[serving] fix schema parameters naming (#429)

Author: wongzhenhao

dataflow/serving/api_google_vertexai_serving.py

@@ -312,7 +312,7 @@ def generate_from_input(
         self, 
         user_inputs: List[str], 
         system_prompt: str = "", 
-        response_schema: Optional[Union[type[BaseModel], dict]] = None,
+        json_schema: Optional[Union[type[BaseModel], dict]] = None,
         use_function_call: Optional[bool] = None,
         use_batch: Optional[bool] = None,
         batch_wait: Optional[bool] = None,
@@ -326,7 +326,7 @@ def generate_from_input(
         Args:
             user_inputs: List of user input strings to process.
             system_prompt: System prompt for the model.
-            response_schema: Optional Pydantic BaseModel or dict for structured output.
+            json_schema: Optional Pydantic BaseModel or dict for structured output.
             use_batch: If True, use batch processing via BigQuery. If False, use parallel real-time generation.
             batch_wait: If True (and use_batch=True), wait for batch job to complete and return results.
                         If False, return the batch job name immediately for later retrieval.
@@ -357,7 +357,7 @@ def generate_from_input(
             return self._generate_with_batch(
                 user_inputs=user_inputs,
                 system_prompt=system_prompt,
-                response_schema=response_schema,
+                response_schema=json_schema,
                 use_function_call=use_function_call,
                 wait_for_completion=batch_wait,
                 dataset_name=batch_dataset,
@@ -368,7 +368,7 @@ def generate_from_input(
             return self._generate_with_parallel(
                 user_inputs=user_inputs,
                 system_prompt=system_prompt,
-                response_schema=response_schema,
+                response_schema=json_schema,
                 use_function_call=use_function_call,
             )
 
@@ -947,7 +947,7 @@ class UserDetails(BaseModel):
             "John Doe is 30 years old and lives in New York.",
             "My name is Jane Smith, I am 25, and I reside in London."
         ]
-        results_json = gemini_server_json.generate_from_input(user_prompts_json, system_prompt_json, response_schema=UserDetails) # Pass the schema here
+        results_json = gemini_server_json.generate_from_input(user_prompts_json, system_prompt_json, json_schema=UserDetails) # Pass the schema here
         print("--- Generation Complete ---")
         for i, (prompt, result) in enumerate(zip(user_prompts_json, results_json)):
             print(f"\n[Prompt {i+1}]: {prompt}")
@@ -975,7 +975,7 @@ class UserDetails(BaseModel):
             "Alice Johnson is 28 years old and lives in San Francisco.",
             "Bob Brown, aged 35, resides in Toronto."
         ]
-        results_json_schema = gemini_server_json_schema.generate_from_input(user_prompts_json_schema, system_prompt_json_schema, response_schema=json_schema)
+        results_json_schema = gemini_server_json_schema.generate_from_input(user_prompts_json_schema, system_prompt_json_schema, json_schema=json_schema)
         print("--- Generation Complete ---")
         for i, (prompt, result) in enumerate(zip(user_prompts_json_schema, results_json_schema)):
             print(f"\n[Prompt {i+1}]: {prompt}")
@@ -1007,7 +1007,7 @@ class Capital(BaseModel):
             batch_job_name = gemini_server_batch.generate_from_input(
                 user_inputs=user_prompts_batch,
                 system_prompt=system_prompt_batch,
-                response_schema=Capital,
+                json_schema=Capital,
                 use_batch=True,
                 batch_wait=False  # Don't wait for completion
             )
@@ -1027,7 +1027,7 @@ class Capital(BaseModel):
             results_batch = gemini_server_batch.generate_from_input(
                 user_inputs=user_prompts_batch,
                 system_prompt=system_prompt_batch,
-                response_schema=Capital,
+                json_schema=Capital,
                 use_batch=True,
                 batch_wait=True  # Wait for completion
             )