# AWS Bedrock invalid template issue **URL:** \ **Category:** Support\ **Tags:** integration, python\ **Created:** [November 8, 2024, 9:17pm UTC](https://forum.weaviate.io/t/aws-bedrock-invalid-template-issue/7515 "2024-11-08T21:17:44Z")\ **Posts on this page:** 3\ **Page:** 1
**Author:** ![taigofranca](https://yyz1.discourse-cdn.com/flex027/user_avatar/forum.weaviate.io/taigofranca/32/2835_2.png) [@taigofranca](https://forum.weaviate.io/u/taigofranca)\ **Post date:** [November 8, 2024, 9:17pm UTC](https://forum.weaviate.io/t/aws-bedrock-invalid-template-issue/7515/1 "2024-11-08T21:17:44Z")
### Description I have the following code: ```python import weaviate from weaviate.classes.config import Configure from langchain.text_splitter import RecursiveCharacterTextSplitter from langchain_aws import BedrockEmbeddings from langchain.document_loaders import PyPDFLoader from langchain_weaviate.vectorstores import WeaviateVectorStore headers = { "X-AWS-Access-Key": "my_access_key", "X-AWS-Secret-Key": "my_secret_key", } client = weaviate.connect_to_local(headers=headers) try: print('Client is ready? ', client.is_ready()) client.collections.delete("MPVirtual") client.collections.create( "MPVirtual", vectorizer_config=Configure.NamedVectors.text2vec_aws( name="MPVirtual", region="sa-east-1", service="bedrock", model="amazon.titan-embed-text-v2:0" ), generative_config=Configure.Generative.aws( region="sa-east-1", service="bedrock", model="amazon.titan-text-express-v1" ) ) text_splitter = RecursiveCharacterTextSplitter(chunk_size=400, chunk_overlap=50) embeddings = BedrockEmbeddings() loader = PyPDFLoader("my_pdf_file.pdf", extract_images=False) docs = loader.load_and_split(text_splitter) print(f"GOT {len(docs)} docs for PDF") db = WeaviateVectorStore.from_documents(docs, embeddings, client=client, index_name="MPVirtual") collection = client.collections.get("MPVirtual") response = collection.aggregate.over_all(total_count=True) print(response) response = collection.aggregate.over_all(group_by="source") for group in response.groups: print(group.grouped_by.value, group.total_count) object = collection.query.fetch_objects(limit=1).objects[0] print(object.properties.keys()) finally: client.close() ``` When I run the script, the following error occurs: ```bash Client is ready? True GOT 66 docs for PDF ERROR:root:Error raised by inference endpoint: An error occurred (ValidationException) when calling the InvokeModel operation: The provided model identifier is invalid. Traceback (most recent call last): File "/my_folder/IA/mpvirtual/teste.py", line 44, in db = WeaviateVectorStore.from_documents(docs, embeddings, client=client, index_name="MPVirtual") ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/my_folder/IA/mpvirtual/.venv/lib/python3.11/site-packages/langchain_core/vectorstores/base.py", line 852, in from_documents return cls.from_texts(texts, embedding, metadatas=metadatas, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/my_folder/IA/mpvirtual/.venv/lib/python3.11/site-packages/langchain_weaviate/vectorstores.py", line 487, in from_texts weaviate_vector_store.add_texts(texts, metadatas, tenant=tenant, **kwargs) File "/my_folder/IA/mpvirtual/.venv/lib/python3.11/site-packages/langchain_weaviate/vectorstores.py", line 165, in add_texts embeddings = self._embedding.embed_documents(list(texts)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/my_folder/IA/mpvirtual/.venv/lib/python3.11/site-packages/langchain_aws/embeddings/bedrock.py", line 178, in embed_documents response = self._embedding_func(text) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/my_folder/IA/mpvirtual/.venv/lib/python3.11/site-packages/langchain_aws/embeddings/bedrock.py", line 159, in _embedding_func raise e File "/my_folder/IA/mpvirtual/.venv/lib/python3.11/site-packages/langchain_aws/embeddings/bedrock.py", line 144, in _embedding_func response = self.client.invoke_model( ^^^^^^^^^^^^^^^^^^^^^^^^^ File "/my_folder/IA/mpvirtual/.venv/lib/python3.11/site-packages/botocore/client.py", line 569, in _api_call return self._make_api_call(operation_name, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/my_folder/IA/mpvirtual/.venv/lib/python3.11/site-packages/botocore/client.py", line 1023, in _make_api_call raise error_class(parsed_response, operation_name) botocore.errorfactory.ValidationException: An error occurred (ValidationException) when calling the InvokeModel operation: The provided model identifier is invalid. ``` I copied the names of the models from this link: > **[AWS + Weaviate | Weaviate Documentation](https://docs.weaviate.io/weaviate/model-providers/aws)** > > AWS offers a wide range of models for natural language processing and generation. Weaviate seamlessly integrates with AWS's APIs, allowing users to leverage AWS's models directly from the Weaviate Database. The user has the necessary accesses. I really believe I’m doing something wrong. Can you help me solve this problem? I’m just starting out in this world of vector banks, RAG and GenIA. ### Server Setup Information - Weaviate Server Version: 1.27.0 - Deployment Method: Local - Multi Node? No - Client Language and Version: Python 3.11 - Multitenancy? No ---
**Author:** ![DudaNogueira](https://yyz1.discourse-cdn.com/flex027/user_avatar/forum.weaviate.io/dudanogueira/32/7846_2.png) [@DudaNogueira](https://forum.weaviate.io/u/DudaNogueira)\ **Post date:** [November 10, 2024, 12:07pm UTC](https://forum.weaviate.io/t/aws-bedrock-invalid-template-issue/7515/2 "2024-11-10T12:07:37Z")
Oi @taigofranca !! Welcome to our community 🤗 I believe that the issue here is that by default, `BedrockEmbeddings` from langchain will grab the credentials from `~/.aws/credentials`, while Weaviate will accept those in headers. So now you need to make sure that you pass a working langchain embeddings object, like so: ```python from langchain_aws import BedrockEmbeddings embeddings = BedrockEmbeddings(model_id="amazon.titan-embed-text-v2:0", credentials_profile_name="my_cool_aws_profile") result = embeddings.embed_query("This is a test") print(result) ``` I was able to run a basic insert/generate with this code, but this will only Weaviate, and rely on the credentials you pass at the client instantiation ```python from weaviate.classes.config import Configure client.collections.delete("DemoCollection") collection = client.collections.create( "DemoCollection", vectorizer_config=[ Configure.NamedVectors.text2vec_aws( name="title_vector", region="sa-east-1", source_properties=["title"], service="bedrock", model="amazon.titan-embed-text-v2:0", ) ], generative_config=Configure.Generative.aws( region="sa-east-1", service="bedrock", model="amazon.titan-text-express-v1" ) ) collection.data.insert({"title": "This is a test"}) obj = collection.generate.fetch_objects( include_vector=True, limit=1, single_prompt="Translate {title} to Portuguese" ).objects[0] print(obj.generated) print(len(obj.vector.get("title_vector"))) ``` Let me know if this helps! ---
**Author:** ![taigofranca](https://yyz1.discourse-cdn.com/flex027/user_avatar/forum.weaviate.io/taigofranca/32/2835_2.png) [@taigofranca](https://forum.weaviate.io/u/taigofranca)\ **Post date:** [November 11, 2024, 3:27pm UTC](https://forum.weaviate.io/t/aws-bedrock-invalid-template-issue/7515/3 "2024-11-11T15:27:32Z")
Oi @DudaNogueira !! Your suggestion worked. I just had to indicate the region, as I changed from the Titan model to the Cohere model. ```python embeddings = BedrockEmbeddings(model_id="cohere.embed-multilingual-v3", credentials_profile_name="avenger_thor_profile", region_name="us-east-1") ``` Thanks for your help. Hugs.