Update app.py

app.py

@@ -7,14 +7,14 @@ 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 summarizer import create_brand_html, create_langchain_openai_query, create_screenshot_from_scrap_fly
 from theme import flux_generated_image, flux_generated_image_seed
 import time
 from PIL import Image
 import io
 from streamlit_gsheets import GSheetsConnection
 
-# conn = st.connection("gsheets", type=GSheetsConnection)
+conn = st.connection("gsheets", type=GSheetsConnection)
 
 
 def process_run(st, thread_id, assistant_id):
@@ -40,6 +40,8 @@ def page5():
                                          key="Caption Generation System Prompt")
     caption_prompt = st.text_area("Caption Prompt", value=prompts["CAPTION_PROMPT"],
                                   key="Caption Generation Prompt")
+    brand_summary_prompt = st.text_area("Prompt for Brand Summary", value=prompts["BRAND_SUMMARY_PROMPT"],
+                                        key="Brand summary prompt")
     st.text("Running on Claude")
     col1, col2 = st.columns([1, 2])
     with col1:
@@ -48,6 +50,7 @@ def page5():
             print(st.session_state["system_prompt"])
             st.session_state["caption_system_prompt"] = caption_system_prompt
             st.session_state["caption_prompt"] = caption_prompt
+            st.session_state["brand_prompt"] = brand_summary_prompt
             st.success("Saved your prompts")
     with col2:
         if st.button("Start Testing!"):
@@ -88,9 +91,20 @@ def page2():
     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.text("Using Scrapfly")
+            brand_summary_html = create_screenshot_from_scrap_fly(brand_link)
+            if brand_summary_html["success"]:
+                brand_image_embed = embed_base64_for_claude(brand_summary_html["location"])
+                brand_summary_response = create_claude_image_request_for_image_captioning(
+                    "Fashion expert of understanding brand details",
+                    st.session_state["brand_prompt"], brand_image_embed)
+                st.session_state['brand_summary'] = brand_summary_response
+            else:
+                st.text(f"Scrapfly failed due to: {brand_summary_html["error"]}")
+                st.text("Using Langchain")
+                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.")