Delete llm_connector.py

llm_connector.py

@@ -1,50 +0,0 @@
-import os
-import requests
-from utils import log
-
-class LLMConnector:
-    def __init__(self, service_config):
-        self.service_config = service_config
-
-    def call_spark(self, project_name, prompt, chat_history):
-        project = self.service_config.get_project(project_name)
-        if not project:
-            raise Exception(f"Project not found: {project_name}")
-
-        llm_config = project.get("llm", {})
-        if not llm_config:
-            raise Exception(f"LLM config missing for project: {project_name}")
-
-        spark_url = self.service_config.llm_inference_service_url
-        work_mode = self.service_config.work_mode
-        cloud_token = self.service_config.get_auth_token()
-
-        headers = {
-            "Authorization": f"Bearer {cloud_token}",
-            "Content-Type": "application/json"
-        }
-
-        payload = {
-            "work_mode": work_mode,
-            "cloud_token": cloud_token,
-            "project_name": project_name,
-            "project_version": project.get("project_version"),
-            "repo_id": llm_config.get("repo_id"),
-            "generation_config": llm_config.get("generation_config"),
-            "use_fine_tune": llm_config.get("use_fine_tune"),
-            "fine_tune_zip": llm_config.get("fine_tune_zip"),
-            "user_input": chat_history[-1]["content"] if chat_history else "",
-            "system_prompt": prompt,
-            "context": chat_history
-        }
-
-        try:
-            log(f"🚀 Sending request to Spark for project: {project_name}")
-            response = requests.post(f"{spark_url}/generate", json=payload, headers=headers, timeout=60)
-            response.raise_for_status()
-            result = response.json()
-            log("✅ Spark response received successfully.")
-            return result.get("model_answer")
-        except Exception as e:
-            log(f"❌ Spark microservice error: {e}")
-            return None