Update app.py

app.py

@@ -1,68 +1,75 @@
 import streamlit as st
-import agent as ag
+from transformers import pipeline
+from langchain_huggingface import HuggingFacePipeline
+import requests
+from bs4 import BeautifulSoup
+from dotenv import load_dotenv
+from time import sleep
+from dataclasses import dataclass
+from typing import List
 
-# Page styling
-st.markdown(
-    """
-    <style>
-        body {font-family: Arial, sans-serif;}
-        .stButton>button {background-color: #4CAF50; color: white;}
-    </style>
-    """,
-    unsafe_allow_html=True
+load_dotenv()
+
+# Setup HuggingFace pipeline
+hf_pipeline = pipeline(
+    "text2text-generation",
+    model="google/flan-t5-small",
+    max_length=512,
+    temperature=0.7,
 )
+model = HuggingFacePipeline(pipeline=hf_pipeline)
+
+@dataclass
+class Command:
+    update: dict = None
+    goto: str = None
+
+def scrape_startpage(query: str, max_results: int = 3) -> List[dict]:
+    """Scrape search results from Startpage."""
+    url = f"https://www.startpage.com/sp/search?query={query.replace(' ', '+')}"
+    headers = {
+        "User-Agent": "Mozilla/5.0"
+    }
+    for attempt in range(3):
+        try:
+            response = requests.get(url, headers=headers, timeout=10)
+            response.raise_for_status()
+            soup = BeautifulSoup(response.text, "html.parser")
+            results = []
+            for result in soup.find_all("div", class_="result")[:max_results]:
+                title = result.find("h3") or result.find("a")
+                snippet = result.find("p", class_="desc")
+                title_text = title.get_text().strip() if title else "No title"
+                snippet_text = snippet.get_text().strip() if snippet else "No snippet"
+                results.append({"title": title_text, "snippet": snippet_text})
+            return results
+        except Exception as e:
+            print(f"Error: {str(e)}")
+            sleep(2 ** attempt)
+            continue
+    return []
+
+def generate_post(platform, topic, search_results):
+    prompt = f"""
+    You are a social media strategist for a B2B bank. Generate a {platform} post.
+    The post should:
+    - Be engaging but professional.
+    - Provide value to corporate clients.
+    - Focus on {topic}.
+    - Incorporate information from {search_results if search_results else "general knowledge"}.
+    Output as plain text.
+    """
+    return model.invoke(prompt)
 
-# Page title
-st.markdown("<h1 style='text-align: center;'>Instagram and LinkedIn Content Generator</h1>", unsafe_allow_html=True)
+# Streamlit UI
+st.title("Social Media Post Generator for B2B Bank")
 
-# Form for user input
-with st.form("platform"):
-    topic = st.text_input(label="Topic", placeholder="e.g., Small Business Financing")
-    platform = st.radio(label="Select a platform", options=["LinkedIn", "Instagram"])
-    submit_button = st.form_submit_button("Generate Content", use_container_width=True)
+platform = st.selectbox("Select Platform", ["LinkedIn", "Twitter", "Facebook"])
+topic = st.text_input("Enter Topic", "digital transformation in banking")
 
-# Process form submission
-if submit_button:
-    if topic:
-        with st.spinner("Generating content..."):
-            try:
-                # Initialize state for agent.py
-                input_data = {
-                    "topic": topic,
-                    "platform": platform,
-                    "tips": "",
-                    "search_results": [],
-                    "post": "",
-                    "engagement_score": 0,
-                    "tone_score": 0,
-                    "clarity_score": 0,
-                    "image_url": ""
-                }
-                # Run the workflow
-                output = ag.graph.invoke(input_data)
-                
-                # Display results
-                st.markdown("**Generated Post:**")
-                st.markdown(output['post'])
-                
-                # Display image URLs and images
-                if output['image_url']:
-                    st.markdown("**Image URLs:**")
-                    for i, url in enumerate(output['image_url']):
-                        st.markdown(f"[Image {i+1}]({url})")
-                        try:
-                            st.image(url, caption=f"Image {i+1} from Pexels", use_column_width=True)
-                        except:
-                            st.warning(f"Could not display Image {i+1}. Use the URL above.")
-                else:
-                    st.warning("No images were fetched from Pexels.")
-                
-                # Display evaluation scores
-                st.markdown("**Evaluation Scores:**")
-                st.write(f"Engagement: {output['engagement_score']}")
-                st.write(f"Tone: {output['tone_score']}")
-                st.write(f"Clarity: {output['clarity_score']}")
-            except Exception as e:
-                st.error(f"Error generating content: {str(e)}")
-    else:
-        st.error("Please provide a topic.")
+if st.button("Generate Post"):
+    with st.spinner("Scraping data and generating post..."):
+        results = scrape_startpage(topic)
+        post = generate_post(platform, topic, results)
+        st.success("Post Generated!")
+        st.text_area("Generated Post", post, height=200)