Update app.py

app.py

@@ -8,9 +8,8 @@ import requests
 import matplotlib.pyplot as plt
 from matplotlib.figure import Figure
 
-
 # ============================================================
-#  LLM REQUEST HANDLER — GPT-4.1 ENFORCED
+#  LLM CALLER — GPT-4.1 ONLY
 # ============================================================
 
 def call_chat_completion(
@@ -19,22 +18,11 @@ def call_chat_completion(
     system_prompt: str,
     user_prompt: str,
     model: str = "gpt-4.1",
-    max_completion_tokens: int = 2400,
+    max_completion_tokens: int = 2000,
 ) -> str:
-    """
-    Universal OpenAI-compatible ChatCompletion caller.
-
-    - Enforces GPT-4.1 (stable, JSON-safe, supports large context)
-    - Removes temperature, top_p, etc. for compatibility
-    - Uses the new OpenAI spec: max_completion_tokens
-    - Falls back to legacy max_tokens for compatible APIs
-    """
 
     if not api_key:
-        raise ValueError("⚠️ Missing API key.")
-
-    if not base_url:
-        base_url = "https://api.openai.com"
+        raise ValueError("Missing API key.")
 
     url = base_url.rstrip("/") + "/v1/chat/completions"
 
@@ -43,7 +31,6 @@ def call_chat_completion(
         "Content-Type": "application/json",
     }
 
-    # Primary OpenAI 2024+ payload
     payload = {
         "model": model,
         "messages": [
@@ -53,39 +40,32 @@ def call_chat_completion(
         "max_completion_tokens": max_completion_tokens,
     }
 
-    # First attempt
-    response = requests.post(url, headers=headers, json=payload, timeout=60)
+    resp = requests.post(url, headers=headers, json=payload, timeout=60)
 
-    # Some models require legacy name: max_tokens
-    if response.status_code == 400 and "max_completion_tokens" in response.text:
-        payload.pop("max_completion_tokens", None)
+    # Fallback for providers requiring max_tokens
+    if resp.status_code == 400 and "max_completion_tokens" in resp.text:
         payload["max_tokens"] = max_completion_tokens
-        response = requests.post(url, headers=headers, json=payload, timeout=60)
+        payload.pop("max_completion_tokens", None)
+        resp = requests.post(url, headers=headers, json=payload, timeout=60)
 
-    if response.status_code != 200:
+    if resp.status_code != 200:
         raise RuntimeError(
-            f"❌ LLM Error {response.status_code}:\n{response.text[:500]}"
+            f"LLM API Error {resp.status_code}:\n{resp.text[:400]}"
         )
 
-    data = response.json()
-
+    data = resp.json()
     try:
         return data["choices"][0]["message"]["content"]
-    except Exception as error:
-        raise RuntimeError(
-            "❌ Unexpected LLM response format:\n\n"
-            f"{json.dumps(data, indent=2)}"
-        ) from error
+    except:
+        raise RuntimeError(f"Malformed response:\n\n{json.dumps(data, indent=2)}")
 
 
 # ============================================================
-#  SOP PROMPTS + PARSING
+#  SOP PROMPT + JSON PARSER
 # ============================================================
 
 SOP_SYSTEM_PROMPT = """
-You are an elite SOP architect. Produce SOPs strictly in JSON.
-
-Use this exact schema:
+You are an expert process engineer. Produce SOPs as JSON using:
 
 {
   "title": "",
@@ -110,7 +90,7 @@ Use this exact schema:
   "versioning": {"version": "1.0","owner": "","last_updated": ""}
 }
 
-Return ONLY JSON — no prose, no commentary.
+Return ONLY JSON.
 """
 
 def build_user_prompt(title, desc, industry, tone, detail):
@@ -120,35 +100,21 @@ Context: {desc}
 Industry: {industry}
 Tone: {tone}
 Detail Level: {detail}
-Audience: mid-career professionals needing clarity, accountability, and structure.
+Audience: mid-career professionals.
 """
 
+
 def parse_sop_json(raw: str) -> Dict[str, Any]:
-    """
-    Extracts JSON from LLM text output.
-    Handles cases where JSON comes wrapped in markdown fences.
-    """
     txt = raw.strip()
-
-    # Strip markdown fences
     if txt.startswith("```"):
-        parts = txt.split("```")
-        txt = next((p for p in parts if "{" in p), parts[-1])
-
-    # Extract JSON object boundaries
-    start = txt.find("{")
-    end = txt.rfind("}")
+        txt = txt.split("```")[1]
 
-    if start == -1 or end == -1:
-        raise ValueError("❌ No valid JSON detected.")
-
-    return json.loads(txt[start:end+1])
+    first = txt.find("{")
+    last = txt.rfind("}")
+    return json.loads(txt[first:last+1])
 
 
 def sop_to_markdown(sop: Dict[str, Any]) -> str:
-    """
-    Converts SOP JSON to clean, readable Markdown.
-    """
 
     def bullet(items):
         if not items:
@@ -156,56 +122,34 @@ def sop_to_markdown(sop: Dict[str, Any]) -> str:
         return "\n".join(f"- {i}" for i in items)
 
     md = []
+    md.append(f"# {sop.get('title','Untitled SOP')}\n")
 
-    # Header
-    md.append(f"# {sop.get('title','Untitled SOP')}")
-
-    # Purpose
-    md.append("\n## 1. Purpose")
-    md.append(sop.get("purpose", "N/A"))
+    md.append("## 1. Purpose\n" + sop.get("purpose","N/A"))
+    md.append("## 2. Scope\n" + sop.get("scope","N/A"))
 
-    # Scope
-    md.append("\n## 2. Scope")
-    md.append(sop.get("scope", "N/A"))
+    md.append("## 3. Definitions\n" + bullet(sop.get("definitions", [])))
 
-    # Definitions
-    md.append("\n## 3. Definitions")
-    md.append(bullet(sop.get("definitions", [])))
-
-    # Roles
-    md.append("\n## 4. Roles & Responsibilities")
+    md.append("## 4. Roles & Responsibilities")
     for r in sop.get("roles", []):
-        md.append(f"### {r.get('name', 'Role')}")
+        md.append(f"### {r.get('name','Role')}")
         md.append(bullet(r.get("responsibilities", [])))
 
-    # Prerequisites
-    md.append("\n## 5. Prerequisites")
-    md.append(bullet(sop.get("prerequisites", [])))
+    md.append("## 5. Prerequisites\n" + bullet(sop.get("prerequisites", [])))
 
-    # Steps
-    md.append("\n## 6. Procedure — Step-by-Step")
+    md.append("## 6. Procedure")
     for st in sop.get("steps", []):
         md.append(f"### Step {st['step_number']}: {st['title']}")
         md.append(f"**Owner:** {st['owner_role']}")
         md.append(st["description"])
-        md.append("\n**Inputs:**\n" + bullet(st["inputs"]))
+        md.append("**Inputs:**\n" + bullet(st["inputs"]))
         md.append("**Outputs:**\n" + bullet(st["outputs"]))
 
-    # Escalation
-    md.append("\n## 7. Escalation")
-    md.append(bullet(sop.get("escalation", [])))
-
-    # Metrics
-    md.append("\n## 8. Metrics")
-    md.append(bullet(sop.get("metrics", [])))
+    md.append("## 7. Escalation\n" + bullet(sop.get("escalation", [])))
+    md.append("## 8. Metrics\n" + bullet(sop.get("metrics")))
+    md.append("## 9. Risks\n" + bullet(sop.get("risks")))
 
-    # Risks
-    md.append("\n## 9. Risks")
-    md.append(bullet(sop.get("risks", [])))
-
-    # Version
     v = sop.get("versioning", {})
-    md.append("\n## 10. Version Control")
+    md.append("## 10. Version Control")
     md.append(f"- Version: {v.get('version','1.0')}")
     md.append(f"- Owner: {v.get('owner','N/A')}")
     md.append(f"- Last Updated: {v.get('last_updated','N/A')}")
@@ -214,141 +158,94 @@ def sop_to_markdown(sop: Dict[str, Any]) -> str:
 
 
 # ============================================================
-#  PERFECTED DIAGRAM RENDERING — AUTO-SIZED CARDS
+#  🆕 PERFECTED DIAGRAM — AUTO-SIZE CARDS
 # ============================================================
 
 def create_sop_steps_figure(sop: Dict[str, Any]) -> Figure:
-    """
-    Produces a fully professional workflow diagram with:
-    - auto-sized card heights
-    - description wrapping
-    - clean left number boxes
-    - modern minimal presentation
-    """
-
     steps = sop.get("steps", [])
     if not steps:
-        fig, ax = plt.subplots(figsize=(8,3))
-        ax.text(
-            0.5, 0.5,
-            "No steps available.",
-            ha="center", va="center", fontsize=14
-        )
+        fig, ax = plt.subplots(figsize=(6,2))
+        ax.text(0.5,0.5,"No steps to visualize.",ha="center",va="center")
         ax.axis("off")
         return fig
 
-    # --------------------------------------------------------------------
-    # Determine total needed height by measuring text line counts
-    # --------------------------------------------------------------------
-
-    block_heights = []
+    # Dynamically compute figure height based on text amount
     total_height = 0
+    block_heights = []
 
     for st in steps:
-        title = st["title"]
-        owner = st["owner_role"]
-        desc_lines = textwrap.wrap(st["description"], width=70)
+        desc_lines = textwrap.wrap(st["description"], width=65)
+        num_lines = 2 + len(desc_lines)  # title + owner + description lines
+        block_h = 0.35 * num_lines
+        block_heights.append(block_h)
+        total_height += block_h + 0.3  # spacing
 
-        # at least 2 lines (title + owner)
-        num_lines = max(2 + len(desc_lines), 3)
-        block_height = num_lines * 0.35 + 0.5  # tuned for readability
-
-        block_heights.append(block_height)
-        total_height += block_height + 0.5  # spacing
-
-    fig_height = min(25, max(6, total_height))
-    fig, ax = plt.subplots(figsize=(12, fig_height))
+    fig_height = min(18, max(5, total_height))
+    fig, ax = plt.subplots(figsize=(10, fig_height))
 
     y = total_height
 
-    # --------------------------------------------------------------------
-    # Draw each step card
-    # --------------------------------------------------------------------
     for idx, st in enumerate(steps):
-
-        block_h = block_heights[idx]
         title = st["title"]
         owner = st["owner_role"]
-        desc_lines = textwrap.wrap(st["description"], width=72)
+        desc_lines = textwrap.wrap(st["description"], width=70)
+        block_h = block_heights[idx]
 
-        # Card horizontal bounds
-        x0 = 0.05
-        x1 = 0.95
+        x0, x1 = 0.05, 0.95
 
-        # Draw card outline
         ax.add_patch(
             plt.Rectangle(
                 (x0, y - block_h),
                 x1 - x0,
                 block_h,
                 fill=False,
-                linewidth=1.8
+                linewidth=1.7
             )
         )
 
-        # Draw number box
-        num_box_w = 0.085
-
+        # Number box
+        nbw = 0.08
         ax.add_patch(
             plt.Rectangle(
                 (x0, y - block_h),
-                num_box_w,
+                nbw,
                 block_h,
                 fill=False,
-                linewidth=1.6
+                linewidth=1.5
             )
         )
 
-        # Step number text
         ax.text(
-            x0 + num_box_w/2,
+            x0 + nbw/2,
             y - block_h/2,
             str(st["step_number"]),
-            fontsize=14,
-            fontweight="bold",
-            ha="center",
-            va="center"
+            ha="center", va="center",
+            fontsize=13, fontweight="bold"
         )
 
-        # Title + owner text start
-        text_x = x0 + num_box_w + 0.02
+        text_x = x0 + nbw + 0.02
 
         # Title
-        ax.text(
-            text_x,
-            y - 0.35,
-            title,
-            fontsize=13,
-            fontweight="bold",
-            ha="left",
-            va="top"
-        )
+        ax.text(text_x, y - 0.2,
+                title,
+                fontsize=12,
+                fontweight="bold",
+                ha="left", va="top")
 
         # Owner
-        ax.text(
-            text_x,
-            y - 0.75,
-            f"Owner: {owner}",
-            fontsize=11,
-            style="italic",
-            ha="left",
-            va="top"
-        )
+        ax.text(text_x, y - 0.45,
+                f"Owner: {owner}",
+                fontsize=10,
+                style="italic",
+                ha="left", va="top")
 
-        # Description — wrapped
-        text_y = y - 1.15
+        # Description (wrapped)
+        text_y = y - 0.75
         for line in desc_lines:
-            ax.text(
-                text_x,
-                text_y,
-                line,
-                fontsize=10,
-                ha="left",
-                va="top"
-            )
-            text_y -= 0.32
+            ax.text(text_x, text_y, line, fontsize=9, ha="left", va="top")
+            text_y -= 0.28
 
-        y -= (block_h + 0.5)
+        y -= (block_h + 0.3)
 
     ax.axis("off")
     fig.tight_layout()
@@ -356,41 +253,41 @@ def create_sop_steps_figure(sop: Dict[str, Any]) -> Figure:
 
 
 # ============================================================
-#  SAMPLE PRESETS
+#  SAMPLE SCENARIOS
 # ============================================================
 
-SAMPLE_SOPS = {
+SAMPLES = {
     "Volunteer Onboarding": {
         "title": "Volunteer Onboarding",
-        "description": "Onboarding volunteers: background check, orientation, training, placement.",
+        "description": "Create SOP for onboarding volunteers: background checks, orientation, training, placement.",
         "industry": "Nonprofit"
     },
     "Remote Employee Onboarding": {
         "title": "Remote Employee Onboarding",
-        "description": "SOP for a hybrid workforce: setup, HR docs, orientation, training.",
+        "description": "SOP for remote hires including IT setup, HR docs, culture onboarding.",
         "industry": "HR"
     },
     "IT Outage Response": {
         "title": "IT Outage Response",
-        "description": "Major IT incident response: triage, escalation, remediation, communication.",
+        "description": "Major outage response: detection, triage, escalation, comms, restoration, post-mortem.",
         "industry": "IT"
-    }
+    },
 }
 
-def load_sample(name: str):
-    if name not in SAMPLE_SOPS:
+def load_sample(name):
+    if name not in SAMPLES:
         return "", "", "General"
-    sample = SAMPLE_SOPS[name]
-    return sample["title"], sample["description"], sample["industry"]
+    s = SAMPLES[name]
+    return s["title"], s["description"], s["industry"]
 
 
 # ============================================================
-#  MAIN GENERATION HANDLER
+#  MAIN GENERATOR
 # ============================================================
 
 def generate_sop(
     api_key_state,
-    api_input,
+    api_key_input,
     base_url,
     model,
     title,
@@ -400,18 +297,12 @@ def generate_sop(
     detail
 ):
 
-    api_key = api_input or api_key_state
-
+    api_key = api_key_input or api_key_state
     if not api_key:
-        return (
-            "⚠️ Please enter an API key.",
-            "",
-            create_sop_steps_figure({"steps": []}),
-            api_key_state
-        )
-
-    # Always force GPT-4.1 for safety
-    model = "gpt-4.1"
+        return ("⚠️ Enter an API key.",
+                "",
+                create_sop_steps_figure({"steps": []}),
+                api_key_state)
 
     try:
         user_prompt = build_user_prompt(title, desc, industry, tone, detail)
@@ -421,8 +312,8 @@ def generate_sop(
             base_url=base_url,
             system_prompt=SOP_SYSTEM_PROMPT,
             user_prompt=user_prompt,
-            model=model,
-            max_completion_tokens=2400,
+            model="gpt-4.1",         # 🔥 Forced stable model
+            max_completion_tokens=2000
         )
 
         sop = parse_sop_json(raw)
@@ -433,107 +324,50 @@ def generate_sop(
         return md, json_out, fig, api_key
 
     except Exception as e:
-        return (
-            f"❌ Error generating SOP:\n{e}",
-            "",
-            create_sop_steps_figure({"steps": []}),
-            api_key_state
-        )
+        return (f"❌ Error generating SOP:\n{e}",
+                "",
+                create_sop_steps_figure({"steps": []}),
+                api_key_state)
 
 
 # ============================================================
-#  UI — FULL GRADIO BLOCKS
+#  GRADIO UI
 # ============================================================
 
 with gr.Blocks(title="ZEN Simple SOP Builder") as demo:
 
     gr.Markdown("""
-# 🧭 ZEN Simple SOP Builder  
-Professional workflows → SOP + Diagram  
-Powered by **GPT-4.1**
+# 🧭 ZEN Simple SOP Builder
+Generate clean SOPs + auto diagrams using **GPT-4.1**.
 """)
 
     api_key_state = gr.State("")
 
     with gr.Row():
-        # Left config column
         with gr.Column(scale=1):
+            api_input = gr.Textbox("API Key", type="password")
+            base_url = gr.Textbox("Base URL", value="https://api.openai.com")
+            model_name = gr.Textbox("Model (GPT-4.1 only)", value="gpt-4.1")
 
-            gr.Markdown("### Step 1 — API Configuration")
-            api_input = gr.Textbox(
-                "API Key",
-                type="password",
-                placeholder="Enter OpenAI API key"
-            )
-
-            base_url = gr.Textbox(
-                "Base URL",
-                value="https://api.openai.com"
-            )
-
-            model_name = gr.Textbox(
-                "Model (forced to GPT-4.1)",
-                value="gpt-4.1"
-            )
-
-            # Samples
-            gr.Markdown("### Load a Sample SOP")
-            sample = gr.Dropdown(
-                "Sample SOP",
-                choices=list(SAMPLE_SOPS.keys())
-            )
-            load_btn = gr.Button("Load Example")
+            sample = gr.Dropdown("Sample SOP", choices=list(SAMPLES.keys()))
+            load_btn = gr.Button("Load Sample")
 
-        # Right SOP config column
         with gr.Column(scale=2):
+            title = gr.Textbox("SOP Title")
+            desc = gr.Textbox("Description", lines=5)
+            industry = gr.Textbox("Industry", value="General")
+            tone = gr.Dropdown("Tone", ["Professional","Executive","Supportive"], value="Professional")
+            detail = gr.Dropdown("Detail Level", ["Standard","High detail","Checklist"], value="Standard")
 
-            gr.Markdown("### Step 2 — Describe Your SOP")
-
-            title = gr.Textbox(
-                "SOP Title",
-                placeholder="e.g. Volunteer Onboarding Workflow"
-            )
-
-            desc = gr.Textbox(
-                "Context / Summary",
-                lines=5,
-                placeholder="Describe what this SOP needs to cover..."
-            )
-
-            industry = gr.Textbox(
-                "Industry",
-                value="General"
-            )
-
-            tone = gr.Dropdown(
-                "Tone",
-                choices=["Professional", "Executive", "Supportive"],
-                value="Professional"
-            )
-
-            detail = gr.Dropdown(
-                "Detail Level",
-                choices=["Standard", "High detail", "Checklist"],
-                value="Standard"
-            )
-
-            generate_btn = gr.Button(
-                "🚀 Generate SOP",
-                variant="primary"
-            )
+            gen_btn = gr.Button("🚀 Generate SOP", variant="primary")
 
-    # SOP results
     sop_md = gr.Markdown()
     sop_json = gr.Code(language="json")
-
-    # Diagram
-    gr.Markdown("### Visual Workflow Diagram")
     sop_fig = gr.Plot()
 
-    # Events
     load_btn.click(load_sample, sample, [title, desc, industry])
 
-    generate_btn.click(
+    gen_btn.click(
         generate_sop,
         [api_key_state, api_input, base_url, model_name, title, desc, industry, tone, detail],
         [sop_md, sop_json, sop_fig, api_key_state],