Update app.py

app.py

@@ -204,24 +204,24 @@ class OptimizedRAGLoader:
             
         return retriever_function
 
-# Initialize components
-# mistral_api_key = os.getenv("mistral_api_key")
-# llm = ChatMistralAI(
-#     model="mistral-large-latest",
-#     mistral_api_key=mistral_api_key,
-#     temperature=0.01,
-#     streaming=True,
-# )
-
-from langchain_openai import ChatOpenAI
-llm = ChatOpenAI(
-    api_key="sk-bahOSQLfPZb62d-q3aZ0JGcN8raIl12mhUj38DkdpeT3BlbkFJ650KTnBNL0rsIvUcdBA1KJw8H7dCCy7-Kl02GO-l4A",
-    model_name="GPT-4 Turbo",
-    temperature=0.1,
+Initialize components
+mistral_api_key = os.getenv("mistral_api_key")
+llm = ChatMistralAI(
+    model="mistral-large-latest",
+    mistral_api_key=mistral_api_key,
+    temperature=0.01,
+    streaming=True,
 )
 
+# from langchain_openai import ChatOpenAI
+# llm = ChatOpenAI(
+#     api_key="sk-bahOSQLfPZb62d-q3aZ0JGcN8raIl12mhUj38DkdpeT3BlbkFJ650KTnBNL0rsIvUcdBA1KJw8H7dCCy7-Kl02GO-l4A",
+#     model_name="GPT-4 Turbo",
+#     temperature=0.1,
+# )
+
 rag_loader = OptimizedRAGLoader()
-retriever = rag_loader.get_retriever(k=30)  # Reduced k for faster retrieval
+retriever = rag_loader.get_retriever(k=20)  # Reduced k for faster retrieval
 
 # Cache for processed questions
 question_cache = {}
@@ -354,7 +354,7 @@ def process_question(question: str) -> Iterator[str]:
     scored_docs = list(zip(scores, context, relevant_docs))
     # scored_docs.sort(reverse=True)
     scored_docs.sort(key=lambda x: x[0], reverse=True)
-    reranked_docs = [d[2].page_content for d in scored_docs][:15]
+    reranked_docs = [d[2].page_content for d in scored_docs][:5]
 
     
     prompt = prompt_template.format_messages(
@@ -376,7 +376,7 @@ def process_question(question: str) -> Iterator[str]:
             sources = list(set([os.path.splitext(source)[0] for source in sources]))
 
 
-            sources = [d[2].metadata['source'] for d in scored_docs][:15]
+            sources = [d[2].metadata['source'] for d in scored_docs][:5]
             sources = list(set([os.path.splitext(source)[0] for source in sources]))