Update main.py

main.py

@@ -9,6 +9,18 @@ from langchain_community.embeddings import HuggingFaceEmbeddings
 from langchain_community.vectorstores import FAISS
 from langchain.chains import ConversationalRetrievalChain
 
+import google.generativeai as genai
+
+
+GOOGLE_API_KEY = 'AIzaSyA13K0uJP5ti0R6eCy_ogK0UlqenbFfr_o'
+
+genai.configure(api_key=GOOGLE_API_KEY)
+
+
+model = genai.GenerativeModel('gemini-pro')
+#response = model.generate_content(query)
+#return response.text
+
 DB_FAISS_PATH = 'vectorstore/db_faiss'
 
 app = FastAPI()
@@ -44,7 +56,15 @@ async def PromptLLM(file: UploadFile = File(...)):
     chain = ConversationalRetrievalChain.from_llm(llm=llm, retriever=db.as_retriever())
 
     result = chain({"question": "Summarise this report", "chat_history": ''})
-    return result['answer']
+    summary =  result['answer']
+
+    response = model.generate_content(summary + "\nBased on the information provided, what are the key medical insights and considerations for this patient?")
+
+    ans = {"summary": summary, "insights": response.text}
+
+    return ans
+
+