fix: nvidia-haystack- Handle non-strict env var secrets correctly (#…

…543)

integrations/nvidia/src/haystack_integrations/components/embedders/nvidia/document_embedder.py

@@ -65,9 +65,6 @@ def __init__(
         if isinstance(model, str):
             model = NvidiaEmbeddingModel.from_str(model)
 
-        resolved_api_key = api_key.resolve_value()
-        assert resolved_api_key is not None
-
         # Upper-limit for the endpoint.
         if batch_size > MAX_INPUTS:
             msg = f"NVIDIA Cloud Functions currently support a maximum batch size of {MAX_INPUTS}."
@@ -83,7 +80,7 @@ def __init__(
         self.embedding_separator = embedding_separator
 
         self.client = NvidiaCloudFunctionsClient(
-            api_key=resolved_api_key,
+            api_key=api_key,
             headers={
                 "Content-Type": "application/json",
                 "Accept": "application/json",
@@ -193,7 +190,7 @@ def run(self, documents: List[Document]):
         if not self._initialized:
             msg = "The embedding model has not been loaded. Please call warm_up() before running."
             raise RuntimeError(msg)
-        if not isinstance(documents, list) or documents and not isinstance(documents[0], Document):
+        elif not isinstance(documents, list) or documents and not isinstance(documents[0], Document):
             msg = (
                 "NvidiaDocumentEmbedder expects a list of Documents as input."
                 "In case you want to embed a string, please use the NvidiaTextEmbedder."

integrations/nvidia/src/haystack_integrations/components/embedders/nvidia/text_embedder.py

@@ -53,15 +53,12 @@ def __init__(
         if isinstance(model, str):
             model = NvidiaEmbeddingModel.from_str(model)
 
-        resolved_api_key = api_key.resolve_value()
-        assert resolved_api_key is not None
-
         self.api_key = api_key
         self.model = model
         self.prefix = prefix
         self.suffix = suffix
         self.client = NvidiaCloudFunctionsClient(
-            api_key=resolved_api_key,
+            api_key=api_key,
             headers={
                 "Content-Type": "application/json",
                 "Accept": "application/json",
@@ -128,7 +125,7 @@ def run(self, text: str):
         if not self._initialized:
             msg = "The embedding model has not been loaded. Please call warm_up() before running."
             raise RuntimeError(msg)
-        if not isinstance(text, str):
+        elif not isinstance(text, str):
             msg = (
                 "NvidiaTextEmbedder expects a string as an input."
                 "In case you want to embed a list of Documents, please use the NvidiaDocumentEmbedder."

integrations/nvidia/src/haystack_integrations/utils/nvidia/client.py

@@ -3,6 +3,7 @@
 from typing import Dict, Optional
 
 import requests
+from haystack.utils import Secret
 
 FUNCTIONS_ENDPOINT = "https://api.nvcf.nvidia.com/v2/nvcf/functions"
 INVOKE_ENDPOINT = "https://api.nvcf.nvidia.com/v2/nvcf/pexec/functions"
@@ -19,13 +20,17 @@ class AvailableNvidiaCloudFunctions:
 
 
 class NvidiaCloudFunctionsClient:
-    def __init__(self, *, api_key: str, headers: Dict[str, str], timeout: int = 60):
-        self.api_key = api_key
+    def __init__(self, *, api_key: Secret, headers: Dict[str, str], timeout: int = 60):
+        self.api_key = api_key.resolve_value()
+        if self.api_key is None:
+            msg = "Nvidia Cloud Functions API key is not set."
+            raise ValueError(msg)
+
         self.fetch_url_format = STATUS_ENDPOINT
         self.headers = copy.deepcopy(headers)
         self.headers.update(
             {
-                "Authorization": f"Bearer {api_key}",
+                "Authorization": f"Bearer {self.api_key}",
             }
         )
         self.timeout = timeout