feat: postgres vector store

[carlos-verdes]

Resolves #5 based on PR #157

@milancermak mentioned not having time to finish his PR so I created this one based on his implementation.

Current code has just the library code but I added an integration test based on rig-qdrant module, it starts a Docker container with Postgres + PgVector and it simulate calls to OpenAI using a mocked API.

Difference from previous PR:

• removed static lifetime
• the documents are stored as json in the database so you can use any type that implements Serializable, Deserializable
• support for more than one embedding per document (this also is not supported in rig-qdrant that only takes first vector), in the case more than one result hit the same document only nearest one is returned.
• use sqlx instead of tokio-postgres
• creation of database is outside the code and I provide example of setup in integration test (using sqlx migrations)
• you can use any distance filter supported by PgVector (is not hardcoded to cosine)
• Created example that can be launch using make run (from rig-postgres folder), load environmental variables from .env file and handles documents with more than one embedding. It also runs migrations automatically on the database to make sure Postgres tables are ready for the test.

Pending:

• add documentation

[carlos-verdes]

@0xMochan @cvauclair do you mind taking a look into this?

[cvauclair]

Hey @carlos-verdes just saw your ping, wasn't sure if the PR was ready for review since it's still a draft but I'll take a look later today!

Thanks a lot for the PR, let's get this postgres integration done 🦾

[carlos-verdes]

It's in draft because documentation is not finished, but the code + example + integration test is ready.

I can add later an example using Streams if that would be useful!

[cvauclair]

Looks solid! I added a couple suggestions/comments, please take a look when you have a moment.

Cheers!

[carlos-verdes]

@cvauclair thanks for the review, I updated code based on your comments, take a look and let me know if you want to squash the commits.

[cvauclair]

Awesome work, thanks for the contribution @carlos-verdes !