Hi Knime Community,
I am attempting to create a Retrieval-Augmented Generation (RAG) workflow using Azure OpenAI, where the workflow simply takes one PDF as input, allowing for Q&A through the GUI.
I have successfully created the workflow using OpenAI Connectors.
However, I am encountering errors with the Azure OpenAI connectors. Specifically, the “Azure OpenAI Embeddings Connector” returns the following error message:
Configure failed (Py4JException): An exception was raised by the Python Proxy. Return Message: Traceback (most recent call last):
File "C:\KNIME\bundling\envs\org_knime_python_llm\Lib\site-packages\py4j\clientserver.py", line 617, in _call_proxy return_value = getattr(self.pool[obj_id], method)(*params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\KNIME\plugins\org.knime.python3.nodes_5.3.0.v202407031038\src\main\python\_node_backend_launcher.py", line 984, in configure java_outputs = self.postprocess_configure_outputs(java_config_context, outputs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\KNIME\plugins\org.knime.python3.nodes_5.3.0.v202407031038\src\main\python\_node_backend_launcher.py", line 1013, in postprocess_configure_outputs self._port_type_registry.spec_from_python(
File "C:\KNIME\plugins\org.knime.python3.nodes_5.3.0.v202407031038\src\main\python\_node_backend_launcher.py", line 549, in spec_from_python data = {"id": port.type.id, "data": spec.serialize()}
^^^^^^^^^^^^^^^^
File "C:\KNIME\plugins\org.knime.python.llm_5.3.0.v202407041639\src\main\python\src\models\openai.py", line 828, in serialize "dimensions": self._dimensions,
^^^^^^^^^^^^^^^^ AttributeError: 'AzureOpenAIEmbeddingsPortObjectSpec' object has no attribute '_dimensions'
I am also attaching an image for your reference.
Configuration for Azure OpenAI nodes, I am using
- Azure OpenAI Chat Model Connector → LLM-gpt-35-turbo
- Azure OpenAI Embedding Connector → text-embedding-ada-002
Could someone please help me resolve this issue?
Thank you in advance for your assistance!