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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+faiss_index/index.faiss filter=lfs diff=lfs merge=lfs -text

Dockerfile

@@ -0,0 +1,26 @@
+# Use the latest Python image
+FROM python:3.10.12
+
+# Set the working directory to /app
+WORKDIR /app
+
+# Install system dependencies
+RUN apt-get update && \
+    apt-get install -y swig && \
+    apt-get install -y libomp-dev
+
+# Copy the current directory contents into the container at /app
+COPY . /app
+
+# Install any needed packages specified in requirements.txt
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Make port 8501 available to the world outside this container
+EXPOSE 8501
+
+# Define environment variable
+ENV NAME World
+
+# Run streamlit when the container launches
+CMD ["streamlit", "run", "pharmagpt.py"]
+

faiss_index/index.faiss

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e9f0c2b9428cdc6c37f62eba62518b5a56a1872999ec5485fe81f479099ffde0
+size 19230765

faiss_index/index.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f51bbc4af3cdeaac50c127a920281d77737735a9a05c5578633a88c2e8fa74ae
+size 63081007

pharmagpt.py

@@ -0,0 +1,181 @@
+from langchain.vectorstores import FAISS
+from langchain import PromptTemplate
+import streamlit as st
+import os
+from langchain.chains import RetrievalQA
+import time
+from datetime import datetime
+import pytz
+from langchain_google_genai import GoogleGenerativeAIEmbeddings
+import google.generativeai as genai
+from langchain.vectorstores import FAISS
+from langchain_google_genai import ChatGoogleGenerativeAI
+
+os.environ["GOOGLE_API_KEY"] = "AIzaSyB9O6fAGbU0ptk5VirtkTrLfmMCmaZqFCA"
+
+# Move this image display up
+st.markdown(
+    '<div class = "center"> <img src = "https://solukraft.com/Home/Black%20BG%20PNG.png" style = "width : 100px;" alt = "Center Aligned Image"> </div>',
+    unsafe_allow_html=True,
+)
+
+st.markdown(
+    """ <style>
+    body {
+        background-size: cover;
+    }
+    .css-fg4pbf {
+        background:rgba(255,255,255,0.8) !important;
+    }
+    .css-18ni7ap {
+        background:none !important;
+    }
+    a.css-eczf16.e1nzilvr3 {
+        display: none;
+    }
+    .block-container {
+        padding: 2rem 0 10rem 0;
+    }
+    button[kind="primary"] {
+        position: fixed;
+        bottom: 8rem;
+    }
+    
+    button[kind="secondary"] {
+        position: fixed;
+        bottom: 8rem;
+        transform: translateX(630px)
+    }
+    h1#private-bot-using-gpt-3-5 {
+        padding-top: 0;
+    }
+    .font {
+        font-size:22px ;
+        font-family: 'Segoe UI';
+        color:#B7D313;
+        font-weight:400;
+        text-align:center;
+    }
+    h1 {
+        font-size:30px ;
+        font-family: 'Segoe UI';
+        color:#002C84;
+        font-weight:bold;
+        text-align:center;
+    }
+    .center {
+        display: flex;
+        justify-content : center ;
+    }
+    </style> """,
+    unsafe_allow_html=True,
+)
+
+def get_conversational_chain():
+
+    prompt_template = """
+    Answer the question as detailed as possible from the provided context, make sure to provide all the details
+    Context:\n {context}?\n
+    Question: \n{question}\n
+
+    Answer:
+    """
+
+    model = ChatGoogleGenerativeAI(model="gemini-pro",
+                             temperature=0.3)
+    embeddings = GoogleGenerativeAIEmbeddings(model = "models/embedding-001")
+    
+    new_db = FAISS.load_local("", embeddings)
+    prompt = PromptTemplate(template = prompt_template, input_variables = ["context", "question"])
+    qa_chain = RetrievalQA.from_chain_type(llm=model,
+                                        chain_type='stuff',
+                                        retriever=new_db.as_retriever(search_kwargs={'k': 2}),
+                                        return_source_documents=True,
+                                        chain_type_kwargs={'prompt': prompt}
+                                        )
+    return qa_chain
+
+
+
+def user_input(user_question):
+    chain = get_conversational_chain()
+    response = chain.invoke(user_question)
+    return response
+
+
+st.title("SoluKraft PharmaGPT")
+
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+
+# Display chat messages from history on app rerun
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+        st.markdown(f"<div style='text-align: right'>{message['timestamp']}</div>", unsafe_allow_html=True)
+        
+
+if prompt := st.chat_input("send a message"):
+    # Display user message in chat message container
+    utc_now = datetime.utcnow()
+    # Convert UTC time to IST
+    ist_timezone = pytz.timezone('Asia/Kolkata')
+    current_time = utc_now.astimezone(ist_timezone).strftime("%Y-%m-%d %H:%M:%S")
+    with st.chat_message("user"):
+        st.markdown(prompt)
+        st.markdown(f"<div style='text-align: right'>{current_time}</div>", unsafe_allow_html=True,)
+    
+    # Add user message to chat history with timestamp
+    st.session_state.messages.append({"role": "user", "content": prompt, "timestamp": current_time})
+    
+    start_time = time.time()
+    response = user_input(prompt)
+    end_time = time.time()
+    utc_now = datetime.utcnow()
+    # Convert UTC time to IST
+    ist_timezone = pytz.timezone('Asia/Kolkata')
+    current_time = utc_now.astimezone(ist_timezone).strftime("%Y-%m-%d %H:%M:%S")
+    execution_time = end_time - start_time
+    #st.write(f"Execution time: {execution_time:.4f} seconds")
+
+    # Display assistant response in chat message container
+    with st.chat_message("assistant"):
+        st.markdown(response['result'])
+        st.markdown(f"<div style='text-align: right'>{current_time}</div>", unsafe_allow_html=True,)
+        st.session_state.messages.append({"role": "assistant", "content": response['result'], "timestamp": current_time})
+
+if len(st.session_state.messages) != 0:
+    if st.button("Clear", type="primary"):
+        st.session_state.messages = []
+        
+    if st.button("Regenerate", type="secondary"):
+        prompt = st.session_state.messages[0]['content']
+        utc_now = datetime.utcnow()
+
+        # Convert UTC time to IST
+        ist_timezone = pytz.timezone('Asia/Kolkata')
+        current_time = utc_now.astimezone(ist_timezone).strftime("%Y-%m-%d %H:%M:%S")
+        with st.chat_message("user"):
+            st.markdown(prompt)
+            st.markdown(f"<div style='text-align: right'>{current_time}</div>", unsafe_allow_html=True,)
+        # Add user message to chat history with timestamp
+        st.session_state.messages.append({"role": "user", "content": prompt, "timestamp": current_time})
+        start_time = time.time()
+        response = user_input(prompt)	
+        end_time = time.time()
+        execution_time = end_time - start_time
+        st.write(f"Execution time: {execution_time:.4f} seconds")
+        with st.chat_message("assistant"):
+            st.markdown(response['result'])
+            utc_now = datetime.utcnow()
+
+            # Convert UTC time to IST
+            ist_timezone = pytz.timezone('Asia/Kolkata')
+            current_time = utc_now.astimezone(ist_timezone).strftime("%Y-%m-%d %H:%M:%S")
+            st.markdown(f"<div style='text-align: right'>{current_time}</div>", unsafe_allow_html=True,)
+
+            # Add assistant response to chat history with timestamp
+            st.session_state.messages.append({"role": "assistant", "content": response['result'], "timestamp": current_time,"metadata":response['source_documents']})
+
+

requirements.txt

@@ -0,0 +1,4 @@
+streamlit
+langchain
+faiss-cpu
+langchain-google-genai