Fixed up requested changes by renaming the name of the mode and chang…

…ing the parsing of the code itself

docs/index.md

@@ -62,7 +62,7 @@ Now, let's see Instructor in action with a simple example:
     from instructor import from_openai, Mode
     from pydantic import BaseModel
 
-    client = from_openai(OpenAI(), mode=Mode.STRUCTURED_OUTPUTS)
+    client = from_openai(OpenAI(), mode=Mode.TOOLS_STRICT)
 
 
     class User(BaseModel):

instructor/client.py

@@ -425,7 +425,7 @@ def from_openai(
             instructor.Mode.FUNCTIONS,
             instructor.Mode.PARALLEL_TOOLS,
             instructor.Mode.MD_JSON,
-            instructor.Mode.STRUCTURED_OUTPUTS,
+            instructor.Mode.TOOLS_STRICT,
         }
 
     if isinstance(client, openai.OpenAI):

instructor/dsl/iterable.py

@@ -94,7 +94,7 @@ def extract_json(
                     elif mode in {Mode.JSON, Mode.MD_JSON, Mode.JSON_SCHEMA}:
                         if json_chunk := chunk.choices[0].delta.content:
                             yield json_chunk
-                    elif mode == Mode.TOOLS or mode == Mode.STRUCTURED_OUTPUTS:
+                    elif mode in {Mode.TOOLS, Mode.TOOLS_STRICT}:
                         if json_chunk := chunk.choices[0].delta.tool_calls:
                             yield json_chunk[0].function.arguments
                     else:
@@ -123,7 +123,7 @@ async def extract_json_async(
                     elif mode in {Mode.JSON, Mode.MD_JSON, Mode.JSON_SCHEMA}:
                         if json_chunk := chunk.choices[0].delta.content:
                             yield json_chunk
-                    elif mode == Mode.TOOLS or mode == Mode.STRUCTURED_OUTPUTS:
+                    elif mode in {Mode.TOOLS, Mode.TOOLS_STRICT}:
                         if json_chunk := chunk.choices[0].delta.tool_calls:
                             yield json_chunk[0].function.arguments
                     else:

instructor/dsl/partial.py

@@ -170,7 +170,7 @@ def extract_json(
                     elif mode in {Mode.JSON, Mode.MD_JSON, Mode.JSON_SCHEMA}:
                         if json_chunk := chunk.choices[0].delta.content:
                             yield json_chunk
-                    elif mode == Mode.TOOLS or mode == Mode.STRUCTURED_OUTPUTS:
+                    elif mode in {Mode.TOOLS, Mode.TOOLS_STRICT}:
                         if json_chunk := chunk.choices[0].delta.tool_calls:
                             yield json_chunk[0].function.arguments
                     else:
@@ -199,7 +199,7 @@ async def extract_json_async(
                     elif mode in {Mode.JSON, Mode.MD_JSON, Mode.JSON_SCHEMA}:
                         if json_chunk := chunk.choices[0].delta.content:
                             yield json_chunk
-                    elif mode == Mode.TOOLS or mode == Mode.STRUCTURED_OUTPUTS:
+                    elif mode in {Mode.TOOLS, Mode.TOOLS_STRICT}:
                         if json_chunk := chunk.choices[0].delta.tool_calls:
                             yield json_chunk[0].function.arguments
                     else:

instructor/function_calls.py

@@ -264,7 +264,7 @@ def from_response(
             Mode.warn_mode_functions_deprecation()
             return cls.parse_functions(completion, validation_context, strict)
 
-        if mode in {Mode.TOOLS, Mode.MISTRAL_TOOLS, Mode.STRUCTURED_OUTPUTS}:
+        if mode in {Mode.TOOLS, Mode.MISTRAL_TOOLS, Mode.TOOLS_STRICT}:
             return cls.parse_tools(completion, validation_context, strict)
 
         if mode in {Mode.JSON, Mode.JSON_SCHEMA, Mode.MD_JSON}:
@@ -294,7 +294,8 @@ def parse_anthropic_tools(
         strict: Optional[bool] = None,
     ) -> BaseModel:
         from anthropic.types import Message
-        if isinstance(completion, Message) and completion.stop_reason == 'max_tokens':
+
+        if isinstance(completion, Message) and completion.stop_reason == "max_tokens":
             raise IncompleteOutputException(last_completion=completion)
 
         # Anthropic returns arguments as a dict, dump to json for model validation below
@@ -322,7 +323,7 @@ def parse_anthropic_json(
 
         assert isinstance(completion, Message)
 
-        if completion.stop_reason == 'max_tokens':
+        if completion.stop_reason == "max_tokens":
             raise IncompleteOutputException(last_completion=completion)
 
         text = completion.content[0].text

instructor/mode.py

@@ -19,7 +19,7 @@ class Mode(enum.Enum):
     VERTEXAI_JSON = "vertexai_json"
     GEMINI_JSON = "gemini_json"
     COHERE_JSON_SCHEMA = "json_object"
-    STRUCTURED_OUTPUTS = "structured_output"
+    TOOLS_STRICT = "tools_strict"
 
     @classmethod
     def warn_mode_functions_deprecation(cls):

instructor/process_response.py

@@ -250,7 +250,7 @@ def handle_response_model(
             Mode.warn_mode_functions_deprecation()
             new_kwargs["functions"] = [response_model.openai_schema]
             new_kwargs["function_call"] = {"name": response_model.openai_schema["name"]}
-        elif mode in {Mode.STRUCTURED_OUTPUTS}:
+        elif mode == Mode.TOOLS_STRICT:
             response_model_schema = pydantic_function_tool(response_model)
             response_model_schema["function"]["strict"] = True
             new_kwargs["tools"] = [response_model_schema]

instructor/retry.py

@@ -108,7 +108,7 @@ def reask_messages(response: ChatCompletion, mode: Mode, exception: Exception):
 
     yield dump_message(response.choices[0].message)
     # TODO: Give users more control on configuration
-    if mode == Mode.TOOLS or mode == Mode.STRUCTURED_OUTPUTS:
+    if mode in {Mode.TOOLS, Mode.TOOLS_STRICT}:
         for tool_call in response.choices[0].message.tool_calls:
             yield {
                 "role": "tool",

tests/llm/test_openai/test_validators.py

@@ -24,7 +24,7 @@ class Response(BaseModel):
 def test_runmodel_validator_error(model, mode, client):
     client = instructor.from_openai(client, mode=mode)
 
-    if mode == instructor.Mode.STRUCTURED_OUTPUTS:
+    if mode == instructor.Mode.TOOLS_STRICT:
         # TODO: Structured outputs currently doesn't support the concept of Validators ( This is Pydantic specific ) so perhaps come back to this later
         pytest.skip("Skipping test for structured output")
 

tests/llm/test_openai/util.py

@@ -3,5 +3,5 @@
 models = ["gpt-4o-mini"]
 modes = [
     instructor.Mode.TOOLS,
-    instructor.Mode.STRUCTURED_OUTPUTS,
+    instructor.Mode.TOOLS_STRICT,
 ]