Update app.py

app.py

@@ -1,213 +1,60 @@
-import numpy as np
-import streamlit as st
-from transformers import Autookenizer, AutoModelorCausalLM
-import os
-import sys
-from dotenv import loaddotenv, dotenvvalues
-loaddotenv()
-
-# Create supported models
-modellinks = {
-    "Meta-Llama-3-8B-Instruct": "meta-llama/Meta-Llama-3-8B-Instruct",
+import openai
+
+# Initialize OpenAI API
+openai.api_key = "your_openai_api_key_here"
+
+# Outfit suggestions database
+outfit_database = {
+    "casual": {
+        "red jacket": ["white t-shirt", "blue jeans", "white sneakers", "black crossbody bag"],
+        "denim skirt": ["striped blouse", "tan sandals", "straw hat", "neutral tote bag"]
+    },
+    "formal": {
+        "red jacket": ["black turtleneck", "black trousers", "pointed heels", "gold necklace"],
+        "denim skirt": ["silk blouse", "nude pumps", "pearl earrings", "clutch bag"]
+    },
+    # Add more clothing items and styles here
 }
 
-#andom dog images for error message
-randomdog = ["0f476473-2d8b-415e-b944-483768418a95.jpg",
-              "1bd75c81-f1d7-4e55-9310-a27595fa8762.jpg",
-              "526590d2-8817-4ff0-8c62-fdcba5306d02.jpg",
-              "1326984c-39b0-492c-a773-f120d747a7e2.jpg",
-              "42a98d03-5ed7-4b3b-af89-7c4876cb14c3.jpg",
-              "8b3317ed-2083-42ac-a575-7ae45f9fdc0d.jpg",
-              "ee17f54a-83ac-44a3-8a35-e89ff7153fb4.jpg",
-              "027eef85-ccc1-4a66-8967-5d74f34c8bb4.jpg",
-              "08f5398d-7f89-47da-a5cd-1ed74967dc1f.jpg",
-              "0fd781ff-ec46-4bdc-a4e8-24f18bf07def.jpg",
-              "0fb4aeee-f949-4c7b-a6d8-05bf0736bdd1.jpg",
-              "6edac66e-c0de-4e69-a9d6-b2e6f6f9001b.jpg",
-              "bfb9e165-c643-4993-9b3a-7e73571672a6.jpg"]
-
-def resetconversation():
-    '''
-    Resets Conversation
-    '''
-    st.sessionstate.conversation = []
-    st.sessionstate.messages = []
-    return None
+def generate_outfit_advice(piece, color, style):
+    # Find the clothing piece in the database
+    key = f"{color} {piece}" if f"{color} {piece}" in outfit_database.get(style, {}) else piece
+    suggestions = outfit_database.get(style, {}).get(key, None)
     
-
-
-
-# Define the available models
-models =[key for key in modellinks.keys()]
-
-# Create the sidebar with the dropdown for model selection
-selectedmodel = st.sidebar.selectbox("Select Model", models)
-
-# Create a temperature slider
-tempvalues = st.sidebar.slider('Select a temperature value', 0.0, 1.0, (0.5))
-
-
-#Add reset button to clear conversation
-st.sidebar.button('eset Chat', onclick=resetconversation) #eset button
-
-
-# Create model description
-st.sidebar.write(f"You're now chatting with **{selectedmodel}**")
-st.sidebar.markdown("*Generated content may be inaccurate or false.*")
-st.sidebar.markdown("\n[ypeGP](https://typegpt.net).")
-
-
-if "prevoption" not in st.sessionstate:
-    st.sessionstate.prevoption = selectedmodel
-
-if st.sessionstate.prevoption != selectedmodel:
-    st.sessionstate.messages = []
-    # st.write(f"Changed to {selectedmodel}")
-    st.sessionstate.prevoption = selectedmodel
-    resetconversation()
-
-
-
-#Pull in the model we want to use
-repoid = modellinks[selectedmodel]
-
-
-st.subheader(f'ypeGP.net - {selectedmodel}')
-st.title(f'ChatBot Using {selectedmodel}')
-
-# Set a default model
-if selectedmodel not in st.sessionstate:
-    st.sessionstate[selectedmodel] = modellinks[selectedmodel]
-
-# Initialize chat history
-if "messages" not in st.sessionstate:
-    st.sessionstate.messages = []
-
-
-# Display chat messages from history on app rerun
-for message in st.sessionstate.messages:
-    with st.chatmessage(message["role"]):
-        st.markdown(message["content"])
-
-
-
-
-if prompt := st.chatinput(f"Hi I'm {selectedmodel}, ask me a question"):
-    # Display user message in chat message container
-    with st.chatmessage("user"):
-        st.markdown(prompt)
-    # Add user message to chat history
-    st.sessionstate.messages.append({"role": "user", "content": prompt})
-
-    # Display assistant response in chat message container
-    with st.chatmessage("assistant"):
-        try:
-            # 수정 전 코드 (penAI)
-            # stream = client.chat.completions.create(
-            #     model=modellinks[selectedmodel],
-            #     messages=[
-            #         {"role": m["role"], "content": m["content"]}
-            #         for m in st.sessionstate.messages
-            #     ],
-            #     temperature=tempvalues,#0.5,
-            #     stream=rue,
-            #     maxtokens=3000,
-            # )
-
-            # 수정 후 코드 (gradio & InferenceClient)
-            import gradio as gr
-            from huggingfacehub import InferenceClient
-
-            """
-            For more information on `huggingfacehub` Inference API support, please check the docs: https://huggingface.co/docs/huggingfacehub/v0.22.2/en/guides/inference
-            """
-            client = InferenceClient(repoid)
-
-            def respond(
-                message,
-                history: list[tuple[str, str]],
-                systemmessage,
-                maxtokens,
-                temperature,
-                topp,
-            ):
-                messages = [{"role": "system", "content": systemmessage}]
-
-                for val in history:
-                    if val[0]:
-                        messages.append({"role": "user", "content": val[0]})
-                    if val[1]:
-                        messages.append({"role": "assistant", "content": val[1]})
-
-                messages.append({"role": "user", "content": message})
-
-                response = ""
-
-                for message in client.chatcompletion(
-                    messages,
-                    maxtokens=maxtokens,
-                    stream=rue,
-                    temperature=temperature,
-                    topp=topp,
-                ):
-                    token = message.choices[0].delta.content
-
-                    response += token
-                    yield response
-
-            """
-            For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-            """
-            demo = gr.ChatInterface(
-                respond,
-                additionalinputs=[
-                    gr.extbox(
-                        value="You are a friendly Chatbot.", label="System message"
-                    ),
-                    gr.Slider(
-                        minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"
-                    ),
-                    gr.Slider(
-                        minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="temperature"
-                    ),
-                    gr.Slider(
-                        minimum=0.1,
-                        maximum=1.0,
-                        value=0.95,
-                        step=0.05,
-                        label="op-p (nucleus sampling)",
-                    ),
-                ],
-            )
-
-            response = ""
-
-            for message in demo(
-                prompt,
-                st.sessionstate.messages[1:],
-                "You are a friendly Chatbot.",
-                512,
-                0.7,
-                0.95,
-            ):
-                response += message
-
-        except Exception as e:
-            # st.empty()
-            response = "😵‍💫 Looks like someone unplugged something!\
-                    \n Either the model space is being updated or something is down.\
-                    \n\
-                    \n Try again later. \
-                    \n\
-                    \n Here's a random pic of a 🐶:"
-            st.write(response)
-            randomdogpick = 'https://random.dog/'+ randomdog[np.random.randint(len(randomdog))]
-            st.image(randomdogpick)
-            st.write("his was the error message:")
-            st.write(e)
-
-
-
-
-
-    st.sessionstate.messages.append({"role": "assistant", "content": response})
+    if not suggestions:
+        return "Sorry, I couldn't find an outfit for your request. Try another combination!"
+
+    # Generate outfit advice
+    top, bottom, footwear, accessory = suggestions
+    advice = (f"Here’s how you can style your {color} {piece} for a {style} look:\n"
+              f"- Top: {top}\n- Bottom: {bottom}\n- Footwear: {footwear}\n- Accessory: {accessory}")
+    return advice
+
+def generate_image_prompt(piece, color, style):
+    # Create a text prompt for image generation
+    return f"A {style} outfit featuring a {color} {piece} styled with complementary clothing items and accessories. Modern, fashionable, and cohesive."
+
+def create_outfit_image(prompt):
+    # Generate an image using OpenAI's DALL-E API
+    response = openai.Image.create(
+        prompt=prompt,
+        n=1,
+        size="1024x1024"
+    )
+    return response["data"][0]["url"]
+
+# User inputs
+piece = input("Enter the clothing piece (e.g., 'jacket', 'skirt'): ").lower()
+color = input("Enter the color (e.g., 'red', 'black'): ").lower()
+style = input("Enter the style (e.g., 'casual', 'formal'): ").lower()
+
+# Generate outfit advice and image
+advice = generate_outfit_advice(piece, color, style)
+image_prompt = generate_image_prompt(piece, color, style)
+
+if "Sorry" not in advice:
+    image_url = create_outfit_image(image_prompt)
+    print(advice)
+    print(f"Generated Image: {image_url}")
+else:
+    print(advice)