Fixed app v2

app.py

@@ -1,39 +1,51 @@
-from fastapi import FastAPI, HTTPException
-from pydantic import BaseModel
-from transformers import pipeline
-from typing import List
-
-# Initialize the FastAPI app
-app = FastAPI()
-
-# Initialize the text generation pipeline with the specified model
-pipe = pipeline("text-generation", model="jcordon5/Mistral-7B-cybersecurity-rules")
-
-# Define the input schema for FastAPI
-class Message(BaseModel):
-    role: str
-    content: str
-
-class MessagesInput(BaseModel):
-    messages: List[Message]
-
-@app.post("/generate/")
-async def generate_response(messages_input: MessagesInput):
-    try:
-        # Convert the messages to the expected format for the pipeline
-        messages = [{"role": msg.role, "content": msg.content} for msg in messages_input.messages]
-
-        # Generate response using the pipeline
-        response = pipe(messages)
-        
-        # Extract generated text from the response
-        generated_text = response[0]["generated_text"]
-
-        return {
-            "response": generated_text
-        }
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-
-# Run the app
-# To start the server, use the command: uvicorn filename:app --host 0.0.0.0 --port 8000
+import openai
+
+# Set up OpenAI API key
+openai.api_key = "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"
+
+# Function to read and process log files
+def read_log_file(file_path):
+    with open(file_path, 'r') as file:
+        log_data = file.read()
+    return log_data
+
+# Function to analyze log data for malicious activity using OpenAI
+def analyze_logs_for_malicious_activity(log_data):
+    # Instruction prompt to guide the model
+    prompt = (
+        "Analyze the following network log data for any indicators of malicious activity, "
+        "such as unusual IP addresses, unauthorized access attempts, data exfiltration, or anomalies. "
+        "Provide details on potential threats, IPs involved, and suggest actions if any threats are detected.\n\n"
+        f"{log_data}"
+    )
+    
+    # Send request to OpenAI API
+    response = openai.Completion.create(
+        engine="gpt-3.5-turbo",  # Ensure to use a suitable model for instructions
+        prompt=prompt,
+        max_tokens=500,
+        temperature=0.5
+    )
+    
+    # Extract response text
+    analysis = response.choices[0].text.strip()
+    return analysis
+
+# Main function to execute log analysis
+def main():
+    # Path to your network log file
+    log_file_path = "log.txt"
+    
+    # Read log data
+    log_data = read_log_file(log_file_path)
+    
+    # Analyze log data
+    analysis = analyze_logs_for_malicious_activity(log_data)
+    
+    # Print or save analysis result
+    print("Analysis of Network Logs for Malicious Activity:\n")
+    print(analysis)
+
+# Run the main function
+if __name__ == "__main__":
+    main()