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fix(sambanova): update pricing, deprecate retired models, and add missing models #30016

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Merged
Sameerlite merged 11 commits into from
Jun 24, 2026
Merged

fix(sambanova): update pricing, deprecate retired models, and add missing models #30016

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376e65a
feat(bedrock): add amazon.titan-embed-g1-text-02 embedding model support
bhumikadangayach Jun 7, 2026
367dd83
style: fix syntax error, trailing whitespace and missing newline
bhumikadangayach Jun 7, 2026
ee4c727
style: apply black formatting to embedding.py
bhumikadangayach Jun 7, 2026
e1660c5
style: apply black formatting to test_bedrock_embedding.py
bhumikadangayach Jun 7, 2026
acb6dda
fix(sambanova): update pricing, fix context windows, add deprecation …
bhumikadangayach Jun 9, 2026
faf8640
fix(sambanova): sync model_prices_and_context_window_backup.json with…
bhumikadangayach Jun 9, 2026
a40fad9
fix(sambanova): fix indentation on Meta-Llama-3.2-1B-Instruct depreca…
bhumikadangayach Jun 9, 2026
8227c32
fix(bedrock): add amazon.titan-embed-g1-text-02 to unmapped model err…
bhumikadangayach Jun 9, 2026
5e0a3bb
style: apply black formatting to embedding.py
bhumikadangayach Jun 9, 2026
fd4bd10
fix(sambanova): correct indentation on DeepSeek-V3.2 entry
bhumikadangayach Jun 24, 2026
ba83bb7
fix(sambanova): replace gemma-3-12b-it with gemma-4-31B-it (verified …
bhumikadangayach Jun 24, 2026
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10 changes: 10 additions & 0 deletions litellm/llms/bedrock/embed/embedding.py
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Original file line number Diff line number Diff line change
Expand Up @@ -224,6 +224,10 @@ def _transform_response(
returned_response = AmazonTitanV2Config()._transform_response(
response_list=response_list, model=model
)
elif model == "amazon.titan-embed-g1-text-02":
returned_response = AmazonTitanG1Config()._transform_response(
response_list=response_list, model=model
)
elif provider == "twelvelabs":
returned_response = (
TwelveLabsMarengoEmbeddingConfig()._transform_response(
Expand Down Expand Up @@ -447,6 +451,7 @@ def embeddings(
"amazon.titan-embed-image-v1",
"amazon.titan-embed-text-v1",
"amazon.titan-embed-text-v2:0",
"amazon.titan-embed-g1-text-02",
]:
batch_data = []
for i in input:
Expand All @@ -464,6 +469,10 @@ def embeddings(
transformed_request = AmazonTitanV2Config()._transform_request(
input=i, inference_params=inference_params
)
elif model == "amazon.titan-embed-g1-text-02":
transformed_request = AmazonTitanG1Config()._transform_request(
input=i, inference_params=inference_params
)
else:
raise Exception(
"Unmapped model. Received={}. Expected={}".format(
Expand All @@ -472,6 +481,7 @@ def embeddings(
"amazon.titan-embed-image-v1",
"amazon.titan-embed-text-v1",
"amazon.titan-embed-text-v2:0",
"amazon.titan-embed-g1-text-02",
],
)
)
Expand Down
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