Reduced some vuln after SAST scan

plugins/sd_text.py

@@ -0,0 +1,95 @@
+"""
+Plugin for generating text using Ollama's Mistral 7B Instruct model and sending it to a Matrix chat room.
+"""
+
+import requests
+from asyncio import Queue
+import simplematrixbotlib as botlib
+import argparse
+
+# Queue to store pending commands
+command_queue = Queue()
+
+API_URL = "http://localhost:11434/api/generate"
+MODEL_NAME = "mistral:7b-instruct"
+
+async def process_command(room, message, bot, prefix, config):
+    """
+    Queue and process !text commands sequentially.
+    """
+    match = botlib.MessageMatch(room, message, bot, prefix)
+    if match.prefix() and match.command("text"):
+        if command_queue.empty():
+            await handle_command(room, message, bot, prefix, config)
+        else:
+            await command_queue.put((room, message, bot, prefix, config))
+
+async def handle_command(room, message, bot, prefix, config):
+    """
+    Send the prompt to Ollama API and return the generated text.
+    """
+    match = botlib.MessageMatch(room, message, bot, prefix)
+    if not (match.prefix() and match.command("text")):
+        return
+
+    # Parse optional arguments
+    parser = argparse.ArgumentParser(description='Generate text using Ollama API')
+    parser.add_argument('--max_tokens', type=int, default=512, help='Maximum tokens to generate')
+    parser.add_argument('--temperature', type=float, default=0.7, help='Temperature for generation')
+    parser.add_argument('prompt', nargs='+', help='Prompt for the model')
+
+    try:
+        args = parser.parse_args(message.body.split()[1:])  # Skip command itself
+        prompt = ' '.join(args.prompt).strip()
+
+        if not prompt:
+            await bot.api.send_text_message(room.room_id, "Usage: !text <your prompt here>")
+            return
+
+        payload = {
+            "model": MODEL_NAME,
+            "prompt": prompt,
+            "max_tokens": args.max_tokens,
+            "temperature": args.temperature,
+            "stream": False
+        }
+
+        response = requests.post(API_URL, json=payload, timeout=60)
+        response.raise_for_status()
+        r = response.json()
+
+        generated_text = r.get("response", "").strip()
+        if not generated_text:
+            generated_text = "(No response from model)"
+
+        await bot.api.send_text_message(room.room_id, generated_text)
+
+    except argparse.ArgumentError as e:
+        await bot.api.send_text_message(room.room_id, f"Argument error: {e}")
+    except requests.exceptions.RequestException as e:
+        await bot.api.send_text_message(room.room_id, f"Error connecting to Ollama API: {e}")
+    except Exception as e:
+        await bot.api.send_text_message(room.room_id, f"Unexpected error: {e}")
+    finally:
+        # Process next command from the queue, if any
+        if not command_queue.empty():
+            next_command = await command_queue.get()
+            await handle_command(*next_command)
+
+def print_help():
+    """
+    Generates help text for the !text command.
+    """
+    return """
+<p>Generate text using Ollama's Mistral 7B Instruct model</p>
+
+<p>Usage:</p>
+<ul>
+<li>!text <prompt> - Basic prompt for the model</li>
+<li>Optional arguments:</li>
+<ul>
+    <li>--max_tokens MAX_TOKENS - Maximum tokens to generate (default 512)</li>
+    <li>--temperature TEMPERATURE - Sampling temperature (default 0.7)</li>
+</ul>
+</ul>
+"""