From a7ffe735fc3f1276c3cf1f6e84d059af6911d23f Mon Sep 17 00:00:00 2001
From: Gabriel D'andrea <134967017+zxcvbs1@users.noreply.github.com>
Date: Sun, 11 Feb 2024 21:37:16 -0300
Subject: [PATCH 1/5] Update streamlit_app.py

---
 streamlit_app.py | 58 +++++++++++++++++-------------------------------
 1 file changed, 20 insertions(+), 38 deletions(-)

diff --git a/streamlit_app.py b/streamlit_app.py
index 7a0ed1272052..12a5af48337f 100644
--- a/streamlit_app.py
+++ b/streamlit_app.py
@@ -1,40 +1,22 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
+from transformers import pipeline
+from PIL import Image
+
+pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
+
+st.title("Hot Dog? Or Not?")
+
+file_name = st.file_uploader("Upload a hot dog candidate image")
+
+if file_name is not None:
+    col1, col2 = st.columns(2)
+
+    image = Image.open(file_name)
+    col1.image(image, use_column_width=True)
+    predictions = pipeline(image)
+
+    col2.header("Probabilities")
+    for p in predictions:
+        col2.subheader(f"{ p['label'] }: { round(p['score'] * 100, 1)}%")
+
 
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))

From b91529bd06cefe03d93d8c9364b28d0c8f409c77 Mon Sep 17 00:00:00 2001
From: Gabriel D'andrea <134967017+zxcvbs1@users.noreply.github.com>
Date: Mon, 12 Feb 2024 01:21:43 +0000
Subject: [PATCH 2/5] COMMIT TO REQ

---
 requirements.txt | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/requirements.txt b/requirements.txt
index 502d7d1a0d19..ff01959d839b 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,3 +1,5 @@
 altair
 pandas
 streamlit
+transformers
+torch

From 3b32c294c57505dd5e05ff5366b75e5c8541f8ae Mon Sep 17 00:00:00 2001
From: Gabriel D'andrea <134967017+zxcvbs1@users.noreply.github.com>
Date: Sun, 11 Feb 2024 23:03:30 -0300
Subject: [PATCH 3/5] Update streamlit_app.py

---
 streamlit_app.py | 25 ++++++++-----------------
 1 file changed, 8 insertions(+), 17 deletions(-)

diff --git a/streamlit_app.py b/streamlit_app.py
index 12a5af48337f..b9a7dcb5afda 100644
--- a/streamlit_app.py
+++ b/streamlit_app.py
@@ -1,22 +1,13 @@
 import streamlit as st
 from transformers import pipeline
-from PIL import Image
 
-pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
-
-st.title("Hot Dog? Or Not?")
-
-file_name = st.file_uploader("Upload a hot dog candidate image")
-
-if file_name is not None:
-    col1, col2 = st.columns(2)
-
-    image = Image.open(file_name)
-    col1.image(image, use_column_width=True)
-    predictions = pipeline(image)
-
-    col2.header("Probabilities")
-    for p in predictions:
-        col2.subheader(f"{ p['label'] }: { round(p['score'] * 100, 1)}%")
+# Load the text-to-speech pipeline
+tts_pipeline = pipeline("text-to-speech", model="your_chosen_model_name")
 
+# Text input field
+text_input = st.text_input("Enter text to be spoken:")
 
+# Generate audio and play it
+if text_input:
+    audio = tts_pipeline(text_input)
+    st.audio(audio)

From c1a0147efb5f2079fff154f7b88b1882fbc31721 Mon Sep 17 00:00:00 2001
From: Gabriel D'andrea <134967017+zxcvbs1@users.noreply.github.com>
Date: Sun, 11 Feb 2024 23:06:59 -0300
Subject: [PATCH 4/5] Update streamlit_app.py

changed model
---
 streamlit_app.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/streamlit_app.py b/streamlit_app.py
index b9a7dcb5afda..de0ac2066739 100644
--- a/streamlit_app.py
+++ b/streamlit_app.py
@@ -2,7 +2,7 @@
 from transformers import pipeline
 
 # Load the text-to-speech pipeline
-tts_pipeline = pipeline("text-to-speech", model="your_chosen_model_name")
+tts_pipeline = pipeline("text-to-speech")
 
 # Text input field
 text_input = st.text_input("Enter text to be spoken:")

From 83d7b4145e6ed95a77a18a0afd6eac746d283534 Mon Sep 17 00:00:00 2001
From: Gabriel D'andrea <134967017+zxcvbs1@users.noreply.github.com>
Date: Tue, 13 Feb 2024 02:15:51 +0000
Subject: [PATCH 5/5] updating requirem

---
 requirements.txt | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/requirements.txt b/requirements.txt
index ff01959d839b..151bd8f69a39 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -3,3 +3,7 @@ pandas
 streamlit
 transformers
 torch
+GoogleBard
+langchain
+ProGPT
+edge-tts
\ No newline at end of file