aktueller stand

src/agents/base.py

@@ -0,0 +1,120 @@
+"""Base agent class."""
+import asyncio
+from abc import ABC, abstractmethod
+from typing import Any, Dict, Optional
+from openai import OpenAI
+import httpx
+from loguru import logger
+
+from src.config import settings
+
+
+class BaseAgent(ABC):
+    """Base class for all AI agents."""
+
+    def __init__(self, name: str):
+        """
+        Initialize base agent.
+
+        Args:
+            name: Name of the agent
+        """
+        self.name = name
+        self.openai_client = OpenAI(api_key=settings.openai_api_key)
+        logger.info(f"Initialized {name} agent")
+
+    @abstractmethod
+    async def process(self, *args, **kwargs) -> Any:
+        """Process the agent's task."""
+        pass
+
+    async def call_openai(
+        self,
+        system_prompt: str,
+        user_prompt: str,
+        model: str = "gpt-4o",
+        temperature: float = 0.7,
+        response_format: Optional[Dict[str, str]] = None
+    ) -> str:
+        """
+        Call OpenAI API.
+
+        Args:
+            system_prompt: System message
+            user_prompt: User message
+            model: Model to use
+            temperature: Temperature for sampling
+            response_format: Optional response format (e.g., {"type": "json_object"})
+
+        Returns:
+            Assistant's response
+        """
+        logger.info(f"[{self.name}] Calling OpenAI ({model})")
+
+        messages = [
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": user_prompt}
+        ]
+
+        kwargs = {
+            "model": model,
+            "messages": messages,
+            "temperature": temperature
+        }
+
+        if response_format:
+            kwargs["response_format"] = response_format
+
+        # Run synchronous OpenAI call in thread pool to avoid blocking event loop
+        response = await asyncio.to_thread(
+            self.openai_client.chat.completions.create,
+            **kwargs
+        )
+
+        result = response.choices[0].message.content
+        logger.debug(f"[{self.name}] Received response (length: {len(result)})")
+
+        return result
+
+    async def call_perplexity(
+        self,
+        system_prompt: str,
+        user_prompt: str,
+        model: str = "sonar"
+    ) -> str:
+        """
+        Call Perplexity API for research.
+
+        Args:
+            system_prompt: System message
+            user_prompt: User message
+            model: Model to use
+
+        Returns:
+            Assistant's response
+        """
+        logger.info(f"[{self.name}] Calling Perplexity ({model})")
+
+        url = "https://api.perplexity.ai/chat/completions"
+        headers = {
+            "Authorization": f"Bearer {settings.perplexity_api_key}",
+            "Content-Type": "application/json"
+        }
+
+        payload = {
+            "model": model,
+            "messages": [
+                {"role": "system", "content": system_prompt},
+                {"role": "user", "content": user_prompt}
+            ]
+        }
+
+        async with httpx.AsyncClient() as client:
+            response = await client.post(url, json=payload, headers=headers, timeout=60.0)
+            response.raise_for_status()
+            result = response.json()
+
+        content = result["choices"][0]["message"]["content"]
+        logger.debug(f"[{self.name}] Received Perplexity response (length: {len(content)})")
+
+        return content