add back deprecated api [v0.9.48] (#10581)

CHANGELOG.md

 # ChangeLog
 
+## [0.9.48] - 2024-02-12
+
+### Bug Fixes / Nits
+
+- Add back deprecated API for BedrockEmbdding (#10581)
+
 ## [0.9.47] - 2024-02-11
 
 Last patch before v0.10!

llama_index/VERSION

-0.9.47
+0.9.48

llama_index/embeddings/bedrock.py

 import json
+import os
+import warnings
 from enum import Enum
 from typing import Any, Callable, Dict, List, Literal, Optional, Sequence
 
+from deprecated import deprecated
+
 from llama_index.bridge.pydantic import Field, PrivateAttr
 from llama_index.callbacks.base import CallbackManager
+from llama_index.constants import DEFAULT_EMBED_BATCH_SIZE
 from llama_index.core.embeddings.base import BaseEmbedding, Embedding
 from llama_index.core.llms.types import ChatMessage
 from llama_index.types import BaseOutputParser, PydanticProgramMode
@@ -166,6 +171,153 @@ class BedrockEmbedding(BaseEmbedding):
     def class_name(self) -> str:
         return "BedrockEmbedding"
 
+    @deprecated(
+        version="0.9.48",
+        reason=(
+            "Use the provided kwargs in the constructor, "
+            "set_credentials will be removed in future releases."
+        ),
+        action="once",
+    )
+    def set_credentials(
+        self,
+        aws_region: Optional[str] = None,
+        aws_access_key_id: Optional[str] = None,
+        aws_secret_access_key: Optional[str] = None,
+        aws_session_token: Optional[str] = None,
+        aws_profile: Optional[str] = None,
+    ) -> None:
+        aws_region = aws_region or os.getenv("AWS_REGION")
+        aws_access_key_id = aws_access_key_id or os.getenv("AWS_ACCESS_KEY_ID")
+        aws_secret_access_key = aws_secret_access_key or os.getenv(
+            "AWS_SECRET_ACCESS_KEY"
+        )
+        aws_session_token = aws_session_token or os.getenv("AWS_SESSION_TOKEN")
+
+        if aws_region is None:
+            warnings.warn(
+                "AWS_REGION not found. Set environment variable AWS_REGION or set aws_region"
+            )
+
+        if aws_access_key_id is None:
+            warnings.warn(
+                "AWS_ACCESS_KEY_ID not found. Set environment variable AWS_ACCESS_KEY_ID or set aws_access_key_id"
+            )
+            assert aws_access_key_id is not None
+
+        if aws_secret_access_key is None:
+            warnings.warn(
+                "AWS_SECRET_ACCESS_KEY not found. Set environment variable AWS_SECRET_ACCESS_KEY or set aws_secret_access_key"
+            )
+            assert aws_secret_access_key is not None
+
+        if aws_session_token is None:
+            warnings.warn(
+                "AWS_SESSION_TOKEN not found. Set environment variable AWS_SESSION_TOKEN or set aws_session_token"
+            )
+            assert aws_session_token is not None
+
+        session_kwargs = {
+            "profile_name": aws_profile,
+            "region_name": aws_region,
+            "aws_access_key_id": aws_access_key_id,
+            "aws_secret_access_key": aws_secret_access_key,
+            "aws_session_token": aws_session_token,
+        }
+
+        try:
+            import boto3
+
+            session = boto3.Session(**session_kwargs)
+        except ImportError:
+            raise ImportError(
+                "boto3 package not found, install with" "'pip install boto3'"
+            )
+
+        if "bedrock-runtime" in session.get_available_services():
+            self._client = session.client("bedrock-runtime")
+        else:
+            self._client = session.client("bedrock")
+
+    @classmethod
+    @deprecated(
+        version="0.9.48",
+        reason=(
+            "Use the provided kwargs in the constructor, "
+            "set_credentials will be removed in future releases."
+        ),
+        action="once",
+    )
+    def from_credentials(
+        cls,
+        model_name: str = Models.TITAN_EMBEDDING,
+        aws_region: Optional[str] = None,
+        aws_access_key_id: Optional[str] = None,
+        aws_secret_access_key: Optional[str] = None,
+        aws_session_token: Optional[str] = None,
+        aws_profile: Optional[str] = None,
+        embed_batch_size: int = DEFAULT_EMBED_BATCH_SIZE,
+        callback_manager: Optional[CallbackManager] = None,
+        verbose: bool = False,
+    ) -> "BedrockEmbedding":
+        """
+        Instantiate using AWS credentials.
+
+        Args:
+            model_name (str) : Name of the model
+            aws_access_key_id (str): AWS access key ID
+            aws_secret_access_key (str): AWS secret access key
+            aws_session_token (str): AWS session token
+            aws_region (str): AWS region where the service is located
+            aws_profile (str): AWS profile, when None, default profile is chosen automatically
+
+        Example:
+                .. code-block:: python
+
+                    from llama_index.embeddings import BedrockEmbedding
+
+                    # Define the model name
+                    model_name = "your_model_name"
+
+                    embeddings = BedrockEmbedding.from_credentials(
+                        model_name,
+                        aws_access_key_id,
+                        aws_secret_access_key,
+                        aws_session_token,
+                        aws_region,
+                        aws_profile,
+                    )
+
+        """
+        session_kwargs = {
+            "profile_name": aws_profile,
+            "region_name": aws_region,
+            "aws_access_key_id": aws_access_key_id,
+            "aws_secret_access_key": aws_secret_access_key,
+            "aws_session_token": aws_session_token,
+        }
+
+        try:
+            import boto3
+
+            session = boto3.Session(**session_kwargs)
+        except ImportError:
+            raise ImportError(
+                "boto3 package not found, install with" "'pip install boto3'"
+            )
+
+        if "bedrock-runtime" in session.get_available_services():
+            client = session.client("bedrock-runtime")
+        else:
+            client = session.client("bedrock")
+        return cls(
+            client=client,
+            model_name=model_name,
+            embed_batch_size=embed_batch_size,
+            callback_manager=callback_manager,
+            verbose=verbose,
+        )
+
     def _get_embedding(self, payload: str, type: Literal["text", "query"]) -> Embedding:
         if self._client is None:
             self.set_credentials()

pyproject.toml

@@ -42,7 +42,7 @@ name = "llama-index"
 packages = [{include = "llama_index"}]
 readme = "README.md"
 repository = "https://github.com/run-llama/llama_index"
-version = "0.9.47"
+version = "0.9.48"
 
 [tool.poetry.dependencies]
 SQLAlchemy = {extras = ["asyncio"], version = ">=1.4.49"}