From 07c633be3aa779f0330c77b25ae35f5a72d3b6f0 Mon Sep 17 00:00:00 2001
From: bhumikadangayach <dangayach.bhumika18@gmail.com>
Date: Sun, 7 Jun 2026 18:30:36 +0530
Subject: [PATCH] feat(bedrock): add amazon.titan-embed-g1-text-02 embedding
 model support

- Add model to provider routing allowlist in embedding.py
- Add request transformation using AmazonTitanG1Config
- Add response transformation using AmazonTitanG1Config
- Add pricing metadata to model_prices_and_context_window.json
- Add unit tests for embedding and model info

Fixes missing cost tracking reported in #29786
Related to VANDRANKI/litellm PR #29790
---
 litellm/llms/bedrock/embed/embedding.py         |  9 +++++++++
 model_prices_and_context_window.json            |  9 +++++++++
 tests/llm_translation/test_bedrock_embedding.py | 13 +++++++++++++
 3 files changed, 31 insertions(+)

diff --git a/litellm/llms/bedrock/embed/embedding.py b/litellm/llms/bedrock/embed/embedding.py
index 27dc785bf57..f78095a6d51 100644
--- a/litellm/llms/bedrock/embed/embedding.py
+++ b/litellm/llms/bedrock/embed/embedding.py
@@ -224,6 +224,10 @@ class BedrockEmbedding(BaseAWSLLM):
                 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(
@@ -447,6 +451,7 @@ class BedrockEmbedding(BaseAWSLLM):
             "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:
@@ -464,6 +469,10 @@ class BedrockEmbedding(BaseAWSLLM):
                     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(
diff --git a/model_prices_and_context_window.json b/model_prices_and_context_window.json
index b2836a096b7..127b1f20e2e 100644
--- a/model_prices_and_context_window.json
+++ b/model_prices_and_context_window.json
@@ -570,6 +570,15 @@
         "output_cost_per_token": 0.0,
         "output_vector_size": 1536
     },
+    "amazon.titan-embed-g1-text-02": {
+        "input_cost_per_token": 1e-07,
+        "litellm_provider": "bedrock",
+        "max_input_tokens": 8192,
+        "max_tokens": 8192,
+        "mode": "embedding",
+        "output_cost_per_token": 0.0,
+        "output_vector_size": 1536
+    },
     "amazon.titan-embed-text-v2:0": {
         "input_cost_per_token": 2e-07,
         "litellm_provider": "bedrock",
diff --git a/tests/llm_translation/test_bedrock_embedding.py b/tests/llm_translation/test_bedrock_embedding.py
index 92c22f582d9..feda016bd9f 100644
--- a/tests/llm_translation/test_bedrock_embedding.py
+++ b/tests/llm_translation/test_bedrock_embedding.py
@@ -34,6 +34,11 @@ img_base_64 = "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAGQAAABkBAMAAACCzIh
             "text",
             titan_embedding_response,
         ),  # V2 text model
+        (
+            "bedrock/amazon.titan-embed-g1-text-02",
+            "text",
+            titan_embedding_response,
+        ),  # G1 text model
         (
             "bedrock/amazon.titan-embed-image-v1",
             "image",
@@ -459,3 +464,11 @@ def test_bedrock_embedding_region_bug_reproduction():
             os.environ["AWS_REGION_NAME"] = original_region_name
         else:
             os.environ.pop("AWS_REGION_NAME", None)
+def test_bedrock_titan_g1_text_02_model_info():
+    """Test that amazon.titan-embed-g1-text-02 has correct pricing metadata"""
+    model_info = litellm.get_model_info("amazon.titan-embed-g1-text-02")
+    assert model_info is not None, "Model info should not be None"
+    assert model_info["litellm_provider"] == "bedrock"
+    assert model_info["mode"] == "embedding"
+    assert model_info["input_cost_per_token"] == 1e-07
+    assert model_info["max_input_tokens"] == 8192
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