working!

simplemind/integrations/openai.py

@@ -39,18 +39,30 @@ class OpenAI(BaseClientProvider):
 
         return bool(len(self.available_models))
 
-    def single_message(self, message, *, response_model=False, **kwargs):
+    def message(self, message, *, response_model=False, **kwargs):
         """Generates a response from the OpenAI client."""
+        use_instructor = bool(response_model)
 
-        client = self.client if not response_model else self.instructor_client
+        client = self.instructor_client if use_instructor else self.client
 
-        completion = self.client.chat.completions.create(
-            model=self.model,
-            messages=[{"role": "user", "content": message}],
-            **kwargs,
-        )
+        # Parameters for the OpenAI client.
+        params = {
+            "messages": [{"role": "user", "content": message}],
+            "model": self.model,
+        }
+        params.update(kwargs)
 
-        return AIResponse(
-            response=completion,
-            text=completion.choices[0].message.content,
-        )
+        if use_instructor:
+            params["response_model"] = response_model
+
+        # Make the request to OpenAI.
+        completion = client.chat.completions.create(**params)
+
+        if use_instructor:
+            return completion.model_dump()
+
+        else:
+            return AIResponse(
+                response=completion,
+                text=completion.choices[0].message.content,
+            )

t.py

@@ -1,18 +1,50 @@
+from pprint import pprint
+from pydantic import BaseModel
 import simplemind
 
 context = None
 
 openai = simplemind.integrations.OpenAI()
 
+
+class YearlyData(BaseModel):
+    year: int
+    events: list[str]
+
+
+class ProjectData(BaseModel):
+    name: str
+    description: str
+    url: str
+    github_url: str
+
+
+class BioData(BaseModel):
+    bio: str
+    spouse_name: str
+    history: list[YearlyData]
+    fun_facts: list[str]
+    # age: int
+    # occupation: str
+    # bio: str
+    # affiliations: list[str]
+
+
+class PersonData(BaseModel):
+    bio: BioData
+    projects: list[ProjectData]
+    yearly_breakdown: list[YearlyData]
+
+
 print(openai.test_connection())
 print(openai.available_models)
 
 print()
 print()
-message = "who is kennethreitz?"
+message = "who is kenneth reitz?"
 
 print(f"> {message}")
-print(openai.single_message(message))
+pprint(openai.message(message, response_model=BioData))
 
 # claude = simplemind.integrations.Anthropic()
 

t2.py

@@ -0,0 +1,32 @@
+import instructor
+from pydantic import BaseModel
+from openai import OpenAI
+
+
+class ProjectInfo(BaseModel):
+    name: str
+    description: str
+    url: str
+    github_url: str
+
+
+# Define your desired output structure
+class UserInfo(BaseModel):
+    name: str
+    age: int
+    bio: str
+    projects: list[ProjectInfo]
+
+
+# Patch the OpenAI client
+client = instructor.from_openai(OpenAI())
+
+# Extract structured data from natural language
+user_info = client.chat.completions.create(
+    model="gpt-4o",
+    response_model=UserInfo,
+    messages=[{"role": "user", "content": "who is kennethreitz?"}],
+)
+
+print(user_info.model_dump())
+# > 30