run pre-commit code_quality check

.gitignore

@@ -110,7 +110,7 @@ docs/_build/
 # PyBuilder
 .pybuilder/
 target/
-`
+
 # Jupyter Notebook
 .ipynb_checkpoints
 

playground/demos/developer_swarm/main_example.py

@@ -33,7 +33,7 @@ CODE
 """
 
 # Initialize the language model
-llm = OpenAIChat(openai_api_key=api_key, max_tokens=5000)
+llm = OpenAIChat(openai_api_key=api_key, max_tokens=4096)
 
 
 # Documentation agent

swarms/memory/lanchain_chroma.py

@@ -3,7 +3,7 @@ from pathlib import Path
 
 from langchain.chains import RetrievalQA
 from langchain.chains.question_answering import load_qa_chain
-from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain_community.embeddings import OpenAIEmbeddings
 from langchain.text_splitter import CharacterTextSplitter
 from langchain_community.vectorstores import Chroma
 

tests/agents/test_multion.py

@@ -23,15 +23,19 @@ def test_multion_agent_run(mock_multion):
     assert result == "result"
     assert status == "status"
     assert last_url == "lastUrl"
-    mock_multion.browse.assert_called_once_with({
+    mock_multion.browse.assert_called_once_with(
+        {
             "cmd": "task",
             "url": "https://www.example.com",
             "maxSteps": 5,
-    })
+        }
+    )
 
 
 # Additional tests for different tasks
-@pytest.mark.parametrize("task", ["task1", "task2", "task3", "task4", "task5"])
+@pytest.mark.parametrize(
+    "task", ["task1", "task2", "task3", "task4", "task5"]
+)
 @patch("swarms.agents.multion_agent.multion")
 def test_multion_agent_run_different_tasks(mock_multion, task):
     mock_response = MagicMock()
@@ -50,8 +54,6 @@ def test_multion_agent_run_different_tasks(mock_multion, task):
     assert result == "result"
     assert status == "status"
     assert last_url == "lastUrl"
-    mock_multion.browse.assert_called_once_with({
-        "cmd": task,
-        "url": "https://www.example.com",
-        "maxSteps": 5
-    })
+    mock_multion.browse.assert_called_once_with(
+        {"cmd": task, "url": "https://www.example.com", "maxSteps": 5}
+    )

tests/agents/test_tool_agent.py

@@ -11,27 +11,18 @@ def test_tool_agent_init():
     json_schema = {
         "type": "object",
         "properties": {
-            "name": {
-                "type": "string"
-            },
-            "age": {
-                "type": "number"
-            },
-            "is_student": {
-                "type": "boolean"
-            },
-            "courses": {
-                "type": "array",
-                "items": {
-                    "type": "string"
-                }
-            },
+            "name": {"type": "string"},
+            "age": {"type": "number"},
+            "is_student": {"type": "boolean"},
+            "courses": {"type": "array", "items": {"type": "string"}},
         },
     }
     name = "Test Agent"
     description = "This is a test agent"
 
-    agent = ToolAgent(name, description, model, tokenizer, json_schema)
+    agent = ToolAgent(
+        name, description, model, tokenizer, json_schema
+    )
 
     assert agent.name == name
     assert agent.description == description
@@ -47,29 +38,22 @@ def test_tool_agent_run(mock_run):
     json_schema = {
         "type": "object",
         "properties": {
-            "name": {
-                "type": "string"
-            },
-            "age": {
-                "type": "number"
-            },
-            "is_student": {
-                "type": "boolean"
-            },
-            "courses": {
-                "type": "array",
-                "items": {
-                    "type": "string"
-                }
-            },
+            "name": {"type": "string"},
+            "age": {"type": "number"},
+            "is_student": {"type": "boolean"},
+            "courses": {"type": "array", "items": {"type": "string"}},
         },
     }
     name = "Test Agent"
     description = "This is a test agent"
-    task = ("Generate a person's information based on the following"
-            " schema:")
+    task = (
+        "Generate a person's information based on the following"
+        " schema:"
+    )
 
-    agent = ToolAgent(name, description, model, tokenizer, json_schema)
+    agent = ToolAgent(
+        name, description, model, tokenizer, json_schema
+    )
     agent.run(task)
 
     mock_run.assert_called_once_with(task)
@@ -81,21 +65,10 @@ def test_tool_agent_init_with_kwargs():
     json_schema = {
         "type": "object",
         "properties": {
-            "name": {
-                "type": "string"
-            },
-            "age": {
-                "type": "number"
-            },
-            "is_student": {
-                "type": "boolean"
-            },
-            "courses": {
-                "type": "array",
-                "items": {
-                    "type": "string"
-                }
-            },
+            "name": {"type": "string"},
+            "age": {"type": "number"},
+            "is_student": {"type": "boolean"},
+            "courses": {"type": "array", "items": {"type": "string"}},
         },
     }
     name = "Test Agent"
@@ -109,8 +82,9 @@ def test_tool_agent_init_with_kwargs():
         "max_string_token_length": 20,
     }
 
-    agent = ToolAgent(name, description, model, tokenizer, json_schema,
-                      **kwargs)
+    agent = ToolAgent(
+        name, description, model, tokenizer, json_schema, **kwargs
+    )
 
     assert agent.name == name
     assert agent.description == description
@@ -121,4 +95,7 @@ def test_tool_agent_init_with_kwargs():
     assert agent.max_array_length == kwargs["max_array_length"]
     assert agent.max_number_tokens == kwargs["max_number_tokens"]
     assert agent.temperature == kwargs["temperature"]
-    assert (agent.max_string_token_length == kwargs["max_string_token_length"])
+    assert (
+        agent.max_string_token_length
+        == kwargs["max_string_token_length"]
+    )

tests/memory/test_dictinternalmemory.py

@@ -33,8 +33,9 @@ def test_memory_limit_enforced(memory):
 
 
 # Parameterized Tests
-@pytest.mark.parametrize("scores, best_score", [([10, 5, 3], 10),
-                                                ([1, 2, 3], 3)])
+@pytest.mark.parametrize(
+    "scores, best_score", [([10, 5, 3], 10), ([1, 2, 3], 3)]
+)
 def test_get_top_n(scores, best_score, memory):
     for score in scores:
         memory.add(score, {"data": f"test{score}"})

tests/memory/test_dictsharedmemory.py

@@ -26,7 +26,8 @@ def memory_instance(memory_file):
 def test_init(memory_file):
     memory = DictSharedMemory(file_loc=memory_file)
     assert os.path.exists(
-        memory.file_loc), "Memory file should be created if non-existent"
+        memory.file_loc
+    ), "Memory file should be created if non-existent"
 
 
 def test_add_entry(memory_instance):
@@ -43,7 +44,8 @@ def test_get_top_n(memory_instance):
     memory_instance.add(9.5, "agent123", 1, "Entry A")
     memory_instance.add(8.5, "agent124", 1, "Entry B")
     top_1 = memory_instance.get_top_n(1)
-    assert (len(top_1) == 1
+    assert (
+        len(top_1) == 1
     ), "get_top_n should return the correct number of top entries"
 
 
@@ -57,13 +59,17 @@ def test_get_top_n(memory_instance):
         # add more test cases
     ],
 )
-def test_parametrized_get_top_n(memory_instance, scores, agent_ids,
-                                expected_top_score):
+def test_parametrized_get_top_n(
+    memory_instance, scores, agent_ids, expected_top_score
+):
     for score, agent_id in zip(scores, agent_ids):
-        memory_instance.add(score, agent_id, 1, f"Entry by {agent_id}")
+        memory_instance.add(
+            score, agent_id, 1, f"Entry by {agent_id}"
+        )
     top_1 = memory_instance.get_top_n(1)
     top_score = next(iter(top_1.values()))["score"]
-    assert (top_score == expected_top_score
+    assert (
+        top_score == expected_top_score
     ), "get_top_n should return the entry with top score"
 
 
@@ -72,7 +78,9 @@ def test_parametrized_get_top_n(memory_instance, scores, agent_ids,
 
 def test_add_entry_invalid_input(memory_instance):
     with pytest.raises(ValueError):
-        memory_instance.add("invalid_score", "agent123", 1, "Test Entry")
+        memory_instance.add(
+            "invalid_score", "agent123", 1, "Test Entry"
+        )
 
 
 # Mocks and monkey-patching

tests/memory/test_langchainchromavectormemory.py

@@ -35,13 +35,16 @@ def qa_mock():
 # Example test cases
 def test_initialization_default_settings(vector_memory):
     assert vector_memory.chunk_size == 1000
-    assert (vector_memory.chunk_overlap == 100
+    assert (
+        vector_memory.chunk_overlap == 100
     )  # assuming default overlap of 0.1
     assert vector_memory.loc.exists()
 
 
 def test_add_entry(vector_memory, embeddings_mock):
-    with patch.object(vector_memory.db, "add_texts") as add_texts_mock:
+    with patch.object(
+        vector_memory.db, "add_texts"
+    ) as add_texts_mock:
         vector_memory.add("Example text")
         add_texts_mock.assert_called()
 
@@ -74,8 +77,9 @@ def test_ask_question_returns_string(vector_memory, qa_mock):
         ),  # Mocked object as a placeholder
     ],
 )
-def test_search_memory_different_params(vector_memory, query, k, type,
-                                        expected):
+def test_search_memory_different_params(
+    vector_memory, query, k, type, expected
+):
     with patch.object(
         vector_memory.db,
         "max_marginal_relevance_search",
@@ -86,5 +90,7 @@ def test_search_memory_different_params(vector_memory, query, k, type,
             "similarity_search_with_score",
             return_value=expected,
         ):
-            result = vector_memory.search_memory(query, k=k, type=type)
+            result = vector_memory.search_memory(
+                query, k=k, type=type
+            )
             assert len(result) == (k if k > 0 else 0)

tests/memory/test_pinecone.py

@@ -8,7 +8,8 @@ api_key = os.getenv("PINECONE_API_KEY") or ""
 
 def test_init():
     with patch("pinecone.init") as MockInit, patch(
-            "pinecone.Index") as MockIndex:
+        "pinecone.Index"
+    ) as MockIndex:
         store = PineconeDB(
             api_key=api_key,
             index_name="test_index",
@@ -70,7 +71,8 @@ def test_query():
 
 def test_create_index():
     with patch("pinecone.init"), patch("pinecone.Index"), patch(
-            "pinecone.create_index") as MockCreateIndex:
+        "pinecone.create_index"
+    ) as MockCreateIndex:
         store = PineconeDB(
             api_key=api_key,
             index_name="test_index",

tests/memory/test_pq_db.py

@@ -32,7 +32,8 @@ def test_create_vector_model():
 
 def test_add_or_update_vector():
     with patch("sqlalchemy.create_engine"), patch(
-            "sqlalchemy.orm.Session") as MockSession:
+        "sqlalchemy.orm.Session"
+    ) as MockSession:
         db = PostgresDB(
             connection_string=PSG_CONNECTION_STRING,
             table_name="test",
@@ -50,7 +51,8 @@ def test_add_or_update_vector():
 
 def test_query_vectors():
     with patch("sqlalchemy.create_engine"), patch(
-            "sqlalchemy.orm.Session") as MockSession:
+        "sqlalchemy.orm.Session"
+    ) as MockSession:
         db = PostgresDB(
             connection_string=PSG_CONNECTION_STRING,
             table_name="test",
@@ -65,7 +67,8 @@ def test_query_vectors():
 
 def test_delete_vector():
     with patch("sqlalchemy.create_engine"), patch(
-            "sqlalchemy.orm.Session") as MockSession:
+        "sqlalchemy.orm.Session"
+    ) as MockSession:
         db = PostgresDB(
             connection_string=PSG_CONNECTION_STRING,
             table_name="test",

tests/memory/test_qdrant.py

@@ -13,7 +13,8 @@ def mock_qdrant_client():
 
 @pytest.fixture
 def mock_sentence_transformer():
-    with patch("sentence_transformers.SentenceTransformer"
+    with patch(
+        "sentence_transformers.SentenceTransformer"
     ) as MockSentenceTransformer:
         yield MockSentenceTransformer()
 
@@ -28,7 +29,9 @@ def test_qdrant_init(qdrant_client, mock_qdrant_client):
     assert qdrant_client.client is not None
 
 
-def test_load_embedding_model(qdrant_client, mock_sentence_transformer):
+def test_load_embedding_model(
+    qdrant_client, mock_sentence_transformer
+):
     qdrant_client._load_embedding_model("model_name")
     mock_sentence_transformer.assert_called_once_with("model_name")
 
@@ -36,7 +39,8 @@ def test_load_embedding_model(qdrant_client, mock_sentence_transformer):
 def test_setup_collection(qdrant_client, mock_qdrant_client):
     qdrant_client._setup_collection()
     mock_qdrant_client.get_collection.assert_called_once_with(
-        qdrant_client.collection_name)
+        qdrant_client.collection_name
+    )
 
 
 def test_add_vectors(qdrant_client, mock_qdrant_client):

tests/memory/test_short_term_memory.py

@@ -12,29 +12,26 @@ def test_init():
 def test_add():
     memory = ShortTermMemory()
     memory.add("user", "Hello, world!")
-    assert memory.short_term_memory == [{
-        "role": "user",
-        "message": "Hello, world!"
-    }]
+    assert memory.short_term_memory == [
+        {"role": "user", "message": "Hello, world!"}
+    ]
 
 
 def test_get_short_term():
     memory = ShortTermMemory()
     memory.add("user", "Hello, world!")
-    assert memory.get_short_term() == [{
-        "role": "user",
-        "message": "Hello, world!"
-    }]
+    assert memory.get_short_term() == [
+        {"role": "user", "message": "Hello, world!"}
+    ]
 
 
 def test_get_medium_term():
     memory = ShortTermMemory()
     memory.add("user", "Hello, world!")
     memory.move_to_medium_term(0)
-    assert memory.get_medium_term() == [{
-        "role": "user",
-        "message": "Hello, world!"
-    }]
+    assert memory.get_medium_term() == [
+        {"role": "user", "message": "Hello, world!"}
+    ]
 
 
 def test_clear_medium_term():
@@ -48,18 +45,19 @@ def test_clear_medium_term():
 def test_get_short_term_memory_str():
     memory = ShortTermMemory()
     memory.add("user", "Hello, world!")
-    assert (memory.get_short_term_memory_str() ==
-            "[{'role': 'user', 'message': 'Hello, world!'}]")
+    assert (
+        memory.get_short_term_memory_str()
+        == "[{'role': 'user', 'message': 'Hello, world!'}]"
+    )
 
 
 def test_update_short_term():
     memory = ShortTermMemory()
     memory.add("user", "Hello, world!")
     memory.update_short_term(0, "user", "Goodbye, world!")
-    assert memory.get_short_term() == [{
-        "role": "user",
-        "message": "Goodbye, world!"
-    }]
+    assert memory.get_short_term() == [
+        {"role": "user", "message": "Goodbye, world!"}
+    ]
 
 
 def test_clear():
@@ -73,10 +71,9 @@ def test_search_memory():
     memory = ShortTermMemory()
     memory.add("user", "Hello, world!")
     assert memory.search_memory("Hello") == {
-        "short_term": [(0, {
-            "role": "user",
-            "message": "Hello, world!"
-        })],
+        "short_term": [
+            (0, {"role": "user", "message": "Hello, world!"})
+        ],
         "medium_term": [],
     }
 
@@ -84,18 +81,19 @@ def test_search_memory():
 def test_return_shortmemory_as_str():
     memory = ShortTermMemory()
     memory.add("user", "Hello, world!")
-    assert (memory.return_shortmemory_as_str() ==
-            "[{'role': 'user', 'message': 'Hello, world!'}]")
+    assert (
+        memory.return_shortmemory_as_str()
+        == "[{'role': 'user', 'message': 'Hello, world!'}]"
+    )
 
 
 def test_move_to_medium_term():
     memory = ShortTermMemory()
     memory.add("user", "Hello, world!")
     memory.move_to_medium_term(0)
-    assert memory.get_medium_term() == [{
-        "role": "user",
-        "message": "Hello, world!"
-    }]
+    assert memory.get_medium_term() == [
+        {"role": "user", "message": "Hello, world!"}
+    ]
     assert memory.get_short_term() == []
 
 
@@ -103,8 +101,10 @@ def test_return_medium_memory_as_str():
     memory = ShortTermMemory()
     memory.add("user", "Hello, world!")
     memory.move_to_medium_term(0)
-    assert (memory.return_medium_memory_as_str() ==
-            "[{'role': 'user', 'message': 'Hello, world!'}]")
+    assert (
+        memory.return_medium_memory_as_str()
+        == "[{'role': 'user', 'message': 'Hello, world!'}]"
+    )
 
 
 def test_thread_safety():
@@ -114,7 +114,9 @@ def test_thread_safety():
         for _ in range(1000):
             memory.add("user", "Hello, world!")
 
-    threads = [threading.Thread(target=add_messages) for _ in range(10)]
+    threads = [
+        threading.Thread(target=add_messages) for _ in range(10)
+    ]
     for thread in threads:
         thread.start()
     for thread in threads:

tests/memory/test_sqlite.py

@@ -8,7 +8,9 @@ from swarms.memory.sqlite import SQLiteDB
 @pytest.fixture
 def db():
     conn = sqlite3.connect(":memory:")
-    conn.execute("CREATE TABLE test (id INTEGER PRIMARY KEY, name TEXT)")
+    conn.execute(
+        "CREATE TABLE test (id INTEGER PRIMARY KEY, name TEXT)"
+    )
     conn.commit()
     return SQLiteDB(":memory:")
 
@@ -28,7 +30,9 @@ def test_delete(db):
 
 def test_update(db):
     db.add("INSERT INTO test (name) VALUES (?)", ("test",))
-    db.update("UPDATE test SET name = ? WHERE name = ?", ("new", "test"))
+    db.update(
+        "UPDATE test SET name = ? WHERE name = ?", ("new", "test")
+    )
     result = db.query("SELECT * FROM test")
     assert result == [(1, "new")]
 
@@ -41,7 +45,9 @@ def test_query(db):
 
 def test_execute_query(db):
     db.add("INSERT INTO test (name) VALUES (?)", ("test",))
-    result = db.execute_query("SELECT * FROM test WHERE name = ?", ("test",))
+    result = db.execute_query(
+        "SELECT * FROM test WHERE name = ?", ("test",)
+    )
     assert result == [(1, "test")]
 
 
@@ -95,4 +101,6 @@ def test_query_with_wrong_query(db):
 
 def test_execute_query_with_wrong_query(db):
     with pytest.raises(sqlite3.OperationalError):
-        db.execute_query("SELECT * FROM wrong WHERE name = ?", ("test",))
+        db.execute_query(
+            "SELECT * FROM wrong WHERE name = ?", ("test",)
+        )

tests/memory/test_weaviate.py

@@ -16,7 +16,9 @@ def weaviate_client_mock():
         grpc_port="mock_grpc_port",
         grpc_secure=False,
         auth_client_secret="mock_api_key",
-        additional_headers={"X-OpenAI-Api-Key": "mock_openai_api_key"},
+        additional_headers={
+            "X-OpenAI-Api-Key": "mock_openai_api_key"
+        },
         additional_config=Mock(),
     )
 
@@ -34,15 +36,13 @@ def weaviate_client_mock():
 # Define tests for the WeaviateDB class
 def test_create_collection(weaviate_client_mock):
     # Test creating a collection
-    weaviate_client_mock.create_collection("test_collection", [{
-        "name": "property"
-    }])
+    weaviate_client_mock.create_collection(
+        "test_collection", [{"name": "property"}]
+    )
     weaviate_client_mock.client.collections.create.assert_called_with(
         name="test_collection",
         vectorizer_config=None,
-        properties=[{
-            "name": "property"
-        }],
+        properties=[{"name": "property"}],
     )
 
 
@@ -51,9 +51,11 @@ def test_add_object(weaviate_client_mock):
     properties = {"name": "John"}
     weaviate_client_mock.add("test_collection", properties)
     weaviate_client_mock.client.collections.get.assert_called_with(
-        "test_collection")
+        "test_collection"
+    )
     weaviate_client_mock.client.collections.data.insert.assert_called_with(
-        properties)
+        properties
+    )
 
 
 def test_query_objects(weaviate_client_mock):
@@ -61,20 +63,26 @@ def test_query_objects(weaviate_client_mock):
     query = "name:John"
     weaviate_client_mock.query("test_collection", query)
     weaviate_client_mock.client.collections.get.assert_called_with(
-        "test_collection")
+        "test_collection"
+    )
     weaviate_client_mock.client.collections.query.bm25.assert_called_with(
-        query=query, limit=10)
+        query=query, limit=10
+    )
 
 
 def test_update_object(weaviate_client_mock):
     # Test updating an object
     object_id = "12345"
     properties = {"name": "Jane"}
-    weaviate_client_mock.update("test_collection", object_id, properties)
+    weaviate_client_mock.update(
+        "test_collection", object_id, properties
+    )
     weaviate_client_mock.client.collections.get.assert_called_with(
-        "test_collection")
+        "test_collection"
+    )
     weaviate_client_mock.client.collections.data.update.assert_called_with(
-        object_id, properties)
+        object_id, properties
+    )
 
 
 def test_delete_object(weaviate_client_mock):
@@ -82,23 +90,25 @@ def test_delete_object(weaviate_client_mock):
     object_id = "12345"
     weaviate_client_mock.delete("test_collection", object_id)
     weaviate_client_mock.client.collections.get.assert_called_with(
-        "test_collection")
+        "test_collection"
+    )
     weaviate_client_mock.client.collections.data.delete_by_id.assert_called_with(
-        object_id)
+        object_id
+    )
 
 
-def test_create_collection_with_vectorizer_config(weaviate_client_mock,):
+def test_create_collection_with_vectorizer_config(
+    weaviate_client_mock,
+):
     # Test creating a collection with vectorizer configuration
     vectorizer_config = {"config_key": "config_value"}
-    weaviate_client_mock.create_collection("test_collection", [{
-        "name": "property"
-    }], vectorizer_config)
+    weaviate_client_mock.create_collection(
+        "test_collection", [{"name": "property"}], vectorizer_config
+    )
     weaviate_client_mock.client.collections.create.assert_called_with(
         name="test_collection",
         vectorizer_config=vectorizer_config,
-        properties=[{
-            "name": "property"
-        }],
+        properties=[{"name": "property"}],
     )
 
 
@@ -108,9 +118,11 @@ def test_query_objects_with_limit(weaviate_client_mock):
     limit = 20
     weaviate_client_mock.query("test_collection", query, limit)
     weaviate_client_mock.client.collections.get.assert_called_with(
-        "test_collection")
+        "test_collection"
+    )
     weaviate_client_mock.client.collections.query.bm25.assert_called_with(
-        query=query, limit=limit)
+        query=query, limit=limit
+    )
 
 
 def test_query_objects_without_limit(weaviate_client_mock):
@@ -118,9 +130,11 @@ def test_query_objects_without_limit(weaviate_client_mock):
     query = "name:John"
     weaviate_client_mock.query("test_collection", query)
     weaviate_client_mock.client.collections.get.assert_called_with(
-        "test_collection")
+        "test_collection"
+    )
     weaviate_client_mock.client.collections.query.bm25.assert_called_with(
-        query=query, limit=10)
+        query=query, limit=10
+    )
 
 
 def test_create_collection_failure(weaviate_client_mock):
@@ -129,10 +143,12 @@ def test_create_collection_failure(weaviate_client_mock):
         "weaviate_client.weaviate.collections.create",
         side_effect=Exception("Create error"),
     ):
-        with pytest.raises(Exception, match="Error creating collection"):
-            weaviate_client_mock.create_collection("test_collection", [{
-                "name": "property"
-            }])
+        with pytest.raises(
+            Exception, match="Error creating collection"
+        ):
+            weaviate_client_mock.create_collection(
+                "test_collection", [{"name": "property"}]
+            )
 
 
 def test_add_object_failure(weaviate_client_mock):
@@ -166,8 +182,9 @@ def test_update_object_failure(weaviate_client_mock):
         side_effect=Exception("Update error"),
     ):
         with pytest.raises(Exception, match="Error updating object"):
-            weaviate_client_mock.update("test_collection", object_id,
-                                        properties)
+            weaviate_client_mock.update(
+                "test_collection", object_id, properties
+            )
 
 
 def test_delete_object_failure(weaviate_client_mock):

tests/models/test_anthropic.py

@@ -8,11 +8,12 @@ from swarms.models.anthropic import Anthropic
 
 # Mock the Anthropic API client for testing
 class MockAnthropicClient:
-
     def __init__(self, *args, **kwargs):
         pass
 
-    def completions_create(self, prompt, stop_sequences, stream, **kwargs):
+    def completions_create(
+        self, prompt, stop_sequences, stream, **kwargs
+    ):
         return MockAnthropicResponse()
 
 
@@ -45,7 +46,9 @@ def test_anthropic_init_default_values(anthropic_instance):
     assert anthropic_instance.streaming is False
     assert anthropic_instance.default_request_timeout == 600
     assert (
-        anthropic_instance.anthropic_api_url == "https://test.anthropic.com")
+        anthropic_instance.anthropic_api_url
+        == "https://test.anthropic.com"
+    )
     assert anthropic_instance.anthropic_api_key == "test_api_key"
 
 
@@ -76,8 +79,9 @@ def test_anthropic_default_params(anthropic_instance):
     }
 
 
-def test_anthropic_run(mock_anthropic_env, mock_requests_post,
-                       anthropic_instance):
+def test_anthropic_run(
+    mock_anthropic_env, mock_requests_post, anthropic_instance
+):
     mock_response = Mock()
     mock_response.json.return_value = {"completion": "Generated text"}
     mock_requests_post.return_value = mock_response
@@ -101,8 +105,9 @@ def test_anthropic_run(mock_anthropic_env, mock_requests_post,
     )
 
 
-def test_anthropic_call(mock_anthropic_env, mock_requests_post,
-                        anthropic_instance):
+def test_anthropic_call(
+    mock_anthropic_env, mock_requests_post, anthropic_instance
+):
     mock_response = Mock()
     mock_response.json.return_value = {"completion": "Generated text"}
     mock_requests_post.return_value = mock_response
@@ -126,8 +131,9 @@ def test_anthropic_call(mock_anthropic_env, mock_requests_post,
     )
 
 
-def test_anthropic_exception_handling(mock_anthropic_env, mock_requests_post,
-                                      anthropic_instance):
+def test_anthropic_exception_handling(
+    mock_anthropic_env, mock_requests_post, anthropic_instance
+):
     mock_response = Mock()
     mock_response.json.return_value = {"error": "An error occurred"}
     mock_requests_post.return_value = mock_response
@@ -142,7 +148,6 @@ def test_anthropic_exception_handling(mock_anthropic_env, mock_requests_post,
 
 
 class MockAnthropicResponse:
-
     def __init__(self):
         self.completion = "Mocked Response from Anthropic"
 
@@ -168,7 +173,9 @@ def test_anthropic_async_call_method(anthropic_instance):
 
 
 def test_anthropic_async_stream_method(anthropic_instance):
-    async_generator = anthropic_instance.async_stream("Translate to French.")
+    async_generator = anthropic_instance.async_stream(
+        "Translate to French."
+    )
     for token in async_generator:
         assert isinstance(token, str)
 
@@ -192,51 +199,63 @@ def test_anthropic_wrap_prompt(anthropic_instance):
 def test_anthropic_convert_prompt(anthropic_instance):
     prompt = "What is the meaning of life?"
     converted_prompt = anthropic_instance.convert_prompt(prompt)
-    assert converted_prompt.startswith(anthropic_instance.HUMAN_PROMPT)
+    assert converted_prompt.startswith(
+        anthropic_instance.HUMAN_PROMPT
+    )
     assert converted_prompt.endswith(anthropic_instance.AI_PROMPT)
 
 
 def test_anthropic_call_with_stop(anthropic_instance):
-    response = anthropic_instance("Translate to French.",
-                                  stop=["stop1", "stop2"])
+    response = anthropic_instance(
+        "Translate to French.", stop=["stop1", "stop2"]
+    )
     assert response == "Mocked Response from Anthropic"
 
 
 def test_anthropic_stream_with_stop(anthropic_instance):
-    generator = anthropic_instance.stream("Write a story.",
-                                          stop=["stop1", "stop2"])
+    generator = anthropic_instance.stream(
+        "Write a story.", stop=["stop1", "stop2"]
+    )
     for token in generator:
         assert isinstance(token, str)
 
 
 def test_anthropic_async_call_with_stop(anthropic_instance):
-    response = anthropic_instance.async_call("Tell me a joke.",
-                                             stop=["stop1", "stop2"])
+    response = anthropic_instance.async_call(
+        "Tell me a joke.", stop=["stop1", "stop2"]
+    )
     assert response == "Mocked Response from Anthropic"
 
 
 def test_anthropic_async_stream_with_stop(anthropic_instance):
-    async_generator = anthropic_instance.async_stream("Translate to French.",
-                                                      stop=["stop1", "stop2"])
+    async_generator = anthropic_instance.async_stream(
+        "Translate to French.", stop=["stop1", "stop2"]
+    )
     for token in async_generator:
         assert isinstance(token, str)
 
 
-def test_anthropic_get_num_tokens_with_count_tokens(anthropic_instance,):
+def test_anthropic_get_num_tokens_with_count_tokens(
+    anthropic_instance,
+):
     anthropic_instance.count_tokens = Mock(return_value=10)
     text = "This is a test sentence."
     num_tokens = anthropic_instance.get_num_tokens(text)
     assert num_tokens == 10
 
 
-def test_anthropic_get_num_tokens_without_count_tokens(anthropic_instance,):
+def test_anthropic_get_num_tokens_without_count_tokens(
+    anthropic_instance,
+):
     del anthropic_instance.count_tokens
     with pytest.raises(NameError):
         text = "This is a test sentence."
         anthropic_instance.get_num_tokens(text)
 
 
-def test_anthropic_wrap_prompt_without_human_ai_prompt(anthropic_instance,):
+def test_anthropic_wrap_prompt_without_human_ai_prompt(
+    anthropic_instance,
+):
     del anthropic_instance.HUMAN_PROMPT
     del anthropic_instance.AI_PROMPT
     prompt = "What is the meaning of life?"

tests/models/test_biogpt.py

@@ -48,8 +48,10 @@ def test_cell_biology_response(biogpt_instance):
 
 # 40. Test for a question about protein structure
 def test_protein_structure_response(biogpt_instance):
-    question = ("What's the difference between alpha helix and beta sheet"
-                " structures in proteins?")
+    question = (
+        "What's the difference between alpha helix and beta sheet"
+        " structures in proteins?"
+    )
     response = biogpt_instance(question)
     assert response
     assert isinstance(response, str)
@@ -81,7 +83,9 @@ def test_bioinformatics_response(biogpt_instance):
 
 # 44. Test for a neuroscience question
 def test_neuroscience_response(biogpt_instance):
-    question = ("Explain the function of synapses in the nervous system.")
+    question = (
+        "Explain the function of synapses in the nervous system."
+    )
     response = biogpt_instance(question)
     assert response
     assert isinstance(response, str)
@@ -104,11 +108,8 @@ def test_init(bio_gpt):
 
 
 def test_call(bio_gpt, monkeypatch):
-
     def mock_pipeline(*args, **kwargs):
-
         class MockGenerator:
-
             def __call__(self, text, **kwargs):
                 return ["Generated text"]
 
@@ -166,7 +167,9 @@ def test_get_config_return_type(biogpt_instance):
 # 28. Test saving model functionality by checking if files are created
 @patch.object(BioGptForCausalLM, "save_pretrained")
 @patch.object(BioGptTokenizer, "save_pretrained")
-def test_save_model(mock_save_model, mock_save_tokenizer, biogpt_instance):
+def test_save_model(
+    mock_save_model, mock_save_tokenizer, biogpt_instance
+):
     path = "test_path"
     biogpt_instance.save_model(path)
     mock_save_model.assert_called_once_with(path)
@@ -176,7 +179,9 @@ def test_save_model(mock_save_model, mock_save_tokenizer, biogpt_instance):
 # 29. Test loading model from path
 @patch.object(BioGptForCausalLM, "from_pretrained")
 @patch.object(BioGptTokenizer, "from_pretrained")
-def test_load_from_path(mock_load_model, mock_load_tokenizer, biogpt_instance):
+def test_load_from_path(
+    mock_load_model, mock_load_tokenizer, biogpt_instance
+):
     path = "test_path"
     biogpt_instance.load_from_path(path)
     mock_load_model.assert_called_once_with(path)
@@ -193,7 +198,9 @@ def test_print_model_metadata(biogpt_instance):
 
 # 31. Test that beam_search_decoding uses the correct number of beams
 @patch.object(BioGptForCausalLM, "generate")
-def test_beam_search_decoding_num_beams(mock_generate, biogpt_instance):
+def test_beam_search_decoding_num_beams(
+    mock_generate, biogpt_instance
+):
     biogpt_instance.beam_search_decoding("test_sentence", num_beams=7)
     _, kwargs = mock_generate.call_args
     assert kwargs["num_beams"] == 7
@@ -201,8 +208,12 @@ def test_beam_search_decoding_num_beams(mock_generate, biogpt_instance):
 
 # 32. Test if beam_search_decoding handles early_stopping
 @patch.object(BioGptForCausalLM, "generate")
-def test_beam_search_decoding_early_stopping(mock_generate, biogpt_instance):
-    biogpt_instance.beam_search_decoding("test_sentence", early_stopping=False)
+def test_beam_search_decoding_early_stopping(
+    mock_generate, biogpt_instance
+):
+    biogpt_instance.beam_search_decoding(
+        "test_sentence", early_stopping=False
+    )
     _, kwargs = mock_generate.call_args
     assert kwargs["early_stopping"] is False
 

tests/models/test_cohere.py

@@ -42,7 +42,9 @@ def test_cohere_async_api_error_handling(cohere_instance):
     cohere_instance.model = "base"
     cohere_instance.cohere_api_key = "invalid-api-key"
     with pytest.raises(Exception):
-        cohere_instance.async_call("Error handling with invalid API key.")
+        cohere_instance.async_call(
+            "Error handling with invalid API key."
+        )
 
 
 def test_cohere_stream_api_error_handling(cohere_instance):
@@ -51,7 +53,8 @@ def test_cohere_stream_api_error_handling(cohere_instance):
     cohere_instance.cohere_api_key = "invalid-api-key"
     with pytest.raises(Exception):
         generator = cohere_instance.stream(
-            "Error handling with invalid API key.")
+            "Error handling with invalid API key."
+        )
         for token in generator:
             pass
 
@@ -91,26 +94,31 @@ def test_cohere_convert_prompt(cohere_instance):
 
 
 def test_cohere_call_with_stop(cohere_instance):
-    response = cohere_instance("Translate to French.", stop=["stop1", "stop2"])
+    response = cohere_instance(
+        "Translate to French.", stop=["stop1", "stop2"]
+    )
     assert response == "Mocked Response from Cohere"
 
 
 def test_cohere_stream_with_stop(cohere_instance):
-    generator = cohere_instance.stream("Write a story.",
-                                       stop=["stop1", "stop2"])
+    generator = cohere_instance.stream(
+        "Write a story.", stop=["stop1", "stop2"]
+    )
     for token in generator:
         assert isinstance(token, str)
 
 
 def test_cohere_async_call_with_stop(cohere_instance):
-    response = cohere_instance.async_call("Tell me a joke.",
-                                          stop=["stop1", "stop2"])
+    response = cohere_instance.async_call(
+        "Tell me a joke.", stop=["stop1", "stop2"]
+    )
     assert response == "Mocked Response from Cohere"
 
 
 def test_cohere_async_stream_with_stop(cohere_instance):
-    async_generator = cohere_instance.async_stream("Translate to French.",
-                                                   stop=["stop1", "stop2"])
+    async_generator = cohere_instance.async_stream(
+        "Translate to French.", stop=["stop1", "stop2"]
+    )
     for token in async_generator:
         assert isinstance(token, str)
 
@@ -166,8 +174,12 @@ def test_base_cohere_validate_environment_without_cohere():
 # Test cases for benchmarking generations with various models
 def test_cohere_generate_with_command_light(cohere_instance):
     cohere_instance.model = "command-light"
-    response = cohere_instance("Generate text with Command Light model.")
-    assert response.startswith("Generated text with Command Light model")
+    response = cohere_instance(
+        "Generate text with Command Light model."
+    )
+    assert response.startswith(
+        "Generated text with Command Light model"
+    )
 
 
 def test_cohere_generate_with_command(cohere_instance):
@@ -190,54 +202,74 @@ def test_cohere_generate_with_base(cohere_instance):
 
 def test_cohere_generate_with_embed_english_v2(cohere_instance):
     cohere_instance.model = "embed-english-v2.0"
-    response = cohere_instance("Generate embeddings with English v2.0 model.")
-    assert response.startswith("Generated embeddings with English v2.0 model")
+    response = cohere_instance(
+        "Generate embeddings with English v2.0 model."
+    )
+    assert response.startswith(
+        "Generated embeddings with English v2.0 model"
+    )
 
 
 def test_cohere_generate_with_embed_english_light_v2(cohere_instance):
     cohere_instance.model = "embed-english-light-v2.0"
     response = cohere_instance(
-        "Generate embeddings with English Light v2.0 model.")
+        "Generate embeddings with English Light v2.0 model."
+    )
     assert response.startswith(
-        "Generated embeddings with English Light v2.0 model")
+        "Generated embeddings with English Light v2.0 model"
+    )
 
 
 def test_cohere_generate_with_embed_multilingual_v2(cohere_instance):
     cohere_instance.model = "embed-multilingual-v2.0"
     response = cohere_instance(
-        "Generate embeddings with Multilingual v2.0 model.")
+        "Generate embeddings with Multilingual v2.0 model."
+    )
     assert response.startswith(
-        "Generated embeddings with Multilingual v2.0 model")
+        "Generated embeddings with Multilingual v2.0 model"
+    )
 
 
 def test_cohere_generate_with_embed_english_v3(cohere_instance):
     cohere_instance.model = "embed-english-v3.0"
-    response = cohere_instance("Generate embeddings with English v3.0 model.")
-    assert response.startswith("Generated embeddings with English v3.0 model")
+    response = cohere_instance(
+        "Generate embeddings with English v3.0 model."
+    )
+    assert response.startswith(
+        "Generated embeddings with English v3.0 model"
+    )
 
 
 def test_cohere_generate_with_embed_english_light_v3(cohere_instance):
     cohere_instance.model = "embed-english-light-v3.0"
     response = cohere_instance(
-        "Generate embeddings with English Light v3.0 model.")
+        "Generate embeddings with English Light v3.0 model."
+    )
     assert response.startswith(
-        "Generated embeddings with English Light v3.0 model")
+        "Generated embeddings with English Light v3.0 model"
+    )
 
 
 def test_cohere_generate_with_embed_multilingual_v3(cohere_instance):
     cohere_instance.model = "embed-multilingual-v3.0"
     response = cohere_instance(
-        "Generate embeddings with Multilingual v3.0 model.")
+        "Generate embeddings with Multilingual v3.0 model."
+    )
     assert response.startswith(
-        "Generated embeddings with Multilingual v3.0 model")
+        "Generated embeddings with Multilingual v3.0 model"
+    )
 
 
-def test_cohere_generate_with_embed_multilingual_light_v3(cohere_instance,):
+def test_cohere_generate_with_embed_multilingual_light_v3(
+    cohere_instance,
+):
     cohere_instance.model = "embed-multilingual-light-v3.0"
     response = cohere_instance(
-        "Generate embeddings with Multilingual Light v3.0 model.")
+        "Generate embeddings with Multilingual Light v3.0 model."
+    )
     assert response.startswith(
-        "Generated embeddings with Multilingual Light v3.0 model")
+        "Generated embeddings with Multilingual Light v3.0 model"
+    )
 
 
 # Add more test cases to benchmark other models and functionalities
@@ -267,13 +299,17 @@ def test_cohere_call_with_embed_english_v3_model(cohere_instance):
     assert isinstance(response, str)
 
 
-def test_cohere_call_with_embed_multilingual_v2_model(cohere_instance,):
+def test_cohere_call_with_embed_multilingual_v2_model(
+    cohere_instance,
+):
     cohere_instance.model = "embed-multilingual-v2.0"
     response = cohere_instance("Translate to French.")
     assert isinstance(response, str)
 
 
-def test_cohere_call_with_embed_multilingual_v3_model(cohere_instance,):
+def test_cohere_call_with_embed_multilingual_v3_model(
+    cohere_instance,
+):
     cohere_instance.model = "embed-multilingual-v3.0"
     response = cohere_instance("Translate to French.")
     assert isinstance(response, str)
@@ -293,7 +329,9 @@ def test_cohere_call_with_long_prompt(cohere_instance):
 
 def test_cohere_call_with_max_tokens_limit_exceeded(cohere_instance):
     cohere_instance.max_tokens = 10
-    prompt = ("This is a test prompt that will exceed the max tokens limit.")
+    prompt = (
+        "This is a test prompt that will exceed the max tokens limit."
+    )
     with pytest.raises(ValueError):
         cohere_instance(prompt)
 
@@ -326,14 +364,18 @@ def test_cohere_stream_with_embed_english_v3_model(cohere_instance):
         assert isinstance(token, str)
 
 
-def test_cohere_stream_with_embed_multilingual_v2_model(cohere_instance,):
+def test_cohere_stream_with_embed_multilingual_v2_model(
+    cohere_instance,
+):
     cohere_instance.model = "embed-multilingual-v2.0"
     generator = cohere_instance.stream("Write a story.")
     for token in generator:
         assert isinstance(token, str)
 
 
-def test_cohere_stream_with_embed_multilingual_v3_model(cohere_instance,):
+def test_cohere_stream_with_embed_multilingual_v3_model(
+    cohere_instance,
+):
     cohere_instance.model = "embed-multilingual-v3.0"
     generator = cohere_instance.stream("Write a story.")
     for token in generator:
@@ -352,25 +394,33 @@ def test_cohere_async_call_with_base_model(cohere_instance):
     assert isinstance(response, str)
 
 
-def test_cohere_async_call_with_embed_english_v2_model(cohere_instance,):
+def test_cohere_async_call_with_embed_english_v2_model(
+    cohere_instance,
+):
     cohere_instance.model = "embed-english-v2.0"
     response = cohere_instance.async_call("Translate to French.")
     assert isinstance(response, str)
 
 
-def test_cohere_async_call_with_embed_english_v3_model(cohere_instance,):
+def test_cohere_async_call_with_embed_english_v3_model(
+    cohere_instance,
+):
     cohere_instance.model = "embed-english-v3.0"
     response = cohere_instance.async_call("Translate to French.")
     assert isinstance(response, str)
 
 
-def test_cohere_async_call_with_embed_multilingual_v2_model(cohere_instance,):
+def test_cohere_async_call_with_embed_multilingual_v2_model(
+    cohere_instance,
+):
     cohere_instance.model = "embed-multilingual-v2.0"
     response = cohere_instance.async_call("Translate to French.")
     assert isinstance(response, str)
 
 
-def test_cohere_async_call_with_embed_multilingual_v3_model(cohere_instance,):
+def test_cohere_async_call_with_embed_multilingual_v3_model(
+    cohere_instance,
+):
     cohere_instance.model = "embed-multilingual-v3.0"
     response = cohere_instance.async_call("Translate to French.")
     assert isinstance(response, str)
@@ -390,28 +440,36 @@ def test_cohere_async_stream_with_base_model(cohere_instance):
         assert isinstance(token, str)
 
 
-def test_cohere_async_stream_with_embed_english_v2_model(cohere_instance,):
+def test_cohere_async_stream_with_embed_english_v2_model(
+    cohere_instance,
+):
     cohere_instance.model = "embed-english-v2.0"
     async_generator = cohere_instance.async_stream("Write a story.")
     for token in async_generator:
         assert isinstance(token, str)
 
 
-def test_cohere_async_stream_with_embed_english_v3_model(cohere_instance,):
+def test_cohere_async_stream_with_embed_english_v3_model(
+    cohere_instance,
+):
     cohere_instance.model = "embed-english-v3.0"
     async_generator = cohere_instance.async_stream("Write a story.")
     for token in async_generator:
         assert isinstance(token, str)
 
 
-def test_cohere_async_stream_with_embed_multilingual_v2_model(cohere_instance,):
+def test_cohere_async_stream_with_embed_multilingual_v2_model(
+    cohere_instance,
+):
     cohere_instance.model = "embed-multilingual-v2.0"
     async_generator = cohere_instance.async_stream("Write a story.")
     for token in async_generator:
         assert isinstance(token, str)
 
 
-def test_cohere_async_stream_with_embed_multilingual_v3_model(cohere_instance,):
+def test_cohere_async_stream_with_embed_multilingual_v3_model(
+    cohere_instance,
+):
     cohere_instance.model = "embed-multilingual-v3.0"
     async_generator = cohere_instance.async_stream("Write a story.")
     for token in async_generator:
@@ -421,7 +479,9 @@ def test_cohere_async_stream_with_embed_multilingual_v3_model(cohere_instance,):
 def test_cohere_representation_model_embedding(cohere_instance):
     # Test using the Representation model for text embedding
     cohere_instance.model = "embed-english-v3.0"
-    embedding = cohere_instance.embed("Generate an embedding for this text.")
+    embedding = cohere_instance.embed(
+        "Generate an embedding for this text."
+    )
     assert isinstance(embedding, list)
     assert len(embedding) > 0
 
@@ -435,20 +495,26 @@ def test_cohere_representation_model_classification(cohere_instance):
     assert "score" in classification
 
 
-def test_cohere_representation_model_language_detection(cohere_instance,):
+def test_cohere_representation_model_language_detection(
+    cohere_instance,
+):
     # Test using the Representation model for language detection
     cohere_instance.model = "embed-english-v3.0"
     language = cohere_instance.detect_language(
-        "Detect the language of this text.")
+        "Detect the language of this text."
+    )
     assert isinstance(language, str)
 
 
 def test_cohere_representation_model_max_tokens_limit_exceeded(
-    cohere_instance,):
+    cohere_instance,
+):
     # Test handling max tokens limit exceeded error
     cohere_instance.model = "embed-english-v3.0"
     cohere_instance.max_tokens = 10
-    prompt = ("This is a test prompt that will exceed the max tokens limit.")
+    prompt = (
+        "This is a test prompt that will exceed the max tokens limit."
+    )
     with pytest.raises(ValueError):
         cohere_instance.embed(prompt)
 
@@ -456,80 +522,102 @@ def test_cohere_representation_model_max_tokens_limit_exceeded(
 # Add more production-grade test cases based on real-world scenarios
 
 
-def test_cohere_representation_model_multilingual_embedding(cohere_instance,):
+def test_cohere_representation_model_multilingual_embedding(
+    cohere_instance,
+):
     # Test using the Representation model for multilingual text embedding
     cohere_instance.model = "embed-multilingual-v3.0"
-    embedding = cohere_instance.embed("Generate multilingual embeddings.")
+    embedding = cohere_instance.embed(
+        "Generate multilingual embeddings."
+    )
     assert isinstance(embedding, list)
     assert len(embedding) > 0
 
 
 def test_cohere_representation_model_multilingual_classification(
-    cohere_instance,):
+    cohere_instance,
+):
     # Test using the Representation model for multilingual text classification
     cohere_instance.model = "embed-multilingual-v3.0"
-    classification = cohere_instance.classify("Classify multilingual text.")
+    classification = cohere_instance.classify(
+        "Classify multilingual text."
+    )
     assert isinstance(classification, dict)
     assert "class" in classification
     assert "score" in classification
 
 
 def test_cohere_representation_model_multilingual_language_detection(
-    cohere_instance,):
+    cohere_instance,
+):
     # Test using the Representation model for multilingual language detection
     cohere_instance.model = "embed-multilingual-v3.0"
     language = cohere_instance.detect_language(
-        "Detect the language of multilingual text.")
+        "Detect the language of multilingual text."
+    )
     assert isinstance(language, str)
 
 
 def test_cohere_representation_model_multilingual_max_tokens_limit_exceeded(
-    cohere_instance,):
+    cohere_instance,
+):
     # Test handling max tokens limit exceeded error for multilingual model
     cohere_instance.model = "embed-multilingual-v3.0"
     cohere_instance.max_tokens = 10
-    prompt = ("This is a test prompt that will exceed the max tokens limit"
-              " for multilingual model.")
+    prompt = (
+        "This is a test prompt that will exceed the max tokens limit"
+        " for multilingual model."
+    )
     with pytest.raises(ValueError):
         cohere_instance.embed(prompt)
 
 
 def test_cohere_representation_model_multilingual_light_embedding(
-    cohere_instance,):
+    cohere_instance,
+):
     # Test using the Representation model for multilingual light text embedding
     cohere_instance.model = "embed-multilingual-light-v3.0"
-    embedding = cohere_instance.embed("Generate multilingual light embeddings.")
+    embedding = cohere_instance.embed(
+        "Generate multilingual light embeddings."
+    )
     assert isinstance(embedding, list)
     assert len(embedding) > 0
 
 
 def test_cohere_representation_model_multilingual_light_classification(
-    cohere_instance,):
+    cohere_instance,
+):
     # Test using the Representation model for multilingual light text classification
     cohere_instance.model = "embed-multilingual-light-v3.0"
     classification = cohere_instance.classify(
-        "Classify multilingual light text.")
+        "Classify multilingual light text."
+    )
     assert isinstance(classification, dict)
     assert "class" in classification
     assert "score" in classification
 
 
 def test_cohere_representation_model_multilingual_light_language_detection(
-    cohere_instance,):
+    cohere_instance,
+):
     # Test using the Representation model for multilingual light language detection
     cohere_instance.model = "embed-multilingual-light-v3.0"
     language = cohere_instance.detect_language(
-        "Detect the language of multilingual light text.")
+        "Detect the language of multilingual light text."
+    )
     assert isinstance(language, str)
 
 
 def test_cohere_representation_model_multilingual_light_max_tokens_limit_exceeded(
-    cohere_instance,):
+    cohere_instance,
+):
     # Test handling max tokens limit exceeded error for multilingual light model
     cohere_instance.model = "embed-multilingual-light-v3.0"
     cohere_instance.max_tokens = 10
-    prompt = ("This is a test prompt that will exceed the max tokens limit"
-              " for multilingual light model.")
+    prompt = (
+        "This is a test prompt that will exceed the max tokens limit"
+        " for multilingual light model."
+    )
     with pytest.raises(ValueError):
         cohere_instance.embed(prompt)
 
@@ -537,14 +625,18 @@ def test_cohere_representation_model_multilingual_light_max_tokens_limit_exceede
 def test_cohere_command_light_model(cohere_instance):
     # Test using the Command Light model for text generation
     cohere_instance.model = "command-light"
-    response = cohere_instance("Generate text using Command Light model.")
+    response = cohere_instance(
+        "Generate text using Command Light model."
+    )
     assert isinstance(response, str)
 
 
 def test_cohere_base_light_model(cohere_instance):
     # Test using the Base Light model for text generation
     cohere_instance.model = "base-light"
-    response = cohere_instance("Generate text using Base Light model.")
+    response = cohere_instance(
+        "Generate text using Base Light model."
+    )
     assert isinstance(response, str)
 
 
@@ -555,7 +647,9 @@ def test_cohere_generate_summarize_endpoint(cohere_instance):
     assert isinstance(response, str)
 
 
-def test_cohere_representation_model_english_embedding(cohere_instance,):
+def test_cohere_representation_model_english_embedding(
+    cohere_instance,
+):
     # Test using the Representation model for English text embedding
     cohere_instance.model = "embed-english-v3.0"
     embedding = cohere_instance.embed("Generate English embeddings.")
@@ -563,69 +657,90 @@ def test_cohere_representation_model_english_embedding(cohere_instance,):
     assert len(embedding) > 0
 
 
-def test_cohere_representation_model_english_classification(cohere_instance,):
+def test_cohere_representation_model_english_classification(
+    cohere_instance,
+):
     # Test using the Representation model for English text classification
     cohere_instance.model = "embed-english-v3.0"
-    classification = cohere_instance.classify("Classify English text.")
+    classification = cohere_instance.classify(
+        "Classify English text."
+    )
     assert isinstance(classification, dict)
     assert "class" in classification
     assert "score" in classification
 
 
 def test_cohere_representation_model_english_language_detection(
-    cohere_instance,):
+    cohere_instance,
+):
     # Test using the Representation model for English language detection
     cohere_instance.model = "embed-english-v3.0"
     language = cohere_instance.detect_language(
-        "Detect the language of English text.")
+        "Detect the language of English text."
+    )
     assert isinstance(language, str)
 
 
 def test_cohere_representation_model_english_max_tokens_limit_exceeded(
-    cohere_instance,):
+    cohere_instance,
+):
     # Test handling max tokens limit exceeded error for English model
     cohere_instance.model = "embed-english-v3.0"
     cohere_instance.max_tokens = 10
-    prompt = ("This is a test prompt that will exceed the max tokens limit"
-              " for English model.")
+    prompt = (
+        "This is a test prompt that will exceed the max tokens limit"
+        " for English model."
+    )
     with pytest.raises(ValueError):
         cohere_instance.embed(prompt)
 
 
-def test_cohere_representation_model_english_light_embedding(cohere_instance,):
+def test_cohere_representation_model_english_light_embedding(
+    cohere_instance,
+):
     # Test using the Representation model for English light text embedding
     cohere_instance.model = "embed-english-light-v3.0"
-    embedding = cohere_instance.embed("Generate English light embeddings.")
+    embedding = cohere_instance.embed(
+        "Generate English light embeddings."
+    )
     assert isinstance(embedding, list)
     assert len(embedding) > 0
 
 
 def test_cohere_representation_model_english_light_classification(
-    cohere_instance,):
+    cohere_instance,
+):
     # Test using the Representation model for English light text classification
     cohere_instance.model = "embed-english-light-v3.0"
-    classification = cohere_instance.classify("Classify English light text.")
+    classification = cohere_instance.classify(
+        "Classify English light text."
+    )
     assert isinstance(classification, dict)
     assert "class" in classification
     assert "score" in classification
 
 
 def test_cohere_representation_model_english_light_language_detection(
-    cohere_instance,):
+    cohere_instance,
+):
     # Test using the Representation model for English light language detection
     cohere_instance.model = "embed-english-light-v3.0"
     language = cohere_instance.detect_language(
-        "Detect the language of English light text.")
+        "Detect the language of English light text."
+    )
     assert isinstance(language, str)
 
 
 def test_cohere_representation_model_english_light_max_tokens_limit_exceeded(
-    cohere_instance,):
+    cohere_instance,
+):
     # Test handling max tokens limit exceeded error for English light model
     cohere_instance.model = "embed-english-light-v3.0"
     cohere_instance.max_tokens = 10
-    prompt = ("This is a test prompt that will exceed the max tokens limit"
-              " for English light model.")
+    prompt = (
+        "This is a test prompt that will exceed the max tokens limit"
+        " for English light model."
+    )
     with pytest.raises(ValueError):
         cohere_instance.embed(prompt)
 
@@ -633,7 +748,9 @@ def test_cohere_representation_model_english_light_max_tokens_limit_exceeded(
 def test_cohere_command_model(cohere_instance):
     # Test using the Command model for text generation
     cohere_instance.model = "command"
-    response = cohere_instance("Generate text using the Command model.")
+    response = cohere_instance(
+        "Generate text using the Command model."
+    )
     assert isinstance(response, str)
 
 
@@ -647,7 +764,9 @@ def test_cohere_invalid_model(cohere_instance):
         cohere_instance("Generate text using an invalid model.")
 
 
-def test_cohere_base_model_generation_with_max_tokens(cohere_instance,):
+def test_cohere_base_model_generation_with_max_tokens(
+    cohere_instance,
+):
     # Test generating text using the base model with a specified max_tokens limit
     cohere_instance.model = "base"
     cohere_instance.max_tokens = 20

tests/models/test_elevenlab.py

@@ -30,30 +30,45 @@ def test_run_text_to_speech(eleven_labs_tool):
 
 
 def test_play_speech(eleven_labs_tool):
-    with patch("builtins.open", mock_open(read_data="fake_audio_data")):
+    with patch(
+        "builtins.open", mock_open(read_data="fake_audio_data")
+    ):
         eleven_labs_tool.play(EXPECTED_SPEECH_FILE)
 
 
 def test_stream_speech(eleven_labs_tool):
-    with patch("tempfile.NamedTemporaryFile", mock_open()) as mock_file:
+    with patch(
+        "tempfile.NamedTemporaryFile", mock_open()
+    ) as mock_file:
         eleven_labs_tool.stream_speech(SAMPLE_TEXT)
-        mock_file.assert_called_with(mode="bx", suffix=".wav", delete=False)
+        mock_file.assert_called_with(
+            mode="bx", suffix=".wav", delete=False
+        )
 
 
 # Testing fixture and environment variables
 def test_api_key_validation(eleven_labs_tool):
-    with patch("langchain.utils.get_from_dict_or_env", return_value=API_KEY):
+    with patch(
+        "langchain.utils.get_from_dict_or_env", return_value=API_KEY
+    ):
         values = {"eleven_api_key": None}
-        validated_values = eleven_labs_tool.validate_environment(values)
+        validated_values = eleven_labs_tool.validate_environment(
+            values
+        )
         assert "eleven_api_key" in validated_values
 
 
 # Mocking the external library
 def test_run_text_to_speech_with_mock(eleven_labs_tool):
-    with patch("tempfile.NamedTemporaryFile", mock_open()) as mock_file, patch(
-            "your_module._import_elevenlabs") as mock_elevenlabs:
+    with patch(
+        "tempfile.NamedTemporaryFile", mock_open()
+    ) as mock_file, patch(
+        "your_module._import_elevenlabs"
+    ) as mock_elevenlabs:
         mock_elevenlabs_instance = mock_elevenlabs.return_value
-        mock_elevenlabs_instance.generate.return_value = (b"fake_audio_data")
+        mock_elevenlabs_instance.generate.return_value = (
+            b"fake_audio_data"
+        )
         eleven_labs_tool.run(SAMPLE_TEXT)
         assert mock_file.call_args[1]["suffix"] == ".wav"
         assert mock_file.call_args[1]["delete"] is False
@@ -65,11 +80,14 @@ def test_run_text_to_speech_error_handling(eleven_labs_tool):
     with patch("your_module._import_elevenlabs") as mock_elevenlabs:
         mock_elevenlabs_instance = mock_elevenlabs.return_value
         mock_elevenlabs_instance.generate.side_effect = Exception(
-            "Test Exception")
+            "Test Exception"
+        )
         with pytest.raises(
             RuntimeError,
-                match=("Error while running ElevenLabsText2SpeechTool: Test"
-                       " Exception"),
+            match=(
+                "Error while running ElevenLabsText2SpeechTool: Test"
+                " Exception"
+            ),
         ):
             eleven_labs_tool.run(SAMPLE_TEXT)
 
@@ -79,7 +97,9 @@ def test_run_text_to_speech_error_handling(eleven_labs_tool):
     "model",
     [ElevenLabsModel.MULTI_LINGUAL, ElevenLabsModel.MONO_LINGUAL],
 )
-def test_run_text_to_speech_with_different_models(eleven_labs_tool, model):
+def test_run_text_to_speech_with_different_models(
+    eleven_labs_tool, model
+):
     eleven_labs_tool.model = model
     speech_file = eleven_labs_tool.run(SAMPLE_TEXT)
     assert isinstance(speech_file, str)

tests/models/test_fire_function_caller.py

@@ -39,4 +39,6 @@ def test_fire_function_caller_run(mocker):
     tokenizer.batch_decode.assert_called_once_with(generated_ids)
 
     # Assert the decoded output is printed
-    assert decoded_output in mocker.patch.object(print, "call_args_list")
+    assert decoded_output in mocker.patch.object(
+        print, "call_args_list"
+    )

tests/models/test_fuyu.py

@@ -38,7 +38,9 @@ def fuyu_instance():
 # Test using the fixture.
 def test_fuyu_processor_initialization(fuyu_instance):
     assert isinstance(fuyu_instance.processor, FuyuProcessor)
-    assert isinstance(fuyu_instance.image_processor, FuyuImageProcessor)
+    assert isinstance(
+        fuyu_instance.image_processor, FuyuImageProcessor
+    )
 
 
 # Test exception when providing an invalid image path.
@@ -49,7 +51,6 @@ def test_invalid_image_path(fuyu_instance):
 
 # Using monkeypatch to replace the Image.open method to simulate a failure.
 def test_image_open_failure(fuyu_instance, monkeypatch):
-
     def mock_open(*args, **kwargs):
         raise Exception("Mocked failure")
 
@@ -78,9 +79,13 @@ def test_tokenizer_type(fuyu_instance):
 
 
 def test_processor_has_image_processor_and_tokenizer(fuyu_instance):
-    assert (fuyu_instance.processor.image_processor ==
-            fuyu_instance.image_processor)
-    assert (fuyu_instance.processor.tokenizer == fuyu_instance.tokenizer)
+    assert (
+        fuyu_instance.processor.image_processor
+        == fuyu_instance.image_processor
+    )
+    assert (
+        fuyu_instance.processor.tokenizer == fuyu_instance.tokenizer
+    )
 
 
 def test_model_device_map(fuyu_instance):
@@ -139,14 +144,22 @@ def test_get_img_invalid_path(fuyu_instance):
 
 # Test `run` method with valid inputs
 def test_run_valid_inputs(fuyu_instance):
-    with patch.object(fuyu_instance, "get_img") as mock_get_img, patch.object(
-            fuyu_instance, "processor") as mock_processor, patch.object(
-                fuyu_instance, "model") as mock_model:
+    with patch.object(
+        fuyu_instance, "get_img"
+    ) as mock_get_img, patch.object(
+        fuyu_instance, "processor"
+    ) as mock_processor, patch.object(
+        fuyu_instance, "model"
+    ) as mock_model:
         mock_get_img.return_value = "Test image"
-        mock_processor.return_value = {"input_ids": torch.tensor([1, 2, 3])}
+        mock_processor.return_value = {
+            "input_ids": torch.tensor([1, 2, 3])
+        }
         mock_model.generate.return_value = torch.tensor([1, 2, 3])
         mock_processor.batch_decode.return_value = ["Test text"]
-        result = fuyu_instance.run("Hello, world!", "valid/path/to/image.png")
+        result = fuyu_instance.run(
+            "Hello, world!", "valid/path/to/image.png"
+        )
     assert result == ["Test text"]
 
 
@@ -173,7 +186,9 @@ def test_run_invalid_image_path(fuyu_instance):
     with patch.object(fuyu_instance, "get_img") as mock_get_img:
         mock_get_img.side_effect = FileNotFoundError
         with pytest.raises(FileNotFoundError):
-            fuyu_instance.run("Hello, world!", "invalid/path/to/image.png")
+            fuyu_instance.run(
+                "Hello, world!", "invalid/path/to/image.png"
+            )
 
 
 # Test `__init__` method with default parameters

tests/models/test_gemini.py

@@ -24,8 +24,12 @@ def test_gemini_init_defaults(mock_gemini_api_key, mock_genai_model):
     assert model.model is mock_genai_model
 
 
-def test_gemini_init_custom_params(mock_gemini_api_key, mock_genai_model):
-    model = Gemini(model_name="custom-model", gemini_api_key="custom-api-key")
+def test_gemini_init_custom_params(
+    mock_gemini_api_key, mock_genai_model
+):
+    model = Gemini(
+        model_name="custom-model", gemini_api_key="custom-api-key"
+    )
     assert model.model_name == "custom-model"
     assert model.gemini_api_key == "custom-api-key"
     assert model.model is mock_genai_model
@@ -50,13 +54,16 @@ def test_gemini_run_with_img(
     response = model.run(task=task, img=img)
 
     assert response == "Generated response"
-    mock_generate_content.assert_called_with(content=[task, "Processed image"])
+    mock_generate_content.assert_called_with(
+        content=[task, "Processed image"]
+    )
     mock_process_img.assert_called_with(img=img)
 
 
 @patch("swarms.models.gemini.genai.GenerativeModel.generate_content")
-def test_gemini_run_without_img(mock_generate_content, mock_gemini_api_key,
-                                mock_genai_model):
+def test_gemini_run_without_img(
+    mock_generate_content, mock_gemini_api_key, mock_genai_model
+):
     model = Gemini()
     task = "A cat"
     response_mock = Mock(text="Generated response")
@@ -69,8 +76,9 @@ def test_gemini_run_without_img(mock_generate_content, mock_gemini_api_key,
 
 
 @patch("swarms.models.gemini.genai.GenerativeModel.generate_content")
-def test_gemini_run_exception(mock_generate_content, mock_gemini_api_key,
-                              mock_genai_model):
+def test_gemini_run_exception(
+    mock_generate_content, mock_gemini_api_key, mock_genai_model
+):
     model = Gemini()
     task = "A cat"
     mock_generate_content.side_effect = Exception("Test exception")
@@ -88,23 +96,30 @@ def test_gemini_process_img(mock_gemini_api_key, mock_genai_model):
 
     with patch("builtins.open", create=True) as open_mock:
         open_mock.return_value.__enter__.return_value.read.return_value = (
-            img_data)
+            img_data
+        )
 
         processed_img = model.process_img(img)
 
-    assert processed_img == [{"mime_type": "image/png", "data": img_data}]
+    assert processed_img == [
+        {"mime_type": "image/png", "data": img_data}
+    ]
     open_mock.assert_called_with(img, "rb")
 
 
 # Test Gemini initialization with missing API key
 def test_gemini_init_missing_api_key():
-    with pytest.raises(ValueError, match="Please provide a Gemini API key"):
+    with pytest.raises(
+        ValueError, match="Please provide a Gemini API key"
+    ):
         Gemini(gemini_api_key=None)
 
 
 # Test Gemini initialization with missing model name
 def test_gemini_init_missing_model_name():
-    with pytest.raises(ValueError, match="Please provide a model name"):
+    with pytest.raises(
+        ValueError, match="Please provide a model name"
+    ):
         Gemini(model_name=None)
 
 
@@ -126,20 +141,26 @@ def test_gemini_run_empty_img(mock_gemini_api_key, mock_genai_model):
 
 
 # Test Gemini process_img method with missing image
-def test_gemini_process_img_missing_image(mock_gemini_api_key,
-                                          mock_genai_model):
+def test_gemini_process_img_missing_image(
+    mock_gemini_api_key, mock_genai_model
+):
     model = Gemini()
     img = None
-    with pytest.raises(ValueError, match="Please provide an image to process"):
+    with pytest.raises(
+        ValueError, match="Please provide an image to process"
+    ):
         model.process_img(img=img)
 
 
 # Test Gemini process_img method with missing image type
-def test_gemini_process_img_missing_image_type(mock_gemini_api_key,
-                                               mock_genai_model):
+def test_gemini_process_img_missing_image_type(
+    mock_gemini_api_key, mock_genai_model
+):
     model = Gemini()
     img = "cat.png"
-    with pytest.raises(ValueError, match="Please provide the image type"):
+    with pytest.raises(
+        ValueError, match="Please provide the image type"
+    ):
         model.process_img(img=img, type=None)
 
 
@@ -147,7 +168,9 @@ def test_gemini_process_img_missing_image_type(mock_gemini_api_key,
 def test_gemini_process_img_missing_api_key(mock_genai_model):
     model = Gemini(gemini_api_key=None)
     img = "cat.png"
-    with pytest.raises(ValueError, match="Please provide a Gemini API key"):
+    with pytest.raises(
+        ValueError, match="Please provide a Gemini API key"
+    ):
         model.process_img(img=img, type="image/png")
 
 
@@ -170,7 +193,9 @@ def test_gemini_run_mock_img_processing(
     response = model.run(task=task, img=img)
 
     assert response == "Generated response"
-    mock_generate_content.assert_called_with(content=[task, "Processed image"])
+    mock_generate_content.assert_called_with(
+        content=[task, "Processed image"]
+    )
     mock_process_img.assert_called_with(img=img)
 
 

tests/models/test_gigabind.py

@@ -11,13 +11,16 @@ except ImportError:
 
 @pytest.fixture
 def api():
-    return Gigabind(host="localhost", port=8000, endpoint="embeddings")
+    return Gigabind(
+        host="localhost", port=8000, endpoint="embeddings"
+    )
 
 
 @pytest.fixture
 def mock(requests_mock):
-    requests_mock.post("http://localhost:8000/embeddings",
-                       json={"result": "success"})
+    requests_mock.post(
+        "http://localhost:8000/embeddings", json={"result": "success"}
+    )
     return requests_mock
 
 
@@ -37,9 +40,9 @@ def test_run_with_audio(api, mock):
 
 
 def test_run_with_all(api, mock):
-    response = api.run(text="Hello, world!",
-                       vision="image.jpg",
-                       audio="audio.mp3")
+    response = api.run(
+        text="Hello, world!", vision="image.jpg", audio="audio.mp3"
+    )
     assert response == {"result": "success"}
 
 
@@ -62,20 +65,9 @@ def test_retry_on_failure(api, requests_mock):
     requests_mock.post(
         "http://localhost:8000/embeddings",
         [
-            {
-                "status_code": 500,
-                "json": {}
-            },
-            {
-                "status_code": 500,
-                "json": {}
-            },
-            {
-                "status_code": 200,
-                "json": {
-                    "result": "success"
-                }
-            },
+            {"status_code": 500, "json": {}},
+            {"status_code": 500, "json": {}},
+            {"status_code": 200, "json": {"result": "success"}},
         ],
     )
     response = api.run(text="Hello, world!")
@@ -86,18 +78,9 @@ def test_retry_exhausted(api, requests_mock):
     requests_mock.post(
         "http://localhost:8000/embeddings",
         [
-            {
-                "status_code": 500,
-                "json": {}
-            },
-            {
-                "status_code": 500,
-                "json": {}
-            },
-            {
-                "status_code": 500,
-                "json": {}
-            },
+            {"status_code": 500, "json": {}},
+            {"status_code": 500, "json": {}},
+            {"status_code": 500, "json": {}},
         ],
     )
     response = api.run(text="Hello, world!")
@@ -110,7 +93,9 @@ def test_proxy_url(api):
 
 
 def test_invalid_response(api, requests_mock):
-    requests_mock.post("http://localhost:8000/embeddings", text="not json")
+    requests_mock.post(
+        "http://localhost:8000/embeddings", text="not json"
+    )
     response = api.run(text="Hello, world!")
     assert response is None
 
@@ -125,7 +110,9 @@ def test_connection_error(api, requests_mock):
 
 
 def test_http_error(api, requests_mock):
-    requests_mock.post("http://localhost:8000/embeddings", status_code=500)
+    requests_mock.post(
+        "http://localhost:8000/embeddings", status_code=500
+    )
     response = api.run(text="Hello, world!")
     assert response is None
 
@@ -161,7 +148,9 @@ def test_run_with_large_all(api, mock):
     large_text = "Hello, world! " * 10000  # 10,000 repetitions
     large_vision = "image.jpg" * 10000  # 10,000 repetitions
     large_audio = "audio.mp3" * 10000  # 10,000 repetitions
-    response = api.run(text=large_text, vision=large_vision, audio=large_audio)
+    response = api.run(
+        text=large_text, vision=large_vision, audio=large_audio
+    )
     assert response == {"result": "success"}
 
 

tests/models/test_gpt4_vision_api.py

@@ -46,7 +46,9 @@ def test_run_success(vision_api):
 
 
 def test_run_request_error(vision_api):
-    with patch("requests.post", side_effect=RequestException("Request Error")):
+    with patch(
+        "requests.post", side_effect=RequestException("Request Error")
+    ):
         with pytest.raises(RequestException):
             vision_api.run("What is this?", img)
 
@@ -62,7 +64,9 @@ def test_run_response_error(vision_api):
 
 
 def test_call(vision_api):
-    expected_response = {"choices": [{"text": "This is the model's response."}]}
+    expected_response = {
+        "choices": [{"text": "This is the model's response."}]
+    }
     with patch(
         "requests.post",
         return_value=Mock(json=lambda: expected_response),
@@ -91,7 +95,9 @@ def test_initialization_with_custom_key():
 def test_run_with_exception(gpt_api):
     task = "What is in the image?"
     img_url = img
-    with patch("requests.post", side_effect=Exception("Test Exception")):
+    with patch(
+        "requests.post", side_effect=Exception("Test Exception")
+    ):
         with pytest.raises(Exception):
             gpt_api.run(task, img_url)
 
@@ -99,10 +105,14 @@ def test_run_with_exception(gpt_api):
 def test_call_method_successful_response(gpt_api):
     task = "What is in the image?"
     img_url = img
-    response_json = {"choices": [{"text": "Answer from GPT-4 Vision"}]}
+    response_json = {
+        "choices": [{"text": "Answer from GPT-4 Vision"}]
+    }
     mock_response = Mock()
     mock_response.json.return_value = response_json
-    with patch("requests.post", return_value=mock_response) as mock_post:
+    with patch(
+        "requests.post", return_value=mock_response
+    ) as mock_post:
         result = gpt_api(task, img_url)
         mock_post.assert_called_once()
     assert result == response_json
@@ -111,7 +121,9 @@ def test_call_method_successful_response(gpt_api):
 def test_call_method_with_exception(gpt_api):
     task = "What is in the image?"
     img_url = img
-    with patch("requests.post", side_effect=Exception("Test Exception")):
+    with patch(
+        "requests.post", side_effect=Exception("Test Exception")
+    ):
         with pytest.raises(Exception):
             gpt_api(task, img_url)
 
@@ -119,17 +131,16 @@ def test_call_method_with_exception(gpt_api):
 @pytest.mark.asyncio
 async def test_arun_success(vision_api):
     expected_response = {
-        "choices": [{
-            "message": {
-                "content": "This is the model's response."
-            }
-        }]
+        "choices": [
+            {"message": {"content": "This is the model's response."}}
+        ]
     }
     with patch(
         "aiohttp.ClientSession.post",
         new_callable=AsyncMock,
-            return_value=AsyncMock(json=AsyncMock(
-                return_value=expected_response)),
+        return_value=AsyncMock(
+            json=AsyncMock(return_value=expected_response)
+        ),
     ) as mock_post:
         result = await vision_api.arun("What is this?", img)
         mock_post.assert_called_once()
@@ -149,11 +160,9 @@ async def test_arun_request_error(vision_api):
 
 def test_run_many_success(vision_api):
     expected_response = {
-        "choices": [{
-            "message": {
-                "content": "This is the model's response."
-            }
-        }]
+        "choices": [
+            {"message": {"content": "This is the model's response."}}
+        ]
     }
     with patch(
         "requests.post",
@@ -170,7 +179,9 @@ def test_run_many_success(vision_api):
 
 
 def test_run_many_request_error(vision_api):
-    with patch("requests.post", side_effect=RequestException("Request Error")):
+    with patch(
+        "requests.post", side_effect=RequestException("Request Error")
+    ):
         tasks = ["What is this?", "What is that?"]
         imgs = [img, img]
         with pytest.raises(RequestException):
@@ -182,7 +193,9 @@ async def test_arun_json_decode_error(vision_api):
     with patch(
         "aiohttp.ClientSession.post",
         new_callable=AsyncMock,
-            return_value=AsyncMock(json=AsyncMock(side_effect=ValueError)),
+        return_value=AsyncMock(
+            json=AsyncMock(side_effect=ValueError)
+        ),
     ):
         with pytest.raises(ValueError):
             await vision_api.arun("What is this?", img)
@@ -194,7 +207,9 @@ async def test_arun_api_error(vision_api):
     with patch(
         "aiohttp.ClientSession.post",
         new_callable=AsyncMock,
-            return_value=AsyncMock(json=AsyncMock(return_value=error_response)),
+        return_value=AsyncMock(
+            json=AsyncMock(return_value=error_response)
+        ),
     ):
         with pytest.raises(Exception, match="API Error"):
             await vision_api.arun("What is this?", img)
@@ -206,8 +221,9 @@ async def test_arun_unexpected_response(vision_api):
     with patch(
         "aiohttp.ClientSession.post",
         new_callable=AsyncMock,
-            return_value=AsyncMock(json=AsyncMock(
-                return_value=unexpected_response)),
+        return_value=AsyncMock(
+            json=AsyncMock(return_value=unexpected_response)
+        ),
     ):
         with pytest.raises(Exception, match="Unexpected response"):
             await vision_api.arun("What is this?", img)

tests/models/test_hf.py

@@ -133,7 +133,9 @@ def test_llm_set_repitition_penalty(llm_instance):
 def test_llm_set_no_repeat_ngram_size(llm_instance):
     new_no_repeat_ngram_size = 6
     llm_instance.set_no_repeat_ngram_size(new_no_repeat_ngram_size)
-    assert (llm_instance.no_repeat_ngram_size == new_no_repeat_ngram_size)
+    assert (
+        llm_instance.no_repeat_ngram_size == new_no_repeat_ngram_size
+    )
 
 
 # Test for setting temperature
@@ -183,7 +185,9 @@ def test_llm_set_model_id(llm_instance):
 
 
 # Test for setting model
-@patch("swarms.models.huggingface.AutoModelForCausalLM.from_pretrained")
+@patch(
+    "swarms.models.huggingface.AutoModelForCausalLM.from_pretrained"
+)
 def test_llm_set_model(mock_model, llm_instance):
     mock_model.return_value = "mocked model"
     llm_instance.set_model(mock_model)

tests/models/test_hf_pipeline.py

@@ -14,14 +14,19 @@ def mock_pipeline():
 
 @pytest.fixture
 def pipeline(mock_pipeline):
-    return HuggingfacePipeline("text-generation",
-                               "meta-llama/Llama-2-13b-chat-hf")
+    return HuggingfacePipeline(
+        "text-generation", "meta-llama/Llama-2-13b-chat-hf"
+    )
 
 
 def test_init(pipeline, mock_pipeline):
     assert pipeline.task_type == "text-generation"
     assert pipeline.model_name == "meta-llama/Llama-2-13b-chat-hf"
-    assert (pipeline.use_fp8 is True if torch.cuda.is_available() else False)
+    assert (
+        pipeline.use_fp8 is True
+        if torch.cuda.is_available()
+        else False
+    )
     mock_pipeline.assert_called_once_with(
         "text-generation",
         "meta-llama/Llama-2-13b-chat-hf",
@@ -46,5 +51,6 @@ def test_run_with_different_task(pipeline, mock_pipeline):
     mock_pipeline.return_value = "Generated text"
     result = pipeline.run("text-classification", "Hello, world!")
     assert result == "Generated text"
-    mock_pipeline.assert_called_once_with("text-classification",
-                                          "Hello, world!")
+    mock_pipeline.assert_called_once_with(
+        "text-classification", "Hello, world!"
+    )

tests/models/test_huggingface.py

@@ -18,7 +18,10 @@ def llm_instance():
 
 # Test for instantiation and attributes
 def test_llm_initialization(llm_instance):
-    assert (llm_instance.model_id == "NousResearch/Nous-Hermes-2-Vision-Alpha")
+    assert (
+        llm_instance.model_id
+        == "NousResearch/Nous-Hermes-2-Vision-Alpha"
+    )
     assert llm_instance.max_length == 500
     # ... add more assertions for all default attributes
 
@@ -85,11 +88,14 @@ def test_llm_memory_consumption(llm_instance):
 )
 def test_llm_initialization_params(model_id, max_length):
     if max_length:
-        instance = HuggingfaceLLM(model_id=model_id, max_length=max_length)
+        instance = HuggingfaceLLM(
+            model_id=model_id, max_length=max_length
+        )
         assert instance.max_length == max_length
     else:
         instance = HuggingfaceLLM(model_id=model_id)
-        assert (instance.max_length == 500
+        assert (
+            instance.max_length == 500
         )  # Assuming 500 is the default max_length
 
 
@@ -138,7 +144,9 @@ def test_llm_run_output_length(mock_run, llm_instance):
 # Test the tokenizer handling special tokens correctly
 @patch("swarms.models.huggingface.HuggingfaceLLM._tokenizer.encode")
 @patch("swarms.models.huggingface.HuggingfaceLLM._tokenizer.decode")
-def test_llm_tokenizer_special_tokens(mock_decode, mock_encode, llm_instance):
+def test_llm_tokenizer_special_tokens(
+    mock_decode, mock_encode, llm_instance
+):
     mock_encode.return_value = "encoded input with special tokens"
     mock_decode.return_value = "decoded output with special tokens"
     result = llm_instance.run("test task with special tokens")
@@ -164,8 +172,9 @@ def test_llm_response_time(mock_run, llm_instance):
     start_time = time.time()
     llm_instance.run("test task for response time")
     end_time = time.time()
-    assert (end_time - start_time
-            < 1)  # Assuming the response should be faster than 1 second
+    assert (
+        end_time - start_time < 1
+    )  # Assuming the response should be faster than 1 second
 
 
 # Test the logging of a warning for long inputs
@@ -188,10 +197,13 @@ def test_llm_run_model_exception(mock_generate, llm_instance):
 
 # Test the behavior when GPU is forced but not available
 @patch("torch.cuda.is_available", return_value=False)
-def test_llm_force_gpu_when_unavailable(mock_is_available, llm_instance):
+def test_llm_force_gpu_when_unavailable(
+    mock_is_available, llm_instance
+):
     with pytest.raises(EnvironmentError):
         llm_instance.set_device(
-            "cuda")  # Attempt to set CUDA when it's not available
+            "cuda"
+        )  # Attempt to set CUDA when it's not available
 
 
 # Test for proper cleanup after model use (releasing resources)
@@ -209,8 +221,9 @@ def test_llm_multilingual_input(mock_run, llm_instance):
     mock_run.return_value = "mocked multilingual output"
     multilingual_input = "Bonjour, ceci est un test multilingue."
     result = llm_instance.run(multilingual_input)
-    assert isinstance(result,
-                      str)  # Simple check to ensure output is string type
+    assert isinstance(
+        result, str
+    )  # Simple check to ensure output is string type
 
 
 # Test caching mechanism to prevent re-running the same inputs

tests/models/test_idefics.py

@@ -13,8 +13,8 @@ from swarms.models.idefics import (
 @pytest.fixture
 def idefics_instance():
     with patch(
-            "torch.cuda.is_available",
-            return_value=False):  # Assuming tests are run on CPU for simplicity
+        "torch.cuda.is_available", return_value=False
+    ):  # Assuming tests are run on CPU for simplicity
         instance = Idefics()
     return instance
 
@@ -46,10 +46,14 @@ def test_init_device(device, expected):
 # Test `run` method
 def test_run(idefics_instance):
     prompts = [["User: Test"]]
-    with patch.object(idefics_instance,
-                      "processor") as mock_processor, patch.object(
-                          idefics_instance, "model") as mock_model:
-        mock_processor.return_value = {"input_ids": torch.tensor([1, 2, 3])}
+    with patch.object(
+        idefics_instance, "processor"
+    ) as mock_processor, patch.object(
+        idefics_instance, "model"
+    ) as mock_model:
+        mock_processor.return_value = {
+            "input_ids": torch.tensor([1, 2, 3])
+        }
         mock_model.generate.return_value = torch.tensor([1, 2, 3])
         mock_processor.batch_decode.return_value = ["Test"]
 
@@ -61,10 +65,14 @@ def test_run(idefics_instance):
 # Test `__call__` method (using the same logic as run for simplicity)
 def test_call(idefics_instance):
     prompts = [["User: Test"]]
-    with patch.object(idefics_instance,
-                      "processor") as mock_processor, patch.object(
-                          idefics_instance, "model") as mock_model:
-        mock_processor.return_value = {"input_ids": torch.tensor([1, 2, 3])}
+    with patch.object(
+        idefics_instance, "processor"
+    ) as mock_processor, patch.object(
+        idefics_instance, "model"
+    ) as mock_model:
+        mock_processor.return_value = {
+            "input_ids": torch.tensor([1, 2, 3])
+        }
         mock_model.generate.return_value = torch.tensor([1, 2, 3])
         mock_processor.batch_decode.return_value = ["Test"]
 
@@ -77,7 +85,9 @@ def test_call(idefics_instance):
 def test_chat(idefics_instance):
     user_input = "User: Hello"
     response = "Model: Hi there!"
-    with patch.object(idefics_instance, "run", return_value=[response]):
+    with patch.object(
+        idefics_instance, "run", return_value=[response]
+    ):
         result = idefics_instance.chat(user_input)
 
     assert result == response
@@ -87,13 +97,16 @@ def test_chat(idefics_instance):
 # Test `set_checkpoint` method
 def test_set_checkpoint(idefics_instance):
     new_checkpoint = "new_checkpoint"
-    with patch.object(IdeficsForVisionText2Text,
-                      "from_pretrained") as mock_from_pretrained, patch.object(
-                          AutoProcessor, "from_pretrained"):
+    with patch.object(
+        IdeficsForVisionText2Text, "from_pretrained"
+    ) as mock_from_pretrained, patch.object(
+        AutoProcessor, "from_pretrained"
+    ):
         idefics_instance.set_checkpoint(new_checkpoint)
 
-    mock_from_pretrained.assert_called_with(new_checkpoint,
-                                            torch_dtype=torch.bfloat16)
+    mock_from_pretrained.assert_called_with(
+        new_checkpoint, torch_dtype=torch.bfloat16
+    )
 
 
 # Test `set_device` method
@@ -130,10 +143,14 @@ def test_run_with_empty_prompts(idefics_instance):
 # Test `run` method with batched_mode set to False
 def test_run_batched_mode_false(idefics_instance):
     task = "User: Test"
-    with patch.object(idefics_instance,
-                      "processor") as mock_processor, patch.object(
-                          idefics_instance, "model") as mock_model:
-        mock_processor.return_value = {"input_ids": torch.tensor([1, 2, 3])}
+    with patch.object(
+        idefics_instance, "processor"
+    ) as mock_processor, patch.object(
+        idefics_instance, "model"
+    ) as mock_model:
+        mock_processor.return_value = {
+            "input_ids": torch.tensor([1, 2, 3])
+        }
         mock_model.generate.return_value = torch.tensor([1, 2, 3])
         mock_processor.batch_decode.return_value = ["Test"]
 
@@ -146,7 +163,9 @@ def test_run_batched_mode_false(idefics_instance):
 # Test `run` method with an exception
 def test_run_with_exception(idefics_instance):
     task = "User: Test"
-    with patch.object(idefics_instance, "processor") as mock_processor:
+    with patch.object(
+        idefics_instance, "processor"
+    ) as mock_processor:
         mock_processor.side_effect = Exception("Test exception")
         with pytest.raises(Exception):
             idefics_instance.run(task)
@@ -155,14 +174,17 @@ def test_run_with_exception(idefics_instance):
 # Test `set_model_name` method
 def test_set_model_name(idefics_instance):
     new_model_name = "new_model_name"
-    with patch.object(IdeficsForVisionText2Text,
-                      "from_pretrained") as mock_from_pretrained, patch.object(
-                          AutoProcessor, "from_pretrained"):
+    with patch.object(
+        IdeficsForVisionText2Text, "from_pretrained"
+    ) as mock_from_pretrained, patch.object(
+        AutoProcessor, "from_pretrained"
+    ):
         idefics_instance.set_model_name(new_model_name)
 
     assert idefics_instance.model_name == new_model_name
-    mock_from_pretrained.assert_called_with(new_model_name,
-                                            torch_dtype=torch.bfloat16)
+    mock_from_pretrained.assert_called_with(
+        new_model_name, torch_dtype=torch.bfloat16
+    )
 
 
 # Test `__init__` method with device set to None

tests/models/test_kosmos.py

@@ -16,7 +16,9 @@ def mock_image_request():
     img_data = open(TEST_IMAGE_URL, "rb").read()
     mock_resp = Mock()
     mock_resp.raw = img_data
-    with patch.object(requests, "get", return_value=mock_resp) as _fixture:
+    with patch.object(
+        requests, "get", return_value=mock_resp
+    ) as _fixture:
         yield _fixture
 
 
@@ -45,16 +47,18 @@ def test_get_image(mock_image_request):
 # Test multimodal grounding
 def test_multimodal_grounding(mock_image_request):
     kosmos = Kosmos()
-    kosmos.multimodal_grounding("Find the red apple in the image.",
-                                TEST_IMAGE_URL)
+    kosmos.multimodal_grounding(
+        "Find the red apple in the image.", TEST_IMAGE_URL
+    )
     # TODO: Validate the result if possible
 
 
 # Test referring expression comprehension
 def test_referring_expression_comprehension(mock_image_request):
     kosmos = Kosmos()
-    kosmos.referring_expression_comprehension("Show me the green bottle.",
-                                              TEST_IMAGE_URL)
+    kosmos.referring_expression_comprehension(
+        "Show me the green bottle.", TEST_IMAGE_URL
+    )
     # TODO: Validate the result if possible
 
 
@@ -89,7 +93,6 @@ IMG_URL5 = "https://images.unsplash.com/photo-1696862761045-0a65acbede8f?auto=fo
 
 # Mock response for requests.get()
 class MockResponse:
-
     @staticmethod
     def json():
         return {}
@@ -108,23 +111,30 @@ def kosmos():
 # Mocking the requests.get() method
 @pytest.fixture
 def mock_request_get(monkeypatch):
-    monkeypatch.setattr(requests, "get", lambda url, **kwargs: MockResponse())
+    monkeypatch.setattr(
+        requests, "get", lambda url, **kwargs: MockResponse()
+    )
 
 
 @pytest.mark.usefixtures("mock_request_get")
 def test_multimodal_grounding(kosmos):
-    kosmos.multimodal_grounding("Find the red apple in the image.", IMG_URL1)
+    kosmos.multimodal_grounding(
+        "Find the red apple in the image.", IMG_URL1
+    )
 
 
 @pytest.mark.usefixtures("mock_request_get")
 def test_referring_expression_comprehension(kosmos):
-    kosmos.referring_expression_comprehension("Show me the green bottle.",
-                                              IMG_URL2)
+    kosmos.referring_expression_comprehension(
+        "Show me the green bottle.", IMG_URL2
+    )
 
 
 @pytest.mark.usefixtures("mock_request_get")
 def test_referring_expression_generation(kosmos):
-    kosmos.referring_expression_generation("It is on the table.", IMG_URL3)
+    kosmos.referring_expression_generation(
+        "It is on the table.", IMG_URL3
+    )
 
 
 @pytest.mark.usefixtures("mock_request_get")
@@ -144,13 +154,16 @@ def test_grounded_image_captioning_detailed(kosmos):
 
 @pytest.mark.usefixtures("mock_request_get")
 def test_multimodal_grounding_2(kosmos):
-    kosmos.multimodal_grounding("Find the yellow fruit in the image.", IMG_URL2)
+    kosmos.multimodal_grounding(
+        "Find the yellow fruit in the image.", IMG_URL2
+    )
 
 
 @pytest.mark.usefixtures("mock_request_get")
 def test_referring_expression_comprehension_2(kosmos):
-    kosmos.referring_expression_comprehension("Where is the water bottle?",
-                                              IMG_URL3)
+    kosmos.referring_expression_comprehension(
+        "Where is the water bottle?", IMG_URL3
+    )
 
 
 @pytest.mark.usefixtures("mock_request_get")

tests/models/test_llama_function_caller.py

@@ -18,7 +18,6 @@ def test_llama_model_loading(llama_caller):
 
 # Test adding and calling custom functions
 def test_llama_custom_function(llama_caller):
-
     def sample_function(arg1, arg2):
         return f"Sample function called with args: {arg1}, {arg2}"
 
@@ -40,11 +39,13 @@ def test_llama_custom_function(llama_caller):
         ],
     )
 
-    result = llama_caller.call_function("sample_function",
-                                        arg1="arg1_value",
-                                        arg2="arg2_value")
+    result = llama_caller.call_function(
+        "sample_function", arg1="arg1_value", arg2="arg2_value"
+    )
     assert (
-        result == "Sample function called with args: arg1_value, arg2_value")
+        result
+        == "Sample function called with args: arg1_value, arg2_value"
+    )
 
 
 # Test streaming user prompts
@@ -63,7 +64,6 @@ def test_llama_custom_function_not_found(llama_caller):
 
 # Test invalid arguments for custom function
 def test_llama_custom_function_invalid_arguments(llama_caller):
-
     def sample_function(arg1, arg2):
         return f"Sample function called with args: {arg1}, {arg2}"
 
@@ -86,7 +86,9 @@ def test_llama_custom_function_invalid_arguments(llama_caller):
     )
 
     with pytest.raises(TypeError):
-        llama_caller.call_function("sample_function", arg1="arg1_value")
+        llama_caller.call_function(
+            "sample_function", arg1="arg1_value"
+        )
 
 
 # Test streaming with custom runtime

tests/models/test_mixtral.py

@@ -21,18 +21,22 @@ def test_mixtral_run(mock_model, mock_tokenizer):
     mixtral = Mixtral()
     mock_tokenizer_instance = MagicMock()
     mock_model_instance = MagicMock()
-    mock_tokenizer.from_pretrained.return_value = (mock_tokenizer_instance)
+    mock_tokenizer.from_pretrained.return_value = (
+        mock_tokenizer_instance
+    )
     mock_model.from_pretrained.return_value = mock_model_instance
     mock_tokenizer_instance.return_tensors = "pt"
     mock_model_instance.generate.return_value = [101, 102, 103]
     mock_tokenizer_instance.decode.return_value = "Generated text"
     result = mixtral.run("Test task")
     assert result == "Generated text"
-    mock_tokenizer_instance.assert_called_once_with("Test task",
-                                                    return_tensors="pt")
+    mock_tokenizer_instance.assert_called_once_with(
+        "Test task", return_tensors="pt"
+    )
     mock_model_instance.generate.assert_called_once()
     mock_tokenizer_instance.decode.assert_called_once_with(
-        [101, 102, 103], skip_special_tokens=True)
+        [101, 102, 103], skip_special_tokens=True
+    )
 
 
 @patch("swarms.models.mixtral.AutoTokenizer")
@@ -41,7 +45,9 @@ def test_mixtral_run_error(mock_model, mock_tokenizer):
     mixtral = Mixtral()
     mock_tokenizer_instance = MagicMock()
     mock_model_instance = MagicMock()
-    mock_tokenizer.from_pretrained.return_value = (mock_tokenizer_instance)
+    mock_tokenizer.from_pretrained.return_value = (
+        mock_tokenizer_instance
+    )
     mock_model.from_pretrained.return_value = mock_model_instance
     mock_tokenizer_instance.return_tensors = "pt"
     mock_model_instance.generate.side_effect = Exception("Test error")

tests/models/test_mpt7b.py

@@ -25,10 +25,14 @@ def test_mpt7b_run():
         "EleutherAI/gpt-neox-20b",
         max_tokens=150,
     )
-    output = mpt.run("generate", "Once upon a time in a land far, far away...")
+    output = mpt.run(
+        "generate", "Once upon a time in a land far, far away..."
+    )
 
     assert isinstance(output, str)
-    assert output.startswith("Once upon a time in a land far, far away...")
+    assert output.startswith(
+        "Once upon a time in a land far, far away..."
+    )
 
 
 def test_mpt7b_run_invalid_task():
@@ -51,10 +55,14 @@ def test_mpt7b_generate():
         "EleutherAI/gpt-neox-20b",
         max_tokens=150,
     )
-    output = mpt.generate("Once upon a time in a land far, far away...")
+    output = mpt.generate(
+        "Once upon a time in a land far, far away..."
+    )
 
     assert isinstance(output, str)
-    assert output.startswith("Once upon a time in a land far, far away...")
+    assert output.startswith(
+        "Once upon a time in a land far, far away..."
+    )
 
 
 def test_mpt7b_batch_generate():

tests/models/test_nougat.py

@@ -43,7 +43,9 @@ def test_model_initialization(setup_nougat):
     "cuda_available, expected_device",
     [(True, "cuda"), (False, "cpu")],
 )
-def test_device_initialization(cuda_available, expected_device, monkeypatch):
+def test_device_initialization(
+    cuda_available, expected_device, monkeypatch
+):
     monkeypatch.setattr(
         torch,
         "cuda",
@@ -72,7 +74,9 @@ def test_get_image_invalid_path(setup_nougat):
         (10, 50),
     ],
 )
-def test_model_call_with_diff_params(setup_nougat, min_len, max_tokens):
+def test_model_call_with_diff_params(
+    setup_nougat, min_len, max_tokens
+):
     setup_nougat.min_length = min_len
     setup_nougat.max_new_tokens = max_tokens
 
@@ -118,7 +122,8 @@ def test_nougat_with_sample_image_1(setup_nougat):
         os.path.join(
             "sample_images",
             "https://plus.unsplash.com/premium_photo-1687149699194-0207c04bc6e8?auto=format&fit=crop&q=80&w=1378&ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D",
-        ))
+        )
+    )
     assert isinstance(result, str)
 
 
@@ -135,7 +140,8 @@ def test_nougat_min_length_param(setup_nougat):
         os.path.join(
             "sample_images",
             "https://plus.unsplash.com/premium_photo-1687149699194-0207c04bc6e8?auto=format&fit=crop&q=80&w=1378&ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D",
-        ))
+        )
+    )
     assert isinstance(result, str)
 
 
@@ -146,7 +152,8 @@ def test_nougat_max_new_tokens_param(setup_nougat):
         os.path.join(
             "sample_images",
             "https://plus.unsplash.com/premium_photo-1687149699194-0207c04bc6e8?auto=format&fit=crop&q=80&w=1378&ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D",
-        ))
+        )
+    )
     assert isinstance(result, str)
 
 
@@ -157,13 +164,16 @@ def test_nougat_different_model_path(setup_nougat):
         os.path.join(
             "sample_images",
             "https://plus.unsplash.com/premium_photo-1687149699194-0207c04bc6e8?auto=format&fit=crop&q=80&w=1378&ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D",
-        ))
+        )
+    )
     assert isinstance(result, str)
 
 
 @pytest.mark.usefixtures("mock_processor_and_model")
 def test_nougat_bad_image_path(setup_nougat):
-    with pytest.raises(Exception):  # Adjust the exception type accordingly.
+    with pytest.raises(
+        Exception
+    ):  # Adjust the exception type accordingly.
         setup_nougat("bad_image_path.png")
 
 
@@ -173,7 +183,8 @@ def test_nougat_image_large_size(setup_nougat):
         os.path.join(
             "sample_images",
             "https://images.unsplash.com/photo-1697641039266-bfa00367f7cb?auto=format&fit=crop&q=60&w=400&ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHx0b3BpYy1mZWVkfDJ8SnBnNktpZGwtSGt8fGVufDB8fHx8fA%3D%3D",
-        ))
+        )
+    )
     assert isinstance(result, str)
 
 
@@ -183,7 +194,8 @@ def test_nougat_image_small_size(setup_nougat):
         os.path.join(
             "sample_images",
             "https://images.unsplash.com/photo-1697638626987-aa865b769276?auto=format&fit=crop&q=60&w=400&ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHx0b3BpYy1mZWVkfDd8SnBnNktpZGwtSGt8fGVufDB8fHx8fA%3D%3D",
-        ))
+        )
+    )
     assert isinstance(result, str)
 
 
@@ -193,7 +205,8 @@ def test_nougat_image_varied_content(setup_nougat):
         os.path.join(
             "sample_images",
             "https://images.unsplash.com/photo-1697469994783-b12bbd9c4cff?auto=format&fit=crop&q=60&w=400&ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHx0b3BpYy1mZWVkfDE0fEpwZzZLaWRsLUhrfHxlbnwwfHx8fHw%3D",
-        ))
+        )
+    )
     assert isinstance(result, str)
 
 
@@ -203,5 +216,6 @@ def test_nougat_image_with_metadata(setup_nougat):
         os.path.join(
             "sample_images",
             "https://images.unsplash.com/photo-1697273300766-5bbaa53ec2f0?auto=format&fit=crop&q=60&w=400&ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHx0b3BpYy1mZWVkfDE5fEpwZzZLaWRsLUhrfHxlbnwwfHx8fHw%3D",
-        ))
+        )
+    )
     assert isinstance(result, str)

tests/models/test_qwen.py

@@ -4,7 +4,8 @@ from swarms.models.qwen import QwenVLMultiModal
 
 
 def test_post_init():
-    with patch("swarms.models.qwen.AutoTokenizer.from_pretrained"
+    with patch(
+        "swarms.models.qwen.AutoTokenizer.from_pretrained"
     ) as mock_tokenizer, patch(
         "swarms.models.qwen.AutoModelForCausalLM.from_pretrained"
     ) as mock_model:
@@ -12,8 +13,9 @@ def test_post_init():
         mock_model.return_value = Mock()
 
         model = QwenVLMultiModal()
-        mock_tokenizer.assert_called_once_with(model.model_name,
-                                               trust_remote_code=True)
+        mock_tokenizer.assert_called_once_with(
+            model.model_name, trust_remote_code=True
+        )
         mock_model.assert_called_once_with(
             model.model_name,
             device_map=model.device,
@@ -25,29 +27,35 @@ def test_run():
     with patch(
         "swarms.models.qwen.AutoTokenizer.from_list_format"
     ) as mock_format, patch(
-            "swarms.models.qwen.AutoTokenizer.__call__") as mock_call, patch(
+        "swarms.models.qwen.AutoTokenizer.__call__"
+    ) as mock_call, patch(
         "swarms.models.qwen.AutoModelForCausalLM.generate"
     ) as mock_generate, patch(
-                "swarms.models.qwen.AutoTokenizer.decode") as mock_decode:
+        "swarms.models.qwen.AutoTokenizer.decode"
+    ) as mock_decode:
         mock_format.return_value = Mock()
         mock_call.return_value = Mock()
         mock_generate.return_value = Mock()
         mock_decode.return_value = "response"
 
         model = QwenVLMultiModal()
-        response = model.run("Hello, how are you?",
-                             "https://example.com/image.jpg")
+        response = model.run(
+            "Hello, how are you?", "https://example.com/image.jpg"
+        )
 
         assert response == "response"
 
 
 def test_chat():
-    with patch("swarms.models.qwen.AutoModelForCausalLM.chat") as mock_chat:
+    with patch(
+        "swarms.models.qwen.AutoModelForCausalLM.chat"
+    ) as mock_chat:
         mock_chat.return_value = ("response", ["history"])
 
         model = QwenVLMultiModal()
-        response, history = model.chat("Hello, how are you?",
-                                       "https://example.com/image.jpg")
+        response, history = model.chat(
+            "Hello, how are you?", "https://example.com/image.jpg"
+        )
 
         assert response == "response"
         assert history == ["history"]

tests/models/test_speech_t5.py

@@ -16,11 +16,16 @@ def speecht5_model():
 
 
 def test_speecht5_init(speecht5_model):
-    assert isinstance(speecht5_model.processor, SpeechT5.processor.__class__)
+    assert isinstance(
+        speecht5_model.processor, SpeechT5.processor.__class__
+    )
     assert isinstance(speecht5_model.model, SpeechT5.model.__class__)
-    assert isinstance(speecht5_model.vocoder, SpeechT5.vocoder.__class__)
-    assert isinstance(speecht5_model.embeddings_dataset,
-                      torch.utils.data.Dataset)
+    assert isinstance(
+        speecht5_model.vocoder, SpeechT5.vocoder.__class__
+    )
+    assert isinstance(
+        speecht5_model.embeddings_dataset, torch.utils.data.Dataset
+    )
 
 
 def test_speecht5_call(speecht5_model):
@@ -44,7 +49,10 @@ def test_speecht5_set_model(speecht5_model):
     speecht5_model.set_model(new_model_name)
     assert speecht5_model.model_name == new_model_name
     assert speecht5_model.processor.model_name == new_model_name
-    assert (speecht5_model.model.config.model_name_or_path == new_model_name)
+    assert (
+        speecht5_model.model.config.model_name_or_path
+        == new_model_name
+    )
     speecht5_model.set_model(old_model_name)  # Restore original model
 
 
@@ -54,8 +62,12 @@ def test_speecht5_set_vocoder(speecht5_model):
     speecht5_model.set_vocoder(new_vocoder_name)
     assert speecht5_model.vocoder_name == new_vocoder_name
     assert (
-        speecht5_model.vocoder.config.model_name_or_path == new_vocoder_name)
-    speecht5_model.set_vocoder(old_vocoder_name)  # Restore original vocoder
+        speecht5_model.vocoder.config.model_name_or_path
+        == new_vocoder_name
+    )
+    speecht5_model.set_vocoder(
+        old_vocoder_name
+    )  # Restore original vocoder
 
 
 def test_speecht5_set_embeddings_dataset(speecht5_model):
@@ -63,10 +75,12 @@ def test_speecht5_set_embeddings_dataset(speecht5_model):
     new_dataset_name = "Matthijs/cmu-arctic-xvectors-test"
     speecht5_model.set_embeddings_dataset(new_dataset_name)
     assert speecht5_model.dataset_name == new_dataset_name
-    assert isinstance(speecht5_model.embeddings_dataset,
-                      torch.utils.data.Dataset)
+    assert isinstance(
+        speecht5_model.embeddings_dataset, torch.utils.data.Dataset
+    )
     speecht5_model.set_embeddings_dataset(
-        old_dataset_name)  # Restore original dataset
+        old_dataset_name
+    )  # Restore original dataset
 
 
 def test_speecht5_get_sampling_rate(speecht5_model):
@@ -98,7 +112,9 @@ def test_speecht5_change_dataset_split(speecht5_model):
 def test_speecht5_load_custom_embedding(speecht5_model):
     xvector = [0.1, 0.2, 0.3, 0.4, 0.5]
     embedding = speecht5_model.load_custom_embedding(xvector)
-    assert torch.all(torch.eq(embedding, torch.tensor(xvector).unsqueeze(0)))
+    assert torch.all(
+        torch.eq(embedding, torch.tensor(xvector).unsqueeze(0))
+    )
 
 
 def test_speecht5_with_different_speakers(speecht5_model):
@@ -109,7 +125,9 @@ def test_speecht5_with_different_speakers(speecht5_model):
         assert isinstance(speech, torch.Tensor)
 
 
-def test_speecht5_save_speech_with_different_extensions(speecht5_model,):
+def test_speecht5_save_speech_with_different_extensions(
+    speecht5_model,
+):
     text = "Hello, how are you?"
     speech = speecht5_model(text)
     extensions = [".wav", ".flac"]
@@ -144,4 +162,6 @@ def test_speecht5_change_vocoder_model(speecht5_model):
     speecht5_model.set_vocoder(new_vocoder_name)
     speech = speecht5_model(text)
     assert isinstance(speech, torch.Tensor)
-    speecht5_model.set_vocoder(old_vocoder_name)  # Restore original vocoder
+    speecht5_model.set_vocoder(
+        old_vocoder_name
+    )  # Restore original vocoder

tests/models/test_ssd_1b.py

@@ -21,30 +21,36 @@ def test_ssd1b_call(ssd1b_model):
     image_url = ssd1b_model(task, neg_prompt)
     assert isinstance(image_url, str)
     assert image_url.startswith(
-        "https://")  # Assuming it starts with "https://"
+        "https://"
+    )  # Assuming it starts with "https://"
 
 
 # Add more tests for various aspects of the class and methods
 
 
 # Example of a parameterized test for different tasks
-@pytest.mark.parametrize("task",
-                         ["A painting of a cat", "A painting of a tree"])
+@pytest.mark.parametrize(
+    "task", ["A painting of a cat", "A painting of a tree"]
+)
 def test_ssd1b_parameterized_task(ssd1b_model, task):
     image_url = ssd1b_model(task)
     assert isinstance(image_url, str)
     assert image_url.startswith(
-        "https://")  # Assuming it starts with "https://"
+        "https://"
+    )  # Assuming it starts with "https://"
 
 
 # Example of a test using mocks to isolate units of code
 def test_ssd1b_with_mock(ssd1b_model, mocker):
-    mocker.patch("your_module.StableDiffusionXLPipeline")  # Mock the pipeline
+    mocker.patch(
+        "your_module.StableDiffusionXLPipeline"
+    )  # Mock the pipeline
     task = "A painting of a cat"
     image_url = ssd1b_model(task)
     assert isinstance(image_url, str)
     assert image_url.startswith(
-        "https://")  # Assuming it starts with "https://"
+        "https://"
+    )  # Assuming it starts with "https://"
 
 
 def test_ssd1b_call_with_cache(ssd1b_model):
@@ -62,7 +68,8 @@ def test_ssd1b_invalid_task(ssd1b_model):
 
 
 def test_ssd1b_failed_api_call(ssd1b_model, mocker):
-    mocker.patch("your_module.StableDiffusionXLPipeline"
+    mocker.patch(
+        "your_module.StableDiffusionXLPipeline"
     )  # Mock the pipeline to raise an exception
     task = "A painting of a cat"
     with pytest.raises(Exception):

tests/models/test_timm.py

@@ -19,16 +19,18 @@ def test_timm_model_init():
 
 
 def test_timm_model_call():
-    with patch("swarms.models.timm.create_model") as mock_create_model:
+    with patch(
+        "swarms.models.timm.create_model"
+    ) as mock_create_model:
         model_name = "resnet18"
         pretrained = True
         in_chans = 3
         timm_model = TimmModel(model_name, pretrained, in_chans)
         task = torch.rand(1, in_chans, 224, 224)
         result = timm_model(task)
-        mock_create_model.assert_called_once_with(model_name,
-                                                  pretrained=pretrained,
-                                                  in_chans=in_chans)
+        mock_create_model.assert_called_once_with(
+            model_name, pretrained=pretrained, in_chans=in_chans
+        )
         assert result == mock_create_model.return_value(task)
 
 

tests/models/test_timm_model.py

@@ -22,14 +22,17 @@ def test_create_model(sample_model_info):
 def test_call(sample_model_info):
     model_handler = TimmModel()
     input_tensor = torch.randn(1, 3, 224, 224)
-    output_shape = model_handler.__call__(sample_model_info, input_tensor)
+    output_shape = model_handler.__call__(
+        sample_model_info, input_tensor
+    )
     assert isinstance(output_shape, torch.Size)
 
 
 def test_get_supported_models_mock():
     model_handler = TimmModel()
     model_handler._get_supported_models = Mock(
-        return_value=["resnet18", "resnet50"])
+        return_value=["resnet18", "resnet50"]
+    )
     supported_models = model_handler._get_supported_models()
     assert supported_models == ["resnet18", "resnet50"]
 

tests/models/test_togther.py

@@ -55,11 +55,7 @@ def test_init_custom_params(mock_api_key):
 def test_run_success(mock_post, mock_api_key):
     mock_response = Mock()
     mock_response.json.return_value = {
-        "choices": [{
-            "message": {
-                "content": "Generated response"
-            }
-        }]
+        "choices": [{"message": {"content": "Generated response"}}]
     }
     mock_post.return_value = mock_response
 
@@ -73,7 +69,8 @@ def test_run_success(mock_post, mock_api_key):
 @patch("swarms.models.together_model.requests.post")
 def test_run_failure(mock_post, mock_api_key):
     mock_post.side_effect = requests.exceptions.RequestException(
-        "Request failed")
+        "Request failed"
+    )
 
     model = TogetherLLM()
     task = "What is the color of the object?"
@@ -92,7 +89,9 @@ def test_run_with_logging_enabled(caplog, mock_api_key):
     assert "Sending request to" in caplog.text
 
 
-@pytest.mark.parametrize("invalid_input", [None, 123, ["list", "of", "items"]])
+@pytest.mark.parametrize(
+    "invalid_input", [None, 123, ["list", "of", "items"]]
+)
 def test_invalid_task_input(invalid_input, mock_api_key):
     model = TogetherLLM()
     response = model.run(invalid_input)
@@ -104,11 +103,7 @@ def test_invalid_task_input(invalid_input, mock_api_key):
 def test_run_streaming_enabled(mock_post, mock_api_key):
     mock_response = Mock()
     mock_response.json.return_value = {
-        "choices": [{
-            "message": {
-                "content": "Generated response"
-            }
-        }]
+        "choices": [{"message": {"content": "Generated response"}}]
     }
     mock_post.return_value = mock_response
 

tests/models/test_ultralytics.py

@@ -20,7 +20,9 @@ def test_ultralytics_call():
         args = (1, 2, 3)
         kwargs = {"a": "A", "b": "B"}
         result = ultralytics(task, *args, **kwargs)
-        mock_yolo.return_value.assert_called_once_with(task, *args, **kwargs)
+        mock_yolo.return_value.assert_called_once_with(
+            task, *args, **kwargs
+        )
         assert result == mock_yolo.return_value.return_value
 
 

tests/models/test_vilt.py

@@ -21,13 +21,17 @@ def test_vilt_initialization(vilt_instance):
 # 2. Test Model Predictions
 @patch.object(requests, "get")
 @patch.object(Image, "open")
-def test_vilt_prediction(mock_image_open, mock_requests_get, vilt_instance):
+def test_vilt_prediction(
+    mock_image_open, mock_requests_get, vilt_instance
+):
     mock_image = Mock()
     mock_image_open.return_value = mock_image
     mock_requests_get.return_value.raw = Mock()
 
     # It's a mock response, so no real answer expected
-    with pytest.raises(Exception):  # Ensure exception is more specific
+    with pytest.raises(
+        Exception
+    ):  # Ensure exception is more specific
         vilt_instance(
             "What is this image",
             "https://images.unsplash.com/photo-1582538885592-e70a5d7ab3d3?ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D&auto=format&fit=crop&w=1770&q=80",
@@ -62,7 +66,9 @@ def test_vilt_network_exception(vilt_instance):
     ],
 )
 def test_vilt_various_inputs(text, image_url, vilt_instance):
-    with pytest.raises(Exception):  # Again, ensure exception is more specific
+    with pytest.raises(
+        Exception
+    ):  # Again, ensure exception is more specific
         vilt_instance(text, image_url)
 
 

tests/models/test_yi_200k.py

@@ -32,7 +32,9 @@ def test_yi34b_generate_text_with_length(yi34b_model, max_length):
 
 
 @pytest.mark.parametrize("temperature", [0.5, 1.0, 1.5])
-def test_yi34b_generate_text_with_temperature(yi34b_model, temperature):
+def test_yi34b_generate_text_with_temperature(
+    yi34b_model, temperature
+):
     prompt = "There's a place where time stands still."
     generated_text = yi34b_model(prompt, temperature=temperature)
     assert isinstance(generated_text, str)
@@ -40,24 +42,27 @@ def test_yi34b_generate_text_with_temperature(yi34b_model, temperature):
 
 def test_yi34b_generate_text_with_invalid_prompt(yi34b_model):
     prompt = None  # Invalid prompt
-    with pytest.raises(ValueError,
-                       match="Input prompt must be a non-empty string"):
+    with pytest.raises(
+        ValueError, match="Input prompt must be a non-empty string"
+    ):
         yi34b_model(prompt)
 
 
 def test_yi34b_generate_text_with_invalid_max_length(yi34b_model):
     prompt = "There's a place where time stands still."
     max_length = -1  # Invalid max_length
-    with pytest.raises(ValueError,
-                       match="max_length must be a positive integer"):
+    with pytest.raises(
+        ValueError, match="max_length must be a positive integer"
+    ):
         yi34b_model(prompt, max_length=max_length)
 
 
 def test_yi34b_generate_text_with_invalid_temperature(yi34b_model):
     prompt = "There's a place where time stands still."
     temperature = 2.0  # Invalid temperature
-    with pytest.raises(ValueError,
-                       match="temperature must be between 0.01 and 1.0"):
+    with pytest.raises(
+        ValueError, match="temperature must be between 0.01 and 1.0"
+    ):
         yi34b_model(prompt, temperature=temperature)
 
 
@@ -78,27 +83,35 @@ def test_yi34b_generate_text_with_top_p(yi34b_model, top_p):
 def test_yi34b_generate_text_with_invalid_top_k(yi34b_model):
     prompt = "There's a place where time stands still."
     top_k = -1  # Invalid top_k
-    with pytest.raises(ValueError,
-                       match="top_k must be a non-negative integer"):
+    with pytest.raises(
+        ValueError, match="top_k must be a non-negative integer"
+    ):
         yi34b_model(prompt, top_k=top_k)
 
 
 def test_yi34b_generate_text_with_invalid_top_p(yi34b_model):
     prompt = "There's a place where time stands still."
     top_p = 1.5  # Invalid top_p
-    with pytest.raises(ValueError, match="top_p must be between 0.0 and 1.0"):
+    with pytest.raises(
+        ValueError, match="top_p must be between 0.0 and 1.0"
+    ):
         yi34b_model(prompt, top_p=top_p)
 
 
 @pytest.mark.parametrize("repitition_penalty", [1.0, 1.2, 1.5])
-def test_yi34b_generate_text_with_repitition_penalty(yi34b_model,
-                                                     repitition_penalty):
+def test_yi34b_generate_text_with_repitition_penalty(
+    yi34b_model, repitition_penalty
+):
     prompt = "There's a place where time stands still."
-    generated_text = yi34b_model(prompt, repitition_penalty=repitition_penalty)
+    generated_text = yi34b_model(
+        prompt, repitition_penalty=repitition_penalty
+    )
     assert isinstance(generated_text, str)
 
 
-def test_yi34b_generate_text_with_invalid_repitition_penalty(yi34b_model,):
+def test_yi34b_generate_text_with_invalid_repitition_penalty(
+    yi34b_model,
+):
     prompt = "There's a place where time stands still."
     repitition_penalty = 0.0  # Invalid repitition_penalty
     with pytest.raises(

tests/models/test_zeroscope.py

@@ -25,11 +25,16 @@ def test_zeroscope_ttv_init(mock_scheduler, mock_pipeline):
 def test_zeroscope_ttv_forward(mock_scheduler, mock_pipeline):
     zeroscope = ZeroscopeTTV()
     mock_pipeline_instance = MagicMock()
-    mock_pipeline.from_pretrained.return_value = (mock_pipeline_instance)
-    mock_pipeline_instance.return_value = MagicMock(frames="Generated frames")
+    mock_pipeline.from_pretrained.return_value = (
+        mock_pipeline_instance
+    )
+    mock_pipeline_instance.return_value = MagicMock(
+        frames="Generated frames"
+    )
     mock_pipeline_instance.enable_vae_slicing.assert_called_once()
     mock_pipeline_instance.enable_forward_chunking.assert_called_once_with(
-        chunk_size=1, dim=1)
+        chunk_size=1, dim=1
+    )
     result = zeroscope.forward("Test task")
     assert result == "Generated frames"
     mock_pipeline_instance.assert_called_once_with(
@@ -46,8 +51,12 @@ def test_zeroscope_ttv_forward(mock_scheduler, mock_pipeline):
 def test_zeroscope_ttv_forward_error(mock_scheduler, mock_pipeline):
     zeroscope = ZeroscopeTTV()
     mock_pipeline_instance = MagicMock()
-    mock_pipeline.from_pretrained.return_value = (mock_pipeline_instance)
-    mock_pipeline_instance.return_value = MagicMock(frames="Generated frames")
+    mock_pipeline.from_pretrained.return_value = (
+        mock_pipeline_instance
+    )
+    mock_pipeline_instance.return_value = MagicMock(
+        frames="Generated frames"
+    )
     mock_pipeline_instance.side_effect = Exception("Test error")
     with pytest.raises(Exception, match="Test error"):
         zeroscope.forward("Test task")
@@ -58,8 +67,12 @@ def test_zeroscope_ttv_forward_error(mock_scheduler, mock_pipeline):
 def test_zeroscope_ttv_call(mock_scheduler, mock_pipeline):
     zeroscope = ZeroscopeTTV()
     mock_pipeline_instance = MagicMock()
-    mock_pipeline.from_pretrained.return_value = (mock_pipeline_instance)
-    mock_pipeline_instance.return_value = MagicMock(frames="Generated frames")
+    mock_pipeline.from_pretrained.return_value = (
+        mock_pipeline_instance
+    )
+    mock_pipeline_instance.return_value = MagicMock(
+        frames="Generated frames"
+    )
     result = zeroscope.__call__("Test task")
     assert result == "Generated frames"
     mock_pipeline_instance.assert_called_once_with(
@@ -76,8 +89,12 @@ def test_zeroscope_ttv_call(mock_scheduler, mock_pipeline):
 def test_zeroscope_ttv_call_error(mock_scheduler, mock_pipeline):
     zeroscope = ZeroscopeTTV()
     mock_pipeline_instance = MagicMock()
-    mock_pipeline.from_pretrained.return_value = (mock_pipeline_instance)
-    mock_pipeline_instance.return_value = MagicMock(frames="Generated frames")
+    mock_pipeline.from_pretrained.return_value = (
+        mock_pipeline_instance
+    )
+    mock_pipeline_instance.return_value = MagicMock(
+        frames="Generated frames"
+    )
     mock_pipeline_instance.side_effect = Exception("Test error")
     with pytest.raises(Exception, match="Test error"):
         zeroscope.__call__("Test task")
@@ -88,8 +105,12 @@ def test_zeroscope_ttv_call_error(mock_scheduler, mock_pipeline):
 def test_zeroscope_ttv_save_video_path(mock_scheduler, mock_pipeline):
     zeroscope = ZeroscopeTTV()
     mock_pipeline_instance = MagicMock()
-    mock_pipeline.from_pretrained.return_value = (mock_pipeline_instance)
-    mock_pipeline_instance.return_value = MagicMock(frames="Generated frames")
+    mock_pipeline.from_pretrained.return_value = (
+        mock_pipeline_instance
+    )
+    mock_pipeline_instance.return_value = MagicMock(
+        frames="Generated frames"
+    )
     result = zeroscope.save_video_path("Test video path")
     assert result == "Test video path"
     mock_pipeline_instance.assert_called_once_with(

tests/structs/test_agent.py

@@ -18,7 +18,9 @@ openai_api_key = os.getenv("OPENAI_API_KEY")
 # Mocks and Fixtures
 @pytest.fixture
 def mocked_llm():
-    return OpenAIChat(openai_api_key=openai_api_key,)
+    return OpenAIChat(
+        openai_api_key=openai_api_key,
+    )
 
 
 @pytest.fixture
@@ -63,12 +65,15 @@ def test_provide_feedback(basic_flow):
 @patch("time.sleep", return_value=None)  # to speed up tests
 def test_run_without_stopping_condition(mocked_sleep, basic_flow):
     response = basic_flow.run("Test task")
-    assert (response == "Test task"
+    assert (
+        response == "Test task"
     )  # since our mocked llm doesn't modify the response
 
 
 @patch("time.sleep", return_value=None)  # to speed up tests
-def test_run_with_stopping_condition(mocked_sleep, flow_with_condition):
+def test_run_with_stopping_condition(
+    mocked_sleep, flow_with_condition
+):
     response = flow_with_condition.run("Stop")
     assert response == "Stop"
 
@@ -108,7 +113,6 @@ def test_env_variable_handling(monkeypatch):
 
 # Test initializing the agent with different stopping conditions
 def test_flow_with_custom_stopping_condition(mocked_llm):
-
     def stopping_condition(x):
         return "terminate" in x.lower()
 
@@ -129,7 +133,9 @@ def test_flow_call(basic_flow):
 
 # Test formatting the prompt
 def test_format_prompt(basic_flow):
-    formatted_prompt = basic_flow.format_prompt("Hello {name}", name="John")
+    formatted_prompt = basic_flow.format_prompt(
+        "Hello {name}", name="John"
+    )
     assert formatted_prompt == "Hello John"
 
 
@@ -158,15 +164,9 @@ def test_interactive_mode(basic_flow):
 # Test bulk run with varied inputs
 def test_bulk_run_varied_inputs(basic_flow):
     inputs = [
-        {
-            "task": "Test1"
-        },
-        {
-            "task": "Test2"
-        },
-        {
-            "task": "Stop now"
-        },
+        {"task": "Test1"},
+        {"task": "Test2"},
+        {"task": "Stop now"},
     ]
     responses = basic_flow.bulk_run(inputs)
     assert responses == ["Test1", "Test2", "Stop now"]
@@ -191,9 +191,12 @@ def test_save_different_memory(basic_flow, tmp_path):
 
 # Test the stopping condition check
 def test_check_stopping_condition(flow_with_condition):
-    assert flow_with_condition._check_stopping_condition("Stop this process")
+    assert flow_with_condition._check_stopping_condition(
+        "Stop this process"
+    )
     assert not flow_with_condition._check_stopping_condition(
-        "Continue the task")
+        "Continue the task"
+    )
 
 
 # Test without providing max loops (default value should be 5)
@@ -249,7 +252,9 @@ def test_different_retry_intervals(mocked_sleep, basic_flow):
 # Test invoking the agent with additional kwargs
 @patch("time.sleep", return_value=None)
 def test_flow_call_with_kwargs(mocked_sleep, basic_flow):
-    response = basic_flow("Test call", param1="value1", param2="value2")
+    response = basic_flow(
+        "Test call", param1="value1", param2="value2"
+    )
     assert response == "Test call"
 
 
@@ -284,7 +289,9 @@ def test_stopping_token_in_response(mocked_sleep, basic_flow):
 def flow_instance():
     # Create an instance of the Agent class with required parameters for testing
     # You may need to adjust this based on your actual class initialization
-    llm = OpenAIChat(openai_api_key=openai_api_key,)
+    llm = OpenAIChat(
+        openai_api_key=openai_api_key,
+    )
     agent = Agent(
         llm=llm,
         max_loops=5,
@@ -331,7 +338,9 @@ def test_flow_autosave(flow_instance):
 def test_flow_response_filtering(flow_instance):
     # Test the response filtering functionality
     flow_instance.add_response_filter("filter_this")
-    response = flow_instance.filtered_run("This message should filter_this")
+    response = flow_instance.filtered_run(
+        "This message should filter_this"
+    )
     assert "filter_this" not in response
 
 
@@ -391,8 +400,11 @@ def test_flow_response_length(flow_instance):
     # Test checking the length of the response
     response = flow_instance.run(
         "Generate a 10,000 word long blog on mental clarity and the"
-        " benefits of meditation.")
-    assert (len(response) > flow_instance.get_response_length_threshold())
+        " benefits of meditation."
+    )
+    assert (
+        len(response) > flow_instance.get_response_length_threshold()
+    )
 
 
 def test_flow_set_response_length_threshold(flow_instance):
@@ -481,7 +493,9 @@ def test_flow_get_conversation_log(flow_instance):
     flow_instance.run("Message 1")
     flow_instance.run("Message 2")
     conversation_log = flow_instance.get_conversation_log()
-    assert (len(conversation_log) == 4)  # Including system and user messages
+    assert (
+        len(conversation_log) == 4
+    )  # Including system and user messages
 
 
 def test_flow_clear_conversation_log(flow_instance):
@@ -565,18 +579,37 @@ def test_flow_rollback(flow_instance):
     flow_instance.change_prompt("New prompt")
     flow_instance.get_state()
     flow_instance.rollback_to_state(state1)
-    assert (flow_instance.get_current_prompt() == state1["current_prompt"])
+    assert (
+        flow_instance.get_current_prompt() == state1["current_prompt"]
+    )
     assert flow_instance.get_instructions() == state1["instructions"]
-    assert (flow_instance.get_user_messages() == state1["user_messages"])
-    assert (flow_instance.get_response_history() == state1["response_history"])
-    assert (flow_instance.get_conversation_log() == state1["conversation_log"])
-    assert (flow_instance.is_dynamic_pacing_enabled() ==
-            state1["dynamic_pacing_enabled"])
-    assert (flow_instance.get_response_length_threshold() ==
-            state1["response_length_threshold"])
-    assert (flow_instance.get_response_filters() == state1["response_filters"])
+    assert (
+        flow_instance.get_user_messages() == state1["user_messages"]
+    )
+    assert (
+        flow_instance.get_response_history()
+        == state1["response_history"]
+    )
+    assert (
+        flow_instance.get_conversation_log()
+        == state1["conversation_log"]
+    )
+    assert (
+        flow_instance.is_dynamic_pacing_enabled()
+        == state1["dynamic_pacing_enabled"]
+    )
+    assert (
+        flow_instance.get_response_length_threshold()
+        == state1["response_length_threshold"]
+    )
+    assert (
+        flow_instance.get_response_filters()
+        == state1["response_filters"]
+    )
     assert flow_instance.get_max_loops() == state1["max_loops"]
-    assert (flow_instance.get_autosave_path() == state1["autosave_path"])
+    assert (
+        flow_instance.get_autosave_path() == state1["autosave_path"]
+    )
     assert flow_instance.get_state() == state1
 
 
@@ -585,7 +618,8 @@ def test_flow_contextual_intent(flow_instance):
     flow_instance.add_context("location", "New York")
     flow_instance.add_context("time", "tomorrow")
     response = flow_instance.run(
-        "What's the weather like in {location} at {time}?")
+        "What's the weather like in {location} at {time}?"
+    )
     assert "New York" in response
     assert "tomorrow" in response
 
@@ -593,9 +627,13 @@ def test_flow_contextual_intent(flow_instance):
 def test_flow_contextual_intent_override(flow_instance):
     # Test contextual intent override
     flow_instance.add_context("location", "New York")
-    response1 = flow_instance.run("What's the weather like in {location}?")
+    response1 = flow_instance.run(
+        "What's the weather like in {location}?"
+    )
     flow_instance.add_context("location", "Los Angeles")
-    response2 = flow_instance.run("What's the weather like in {location}?")
+    response2 = flow_instance.run(
+        "What's the weather like in {location}?"
+    )
     assert "New York" in response1
     assert "Los Angeles" in response2
 
@@ -603,9 +641,13 @@ def test_flow_contextual_intent_override(flow_instance):
 def test_flow_contextual_intent_reset(flow_instance):
     # Test resetting contextual intent
     flow_instance.add_context("location", "New York")
-    response1 = flow_instance.run("What's the weather like in {location}?")
+    response1 = flow_instance.run(
+        "What's the weather like in {location}?"
+    )
     flow_instance.reset_context()
-    response2 = flow_instance.run("What's the weather like in {location}?")
+    response2 = flow_instance.run(
+        "What's the weather like in {location}?"
+    )
     assert "New York" in response1
     assert "New York" in response2
 
@@ -630,7 +672,9 @@ def test_flow_non_interruptible(flow_instance):
 def test_flow_timeout(flow_instance):
     # Test conversation timeout
     flow_instance.timeout = 60  # Set a timeout of 60 seconds
-    response = flow_instance.run("This should take some time to respond.")
+    response = flow_instance.run(
+        "This should take some time to respond."
+    )
     assert "Timed out" in response
     assert flow_instance.is_timed_out() is True
 
@@ -679,14 +723,20 @@ def test_flow_save_and_load_conversation(flow_instance):
 
 def test_flow_inject_custom_system_message(flow_instance):
     # Test injecting a custom system message into the conversation
-    flow_instance.inject_custom_system_message("Custom system message")
-    assert ("Custom system message" in flow_instance.get_message_history())
+    flow_instance.inject_custom_system_message(
+        "Custom system message"
+    )
+    assert (
+        "Custom system message" in flow_instance.get_message_history()
+    )
 
 
 def test_flow_inject_custom_user_message(flow_instance):
     # Test injecting a custom user message into the conversation
     flow_instance.inject_custom_user_message("Custom user message")
-    assert ("Custom user message" in flow_instance.get_message_history())
+    assert (
+        "Custom user message" in flow_instance.get_message_history()
+    )
 
 
 def test_flow_inject_custom_response(flow_instance):
@@ -697,28 +747,45 @@ def test_flow_inject_custom_response(flow_instance):
 
 def test_flow_clear_injected_messages(flow_instance):
     # Test clearing injected messages from the conversation
-    flow_instance.inject_custom_system_message("Custom system message")
+    flow_instance.inject_custom_system_message(
+        "Custom system message"
+    )
     flow_instance.inject_custom_user_message("Custom user message")
     flow_instance.inject_custom_response("Custom response")
     flow_instance.clear_injected_messages()
-    assert ("Custom system message" not in flow_instance.get_message_history())
-    assert ("Custom user message" not in flow_instance.get_message_history())
-    assert ("Custom response" not in flow_instance.get_message_history())
+    assert (
+        "Custom system message"
+        not in flow_instance.get_message_history()
+    )
+    assert (
+        "Custom user message"
+        not in flow_instance.get_message_history()
+    )
+    assert (
+        "Custom response" not in flow_instance.get_message_history()
+    )
 
 
 def test_flow_disable_message_history(flow_instance):
     # Test disabling message history recording
     flow_instance.disable_message_history()
     response = flow_instance.run(
-        "This message should not be recorded in history.")
-    assert ("This message should not be recorded in history." in response)
-    assert (len(flow_instance.get_message_history()) == 0)  # History is empty
+        "This message should not be recorded in history."
+    )
+    assert (
+        "This message should not be recorded in history." in response
+    )
+    assert (
+        len(flow_instance.get_message_history()) == 0
+    )  # History is empty
 
 
 def test_flow_enable_message_history(flow_instance):
     # Test enabling message history recording
     flow_instance.enable_message_history()
-    response = flow_instance.run("This message should be recorded in history.")
+    response = flow_instance.run(
+        "This message should be recorded in history."
+    )
     assert "This message should be recorded in history." in response
     assert len(flow_instance.get_message_history()) == 1
 
@@ -728,7 +795,9 @@ def test_flow_custom_logger(flow_instance):
     custom_logger = logger  # Replace with your custom logger class
     flow_instance.set_logger(custom_logger)
     response = flow_instance.run("Custom logger test")
-    assert ("Logged using custom logger" in response)  # Verify logging message
+    assert (
+        "Logged using custom logger" in response
+    )  # Verify logging message
 
 
 def test_flow_batch_processing(flow_instance):
@@ -802,35 +871,43 @@ def test_flow_input_validation(flow_instance):
 
     with pytest.raises(ValueError):
         flow_instance.set_message_delimiter(
-            "")  # Empty delimiter, should raise ValueError
+            ""
+        )  # Empty delimiter, should raise ValueError
 
     with pytest.raises(ValueError):
         flow_instance.set_message_delimiter(
-            None)  # None delimiter, should raise ValueError
+            None
+        )  # None delimiter, should raise ValueError
 
     with pytest.raises(ValueError):
         flow_instance.set_message_delimiter(
-            123)  # Invalid delimiter type, should raise ValueError
+            123
+        )  # Invalid delimiter type, should raise ValueError
 
     with pytest.raises(ValueError):
         flow_instance.set_logger(
-            "invalid_logger")  # Invalid logger type, should raise ValueError
+            "invalid_logger"
+        )  # Invalid logger type, should raise ValueError
 
     with pytest.raises(ValueError):
-        flow_instance.add_context(None,
-                                  "value")  # None key, should raise ValueError
+        flow_instance.add_context(
+            None, "value"
+        )  # None key, should raise ValueError
 
     with pytest.raises(ValueError):
-        flow_instance.add_context("key",
-                                  None)  # None value, should raise ValueError
+        flow_instance.add_context(
+            "key", None
+        )  # None value, should raise ValueError
 
     with pytest.raises(ValueError):
         flow_instance.update_context(
-            None, "value")  # None key, should raise ValueError
+            None, "value"
+        )  # None key, should raise ValueError
 
     with pytest.raises(ValueError):
         flow_instance.update_context(
-            "key", None)  # None value, should raise ValueError
+            "key", None
+        )  # None value, should raise ValueError
 
 
 def test_flow_conversation_reset(flow_instance):
@@ -857,7 +934,6 @@ def test_flow_conversation_persistence(flow_instance):
 def test_flow_custom_event_listener(flow_instance):
     # Test custom event listener
     class CustomEventListener:
-
         def on_message_received(self, message):
             pass
 
@@ -869,10 +945,10 @@ def test_flow_custom_event_listener(flow_instance):
 
     # Ensure that the custom event listener methods are called during a conversation
     with mock.patch.object(
-            custom_event_listener,
-            "on_message_received") as mock_received, mock.patch.object(
-                custom_event_listener,
-                "on_response_generated") as mock_response:
+        custom_event_listener, "on_message_received"
+    ) as mock_received, mock.patch.object(
+        custom_event_listener, "on_response_generated"
+    ) as mock_response:
         flow_instance.run("Message 1")
         mock_received.assert_called_once()
         mock_response.assert_called_once()
@@ -881,7 +957,6 @@ def test_flow_custom_event_listener(flow_instance):
 def test_flow_multiple_event_listeners(flow_instance):
     # Test multiple event listeners
     class FirstEventListener:
-
         def on_message_received(self, message):
             pass
 
@@ -889,7 +964,6 @@ def test_flow_multiple_event_listeners(flow_instance):
             pass
 
     class SecondEventListener:
-
         def on_message_received(self, message):
             pass
 
@@ -903,14 +977,14 @@ def test_flow_multiple_event_listeners(flow_instance):
 
     # Ensure that both event listeners receive events during a conversation
     with mock.patch.object(
-            first_event_listener,
-            "on_message_received") as mock_first_received, mock.patch.object(
+        first_event_listener, "on_message_received"
+    ) as mock_first_received, mock.patch.object(
         first_event_listener, "on_response_generated"
     ) as mock_first_response, mock.patch.object(
         second_event_listener, "on_message_received"
     ) as mock_second_received, mock.patch.object(
-                second_event_listener,
-                "on_response_generated") as mock_second_response:
+        second_event_listener, "on_response_generated"
+    ) as mock_second_response:
         flow_instance.run("Message 1")
         mock_first_received.assert_called_once()
         mock_first_response.assert_called_once()
@@ -923,31 +997,38 @@ def test_flow_error_handling(flow_instance):
     # Test error handling and exceptions
     with pytest.raises(ValueError):
         flow_instance.set_message_delimiter(
-            "")  # Empty delimiter, should raise ValueError
+            ""
+        )  # Empty delimiter, should raise ValueError
 
     with pytest.raises(ValueError):
         flow_instance.set_message_delimiter(
-            None)  # None delimiter, should raise ValueError
+            None
+        )  # None delimiter, should raise ValueError
 
     with pytest.raises(ValueError):
         flow_instance.set_logger(
-            "invalid_logger")  # Invalid logger type, should raise ValueError
+            "invalid_logger"
+        )  # Invalid logger type, should raise ValueError
 
     with pytest.raises(ValueError):
-        flow_instance.add_context(None,
-                                  "value")  # None key, should raise ValueError
+        flow_instance.add_context(
+            None, "value"
+        )  # None key, should raise ValueError
 
     with pytest.raises(ValueError):
-        flow_instance.add_context("key",
-                                  None)  # None value, should raise ValueError
+        flow_instance.add_context(
+            "key", None
+        )  # None value, should raise ValueError
 
     with pytest.raises(ValueError):
         flow_instance.update_context(
-            None, "value")  # None key, should raise ValueError
+            None, "value"
+        )  # None key, should raise ValueError
 
     with pytest.raises(ValueError):
         flow_instance.update_context(
-            "key", None)  # None value, should raise ValueError
+            "key", None
+        )  # None value, should raise ValueError
 
 
 def test_flow_context_operations(flow_instance):
@@ -984,8 +1065,14 @@ def test_flow_custom_response(flow_instance):
     flow_instance.set_response_generator(custom_response_generator)
 
     assert flow_instance.run("Hello") == "Hi there!"
-    assert (flow_instance.run("How are you?") == "I'm doing well, thank you.")
-    assert (flow_instance.run("What's your name?") == "I don't understand.")
+    assert (
+        flow_instance.run("How are you?")
+        == "I'm doing well, thank you."
+    )
+    assert (
+        flow_instance.run("What's your name?")
+        == "I don't understand."
+    )
 
 
 def test_flow_message_validation(flow_instance):
@@ -996,8 +1083,12 @@ def test_flow_message_validation(flow_instance):
     flow_instance.set_message_validator(custom_message_validator)
 
     assert flow_instance.run("Valid message") is not None
-    assert (flow_instance.run("") is None)  # Empty message should be rejected
-    assert (flow_instance.run(None) is None)  # None message should be rejected
+    assert (
+        flow_instance.run("") is None
+    )  # Empty message should be rejected
+    assert (
+        flow_instance.run(None) is None
+    )  # None message should be rejected
 
 
 def test_flow_custom_logging(flow_instance):
@@ -1022,10 +1113,15 @@ def test_flow_complex_use_case(flow_instance):
     flow_instance.add_context("user_id", "12345")
     flow_instance.run("Hello")
     flow_instance.run("How can I help you?")
-    assert (flow_instance.get_response() == "Please provide more details.")
+    assert (
+        flow_instance.get_response() == "Please provide more details."
+    )
     flow_instance.update_context("user_id", "54321")
     flow_instance.run("I need help with my order")
-    assert (flow_instance.get_response() == "Sure, I can assist with that.")
+    assert (
+        flow_instance.get_response()
+        == "Sure, I can assist with that."
+    )
     flow_instance.reset_conversation()
     assert len(flow_instance.get_message_history()) == 0
     assert flow_instance.get_context("user_id") is None
@@ -1064,7 +1160,9 @@ def test_flow_concurrent_requests(flow_instance):
 
 def test_flow_custom_timeout(flow_instance):
     # Test custom timeout handling
-    flow_instance.set_timeout(10)  # Set a custom timeout of 10 seconds
+    flow_instance.set_timeout(
+        10
+    )  # Set a custom timeout of 10 seconds
     assert flow_instance.get_timeout() == 10
 
     import time
@@ -1115,10 +1213,16 @@ def test_flow_agent_history_prompt(flow_instance):
     history = ["User: Hi", "AI: Hello"]
 
     agent_history_prompt = flow_instance.agent_history_prompt(
-        system_prompt, history)
+        system_prompt, history
+    )
 
-    assert ("SYSTEM_PROMPT: This is the system prompt." in agent_history_prompt)
-    assert ("History: ['User: Hi', 'AI: Hello']" in agent_history_prompt)
+    assert (
+        "SYSTEM_PROMPT: This is the system prompt."
+        in agent_history_prompt
+    )
+    assert (
+        "History: ['User: Hi', 'AI: Hello']" in agent_history_prompt
+    )
 
 
 async def test_flow_run_concurrent(flow_instance):
@@ -1133,18 +1237,9 @@ async def test_flow_run_concurrent(flow_instance):
 def test_flow_bulk_run(flow_instance):
     # Test bulk running of tasks
     input_data = [
-        {
-            "task": "Task 1",
-            "param1": "value1"
-        },
-        {
-            "task": "Task 2",
-            "param2": "value2"
-        },
-        {
-            "task": "Task 3",
-            "param3": "value3"
-        },
+        {"task": "Task 1", "param1": "value1"},
+        {"task": "Task 2", "param2": "value2"},
+        {"task": "Task 3", "param3": "value3"},
     ]
     responses = flow_instance.bulk_run(input_data)
 
@@ -1159,7 +1254,9 @@ def test_flow_from_llm_and_template():
     llm_instance = mocked_llm  # Replace with your LLM class
     template = "This is a template for testing."
 
-    flow_instance = Agent.from_llm_and_template(llm_instance, template)
+    flow_instance = Agent.from_llm_and_template(
+        llm_instance, template
+    )
 
     assert isinstance(flow_instance, Agent)
 
@@ -1168,10 +1265,12 @@ def test_flow_from_llm_and_template_file():
     # Test creating Agent instance from an LLM and a template file
     llm_instance = mocked_llm  # Replace with your LLM class
     template_file = (  # Create a template file for testing
-        "template.txt")
+        "template.txt"
+    )
 
-    flow_instance = Agent.from_llm_and_template_file(llm_instance,
-                                                     template_file)
+    flow_instance = Agent.from_llm_and_template_file(
+        llm_instance, template_file
+    )
 
     assert isinstance(flow_instance, Agent)
 

tests/structs/test_autoscaler.py

@@ -44,7 +44,9 @@ def test_autoscaler_run():
         agent.id,
         "Generate a 10,000 word blog on health and wellness.",
     )
-    assert (out == "Generate a 10,000 word blog on health and wellness.")
+    assert (
+        out == "Generate a 10,000 word blog on health and wellness."
+    )
 
 
 def test_autoscaler_add_agent():
@@ -237,7 +239,9 @@ def test_autoscaler_add_task():
 
 
 def test_autoscaler_scale_up():
-    autoscaler = AutoScaler(initial_agents=5, scale_up_factor=2, agent=agent)
+    autoscaler = AutoScaler(
+        initial_agents=5, scale_up_factor=2, agent=agent
+    )
     autoscaler.scale_up()
     assert len(autoscaler.agents_pool) == 10
 

tests/structs/test_base.py

@@ -7,7 +7,6 @@ from swarms.structs.base import BaseStructure
 
 
 class TestBaseStructure:
-
     def test_init(self):
         base_structure = BaseStructure(
             name="TestStructure",
@@ -89,8 +88,11 @@ class TestBaseStructure:
         with open(log_file) as file:
             lines = file.readlines()
             assert len(lines) == 1
-            assert (lines[0] == f"[{base_structure._current_timestamp()}]"
-                    f" [{event_type}] {event}\n")
+            assert (
+                lines[0]
+                == f"[{base_structure._current_timestamp()}]"
+                f" [{event_type}] {event}\n"
+            )
 
     @pytest.mark.asyncio
     async def test_run_async(self):
@@ -134,7 +136,9 @@ class TestBaseStructure:
 
         artifact = {"key": "value"}
         artifact_name = "test_artifact"
-        await base_structure.save_artifact_async(artifact, artifact_name)
+        await base_structure.save_artifact_async(
+            artifact, artifact_name
+        )
         loaded_artifact = base_structure.load_artifact(artifact_name)
 
         assert loaded_artifact == artifact
@@ -147,7 +151,8 @@ class TestBaseStructure:
         artifact = {"key": "value"}
         artifact_name = "test_artifact"
         base_structure.save_artifact(artifact, artifact_name)
-        loaded_artifact = await base_structure.load_artifact_async(artifact_name
+        loaded_artifact = await base_structure.load_artifact_async(
+            artifact_name
         )
 
         assert loaded_artifact == artifact
@@ -165,8 +170,11 @@ class TestBaseStructure:
         with open(log_file) as file:
             lines = file.readlines()
             assert len(lines) == 1
-            assert (lines[0] == f"[{base_structure._current_timestamp()}]"
-                    f" [{event_type}] {event}\n")
+            assert (
+                lines[0]
+                == f"[{base_structure._current_timestamp()}]"
+                f" [{event_type}] {event}\n"
+            )
 
     @pytest.mark.asyncio
     async def test_asave_to_file(self, tmpdir):
@@ -193,14 +201,18 @@ class TestBaseStructure:
 
     def test_run_in_thread(self):
         base_structure = BaseStructure()
-        result = base_structure.run_in_thread(lambda: "Thread Test Result")
+        result = base_structure.run_in_thread(
+            lambda: "Thread Test Result"
+        )
         assert result.result() == "Thread Test Result"
 
     def test_save_and_decompress_data(self):
         base_structure = BaseStructure()
         data = {"key": "value"}
         compressed_data = base_structure.compress_data(data)
-        decompressed_data = base_structure.decompres_data(compressed_data)
+        decompressed_data = base_structure.decompres_data(
+            compressed_data
+        )
         assert decompressed_data == data
 
     def test_run_batched(self):
@@ -210,11 +222,13 @@ class TestBaseStructure:
             return f"Processed {data}"
 
         batched_data = list(range(10))
-        result = base_structure.run_batched(batched_data,
-                                            batch_size=5,
-                                            func=run_function)
+        result = base_structure.run_batched(
+            batched_data, batch_size=5, func=run_function
+        )
 
-        expected_result = [f"Processed {data}" for data in batched_data]
+        expected_result = [
+            f"Processed {data}" for data in batched_data
+        ]
         assert result == expected_result
 
     def test_load_config(self, tmpdir):
@@ -232,12 +246,15 @@ class TestBaseStructure:
         tmp_dir = tmpdir.mkdir("test_dir")
         base_structure = BaseStructure()
         data_to_backup = {"key": "value"}
-        base_structure.backup_data(data_to_backup, backup_path=tmp_dir)
+        base_structure.backup_data(
+            data_to_backup, backup_path=tmp_dir
+        )
         backup_files = os.listdir(tmp_dir)
 
         assert len(backup_files) == 1
         loaded_data = base_structure.load_from_file(
-            os.path.join(tmp_dir, backup_files[0]))
+            os.path.join(tmp_dir, backup_files[0])
+        )
         assert loaded_data == data_to_backup
 
     def test_monitor_resources(self):
@@ -262,9 +279,11 @@ class TestBaseStructure:
             return f"Processed {data}"
 
         batched_data = list(range(10))
-        result = base_structure.run_with_resources_batched(batched_data,
-                                                           batch_size=5,
-                                                           func=run_function)
+        result = base_structure.run_with_resources_batched(
+            batched_data, batch_size=5, func=run_function
+        )
 
-        expected_result = [f"Processed {data}" for data in batched_data]
+        expected_result = [
+            f"Processed {data}" for data in batched_data
+        ]
         assert result == expected_result

tests/structs/test_base_workflow.py

@@ -30,8 +30,13 @@ def test_load_workflow_state():
     workflow.load_workflow_state("workflow_state.json")
     assert workflow.max_loops == 1
     assert len(workflow.tasks) == 2
-    assert (workflow.tasks[0].description == "What's the weather in miami")
-    assert (workflow.tasks[1].description == "Create a report on these metrics")
+    assert (
+        workflow.tasks[0].description == "What's the weather in miami"
+    )
+    assert (
+        workflow.tasks[1].description
+        == "Create a report on these metrics"
+    )
     teardown_workflow()
 
 

tests/structs/test_concurrent_workflow.py

@@ -18,7 +18,9 @@ def test_run():
     workflow.add(task1)
     workflow.add(task2)
 
-    with patch("concurrent.futures.ThreadPoolExecutor") as mock_executor:
+    with patch(
+        "concurrent.futures.ThreadPoolExecutor"
+    ) as mock_executor:
         future1 = Future()
         future1.set_result(None)
         future2 = Future()

tests/structs/test_conversation.py

@@ -87,13 +87,16 @@ def test_return_history_as_string_with_different_roles(role, content):
 
 
 @pytest.mark.parametrize("message_count", range(1, 11))
-def test_return_history_as_string_with_multiple_messages(message_count,):
+def test_return_history_as_string_with_multiple_messages(
+    message_count,
+):
     conv = Conversation()
     for i in range(message_count):
         conv.add("user", f"Message {i + 1}")
     result = conv.return_history_as_string()
     expected = "".join(
-        [f"user: Message {i + 1}\n\n" for i in range(message_count)])
+        [f"user: Message {i + 1}\n\n" for i in range(message_count)]
+    )
     assert result == expected
 
 
@@ -119,8 +122,10 @@ def test_return_history_as_string_with_large_message(conversation):
     large_message = "Hello, world! " * 10000  # 10,000 repetitions
     conversation.add("user", large_message)
     result = conversation.return_history_as_string()
-    expected = ("user: Hello, world!\n\nassistant: Hello, user!\n\nuser:"
-                f" {large_message}\n\n")
+    expected = (
+        "user: Hello, world!\n\nassistant: Hello, user!\n\nuser:"
+        f" {large_message}\n\n"
+    )
     assert result == expected
 
 
@@ -136,8 +141,10 @@ def test_export_import_conversation(conversation, tmp_path):
     conversation.export_conversation(filename)
     new_conversation = Conversation()
     new_conversation.import_conversation(filename)
-    assert (new_conversation.return_history_as_string() ==
-            conversation.return_history_as_string())
+    assert (
+        new_conversation.return_history_as_string()
+        == conversation.return_history_as_string()
+    )
 
 
 def test_count_messages_by_role(conversation):

tests/structs/test_groupchat.py

@@ -11,7 +11,6 @@ llm2 = Anthropic()
 
 # Mock the OpenAI class for testing
 class MockOpenAI:
-
     def __init__(self, *args, **kwargs):
         pass
 
@@ -140,9 +139,9 @@ def test_groupchat_manager_generate_reply():
     selector = agent1
 
     # Initialize GroupChatManager
-    manager = GroupChatManager(groupchat=groupchat,
-                               selector=selector,
-                               openai=mocked_openai)
+    manager = GroupChatManager(
+        groupchat=groupchat, selector=selector, openai=mocked_openai
+    )
 
     # Generate a reply
     task = "Write me a riddle"
@@ -166,8 +165,9 @@ def test_groupchat_select_speaker():
 
     # Simulate selecting the next speaker
     last_speaker = agent1
-    next_speaker = manager.select_speaker(last_speaker=last_speaker,
-                                          selector=selector)
+    next_speaker = manager.select_speaker(
+        last_speaker=last_speaker, selector=selector
+    )
 
     # Ensure the next speaker is agent2
     assert next_speaker == agent2
@@ -185,8 +185,9 @@ def test_groupchat_underpopulated_group():
 
     # Simulate selecting the next speaker in an underpopulated group
     last_speaker = agent1
-    next_speaker = manager.select_speaker(last_speaker=last_speaker,
-                                          selector=selector)
+    next_speaker = manager.select_speaker(
+        last_speaker=last_speaker, selector=selector
+    )
 
     # Ensure the next speaker is the same as the last speaker in an underpopulated group
     assert next_speaker == last_speaker
@@ -204,13 +205,15 @@ def test_groupchat_max_rounds():
     # Simulate the conversation with max rounds
     last_speaker = agent1
     for _ in range(2):
-        next_speaker = manager.select_speaker(last_speaker=last_speaker,
-                                              selector=selector)
+        next_speaker = manager.select_speaker(
+            last_speaker=last_speaker, selector=selector
+        )
         last_speaker = next_speaker
 
     # Try one more round, should stay with the last speaker
-    next_speaker = manager.select_speaker(last_speaker=last_speaker,
-                                          selector=selector)
+    next_speaker = manager.select_speaker(
+        last_speaker=last_speaker, selector=selector
+    )
 
     # Ensure the next speaker is the same as the last speaker after reaching max rounds
     assert next_speaker == last_speaker

tests/structs/test_json.py

@@ -15,8 +15,10 @@ def valid_schema_path(tmp_path):
     d = tmp_path / "sub"
     d.mkdir()
     p = d / "schema.json"
-    p.write_text('{"type": "object", "properties": {"name": {"type":'
-                 ' "string"}}}')
+    p.write_text(
+        '{"type": "object", "properties": {"name": {"type":'
+        ' "string"}}}'
+    )
     return str(p)
 
 
@@ -31,7 +33,6 @@ def invalid_schema_path(tmp_path):
 
 # This test class must be subclassed as JSON class is abstract
 class TestableJSON(JSON):
-
     def validate(self, data):
         # Here must be a real validation implementation for testing
         pass

tests/structs/test_majority_voting.py

@@ -35,9 +35,15 @@ def test_majority_voting_run_concurrent(mocker):
     majority_vote = mv.run("What is the capital of France?")
 
     # Assert agent.run method was called with the correct task
-    agent1.run.assert_called_once_with("What is the capital of France?")
-    agent2.run.assert_called_once_with("What is the capital of France?")
-    agent3.run.assert_called_once_with("What is the capital of France?")
+    agent1.run.assert_called_once_with(
+        "What is the capital of France?"
+    )
+    agent2.run.assert_called_once_with(
+        "What is the capital of France?"
+    )
+    agent3.run.assert_called_once_with(
+        "What is the capital of France?"
+    )
 
     # Assert conversation.add method was called with the correct responses
     conversation.add.assert_any_call(agent1.agent_name, results[0])
@@ -77,9 +83,15 @@ def test_majority_voting_run_multithreaded(mocker):
     majority_vote = mv.run("What is the capital of France?")
 
     # Assert agent.run method was called with the correct task
-    agent1.run.assert_called_once_with("What is the capital of France?")
-    agent2.run.assert_called_once_with("What is the capital of France?")
-    agent3.run.assert_called_once_with("What is the capital of France?")
+    agent1.run.assert_called_once_with(
+        "What is the capital of France?"
+    )
+    agent2.run.assert_called_once_with(
+        "What is the capital of France?"
+    )
+    agent3.run.assert_called_once_with(
+        "What is the capital of France?"
+    )
 
     # Assert conversation.add method was called with the correct responses
     conversation.add.assert_any_call(agent1.agent_name, results[0])
@@ -121,9 +133,15 @@ async def test_majority_voting_run_asynchronous(mocker):
     majority_vote = await mv.run("What is the capital of France?")
 
     # Assert agent.run method was called with the correct task
-    agent1.run.assert_called_once_with("What is the capital of France?")
-    agent2.run.assert_called_once_with("What is the capital of France?")
-    agent3.run.assert_called_once_with("What is the capital of France?")
+    agent1.run.assert_called_once_with(
+        "What is the capital of France?"
+    )
+    agent2.run.assert_called_once_with(
+        "What is the capital of France?"
+    )
+    agent3.run.assert_called_once_with(
+        "What is the capital of France?"
+    )
 
     # Assert conversation.add method was called with the correct responses
     conversation.add.assert_any_call(agent1.agent_name, results[0])

tests/structs/test_message_pool.py

@@ -8,7 +8,9 @@ def test_message_pool_initialization():
     agent2 = Agent(llm=OpenAIChat(), agent_name="agent1")
     moderator = Agent(llm=OpenAIChat(), agent_name="agent1")
     agents = [agent1, agent2]
-    message_pool = MessagePool(agents=agents, moderator=moderator, turns=5)
+    message_pool = MessagePool(
+        agents=agents, moderator=moderator, turns=5
+    )
 
     assert message_pool.agent == agents
     assert message_pool.moderator == moderator
@@ -18,21 +20,27 @@ def test_message_pool_initialization():
 
 def test_message_pool_add():
     agent1 = Agent(llm=OpenAIChat(), agent_name="agent1")
-    message_pool = MessagePool(agents=[agent1], moderator=agent1, turns=5)
+    message_pool = MessagePool(
+        agents=[agent1], moderator=agent1, turns=5
+    )
     message_pool.add(agent=agent1, content="Hello, world!", turn=1)
 
-    assert message_pool.messages == [{
+    assert message_pool.messages == [
+        {
             "agent": agent1,
             "content": "Hello, world!",
             "turn": 1,
             "visible_to": "all",
             "logged": True,
-    }]
+        }
+    ]
 
 
 def test_message_pool_reset():
     agent1 = Agent(llm=OpenAIChat(), agent_name="agent1")
-    message_pool = MessagePool(agents=[agent1], moderator=agent1, turns=5)
+    message_pool = MessagePool(
+        agents=[agent1], moderator=agent1, turns=5
+    )
     message_pool.add(agent=agent1, content="Hello, world!", turn=1)
     message_pool.reset()
 
@@ -41,7 +49,9 @@ def test_message_pool_reset():
 
 def test_message_pool_last_turn():
     agent1 = Agent(llm=OpenAIChat(), agent_name="agent1")
-    message_pool = MessagePool(agents=[agent1], moderator=agent1, turns=5)
+    message_pool = MessagePool(
+        agents=[agent1], moderator=agent1, turns=5
+    )
     message_pool.add(agent=agent1, content="Hello, world!", turn=1)
 
     assert message_pool.last_turn() == 1
@@ -49,7 +59,9 @@ def test_message_pool_last_turn():
 
 def test_message_pool_last_message():
     agent1 = Agent(llm=OpenAIChat(), agent_name="agent1")
-    message_pool = MessagePool(agents=[agent1], moderator=agent1, turns=5)
+    message_pool = MessagePool(
+        agents=[agent1], moderator=agent1, turns=5
+    )
     message_pool.add(agent=agent1, content="Hello, world!", turn=1)
 
     assert message_pool.last_message == {
@@ -63,24 +75,28 @@ def test_message_pool_last_message():
 
 def test_message_pool_get_all_messages():
     agent1 = Agent(llm=OpenAIChat(), agent_name="agent1")
-    message_pool = MessagePool(agents=[agent1], moderator=agent1, turns=5)
+    message_pool = MessagePool(
+        agents=[agent1], moderator=agent1, turns=5
+    )
     message_pool.add(agent=agent1, content="Hello, world!", turn=1)
 
-    assert message_pool.get_all_messages() == [{
+    assert message_pool.get_all_messages() == [
+        {
             "agent": agent1,
             "content": "Hello, world!",
             "turn": 1,
             "visible_to": "all",
             "logged": True,
-    }]
+        }
+    ]
 
 
 def test_message_pool_get_visible_messages():
     agent1 = Agent(llm=OpenAIChat(), agent_name="agent1")
     agent2 = Agent(agent_name="agent2")
-    message_pool = MessagePool(agents=[agent1, agent2],
-                               moderator=agent1,
-                               turns=5)
+    message_pool = MessagePool(
+        agents=[agent1, agent2], moderator=agent1, turns=5
+    )
     message_pool.add(
         agent=agent1,
         content="Hello, agent2!",
@@ -88,10 +104,14 @@ def test_message_pool_get_visible_messages():
         visible_to=[agent2.agent_name],
     )
 
-    assert message_pool.get_visible_messages(agent=agent2, turn=2) == [{
+    assert message_pool.get_visible_messages(
+        agent=agent2, turn=2
+    ) == [
+        {
             "agent": agent1,
             "content": "Hello, agent2!",
             "turn": 1,
             "visible_to": [agent2.agent_name],
             "logged": True,
-    }]
+        }
+    ]

tests/structs/test_model_parallizer.py

@@ -11,9 +11,7 @@ from swarms.structs.model_parallizer import ModelParallelizer
 # Initialize the models
 custom_config = {
     "quantize": True,
-    "quantization_config": {
-        "load_in_4bit": True
-    },
+    "quantization_config": {"load_in_4bit": True},
     "verbose": True,
 }
 huggingface_llm = HuggingfaceLLM(
@@ -26,12 +24,14 @@ zeroscope_ttv = ZeroscopeTTV()
 
 
 def test_init():
-    mp = ModelParallelizer([
+    mp = ModelParallelizer(
+        [
             huggingface_llm,
             mixtral,
             gpt4_vision_api,
             zeroscope_ttv,
-    ])
+        ]
+    )
     assert isinstance(mp, ModelParallelizer)
 
 
@@ -39,20 +39,24 @@ def test_run():
     mp = ModelParallelizer([huggingface_llm])
     result = mp.run(
         "Create a list of known biggest risks of structural collapse"
-        " with references")
+        " with references"
+    )
     assert isinstance(result, str)
 
 
 def test_run_all():
-    mp = ModelParallelizer([
+    mp = ModelParallelizer(
+        [
             huggingface_llm,
             mixtral,
             gpt4_vision_api,
             zeroscope_ttv,
-    ])
+        ]
+    )
     result = mp.run_all(
         "Create a list of known biggest risks of structural collapse"
-        " with references")
+        " with references"
+    )
     assert isinstance(result, list)
     assert len(result) == 5
 
@@ -71,8 +75,10 @@ def test_remove_llm():
 
 def test_save_responses_to_file(tmp_path):
     mp = ModelParallelizer([huggingface_llm])
-    mp.run("Create a list of known biggest risks of structural collapse"
-           " with references")
+    mp.run(
+        "Create a list of known biggest risks of structural collapse"
+        " with references"
+    )
     file = tmp_path / "responses.txt"
     mp.save_responses_to_file(file)
     assert file.read_text() != ""
@@ -80,8 +86,10 @@ def test_save_responses_to_file(tmp_path):
 
 def test_get_task_history():
     mp = ModelParallelizer([huggingface_llm])
-    mp.run("Create a list of known biggest risks of structural collapse"
-           " with references")
+    mp.run(
+        "Create a list of known biggest risks of structural collapse"
+        " with references"
+    )
     assert mp.get_task_history() == [
         "Create a list of known biggest risks of structural collapse"
         " with references"
@@ -90,8 +98,10 @@ def test_get_task_history():
 
 def test_summary(capsys):
     mp = ModelParallelizer([huggingface_llm])
-    mp.run("Create a list of known biggest risks of structural collapse"
-           " with references")
+    mp.run(
+        "Create a list of known biggest risks of structural collapse"
+        " with references"
+    )
     mp.summary()
     captured = capsys.readouterr()
     assert "Tasks History:" in captured.out
@@ -113,7 +123,8 @@ def test_concurrent_run():
     mp = ModelParallelizer([huggingface_llm, mixtral])
     result = mp.concurrent_run(
         "Create a list of known biggest risks of structural collapse"
-        " with references")
+        " with references"
+    )
     assert isinstance(result, list)
     assert len(result) == 2
 

tests/structs/test_multi_agent_collab.py

@@ -73,8 +73,12 @@ def test_run(collaboration):
 
 
 def test_format_results(collaboration):
-    collaboration.results = [{"agent": "Agent1", "response": "Response1"}]
-    formatted_results = collaboration.format_results(collaboration.results)
+    collaboration.results = [
+        {"agent": "Agent1", "response": "Response1"}
+    ]
+    formatted_results = collaboration.format_results(
+        collaboration.results
+    )
     assert "Agent1 responded: Response1" in formatted_results
 
 
@@ -108,10 +112,7 @@ def test_repr(collaboration):
 def test_load(collaboration):
     state = {
         "step": 5,
-        "results": [{
-            "agent": "Agent1",
-            "response": "Response1"
-        }],
+        "results": [{"agent": "Agent1", "response": "Response1"}],
     }
     with open(collaboration.saved_file_path_name, "w") as file:
         json.dump(state, file)

tests/structs/test_nonlinear_workflow.py

@@ -5,7 +5,6 @@ from swarms.structs import NonlinearWorkflow, Task
 
 
 class TestNonlinearWorkflow:
-
     def test_add_task(self):
         llm = OpenAIChat(openai_api_key="")
         task = Task(llm, "What's the weather in miami")
@@ -34,7 +33,9 @@ class TestNonlinearWorkflow:
         workflow = NonlinearWorkflow()
         workflow.add(task1, task2.name)
         workflow.add(task2, task1.name)
-        with pytest.raises(Exception, match="Circular dependency detected"):
+        with pytest.raises(
+            Exception, match="Circular dependency detected"
+        ):
             workflow.run()
 
     def test_run_with_stopping_token(self):

tests/structs/test_recursive_workflow.py

@@ -53,7 +53,9 @@ def test_run_stop_token_not_in_result():
         try:
             workflow.run()
         except RecursionError:
-            pytest.fail("RecursiveWorkflow.run caused a RecursionError")
+            pytest.fail(
+                "RecursiveWorkflow.run caused a RecursionError"
+            )
 
     assert agent.execute.call_count == max_iterations
 

tests/structs/test_sequential_workflow.py

@@ -17,7 +17,6 @@ os.environ["OPENAI_API_KEY"] = "mocked_api_key"
 
 # Mock OpenAIChat class for testing
 class MockOpenAIChat:
-
     def __init__(self, *args, **kwargs):
         pass
 
@@ -27,7 +26,6 @@ class MockOpenAIChat:
 
 # Mock Agent class for testing
 class MockAgent:
-
     def __init__(self, *args, **kwargs):
         pass
 
@@ -37,7 +35,6 @@ class MockAgent:
 
 # Mock SequentialWorkflow class for testing
 class MockSequentialWorkflow:
-
     def __init__(self, *args, **kwargs):
         pass
 
@@ -72,7 +69,10 @@ def test_sequential_workflow_initialization():
     assert len(workflow.tasks) == 0
     assert workflow.max_loops == 1
     assert workflow.autosave is False
-    assert (workflow.saved_state_filepath == "sequential_workflow_state.json")
+    assert (
+        workflow.saved_state_filepath
+        == "sequential_workflow_state.json"
+    )
     assert workflow.restore_state_filepath is None
     assert workflow.dashboard is False
 
@@ -177,7 +177,6 @@ def test_sequential_workflow_workflow_dashboard(capfd):
 
 # Mock Agent class for async testing
 class MockAsyncAgent:
-
     def __init__(self, *args, **kwargs):
         pass
 

tests/structs/test_swarmnetwork.py

@@ -20,7 +20,9 @@ def test_swarm_network_init(swarm_network):
 @patch("swarms.structs.swarm_net.SwarmNetwork.logger")
 def test_run(mock_logger, swarm_network):
     swarm_network.run()
-    assert (mock_logger.info.call_count == 10)  # 2 log messages per agent
+    assert (
+        mock_logger.info.call_count == 10
+    )  # 2 log messages per agent
 
 
 def test_run_with_mocked_agents(mocker, swarm_network):

tests/structs/test_task.py

@@ -7,7 +7,8 @@ from dotenv import load_dotenv
 
 from swarms.models.gpt4_vision_api import GPT4VisionAPI
 from swarms.prompts.multi_modal_autonomous_instruction_prompt import (
-    MULTI_MODAL_AUTO_AGENT_SYSTEM_PROMPT_1,)
+    MULTI_MODAL_AUTO_AGENT_SYSTEM_PROMPT_1,
+)
 from swarms.structs.agent import Agent
 from swarms.structs.task import Task
 
@@ -20,11 +21,13 @@ def llm():
 
 
 def test_agent_run_task(llm):
-    task = ("Analyze this image of an assembly line and identify any"
+    task = (
+        "Analyze this image of an assembly line and identify any"
         " issues such as misaligned parts, defects, or deviations"
         " from the standard assembly process. IF there is anything"
         " unsafe in the image, explain why it is unsafe and how it"
-            " could be improved.")
+        " could be improved."
+    )
     img = "assembly_line.jpg"
 
     agent = Agent(
@@ -46,7 +49,9 @@ def test_agent_run_task(llm):
 @pytest.fixture
 def task():
     agents = [Agent(llm=llm, id=f"Agent_{i}") for i in range(5)]
-    return Task(id="Task_1", task="Task_Name", agents=agents, dependencies=[])
+    return Task(
+        id="Task_1", task="Task_Name", agents=agents, dependencies=[]
+    )
 
 
 # Basic tests
@@ -184,7 +189,9 @@ def test_task_execute_with_condition(mocker):
     mock_agent = mocker.Mock(spec=Agent)
     mock_agent.run.return_value = "result"
     condition = mocker.Mock(return_value=True)
-    task = Task(description="Test task", agent=mock_agent, condition=condition)
+    task = Task(
+        description="Test task", agent=mock_agent, condition=condition
+    )
     task.execute()
     assert task.result == "result"
     assert task.history == ["result"]
@@ -194,7 +201,9 @@ def test_task_execute_with_condition_false(mocker):
     mock_agent = mocker.Mock(spec=Agent)
     mock_agent.run.return_value = "result"
     condition = mocker.Mock(return_value=False)
-    task = Task(description="Test task", agent=mock_agent, condition=condition)
+    task = Task(
+        description="Test task", agent=mock_agent, condition=condition
+    )
     task.execute()
     assert task.result is None
     assert task.history == []
@@ -204,7 +213,9 @@ def test_task_execute_with_action(mocker):
     mock_agent = mocker.Mock(spec=Agent)
     mock_agent.run.return_value = "result"
     action = mocker.Mock()
-    task = Task(description="Test task", agent=mock_agent, action=action)
+    task = Task(
+        description="Test task", agent=mock_agent, action=action
+    )
     task.execute()
     assert task.result == "result"
     assert task.history == ["result"]
@@ -232,9 +243,11 @@ def test_task_handle_scheduled_task_future(mocker):
         agent=mock_agent,
         schedule_time=datetime.now() + timedelta(days=1),
     )
-    with mocker.patch.object(task.scheduler,
-                             "enter") as mock_enter, mocker.patch.object(
-                                 task.scheduler, "run") as mock_run:
+    with mocker.patch.object(
+        task.scheduler, "enter"
+    ) as mock_enter, mocker.patch.object(
+        task.scheduler, "run"
+    ) as mock_run:
         task.handle_scheduled_task()
     mock_enter.assert_called_once()
     mock_run.assert_called_once()

tests/structs/test_taskqueuebase.py

@@ -21,9 +21,7 @@ def agent():
 
 @pytest.fixture()
 def concrete_task_queue():
-
     class ConcreteTaskQueue(TaskQueueBase):
-
         def add_task(self, task):
             pass  # Here you would add concrete implementation of add_task
 
@@ -53,8 +51,9 @@ def test_add_task_failure(concrete_task_queue, task):
     # Assuming the task is somehow invalid
     # Note: Concrete implementation requires logic defining what an invalid task is
     concrete_task_queue.add_task(task)
-    assert (concrete_task_queue.add_task(task)
-            is False)  # Adding the same task again
+    assert (
+        concrete_task_queue.add_task(task) is False
+    )  # Adding the same task again
 
 
 @pytest.mark.parametrize("invalid_task", [None, "", {}, []])

tests/structs/test_team.py

@@ -7,7 +7,6 @@ from swarms.structs.team import Team
 
 
 class TestTeam(unittest.TestCase):
-
     def setUp(self):
         self.agent = Agent(
             llm=OpenAIChat(openai_api_key=""),
@@ -31,17 +30,16 @@ class TestTeam(unittest.TestCase):
 
         with self.assertRaises(ValueError):
             self.team.check_config(
-                {"config": json.dumps({
-                    "agents": [],
-                    "tasks": []
-                })})
+                {"config": json.dumps({"agents": [], "tasks": []})}
+            )
 
     def test_run(self):
         self.assertEqual(self.team.run(), self.task.execute())
 
     def test_sequential_loop(self):
-        self.assertEqual(self.team._Team__sequential_loop(),
-                         self.task.execute())
+        self.assertEqual(
+            self.team._Team__sequential_loop(), self.task.execute()
+        )
 
     def test_log(self):
         self.assertIsNone(self.team._Team__log("Test message"))

tests/structs/test_tests_graph_workflow.py

@@ -27,7 +27,9 @@ def test_set_entry_point(graph_workflow):
 
 
 def test_set_entry_point_nonexistent_node(graph_workflow):
-    with pytest.raises(ValueError, match="Node does not exist in graph"):
+    with pytest.raises(
+        ValueError, match="Node does not exist in graph"
+    ):
         graph_workflow.set_entry_point("nonexistent")
 
 
@@ -40,23 +42,29 @@ def test_add_edge(graph_workflow):
 
 def test_add_edge_nonexistent_node(graph_workflow):
     graph_workflow.add("node1", "value1")
-    with pytest.raises(ValueError, match="Node does not exist in graph"):
+    with pytest.raises(
+        ValueError, match="Node does not exist in graph"
+    ):
         graph_workflow.add_edge("node1", "nonexistent")
 
 
 def test_add_conditional_edges(graph_workflow):
     graph_workflow.add("node1", "value1")
     graph_workflow.add("node2", "value2")
-    graph_workflow.add_conditional_edges("node1", "condition1",
-                                         {"condition_value1": "node2"})
+    graph_workflow.add_conditional_edges(
+        "node1", "condition1", {"condition_value1": "node2"}
+    )
     assert "node2" in graph_workflow.graph["node1"]["edges"]
 
 
 def test_add_conditional_edges_nonexistent_node(graph_workflow):
     graph_workflow.add("node1", "value1")
-    with pytest.raises(ValueError, match="Node does not exist in graph"):
+    with pytest.raises(
+        ValueError, match="Node does not exist in graph"
+    ):
         graph_workflow.add_conditional_edges(
-            "node1", "condition1", {"condition_value1": "nonexistent"})
+            "node1", "condition1", {"condition_value1": "nonexistent"}
+        )
 
 
 def test_run(graph_workflow):

tests/telemetry/test_posthog_utils.py

@@ -35,8 +35,9 @@ def test_log_activity_posthog(mock_posthog, mock_env):
     test_function()
 
     # Check if the Posthog capture method was called with the expected arguments
-    mock_posthog.capture.assert_called_once_with("test_user_id", event_name,
-                                                 event_properties)
+    mock_posthog.capture.assert_called_once_with(
+        "test_user_id", event_name, event_properties
+    )
 
 
 # Test a scenario where environment variables are not set

tests/telemetry/test_user_utils.py

@@ -46,7 +46,9 @@ def test_generate_unique_identifier():
     # Generate unique identifiers and ensure they are valid UUID strings
     unique_id = generate_unique_identifier()
     assert isinstance(unique_id, str)
-    assert uuid.UUID(unique_id, version=5, namespace=uuid.NAMESPACE_DNS)
+    assert uuid.UUID(
+        unique_id, version=5, namespace=uuid.NAMESPACE_DNS
+    )
 
 
 def test_generate_user_id_edge_case():
@@ -71,7 +73,9 @@ def test_get_system_info_edge_case():
     # Test get_system_info for consistency
     system_info1 = get_system_info()
     system_info2 = get_system_info()
-    assert (system_info1 == system_info2)  # Ensure system info remains the same
+    assert (
+        system_info1 == system_info2
+    )  # Ensure system info remains the same
 
 
 def test_generate_unique_identifier_edge_case():

tests/test_upload_tests_to_issues.py

@@ -20,7 +20,9 @@ headers = {
 
 
 def run_pytest():
-    result = subprocess.run(["pytest"], capture_output=True, text=True)
+    result = subprocess.run(
+        ["pytest"], capture_output=True, text=True
+    )
     return result.stdout + result.stderr
 
 
@@ -54,7 +56,9 @@ def main():
     errors = parse_pytest_output(pytest_output)
 
     for error in errors:
-        issue_response = create_github_issue(error["title"], error["body"])
+        issue_response = create_github_issue(
+            error["title"], error["body"]
+        )
         print(f"Issue created: {issue_response.get('html_url')}")
 
 

tests/tokenizers/test_anthropictokenizer.py

@@ -16,8 +16,9 @@ def test_default_max_tokens():
     assert tokenizer.default_max_tokens() == 100000
 
 
-@pytest.mark.parametrize("model,tokens", [("claude-2.1", 200000),
-                                          ("claude", 100000)])
+@pytest.mark.parametrize(
+    "model,tokens", [("claude-2.1", 200000), ("claude", 100000)]
+)
 def test_default_max_tokens_models(model, tokens):
     tokenizer = AnthropicTokenizer(model=model)
     assert tokenizer.default_max_tokens() == tokens

tests/tokenizers/test_basetokenizer.py

@@ -18,7 +18,9 @@ def test_post_init(base_tokenizer):
 
 
 # 3. Tests for count_tokens_left with different inputs.
-def test_count_tokens_left_with_positive_diff(base_tokenizer, monkeypatch):
+def test_count_tokens_left_with_positive_diff(
+    base_tokenizer, monkeypatch
+):
     # Mocking count_tokens to return a specific value
     monkeypatch.setattr(
         "swarms.tokenizers.BaseTokenizer.count_tokens",
@@ -27,7 +29,9 @@ def test_count_tokens_left_with_positive_diff(base_tokenizer, monkeypatch):
     assert base_tokenizer.count_tokens_left("some text") == 50
 
 
-def test_count_tokens_left_with_zero_diff(base_tokenizer, monkeypatch):
+def test_count_tokens_left_with_zero_diff(
+    base_tokenizer, monkeypatch
+):
     monkeypatch.setattr(
         "swarms.tokenizers.BaseTokenizer.count_tokens",
         lambda x, y: 100,

tests/tokenizers/test_huggingfacetokenizer.py

@@ -51,10 +51,18 @@ def test_prefix_space_tokens(hftokenizer):
 
 # testing _maybe_add_prefix_space method
 def test__maybe_add_prefix_space(hftokenizer):
-    assert (hftokenizer._maybe_add_prefix_space(
-        [101, 2003, 2010, 2050, 2001, 2339], " is why") == " is why")
-    assert (hftokenizer._maybe_add_prefix_space([2003, 2010, 2050, 2001, 2339],
-                                                "is why") == " is why")
+    assert (
+        hftokenizer._maybe_add_prefix_space(
+            [101, 2003, 2010, 2050, 2001, 2339], " is why"
+        )
+        == " is why"
+    )
+    assert (
+        hftokenizer._maybe_add_prefix_space(
+            [2003, 2010, 2050, 2001, 2339], "is why"
+        )
+        == " is why"
+    )
 
 
 # continuing tests for other methods...

tests/tokenizers/test_openaitokenizer.py

@@ -18,21 +18,31 @@ def test_default_max_tokens(openai_tokenizer):
     assert openai_tokenizer.default_max_tokens() == 4096
 
 
-@pytest.mark.parametrize("text, expected_output", [("Hello, world!", 3),
-                                                   (["Hello"], 4)])
+@pytest.mark.parametrize(
+    "text, expected_output", [("Hello, world!", 3), (["Hello"], 4)]
+)
 def test_count_tokens_single(openai_tokenizer, text, expected_output):
-    assert (openai_tokenizer.count_tokens(text, "gpt-3") == expected_output)
+    assert (
+        openai_tokenizer.count_tokens(text, "gpt-3")
+        == expected_output
+    )
 
 
 @pytest.mark.parametrize(
     "texts, expected_output",
     [(["Hello, world!", "This is a test"], 6), (["Hello"], 4)],
 )
-def test_count_tokens_multiple(openai_tokenizer, texts, expected_output):
-    assert (openai_tokenizer.count_tokens(texts, "gpt-3") == expected_output)
+def test_count_tokens_multiple(
+    openai_tokenizer, texts, expected_output
+):
+    assert (
+        openai_tokenizer.count_tokens(texts, "gpt-3")
+        == expected_output
+    )
 
 
-@pytest.mark.parametrize("text, expected_output", [("Hello, world!", 3),
-                                                   (["Hello"], 4)])
+@pytest.mark.parametrize(
+    "text, expected_output", [("Hello, world!", 3), (["Hello"], 4)]
+)
 def test_len(openai_tokenizer, text, expected_output):
     assert openai_tokenizer.len(text, "gpt-3") == expected_output

tests/tokenizers/test_tokenizer.py

@@ -7,7 +7,9 @@ from swarms.tokenizers.r_tokenizers import Tokenizer
 
 def test_initializer_existing_model_file():
     with patch("os.path.exists", return_value=True):
-        with patch("swarms.tokenizers.SentencePieceTokenizer") as mock_model:
+        with patch(
+            "swarms.tokenizers.SentencePieceTokenizer"
+        ) as mock_model:
             tokenizer = Tokenizer("tokenizers/my_model.model")
             mock_model.assert_called_with("tokenizers/my_model.model")
             assert tokenizer.model == mock_model.return_value
@@ -15,43 +17,66 @@ def test_initializer_existing_model_file():
 
 def test_initializer_model_folder():
     with patch("os.path.exists", side_effect=[False, True]):
-        with patch("swarms.tokenizers.HuggingFaceTokenizer") as mock_model:
+        with patch(
+            "swarms.tokenizers.HuggingFaceTokenizer"
+        ) as mock_model:
             tokenizer = Tokenizer("my_model_directory")
             mock_model.assert_called_with("my_model_directory")
             assert tokenizer.model == mock_model.return_value
 
 
 def test_vocab_size():
-    with patch("swarms.tokenizers.SentencePieceTokenizer") as mock_model:
+    with patch(
+        "swarms.tokenizers.SentencePieceTokenizer"
+    ) as mock_model:
         tokenizer = Tokenizer("tokenizers/my_model.model")
-        assert (tokenizer.vocab_size == mock_model.return_value.vocab_size)
+        assert (
+            tokenizer.vocab_size == mock_model.return_value.vocab_size
+        )
 
 
 def test_bos_token_id():
-    with patch("swarms.tokenizers.SentencePieceTokenizer") as mock_model:
+    with patch(
+        "swarms.tokenizers.SentencePieceTokenizer"
+    ) as mock_model:
         tokenizer = Tokenizer("tokenizers/my_model.model")
-        assert (tokenizer.bos_token_id == mock_model.return_value.bos_token_id)
+        assert (
+            tokenizer.bos_token_id
+            == mock_model.return_value.bos_token_id
+        )
 
 
 def test_encode():
-    with patch("swarms.tokenizers.SentencePieceTokenizer") as mock_model:
+    with patch(
+        "swarms.tokenizers.SentencePieceTokenizer"
+    ) as mock_model:
         tokenizer = Tokenizer("tokenizers/my_model.model")
-        assert (tokenizer.encode("hello") ==
-                mock_model.return_value.encode.return_value)
+        assert (
+            tokenizer.encode("hello")
+            == mock_model.return_value.encode.return_value
+        )
 
 
 def test_decode():
-    with patch("swarms.tokenizers.SentencePieceTokenizer") as mock_model:
+    with patch(
+        "swarms.tokenizers.SentencePieceTokenizer"
+    ) as mock_model:
         tokenizer = Tokenizer("tokenizers/my_model.model")
-        assert (tokenizer.decode(
-            [1, 2, 3]) == mock_model.return_value.decode.return_value)
+        assert (
+            tokenizer.decode([1, 2, 3])
+            == mock_model.return_value.decode.return_value
+        )
 
 
 def test_call():
-    with patch("swarms.tokenizers.SentencePieceTokenizer") as mock_model:
+    with patch(
+        "swarms.tokenizers.SentencePieceTokenizer"
+    ) as mock_model:
         tokenizer = Tokenizer("tokenizers/my_model.model")
         assert (
-            tokenizer("hello") == mock_model.return_value.__call__.return_value)
+            tokenizer("hello")
+            == mock_model.return_value.__call__.return_value
+        )
 
 
 # More tests can be added here

tests/tools/test_tools_base.py

@@ -65,20 +65,23 @@ def test_structured_tool_invoke():
 
 
 def test_tool_creation():
-    tool = Tool(name="test_tool", func=lambda x: x, description="Test tool")
+    tool = Tool(
+        name="test_tool", func=lambda x: x, description="Test tool"
+    )
     assert tool.name == "test_tool"
     assert tool.func is not None
     assert tool.description == "Test tool"
 
 
 def test_tool_ainvoke():
-    tool = Tool(name="test_tool", func=lambda x: x, description="Test tool")
+    tool = Tool(
+        name="test_tool", func=lambda x: x, description="Test tool"
+    )
     result = tool.ainvoke("input_data")
     assert result == "input_data"
 
 
 def test_tool_ainvoke_with_coroutine():
-
     async def async_function(input_data):
         return input_data
 
@@ -92,7 +95,6 @@ def test_tool_ainvoke_with_coroutine():
 
 
 def test_tool_args():
-
     def sample_function(input_data):
         return input_data
 
@@ -108,7 +110,6 @@ def test_tool_args():
 
 
 def test_structured_tool_creation():
-
     class SampleArgsSchema:
         pass
 
@@ -125,7 +126,6 @@ def test_structured_tool_creation():
 
 
 def test_structured_tool_ainvoke():
-
     class SampleArgsSchema:
         pass
 
@@ -140,7 +140,6 @@ def test_structured_tool_ainvoke():
 
 
 def test_structured_tool_ainvoke_with_coroutine():
-
     class SampleArgsSchema:
         pass
 
@@ -158,7 +157,6 @@ def test_structured_tool_ainvoke_with_coroutine():
 
 
 def test_structured_tool_args():
-
     class SampleArgsSchema:
         pass
 
@@ -184,13 +182,14 @@ def test_tool_ainvoke_exception():
 
 
 def test_tool_ainvoke_with_coroutine_exception():
-    tool = Tool(name="test_tool", coroutine=None, description="Test tool")
+    tool = Tool(
+        name="test_tool", coroutine=None, description="Test tool"
+    )
     with pytest.raises(NotImplementedError):
         tool.ainvoke("input_data")
 
 
 def test_structured_tool_ainvoke_exception():
-
     class SampleArgsSchema:
         pass
 
@@ -205,7 +204,6 @@ def test_structured_tool_ainvoke_exception():
 
 
 def test_structured_tool_ainvoke_with_coroutine_exception():
-
     class SampleArgsSchema:
         pass
 
@@ -227,7 +225,6 @@ def test_tool_description_not_provided():
 
 
 def test_tool_invoke_with_callbacks():
-
     def sample_function(input_data, callbacks=None):
         if callbacks:
             callbacks.on_start()
@@ -243,7 +240,6 @@ def test_tool_invoke_with_callbacks():
 
 
 def test_tool_invoke_with_new_argument():
-
     def sample_function(input_data, callbacks=None):
         return input_data
 
@@ -253,7 +249,6 @@ def test_tool_invoke_with_new_argument():
 
 
 def test_tool_ainvoke_with_new_argument():
-
     async def async_function(input_data, callbacks=None):
         return input_data
 
@@ -263,7 +258,6 @@ def test_tool_ainvoke_with_new_argument():
 
 
 def test_tool_description_from_docstring():
-
     def sample_function(input_data):
         """Sample function docstring"""
         return input_data
@@ -273,7 +267,6 @@ def test_tool_description_from_docstring():
 
 
 def test_tool_ainvoke_with_exceptions():
-
     async def async_function(input_data):
         raise ValueError("Test exception")
 
@@ -286,7 +279,6 @@ def test_tool_ainvoke_with_exceptions():
 
 
 def test_structured_tool_infer_schema_false():
-
     def sample_function(input_data):
         return input_data
 
@@ -300,7 +292,6 @@ def test_structured_tool_infer_schema_false():
 
 
 def test_structured_tool_ainvoke_with_callbacks():
-
     class SampleArgsSchema:
         pass
 
@@ -316,14 +307,15 @@ def test_structured_tool_ainvoke_with_callbacks():
         args_schema=SampleArgsSchema,
     )
     callbacks = MagicMock()
-    result = tool.ainvoke({"tool_input": "input_data"}, callbacks=callbacks)
+    result = tool.ainvoke(
+        {"tool_input": "input_data"}, callbacks=callbacks
+    )
     assert result == "input_data"
     callbacks.on_start.assert_called_once()
     callbacks.on_finish.assert_called_once()
 
 
 def test_structured_tool_description_not_provided():
-
     class SampleArgsSchema:
         pass
 
@@ -338,7 +330,6 @@ def test_structured_tool_description_not_provided():
 
 
 def test_structured_tool_args_schema():
-
     class SampleArgsSchema:
         pass
 
@@ -354,7 +345,6 @@ def test_structured_tool_args_schema():
 
 
 def test_structured_tool_args_schema_inference():
-
     def sample_function(input_data):
         return input_data
 
@@ -368,7 +358,6 @@ def test_structured_tool_args_schema_inference():
 
 
 def test_structured_tool_ainvoke_with_new_argument():
-
     class SampleArgsSchema:
         pass
 
@@ -380,12 +369,13 @@ def test_structured_tool_ainvoke_with_new_argument():
         func=sample_function,
         args_schema=SampleArgsSchema,
     )
-    result = tool.ainvoke({"tool_input": "input_data"}, callbacks=None)
+    result = tool.ainvoke(
+        {"tool_input": "input_data"}, callbacks=None
+    )
     assert result == "input_data"
 
 
 def test_structured_tool_ainvoke_with_exceptions():
-
     class SampleArgsSchema:
         pass
 
@@ -471,7 +461,9 @@ def test_tool_with_runnable(mock_runnable):
 def test_tool_with_invalid_argument():
     # Test passing an invalid argument type
     with pytest.raises(ValueError):
-        tool(123)  # Using an integer instead of a string/callable/Runnable
+        tool(
+            123
+        )  # Using an integer instead of a string/callable/Runnable
 
 
 def test_tool_with_multiple_arguments(mock_func):
@@ -533,7 +525,9 @@ class MockSchema(BaseModel):
 # Test suite starts here
 class TestTool:
     # Basic Functionality Tests
-    def test_tool_with_valid_callable_creates_base_tool(self, mock_func):
+    def test_tool_with_valid_callable_creates_base_tool(
+        self, mock_func
+    ):
         result = tool(mock_func)
         assert isinstance(result, BaseTool)
 
@@ -566,7 +560,6 @@ class TestTool:
 
     # Error Handling Tests
     def test_tool_raises_error_without_docstring(self):
-
         def no_doc_func(arg: str) -> str:
             return arg
 
@@ -574,14 +567,14 @@ class TestTool:
             tool(no_doc_func)
 
     def test_tool_raises_error_runnable_without_object_schema(
-            self, mock_runnable):
+        self, mock_runnable
+    ):
         with pytest.raises(ValueError):
             tool(mock_runnable)
 
     # Decorator Behavior Tests
     @pytest.mark.asyncio
     async def test_async_tool_function(self):
-
         @tool
         async def async_func(arg: str) -> str:
             return arg
@@ -604,7 +597,6 @@ class TestTool:
         pass
 
     def test_tool_with_different_return_types(self):
-
         @tool
         def return_int(arg: str) -> int:
             return int(arg)
@@ -623,7 +615,6 @@ class TestTool:
 
     # Test with multiple arguments
     def test_tool_with_multiple_args(self):
-
         @tool
         def concat_strings(a: str, b: str) -> str:
             return a + b
@@ -633,7 +624,6 @@ class TestTool:
 
     # Test handling of optional arguments
     def test_tool_with_optional_args(self):
-
         @tool
         def greet(name: str, greeting: str = "Hello") -> str:
             return f"{greeting} {name}"
@@ -643,7 +633,6 @@ class TestTool:
 
     # Test with variadic arguments
     def test_tool_with_variadic_args(self):
-
         @tool
         def sum_numbers(*numbers: int) -> int:
             return sum(numbers)
@@ -653,7 +642,6 @@ class TestTool:
 
     # Test with keyword arguments
     def test_tool_with_kwargs(self):
-
         @tool
         def build_query(**kwargs) -> str:
             return "&".join(f"{k}={v}" for k, v in kwargs.items())
@@ -663,7 +651,6 @@ class TestTool:
 
     # Test with mixed types of arguments
     def test_tool_with_mixed_args(self):
-
         @tool
         def mixed_args(a: int, b: str, *args, **kwargs) -> str:
             return f"{a}{b}{len(args)}{'-'.join(kwargs.values())}"
@@ -672,7 +659,6 @@ class TestTool:
 
     # Test error handling with incorrect types
     def test_tool_error_with_incorrect_types(self):
-
         @tool
         def add_numbers(a: int, b: int) -> int:
             return a + b
@@ -682,7 +668,6 @@ class TestTool:
 
     # Test with nested tools
     def test_nested_tools(self):
-
         @tool
         def inner_tool(arg: str) -> str:
             return f"Inner {arg}"
@@ -694,7 +679,6 @@ class TestTool:
         assert outer_tool("Test") == "Outer Inner Test"
 
     def test_tool_with_global_variable(self):
-
         @tool
         def access_global(arg: str) -> str:
             return f"{global_var} {arg}"
@@ -717,7 +701,6 @@ class TestTool:
 
     # Test with complex data structures
     def test_tool_with_complex_data_structures(self):
-
         @tool
         def process_data(data: dict) -> list:
             return [data[key] for key in sorted(data.keys())]
@@ -727,7 +710,6 @@ class TestTool:
 
     # Test handling exceptions within the tool function
     def test_tool_handling_internal_exceptions(self):
-
         @tool
         def function_that_raises(arg: str):
             if arg == "error":
@@ -740,7 +722,6 @@ class TestTool:
 
     # Test with functions returning None
     def test_tool_with_none_return(self):
-
         @tool
         def return_none(arg: str):
             return None
@@ -754,9 +735,7 @@ class TestTool:
 
     # Test with class methods
     def test_tool_with_class_method(self):
-
         class MyClass:
-
             @tool
             def method(self, arg: str) -> str:
                 return f"Method {arg}"
@@ -766,15 +745,12 @@ class TestTool:
 
     # Test tool function with inheritance
     def test_tool_with_inheritance(self):
-
         class Parent:
-
             @tool
             def parent_method(self, arg: str) -> str:
                 return f"Parent {arg}"
 
         class Child(Parent):
-
             @tool
             def child_method(self, arg: str) -> str:
                 return f"Child {arg}"
@@ -785,9 +761,7 @@ class TestTool:
 
     # Test with decorators stacking
     def test_tool_with_multiple_decorators(self):
-
         def another_decorator(func):
-
             def wrapper(*args, **kwargs):
                 return f"Decorated {func(*args, **kwargs)}"
 
@@ -813,7 +787,9 @@ class TestTool:
         def thread_target():
             results.append(threaded_function(5))
 
-        threads = [threading.Thread(target=thread_target) for _ in range(10)]
+        threads = [
+            threading.Thread(target=thread_target) for _ in range(10)
+        ]
         for t in threads:
             t.start()
         for t in threads:
@@ -823,7 +799,6 @@ class TestTool:
 
     # Test with recursive functions
     def test_tool_with_recursive_function(self):
-
         @tool
         def recursive_function(n: int) -> int:
             if n == 0:

tests/utils/test_check_device.py

@@ -19,8 +19,9 @@ def test_check_device_no_cuda(monkeypatch):
 
 def test_check_device_cuda_exception(monkeypatch):
     # Mock torch.cuda.is_available to raise an exception
-    monkeypatch.setattr(torch.cuda, "is_available",
-                        lambda: 1 / 0)  # Raises ZeroDivisionError
+    monkeypatch.setattr(
+        torch.cuda, "is_available", lambda: 1 / 0
+    )  # Raises ZeroDivisionError
 
     result = check_device(log_level=logging.DEBUG)
     assert result.type == "cpu"
@@ -32,8 +33,12 @@ def test_check_device_one_cuda(monkeypatch):
     # Mock torch.cuda.device_count to return 1
     monkeypatch.setattr(torch.cuda, "device_count", lambda: 1)
     # Mock torch.cuda.memory_allocated and torch.cuda.memory_reserved to return 0
-    monkeypatch.setattr(torch.cuda, "memory_allocated", lambda device: 0)
-    monkeypatch.setattr(torch.cuda, "memory_reserved", lambda device: 0)
+    monkeypatch.setattr(
+        torch.cuda, "memory_allocated", lambda device: 0
+    )
+    monkeypatch.setattr(
+        torch.cuda, "memory_reserved", lambda device: 0
+    )
 
     result = check_device(log_level=logging.DEBUG)
     assert len(result) == 1
@@ -47,8 +52,12 @@ def test_check_device_multiple_cuda(monkeypatch):
     # Mock torch.cuda.device_count to return 4
     monkeypatch.setattr(torch.cuda, "device_count", lambda: 4)
     # Mock torch.cuda.memory_allocated and torch.cuda.memory_reserved to return 0
-    monkeypatch.setattr(torch.cuda, "memory_allocated", lambda device: 0)
-    monkeypatch.setattr(torch.cuda, "memory_reserved", lambda device: 0)
+    monkeypatch.setattr(
+        torch.cuda, "memory_allocated", lambda device: 0
+    )
+    monkeypatch.setattr(
+        torch.cuda, "memory_reserved", lambda device: 0
+    )
 
     result = check_device(log_level=logging.DEBUG)
     assert len(result) == 4

tests/utils/test_class_args_wrapper.py

@@ -19,7 +19,8 @@ def test_print_class_parameters_agent():
     # Replace with the expected output for Agent class
     expected_output = (
         "Parameter: name, Type: <class 'str'>\nParameter: age, Type:"
-        " <class 'int'>")
+        " <class 'int'>"
+    )
     assert output == expected_output
 
 
@@ -32,7 +33,9 @@ def test_print_class_parameters_error():
 def get_parameters(class_name: str):
     classes = {"Agent": Agent}
     if class_name in classes:
-        return print_class_parameters(classes[class_name], api_format=True)
+        return print_class_parameters(
+            classes[class_name], api_format=True
+        )
     else:
         return {"error": "Class not found"}
 

tests/utils/test_device.py

@@ -32,14 +32,18 @@ def test_multiple_gpus_available(mocker):
 def test_device_properties(mocker):
     mocker.patch("torch.cuda.is_available", return_value=True)
     mocker.patch("torch.cuda.device_count", return_value=1)
-    mocker.patch("torch.cuda.get_device_capability", return_value=(7, 5))
+    mocker.patch(
+        "torch.cuda.get_device_capability", return_value=(7, 5)
+    )
     mocker.patch(
         "torch.cuda.get_device_properties",
         return_value=MagicMock(total_memory=1000),
     )
     mocker.patch("torch.cuda.memory_allocated", return_value=200)
     mocker.patch("torch.cuda.memory_reserved", return_value=300)
-    mocker.patch("torch.cuda.get_device_name", return_value="Tesla K80")
+    mocker.patch(
+        "torch.cuda.get_device_name", return_value="Tesla K80"
+    )
     devices = check_device()
     assert len(devices) == 1
     assert str(devices[0]) == "cuda"
@@ -48,21 +52,27 @@ def test_device_properties(mocker):
 def test_memory_threshold(mocker):
     mocker.patch("torch.cuda.is_available", return_value=True)
     mocker.patch("torch.cuda.device_count", return_value=1)
-    mocker.patch("torch.cuda.get_device_capability", return_value=(7, 5))
+    mocker.patch(
+        "torch.cuda.get_device_capability", return_value=(7, 5)
+    )
     mocker.patch(
         "torch.cuda.get_device_properties",
         return_value=MagicMock(total_memory=1000),
     )
-    mocker.patch("torch.cuda.memory_allocated",
-                 return_value=900)  # 90% of total memory
+    mocker.patch(
+        "torch.cuda.memory_allocated", return_value=900
+    )  # 90% of total memory
     mocker.patch("torch.cuda.memory_reserved", return_value=300)
-    mocker.patch("torch.cuda.get_device_name", return_value="Tesla K80")
+    mocker.patch(
+        "torch.cuda.get_device_name", return_value="Tesla K80"
+    )
     with pytest.warns(
         UserWarning,
         match=r"Memory usage for device cuda exceeds threshold",
     ):
         devices = check_device(
-            memory_threshold=0.8)  # Set memory threshold to 80%
+            memory_threshold=0.8
+        )  # Set memory threshold to 80%
     assert len(devices) == 1
     assert str(devices[0]) == "cuda"
 
@@ -70,21 +80,27 @@ def test_memory_threshold(mocker):
 def test_compute_capability_threshold(mocker):
     mocker.patch("torch.cuda.is_available", return_value=True)
     mocker.patch("torch.cuda.device_count", return_value=1)
-    mocker.patch("torch.cuda.get_device_capability",
-                 return_value=(3, 0))  # Compute capability 3.0
+    mocker.patch(
+        "torch.cuda.get_device_capability", return_value=(3, 0)
+    )  # Compute capability 3.0
     mocker.patch(
         "torch.cuda.get_device_properties",
         return_value=MagicMock(total_memory=1000),
     )
     mocker.patch("torch.cuda.memory_allocated", return_value=200)
     mocker.patch("torch.cuda.memory_reserved", return_value=300)
-    mocker.patch("torch.cuda.get_device_name", return_value="Tesla K80")
+    mocker.patch(
+        "torch.cuda.get_device_name", return_value="Tesla K80"
+    )
     with pytest.warns(
         UserWarning,
-            match=(r"Compute capability for device cuda is below threshold"),
+        match=(
+            r"Compute capability for device cuda is below threshold"
+        ),
     ):
         devices = check_device(
-            capability_threshold=3.5)  # Set compute capability threshold to 3.5
+            capability_threshold=3.5
+        )  # Set compute capability threshold to 3.5
     assert len(devices) == 1
     assert str(devices[0]) == "cuda"
 

tests/utils/test_display_markdown_message.py

@@ -14,7 +14,8 @@ def test_basic_message():
     with mock.patch.object(Console, "print") as mock_print:
         display_markdown_message("This is a test")
         mock_print.assert_called_once_with(
-            Markdown("This is a test", style="cyan"))
+            Markdown("This is a test", style="cyan")
+        )
 
 
 def test_empty_message():
@@ -30,7 +31,8 @@ def test_colors(color):
     with mock.patch.object(Console, "print") as mock_print:
         display_markdown_message("This is a test", color)
         mock_print.assert_called_once_with(
-            Markdown("This is a test", style=color))
+            Markdown("This is a test", style=color)
+        )
 
 
 def test_dash_line():

tests/utils/test_extract_code_from_markdown.py

@@ -22,8 +22,12 @@ def markdown_content_without_code():
     """
 
 
-def test_extract_code_from_markdown_with_code(markdown_content_with_code,):
-    extracted_code = extract_code_from_markdown(markdown_content_with_code)
+def test_extract_code_from_markdown_with_code(
+    markdown_content_with_code,
+):
+    extracted_code = extract_code_from_markdown(
+        markdown_content_with_code
+    )
     assert "def my_func():" in extracted_code
     assert 'print("This is my function.")' in extracted_code
     assert "class MyClass:" in extracted_code
@@ -31,8 +35,11 @@ def test_extract_code_from_markdown_with_code(markdown_content_with_code,):
 
 
 def test_extract_code_from_markdown_without_code(
-    markdown_content_without_code,):
-    extracted_code = extract_code_from_markdown(markdown_content_without_code)
+    markdown_content_without_code,
+):
+    extracted_code = extract_code_from_markdown(
+        markdown_content_without_code
+    )
     assert extracted_code == ""
 
 

tests/utils/test_find_image_path.py

@@ -8,8 +8,12 @@ from swarms.utils import find_image_path
 
 
 def test_find_image_path_no_images():
-    assert (find_image_path("This is a test string without any image paths.")
-            is None)
+    assert (
+        find_image_path(
+            "This is a test string without any image paths."
+        )
+        is None
+    )
 
 
 def test_find_image_path_one_image():
@@ -19,7 +23,9 @@ def test_find_image_path_one_image():
 
 def test_find_image_path_multiple_images():
     text = "This string has two image paths: img1.png, and img2.jpg."
-    assert (find_image_path(text) == "img2.jpg")  # Assuming both images exist
+    assert (
+        find_image_path(text) == "img2.jpg"
+    )  # Assuming both images exist
 
 
 def test_find_image_path_wrong_input():

tests/utils/test_limit_tokens_from_string.py

@@ -4,11 +4,14 @@ from swarms.utils import limit_tokens_from_string
 
 
 def test_limit_tokens_from_string():
-    sentence = ("This is a test sentence. It is used for testing the number"
-                " of tokens.")
+    sentence = (
+        "This is a test sentence. It is used for testing the number"
+        " of tokens."
+    )
     limited = limit_tokens_from_string(sentence, limit=5)
-    assert (len(limited.split())
-            <= 5), "The output string has more than 5 tokens."
+    assert (
+        len(limited.split()) <= 5
+    ), "The output string has more than 5 tokens."
 
 
 def test_limit_zero_tokens():
@@ -18,21 +21,26 @@ def test_limit_zero_tokens():
 
 
 def test_negative_token_limit():
-    sentence = ("This test will raise an exception when limit is negative.")
+    sentence = (
+        "This test will raise an exception when limit is negative."
+    )
     with pytest.raises(Exception):
         limit_tokens_from_string(sentence, limit=-1)
 
 
-@pytest.mark.parametrize("sentence, model",
-                         [("Some sentence", "unavailable-model")])
+@pytest.mark.parametrize(
+    "sentence, model", [("Some sentence", "unavailable-model")]
+)
 def test_unknown_model(sentence, model):
     with pytest.raises(Exception):
         limit_tokens_from_string(sentence, model=model)
 
 
 def test_string_token_limit_exceeded():
-    sentence = ("This is a long sentence with more than twenty tokens which"
+    sentence = (
+        "This is a long sentence with more than twenty tokens which"
         " is used for testing. It checks whether the function"
-                " correctly limits the tokens to a specified amount.")
+        " correctly limits the tokens to a specified amount."
+    )
     limited = limit_tokens_from_string(sentence, limit=20)
     assert len(limited.split()) <= 20, "The token limit is exceeded."

tests/utils/test_load_model_torch.py

@@ -6,7 +6,6 @@ from swarms.utils import load_model_torch
 
 
 class DummyModel(nn.Module):
-
     def __init__(self):
         super().__init__()
         self.fc = nn.Linear(10, 2)
@@ -26,7 +25,9 @@ def test_load_model_torch_success(tmp_path):
     model_loaded = load_model_torch(model_path, model=DummyModel())
 
     # Check if loaded model has the same architecture
-    assert isinstance(model_loaded, DummyModel), "Loaded model type mismatch."
+    assert isinstance(
+        model_loaded, DummyModel
+    ), "Loaded model type mismatch."
 
 
 # Test case 2: Test if function raises FileNotFoundError for non-existent file
@@ -65,11 +66,12 @@ def test_load_model_torch_device_handling(tmp_path):
 
     # Define a device other than default and load the model to the specified device
     device = torch.device("cpu")
-    model_loaded = load_model_torch(model_path,
-                                    model=DummyModel(),
-                                    device=device)
+    model_loaded = load_model_torch(
+        model_path, model=DummyModel(), device=device
+    )
 
-    assert (model_loaded.fc.weight.device == device
+    assert (
+        model_loaded.fc.weight.device == device
     ), "Model not loaded to specified device."
 
 
@@ -80,14 +82,15 @@ def test_load_model_torch_args_kwargs_handling(monkeypatch, tmp_path):
     torch.save(model.state_dict(), model_path)
 
     def mock_torch_load(*args, **kwargs):
-        assert ("pickle_module"
-                in kwargs), "Keyword arguments not passed to 'torch.load'."
+        assert (
+            "pickle_module" in kwargs
+        ), "Keyword arguments not passed to 'torch.load'."
 
     # Monkeypatch 'torch.load' to check if '*args' and '**kwargs' are passed correctly
     monkeypatch.setattr(torch, "load", mock_torch_load)
-    load_model_torch(model_path,
-                     model=DummyModel(),
-                     pickle_module="dummy_module")
+    load_model_torch(
+        model_path, model=DummyModel(), pickle_module="dummy_module"
+    )
 
 
 # Test case 7: Test for model loading on CPU if no GPU is available
@@ -100,8 +103,9 @@ def test_load_model_torch_cpu(tmp_path):
         return False
 
     # Monkeypatch to simulate no GPU available
-    pytest.MonkeyPatch.setattr(torch.cuda, "is_available",
-                               mock_torch_cuda_is_available)
+    pytest.MonkeyPatch.setattr(
+        torch.cuda, "is_available", mock_torch_cuda_is_available
+    )
     model_loaded = load_model_torch(model_path, model=DummyModel())
 
     # Ensure model is loaded on CPU

tests/utils/test_load_models_torch.py

@@ -42,13 +42,15 @@ def test_load_model_torch_model_specified(mocker):
     mock_model = MagicMock(spec=torch.nn.Module)
     mocker.patch("torch.load", return_value={"key": "value"})
     load_model_torch("model_path", model=mock_model)
-    mock_model.load_state_dict.assert_called_once_with({"key": "value"},
-                                                       strict=True)
+    mock_model.load_state_dict.assert_called_once_with(
+        {"key": "value"}, strict=True
+    )
 
 
 def test_load_model_torch_model_specified_strict_false(mocker):
     mock_model = MagicMock(spec=torch.nn.Module)
     mocker.patch("torch.load", return_value={"key": "value"})
     load_model_torch("model_path", model=mock_model, strict=False)
-    mock_model.load_state_dict.assert_called_once_with({"key": "value"},
-                                                       strict=False)
+    mock_model.load_state_dict.assert_called_once_with(
+        {"key": "value"}, strict=False
+    )

tests/utils/test_math_eval.py

@@ -18,7 +18,6 @@ def func2_with_exception(x):
 
 
 def test_same_results_no_exception(caplog):
-
     @math_eval(func1_no_exception, func2_no_exception)
     def test_func(x):
         return x
@@ -29,7 +28,6 @@ def test_same_results_no_exception(caplog):
 
 
 def test_func1_exception(caplog):
-
     @math_eval(func1_with_exception, func2_no_exception)
     def test_func(x):
         return x

tests/utils/test_metrics_decorator.py

@@ -10,7 +10,6 @@ from swarms.utils import metrics_decorator
 
 # Basic successful test
 def test_metrics_decorator_success():
-
     @metrics_decorator
     def decorated_func():
         time.sleep(0.1)
@@ -31,8 +30,8 @@ def test_metrics_decorator_success():
     ],
 )
 def test_metrics_decorator_with_various_wait_times_and_return_vals(
-        wait_time, return_val):
-
+    wait_time, return_val
+):
     @metrics_decorator
     def decorated_func():
         time.sleep(wait_time)
@@ -56,17 +55,19 @@ def test_metrics_decorator_with_mocked_time(mocker):
         return ["tok_1", "tok_2"]
 
     metrics = decorated_func()
-    assert (metrics == """
+    assert (
+        metrics
+        == """
     Time to First Token: 5
     Generation Latency: 20
     Throughput: 0.1
-    """)
+    """
+    )
     mocked_time.assert_any_call()
 
 
 # Test to ensure that exceptions in the decorated function are propagated
 def test_metrics_decorator_raises_exception():
-
     @metrics_decorator
     def decorated_func():
         raise ValueError("Oops!")
@@ -77,7 +78,6 @@ def test_metrics_decorator_raises_exception():
 
 # Test to ensure proper handling when decorated function returns non-list value
 def test_metrics_decorator_with_non_list_return_val():
-
     @metrics_decorator
     def decorated_func():
         return "Hello, world!"

tests/utils/test_prep_torch_inference.py

@@ -9,13 +9,16 @@ from swarms.utils import prep_torch_inference
 
 def test_prep_torch_inference():
     model_path = "model_path"
-    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    device = torch.device(
+        "cuda" if torch.cuda.is_available() else "cpu"
+    )
     model_mock = Mock()
     model_mock.eval = Mock()
 
     # Mocking the load_model_torch function to return our mock model.
-    with unittest.mock.patch("swarms.utils.load_model_torch",
-                             return_value=model_mock) as _:
+    with unittest.mock.patch(
+        "swarms.utils.load_model_torch", return_value=model_mock
+    ) as _:
         model = prep_torch_inference(model_path, device)
 
     # Check if model was properly loaded and eval function was called

tests/utils/test_prep_torch_model_inference.py

@@ -3,7 +3,8 @@ from unittest.mock import MagicMock
 import torch
 
 from swarms.utils.prep_torch_model_inference import (
-    prep_torch_inference,)
+    prep_torch_inference,
+)
 
 
 def test_prep_torch_inference_no_model_path():

tests/utils/test_print_class_parameters.py

@@ -4,30 +4,27 @@ from swarms.utils import print_class_parameters
 
 
 class TestObject:
-
     def __init__(self, value1, value2: int):
         pass
 
 
 class TestObject2:
-
     def __init__(self: "TestObject2", value1, value2: int = 5):
         pass
 
 
 def test_class_with_complex_parameters():
-
     class ComplexArgs:
-
         def __init__(self, value1: list, value2: dict = {}):
             pass
 
     output = {"value1": "<class 'list'>", "value2": "<class 'dict'>"}
-    assert (print_class_parameters(ComplexArgs, api_format=True) == output)
+    assert (
+        print_class_parameters(ComplexArgs, api_format=True) == output
+    )
 
 
 def test_empty_class():
-
     class Empty:
         pass
 
@@ -36,9 +33,7 @@ def test_empty_class():
 
 
 def test_class_with_no_annotations():
-
     class NoAnnotations:
-
         def __init__(self, value1, value2):
             pass
 
@@ -46,13 +41,14 @@ def test_class_with_no_annotations():
         "value1": "<class 'inspect._empty'>",
         "value2": "<class 'inspect._empty'>",
     }
-    assert (print_class_parameters(NoAnnotations, api_format=True) == output)
+    assert (
+        print_class_parameters(NoAnnotations, api_format=True)
+        == output
+    )
 
 
 def test_class_with_partial_annotations():
-
     class PartialAnnotations:
-
         def __init__(self, value1, value2: int):
             pass
 
@@ -60,8 +56,10 @@ def test_class_with_partial_annotations():
         "value1": "<class 'inspect._empty'>",
         "value2": "<class 'int'>",
     }
-    assert (print_class_parameters(PartialAnnotations,
-                                   api_format=True) == output)
+    assert (
+        print_class_parameters(PartialAnnotations, api_format=True)
+        == output
+    )
 
 
 @pytest.mark.parametrize(