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import streamlit as st
import base64
from threading import Lock, Thread
import cv2
import openai
from dotenv import load_dotenv
from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
from langchain.schema.messages import SystemMessage
from langchain_community.chat_message_histories import ChatMessageHistory
from langchain_core.output_parsers import StrOutputParser
from langchain_core.runnables.history import RunnableWithMessageHistory
from langchain_openai import ChatOpenAI
from langchain_google_genai import ChatGoogleGenerativeAI
import pyaudio
import speech_recognition as sr
import os
import json
import random
import requests
import time
import zipfile
from PIL import Image
from urllib.parse import quote
load_dotenv()
class WebcamStream:
def __init__(self):
self.stream = cv2.VideoCapture(0)
_, self.frame = self.stream.read()
self.running = False
self.lock = Lock()
def start(self):
if self.running:
return self
self.running = True
self.thread = Thread(target=self.update, args=())
self.thread.start()
return self
def update(self):
while self.running:
_, frame = self.stream.read()
self.lock.acquire()
self.frame = frame
self.lock.release()
def read(self, encode=False):
self.lock.acquire()
frame = self.frame.copy()
self.lock.release()
if encode:
_, buffer = cv2.imencode(".jpeg", frame)
return base64.b64encode(buffer)
return frame
def stop(self):
self.running = False
if self.thread.is_alive():
self.thread.join()
def __exit__(self, exc_type, exc_value, exc_traceback):
self.stream.release()
class Assistant:
def __init__(self, model):
self.chain = self._create_inference_chain(model)
def answer(self, prompt, image):
if not prompt:
return
st.write("Prompt:", prompt)
response = self.chain.invoke(
{"prompt": prompt, "image_base64": image.decode()},
config={"configurable": {"session_id": "unused"}},
).strip()
st.write("Response:", response)
if response:
self._tts(response)
def _tts(self, response):
player = pyaudio.PyAudio().open(format=pyaudio.paInt16, channels=1, rate=24000, output=True)
with openai.audio.speech.with_streaming_response.create(
model="tts-1",
voice="alloy",
response_format="pcm",
input=response,
) as stream:
for chunk in stream.iter_bytes(chunk_size=1024):
player.write(chunk)
def _create_inference_chain(self, model):
SYSTEM_PROMPT = """
You are a witty assistant that will use the chat history and the image
provided by the user to answer its questions.
Use few words on your answers. Go straight to the point. Do not use any
emoticons or emojis. Do not ask the user any questions.
Be friendly and helpful. Show some personality. Do not be too formal.
"""
prompt_template = ChatPromptTemplate.from_messages([
SystemMessage(content=SYSTEM_PROMPT),
MessagesPlaceholder(variable_name="chat_history"),
("human", [
{"type": "text", "text": "{prompt}"},
{"type": "image_url", "image_url": "data:image/jpeg;base64,{image_base64}"},
]),
])
chain = prompt_template | model | StrOutputParser()
chat_message_history = ChatMessageHistory()
return RunnableWithMessageHistory(
chain,
lambda _: chat_message_history,
input_messages_key="prompt",
history_messages_key="chat_history",
)
def main():
st.title("🚀🌌 Scholarly Article Document Search with Memory")
webcam_stream = WebcamStream().start()
model = ChatGoogleGenerativeAI(model="gemini-1.5-flash-latest")
assistant = Assistant(model)
# Sidebar
st.sidebar.title("Options")
should_save = st.sidebar.checkbox("💾 Save", value=True, help="Save your session data.")
# Main content
query = st.text_input("Enter your search query:")
if st.button("Search"):
image = webcam_stream.read(encode=True)
assistant.answer(query, image)
# File upload
uploaded_file = st.file_uploader("Upload a file for context", type=["txt", "pdf", "docx"])
if uploaded_file:
file_contents = uploaded_file.read()
st.write("File contents:", file_contents)
# Display webcam feed
st.image(webcam_stream.read(), channels="BGR")
# Audio recording
if st.button("Record Audio"):
r = sr.Recognizer()
with sr.Microphone() as source:
st.write("Speak now...")
audio = r.listen(source)
st.write("Processing audio...")
try:
text = r.recognize_google(audio)
st.write("You said:", text)
assistant.answer(text, webcam_stream.read(encode=True))
except sr.UnknownValueError:
st.write("Could not understand audio")
except sr.RequestError as e:
st.write("Could not request results; {0}".format(e))
webcam_stream.stop()
if __name__ == "__main__":
main() |