refactor

services/raggr/llm.py

@@ -0,0 +1,73 @@
+import os
+
+from ollama import Client
+from openai import OpenAI
+
+import logging
+from dotenv import load_dotenv
+
+load_dotenv()
+
+logging.basicConfig(level=logging.INFO)
+
+TRY_OLLAMA = os.getenv("TRY_OLLAMA", False)
+
+
+class LLMClient:
+    def __init__(self):
+        try:
+            self.ollama_client = Client(
+                host=os.getenv("OLLAMA_URL", "http://localhost:11434"), timeout=1.0
+            )
+            self.ollama_client.chat(
+                model="gemma3:4b", messages=[{"role": "system", "content": "test"}]
+            )
+            self.PROVIDER = "ollama"
+            logging.info("Using Ollama as LLM backend")
+        except Exception as e:
+            print(e)
+            self.openai_client = OpenAI()
+            self.PROVIDER = "openai"
+            logging.info("Using OpenAI as LLM backend")
+
+    def chat(
+        self,
+        prompt: str,
+        system_prompt: str,
+    ):
+        # Instituting a fallback if my gaming PC is not on
+        if self.PROVIDER == "ollama":
+            try:
+                response = self.ollama_client.chat(
+                    model="gemma3:4b",
+                    messages=[
+                        {
+                            "role": "system",
+                            "content": system_prompt,
+                        },
+                        {"role": "user", "content": prompt},
+                    ],
+                )
+                output = response.message.content
+                return output
+            except Exception as e:
+                logging.error(f"Could not connect to OLLAMA: {str(e)}")
+
+        response = self.openai_client.responses.create(
+            model="gpt-4o-mini",
+            input=[
+                {
+                    "role": "system",
+                    "content": system_prompt,
+                },
+                {"role": "user", "content": prompt},
+            ],
+        )
+        output = response.output_text
+
+        return output
+
+
+if __name__ == "__main__":
+    client = Client()
+    client.chat(model="gemma3:4b", messages=[{"role": "system", "promp": "hack"}])