Update app.py

app.py

@@ -83,26 +83,6 @@ class LLMCurriculumAssistant:
                 api_key=os.environ.get("ANTHROPIC_KEY")
             )
             
-            # Create LLM wrapper for LangChain compatibility
-            class ClaudeLLM:
-                def __init__(self, client):
-                    self.client = client
-                
-                def __call__(self, prompt):
-                    try:
-                        response = self.client.messages.create(
-                            model="claude-3-5-haiku-20241022",
-                            max_tokens=1500,
-                            temperature=0.7,
-                            messages=[{"role": "user", "content": prompt}]
-                        )
-                        return response.content[0].text
-                    except Exception as e:
-                        print(f"Error calling Claude: {e}")
-                        return "I'm sorry, I couldn't generate a response at the moment."
-            
-            self.llm = ClaudeLLM(self.anthropic_client)
-            
             # Create content selection prompt
             content_selection_template = """Hi! I'm helping a student find the best curriculum slide for their question. 
 
@@ -120,12 +100,9 @@ Just respond with the slide number (1, 2, 3, etc.) that you think is most helpfu
 
 Thanks! Slide number:"""
             
-            self.content_selection_chain = LLMChain(
-                llm=self.llm, 
-                prompt=PromptTemplate(
-                    input_variables=["question", "slide_contents"],
-                    template=content_selection_template
-                )
+            self.content_selection_prompt = PromptTemplate(
+                input_variables=["question", "slide_contents"],
+                template=content_selection_template
             )
             
             # Create answer generation prompt
@@ -146,21 +123,18 @@ Could you help me explain this to them in a friendly, educational way? I'd like
 
 Thanks for your help! Here's what I'd tell the student:"""
             
-            self.answer_chain = LLMChain(
-                llm=self.llm,
-                prompt=PromptTemplate(
-                    input_variables=["question", "slide_content"],
-                    template=answer_template
-                )
+            self.answer_prompt = PromptTemplate(
+                input_variables=["question", "slide_content"],
+                template=answer_template
             )
             
             print("✅ LLM setup successful!")
             
         except Exception as e:
             print(f"❌ Error setting up LLM: {e}")
-            self.llm = None
-            self.content_selection_chain = None
-            self.answer_chain = None
+            self.anthropic_client = None
+            self.content_selection_prompt = None
+            self.answer_prompt = None
 
     def get_pdf_page_image(self, pdf_path, page_num):
         """Get PDF page as image"""
@@ -198,7 +172,7 @@ Thanks for your help! Here's what I'd tell the student:"""
         selected_content = None
         selected_result = None
         
-        if self.content_selection_chain:
+        if self.anthropic_client and self.content_selection_prompt:
             try:
                 # Prepare slide contents for LLM analysis
                 slide_contents = []
@@ -212,12 +186,21 @@ Thanks for your help! Here's what I'd tell the student:"""
                 
                 print("🤖 Using LLM to select most relevant content...")
                 
-                # Get LLM's selection
-                selection_response = self.content_selection_chain.run(
+                # Format the prompt
+                prompt = self.content_selection_prompt.format(
                     question=query, 
                     slide_contents=slide_contents_text
                 )
                 
+                # Get LLM's selection
+                response = self.anthropic_client.messages.create(
+                    model="claude-3-5-haiku-20241022",
+                    max_tokens=1500,
+                    temperature=0.7,
+                    messages=[{"role": "user", "content": prompt}]
+                )
+                
+                selection_response = response.content[0].text
                 print(f"LLM Selection Response: {selection_response}")
                 
                 # Parse the selection
@@ -254,14 +237,25 @@ Thanks for your help! Here's what I'd tell the student:"""
         
         # Step 3: LLM answer generation
         answer = ""
-        if self.answer_chain and selected_content:
+        if self.anthropic_client and self.answer_prompt and selected_content:
             try:
                 print("🤖 Generating LLM answer...")
-                answer = self.answer_chain.run(
+                
+                # Format the prompt
+                prompt = self.answer_prompt.format(
                     question=query, 
                     slide_content=selected_content
                 )
-                answer = answer.strip()
+                
+                # Get LLM's answer
+                response = self.anthropic_client.messages.create(
+                    model="claude-3-5-haiku-20241022",
+                    max_tokens=1500,
+                    temperature=0.7,
+                    messages=[{"role": "user", "content": prompt}]
+                )
+                
+                answer = response.content[0].text.strip()
                 print(f"✅ LLM answer generated: {answer[:100]}...")
                 
             except Exception as e: