Update page1.py
Browse files
page1.py
CHANGED
@@ -1,4 +1,5 @@
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import streamlit as st
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from langchain_core.messages import HumanMessage, AIMessage
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from langchain_google_genai import ChatGoogleGenerativeAI
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from langchain.chains import LLMChain
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@@ -78,8 +79,8 @@ def text():
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google_api_key=GOOGLE_API_KEY,
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temperature=0.3,
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streaming=True,
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timeout=
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max_retries=
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)
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@@ -89,7 +90,7 @@ def text():
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# Show initial bot message
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if len(st.session_state.messages) == 0:
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animated_text = '<div class="anim-typewriter">Hello π, how may I assist you today?</div>'
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#st.chat_message("assistant").markdown(animated_text, unsafe_allow_html=True)
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st.session_state.messages.append({"role": "assistant", "content": "Hello π, how may I assist you today?"})
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# Display historical messages
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@@ -97,7 +98,7 @@ def text():
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if message["role"] == "user":
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if message.get("image"):
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st.chat_message("user", avatar="π§").markdown(
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f
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unsafe_allow_html=True
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)
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else:
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@@ -106,30 +107,52 @@ def text():
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st.chat_message("assistant", avatar="π€").markdown(message["content"])
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# Chat input with multimodal support
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user_input = st.chat_input("Say something", accept_file=True, file_type=["png", "jpg", "jpeg"])
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if user_input:
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# Process user input
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image_url = ""
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message_content = [{"type": "text", "text": user_input.text}]
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uploaded_file = user_input["files"][0]
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image_base64 = convert_to_base64(uploaded_file)
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image_url = f"data:image/jpeg;base64,{image_base64}"
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message_content.append({"type": "image_url", "image_url": image_url})
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# Add user message to UI
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with chat_container:
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if
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st.chat_message("user", avatar="π§").markdown(
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f
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unsafe_allow_html=True
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)
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@@ -140,7 +163,9 @@ def text():
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st.session_state.messages.append({
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"role": "user",
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"content": user_input.text,
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"image": image_url if user_input["files"] else ""
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})
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# Create LangChain message
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@@ -242,6 +267,4 @@ def text():
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{"input": user_message.content},
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{"output": ai_message.content}
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)
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#st.sidebar.subheader("Raw Chat History")
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#st.sidebar.write(st.session_state.chat_history.messages)
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import streamlit as st
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from PyPDF2 import PdfReader
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from langchain_core.messages import HumanMessage, AIMessage
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from langchain_google_genai import ChatGoogleGenerativeAI
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from langchain.chains import LLMChain
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google_api_key=GOOGLE_API_KEY,
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temperature=0.3,
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streaming=True,
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timeout=120,
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max_retries=6
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)
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# Show initial bot message
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if len(st.session_state.messages) == 0:
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animated_text = '<div class="anim-typewriter">Hello π, how may I assist you today?</div>'
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# st.chat_message("assistant").markdown(animated_text, unsafe_allow_html=True)
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st.session_state.messages.append({"role": "assistant", "content": "Hello π, how may I assist you today?"})
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# Display historical messages
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if message["role"] == "user":
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if message.get("image"):
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st.chat_message("user", avatar="π§").markdown(
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f"""{message["content"]}<br><br>{'<img src="' + message["image"] + f'" width="50" style="margin-top: 10px; border-radius: 8px;">' if message["file_type"] == "application/pdf" else '<img src="' + message["image"] + f'" width="200" style="margin-top: 10px; border-radius: 8px;">'}<br> {f'<i style="font-size: 12px;">{message["file_name"]}</i>' if message["file_type"] == "application/pdf" else message["file_name"] if message["file_type"] else ''}""",
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unsafe_allow_html=True
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)
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else:
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st.chat_message("assistant", avatar="π€").markdown(message["content"])
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# Chat input with multimodal support
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user_input = st.chat_input("Say something", accept_file=True, file_type=["png", "jpg", "jpeg", "pdf"])
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if user_input:
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file_type = None
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file_name = ""
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image_base64 = convert_to_base64("pdf_icon.png")
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image_url = f"data:image/jpeg;base64,{image_base64}"
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# Process user input
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#image_url = ""
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message_content = [{"type": "text", "text": user_input.text}]
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files = user_input["files"]
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if files:
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file_type = files[0].type
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if file_type in ["image/png", "image/jpg", "image/jpeg"]:
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uploaded_file = user_input["files"][0]
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image_base64 = convert_to_base64(uploaded_file)
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image_url = f"data:image/jpeg;base64,{image_base64}"
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message_content.append({"type": "image_url", "image_url": image_url})
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text = ""
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if file_type == "application/pdf":
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uploaded_file = user_input["files"][0]
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file_name = files[0].name
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pdf_reader = PdfReader(uploaded_file)
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for page in pdf_reader.pages:
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text += page.extract_text()
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#st.sidebar.write(text)
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prompt = "this is pdf data: \n"+text +"this is user asking about pdf:"+user_input.text
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message_content = [{"type": "text", "text": prompt}]
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message_content.append({"type": "text", "text": file_name})
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#message_content.append({"type": "image_url", "image_url": image_url})
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# Add user message to UI
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with chat_container:
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if file_type:
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st.chat_message("user", avatar="π§").markdown(
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f"""
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{user_input.text}
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<br><br>
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{'<img src="' + image_url + f'" width="50" style="margin-top: 10px; border-radius: 8px;">' if file_type == "application/pdf" else '<img src="' + image_url + f'" width="200" style="margin-top: 10px; border-radius: 8px;">' if file_type else ''}
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<br>
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{f'<i style="font-size: 12px;">{file_name}</i>' if file_type == "application/pdf" else file_name if file_type else ''}
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""",
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unsafe_allow_html=True
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)
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st.session_state.messages.append({
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"role": "user",
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"content": user_input.text,
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"image": image_url if user_input["files"] else "",
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"file_name" : file_name,
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"file_type" : file_type
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})
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# Create LangChain message
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{"input": user_message.content},
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{"output": ai_message.content}
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)
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#st.sidebar.write(user_message)
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