* embeddings/vertexai,memory: remove deprecated PaLM test and add recordings
Remove deprecated VertexAI PaLM embeddings test (PaLM API deprecated August 2024).
Add missing test recordings for memory/token buffer tests.
* vectorstores/redisvector: regenerate test recordings and compress
Regenerate test recordings for Docker container compatibility.
Compress large recordings (>50KB) with gzip for space efficiency.
* vectorstores/chroma: regenerate test recordings and compress
Regenerate test recordings for Docker container compatibility.
Compress large recordings (>50KB) with gzip for space efficiency.
* vectorstores/milvus: add deprecation notice and compress recordings
Add deprecation notice for Milvus vectorstore.
Compress test recordings with gzip for space efficiency.
* vectorstores/opensearch: regenerate test recordings and compress
Regenerate test recordings for Docker container compatibility.
Fix test to properly set up service_role for local tests.
Compress large recordings with gzip for space efficiency.
* vectorstores/weaviate: regenerate test recordings and compress
Regenerate test recordings for Docker container compatibility.
Compress large recordings (>50KB) with gzip for space efficiency.
* vectorstores/{pgvector,alloydb,cloudsql}: regenerate and compress recordings
Regenerate test recordings for Docker container compatibility.
Compress large recordings (>50KB) with gzip for space efficiency.
Covers pgvector, AlloyDB, and CloudSQL PostgreSQL vectorstores.
* tools/wikipedia: regenerate test recordings
Update test recordings with current Wikipedia API responses.
* all: add broad httprr coverage, update dependencies, organize go.mod file, bump to 1.23
update go version to 1.23
add lots of test coverage via httprr recordings
update dependencies and organize go.mod
add testutil/testctr which helps work around a testcontainers-go+colima bug
expand the huggingface implementation and tests
expand capabilities of the ollama package
It's not used and not implemented correctly for almost any model.
If this is deemed useful, it will be more correct to expose a model name
from the LLM (or cliena?) and then invoke a standalone function familiar
with non-openai models.
Re #482
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