Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

TypeError: unsupported operand type(s) for -: 'int' and 'simsimd.OutputDistances' #18022

Open
4 tasks done
mborho opened this issue Feb 23, 2024 · 4 comments
Open
4 tasks done

TypeError: unsupported operand type(s) for -: 'int' and 'simsimd.OutputDistances' #18022

mborho opened this issue Feb 23, 2024 · 4 comments
Labels
🤖:bug Related to a bug, vulnerability, unexpected error with an existing feature stale Issue has not had recent activity or appears to be solved. Stale issues will be automatically closed

Comments

@mborho
Copy link

mborho commented Feb 23, 2024 •
edited
Loading

Checked other resources

  • I added a very descriptive title to this issue.
  • I searched the LangChain documentation with the integrated search.
  • I used the GitHub search to find a similar question and didn't find it.
  • I am sure that this is a bug in LangChain rather than my code.

Example Code

print("?")

Error Message and Stack Trace (if applicable)

  File "/home/martin/dev/mlki/langchain/llmaa/env/lib/python3.10/site-packages/langchain_community/utils/math.py", line 29, in cosine_similarity
    Z = 1 - simd.cdist(X, Y, metric="cosine")
TypeError: unsupported operand type(s) for -: 'int' and 'simsimd.OutputDistances'

Description

Error came up after installing langchain v0.1.9 and the python bindings for simsimd v3.8.1.

After switching the python package to simsimd v3.7.7, the error disappeared.

Seems to be related to this change ashvardanian/SimSIMD@819a406

System Info

langchain==0.1.9
langchain-community==0.0.22
langchain-core==0.1.26
langchain-openai==0.0.7
langchainhub==0.1.14
@dosubot dosubot bot added the 🤖:bug Related to a bug, vulnerability, unexpected error with an existing feature label Feb 23, 2024
@andy-tmpt-me
Copy link

Confirming that in my setup (which generally picks up langchain latest), pinning simsimd == 3.7.7 resolved the issue.

@ravi-bhanabhai
Copy link

Still an issue with the newest simsimd.

>>> simsimd.__version__
'4.0.0'
>>> import langchain
>>> langchain.__version__
'0.1.13'
>>>

@ashvardanian
Copy link
Contributor

Hey! To convert to NumPy, you simply need to wrap the output tensor with np.array 🤗

We couldn't continue returning the NumPy array directly, because surprisingly to us, NumPy doesn't support most platforms. They only ship 35 binaries, while SimSIMD ships 105... and on some platforms, they don't even pass compilation.

ashvardanian added a commit to ashvardanian/langchain that referenced this issue Mar 23, 2024
@ashvardanian
Convert SimSIMD back to NumPy
cacf078 
Closes langchain-ai#18022
@ashvardanian ashvardanian mentioned this issue Mar 23, 2024
Merged
baskaryan pushed a commit that referenced this issue Mar 25, 2024
@ashvardanian
core[patch]: Convert SimSIMD back to NumPy (#19473)
d01bad5 
This patch fixes the #18022 issue, converting the SimSIMD internal
zero-copy outputs to NumPy.

I've also noticed, that oftentimes `dtype=np.float32` conversion is used
before passing to SimSIMD. Which numeric types do LangChain users
generally care about? We support `float64`, `float32`, `float16`, and
`int8` for cosine distances and `float16` seems reasonable for
practically any kind of embeddings and any modern piece of hardware, so
we can change that part as well 🤗
rahul-trip pushed a commit to daxa-ai/langchain that referenced this issue Mar 27, 2024
@ashvardanian @rahul-trip
core[patch]: Convert SimSIMD back to NumPy (langchain-ai#19473)
045a9a3 
This patch fixes the langchain-ai#18022 issue, converting the SimSIMD internal
zero-copy outputs to NumPy.

I've also noticed, that oftentimes `dtype=np.float32` conversion is used
before passing to SimSIMD. Which numeric types do LangChain users
generally care about? We support `float64`, `float32`, `float16`, and
`int8` for cosine distances and `float16` seems reasonable for
practically any kind of embeddings and any modern piece of hardware, so
we can change that part as well 🤗
bechbd pushed a commit to bechbd/langchain that referenced this issue Mar 29, 2024
@ashvardanian
core[patch]: Convert SimSIMD back to NumPy (langchain-ai#19473)
e52c835 
This patch fixes the langchain-ai#18022 issue, converting the SimSIMD internal
zero-copy outputs to NumPy.

I've also noticed, that oftentimes `dtype=np.float32` conversion is used
before passing to SimSIMD. Which numeric types do LangChain users
generally care about? We support `float64`, `float32`, `float16`, and
`int8` for cosine distances and `float16` seems reasonable for
practically any kind of embeddings and any modern piece of hardware, so
we can change that part as well 🤗
gkorland pushed a commit to FalkorDB/langchain that referenced this issue Mar 30, 2024
@ashvardanian @gkorland
core[patch]: Convert SimSIMD back to NumPy (langchain-ai#19473)
de1e53c 
This patch fixes the langchain-ai#18022 issue, converting the SimSIMD internal
zero-copy outputs to NumPy.

I've also noticed, that oftentimes `dtype=np.float32` conversion is used
before passing to SimSIMD. Which numeric types do LangChain users
generally care about? We support `float64`, `float32`, `float16`, and
`int8` for cosine distances and `float16` seems reasonable for
practically any kind of embeddings and any modern piece of hardware, so
we can change that part as well 🤗
chrispy-snps pushed a commit to chrispy-snps/langchain that referenced this issue Mar 30, 2024
@ashvardanian @chrispy-snps
core[patch]: Convert SimSIMD back to NumPy (langchain-ai#19473)
e66653d 
This patch fixes the langchain-ai#18022 issue, converting the SimSIMD internal
zero-copy outputs to NumPy.

I've also noticed, that oftentimes `dtype=np.float32` conversion is used
before passing to SimSIMD. Which numeric types do LangChain users
generally care about? We support `float64`, `float32`, `float16`, and
`int8` for cosine distances and `float16` seems reasonable for
practically any kind of embeddings and any modern piece of hardware, so
we can change that part as well 🤗
chrispy-snps pushed a commit to chrispy-snps/langchain that referenced this issue Mar 30, 2024
@ashvardanian @chrispy-snps
core[patch]: Convert SimSIMD back to NumPy (langchain-ai#19473)
07f43d8 
This patch fixes the langchain-ai#18022 issue, converting the SimSIMD internal
zero-copy outputs to NumPy.

I've also noticed, that oftentimes `dtype=np.float32` conversion is used
before passing to SimSIMD. Which numeric types do LangChain users
generally care about? We support `float64`, `float32`, `float16`, and
`int8` for cosine distances and `float16` seems reasonable for
practically any kind of embeddings and any modern piece of hardware, so
we can change that part as well 🤗
@rachel-pai rachel-pai mentioned this issue Apr 9, 2024
Open
5 tasks
@yaoyuansheng0403
Copy link

Confirming that in my setup (which generally picks up langchain latest), pinning simsimd == 3.7.7 resolved the issue.

it is helpful,my problem has solved. thank you

hinthornw pushed a commit that referenced this issue Apr 26, 2024
@ashvardanian @hinthornw
core[patch]: Convert SimSIMD back to NumPy (#19473)
446dac4 
This patch fixes the #18022 issue, converting the SimSIMD internal
zero-copy outputs to NumPy.

I've also noticed, that oftentimes `dtype=np.float32` conversion is used
before passing to SimSIMD. Which numeric types do LangChain users
generally care about? We support `float64`, `float32`, `float16`, and
`int8` for cosine distances and `float16` seems reasonable for
practically any kind of embeddings and any modern piece of hardware, so
we can change that part as well 🤗
@joydeepbroy-zeotap joydeepbroy-zeotap mentioned this issue May 29, 2024
Merged
3 tasks
baskaryan added a commit that referenced this issue Jun 4, 2024
@joydeepbroy-zeotap @baskaryan
community, milvus, pinecone, qdrant, mongo: Broadcast operation failu…
3796672 
…re while using simsimd beyond v3.7.7 (#22271)

- [ ] **Packages affected**: 
  - community: fix `cosine_similarity` to support simsimd beyond 3.7.7
- partners/milvus: fix `cosine_similarity` to support simsimd beyond
3.7.7
- partners/mongodb: fix `cosine_similarity` to support simsimd beyond
3.7.7
- partners/pinecone: fix `cosine_similarity` to support simsimd beyond
3.7.7
- partners/qdrant: fix `cosine_similarity` to support simsimd beyond
3.7.7


- [ ] **Broadcast operation failure while using simsimd beyond v3.7.7**:
- **Description:** I was using simsimd 4.3.1 and the unsupported operand
type issue popped up. When I checked out the repo and ran the tests,
they failed as well (have attached a screenshot for that). Looks like it
is a variant of #18022 .
Prior to 3.7.7, simd.cdist returned an ndarray but now it returns
simsimd.DistancesTensor which is ineligible for a broadcast operation
with numpy. With this change, it also remove the need to explicitly cast
`Z` to numpy array
    - **Issue:** #19905
    - **Dependencies:** No
    - **Twitter handle:** https://x.com/GetzJoydeep

<img width="1622" alt="Screenshot 2024-05-29 at 2 50 00 PM"
src="https://github.com/langchain-ai/langchain/assets/31132555/fb27b383-a9ae-4a6f-b355-6d503b72db56">

- [ ] **Considerations**: 
1. I started with community but since similar changes were there in
Milvus, MongoDB, Pinecone, and QDrant so I modified their files as well.
If touching multiple packages in one PR is not the norm, then I can
remove them from this PR and raise separate ones
2. I have run and verified that the tests work. Since, only MongoDB had
tests, I ran theirs and verified it works as well. Screenshots attached
:
<img width="1573" alt="Screenshot 2024-05-29 at 2 52 13 PM"
src="https://github.com/langchain-ai/langchain/assets/31132555/ce87d1ea-19b6-4900-9384-61fbc1a30de9">
<img width="1614" alt="Screenshot 2024-05-29 at 3 33 51 PM"
src="https://github.com/langchain-ai/langchain/assets/31132555/6ce1d679-db4c-4291-8453-01028ab2dca5">
  

I have added a test for simsimd. I feel it may not go well with the
CI/CD setup as installing simsimd is not a dependency requirement. I
have just imported simsimd to ensure simsimd cosine similarity is
invoked. However, its not a good approach. Suggestions are welcome and I
can make the required changes on the PR. Please provide guidance on the
same as I am new to the community.

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
hinthornw pushed a commit that referenced this issue Jun 20, 2024
@joydeepbroy-zeotap @baskaryan @hinthornw
community, milvus, pinecone, qdrant, mongo: Broadcast operation failu…
ee55b59 
…re while using simsimd beyond v3.7.7 (#22271)

- [ ] **Packages affected**: 
  - community: fix `cosine_similarity` to support simsimd beyond 3.7.7
- partners/milvus: fix `cosine_similarity` to support simsimd beyond
3.7.7
- partners/mongodb: fix `cosine_similarity` to support simsimd beyond
3.7.7
- partners/pinecone: fix `cosine_similarity` to support simsimd beyond
3.7.7
- partners/qdrant: fix `cosine_similarity` to support simsimd beyond
3.7.7


- [ ] **Broadcast operation failure while using simsimd beyond v3.7.7**:
- **Description:** I was using simsimd 4.3.1 and the unsupported operand
type issue popped up. When I checked out the repo and ran the tests,
they failed as well (have attached a screenshot for that). Looks like it
is a variant of #18022 .
Prior to 3.7.7, simd.cdist returned an ndarray but now it returns
simsimd.DistancesTensor which is ineligible for a broadcast operation
with numpy. With this change, it also remove the need to explicitly cast
`Z` to numpy array
    - **Issue:** #19905
    - **Dependencies:** No
    - **Twitter handle:** https://x.com/GetzJoydeep

<img width="1622" alt="Screenshot 2024-05-29 at 2 50 00 PM"
src="https://github.com/langchain-ai/langchain/assets/31132555/fb27b383-a9ae-4a6f-b355-6d503b72db56">

- [ ] **Considerations**: 
1. I started with community but since similar changes were there in
Milvus, MongoDB, Pinecone, and QDrant so I modified their files as well.
If touching multiple packages in one PR is not the norm, then I can
remove them from this PR and raise separate ones
2. I have run and verified that the tests work. Since, only MongoDB had
tests, I ran theirs and verified it works as well. Screenshots attached
:
<img width="1573" alt="Screenshot 2024-05-29 at 2 52 13 PM"
src="https://github.com/langchain-ai/langchain/assets/31132555/ce87d1ea-19b6-4900-9384-61fbc1a30de9">
<img width="1614" alt="Screenshot 2024-05-29 at 3 33 51 PM"
src="https://github.com/langchain-ai/langchain/assets/31132555/6ce1d679-db4c-4291-8453-01028ab2dca5">
  

I have added a test for simsimd. I feel it may not go well with the
CI/CD setup as installing simsimd is not a dependency requirement. I
have just imported simsimd to ensure simsimd cosine similarity is
invoked. However, its not a good approach. Suggestions are welcome and I
can make the required changes on the PR. Please provide guidance on the
same as I am new to the community.

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
@dosubot dosubot bot added the stale Issue has not had recent activity or appears to be solved. Stale issues will be automatically closed label Jul 10, 2024
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
🤖:bug Related to a bug, vulnerability, unexpected error with an existing feature stale Issue has not had recent activity or appears to be solved. Stale issues will be automatically closed
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
5 participants
@mborho @ashvardanian @yaoyuansheng0403 @ravi-bhanabhai @andy-tmpt-me