Update app.py

app.py

@@ -34,51 +34,53 @@ def get_embedding(text):
     return response.data[0].embedding
 
 # Core function: generate contextual pitch
-def contextual_pitch_assistant(csv_file, query):
+def contextual_pitch_assistant(csv_file, query, sender_name):
     df = pd.read_csv(csv_file.name)
     text_chunks = df.apply(row_to_text, axis=1).tolist()
     embeddings = [get_embedding(t) for t in text_chunks]
 
     dim = len(embeddings[0])
     index = faiss.IndexFlatL2(dim)
-    index.add(np.array(embeddings).astype('float32'))
+    index.add(np.array(embeddings).astype("float32"))
 
-    q_emb = np.array([get_embedding(query)]).astype('float32')
+    q_emb = np.array([get_embedding(query)]).astype("float32")
     D, I = index.search(q_emb, 3)
     retrieved = [text_chunks[i] for i in I[0]]
 
-    # Extract name and clinic safely first (outside the f-string)
+    # Extract name and clinic safely first
     try:
         account_manager = retrieved[0].split("Account Manager: ")[1].split("\n")[0].strip()
     except Exception:
         account_manager = "team"
-    
     try:
         account_name = retrieved[0].split("Clinic: ")[1].split("\n")[0].strip()
     except Exception:
         account_name = "your clinic"
-    
+
+    if not sender_name.strip():
+        sender_name = "The Sales Team"
+
     prompt = f"""
-    You are an expert in B2B email sales and marketing for dental technology solutions.
-    
-    Write a short, natural-sounding HTML sales email for a dental clinic.
-    
-    Rules:
-    - Always begin with "Dear {account_manager}," as the greeting.
-    - Refer naturally to the clinic "{account_name}" in the body.
-    - Focus on value, benefits, and a helpful tone — avoid technical jargon or metrics like churn or satisfaction scores.
-    - Never include placeholders such as "Your Company Name" or "[Your Name]".
-    - Keep it under 150 words.
-    - Include a polite call to action at the end (e.g. suggesting a demo or short call).
-    - Return only HTML — no markdown, no code fences.
-    
-    Query:
-    {query}
-    
-    CRM context (for your understanding, do not copy verbatim):
-    {'---'.join(retrieved)}
-    """
+You are an expert in B2B email sales and marketing for dental technology solutions.
+
+Write a short, natural-sounding HTML sales email for a dental clinic.
+
+Rules:
+- Always begin with "Dear {account_manager}," as the greeting.
+- Refer naturally to the clinic "{account_name}" in the body.
+- Focus on value, benefits, and a helpful tone — avoid technical jargon or metrics like churn or satisfaction scores.
+- Never include placeholders such as "Your Company Name" or "[Your Name]".
+- End the email with "Best regards," followed by "{sender_name}".
+- Keep it under 150 words.
+- Include a polite call to action at the end (e.g. suggesting a demo or short call).
+- Return only HTML — no markdown, no code fences.
 
+Query:
+{query}
+
+CRM context (for your understanding, do not copy verbatim):
+{'---'.join(retrieved)}
+"""
 
     response = client.chat.completions.create(
         model="gpt-4o-mini",
@@ -88,10 +90,6 @@ def contextual_pitch_assistant(csv_file, query):
 
     output_text = response.choices[0].message.content
 
-    # Extract image prompt (for later)
-    match = re.search(r"(Image prompt|DALL·E prompt)[:\-]\s*(.*)", output_text)
-    image_prompt = match.group(2).strip() if match else "modern dental clinic interior with dentist and patient"
-
     # TEMP FIX: use random pre-uploaded header image
     image_choices = [
         "https://huggingface.co/spaces/nmcamacho/RAGdemo/resolve/main/dental_header_1.png",
@@ -107,9 +105,9 @@ def contextual_pitch_assistant(csv_file, query):
     output_text = output_text.strip()
 
     html = f"""
-    <div style='font-family:Arial,sans-serif;max-width:600px;margin:auto;padding:16px;background:#ffffff;
-    border-radius:12px;box-shadow:0 2px 8px rgba(0,0,0,0.1);'>
-      <img src="{image_url}" style="width:100%;border-radius:8px;margin-bottom:16px;">
+    <div style='font-family:Arial,sans-serif;max-width:700px;margin:auto;padding:24px;background:#ffffff;
+    border-radius:12px;box-shadow:0 3px 10px rgba(0,0,0,0.1);'>
+      <img src="{image_url}" style="width:100%;border-radius:8px;margin-bottom:20px;">
       {output_text}
     </div>
     """
@@ -118,28 +116,31 @@ def contextual_pitch_assistant(csv_file, query):
 # Build the Gradio app UI
 with gr.Blocks(
     title="Contextual Pitch Assistant for Dental Sales",
-    css="#output_html {min-height: 400px;} .gradio-container {max-width: 100%!important;}"
+    css="""
+    #output_html {min-height: 450px;}
+    .gradio-container {max-width: 90% !important; margin:auto;}
+    """
 ) as app:
     gr.Markdown(
         """
-        # 🦷 Contextual Pitch Assistant for Dental Sales
-        Upload a CRM file and ask a sales question — get a contextualized email pitch with a generated image.
+        # 🦷 Contextual Pitch Assistant for Dental Sales  
+        Upload a CRM file and ask a sales question — get a contextualized email pitch with a matching image.
         """
     )
 
     csv_file = gr.File(label="📂 Upload CRM CSV (5–100 rows)", file_types=[".csv"])
     query = gr.Textbox(label="💬 Sales Query", placeholder="e.g. Which clinic is best for our imaging subscription?")
-    run_btn = gr.Button("🚀 Generate Pitch")
+    sender_name = gr.Textbox(label="✍️ Who signs the email?", placeholder="e.g. Nuno Camacho, Sales Director", value="Nuno Camacho")
+    run_btn = gr.Button("🚀 Generate Pitch", variant="primary")
     output = gr.HTML(label="✨ Email Pitch Preview", elem_id="output_html")
 
-    run_btn.click(fn=contextual_pitch_assistant, inputs=[csv_file, query], outputs=output)
+    run_btn.click(fn=contextual_pitch_assistant, inputs=[csv_file, query, sender_name], outputs=output)
 
     run_btn.click(
-    lambda: "<p style='color:gray;'>⏳ Processing... please wait 30–60 seconds.</p>",
-    inputs=None,
-    outputs=output,
-    queue=False
-)
-
+        lambda: "<p style='color:gray;'>⏳ Processing... please wait 30–60 seconds.</p>",
+        inputs=None,
+        outputs=output,
+        queue=False
+    )
 
 app.launch()