Python: postgres memory store #1354
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
@microsoft-github-policy-service agree |
|
Working on change to conform to new Memory Record field |
dmytrostruk
reviewed
Jun 28, 2023
There was a problem hiding this comment.
@cschadewitz Thank you for contribution! I left initial comments. As soon as they are resolved, we will test it locally and if everything works as expected - merge it to main! 😃
python/semantic_kernel/connectors/memory/postgres/postgres_memory_store.py
Show resolved
Hide resolved
python/semantic_kernel/connectors/memory/postgres/postgres_memory_store.py
Outdated
Show resolved
Hide resolved
python/semantic_kernel/connectors/memory/postgres/postgres_memory_store.py
Outdated
Show resolved
Hide resolved
python/semantic_kernel/connectors/memory/postgres/postgres_memory_store.py
Outdated
Show resolved
Hide resolved
dmytrostruk
added
PR: feedback to address
Co-authored-by: Dmytro Struk <13853051+dmytrostruk@users.noreply.github.com>
Co-authored-by: Dmytro Struk <13853051+dmytrostruk@users.noreply.github.com>
github-actions
bot
added
the
docs and tests
dmytrostruk
reviewed
Jul 7, 2023
There was a problem hiding this comment.
@cschadewitz Thank you for all the hard work! I left some comments, but some of them can be definitely resolved in scope of follow-up PR. I think the most important one which should be resolved before merging to main is regarding timezones, please find the details under my comment. Thanks again!
Thanks again!
python/semantic_kernel/connectors/memory/postgres/postgres_memory_store.py
Outdated
Show resolved
Hide resolved
python/semantic_kernel/connectors/memory/postgres/postgres_memory_store.py
Outdated
Show resolved
Hide resolved
python/semantic_kernel/connectors/memory/postgres/postgres_memory_store.py
Show resolved
Hide resolved
python/semantic_kernel/connectors/memory/postgres/postgres_memory_store.py
Outdated
Show resolved
Hide resolved
python/semantic_kernel/connectors/memory/postgres/postgres_memory_store.py
Show resolved
Hide resolved
…hadewitz/semantic-kernel_python-pinecone-connector into python_postgres_memory_store
…opg (psycopg-binary) is not recommened for production dependencies)
…hadewitz/semantic-kernel into python_postgres_memory_store
|
Hi @cschadewitz - I'm setting up infra to be able to run the integration tests in CI. As soon as that's set up, we'll get this in asap. |
awharrison-28
approved these changes
Jul 11, 2023
awharrison-28
removed
the
PR: feedback to address
|
Great work @cschadewitz , wondering if there is any pre-release i can use to test it ? |
Funny you should ask, I made a request for python to get nightly/pre-release builds during yesterdays community hour. Here is another community member that wants pre-release pip packages @alexchaomander . |
|
for now i download the code and added a reference to this file so i can test my kernel with this memory connector, if i find a problem will report here, thanks again for putting it together. |
piotrek-appstream
pushed a commit
to Appstream-Studio/semantic-kernel
that referenced
this pull request
Jul 19, 2023
### Motivation and Context <!-- Thank you for your contribution to the semantic-kernel repo! Please help reviewers and future users, providing the following information: 1. Why is this change required? Brings parity to python implementation 2. What problem does it solve? With the pgvector extension, Postgres is a viable option for the storing of embeddings for memory in Semantic Kernel. The C# implementation is already capable of this, but the feature has yet to be added to python. 3. What scenario does it contribute to? Additional options for memory storage 4. If it fixes an open issue, please link to the issue here. --> ### Description Implemention of the MemoryStore to use a Postgresql (with pgvector extension) to resolve microsoft#1270 Taking a different approach from the .net implementation: Collections as postgres schemas as opposed to collection being another column in the table, willing to change to match but would love to have a discussion comparing the options. ### Contribution Checklist <!-- Before submitting this PR, please make sure: --> - [x] The code builds clean without any errors or warnings - [x] The PR follows SK Contribution Guidelines (https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md) - [x] The code follows the .NET coding conventions (https://learn.microsoft.com/dotnet/csharp/fundamentals/coding-style/coding-conventions) verified with `dotnet format` - [x] All unit tests pass, and I have added new tests where possible - [x] I didn't break anyone 😄 --------- Co-authored-by: Dmytro Struk <13853051+dmytrostruk@users.noreply.github.com> Co-authored-by: Shawn Callegari <36091529+shawncal@users.noreply.github.com> Co-authored-by: Abby Harrison <abby.harrison@microsoft.com> Co-authored-by: Abby Harrison <54643756+awharrison-28@users.noreply.github.com>
johnoliver
pushed a commit
to johnoliver/semantic-kernel
that referenced
this pull request
Jun 5, 2024
### Motivation and Context <!-- Thank you for your contribution to the semantic-kernel repo! Please help reviewers and future users, providing the following information: 1. Why is this change required? Brings parity to python implementation 2. What problem does it solve? With the pgvector extension, Postgres is a viable option for the storing of embeddings for memory in Semantic Kernel. The C# implementation is already capable of this, but the feature has yet to be added to python. 3. What scenario does it contribute to? Additional options for memory storage 4. If it fixes an open issue, please link to the issue here. --> ### Description Implemention of the MemoryStore to use a Postgresql (with pgvector extension) to resolve microsoft#1270 Taking a different approach from the .net implementation: Collections as postgres schemas as opposed to collection being another column in the table, willing to change to match but would love to have a discussion comparing the options. ### Contribution Checklist <!-- Before submitting this PR, please make sure: --> - [x] The code builds clean without any errors or warnings - [x] The PR follows SK Contribution Guidelines (https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md) - [x] The code follows the .NET coding conventions (https://learn.microsoft.com/dotnet/csharp/fundamentals/coding-style/coding-conventions) verified with `dotnet format` - [x] All unit tests pass, and I have added new tests where possible - [x] I didn't break anyone 😄 --------- Co-authored-by: Dmytro Struk <13853051+dmytrostruk@users.noreply.github.com> Co-authored-by: Shawn Callegari <36091529+shawncal@users.noreply.github.com> Co-authored-by: Abby Harrison <abby.harrison@microsoft.com> Co-authored-by: Abby Harrison <54643756+awharrison-28@users.noreply.github.com>
johnoliver
pushed a commit
to johnoliver/semantic-kernel
that referenced
this pull request
Jun 5, 2024
### Motivation and Context <!-- Thank you for your contribution to the semantic-kernel repo! Please help reviewers and future users, providing the following information: 1. Why is this change required? Brings parity to python implementation 2. What problem does it solve? With the pgvector extension, Postgres is a viable option for the storing of embeddings for memory in Semantic Kernel. The C# implementation is already capable of this, but the feature has yet to be added to python. 3. What scenario does it contribute to? Additional options for memory storage 4. If it fixes an open issue, please link to the issue here. --> ### Description Implemention of the MemoryStore to use a Postgresql (with pgvector extension) to resolve microsoft#1270 Taking a different approach from the .net implementation: Collections as postgres schemas as opposed to collection being another column in the table, willing to change to match but would love to have a discussion comparing the options. ### Contribution Checklist <!-- Before submitting this PR, please make sure: --> - [x] The code builds clean without any errors or warnings - [x] The PR follows SK Contribution Guidelines (https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md) - [x] The code follows the .NET coding conventions (https://learn.microsoft.com/dotnet/csharp/fundamentals/coding-style/coding-conventions) verified with `dotnet format` - [x] All unit tests pass, and I have added new tests where possible - [x] I didn't break anyone 😄 --------- Co-authored-by: Dmytro Struk <13853051+dmytrostruk@users.noreply.github.com> Co-authored-by: Shawn Callegari <36091529+shawncal@users.noreply.github.com> Co-authored-by: Abby Harrison <abby.harrison@microsoft.com> Co-authored-by: Abby Harrison <54643756+awharrison-28@users.noreply.github.com>
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Motivation and Context
Description
Implemention of the MemoryStore to use a Postgresql (with pgvector extension) to resolve #1270
Taking a different approach from the .net implementation:
Collections as postgres schemas as opposed to collection being another column in the table, willing to change to match but would love to have a discussion comparing the options.
Contribution Checklist
dotnet format