fix: pyright types for responses_tool_calling (dotenv, input, tools)

Co-authored-by: Cursor <cursoragent@cursor.com>

Author: rushitat

examples/responses_tool_calling.py

@@ -9,15 +9,21 @@
 """
 
 import os
-from typing import Any, Dict, List
+from typing import List, cast
 
 from gradient import Gradient, ResponsesModels
+from gradient.types.responses import (
+    ResponseInputFunctionCall,
+    ResponseInputFunctionCallOutput,
+    ResponseInputItem,
+    ResponseTool,
+)
 from gradient.types.responses.response_create_response import ResponseOutputFunctionCall
 
 
 def _load_dotenv() -> None:
     try:
-        from dotenv import load_dotenv
+        from dotenv import load_dotenv  # type: ignore[reportMissingImports]
 
         load_dotenv()
     except ImportError:
@@ -33,7 +39,7 @@ def _load_dotenv() -> None:
 client = Gradient(model_access_key=MODEL_ACCESS_KEY)
 
 # One function tool: get_weather
-get_weather_tool = {
+get_weather_tool: ResponseTool = {
     "type": "function",
     "function": {
         "name": "get_weather",
@@ -50,9 +56,10 @@ def _load_dotenv() -> None:
 }
 
 # Initial conversation: single user message
-input_messages: List[Dict[str, Any]] = [
-    {"type": "message", "role": "user", "content": "What's the weather in New York?"},
-]
+input_messages: List[ResponseInputItem] = cast(
+    List[ResponseInputItem],
+    [{"type": "message", "role": "user", "content": "What's the weather in New York?"}],
+)
 
 # First call: model may return a function_call
 response = client.responses.create(
@@ -65,18 +72,23 @@ def _load_dotenv() -> None:
 # If the model returned a function call, append it and the tool result, then call again
 for item in response.output:
     if isinstance(item, ResponseOutputFunctionCall):
-        input_messages.append({
-            "type": "function_call",
-            "id": item.id,
-            "name": item.name,
-            "arguments": item.arguments,
-        })
+        input_messages.append(
+            cast(
+                ResponseInputFunctionCall,
+                {"type": "function_call", "id": item.id, "name": item.name, "arguments": item.arguments},
+            )
+        )
         # Simulated tool result (in a real app you would call your function here)
-        input_messages.append({
-            "type": "function_call_output",
-            "call_id": item.id,
-            "output": '{"temperature": 22, "unit": "celsius", "conditions": "sunny"}',
-        })
+        input_messages.append(
+            cast(
+                ResponseInputFunctionCallOutput,
+                {
+                    "type": "function_call_output",
+                    "call_id": item.id,
+                    "output": '{"temperature": 22, "unit": "celsius", "conditions": "sunny"}',
+                },
+            )
+        )
         response = client.responses.create(
             model=ResponsesModels.GPT_5_1_CODEX_MAX,
             input=input_messages,