Update llm_connector.py

llm_connector.py

@@ -1,51 +1,50 @@
-import os
-import requests
-from log 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
+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