change in prompt

.gitignore

@@ -0,0 +1 @@
+.env

app.py

@@ -1,12 +1,21 @@
 import streamlit as st
 import os
 import time
+from dotenv import load_dotenv
+from getpass import getpass
+from langchain.llms import replicate
+from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
+from langchain.prompts import PromptTemplate
+
 from PyPDF2 import PdfReader
 from streamlit_extras.add_vertical_space import add_vertical_space
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 #from langchain.embeddings.openai import OpenAIEmbeddings
 from langchain.vectorstores import faiss
 
+load_dotenv()
+REPLICATE_API_TOKEN = os.environ.get("REPLICATE_API_TOKEN")
+
 with st.sidebar:
     st.title("File Research using LLM")
     st.markdown(''' Upload your file and ask questions and do Research''')
@@ -23,19 +32,21 @@ with st.sidebar:
             length_function=len
         )
         chunks=text_splitter.split_text(text)
+        
+        
            
         
     st.write('Made by ALOK')
     
 
 def main():
-    import replicate
     st.header('Talk to your file')
+    os.environ["REPLICATE_API_TOKEN"]=REPLICATE_API_TOKEN
     #embeddings=OpenAIEmbeddings()
     #vectorstore=faiss.FAISS.from_texts(chunks, embedding=embeddings)
     
     # The meta/llama-2-70b-chat model can stream output as it's running.
-      
+
     
     if "messages" not in st.session_state:
         st.session_state.messages = []
@@ -51,28 +62,46 @@ def main():
         st.chat_message("user").markdown(prompt)
         # Add user message to chat history
         st.session_state.messages.append({"role": "user", "content": prompt})
-        replicate = replicate.Client(api_token='r8_4fktoXrDGkgHY8uw1XlVtQJKQlAILKv0iBmPI')
-        output = replicate.run(
-        "meta/llama-2-70b-chat:02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3",
-        input={"prompt": prompt}
+        replite_api='r8_4fktoXrDGkgHY8uw1XlVtQJKQlAILKv0iBmPI'
+        
+        
+        # rep = replicate.Client(api_token=replite_api)
+        # output = replicate.run(
+        # "meta/llama-2-70b-chat:02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3",
+        # input={"prompt": prompt}
+        # )
+        
+        model="meta/llama-2-70b-chat:02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3"
+        llm=replicate.Replicate(
+            streaming=True,
+            callbacks=[StreamingStdOutCallbackHandler()],
+            model=model,
+            model_kwargs={"temperature": 0.75, "max_length": 500, "top_p": 1},
+            replicate_api_token=REPLICATE_API_TOKEN
         )
+        prompt = """
+        User: Answer the following yes/no question by reasoning step by step. Please don't provide incomplete answer. Can a dog drive a car?
+        Assistant:
+        """
+        
         
         # Display assistant response in chat message container
         with st.chat_message("assistant"):
             message_placeholder = st.empty()
+        message_placeholder.markdown(llm(prompt) + "▌")
             
-        # The predict method returns an iterator, and you can iterate over that output.
-        response_till_now=''
-        for item in output:
-            response_till_now+=item
-            time.sleep(0.03)
-            message_placeholder.markdown(response_till_now + "▌")
-        message_placeholder.markdown(response_till_now)
-        response = f"AI: {response_till_now}"
+        # # The predict method returns an iterator, and you can iterate over that output.
+        # response_till_now=''
+        # for item in output:
+        #     response_till_now+=item
+        #     time.sleep(0.03)
+        #     message_placeholder.markdown(response_till_now + "▌")
+        # message_placeholder.markdown(response_till_now)
+        # response = f"AI: {response_till_now}"
         
         
         # Add assistant response to chat history
-        st.session_state.messages.append({"role": "assistant", "content": response})
+        # st.session_state.messages.append({"role": "assistant", "content": response})
             # https://replicate.com/meta/llama-2-70b-chat/versions/02e509c789964a7ea8736978a43525956ef40397be9033abf9fd2badfe68c9e3/api#output-schema
             #print(item, end="")