Update app.py

app.py

@@ -8,8 +8,9 @@ import requests
 import matplotlib.pyplot as plt
 from matplotlib.figure import Figure
 
+
 # ============================================================
-#  LLM CALLER — GPT-4.1 ONLY
+#  LLM REQUEST HANDLER — GPT-4.1 ENFORCED
 # ============================================================
 
 def call_chat_completion(
@@ -18,11 +19,22 @@ def call_chat_completion(
     system_prompt: str,
     user_prompt: str,
     model: str = "gpt-4.1",
-    max_completion_tokens: int = 2000,
+    max_completion_tokens: int = 2400,
 ) -> 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.")
+        raise ValueError("⚠️ Missing API key.")
+
+    if not base_url:
+        base_url = "https://api.openai.com"
 
     url = base_url.rstrip("/") + "/v1/chat/completions"
 
@@ -31,6 +43,7 @@ def call_chat_completion(
         "Content-Type": "application/json",
     }
 
+    # Primary OpenAI 2024+ payload
     payload = {
         "model": model,
         "messages": [
@@ -40,32 +53,39 @@ def call_chat_completion(
         "max_completion_tokens": max_completion_tokens,
     }
 
-    resp = requests.post(url, headers=headers, json=payload, timeout=60)
+    # First attempt
+    response = requests.post(url, headers=headers, json=payload, timeout=60)
 
-    # Fallback for providers requiring max_tokens
-    if resp.status_code == 400 and "max_completion_tokens" in resp.text:
-        payload["max_tokens"] = max_completion_tokens
+    # 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)
-        resp = requests.post(url, headers=headers, json=payload, timeout=60)
+        payload["max_tokens"] = max_completion_tokens
+        response = requests.post(url, headers=headers, json=payload, timeout=60)
 
-    if resp.status_code != 200:
+    if response.status_code != 200:
         raise RuntimeError(
-            f"LLM API Error {resp.status_code}:\n{resp.text[:400]}"
+            f"❌ LLM Error {response.status_code}:\n{response.text[:500]}"
         )
 
-    data = resp.json()
+    data = response.json()
+
     try:
         return data["choices"][0]["message"]["content"]
-    except:
-        raise RuntimeError(f"Malformed response:\n\n{json.dumps(data, indent=2)}")
+    except Exception as error:
+        raise RuntimeError(
+            "❌ Unexpected LLM response format:\n\n"
+            f"{json.dumps(data, indent=2)}"
+        ) from error
 
 
 # ============================================================
-#  SOP PROMPT + JSON PARSER
+#  SOP PROMPTS + PARSING
 # ============================================================
 
 SOP_SYSTEM_PROMPT = """
-You are an expert process engineer. Produce SOPs as JSON using:
+You are an elite SOP architect. Produce SOPs strictly in JSON.
+
+Use this exact schema:
 
 {
   "title": "",
@@ -90,7 +110,7 @@ You are an expert process engineer. Produce SOPs as JSON using:
   "versioning": {"version": "1.0","owner": "","last_updated": ""}
 }
 
-Return ONLY JSON.
+Return ONLY JSON — no prose, no commentary.
 """
 
 def build_user_prompt(title, desc, industry, tone, detail):
@@ -100,21 +120,35 @@ Context: {desc}
 Industry: {industry}
 Tone: {tone}
 Detail Level: {detail}
-Audience: mid-career professionals.
+Audience: mid-career professionals needing clarity, accountability, and structure.
 """
 
-
 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("```"):
-        txt = txt.split("```")[1]
+        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("}")
 
-    first = txt.find("{")
-    last = txt.rfind("}")
-    return json.loads(txt[first:last+1])
+    if start == -1 or end == -1:
+        raise ValueError("❌ No valid JSON detected.")
+
+    return json.loads(txt[start:end+1])
 
 
 def sop_to_markdown(sop: Dict[str, Any]) -> str:
+    """
+    Converts SOP JSON to clean, readable Markdown.
+    """
 
     def bullet(items):
         if not items:
@@ -122,34 +156,56 @@ 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")
 
-    md.append("## 1. Purpose\n" + sop.get("purpose","N/A"))
-    md.append("## 2. Scope\n" + sop.get("scope","N/A"))
+    # Header
+    md.append(f"# {sop.get('title','Untitled SOP')}")
+
+    # Purpose
+    md.append("\n## 1. Purpose")
+    md.append(sop.get("purpose", "N/A"))
 
-    md.append("## 3. Definitions\n" + bullet(sop.get("definitions", [])))
+    # Scope
+    md.append("\n## 2. Scope")
+    md.append(sop.get("scope", "N/A"))
 
-    md.append("## 4. Roles & Responsibilities")
+    # Definitions
+    md.append("\n## 3. Definitions")
+    md.append(bullet(sop.get("definitions", [])))
+
+    # Roles
+    md.append("\n## 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", [])))
 
-    md.append("## 5. Prerequisites\n" + bullet(sop.get("prerequisites", [])))
+    # Prerequisites
+    md.append("\n## 5. Prerequisites")
+    md.append(bullet(sop.get("prerequisites", [])))
 
-    md.append("## 6. Procedure")
+    # Steps
+    md.append("\n## 6. Procedure — Step-by-Step")
     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("**Inputs:**\n" + bullet(st["inputs"]))
+        md.append("\n**Inputs:**\n" + bullet(st["inputs"]))
         md.append("**Outputs:**\n" + bullet(st["outputs"]))
 
-    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")))
+    # Escalation
+    md.append("\n## 7. Escalation")
+    md.append(bullet(sop.get("escalation", [])))
+
+    # Metrics
+    md.append("\n## 8. Metrics")
+    md.append(bullet(sop.get("metrics", [])))
 
+    # Risks
+    md.append("\n## 9. Risks")
+    md.append(bullet(sop.get("risks", [])))
+
+    # Version
     v = sop.get("versioning", {})
-    md.append("## 10. Version Control")
+    md.append("\n## 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')}")
@@ -158,94 +214,141 @@ def sop_to_markdown(sop: Dict[str, Any]) -> str:
 
 
 # ============================================================
-#  🆕 PERFECTED DIAGRAM — AUTO-SIZE CARDS
+#  PERFECTED DIAGRAM RENDERING — AUTO-SIZED 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=(6,2))
-        ax.text(0.5,0.5,"No steps to visualize.",ha="center",va="center")
+        fig, ax = plt.subplots(figsize=(8,3))
+        ax.text(
+            0.5, 0.5,
+            "No steps available.",
+            ha="center", va="center", fontsize=14
+        )
         ax.axis("off")
         return fig
 
-    # Dynamically compute figure height based on text amount
-    total_height = 0
+    # --------------------------------------------------------------------
+    # Determine total needed height by measuring text line counts
+    # --------------------------------------------------------------------
+
     block_heights = []
+    total_height = 0
 
     for st in steps:
-        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
+        title = st["title"]
+        owner = st["owner_role"]
+        desc_lines = textwrap.wrap(st["description"], width=70)
 
-    fig_height = min(18, max(5, total_height))
-    fig, ax = plt.subplots(figsize=(10, fig_height))
+        # 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))
 
     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=70)
-        block_h = block_heights[idx]
+        desc_lines = textwrap.wrap(st["description"], width=72)
 
-        x0, x1 = 0.05, 0.95
+        # Card horizontal bounds
+        x0 = 0.05
+        x1 = 0.95
 
+        # Draw card outline
         ax.add_patch(
             plt.Rectangle(
                 (x0, y - block_h),
                 x1 - x0,
                 block_h,
                 fill=False,
-                linewidth=1.7
+                linewidth=1.8
             )
         )
 
-        # Number box
-        nbw = 0.08
+        # Draw number box
+        num_box_w = 0.085
+
         ax.add_patch(
             plt.Rectangle(
                 (x0, y - block_h),
-                nbw,
+                num_box_w,
                 block_h,
                 fill=False,
-                linewidth=1.5
+                linewidth=1.6
             )
         )
 
+        # Step number text
         ax.text(
-            x0 + nbw/2,
+            x0 + num_box_w/2,
             y - block_h/2,
             str(st["step_number"]),
-            ha="center", va="center",
-            fontsize=13, fontweight="bold"
+            fontsize=14,
+            fontweight="bold",
+            ha="center",
+            va="center"
         )
 
-        text_x = x0 + nbw + 0.02
+        # Title + owner text start
+        text_x = x0 + num_box_w + 0.02
 
         # Title
-        ax.text(text_x, y - 0.2,
-                title,
-                fontsize=12,
-                fontweight="bold",
-                ha="left", va="top")
+        ax.text(
+            text_x,
+            y - 0.35,
+            title,
+            fontsize=13,
+            fontweight="bold",
+            ha="left",
+            va="top"
+        )
 
         # Owner
-        ax.text(text_x, y - 0.45,
-                f"Owner: {owner}",
-                fontsize=10,
-                style="italic",
-                ha="left", va="top")
+        ax.text(
+            text_x,
+            y - 0.75,
+            f"Owner: {owner}",
+            fontsize=11,
+            style="italic",
+            ha="left",
+            va="top"
+        )
 
-        # Description (wrapped)
-        text_y = y - 0.75
+        # Description — wrapped
+        text_y = y - 1.15
         for line in desc_lines:
-            ax.text(text_x, text_y, line, fontsize=9, ha="left", va="top")
-            text_y -= 0.28
+            ax.text(
+                text_x,
+                text_y,
+                line,
+                fontsize=10,
+                ha="left",
+                va="top"
+            )
+            text_y -= 0.32
 
-        y -= (block_h + 0.3)
+        y -= (block_h + 0.5)
 
     ax.axis("off")
     fig.tight_layout()
@@ -253,41 +356,41 @@ def create_sop_steps_figure(sop: Dict[str, Any]) -> Figure:
 
 
 # ============================================================
-#  SAMPLE SCENARIOS
+#  SAMPLE PRESETS
 # ============================================================
 
-SAMPLES = {
+SAMPLE_SOPS = {
     "Volunteer Onboarding": {
         "title": "Volunteer Onboarding",
-        "description": "Create SOP for onboarding volunteers: background checks, orientation, training, placement.",
+        "description": "Onboarding volunteers: background check, orientation, training, placement.",
         "industry": "Nonprofit"
     },
     "Remote Employee Onboarding": {
         "title": "Remote Employee Onboarding",
-        "description": "SOP for remote hires including IT setup, HR docs, culture onboarding.",
+        "description": "SOP for a hybrid workforce: setup, HR docs, orientation, training.",
         "industry": "HR"
     },
     "IT Outage Response": {
         "title": "IT Outage Response",
-        "description": "Major outage response: detection, triage, escalation, comms, restoration, post-mortem.",
+        "description": "Major IT incident response: triage, escalation, remediation, communication.",
         "industry": "IT"
-    },
+    }
 }
 
-def load_sample(name):
-    if name not in SAMPLES:
+def load_sample(name: str):
+    if name not in SAMPLE_SOPS:
         return "", "", "General"
-    s = SAMPLES[name]
-    return s["title"], s["description"], s["industry"]
+    sample = SAMPLE_SOPS[name]
+    return sample["title"], sample["description"], sample["industry"]
 
 
 # ============================================================
-#  MAIN GENERATOR
+#  MAIN GENERATION HANDLER
 # ============================================================
 
 def generate_sop(
     api_key_state,
-    api_key_input,
+    api_input,
     base_url,
     model,
     title,
@@ -297,12 +400,18 @@ def generate_sop(
     detail
 ):
 
-    api_key = api_key_input or api_key_state
+    api_key = api_input or api_key_state
+
     if not api_key:
-        return ("⚠️ Enter an API key.",
-                "",
-                create_sop_steps_figure({"steps": []}),
-                api_key_state)
+        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"
 
     try:
         user_prompt = build_user_prompt(title, desc, industry, tone, detail)
@@ -312,8 +421,8 @@ def generate_sop(
             base_url=base_url,
             system_prompt=SOP_SYSTEM_PROMPT,
             user_prompt=user_prompt,
-            model="gpt-4.1",         # 🔥 Forced stable model
-            max_completion_tokens=2000
+            model=model,
+            max_completion_tokens=2400,
         )
 
         sop = parse_sop_json(raw)
@@ -324,50 +433,107 @@ 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
+        )
 
 
 # ============================================================
-#  GRADIO UI
+#  UI — FULL GRADIO BLOCKS
 # ============================================================
 
 with gr.Blocks(title="ZEN Simple SOP Builder") as demo:
 
     gr.Markdown("""
-# 🧭 ZEN Simple SOP Builder
-Generate clean SOPs + auto diagrams using **GPT-4.1**.
+# 🧭 ZEN Simple SOP Builder  
+Professional workflows → SOP + Diagram  
+Powered by **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")
 
-            sample = gr.Dropdown("Sample SOP", choices=list(SAMPLES.keys()))
-            load_btn = gr.Button("Load Sample")
+            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")
 
+        # 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")
 
-            gen_btn = gr.Button("🚀 Generate SOP", variant="primary")
+            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"
+            )
 
+    # 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])
 
-    gen_btn.click(
+    generate_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],