jina | 🔮 Build multimodal AI services via cloud native technologies | Machine Learning library
kandi X-RAY | jina Summary
kandi X-RAY | jina Summary
Jina is a neural search framework that empowers anyone to build SOTA and scalable neural search applications in minutes. ️ Save time - The design pattern of neural search systems. Quickly build solutions for indexing, querying, understanding multi-/cross-modal data such as video, image, text, audio, source code, PDF. ️ Local & cloud friendly - Distributed architecture, scalable & cloud-native from day one. Same developer experience on local, Docker Compose, Kubernetes. Serve, scale & share - Serve a local project with HTTP, WebSockets or gRPC endpoints in just minutes. Scale your neural search applications to meet your availability and throughput requirements. Share and reuse building blocks from Hub. Own your stack - Keep end-to-end stack ownership of your solution. Avoid integration pitfalls you get with fragmented, multi-vendor, generic legacy tools. Enjoy the integration with the neural search ecosystem including DocArray, Hub and Finetuner.
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Top functions reviewed by kandi - BETA
- Return an instance of FastAPI
- Get the full version of the module
- Details of the exception
- Return the exception code
- Get results from requests
- Yields all responses from a stream
- Return a sequence of Request objects
- Helper method to stream the requests
- Parse deployment arguments
- Fill an overloaded decorator
- Setup metrics
- Fill the docstring for an implementation
- Performs an async post request
- Add handlers to the logger
- Setup the server
- Performs a post request
- Setup the uvicorn server
- Write the workflow to a yaml file
- Parse the data into a BaseExecutor
- Start a running container
- Handle a request
- Creates a client
- Get results from the API
- Parse the arguments passed into the command line
- Perform a single request
- Convert a protobuf protobuf to a pydant model
jina Key Features
jina Examples and Code Snippets
Lines of Code : 104
License : No License
Copypython -m clip_server my.yml
cat my.yml | python -m clip_server -i
```yaml
jtype: Flow
version: '1'
with:
port: 51000
executors:
- name: clip_t
uses:
jtype: CLIPEncoder
metas:
py_modules:
- clip_server.executo python -m clip_server search_flow.yml
```{code-block} yaml
---
emphasize-lines: 9
---
jtype: Flow
version: '1'
with:
port: 61000
executors:
- name: encoder
uses:
jtype: CLIPEncoder
metas:
py_modules:
- clip_se
```{code-block} python
---
emphasize-lines: 4
---
from clip_client import Client
c = Client(
'grpcs://api.clip.jina.ai:2096', credential={'Authorization': ''}
)
r = c.encode(
[
'First do it',
'then do it right',
'th Community Discussions
Trending Discussions on jina
QUESTION
i have a table like this:
id person 20 adams 20 george 40 jina 46 rico 80 naya 90 john 90 peter 90 richardi want to find a way to select a new_id starting from 1 and increazing +1 every time id is different. for example i want a select with a result like this:
new_id id person 1 20 adams 1 20 george 2 40 jina 3 46 rico 4 80 naya 5 90 john 5 90 peter 5 90 richardis there any function in postgres doing something like that?
...ANSWER
Answered 2022-Feb-16 at 11:13use dense_rank()
QUESTION
In the dropdownlist field when option Jiná společnost: is selected I need to show that the JinaSpolecnostTextBox textbox
Can you help me?
...ANSWER
Answered 2022-Jan-27 at 10:00The issue in your code is because $('[PrimaGroupList]') isn't a valid selector. You need to use the 'attribute selector' to retrieve the element by its name. The code should look like this:
QUESTION
Context:
I have a Topic enum:
ANSWER
Answered 2021-Oct-12 at 17:05Flattening into tuples could help.
For example with:
QUESTION
I am getting one list of objects from the database and iterate through that list inside html page with thymeleaf engine using th:switch and th:each. Now I want to change one property from each object from this list to another format, The problem is how do I use those formatted value inside another list in switch statement in thymeleaf with it's corresponding object from the first list.
Below shows how I loop inside every object to get the value of getKinachoitajika() which is a double number that appears as 5.0E7 in output, now I format it so as to get a display of normal number like 50,000,000 and put those value into an ArrayList of arrItajika and use them inside html file while looping through the objects of the first list.
...ANSWER
Answered 2021-Mar-12 at 13:36If the indexes of both lists are equal, you can use th:each with an index. See Thymeleaf - How to loop a list by index
QUESTION
I try to generate csv file from json type data. These are my json test data.
...ANSWER
Answered 2020-Sep-26 at 07:47You can do it with a library Apache Commons IO
pom.xml
QUESTION
In my desktop version, I have some code that allows you to hover over a button to reveal some info/text. How do I reset this in mobile to not do anything at all when tapped on.
...ANSWER
Answered 2020-Sep-18 at 10:20Try with this media query
QUESTION
I am using MongoDB via mongoose.
What happens when you query an indexed field with a non-indexed field? See code below.
...
ANSWER
Answered 2020-Jun-21 at 07:39To understand what is happening under the hood in mongo queries, you can use explain. For example, consider the following query:
db.getCollection('users').find({"name":"ana"})
which queries a non-indexed field. You can use explain on this query as below:
db.getCollection('users').find({"name":"ana"}).explain("executionStats")
Part of the result is:
QUESTION
I have two dropdowns in my .html file of Django app namely:
...ANSWER
Answered 2020-Jun-19 at 14:35You can use Django's template rendering to populate the first dropdown, something like:
QUESTION
I am in my homepage template where I have only search box like google main search page looks like, Now I want to search variables from another template and display it but nothing happen. Below is my code
Homepage template
...ANSWER
Answered 2020-Jan-18 at 13:30If I understand you correctly you want to pass the q parameter from the form on your home page to the Miscellaneous view. Currently your code just calls your IndexView in submitting the form and returns to it.
I guess you are expecting that the form to submit to the Miscellaneous view by adding the url to onclick of your button. I do not think that works like that as onclick expects some javascript function. Your form submits to the url you put into the action attribute of your form, and this is your homepage.
So the simplest approach would be to change the action attribute of your form to point to your Miscellaneous view:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install jina
We promise you can build a scalable ResNet-powered image search service in 20 minutes or less, from scratch to Kubernetes. If not, you can forget about Jina.
Import what we need.
Import what we need. from docarray import Document, DocumentArray from jina import Executor, Flow, requests
Copy-paste the preprocessing step and wrap it via Executor: class PreprocImg(Executor): @requests async def foo(self, docs: DocumentArray, **kwargs): for d in docs: ( d.load_uri_to_image_tensor(200, 200) # load .set_image_tensor_normalization() # normalize color .set_image_tensor_channel_axis( -1, 0 ) # switch color axis for the PyTorch model later )
Copy-paste the embedding step and wrap it via Executor: class EmbedImg(Executor): def __init__(self, **kwargs): super().__init__(**kwargs) import torchvision self.model = torchvision.models.resnet50(pretrained=True) @requests async def foo(self, docs: DocumentArray, **kwargs): docs.embed(self.model)
Wrap the matching step into an Executor: class MatchImg(Executor): _da = DocumentArray() @requests(on='/index') async def index(self, docs: DocumentArray, **kwargs): self._da.extend(docs) docs.clear() # clear content to save bandwidth @requests(on='/search') async def foo(self, docs: DocumentArray, **kwargs): docs.match(self._da, limit=9) del docs[...][:, ('embedding', 'tensor')] # save bandwidth as it is not needed
Connect all Executors in a Flow, scale embedding to 3: f = ( Flow(port_expose=12345) .add(uses=PreprocImg) .add(uses=EmbedImg, replicas=3) .add(uses=MatchImg) ) Plot it via f.plot('flow.svg') and you get:
Download the image dataset.
Index image data: with f: f.post( '/index', index_data, show_progress=True, request_size=8, ) f.block()
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