fix: lint issues

.flake8

@@ -1,4 +1,4 @@
 [flake8]
 max-line-length = 88
-exclude = .git,.github,.chglog,__pycache__,docs,venv
+exclude = .git,.github,.chglog,__pycache__,docs,venv,env,mypy_cache
 max-complexity = 10

examples/agents/adk_gemini_agent_javelin/__init__.py

@@ -1 +0,0 @@
-from .agent import root_agent

examples/agents/adk_gemini_agent_javelin/agent.py

@@ -69,9 +69,10 @@
 # Coordinator agent
 root_agent = SequentialAgent(
     name="GeminiMultiAgentCoordinator",
-    sub_agents=[research_agent, summary_agent, report_agent]
+    sub_agents=[research_agent, summary_agent, report_agent],
 )
 
+
 async def main():
     session_service = InMemorySessionService()
     session_service.create_session("gemini_multi_agent_app", "user", "sess")
@@ -93,5 +94,6 @@ async def main():
 
     print("\n--- Final Report ---\n", final_answer)
 
+
 if __name__ == "__main__":
     asyncio.run(main())

examples/agents/adk_openai_agent_javelin/__init__.py

@@ -1 +0,0 @@
-from .agent import root_agent

examples/agents/adk_openai_agent_javelin/agent.py

@@ -69,7 +69,7 @@
 # Coordinator agent running all three sequentially
 coordinator = SequentialAgent(
     name="OpenAI_MultiAgentCoordinator",
-    sub_agents=[research_agent, summary_agent, report_agent]
+    sub_agents=[research_agent, summary_agent, report_agent],
 )
 root_agent = coordinator
 
@@ -96,5 +96,6 @@ async def main():
 
     print("\n--- Final Report ---\n", final_answer)
 
+
 if __name__ == "__main__":
-    asyncio.run(main())
+    asyncio.run(main())

examples/agents/openai_agents_javelin.py

@@ -27,17 +27,19 @@
 javelin_base_url = os.getenv("JAVELIN_BASE_URL", "")
 
 if not (openai_api_key and javelin_api_key and javelin_base_url):
-    raise ValueError("Missing OPENAI_API_KEY, JAVELIN_API_KEY, or JAVELIN_BASE_URL in .env")
+    raise ValueError(
+        "Missing OPENAI_API_KEY, JAVELIN_API_KEY, or JAVELIN_BASE_URL in .env"
+    )
 
 # Create async OpenAI client
 async_openai_client = AsyncOpenAI(api_key=openai_api_key)
 
 # Register with Javelin
-javelin_client = JavelinClient(JavelinConfig(
-    javelin_api_key=javelin_api_key,
-    base_url=javelin_base_url
-))
-javelin_client.register_openai(async_openai_client, route_name="openai_univ")  # Adjust route name if needed
+javelin_client = JavelinClient(
+    JavelinConfig(javelin_api_key=javelin_api_key, base_url=javelin_base_url)
+)
+# Adjust route name if needed
+javelin_client.register_openai(async_openai_client, route_name="openai_univ")
 
 # Let the Agents SDK use this Javelin-patched client globally
 set_default_openai_client(async_openai_client)
@@ -59,7 +61,7 @@
 ##############################################################################
 translator_agent = Agent(
     name="TranslatorAgent",
-    instructions="Translate any English text into Spanish. Keep it concise."
+    instructions="Translate any English text into Spanish. Keep it concise.",
 )
 
 ##############################################################################
@@ -78,18 +80,20 @@
     tools=[
         faux_search_agent.as_tool(
             tool_name="summarize_topic",
-            tool_description="Produce a concise internal summary of the user’s topic."
+            tool_description="Produce a concise internal summary of the user’s topic.",
         ),
         translator_agent.as_tool(
             tool_name="translate_to_spanish",
-            tool_description="Translate text into Spanish."
+            tool_description="Translate text into Spanish.",
         ),
     ],
 )
 
 ##############################################################################
 # 5) Demo Usage
 ##############################################################################
+
+
 async def main():
     user_query = "Why is pollution increasing ?"
     print(f"\n=== User Query: {user_query} ===\n")
@@ -98,5 +102,6 @@ async def main():
     print("=== Final Output ===\n")
     print(final_result.final_output)
 
+
 if __name__ == "__main__":
     asyncio.run(main())

examples/anthropic/anthropic_api_function_calling.py

@@ -16,10 +16,10 @@
 # Headers
 headers = {
     "Content-Type": "application/json",
-    "x-javelin-route": "anthropic_univ", # add your universal route
-    "x-javelin-model": "claude-3-5-sonnet-20240620", # add any supported model
+    "x-javelin-route": "anthropic_univ",  # add your universal route
+    "x-javelin-model": "claude-3-5-sonnet-20240620",  # add any supported model
     "x-javelin-provider": "https://api.anthropic.com/v1",
-    "x-api-key": os.getenv("ANTHROPIC_API_KEY"), 
+    "x-api-key": os.getenv("ANTHROPIC_API_KEY"),
     "anthropic-version": "2023-06-01",
 }
 client.set_headers(headers)
@@ -44,7 +44,9 @@
 messages = [
     {
         "role": "user",
-        "content": [{"type": "text", "text": "What's the weather like in Mumbai in celsius?"}],
+        "content": [
+            {"type": "text", "text": "What's the weather like in Mumbai in celsius?"}
+        ],
     }
 ]
 

examples/anthropic/anthropic_function_call.py

@@ -6,6 +6,7 @@
 
 # Load environment variables
 from dotenv import load_dotenv
+
 load_dotenv()
 
 # Javelin Setup
@@ -25,7 +26,10 @@
 
 # Messages and dummy tool call (check if tool support throws any error)
 messages = [
-    {"role": "user", "content": "Please call the tool to fetch today's weather in Paris."}
+    {
+        "role": "user",
+        "content": "Please call the tool to fetch today's weather in Paris.",
+    }
 ]
 
 tools = [
@@ -37,11 +41,12 @@
             "properties": {
                 "city": {"type": "string", "description": "Name of the city"},
             },
-            "required": ["city"]
-        }
+            "required": ["city"],
+        },
     }
 ]
 
+
 async def run_anthropic_test():
     print("\n==== Testing Anthropic Function Calling Support via Javelin ====")
     try:
@@ -64,5 +69,6 @@ async def run_anthropic_test():
     except Exception as e:
         print(f"Function/tool call failed for Anthropic: {str(e)}")
 
+
 if __name__ == "__main__":
     asyncio.run(run_anthropic_test())

examples/anthropic/javelin_anthropic_api_call.py

@@ -7,10 +7,13 @@
 load_dotenv()
 
 # Helper for pretty print
+
+
 def print_response(provider: str, response: Dict[str, Any]) -> None:
     print(f"=== Response from {provider} ===")
     print(json.dumps(response, indent=2))
 
+
 # Javelin client config
 config = JavelinConfig(
     base_url=os.getenv("JAVELIN_BASE_URL"),
@@ -40,7 +43,7 @@ def print_response(provider: str, response: Dict[str, Any]) -> None:
     "messages": [
         {
             "role": "user",
-            "content": [{"type": "text", "text": "What are the three primary colors?"}]
+            "content": [{"type": "text", "text": "What are the three primary colors?"}],
         }
     ],
 }

examples/azure-openai/azure-universal.py

@@ -30,9 +30,7 @@ def initialize_client():
         print("AZURE_OPENAI_API_KEY found.")
 
     # Create the Azure client
-    azure_client = AzureOpenAI(
-        api_version="2023-09-15-preview"
-    )
+    azure_client = AzureOpenAI(api_version="2023-09-15-preview")
 
     # Initialize the Javelin client and register the Azure client
     config = JavelinConfig(javelin_api_key=javelin_api_key)
@@ -113,10 +111,14 @@ def main():
         print("Client initialization failed.")
         return
 
-    # Example chat messages
-    messages = [{"role": "user", "content": "say hello"}]
+    run_chat_completion_sync(azure_client)
+    run_chat_completion_stream(azure_client)
+    run_embeddings(azure_client)
+    print("\nScript complete.")
 
-    # 1) Chat Completion (Synchronous)
+
+def run_chat_completion_sync(azure_client):
+    messages = [{"role": "user", "content": "say hello"}]
     try:
         print("\n--- Chat Completion (Non-Streaming) ---")
         response_chat_sync = get_chat_completion_sync(azure_client, messages)
@@ -127,7 +129,9 @@ def main():
     except Exception as e:
         print("Error in chat completion (sync):", e)
 
-    # 2) Chat Completion (Streaming)
+
+def run_chat_completion_stream(azure_client):
+    messages = [{"role": "user", "content": "say hello"}]
     try:
         print("\n--- Chat Completion (Streaming) ---")
         response_streamed = get_chat_completion_stream(azure_client, messages)
@@ -138,7 +142,8 @@ def main():
     except Exception as e:
         print("Error in chat completion (streaming):", e)
 
-    # 3) Embeddings
+
+def run_embeddings(azure_client):
     try:
         print("\n--- Embeddings ---")
         embed_text = "Sample text to embed."
@@ -150,8 +155,6 @@ def main():
     except Exception as e:
         print("Error in embeddings:", e)
 
-    print("\nScript complete.")
-
 
 if __name__ == "__main__":
     main()

examples/azure-openai/azure_function_call.py

@@ -1,12 +1,12 @@
 #!/usr/bin/env python
 import os
-import json
 from dotenv import load_dotenv
 from openai import AzureOpenAI
 from javelin_sdk import JavelinClient, JavelinConfig
 
 load_dotenv()
 
+
 def init_azure_client_with_javelin():
     azure_api_key = os.getenv("AZURE_OPENAI_API_KEY")
     javelin_api_key = os.getenv("JAVELIN_API_KEY")
@@ -18,7 +18,7 @@ def init_azure_client_with_javelin():
     azure_client = AzureOpenAI(
         api_version="2023-07-01-preview",
         azure_endpoint="https://javelinpreview.openai.azure.com",
-        api_key=azure_api_key
+        api_key=azure_api_key,
     )
 
     # Register with Javelin
@@ -28,6 +28,7 @@ def init_azure_client_with_javelin():
 
     return azure_client
 
+
 def run_function_call_test(azure_client):
     print("\n==== Azure OpenAI Function Calling via Javelin ====")
 
@@ -46,20 +47,21 @@ def run_function_call_test(azure_client):
                             "unit": {
                                 "type": "string",
                                 "enum": ["celsius", "fahrenheit"],
-                                "description": "Temperature unit"
-                            }
+                                "description": "Temperature unit",
+                            },
                         },
-                        "required": ["city"]
-                    }
+                        "required": ["city"],
+                    },
                 }
             ],
-            function_call="auto"
+            function_call="auto",
         )
         print("Function Call Output:")
         print(response.to_json(indent=2))
     except Exception as e:
         print("Azure Function Calling Error:", e)
 
+
 def run_tool_call_test(azure_client):
     print("\n==== Azure OpenAI Tool Calling via Javelin ====")
 
@@ -76,24 +78,29 @@ def run_tool_call_test(azure_client):
                         "parameters": {
                             "type": "object",
                             "properties": {
-                                "category": {"type": "string", "description": "e.g. success, life"}
+                                "category": {
+                                    "type": "string",
+                                    "description": "e.g. success, life",
+                                }
                             },
-                            "required": []
-                        }
-                    }
+                            "required": [],
+                        },
+                    },
                 }
             ],
-            tool_choice="auto"
+            tool_choice="auto",
         )
         print("Tool Call Output:")
         print(response.to_json(indent=2))
     except Exception as e:
         print("Azure Tool Calling Error:", e)
 
+
 def main():
     client = init_azure_client_with_javelin()
     run_function_call_test(client)
     run_tool_call_test(client)
 
+
 if __name__ == "__main__":
     main()