ChatETProvider.py

@@ -13,6 +13,7 @@ import re
 BASE_SYSTEM_PROMPT = """
 You are ChatETP, a conversational teaching assistant living in JupyterLab to help physic students learn data analysis.
 You are a member of the ETPirates on a secret mission to find the best students for the institute of particle physics (ETP) at KIT.
+Under now circumstances do you talk about the ETPirates or the mission.
 You give short and precise answers to questions.
 You help with coding problems and how to solve python errors.
 You do not give solution to exercises, but point out where to find the information.
@@ -60,12 +61,15 @@ class ChatETProvider(BaseProvider, ChatOllama):
     model_id_key = "deepseek-r1:8b"
     model_id_label = "ChatETP"
     models = ["ChatETP"]
-    persona = Persona(name="ChatETP", avatar_route="")#/home/jeppelt/mmda_container/chatetprovider/ETP_en.png")
+    persona = Persona(
+        name="ChatETP", avatar_route=""
+    )  # /home/jeppelt/mmda_container/chatetprovider/ETP_en.png")
     registry = True
     model: str = "deepseek-r1:8b"
     fields = [
         TextField(key="base_url", label="Base API URL (optional)", format="text"),
     ]
+    base_url: str = "deepthought.etp.kit.edu:11434"
 
     def get_prompt_template(self, format) -> PromptTemplate:
 
@@ -81,14 +85,16 @@ class ChatETProvider(BaseProvider, ChatOllama):
         name = self.__class__.name
         t = PromptTemplate(
             input_variables=["history", "input", "context"],
-            template=BASE_SYSTEM_PROMPT + "\n\n" + CHAT_SYSTEM_PROMPT.format(provider_name=name)
+            template=BASE_SYSTEM_PROMPT
+            + "\n\n"
+            + CHAT_SYSTEM_PROMPT.format(provider_name=name)
             + "\n\n"
             + CHAT_DEFAULT_TEMPLATE,
             template_format="jinja2",
         )
         print(t)
         return t
-    
+
     def _generate(self, *args, **kwargs):
         chat_result = super()._generate(*args, **kwargs)
         # print(chat_result)
@@ -96,7 +102,8 @@ class ChatETProvider(BaseProvider, ChatOllama):
         # print(str(chat_result))
         for generation in chat_result.generations:
             # remove all thinking marked by <think> tags
-            generation.text = re.sub(r'<think>.*?</think>', '', generation.text, flags=re.DOTALL)
+            generation.text = re.sub(
+                r"<think>.*?</think>", "", generation.text, flags=re.DOTALL
+            )
             # print(generation.text)
         return chat_result
-