commit

app.py

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+import gradio as gr
+import sqlite3
+from huggingface_hub import InferenceClient
+
+DB_PATH = "logs.db"
+client = InferenceClient(token="your_hf_token_here")
+
+def retrieve_evidence(question):
+    # simplified — swap in your actual routing logic
+    conn = sqlite3.connect(DB_PATH)
+    cursor = conn.cursor()
+    cursor.execute("SELECT * FROM your_summary_table LIMIT 10")
+    rows = cursor.fetchall()
+    conn.close()
+    return str(rows)
+
+def answer_question(question):
+    evidence = retrieve_evidence(question)
+    
+    prompt = f"""You are a security log analyst.
+Here is the relevant evidence from the database:
+{evidence}
+
+Answer this question based only on the evidence above:
+{question}"""
+    
+    response = client.text_generation(
+        prompt,
+        model="mistralai/Mistral-7B-Instruct-v0.3",  # free model
+        max_new_tokens=512
+    )
+    return response
+
+demo = gr.Interface(
+    fn=answer_question,
+    inputs=gr.Textbox(label="Ask a question about the logs"),
+    outputs=gr.Textbox(label="Answer"),
+    title="Security Log Analyzer",
+    description="Ask questions about the open source log dataset."
+)
+
+demo.launch()

requirements.txt

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+gradio
+huggingface_hub
+sqlite3