too much

living_agents/llmagent.py

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+import os
+import logging
+from typing import List, Dict
+
+from llm_connector import LLMClient, LLMBackend
+
+logger = logging.getLogger(__name__)
+
+
+class LLMAgent:
+    client: LLMClient
+
+    def __init__(self, temperature: float = 0.8):
+        # TODO User temperature
+        backend: LLMBackend = {'base_url': os.environ['BACKEND_BASE_URL'],
+                               'api_token': os.environ['BACKEND_API_TOKEN'],
+                               'model': os.environ['BACKEND_MODEL']}
+        agent_backend: LLMBackend = {
+            'base_url': os.environ['AGENT_BASE_URL'],
+            'api_token': os.environ['AGENT_API_TOKEN'],
+            'model': os.environ['AGENT_MODEL']}
+        embedding_backend: LLMBackend = {
+            'base_url': os.environ['EMBEDDING_BASE_URL'],
+            'api_token': os.environ['EMBEDDING_API_TOKEN'],
+            'model': os.environ['EMBEDDING_MODEL']}
+        self.client = LLMClient(agent_backend, embedding_backend)
+        self.temperature = temperature
+
+    async def chat(self, messages: List[Dict[str, str]], max_tokens: int = 200) -> str:
+        logger.info('Chat')
+        try:
+            response = ''
+            async for chunk in self.client.get_response(messages, stream=False):  # type: ignore
+
+                if 'content' in chunk:
+                    response += chunk['content']
+
+            """response = client.chat.completions.create(
+                model=self.model,
+                messages=messages,
+                temperature=self.temperature,
+                max_tokens=max_tokens
+            )"""
+            return response.strip()
+        except Exception as e:
+            return f"[LLM Error: {str(e)}]"
+
+    async def get_embedding(self, text: str) -> List[float]:
+        """Get embedding for memory relevance scoring"""
+        try:
+            response = await self.client.get_embedding(text)
+            """response = client.embeddings.create(
+                model="text-embedding-ada-002",
+                input=text
+            )"""
+            return response
+        except Exception as e:
+            print(f"Embedding error: {e}")
+            return [0.0] * 1536  # Default embedding size