Update rag_service.py

rag_service.py

@@ -103,52 +103,41 @@ class RAGService:
                 text.append(doc)
         return {"images": b64, "texts": text}
 
+
     def build_prompt(self, kwargs):
-        """Build prompt with context and images"""
-        docs_by_type = kwargs["context"]
-        user_question = kwargs["question"]
-
-        context_text = ""
-        if len(docs_by_type["texts"]) > 0:
-            for text_element in docs_by_type["texts"]:
-                context_text += str(text_element)
-
-        # If no relevant context found, make it fully general
-        if not context_text.strip():
-            prompt_template = f""" 
-            You are a helpful AI assistant. Answer the following question:
-            Question: {user_question}
-            """
-        else:
-            prompt_template = f"""
-            You are a helpful AI assistant. You have access to the following context from uploaded documents:
-
-            Context: {context_text}
-
-            Question: {user_question}
-
-            Instructions:
-            - If the question is related to the provided context, use that information to answer
-            - If the question is not related to the context or is a general query, answer based on your general knowledge
-            - Be clear about whether you're using the provided context or general knowledge in your response
-            """
-
-        prompt_content = [{"type": "text", "text": prompt_template}]
-        
-        if len(docs_by_type["images"]) > 0:
-            for image in docs_by_type["images"]:
-                prompt_content.append(
-                    {
-                        "type": "image_url",
-                        "image_url": {"url": f"data:image/jpeg;base64,{image}"},
-                    }
-                )
-
-        return ChatPromptTemplate.from_messages(
-            [
-                HumanMessage(content=prompt_content),
-            ]
-        )
+    """Build prompt with context and images"""
+    docs_by_type = kwargs["context"]
+    user_question = kwargs["question"]
+
+    context_text = ""
+    if len(docs_by_type["texts"]) > 0:
+        for text_element in docs_by_type["texts"]:
+            context_text += str(text_element)
+
+    # Always use this flexible prompt
+    prompt_template = f"""
+    You are a helpful AI assistant. 
+    
+    Context from documents (use if relevant): {context_text}
+    
+    Question: {user_question}
+    
+    Instructions: Answer the question. If the provided context is relevant to the question, use it. If not, answer using your general knowledge.
+    """
+
+    prompt_content = [{"type": "text", "text": prompt_template}]
+    
+    # Add images only if context exists
+    if len(docs_by_type["images"]) > 0:
+        for image in docs_by_type["images"]:
+            prompt_content.append(
+                {
+                    "type": "image_url",
+                    "image_url": {"url": f"data:image/jpeg;base64,{image}"},
+                }
+            )
+
+    return ChatPromptTemplate.from_messages([HumanMessage(content=prompt_content)])
 
     def ask_question(self, question: str):
         """Process a question and return response"""