Fixed response schema for vllm

flo_ai/examples/output_formatter.py

@@ -96,7 +96,7 @@ async def main():
             {'role': 'user', 'content': 'Solve 8x + 7 = -23'},
         ],
         output_schema={
-            'name': 'math_reasoning',
+            'title': 'math_reasoning',
             'schema': {
                 'type': 'object',
                 'properties': {
@@ -136,15 +136,18 @@ async def agent_example():
 
     # Define output schema
     math_schema = {
-        'type': 'object',
-        'properties': {
-            'solution': {
-                'type': 'string',
-                'description': 'The step-by-step solution to the math problem',
+        'title': 'math_tutor',
+        'schema': {
+            'type': 'object',
+            'properties': {
+                'solution': {
+                    'type': 'string',
+                    'description': 'The step-by-step solution to the math problem',
+                },
+                'answer': {'type': 'string', 'description': 'The final answer'},
             },
-            'answer': {'type': 'string', 'description': 'The final answer'},
+            'required': ['solution', 'answer'],
         },
-        'required': ['solution', 'answer'],
     }
 
     # Create OpenAI agent

flo_ai/examples/vllm_agent_usage.py

@@ -10,6 +10,8 @@
 
 vllm_base_url = os.getenv('VLLM_BASE_URL')
 
+vllm_model = 'microsoft/phi-4'
+
 
 async def example_simple_vllm_agent():
     # Create a simple conversational agent with vLLM
@@ -19,7 +21,7 @@ async def example_simple_vllm_agent():
         .with_prompt('You are a helpful math tutor.')
         .with_llm(
             OpenAIVLLM(
-                model='microsoft/phi-4',
+                model=vllm_model,
                 base_url=vllm_base_url,
                 temperature=0.7,
                 api_key='',
@@ -68,7 +70,7 @@ async def calculate(operation: str, x: float, y: float) -> float:
         )
         .with_llm(
             OpenAIVLLM(
-                model='microsoft/phi-4',
+                model=vllm_model,
                 base_url=vllm_base_url,
                 temperature=0.7,
                 api_key='',
@@ -89,7 +91,7 @@ async def calculate(operation: str, x: float, y: float) -> float:
 async def example_vllm_structured_output():
     # Define output schema for structured responses with name field
     math_schema = {
-        'name': 'math_solution',
+        'title': 'math_solution',
         'schema': {
             'type': 'object',
             'properties': {
@@ -122,7 +124,7 @@ async def example_vllm_structured_output():
         )
         .with_llm(
             OpenAIVLLM(
-                model='microsoft/phi-4',
+                model=vllm_model,
                 base_url=vllm_base_url,
                 temperature=0.3,
                 api_key='',
@@ -165,7 +167,7 @@ async def calculate(operation: str, x: float, y: float) -> float:
 
     # Define structured output schema for calculation results
     calculation_report_schema = {
-        'name': 'calculation_report',
+        'title': 'calculation_report',
         'schema': {
             'type': 'object',
             'properties': {
@@ -217,7 +219,7 @@ async def calculate(operation: str, x: float, y: float) -> float:
         )
         .with_llm(
             OpenAIVLLM(
-                model='microsoft/phi-4',
+                model=vllm_model,
                 base_url=vllm_base_url,
                 temperature=0.3,
                 api_key='',

flo_ai/flo_ai/__init__.py

@@ -8,7 +8,7 @@
 from .builder.agent_builder import AgentBuilder
 
 # LLM package - Language model integrations
-from .llm import BaseLLM, Anthropic, OpenAI, OllamaLLM, Gemini, ImageMessage
+from .llm import BaseLLM, Anthropic, OpenAI, OllamaLLM, Gemini, OpenAIVLLM, ImageMessage
 
 # Tool package - Tool framework components
 from .tool import Tool, ToolExecutionError, flo_tool, create_tool_from_function
@@ -43,6 +43,7 @@
     'OpenAI',
     'OllamaLLM',
     'Gemini',
+    'OpenAIVLLM',
     # LLM DataClass
     'ImageMessage',
     # Tools

flo_ai/flo_ai/llm/openai_llm.py

@@ -28,11 +28,11 @@ async def generate(
             kwargs['response_format'] = {'type': 'json_object'}
             kwargs['functions'] = [
                 {
-                    'name': output_schema.get('name', 'default'),
+                    'name': output_schema.get('title', 'default'),
                     'parameters': output_schema.get('schema', output_schema),
                 }
             ]
-            kwargs['function_call'] = {'name': output_schema.get('name', 'default')}
+            kwargs['function_call'] = {'name': output_schema.get('title', 'default')}
 
             # Add JSON format instruction to the system prompt
             if messages and messages[0]['role'] == 'system':

flo_ai/flo_ai/llm/openai_vllm.py

@@ -25,7 +25,13 @@ async def generate(
     ) -> Any:
         # Convert output_schema to OpenAI format if provided
         if output_schema:
-            kwargs['extra_body'] = {'guided_json': output_schema.get('schema')}
+            kwargs['response_format'] = {
+                'type': 'json_schema',
+                'json_schema': {
+                    'name': output_schema.get('title', 'default'),
+                    'schema': output_schema.get('schema', output_schema),
+                },
+            }
 
             # Add JSON format instruction to the system prompt
             if messages and messages[0]['role'] == 'system':