Create app.py

app.py

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+# === Imports ===
+import os
+import re
+import gradio as gr
+import openai
+from datetime import datetime
+from bs4 import BeautifulSoup
+
+# --- API Keys ---
+openai_api_key = os.environ.get("OPENAI_API_KEY")
+if not openai_api_key:
+    raise ValueError("OPENAI_API_KEY environment variable is not set.")
+
+client = openai.OpenAI(api_key=openai_api_key)
+
+# --- Exadata Specs ---
+exadata_specs = {
+    "X7": {"Quarter Rack": {"max_iops": 350000, "max_throughput": 25}, "Half Rack": {"max_iops": 700000, "max_throughput": 50}, "Full Rack": {"max_iops": 1400000, "max_throughput": 100}},
+    "X8": {"Quarter Rack": {"max_iops": 380000, "max_throughput": 28}, "Half Rack": {"max_iops": 760000, "max_throughput": 56}, "Full Rack": {"max_iops": 1520000, "max_throughput": 112}},
+    "X9": {"Quarter Rack": {"max_iops": 450000, "max_throughput": 30}, "Half Rack": {"max_iops": 900000, "max_throughput": 60}, "Full Rack": {"max_iops": 1800000, "max_throughput": 120}},
+    "X10": {"Quarter Rack": {"max_iops": 500000, "max_throughput": 35}, "Half Rack": {"max_iops": 1000000, "max_throughput": 70}, "Full Rack": {"max_iops": 2000000, "max_throughput": 140}},
+    "X11M": {"Quarter Rack": {"max_iops": 600000, "max_throughput": 40}, "Half Rack": {"max_iops": 1200000, "max_throughput": 80}, "Full Rack": {"max_iops": 2400000, "max_throughput": 160}},
+}
+
+# --- Utils ---
+def clean_awr_content(content):
+    if "<html" in content.lower():
+        soup = BeautifulSoup(content, "html.parser")
+        return soup.get_text()
+    return content
+
+# === AGENTS ===
+
+class CriticalAnalyzerAgent:
+    def analyze(self, content, performance_test_mode, exadata_model, rack_size):
+        cleaned_content = clean_awr_content(content)
+        if len(cleaned_content) > 128000:
+            cleaned_content = cleaned_content[:128000] + "\n\n[TRUNCATED]..."
+
+        prompt = f"""
+You are an expert Oracle DBA performance analyst specialized in AWR + Exadata.
+
+Please perform advanced analysis on the following report:
+
+======== AWR REPORT START ========
+{cleaned_content}
+======== AWR REPORT END ========
+
+Required Output:
+- Performance Summary (with metric values)
+- Detailed Bottlenecks + Risks (quantified)
+- Forecast + Predictions
+- Monitoring Recommendations
+- Exadata Statistics (IO, Flash Cache, Smart Scan)
+- Recommended Next Steps to Bridge Gaps
+"""
+
+        if performance_test_mode and exadata_model and rack_size:
+            specs = exadata_specs.get(exadata_model, {}).get(rack_size, {})
+            if specs:
+                prompt += f"""
+
+This was a PERFORMANCE TEST on Oracle Exadata {exadata_model} {rack_size}.
+Theoretical Max:
+- IOPS: {specs['max_iops']}
+- Throughput: {specs['max_throughput']} GB/s
+
+Compare observed vs theoretical. Recommend actions to close the performance gap.
+"""
+
+        response = client.chat.completions.create(
+            model="gpt-4-turbo",
+            messages=[
+                {"role": "system", "content": "You are an expert Oracle DBA."},
+                {"role": "user", "content": prompt}
+            ]
+        )
+
+        return response.choices[0].message.content.strip()
+
+class HealthAgent:
+    def check_health(self, content):
+        cleaned_content = clean_awr_content(content)
+        if len(cleaned_content) > 128000:
+            cleaned_content = cleaned_content[:128000] + "\n\n[TRUNCATED]..."
+
+        prompt = f"""
+You are a health diagnostic agent for Oracle AWR reports.
+
+Please detect CRITICAL and SEVERE problems. Examples include:
+- Flash device failures or zero hit rates
+- ORA-12170 or interconnect stalls
+- Very high gc buffer busy waits
+- IO stalls / disk saturation
+- Redo log sync slowdowns
+
+Categorize issues as:
+- 🚨 Critical
+- ⚠️ Warning
+- ✅ Healthy
+
+AWR CONTENT:
+{cleaned_content}
+"""
+
+        response = client.chat.completions.create(
+            model="gpt-4-turbo",
+            messages=[
+                {"role": "system", "content": "You are an Oracle AWR health check agent."},
+                {"role": "user", "content": prompt}
+            ]
+        )
+
+        return response.choices[0].message.content.strip()
+
+class RaterAgent:
+    def rate(self, content):
+        prompt = f"Rate the following analysis from 1-5 stars and explain:\n\n{content}"
+        response = client.chat.completions.create(
+            model="gpt-4-turbo",
+            messages=[{"role": "user", "content": prompt}]
+        )
+        return response.choices[0].message.content.strip()
+
+# === Main Process ===
+def process_awr(awr_text, threshold, performance_test_mode, exadata_model, rack_size):
+    analyzer = CriticalAnalyzerAgent()
+    health = HealthAgent()
+    rater = RaterAgent()
+
+    if not awr_text.strip():
+        return "No AWR text provided", "", ""
+
+    analysis = analyzer.analyze(awr_text, performance_test_mode, exadata_model, rack_size)
+    health_status = health.check_health(awr_text)
+    rating_text = rater.rate(analysis)
+
+    stars = 0
+    match = re.search(r"(\d+)", rating_text)
+    if match:
+        stars = int(match.group(1))
+
+    retry_status = "✅ Accepted"
+
+    if stars < threshold:
+        analysis_retry = analyzer.analyze(awr_text, performance_test_mode, exadata_model, rack_size)
+        rating_text_retry = rater.rate(analysis_retry)
+        retry_status = "✅ Retry Occurred"
+        analysis = analysis_retry
+        rating_text = rating_text_retry
+
+    return analysis, health_status, rating_text, retry_status
+
+# === Gradio UI ===
+with gr.Blocks() as demo:
+    gr.Markdown("# 🧠 Multi-Agent Oracle AWR Analyzer (Production Edition)")
+
+    awr_text = gr.Textbox(label="Paste AWR Report", lines=30)
+    threshold = gr.Slider(0, 5, value=3, step=1, label="Correctness Threshold (Stars)")
+    performance_test_mode = gr.Checkbox(label="Performance Test Mode")
+    exadata_model = gr.Dropdown(choices=list(exadata_specs.keys()), label="Exadata Model", visible=False)
+    rack_size = gr.Dropdown(choices=["Quarter Rack", "Half Rack", "Full Rack"], label="Rack Size", visible=False)
+
+    def toggle_visibility(mode):
+        return gr.update(visible=mode), gr.update(visible=mode)
+
+    performance_test_mode.change(toggle_visibility, inputs=performance_test_mode, outputs=[exadata_model, rack_size])
+
+    analyze_btn = gr.Button("Analyze AWR Report")
+    output = gr.Textbox(label="AWR Analysis", lines=20)
+    health = gr.Textbox(label="Health Agent Findings", lines=5)
+    rating = gr.Textbox(label="Rater", lines=3)
+    retry_status = gr.Textbox(label="Retry Status")
+
+    analyze_btn.click(process_awr, inputs=[awr_text, threshold, performance_test_mode, exadata_model, rack_size], outputs=[output, health, rating, retry_status])
+
+demo.launch(debug=True)