Update app.py

app.py

@@ -1,414 +1,414 @@
-import streamlit as st
-import os
-from prompts import prompts
-from constants import JSON_SCHEMA_FOR_GPT, UPDATED_MODEL_ONLY_SCHEMA, JSON_SCHEMA_FOR_LOC_ONLY
-from gpt import runAssistant, checkRunStatus, retrieveThread, createAssistant, saveFileOpenAI, startAssistantThread, \
-    create_chat_completion_request_open_ai_for_summary, addMessageToThread, create_image_completion_request_gpt
-from summarizer import create_brand_html, create_langchain_openai_query
-from theme import flux_generated_image, flux_generated_image_seed
-import time
-from PIL import Image
-import io
-
-
-def process_run(st, thread_id, assistant_id):
-    run_id = runAssistant(thread_id, assistant_id)
-    status = 'running'
-    while status != 'completed':
-        with st.spinner('. . .'):
-            time.sleep(20)
-            status = checkRunStatus(thread_id, run_id)
-    thread_messages = retrieveThread(thread_id)
-    for message in thread_messages:
-        if not message['role'] == 'user':
-            return message["content"]
-        else:
-            pass
-
-
-def page1():
-    st.title("Upload Product")
-    st.markdown("<h2 style='color:#FF5733; font-weight:bold;'>Add a Product</h2>", unsafe_allow_html=True)
-    st.markdown("<p style='color:#444;'>Upload your product images, more images you upload better the AI learns</p>",
-                unsafe_allow_html=True)
-    uploaded_files = st.file_uploader("Upload Images", accept_multiple_files=True, key="uploaded_files_key")
-    product_description = st.text_area("Describe the product", value=st.session_state.get("product_description", ""))
-    col1, col2 = st.columns([1, 2])
-    with col1:
-        if st.button("Save"):
-            st.session_state['uploaded_files'] = uploaded_files
-            st.session_state['product_description'] = product_description
-            st.success("Product information saved!")
-    with col2:
-        if st.button("Add product and move to next page"):
-            if not uploaded_files:
-                st.warning("Please upload at least one image.")
-            elif not product_description:
-                st.warning("Please provide a description for the product.")
-            else:
-                st.session_state['uploaded_files'] = uploaded_files
-                st.session_state['product_description'] = product_description
-                st.session_state['page'] = "Page 2"
-
-
-def page2():
-    st.title("Tell us about your shoot preference")
-    st.markdown("<h3 style='color:#444;'>What are you shooting today?</h3>", unsafe_allow_html=True)
-    shoot_type = st.radio("Select your shoot type:", ["Editorial", "Catalogue"], index=0)
-    st.session_state['shoot_type'] = shoot_type
-    brand_link = st.text_input("Add your brand link:", value=st.session_state.get("brand_link", ""))
-    st.session_state['brand_link'] = brand_link
-    if st.button("Get Brand Summary"):
-        if brand_link:
-            brand_summary_html = create_brand_html(brand_link)
-            brand_summary = create_langchain_openai_query(brand_summary_html)
-            st.session_state['brand_summary'] = brand_summary
-            st.success("Brand summary fetched!")
-        else:
-            st.warning("Please add a brand link.")
-    brand_summary_value = st.session_state.get('brand_summary', "")
-    editable_summary = st.text_area("Brand Summary:", value=brand_summary_value, height=100)
-    st.session_state['brand_summary'] = editable_summary
-    product_info = st.text_area("Tell us something about your product:", value=st.session_state.get("product_info", ""))
-    st.session_state['product_info'] = product_info
-    reference_images = st.file_uploader("Upload Reference Images", accept_multiple_files=True,
-                                        key="reference_images_key")
-    st.session_state['reference_images'] = reference_images
-    if st.button("Give Me Ideas"):
-        st.session_state['page'] = "Page 3"
-
-
-def page3():
-    st.title("Scene Suggestions")
-    st.write("Based on your uploaded product and references!")
-    feedback = st.chat_input("Provide feedback:")
-    if not st.session_state.get("assistant_initialized", False):
-        assistant_id = createAssistant("You are a helpful assistant who is an expert in Fashion Shoots.")
-        updated_prompt = prompts["IDEA_GENERATION_PROMPT"].format(
-            brand_details=st.session_state["brand_summary"],
-            product_details=st.session_state["product_info"],
-            type_of_shoot=st.session_state["shoot_type"],
-            json_schema=JSON_SCHEMA_FOR_GPT,
-            product_name=st.session_state["product_description"]
-        )
-        file_locations = []
-        for uploaded_file in st.session_state['uploaded_files']:
-            bytes_data = uploaded_file.getvalue()
-            image = Image.open(io.BytesIO(bytes_data))
-            image.verify()
-            location = f"temp_image_{uploaded_file.name}"
-            with open(location, "wb") as f:
-                f.write(bytes_data)
-            file_locations.append(location)
-            image.close()
-        for uploaded_file in st.session_state['reference_images']:
-            bytes_data = uploaded_file.getvalue()
-            image = Image.open(io.BytesIO(bytes_data))
-            image.verify()
-            location = f"temp2_image_{uploaded_file.name}"
-            with open(location, "wb") as f:
-                f.write(bytes_data)
-            file_locations.append(location)
-            image.close()
-        file_ids = [saveFileOpenAI(location) for location in file_locations]
-        thread_id = startAssistantThread(file_ids, updated_prompt, "yes", "yes")
-        st.session_state.assistant_id = assistant_id
-        st.session_state.thread_id = thread_id
-        st.session_state.assistant_initialized = True
-        regenerate_images(thread_id, assistant_id)
-    if feedback:
-        if 'images' in st.session_state and 'descriptions' in st.session_state:
-            for image_path in st.session_state['images']:
-                os.remove(image_path)
-            del st.session_state['images']
-            del st.session_state['descriptions']
-            del st.session_state["json_descriptions"]
-        addMessageToThread(st.session_state.thread_id, feedback)
-        regenerate_images(st.session_state.thread_id, st.session_state.assistant_id)
-    selected_image_index = None
-    cols = st.columns(1)
-    for i in range(len(st.session_state["images"])):
-        with cols[i]:
-            st.image(st.session_state.images[i], caption=st.session_state.descriptions[i], use_column_width=True)
-            if st.radio(f"Select {i + 1}", [f"Select Image {i + 1}"], key=f"radio_{i}"):
-                selected_image_index = i
-    if selected_image_index is not None and st.button("Refine"):
-        st.session_state.selected_image_index = selected_image_index
-        st.session_state.selected_image = st.session_state.images[selected_image_index]
-        st.session_state.selected_text = st.session_state.descriptions[selected_image_index]
-        st.session_state['page'] = "Page 4"
-    if st.button("Go Back!"):
-        st.session_state.page = "Page 2"
-
-
-def regenerate_images(thread_id, assistant_id):
-    """Helper function to generate images and descriptions."""
-    response_from_process_list = []
-    for _ in range(1):  # Assuming you generate 1 set of image/description
-        response_from_process = process_run(st, thread_id, assistant_id)
-        response_from_process_list.append(response_from_process)
-
-    summary_list = []
-    for final_response in response_from_process_list:
-        prompt_for_idea_summary = prompts["IDEA_SUMMARY_PROMPT"].format(
-            json_schema=str(final_response)
-        )
-        summary = create_chat_completion_request_open_ai_for_summary(prompt_for_idea_summary, "No")
-        summary_list.append(summary)
-
-    # Generate images based on the summaries
-    flux_generated_theme_image = []
-    for summary in summary_list:
-        theme_image = flux_generated_image(summary)
-        flux_generated_theme_image.append(theme_image["file_name"])
-
-    # Save the new images and descriptions in session state
-    st.session_state["images"] = flux_generated_theme_image
-    st.session_state["descriptions"] = summary_list
-    st.session_state["json_descriptions"] = response_from_process_list
-
-
-def page4():
-    import json
-    selected_theme_text_by_user = st.session_state.json_descriptions[st.session_state.selected_image_index]
-    print(selected_theme_text_by_user)
-    schema_for_model_bg = {"type": "object",
-                           "properties": {
-                               "Model": {
-                                   "type": "string",
-                                   "description": "The model name or identifier."
-                               },
-                               "Background": {
-                                   "type": "string",
-                                   "description": "Description or type of the background."
-                               }},
-                           "required": ["Model", "Background"],
-                           "additionalProperties": False
-                           }
-    prompt_to_get_details = (f"You are provided with a brief of a Fashion Shoot : "
-                             f"{st.session_state["json_descriptions"]}).\n Now provide me a JSON which will"
-                             f"have two keys ```Model``` and ```Background```. Provide all detail's"
-                             f"present about model and background in the brief provided by you. Just provide a "
-                             f"natural langauge description. I will use it as description of model and "
-                             f"background needed by the brand Output JSON following the schema")
-    response_from_open_ai = create_chat_completion_request_open_ai_for_summary(prompt_to_get_details,
-                                                                               schema_name="model_bg",
-                                                                               json_schema=schema_for_model_bg,
-                                                                               json_mode="yes")
-    json_response_from_open_ai = json.loads(response_from_open_ai)
-    with (st.sidebar):
-        st.title(st.session_state["product_info"])
-        st.write("Product Image")
-        st.image(st.session_state['uploaded_files'])
-        st.text("Scene Suggestion:")
-        st.image(st.session_state.selected_image)
-        dimensions = st.text_input("Enter Dimensions e.g 3:4, 1:2", key="Dimensions")
-        seed = st.selectbox(
-            "Seed Preference",
-            ("Fixed", "Random"),
-        )
-        if seed == "Fixed":
-            seed_number = st.number_input("Enter an integer:", min_value=1, max_value=100000, value=10, step=1)
-        else:
-            seed_number = 0
-            st.text("Thanks will take care")
-        model_preference = st.selectbox(
-            "Model Preference",
-            ("Create Own/Edit Pre-filled", "Ideas", "Upload Reference"),
-        )
-        if model_preference == "Create Own/Edit Pre-filled":
-            pre_filled_model_details = st.text_area("Model Idea", value=json_response_from_open_ai["Model"],
-                                                    key="Model Idea")
-        elif model_preference == "Ideas":
-            prompt_to_generate_idea = ("Your task is to create model ideas for shoot of a  product of a brand. "
-                                       "The details about the brand: ```{brand_details}.\n The product: {product_name},"
-                                       "which is: ```{product_details}```.\n Reference images for the product and "
-                                       "brands shoot idea is already provided with you. Additionally brand wants to "
-                                       "have a ```{type_of_shoot}``` of the model. Now based on all provided details, "
-                                       "think step by step and provide your ideas about what type of model the brand"
-                                       "should need based on mentioned JSON format. Also provide a combined prompt "
-                                       "which the brand will use to create a shoot image. While creating the "
-                                       "combined prompt as mentioned in the JSON schema, do not miss any details you"
-                                       " mentioned in the JSON.")
-            updated_model_idea_gen_prompt = prompt_to_generate_idea.format(
-                brand_details=st.session_state["brand_summary"],
-                product_details=st.session_state["product_info"],
-                type_of_shoot=st.session_state["shoot_type"],
-                product_name=st.session_state["product_description"]
-
-            )
-            response_for_only_model = create_chat_completion_request_open_ai_for_summary(updated_model_idea_gen_prompt
-                                                                                         , schema_name="model_only",
-                                                                                         json_schema=
-                                                                                         UPDATED_MODEL_ONLY_SCHEMA,
-                                                                                         json_mode="yes")
-            pre_filled_model_details = st.text_area("Model Idea", value=response_for_only_model,
-                                                    key="Model Idea")
-        else:
-            uploaded_files = st.file_uploader("Upload one Model Reference Image here",
-                                              accept_multiple_files=False, key="uploader")
-            bytes_data = uploaded_files.getvalue()
-            image = Image.open(io.BytesIO(bytes_data))
-            image.verify()
-            location = f"temp_image_{uploaded_files.name}"
-            with open(location, "wb") as f:
-                f.write(bytes_data)
-            image.close()
-            prompt_to_generate_idea = ("Follow this JSON Schema : {json_schema_model_only}."
-                                       "Your task is to create model ideas for shoot of a  product of a brand. "
-                                       "The details about the brand: ```{brand_details}.\n The product: {product_name},"
-                                       "which is: ```{product_details}```.\n Reference images for the product and "
-                                       "brands shoot idea is already provided with you. Additionally brand wants to "
-                                       "have a ```{type_of_shoot}``` of the model. Now based on all provided details, "
-                                       "think step by step and provide your ideas about what type of model the brand"
-                                       "should need based on mentioned JSON format. Also provide a combined prompt "
-                                       "which the brand will use to create a shoot image. While creating the "
-                                       "combined prompt as mentioned in the JSON schema, do not miss any details you"
-                                       " mentioned in the JSON.")
-            updated_model_idea_gen_prompt = prompt_to_generate_idea.format(
-                json_schema_model_only=UPDATED_MODEL_ONLY_SCHEMA,
-                brand_details=st.session_state["brand_summary"],
-                product_details=st.session_state["product_info"],
-                type_of_shoot=st.session_state["shoot_type"],
-                product_name=st.session_state["product_description"]
-
-            )
-            json_response = create_image_completion_request_gpt(location, updated_model_idea_gen_prompt)
-            pre_filled_model_details = st.text_area("Model Idea", value=json_response,
-                                                    key="Model Idea")
-        background_preference = st.selectbox(
-            "Background Preference",
-            ("Create Own/Edit Pre-filled", "Ideas", "Upload Reference"),
-        )
-        if background_preference == "Create Own/Edit Pre-filled":
-            pre_filled_background_details = st.text_area("Background Idea",
-                                                         value=json_response_from_open_ai["Background"],
-                                                         key="Background Idea")
-        elif background_preference == "Ideas":
-            prompt_to_generate_idea = ("Follow this JSON Schema : {json_schema_background_only}."
-                                       "Your task is to create location/background ideas for shoot of a  "
-                                       "product of a brand. "
-                                       "The details about the brand: ```{brand_details}.\n The product: {product_name},"
-                                       "which is: ```{product_details}```.\n Reference images for the product and "
-                                       "brands shoot idea is already provided with you. Additionally brand wants to "
-                                       "have a ```{type_of_shoot}``` of the model. Now based on all provided details, "
-                                       "think step by step and provide your ideas about what type of location the brand"
-                                       "should need based on mentioned JSON format. Also provide a combined prompt "
-                                       "which the brand will use to create a shoot image. While creating the "
-                                       "combined prompt as mentioned in the JSON schema, do not miss any details you"
-                                       " mentioned in the JSON.")
-            updated_bg_idea_gen_prompt = prompt_to_generate_idea.format(
-                json_schema_background_only=JSON_SCHEMA_FOR_LOC_ONLY,
-                brand_details=st.session_state["brand_summary"],
-                product_details=st.session_state["product_info"],
-                type_of_shoot=st.session_state["shoot_type"],
-                product_name=st.session_state["product_description"]
-
-            )
-            response_for_only_bg = create_chat_completion_request_open_ai_for_summary(updated_bg_idea_gen_prompt,
-                                                                                      schema_name="bg_o",
-                                                                                      json_schema=JSON_SCHEMA_FOR_LOC_ONLY,
-                                                                                      json_mode="yes")
-            pre_filled_background_details = st.text_area("Background Idea", value=response_for_only_bg,
-                                                         key="Background Idea")
-        else:
-            uploaded_files = st.file_uploader("Upload one Background Reference Image here",
-                                              accept_multiple_files=False, key="uploader")
-            bytes_data = uploaded_files.getvalue()
-            image = Image.open(io.BytesIO(bytes_data))
-            image.verify()
-            location = f"temp2_image_{uploaded_files.name}"
-            with open(location, "wb") as f:
-                f.write(bytes_data)
-            image.close()
-            prompt_to_generate_idea = ("Follow this JSON Schema : {json_schema_bg_only}."
-                                       "Your task is to create Background/Location ideas for shoot of a  "
-                                       "product of a brand. "
-                                       "The details about the brand: ```{brand_details}.\n The product: {product_name},"
-                                       "which is: ```{product_details}```.\n Reference images for the product and "
-                                       "brands shoot idea is already provided with you. Additionally brand wants to "
-                                       "have a ```{type_of_shoot}``` of the model. Now based on all provided details, "
-                                       "think step by step and provide your ideas about what type of location the brand"
-                                       "should need based on mentioned JSON format. Also provide a combined prompt "
-                                       "which the brand will use to create a shoot image. While creating the "
-                                       "combined prompt as mentioned in the JSON schema, do not miss any details you"
-                                       " mentioned in the JSON.")
-            updated_bg_idea_gen_prompt = prompt_to_generate_idea.format(
-                json_schema_bg_only=JSON_SCHEMA_FOR_LOC_ONLY,
-                brand_details=st.session_state["brand_summary"],
-                product_details=st.session_state["product_info"],
-                type_of_shoot=st.session_state["shoot_type"],
-                product_name=st.session_state["product_description"]
-
-            )
-            json_response = create_image_completion_request_gpt(location, updated_bg_idea_gen_prompt)
-            pre_filled_background_details = st.text_area("Background Idea", value=json_response,
-                                                         key="Background Idea")
-        start_chat = st.button("Start Chat")
-    if "mood_chat_messages" not in st.session_state:
-        st.session_state["mood_chat_messages"] = []
-    if seed and dimensions and model_preference and background_preference:
-        if start_chat:
-            final_mood_board_image_prompt = prompts["FINAL_PROMPT_GENERATION"].format(
-                brand_details=st.session_state["brand_summary"],
-                product_details=st.session_state["product_info"],
-                type_of_shoot=st.session_state["shoot_type"],
-                product_name=st.session_state["product_description"],
-                model_details=pre_filled_model_details,
-                location_details=pre_filled_background_details,
-                theme_details=str(selected_theme_text_by_user),
-                chat_history=str(st.session_state["mood_chat_messages"])
-            )
-            prompt_for_flux_mood_board = create_chat_completion_request_open_ai_for_summary(
-                final_mood_board_image_prompt, "No", system_message=prompts["SYSTEM_PROMPT_FOR_MOOD_BOARD"])
-            if seed == "Fixed":
-                generated_flux_image = flux_generated_image_seed(prompt_for_flux_mood_board, seed_number, dimensions)
-            else:
-                generated_flux_image = flux_generated_image(prompt_for_flux_mood_board)
-            st.session_state["mood_chat_messages"].append({
-                "role": "AI",
-                "message": prompt_for_flux_mood_board,
-                "image": generated_flux_image["file_name"]
-            })
-        # for message in st.session_state["mood_chat_messages"]:
-          #  if message["role"] == "AI":
-           #     st.write(f"Caimera AI: {message['message']}")
-            #    st.image(message['image'])
-            #else:
-             #   st.write(f"**You**: {message['message']}")
-        user_input = st.chat_input("Type your message here...")
-        if user_input:
-            st.session_state["mood_chat_messages"].append({"role": "User", "message": user_input})
-            prompt_for_flux_mood_board_n = create_chat_completion_request_open_ai_for_summary(
-                user_input, "No", system_message=prompts["SYSTEM_PROMPT_FOR_MOOD_BOARD"])
-            if seed == "Fixed":
-                generated_flux_image_n = flux_generated_image_seed(prompt_for_flux_mood_board_n, seed_number,
-                                                                   dimensions)
-            else:
-                generated_flux_image_n = flux_generated_image(prompt_for_flux_mood_board_n)
-            st.session_state["mood_chat_messages"].append({
-                "role": "AI",
-                "message": prompt_for_flux_mood_board_n,
-                "image": generated_flux_image_n["file_name"]
-            })
-        for message in st.session_state["mood_chat_messages"]:
-            if message["role"] == "AI":
-                st.write(f"**AI**: {message['message']}")
-                st.image(message['image'])
-            else:
-                st.write(f"**You**: {message['message']}")
-        print(seed_number)
-
-
-if 'page' not in st.session_state:
-    st.session_state.page = "Page 1"
-
-# Routing between pages
-if st.session_state.page == "Page 1":
-    page1()
-elif st.session_state.page == "Page 2":
-    page2()
-elif st.session_state.page == "Page 3":
-    page3()
-elif st.session_state.page == "Page 4":
-    page4()
+import streamlit as st
+import os
+from prompts import prompts
+from constants import JSON_SCHEMA_FOR_GPT, UPDATED_MODEL_ONLY_SCHEMA, JSON_SCHEMA_FOR_LOC_ONLY
+from gpt import runAssistant, checkRunStatus, retrieveThread, createAssistant, saveFileOpenAI, startAssistantThread, \
+    create_chat_completion_request_open_ai_for_summary, addMessageToThread, create_image_completion_request_gpt
+from summarizer import create_brand_html, create_langchain_openai_query
+from theme import flux_generated_image, flux_generated_image_seed
+import time
+from PIL import Image
+import io
+
+
+def process_run(st, thread_id, assistant_id):
+    run_id = runAssistant(thread_id, assistant_id)
+    status = 'running'
+    while status != 'completed':
+        with st.spinner('. . .'):
+            time.sleep(20)
+            status = checkRunStatus(thread_id, run_id)
+    thread_messages = retrieveThread(thread_id)
+    for message in thread_messages:
+        if not message['role'] == 'user':
+            return message["content"]
+        else:
+            pass
+
+
+def page1():
+    st.title("Upload Product")
+    st.markdown("<h2 style='color:#FF5733; font-weight:bold;'>Add a Product</h2>", unsafe_allow_html=True)
+    st.markdown("<p style='color:#444;'>Upload your product images, more images you upload better the AI learns</p>",
+                unsafe_allow_html=True)
+    uploaded_files = st.file_uploader("Upload Images", accept_multiple_files=True, key="uploaded_files_key")
+    product_description = st.text_area("Describe the product", value=st.session_state.get("product_description", ""))
+    col1, col2 = st.columns([1, 2])
+    with col1:
+        if st.button("Save"):
+            st.session_state['uploaded_files'] = uploaded_files
+            st.session_state['product_description'] = product_description
+            st.success("Product information saved!")
+    with col2:
+        if st.button("Add product and move to next page"):
+            if not uploaded_files:
+                st.warning("Please upload at least one image.")
+            elif not product_description:
+                st.warning("Please provide a description for the product.")
+            else:
+                st.session_state['uploaded_files'] = uploaded_files
+                st.session_state['product_description'] = product_description
+                st.session_state['page'] = "Page 2"
+
+
+def page2():
+    st.title("Tell us about your shoot preference")
+    st.markdown("<h3 style='color:#444;'>What are you shooting today?</h3>", unsafe_allow_html=True)
+    shoot_type = st.radio("Select your shoot type:", ["Editorial", "Catalogue"], index=0)
+    st.session_state['shoot_type'] = shoot_type
+    brand_link = st.text_input("Add your brand link:", value=st.session_state.get("brand_link", ""))
+    st.session_state['brand_link'] = brand_link
+    if st.button("Get Brand Summary"):
+        if brand_link:
+            brand_summary_html = create_brand_html(brand_link)
+            brand_summary = create_langchain_openai_query(brand_summary_html)
+            st.session_state['brand_summary'] = brand_summary
+            st.success("Brand summary fetched!")
+        else:
+            st.warning("Please add a brand link.")
+    brand_summary_value = st.session_state.get('brand_summary', "")
+    editable_summary = st.text_area("Brand Summary:", value=brand_summary_value, height=100)
+    st.session_state['brand_summary'] = editable_summary
+    product_info = st.text_area("Tell us something about your product:", value=st.session_state.get("product_info", ""))
+    st.session_state['product_info'] = product_info
+    reference_images = st.file_uploader("Upload Reference Images", accept_multiple_files=True,
+                                        key="reference_images_key")
+    st.session_state['reference_images'] = reference_images
+    if st.button("Give Me Ideas"):
+        st.session_state['page'] = "Page 3"
+
+
+def page3():
+    st.title("Scene Suggestions")
+    st.write("Based on your uploaded product and references!")
+    feedback = st.chat_input("Provide feedback:")
+    if not st.session_state.get("assistant_initialized", False):
+        assistant_id = createAssistant("You are a helpful assistant who is an expert in Fashion Shoots.")
+        updated_prompt = prompts["IDEA_GENERATION_PROMPT"].format(
+            brand_details=st.session_state["brand_summary"],
+            product_details=st.session_state["product_info"],
+            type_of_shoot=st.session_state["shoot_type"],
+            json_schema=JSON_SCHEMA_FOR_GPT,
+            product_name=st.session_state["product_description"]
+        )
+        file_locations = []
+        for uploaded_file in st.session_state['uploaded_files']:
+            bytes_data = uploaded_file.getvalue()
+            image = Image.open(io.BytesIO(bytes_data))
+            image.verify()
+            location = f"temp_image_{uploaded_file.name}"
+            with open(location, "wb") as f:
+                f.write(bytes_data)
+            file_locations.append(location)
+            image.close()
+        for uploaded_file in st.session_state['reference_images']:
+            bytes_data = uploaded_file.getvalue()
+            image = Image.open(io.BytesIO(bytes_data))
+            image.verify()
+            location = f"temp2_image_{uploaded_file.name}"
+            with open(location, "wb") as f:
+                f.write(bytes_data)
+            file_locations.append(location)
+            image.close()
+        file_ids = [saveFileOpenAI(location) for location in file_locations]
+        thread_id = startAssistantThread(file_ids, updated_prompt, "yes", "yes")
+        st.session_state.assistant_id = assistant_id
+        st.session_state.thread_id = thread_id
+        st.session_state.assistant_initialized = True
+        regenerate_images(thread_id, assistant_id)
+    if feedback:
+        if 'images' in st.session_state and 'descriptions' in st.session_state:
+            for image_path in st.session_state['images']:
+                os.remove(image_path)
+            del st.session_state['images']
+            del st.session_state['descriptions']
+            del st.session_state["json_descriptions"]
+        addMessageToThread(st.session_state.thread_id, feedback)
+        regenerate_images(st.session_state.thread_id, st.session_state.assistant_id)
+    selected_image_index = None
+    cols = st.columns(1)
+    for i in range(len(st.session_state["images"])):
+        with cols[i]:
+            st.image(st.session_state.images[i], caption=st.session_state.descriptions[i], use_column_width=True)
+            if st.radio(f"Select {i + 1}", [f"Select Image {i + 1}"], key=f"radio_{i}"):
+                selected_image_index = i
+    if selected_image_index is not None and st.button("Refine"):
+        st.session_state.selected_image_index = selected_image_index
+        st.session_state.selected_image = st.session_state.images[selected_image_index]
+        st.session_state.selected_text = st.session_state.descriptions[selected_image_index]
+        st.session_state['page'] = "Page 4"
+    if st.button("Go Back!"):
+        st.session_state.page = "Page 2"
+
+
+def regenerate_images(thread_id, assistant_id):
+    """Helper function to generate images and descriptions."""
+    response_from_process_list = []
+    for _ in range(1):  # Assuming you generate 1 set of image/description
+        response_from_process = process_run(st, thread_id, assistant_id)
+        response_from_process_list.append(response_from_process)
+
+    summary_list = []
+    for final_response in response_from_process_list:
+        prompt_for_idea_summary = prompts["IDEA_SUMMARY_PROMPT"].format(
+            json_schema=str(final_response)
+        )
+        summary = create_chat_completion_request_open_ai_for_summary(prompt_for_idea_summary, "No")
+        summary_list.append(summary)
+
+    # Generate images based on the summaries
+    flux_generated_theme_image = []
+    for summary in summary_list:
+        theme_image = flux_generated_image(summary)
+        flux_generated_theme_image.append(theme_image["file_name"])
+
+    # Save the new images and descriptions in session state
+    st.session_state["images"] = flux_generated_theme_image
+    st.session_state["descriptions"] = summary_list
+    st.session_state["json_descriptions"] = response_from_process_list
+
+
+def page4():
+    import json
+    selected_theme_text_by_user = st.session_state.json_descriptions[st.session_state.selected_image_index]
+    print(selected_theme_text_by_user)
+    schema_for_model_bg = {"type": "object",
+                           "properties": {
+                               "Model": {
+                                   "type": "string",
+                                   "description": "The model name or identifier."
+                               },
+                               "Background": {
+                                   "type": "string",
+                                   "description": "Description or type of the background."
+                               }},
+                           "required": ["Model", "Background"],
+                           "additionalProperties": False
+                           }
+    prompt_to_get_details = (f"You are provided with a brief of a Fashion Shoot : "
+                             f"{st.session_state[\"json_descriptions\"]}.\n Now provide me a JSON which will"
+                             f"have two keys ```Model``` and ```Background```. Provide all detail's"
+                             f"present about model and background in the brief provided by you. Just provide a "
+                             f"natural langauge description. I will use it as description of model and "
+                             f"background needed by the brand Output JSON following the schema")
+    response_from_open_ai = create_chat_completion_request_open_ai_for_summary(prompt_to_get_details,
+                                                                               schema_name="model_bg",
+                                                                               json_schema=schema_for_model_bg,
+                                                                               json_mode="yes")
+    json_response_from_open_ai = json.loads(response_from_open_ai)
+    with (st.sidebar):
+        st.title(st.session_state["product_info"])
+        st.write("Product Image")
+        st.image(st.session_state['uploaded_files'])
+        st.text("Scene Suggestion:")
+        st.image(st.session_state.selected_image)
+        dimensions = st.text_input("Enter Dimensions e.g 3:4, 1:2", key="Dimensions")
+        seed = st.selectbox(
+            "Seed Preference",
+            ("Fixed", "Random"),
+        )
+        if seed == "Fixed":
+            seed_number = st.number_input("Enter an integer:", min_value=1, max_value=100000, value=10, step=1)
+        else:
+            seed_number = 0
+            st.text("Thanks will take care")
+        model_preference = st.selectbox(
+            "Model Preference",
+            ("Create Own/Edit Pre-filled", "Ideas", "Upload Reference"),
+        )
+        if model_preference == "Create Own/Edit Pre-filled":
+            pre_filled_model_details = st.text_area("Model Idea", value=json_response_from_open_ai["Model"],
+                                                    key="Model Idea")
+        elif model_preference == "Ideas":
+            prompt_to_generate_idea = ("Your task is to create model ideas for shoot of a  product of a brand. "
+                                       "The details about the brand: ```{brand_details}.\n The product: {product_name},"
+                                       "which is: ```{product_details}```.\n Reference images for the product and "
+                                       "brands shoot idea is already provided with you. Additionally brand wants to "
+                                       "have a ```{type_of_shoot}``` of the model. Now based on all provided details, "
+                                       "think step by step and provide your ideas about what type of model the brand"
+                                       "should need based on mentioned JSON format. Also provide a combined prompt "
+                                       "which the brand will use to create a shoot image. While creating the "
+                                       "combined prompt as mentioned in the JSON schema, do not miss any details you"
+                                       " mentioned in the JSON.")
+            updated_model_idea_gen_prompt = prompt_to_generate_idea.format(
+                brand_details=st.session_state["brand_summary"],
+                product_details=st.session_state["product_info"],
+                type_of_shoot=st.session_state["shoot_type"],
+                product_name=st.session_state["product_description"]
+
+            )
+            response_for_only_model = create_chat_completion_request_open_ai_for_summary(updated_model_idea_gen_prompt
+                                                                                         , schema_name="model_only",
+                                                                                         json_schema=
+                                                                                         UPDATED_MODEL_ONLY_SCHEMA,
+                                                                                         json_mode="yes")
+            pre_filled_model_details = st.text_area("Model Idea", value=response_for_only_model,
+                                                    key="Model Idea")
+        else:
+            uploaded_files = st.file_uploader("Upload one Model Reference Image here",
+                                              accept_multiple_files=False, key="uploader")
+            bytes_data = uploaded_files.getvalue()
+            image = Image.open(io.BytesIO(bytes_data))
+            image.verify()
+            location = f"temp_image_{uploaded_files.name}"
+            with open(location, "wb") as f:
+                f.write(bytes_data)
+            image.close()
+            prompt_to_generate_idea = ("Follow this JSON Schema : {json_schema_model_only}."
+                                       "Your task is to create model ideas for shoot of a  product of a brand. "
+                                       "The details about the brand: ```{brand_details}.\n The product: {product_name},"
+                                       "which is: ```{product_details}```.\n Reference images for the product and "
+                                       "brands shoot idea is already provided with you. Additionally brand wants to "
+                                       "have a ```{type_of_shoot}``` of the model. Now based on all provided details, "
+                                       "think step by step and provide your ideas about what type of model the brand"
+                                       "should need based on mentioned JSON format. Also provide a combined prompt "
+                                       "which the brand will use to create a shoot image. While creating the "
+                                       "combined prompt as mentioned in the JSON schema, do not miss any details you"
+                                       " mentioned in the JSON.")
+            updated_model_idea_gen_prompt = prompt_to_generate_idea.format(
+                json_schema_model_only=UPDATED_MODEL_ONLY_SCHEMA,
+                brand_details=st.session_state["brand_summary"],
+                product_details=st.session_state["product_info"],
+                type_of_shoot=st.session_state["shoot_type"],
+                product_name=st.session_state["product_description"]
+
+            )
+            json_response = create_image_completion_request_gpt(location, updated_model_idea_gen_prompt)
+            pre_filled_model_details = st.text_area("Model Idea", value=json_response,
+                                                    key="Model Idea")
+        background_preference = st.selectbox(
+            "Background Preference",
+            ("Create Own/Edit Pre-filled", "Ideas", "Upload Reference"),
+        )
+        if background_preference == "Create Own/Edit Pre-filled":
+            pre_filled_background_details = st.text_area("Background Idea",
+                                                         value=json_response_from_open_ai["Background"],
+                                                         key="Background Idea")
+        elif background_preference == "Ideas":
+            prompt_to_generate_idea = ("Follow this JSON Schema : {json_schema_background_only}."
+                                       "Your task is to create location/background ideas for shoot of a  "
+                                       "product of a brand. "
+                                       "The details about the brand: ```{brand_details}.\n The product: {product_name},"
+                                       "which is: ```{product_details}```.\n Reference images for the product and "
+                                       "brands shoot idea is already provided with you. Additionally brand wants to "
+                                       "have a ```{type_of_shoot}``` of the model. Now based on all provided details, "
+                                       "think step by step and provide your ideas about what type of location the brand"
+                                       "should need based on mentioned JSON format. Also provide a combined prompt "
+                                       "which the brand will use to create a shoot image. While creating the "
+                                       "combined prompt as mentioned in the JSON schema, do not miss any details you"
+                                       " mentioned in the JSON.")
+            updated_bg_idea_gen_prompt = prompt_to_generate_idea.format(
+                json_schema_background_only=JSON_SCHEMA_FOR_LOC_ONLY,
+                brand_details=st.session_state["brand_summary"],
+                product_details=st.session_state["product_info"],
+                type_of_shoot=st.session_state["shoot_type"],
+                product_name=st.session_state["product_description"]
+
+            )
+            response_for_only_bg = create_chat_completion_request_open_ai_for_summary(updated_bg_idea_gen_prompt,
+                                                                                      schema_name="bg_o",
+                                                                                      json_schema=JSON_SCHEMA_FOR_LOC_ONLY,
+                                                                                      json_mode="yes")
+            pre_filled_background_details = st.text_area("Background Idea", value=response_for_only_bg,
+                                                         key="Background Idea")
+        else:
+            uploaded_files = st.file_uploader("Upload one Background Reference Image here",
+                                              accept_multiple_files=False, key="uploader")
+            bytes_data = uploaded_files.getvalue()
+            image = Image.open(io.BytesIO(bytes_data))
+            image.verify()
+            location = f"temp2_image_{uploaded_files.name}"
+            with open(location, "wb") as f:
+                f.write(bytes_data)
+            image.close()
+            prompt_to_generate_idea = ("Follow this JSON Schema : {json_schema_bg_only}."
+                                       "Your task is to create Background/Location ideas for shoot of a  "
+                                       "product of a brand. "
+                                       "The details about the brand: ```{brand_details}.\n The product: {product_name},"
+                                       "which is: ```{product_details}```.\n Reference images for the product and "
+                                       "brands shoot idea is already provided with you. Additionally brand wants to "
+                                       "have a ```{type_of_shoot}``` of the model. Now based on all provided details, "
+                                       "think step by step and provide your ideas about what type of location the brand"
+                                       "should need based on mentioned JSON format. Also provide a combined prompt "
+                                       "which the brand will use to create a shoot image. While creating the "
+                                       "combined prompt as mentioned in the JSON schema, do not miss any details you"
+                                       " mentioned in the JSON.")
+            updated_bg_idea_gen_prompt = prompt_to_generate_idea.format(
+                json_schema_bg_only=JSON_SCHEMA_FOR_LOC_ONLY,
+                brand_details=st.session_state["brand_summary"],
+                product_details=st.session_state["product_info"],
+                type_of_shoot=st.session_state["shoot_type"],
+                product_name=st.session_state["product_description"]
+
+            )
+            json_response = create_image_completion_request_gpt(location, updated_bg_idea_gen_prompt)
+            pre_filled_background_details = st.text_area("Background Idea", value=json_response,
+                                                         key="Background Idea")
+        start_chat = st.button("Start Chat")
+    if "mood_chat_messages" not in st.session_state:
+        st.session_state["mood_chat_messages"] = []
+    if seed and dimensions and model_preference and background_preference:
+        if start_chat:
+            final_mood_board_image_prompt = prompts["FINAL_PROMPT_GENERATION"].format(
+                brand_details=st.session_state["brand_summary"],
+                product_details=st.session_state["product_info"],
+                type_of_shoot=st.session_state["shoot_type"],
+                product_name=st.session_state["product_description"],
+                model_details=pre_filled_model_details,
+                location_details=pre_filled_background_details,
+                theme_details=str(selected_theme_text_by_user),
+                chat_history=str(st.session_state["mood_chat_messages"])
+            )
+            prompt_for_flux_mood_board = create_chat_completion_request_open_ai_for_summary(
+                final_mood_board_image_prompt, "No", system_message=prompts["SYSTEM_PROMPT_FOR_MOOD_BOARD"])
+            if seed == "Fixed":
+                generated_flux_image = flux_generated_image_seed(prompt_for_flux_mood_board, seed_number, dimensions)
+            else:
+                generated_flux_image = flux_generated_image(prompt_for_flux_mood_board)
+            st.session_state["mood_chat_messages"].append({
+                "role": "AI",
+                "message": prompt_for_flux_mood_board,
+                "image": generated_flux_image["file_name"]
+            })
+        # for message in st.session_state["mood_chat_messages"]:
+          #  if message["role"] == "AI":
+           #     st.write(f"Caimera AI: {message['message']}")
+            #    st.image(message['image'])
+            #else:
+             #   st.write(f"**You**: {message['message']}")
+        user_input = st.chat_input("Type your message here...")
+        if user_input:
+            st.session_state["mood_chat_messages"].append({"role": "User", "message": user_input})
+            prompt_for_flux_mood_board_n = create_chat_completion_request_open_ai_for_summary(
+                user_input, "No", system_message=prompts["SYSTEM_PROMPT_FOR_MOOD_BOARD"])
+            if seed == "Fixed":
+                generated_flux_image_n = flux_generated_image_seed(prompt_for_flux_mood_board_n, seed_number,
+                                                                   dimensions)
+            else:
+                generated_flux_image_n = flux_generated_image(prompt_for_flux_mood_board_n)
+            st.session_state["mood_chat_messages"].append({
+                "role": "AI",
+                "message": prompt_for_flux_mood_board_n,
+                "image": generated_flux_image_n["file_name"]
+            })
+        for message in st.session_state["mood_chat_messages"]:
+            if message["role"] == "AI":
+                st.write(f"**AI**: {message['message']}")
+                st.image(message['image'])
+            else:
+                st.write(f"**You**: {message['message']}")
+        print(seed_number)
+
+
+if 'page' not in st.session_state:
+    st.session_state.page = "Page 1"
+
+# Routing between pages
+if st.session_state.page == "Page 1":
+    page1()
+elif st.session_state.page == "Page 2":
+    page2()
+elif st.session_state.page == "Page 3":
+    page3()
+elif st.session_state.page == "Page 4":
+    page4()