Fix: LLMs test cases and added new xfail test case

pkgs/swarmauri/swarmauri/llms/concrete/PerplexityModel.py

@@ -11,7 +11,7 @@
 class PerplexityModel(LLMBase):
     """
     Provider resources: https://docs.perplexity.ai/guides/model-cards
-    Link to depreciated models: https://docs.perplexity.ai/changelog/changelog#model-deprecation-notice
+    Link to deprecated models: https://docs.perplexity.ai/changelog/changelog#model-deprecation-notice
     """
 
     api_key: str
@@ -54,7 +54,6 @@ def predict(
         presence_penalty: Optional[float] = None,
         frequency_penalty: Optional[float] = None,
     ):
-
         if top_p and top_k:
             raise ValueError("Do not set top_p and top_k")
 

pkgs/swarmauri/tests/integration/llms/CohereModel_i9n_test.py

@@ -40,7 +40,7 @@ def test_nonpreamble_system_context(cohere_model):
     human_message = HumanMessage(content=input_data)
     conversation.add_message(human_message)
 
-    model.predict(conversation=conversation)
+    model.predict(conversation=conversation, temperature=0)
     prediction = conversation.get_last().content
     assert "Jeff" in prediction
 
@@ -68,7 +68,7 @@ def test_multiple_system_contexts(cohere_model):
     human_message = HumanMessage(content=input_data_2)
     conversation.add_message(human_message)
 
-    model.predict(conversation=conversation)
+    model.predict(conversation=conversation, temperature=0)
     prediction = conversation.get_last().content
     assert type(prediction) == str
     assert "Ben" in prediction

pkgs/swarmauri/tests/unit/llms/GroqModel_unit_test.py

@@ -24,6 +24,7 @@ def get_allowed_models():
     if not API_KEY:
         return []
     llm = LLM(api_key=API_KEY)
+    llm.allowed_models.remove("llava-v1.5-7b-4096-preview")
     return llm.allowed_models
 
 
@@ -82,3 +83,32 @@ def test_preamble_system_context(groq_model, model_name):
     prediction = conversation.get_last().content
     assert type(prediction) == str
     assert "Jeff" in prediction
+
+
+@pytest.mark.unit
+def test_preamble_system_context_custom():
+    """
+    specifically for llava-v1.5-7b-4096-preview
+    """
+    if not API_KEY:
+        return []
+
+    groq_model = LLM(api_key=API_KEY)
+    model_name = "llava-v1.5-7b-4096-preview"
+
+    model = groq_model
+    model.name = model_name
+    conversation = Conversation()
+
+    system_context = 'You only respond with the following phrase, "Jeff"'
+    human_message = SystemMessage(content=system_context)
+    conversation.add_message(human_message)
+
+    input_data = "Hi"
+    human_message = HumanMessage(content=input_data)
+    conversation.add_message(human_message)
+
+    model.predict(conversation=conversation)
+    prediction = conversation.get_last().content
+    assert type(prediction) == str
+    assert "Jeff" in prediction