun Apr 23 2023 Python_Bot - 3.15.0-1 - Package Spec generated diff --git a/sources b/sources index 5c83cb1..258ba29 100644 --- a/sources +++ b/sources @@ -1 +1 @@ -4b6a33345d4c258924fcb6cebe45642a jina-3.14.1.tar.gz +0d50ec365278099aa914c711fa5b7456 jina-3.15.0.tar.gz -- cgit v1.2.3