Update learning_platform.py

learning_platform.py

@@ -125,76 +125,75 @@ class CoursePrompts:
         Return in the same JSON format."""
 
 class CourseBuilder:
-    def __init__(self, api_key: str = None):
-        self.api_key = api_key or os.getenv("OPENAI_API_KEY")
-        self.setup_agents()
-        self.setup_graph()
-
-    def setup_agents(self):
-        self.llm = ChatOpenAI(
-            temperature=0.7,
-            model="gpt-4",
-            openai_api_key=self.api_key
-        )
-
-    def course_planner(self, state: CourseState) -> CourseState:
-            """Course planning agent node"""
-            print("---COURSE PLANNER---")
-            prompt = PromptTemplate(
-                template=CoursePrompts.planner_prompt(),
-                input_variables=["topic", "difficulty"]
-            )
-            
-            response = self.llm.predict(
-                prompt.format(
-                    topic=state["current_topic"],
-                    difficulty=state["difficulty"]
-                )
-            )
-            return {
-                "messages": [AIMessage(content=response)],
-                "status": "planning",
-                "current_topic": state["current_topic"],
-                "difficulty": state["difficulty"],
-                "modules": []
-            }
-
-    async def generate_module_content(self, module: CourseModule) -> List[Section]:
-    try:
-        section = Section(
-            title=f"Introduction to {module.title}",
-            content=f"Basic concepts of {module.title}",
-            key_points=["Key concept 1", "Key concept 2"],
-            quiz_questions=[{
-                "question": f"What is {module.title}?",
-                "options": ["A", "B", "C", "D"],
-                "correct_answer": "A",
-                "explanation": "Basic explanation"
-            }]
-        )
-        return [section]
-    except Exception as e:
-        print(f"Error generating content: {e}")
-        return []
-
-    def check_quality(self, state: CourseState) -> Literal["edit", "complete"]:
-        messages = state["messages"]
-        last_message = messages[-1]
-        
-        if len(last_message.content) > 1000 and "code example" in last_message.content.lower():
-            return "complete"
-        return "edit"
-
-    def setup_graph(self):
-        workflow = StateGraph(CourseState)
-        
-        workflow.add_node("planner", self.course_planner)
-        workflow.add_edge(START, "planner")
-        workflow.add_edge("planner", END)
-        
-        self.graph = workflow.compile()
-
-
+   def __init__(self, api_key: str = None):
+       self.api_key = api_key or os.getenv("OPENAI_API_KEY")
+       self.setup_agents()
+       self.setup_graph()
+
+   def setup_agents(self):
+       self.llm = ChatOpenAI(
+           temperature=0.7,
+           model="gpt-4",
+           openai_api_key=self.api_key
+       )
+
+   def course_planner(self, state: CourseState) -> CourseState:
+       """Course planning agent node"""
+       print("---COURSE PLANNER---")
+       prompt = PromptTemplate(
+           template=CoursePrompts.planner_prompt(),
+           input_variables=["topic", "difficulty"]
+       )
+       
+       response = self.llm.predict(
+           prompt.format(
+               topic=state["current_topic"],
+               difficulty=state["difficulty"]
+           )
+       )
+       return {
+           "messages": [AIMessage(content=response)],
+           "status": "planning",
+           "current_topic": state["current_topic"],
+           "difficulty": state["difficulty"],
+           "modules": []
+       }
+
+   async def generate_module_content(self, module: CourseModule) -> List[Section]:
+       try:
+           section = Section(
+               title=f"Introduction to {module.title}",
+               content=f"Basic concepts of {module.title}",
+               key_points=["Key concept 1", "Key concept 2"],
+               quiz_questions=[{
+                   "question": f"What is {module.title}?",
+                   "options": ["A", "B", "C", "D"],
+                   "correct_answer": "A",
+                   "explanation": "Basic explanation"
+               }]
+           )
+           return [section]
+       except Exception as e:
+           print(f"Error generating content: {e}")
+           return []
+
+   def check_quality(self, state: CourseState) -> Literal["edit", "complete"]:
+       messages = state["messages"]
+       last_message = messages[-1]
+       
+       if len(last_message.content) > 1000 and "code example" in last_message.content.lower():
+           return "complete"
+       return "edit"
+
+   def setup_graph(self):
+       workflow = StateGraph(CourseState)
+       
+       workflow.add_node("planner", self.course_planner)
+       workflow.add_edge(START, "planner")
+       workflow.add_edge("planner", END)
+       
+       self.graph = workflow.compile()
+       
 class LearningPlatform:
    def __init__(self, api_key: str = None):
        self.api_key = api_key or os.getenv("OPENAI_API_KEY")