Generate text from machine-learning models right in your browser
alexcg1/jina-streamlit-frontend 1
A simple front-end for Jina neural search framework, written in Streamlit, that supports querying with image, text, or drawing on a canvas.
Convert mediawiki pages into beautiful PDF books
Personal README
Alex C-G's personal website
repository for OpenSCAD scripts for e-nable project
A curated list of amazingly awesome articles, websites and resources about diversity in technology.
alexcg1/comics-on-microsoft-surface-with-linux 0
Using Linux to read comicbooks on a Microsoft Surface sucks. Here's how to improve the experience
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issue commentjina-ai/jina
Periodical health check of pods/peas
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issue commentjina-ai/jina
can not run on pypy3.7 as pypy does not fully support numpy and grpcio
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chore(version): the next version will be 0.8.3
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pull request commentjina-ai/jina
@JoanFM how about
MultimodalDocument.from_content_modality_mapping({'visual': xxx, 'textual': xxx})Where xxx could be content or embedding. this classmethod has the same naming convention as the property
MultimodalDocument.content_modality_mappingThis is what I meant yes. The problem we have is that is not easy to tell if the content when is a numpy array if it is embedding or content. So we need a flag to say that.
Well i thought it twice and no, I think is better to assume they arr created from content so u assume the chunks are filled by document. But make sure it is documented that if one chunk is created from embeddings they will need to create from the other interface
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pull request commentjina-ai/jina
Also I think that this class should have better care of setting the right granularity parameters for the MultiModalDocument and the chunks. (Not so important but needed for the sake of coherence)
Agreed, I'll create a getter & setter in :class:Document to expose granularity, now we can only access the property from :class:DocumentProto
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pull request commentjina-ai/jina
@JoanFM how about
MultimodalDocument.from_content_modality_mapping({'visual': xxx, 'textual': xxx})Where xxx could be content or embedding. this classmethod has the same naming convention as the property
MultimodalDocument.content_modality_mapping
This is what I meant yes. The problem we have is that is not easy to tell if the content when is a numpy array if it is embedding or content. So we need a flag to say that.
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pull request commentjina-ai/jina
@JoanFM how about
MultimodalDocument.from_content_modality_mapping({'visual': xxx, 'textual': xxx})
Where xxx could be content or embedding. this classmethod has the same naming convention as the property MultimodalDocument.content_modality_mapping
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issue commentjina-ai/jina
Refactoring document creation and access in unit tests
The first step is to use random_docs_new_api instead of random_docs Done in #1356
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pull request commentjina-ai/jina
refactor chunkset and matchset append method
Codecov Report
Merging #1372 (81df8fa) into master (54c501d) will increase coverage by
0.04%. The diff coverage is100.00%.
@@ Coverage Diff @@
## master #1372 +/- ##
==========================================
+ Coverage 82.99% 83.04% +0.04%
==========================================
Files 103 103
Lines 6746 6759 +13
==========================================
+ Hits 5599 5613 +14
+ Misses 1147 1146 -1
| Impacted Files | Coverage Δ | |
|---|---|---|
| jina/types/sets/chunk_set.py | 100.00% <100.00%> (ø) |
|
| jina/types/sets/document_set.py | 98.24% <100.00%> (+15.78%) |
:arrow_up: |
| jina/types/sets/match_set.py | 100.00% <100.00%> (ø) |
|
| jina/peapods/grpc_asyncio.py | 76.53% <0.00%> (-7.15%) |
:arrow_down: |
| jina/logging/sse.py | 91.93% <0.00%> (-3.23%) |
:arrow_down: |
| jina/types/document/__init__.py | 97.30% <0.00%> (+0.44%) |
:arrow_up: |
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feat: manually update document id for chunk
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feat: refactor chunkset matchset append method
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feat: refactor chunkset matchset append method
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feat: refactor chunkset matchset append method
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feat: refactor chunkset matchset append method
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feat(flow): pretty print flow obj in ipython (#1373)
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pull request commentjina-ai/jina
feat(flow): pretty print flow obj in ipython
Codecov Report
Merging #1373 (075af9f) into master (54c501d) will increase coverage by
0.05%. The diff coverage is100.00%.
@@ Coverage Diff @@
## master #1373 +/- ##
==========================================
+ Coverage 82.99% 83.05% +0.05%
==========================================
Files 103 103
Lines 6746 6746
==========================================
+ Hits 5599 5603 +4
+ Misses 1147 1143 -4
| Impacted Files | Coverage Δ | |
|---|---|---|
| jina/types/sets/document_set.py | 98.24% <100.00%> (+15.78%) |
:arrow_up: |
| jina/peapods/grpc_asyncio.py | 75.51% <0.00%> (-8.17%) |
:arrow_down: |
| jina/types/document/__init__.py | 97.30% <0.00%> (+0.44%) |
:arrow_up: |
| jina/drivers/querylang/select.py | 86.20% <0.00%> (+6.89%) |
:arrow_up: |
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refactor(gateway): clean code, move file structure (#1371) * refactor(gateway): clean code, move file structure * refactor(proto): jina primitive types
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PR merged jina-ai/jina
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pull request commentjina-ai/jina
refactor chunkset append method
Makes sense ! Thanks for clarification
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pull request commentjina-ai/jina
refactor chunkset append method
Why does it exist thr class ChunkSet and is not merged with DocumentSet?
ChunkSet and MatchSet are inherited from DocumentSet, I did it on purpose to abstract the logic of add_chunk and add_match
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feat: refactor chunkset append method
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