Merge branch 'main' into revise_few_shot_docs

docs/blog/posts/introducing-structured-outputs.md

@@ -179,7 +179,7 @@ print(resp)
 #> name='JASON' age=25
 ```
 
-This built-in retry logic allows for targetted correction to the generated response, ensuring that outputs are not only consistent with your schema but also corect for your use-case. This is invaluable in building reliable LLM systems.
+This built-in retry logic allows for targetted correction to the generated response, ensuring that outputs are not only consistent with your schema but also correct for your use-case. This is invaluable in building reliable LLM systems.
 
 ### Real-time Streaming Validation
 
@@ -240,7 +240,7 @@ During the meeting, we agreed on several key points. The conference will be held
 
 The budget for the event is set at $50,000, covering venue costs, speaker fees, and promotional activities. Each participant is expected to contribute an article to the conference blog by February 20th.
 
-A follow-up meetingis scheduled for January 25th at 3 PM GMT to finalize the agenda and confirm the list of speakers.
+A follow-up meeting is scheduled for January 25th at 3 PM GMT to finalize the agenda and confirm the list of speakers.
 """
 
 

instructor/client.py

@@ -426,6 +426,7 @@ def from_openai(
             instructor.Mode.PARALLEL_TOOLS,
             instructor.Mode.MD_JSON,
             instructor.Mode.TOOLS_STRICT,
+            instructor.Mode.JSON_O1,
         }
 
     if isinstance(client, openai.OpenAI):

instructor/dsl/partial.py

@@ -129,7 +129,7 @@ def model_from_chunks(
         partial_model = cls.get_partial_model()
         for chunk in json_chunks:
             potential_object += chunk
-            obj = from_json((potential_object or "{}").encode(), partial_mode="on")
+            obj = from_json((potential_object.strip() or "{}").encode(), partial_mode="on")
             obj = partial_model.model_validate(obj, strict=None, **kwargs)
             yield obj
 
@@ -141,7 +141,7 @@ async def model_from_chunks_async(
         partial_model = cls.get_partial_model()
         async for chunk in json_chunks:
             potential_object += chunk
-            obj = from_json((potential_object or "{}").encode(), partial_mode="on")
+            obj = from_json((potential_object.strip() or "{}").encode(), partial_mode="on")
             obj = partial_model.model_validate(obj, strict=None, **kwargs)
             yield obj
 

instructor/function_calls.py

@@ -146,7 +146,7 @@ def from_response(
         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}:
+        if mode in {Mode.JSON, Mode.JSON_SCHEMA, Mode.MD_JSON, Mode.JSON_O1}:
             return cls.parse_json(completion, validation_context, strict)
 
         raise ValueError(f"Invalid patch mode: {mode}")

instructor/mode.py

@@ -10,6 +10,7 @@ class Mode(enum.Enum):
     TOOLS = "tool_call"
     MISTRAL_TOOLS = "mistral_tools"
     JSON = "json_mode"
+    JSON_O1 = "json_o1"
     MD_JSON = "markdown_json_mode"
     JSON_SCHEMA = "json_schema_mode"
     ANTHROPIC_TOOLS = "anthropic_tools"

instructor/process_response.py

@@ -260,6 +260,29 @@ def handle_response_model(
                     "type": "function",
                     "function": {"name": response_model.openai_schema["name"]},
                 }
+        elif mode in {Mode.JSON_O1}:
+            # O1 doesn't accept system messages so you'll need to assert that
+            roles = [message["role"] for message in new_kwargs.get("messages", [])]
+            if "system" in roles:
+                raise ValueError("System messages are not supported For the O1 models")
+
+            message = dedent(
+                f"""
+                Understand the content and provide
+                the parsed objects in json that match the following json_schema:\n
+
+                {json.dumps(response_model.model_json_schema(), indent=2, ensure_ascii=False)}
+
+                Make sure to return an instance of the JSON, not the schema itself
+                """
+            )
+
+            new_kwargs["messages"].append(
+                {
+                    "role": "user",
+                    "content": message,
+                },
+            )
 
         elif mode in {Mode.JSON, Mode.MD_JSON, Mode.JSON_SCHEMA}:
             # If its a JSON Mode we need to massage the prompt a bit

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "instructor"
-version = "1.4.1"
+version = "1.4.2"
 description = "structured outputs for llm"
 authors = ["Jason Liu <[email protected]>"]
 license = "MIT"
@@ -10,7 +10,7 @@ repository = "https://github.com/jxnl/instructor"
 
 [tool.poetry.dependencies]
 python = "^3.9"
-openai = "^1.40.0"
+openai = "^1.45.0"
 pydantic = "^2.8.0"
 docstring-parser = "^0.16"
 typer = ">=0.9.0,<1.0.0"

tests/dsl/test_partial.py

@@ -71,7 +71,8 @@ def test_partial():
         "type": "object",
     }, "Partial model JSON schema has changed"
 
-    for model in partial.model_from_chunks(['{"b": {"b": 1}}']):
+    # Handle any leading whitespace from the model
+    for model in partial.model_from_chunks(['\n', '\t', ' ', '{"b": {"b": 1}}']):
         assert model.model_dump() == {"a": None, "b": {"b": 1}}