Update to match deployed version

app.py

@@ -1,64 +1,76 @@
+3.25 kB
+import os
+os.environ["OPENAI_API_KEY"]
+
 from llama_index.llms.openai import OpenAI
 from llama_index.core.schema import MetadataMode
-from llama_index.core import VectorStoreIndex
-from llama_index.core import StorageContext
-from llama_index.core import load_index_from_storage
-import os
 import openai
-os.environ["OPENAI_API_KEY"]
+from openai import OpenAI as OpenAIOG
 import logging
 import sys
-llm = OpenAI(temperature=0.0, model="gpt-3.5-turbo", max_tokens=512)
+llm = OpenAI(temperature=0.0, model="gpt-3.5-turbo")
+client = OpenAIOG()
+
+from langdetect import detect
+from langdetect import DetectorFactory
+DetectorFactory.seed = 0
+from deep_translator import GoogleTranslator
 
-PERSIST_DIR = "arv_metadata"
-storage_context = StorageContext.from_defaults(persist_dir=PERSIST_DIR)
+# Load index
+from llama_index.core import VectorStoreIndex
+from llama_index.core import StorageContext
+from llama_index.core import load_index_from_storage
+storage_context = StorageContext.from_defaults(persist_dir="arv_metadata")
 index = load_index_from_storage(storage_context)
 query_engine = index.as_query_engine(similarity_top_k=3, llm=llm)
 
+import gradio as gr
 
-preamble = (" The person asking the following prompt is a person living with HIV in Kenya."
-            " For every response, recognize that they already have HIV and do not suggest that they have to get tested"
+def nishauri(question: str, conversation_history: list[str]):
+    
+    
+    context = " ".join([item["user"] + " " + item["chatbot"] for item in conversation_history])
+
+    lang_question = detect(question)
+    
+    if lang_question=="sw":
+        question = GoogleTranslator(source='sw', target='en').translate(question)
+        
+    response = query_engine.query(question)
+
+    background = ("The person who asked the question is a person living with HIV."
+                  " If the person says sasa or niaje, that is swahili slang for hello."
+            " Recognize that they already have HIV and do not suggest that they have to get tested"
             " for HIV or take post-exposure prophylaxis, as that is not relevant, though their partners perhaps should."  
             " Do not suggest anything that is not relevant to someone who already has HIV."
-           " They are asking questions through a mobile application called Nishauri"
-           " through which they can see their lab results, appointment histories, and upcoming appointments."
-            " Questions about those topics should be answered based on Nishauri user guide."
-           " Here is some information that is authoritative and should guide responses, when relevant."
-           " For questions about viral load, be sure to provide specific information"
-           " about cutoffs for viral load categories. Under 50 copies/ml is low detectable level,"
+             " Do not mention in the response that the person is living with HIV."
+            " The following information about viral loads is authoritative for any question about viral loads:"
+           " Under 50 copies/ml is low detectable level,"
            " 50 - 199 copies/ml is low level viremia, 200 - 999 is high level viremia, and "
            " 1000 and above is suspected treatment failure." 
            " A high viral load or non-suppressed viral load is any viral load above 200 copies/ml."
-           " A suppressed viral load is one below 200 copies / ml."
-           " An established client is one who is on their current ART regimen for a period greater"
-           " than 6 months, had no active OI or in the previous 6 months, has adhered to scheduled"
-           " clinic visits for the previous 6 months and Viral load results has been less than 200 copies/ml"
-           " within the last 6 months."
-           " For questions about when patients should get their viral loads taken," 
-           " if they are newly initiated on ART, the first viral load sample should be taken after 3 months of"
-           " taking ART. Otherwise, if they are not new on ART, then if their previous result was below 50 to 199 cp/ml,"
-           " their viral load should be taken after every 12 months. If  their previous result was above 200cp/ml,"
-           " then viral load sample should be taken after three months."
-           " Please answer the prompt using the information retrieved" 
-           " and do not rely at all on your prior knowledge."
-           # " Please keep your reply to no longer than three sentences, and please use simple language. ")
-           )
+           " A suppressed viral load is one below 200 copies / ml.")
 
-prompt_intro = (" Here is the prompt: ")
+    question_final = (
+        f"The user previously asked and answered the following: {context}"
+        f" The user just asked the following question: {question}"
+        f" The following response was generated in response: {response}"
+        f" Please update the response provided only if needed, based on the following background information {background}"
+    )
 
-import gradio as gr
+    completion = client.chat.completions.create(
+      model="gpt-3.5-turbo",
+        messages=[
+        {"role": "user", "content": question_final}
+      ]
+    )
 
-def nishauri(question: str, conversation_history: list[str]):
+    reply_to_user = completion.choices[0].message.content
     
+    if lang_question=="sw":
+        reply_to_user = GoogleTranslator(source='auto', target='sw').translate(reply_to_user)
     
-    context = " ".join([item["user"] + " " + item["chatbot"] for item in conversation_history])
-    response = query_engine.query(preamble +
-                                  "the user previously asked and received the following: " +
-                                  context +
-                                  prompt_intro +
-                                  question)
-
-    conversation_history.append({"user": question, "chatbot": response.response})   
+    conversation_history.append({"user": question, "chatbot": response.response})  
 
     source1 = ("File Name: " +
       response.source_nodes[0].metadata["file_name"] +