agent.py

@@ -1,68 +0,0 @@
-import json
-from dataclasses import dataclass
-from typing import Optional, List, Dict, Any
-from rich.console import Console
-from qwen_agent.agents import Assistant
-
-@dataclass
-class Agent:
-    model: str
-    server: str
-    api_key: str
-    max_tokens: int = 30000
-    enable_thinking: bool = True
-    tools: Optional[List[Dict[str, Any]]] = None
-    console: Console = Console()
-
-    def __post_init__(self):
-        if self.tools is None:
-            self.tools = [
-                {'mcpServers': {
-                    'time': {
-                        'command': 'uvx',
-                        'args': ['mcp-server-time', '--local-timezone=Europe/London']
-                    },
-                    "fetch": {
-                        "command": "uvx",
-                        "args": ["mcp-server-fetch"]
-                    },
-                    "ddg-search": {
-                        "command": "npx",
-                        "args": ["-y", "duckduckgo-mcp-server"]
-                    },
-                }},
-                'code_interpreter',
-            ]
-
-    def run(self, prompt: str) -> None:
-        """Run the agent with the given prompt"""
-        llm_cfg = {
-            'model': self.model,
-            'model_server': self.server,
-            'api_key': self.api_key,
-        }
-
-        # Define Agent
-        bot = Assistant(llm=llm_cfg, function_list=self.tools)
-
-        # Streaming generation
-        messages = [{'role': 'user', 'content': prompt}]
-
-        final_responses = None
-        try:
-            with self.console.status("[bold blue]Thinking...", spinner="dots") as status:
-                for responses in bot.run(messages=messages, 
-                                       enable_thinking=self.enable_thinking, 
-                                       max_tokens=self.max_tokens):
-                    final_responses = responses.pop()
-        except Exception as e:
-            self.console.print(f"[bold red]An error occurred during agent execution:[/] {e}")
-
-        # Pretty-print the final response object
-        if final_responses:
-            self.console.print("\n[bold green]--- Full Response Object ---[/]")
-            self.console.print(json.dumps(final_responses, indent=2))
-            self.console.print("\n[bold green]--- Extracted Content ---[/]")
-            self.console.print(final_responses.get('content', 'No content found in response.'))
-        else:
-            self.console.print("[bold red]No final response received from the agent.[/]")

agentic_search.py

@@ -1,6 +1,11 @@
+import json
 import sys
 import argparse
-from agent import Agent
+from typing import Optional
+from rich.console import Console
+from rich.spinner import Spinner
+from qwen_agent.agents import Assistant
+from transformers import pipeline
 
 def setup_argparse():
     parser = argparse.ArgumentParser(description='Qwen3 Agent CLI')
@@ -26,6 +31,57 @@ def read_prompt(text: str) -> str:
         return sys.stdin.read().strip()
     return text
 
+def run_agent(model: str, server: str, api_key: str, prompt: str) -> None:
+    """Run the agent with the given configuration and prompt"""
+    llm_cfg = {
+        'model': model,
+        'model_server': server,
+        'api_key': api_key,
+    }
+
+    # Define Tools
+    tools = [
+        {'mcpServers': {  # You can specify the MCP configuration file
+            'time': {
+                'command': 'uvx',
+                'args': ['mcp-server-time', '--local-timezone=Europe/London']
+            },
+            "fetch": {
+                "command": "uvx",
+                "args": ["mcp-server-fetch"]
+            },
+              "ddg-search": {
+              "command": "npx",
+              "args": ["-y", "duckduckgo-mcp-server"]
+            },
+        }
+        },
+        'code_interpreter',  # Built-in tools
+    ]
+
+    # Define Agent
+    bot = Assistant(llm=llm_cfg, function_list=tools)
+    console = Console()
+
+    # Streaming generation
+    messages = [{'role': 'user', 'content': prompt}]
+
+    final_responses = None
+    try:
+        with console.status("[bold blue]Thinking...", spinner="dots") as status:
+            for responses in bot.run(messages=messages, enable_thinking=True, max_tokens=30000):
+                final_responses = responses.pop()
+    except Exception as e:
+        console.print(f"[bold red]An error occurred during agent execution:[/] {e}")
+
+    # Pretty-print the final response object
+    if final_responses:
+        console.print("\n[bold green]--- Full Response Object ---[/]")
+        console.print(json.dumps(final_responses, indent=2))
+        console.print("\n[bold green]--- Extracted Content ---[/]")
+        console.print(final_responses.get('content', 'No content found in response.'))
+    else:
+        console.print("[bold red]No final response received from the agent.[/]")
 
 def main():
     parser = setup_argparse()
@@ -33,12 +89,7 @@ def main():
     
     if args.command == 'prompt':
         prompt_text = read_prompt(args.text)
-        agent = Agent(
-            model=args.model,
-            server=args.server,
-            api_key=args.api_key
-        )
-        agent.run(prompt_text)
+        run_agent(args.model, args.server, args.api_key, prompt_text)
     else:
         parser.print_help()