Create app.py

app.py

@@ -0,0 +1,149 @@
+import os
+import re
+import gradio as gr
+from huggingface_hub import InferenceClient
+
+HF_TOKEN = os.getenv("HF_TOKEN", "")
+DEFAULT_MODEL = os.getenv("HF_MODEL", "Qwen/Qwen2.5-72B-Instruct")
+
+MAX_TOKENS = 1400
+TEMPERATURE = 0.4
+
+SYSTEM_INSTRUCTIONS = """
+You are a senior enterprise Account Executive specializing in converting
+open-source platform usage into enterprise-grade commercial engagements.
+
+You do NOT represent any specific vendor.
+You do NOT claim access to private or internal data.
+
+Hard rules:
+- Anchor everything in public signals
+- Separate technical users from decision makers
+- Be practical and executable
+- Avoid generic SaaS language
+- If information is missing, state assumptions clearly
+
+You MUST output exactly these sections:
+
+1. Account Snapshot
+2. Usage Hypotheses
+3. Persona Mapping
+4. Outbound Campaign Design
+5. Message Examples
+6. How This Scales
+
+Under Message Examples:
+- One technical-user message
+- One decision-maker message
+
+Tone: senior AE speaking to peers. No emojis.
+"""
+
+USER_TEMPLATE = """
+Account (name or org URL):
+{account}
+
+Optional context:
+Industry: {industry}
+Region: {region}
+Primary persona: {primary_persona}
+Secondary personas: {secondary_personas}
+Offer focus: {offer_focus}
+Goal: {goal}
+Notes: {notes}
+
+Task:
+Create a structured outbound plan for this account based on public
+open-source platform usage and OSS → Enterprise conversion patterns.
+"""
+
+def call_model(prompt, model):
+    if not HF_TOKEN:
+        return "Missing HF_TOKEN. Add it in Space Settings → Secrets."
+
+    client = InferenceClient(model=model, token=HF_TOKEN)
+
+    response = client.chat.completions.create(
+        messages=[
+            {"role": "system", "content": SYSTEM_INSTRUCTIONS},
+            {"role": "user", "content": prompt},
+        ],
+        temperature=TEMPERATURE,
+        max_tokens=MAX_TOKENS,
+    )
+
+    return response.choices[0].message.content.strip()
+
+def generate(
+    account,
+    industry,
+    region,
+    primary_persona,
+    secondary_personas,
+    offer_focus,
+    goal,
+    notes,
+    model,
+):
+    if not account:
+        return "Please input an account name or org URL."
+
+    prompt = USER_TEMPLATE.format(
+        account=account,
+        industry=industry or "Not provided",
+        region=region or "Not provided",
+        primary_persona=primary_persona or "Not provided",
+        secondary_personas=secondary_personas or "Not provided",
+        offer_focus=offer_focus or "Not provided",
+        goal=goal or "Convert free usage to enterprise engagement",
+        notes=notes or "Not provided",
+    )
+
+    return call_model(prompt, model or DEFAULT_MODEL)
+
+with gr.Blocks(title="Enterprise OSS → Outbound Ops") as app:
+    gr.Markdown(
+        "# Enterprise OSS → Outbound Ops\n"
+        "Input an **account name or public org URL** to generate an enterprise outbound plan."
+    )
+
+    account = gr.Textbox(label="Account name or org URL")
+
+    with gr.Row():
+        industry = gr.Textbox(label="Industry (optional)")
+        region = gr.Textbox(label="Region (optional)")
+
+    with gr.Row():
+        primary_persona = gr.Textbox(label="Primary persona (optional)")
+        secondary_personas = gr.Textbox(label="Secondary personas (optional)")
+
+    offer_focus = gr.Textbox(label="Offer focus (optional)")
+    goal = gr.Textbox(label="Goal (optional)")
+    notes = gr.Textbox(label="Notes / known public signals (optional)", lines=4)
+
+    model = gr.Textbox(
+        label="Model",
+        value=DEFAULT_MODEL,
+        help="Change only if you know what you're doing",
+    )
+
+    run = gr.Button("Generate outbound plan")
+    output = gr.Markdown()
+
+    run.click(
+        fn=generate,
+        inputs=[
+            account,
+            industry,
+            region,
+            primary_persona,
+            secondary_personas,
+            offer_focus,
+            goal,
+            notes,
+            model,
+        ],
+        outputs=output,
+    )
+
+app.launch()