App init

src/streamlit_app.py

@@ -1,40 +1,323 @@
-import altair as alt
-import numpy as np
-import pandas as pd
 import streamlit as st
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from peft import PeftModel
+import torch
+from PIL import Image, ImageDraw, ImageFont
+import io
+import base64
+import textwrap
+import urllib.parse
 
-"""
-# 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])),
-    ))
+@st.cache_resource
+def load_model():
+    """Load and cache the model"""
+    base_model = "mistralai/Mistral-7B-Instruct-v0.2"
+    adapter_model = "phxdev/corporate-synergy-bot-7b"
+    
+    tokenizer = AutoTokenizer.from_pretrained(base_model)
+    model = AutoModelForCausalLM.from_pretrained(
+        base_model,
+        torch_dtype=torch.float16,
+        device_map="auto"
+    )
+    model = PeftModel.from_pretrained(model, adapter_model)
+    return tokenizer, model
+
+tokenizer, model = load_model()
+
+def transform_text(text, mode="To Corporate", domain="general", seniority="mid"):
+    """Transform text between casual and corporate speak"""
+    
+    if mode == "To Corporate":
+        instruction = f"Transform to {domain} corporate speak (seniority: {seniority})"
+    else:
+        instruction = "Translate corporate speak to plain English"
+    
+    prompt = f"""### Instruction: {instruction}
+### Input: {text}
+### Response:"""
+    
+    inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=512)
+    
+    with torch.no_grad():
+        outputs = model.generate(
+            **inputs,
+            max_new_tokens=150,
+            temperature=0.7,
+            top_p=0.9,
+            do_sample=True,
+            pad_token_id=tokenizer.eos_token_id
+        )
+    
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response.split("### Response:")[-1].strip()
+
+def create_shareable_card(input_text, output_text, mode, domain, seniority):
+    """Create a shareable image card with the transformation"""
+    # Card dimensions
+    width, height = 800, 600
+    
+    # Colors
+    bg_color = "#f8f9fa"
+    primary_color = "#2c3e50"
+    secondary_color = "#3498db"
+    text_color = "#2c3e50"
+    
+    # Create image
+    img = Image.new('RGB', (width, height), bg_color)
+    draw = ImageDraw.Draw(img)
+    
+    try:
+        # Try to load a nicer font
+        title_font = ImageFont.truetype("arial.ttf", 28)
+        subtitle_font = ImageFont.truetype("arial.ttf", 18)
+        text_font = ImageFont.truetype("arial.ttf", 16)
+        small_font = ImageFont.truetype("arial.ttf", 14)
+    except:
+        # Fallback to default font
+        title_font = ImageFont.load_default()
+        subtitle_font = ImageFont.load_default()
+        text_font = ImageFont.load_default()
+        small_font = ImageFont.load_default()
+    
+    # Title
+    title = "🏢 Corporate Synergy Bot"
+    title_bbox = draw.textbbox((0, 0), title, font=title_font)
+    title_width = title_bbox[2] - title_bbox[0]
+    draw.text(((width - title_width) // 2, 30), title, fill=primary_color, font=title_font)
+    
+    # Mode indicator
+    mode_text = f"{mode} • {domain.title()} • {seniority.title()}"
+    mode_bbox = draw.textbbox((0, 0), mode_text, font=subtitle_font)
+    mode_width = mode_bbox[2] - mode_bbox[0]
+    draw.text(((width - mode_width) // 2, 80), mode_text, fill=secondary_color, font=subtitle_font)
+    
+    # Input section
+    draw.text((50, 140), "INPUT:", fill=primary_color, font=subtitle_font)
+    
+    # Wrap input text
+    input_lines = textwrap.wrap(input_text, width=70)
+    y_pos = 170
+    for line in input_lines[:4]:  # Max 4 lines
+        draw.text((50, y_pos), line, fill=text_color, font=text_font)
+        y_pos += 25
+    
+    # Arrow
+    arrow = "⬇️"
+    arrow_bbox = draw.textbbox((0, 0), arrow, font=title_font)
+    arrow_width = arrow_bbox[2] - arrow_bbox[0]
+    draw.text(((width - arrow_width) // 2, y_pos + 20), arrow, fill=secondary_color, font=title_font)
+    
+    # Output section
+    y_pos += 80
+    draw.text((50, y_pos), "OUTPUT:", fill=primary_color, font=subtitle_font)
+    
+    # Wrap output text
+    output_lines = textwrap.wrap(output_text, width=70)
+    y_pos += 30
+    for line in output_lines[:4]:  # Max 4 lines
+        draw.text((50, y_pos), line, fill=text_color, font=text_font)
+        y_pos += 25
+    
+    # Footer
+    footer_text = "Generated with Corporate Synergy Bot 7B"
+    footer_bbox = draw.textbbox((0, 0), footer_text, font=small_font)
+    footer_width = footer_bbox[2] - footer_bbox[0]
+    draw.text(((width - footer_width) // 2, height - 40), footer_text, fill=secondary_color, font=small_font)
+    
+    return img
+
+def generate_linkedin_post_text(input_text, output_text, mode, domain):
+    """Generate LinkedIn post text"""
+    if mode == "To Corporate":
+        post = f"""🏢 Transform your communication with AI!
+
+From casual: "{input_text}"
+To professional: "{output_text}"
+
+#{domain}Career #ProfessionalCommunication #CorporateSpeak #AI #WorkplaceCommunication #ProfessionalDevelopment
+
+Try it yourself with Corporate Synergy Bot 7B! 🚀"""
+    else:
+        post = f"""💬 Decode corporate jargon with AI!
+
+From corporate: "{input_text}"
+To plain English: "{output_text}"
+
+#ClearCommunication #CorporateJargon #WorkplaceCommunication #AI #ProfessionalDevelopment #PlainEnglish
+
+Cut through the corporate speak with Corporate Synergy Bot 7B! ✨"""
+    
+    return post
+
+# Streamlit interface
+st.set_page_config(
+    page_title="Corporate Synergy Bot 7B",
+    page_icon="🏢",
+    layout="wide"
+)
+
+st.title("🏢 Corporate Synergy Bot 7B")
+st.markdown("""
+Transform casual language into professional corporate communication or decode corporate jargon back to plain English.
+
+Powered by fine-tuned Mistral-7B with LoRA.
+""")
+
+col1, col2 = st.columns(2)
+
+with col1:
+    st.subheader("Input")
+    input_text = st.text_area(
+        "Input Text",
+        placeholder="Enter text to transform...",
+        height=100,
+        key="input_text"
+    )
+    
+    mode = st.radio(
+        "Transformation Mode",
+        ["To Corporate", "To Plain English"],
+        index=0,
+        key="mode"
+    )
+    
+    col1a, col1b = st.columns(2)
+    with col1a:
+        domain = st.selectbox(
+            "Domain (for corporate mode)",
+            ["general", "tech", "finance", "consulting", "healthcare", "retail"],
+            index=0,
+            key="domain"
+        )
+    
+    with col1b:
+        seniority = st.selectbox(
+            "Seniority Level",
+            ["junior", "mid", "senior", "executive"],
+            index=1,
+            key="seniority"
+        )
+    
+    transform_btn = st.button("Transform", type="primary", use_container_width=True)
+
+with col2:
+    st.subheader("Output")
+    
+    if transform_btn and input_text:
+        with st.spinner("Transforming..."):
+            output_text = transform_text(input_text, mode, domain, seniority)
+            st.text_area(
+                "Transformed Text",
+                value=output_text,
+                height=100,
+                key="output_text"
+            )
+            
+            # Store the output for card generation
+            st.session_state.last_output = output_text
+            st.session_state.last_input = input_text
+            st.session_state.last_mode = mode
+            st.session_state.last_domain = domain
+            st.session_state.last_seniority = seniority
+    elif "last_output" in st.session_state:
+        st.text_area(
+            "Transformed Text",
+            value=st.session_state.last_output,
+            height=100,
+            key="output_display"
+        )
+
+# Social sharing section
+if "last_output" in st.session_state and "last_input" in st.session_state:
+    st.subheader("📱 Share Your Transformation")
+    
+    col_share1, col_share2 = st.columns(2)
+    
+    with col_share1:
+        if st.button("🎨 Generate Shareable Card", use_container_width=True):
+            with st.spinner("Creating your card..."):
+                card_img = create_shareable_card(
+                    st.session_state.last_input,
+                    st.session_state.last_output,
+                    st.session_state.last_mode,
+                    st.session_state.last_domain,
+                    st.session_state.last_seniority
+                )
+                
+                # Convert to bytes for download
+                img_buffer = io.BytesIO()
+                card_img.save(img_buffer, format='PNG')
+                img_buffer.seek(0)
+                
+                # Display the card
+                st.image(card_img, caption="Your shareable card", use_column_width=True)
+                
+                # Download button
+                st.download_button(
+                    label="💾 Download Card",
+                    data=img_buffer.getvalue(),
+                    file_name="corporate_synergy_transformation.png",
+                    mime="image/png",
+                    use_container_width=True
+                )
+    
+    with col_share2:
+        if st.button("📝 Generate LinkedIn Post", use_container_width=True):
+            linkedin_text = generate_linkedin_post_text(
+                st.session_state.last_input,
+                st.session_state.last_output,
+                st.session_state.last_mode,
+                st.session_state.last_domain
+            )
+            
+            st.text_area(
+                "LinkedIn Post Text",
+                value=linkedin_text,
+                height=200,
+                key="linkedin_post"
+            )
+            
+            # LinkedIn share button
+            linkedin_url = f"https://www.linkedin.com/sharing/share-offsite/?url={urllib.parse.quote('https://huggingface.co/spaces/phxdev/corporate-synergy-bot')}&summary={urllib.parse.quote(linkedin_text[:200])}"
+            
+            st.markdown(f"""
+            <a href="{linkedin_url}" target="_blank">
+                <button style="
+                    background-color: #0077B5;
+                    color: white;
+                    padding: 10px 20px;
+                    border: none;
+                    border-radius: 5px;
+                    cursor: pointer;
+                    width: 100%;
+                    font-size: 16px;
+                    text-decoration: none;
+                ">
+                    🔗 Share on LinkedIn
+                </button>
+            </a>
+            """, unsafe_allow_html=True)
+
+# Examples section
+st.subheader("Examples")
+examples = [
+    ["let's meet tomorrow", "To Corporate", "general", "mid"],
+    ["I need help with this project", "To Corporate", "tech", "senior"],
+    ["good job on the presentation", "To Corporate", "consulting", "executive"],
+    ["We need to leverage our synergies to maximize stakeholder value", "To Plain English", "general", "mid"],
+    ["Let's circle back on the deliverables", "To Plain English", "general", "mid"],
+]
+
+example_cols = st.columns(len(examples))
+for i, (text, ex_mode, ex_domain, ex_seniority) in enumerate(examples):
+    with example_cols[i]:
+        if st.button(f"Example {i+1}", key=f"example_{i}"):
+            st.session_state.input_text = text
+            st.session_state.mode = ex_mode
+            st.session_state.domain = ex_domain
+            st.session_state.seniority = ex_seniority
+            st.rerun()
+
+if __name__ == "__main__":
+    pass