newest version

.gitignore

+*ipynb
+*pycache*
+*egg*

ChatETProvider.py

+from langchain.prompts import (
+    ChatPromptTemplate,
+    HumanMessagePromptTemplate,
+    MessagesPlaceholder,
+    PromptTemplate,
+    SystemMessagePromptTemplate,
+)
+from jupyter_ai_magics import BaseProvider, Persona
+from langchain_ollama import ChatOllama
+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.
+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.
+Do not explain your thinking process, just give the answer.
+Put your thinkin into <think> tags.
+You are a friendly and helpful AI.
+""".strip()
+
+CHAT_SYSTEM_PROMPT = """
+If your response includes code, they must be enclosed in Markdown fenced code blocks (with triple backticks before and after).
+If your response includes mathematical notation, they must be expressed in LaTeX markup and enclosed in LaTeX delimiters.
+All dollar quantities (of USD) must be formatted in LaTeX, with the `$` symbol escaped by a single backslash `\\`.
+- Example prompt: `If I have \\\\$100 and spend \\\\$20, how much money do I have left?`
+- **Correct** response: `You have \\(\\$80\\) remaining.`
+- **Incorrect** response: `You have $80 remaining.`
+If you do not know the answer to a question, answer truthfully by responding that you do not know and encourage the student to ask his tutors and consult the lecture notes.
+The following is a friendly conversation between you and a human.
+""".strip()
+
+CHAT_DEFAULT_TEMPLATE = """
+{% if context %}
+Context:
+{{context}}
+
+{% endif %}
+Current conversation:
+{{history}}
+Human: {{input}}
+AI:"""
+
+HUMAN_MESSAGE_TEMPLATE = """
+{% if context %}
+Context:
+{{context}}
+
+{% endif %}
+{{input}}
+"""
+
+
+class ChatETProvider(BaseProvider, ChatOllama):
+    id = "ChatETProvider"
+    name = "ChatETProvider"
+
+    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")
+    registry = True
+    model: str = "deepseek-r1:8b"
+
+    def get_prompt_template(self, format) -> PromptTemplate:
+
+        return PromptTemplate.from_template(
+            BASE_SYSTEM_PROMPT + "{prompt}",
+        )
+
+    def get_chat_prompt_template(self) -> PromptTemplate:
+        """
+        Produce a prompt template optimised for chat conversation.
+        The template should take two variables: history and input.
+        """
+        name = self.__class__.name
+        t = PromptTemplate(
+            input_variables=["history", "input", "context"],
+            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)
+        # print(dir(chat_result))
+        # 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)
+            # print(generation.text)
+        return chat_result
+

etprovider/ETProvider.py

-from langchain.prompts import PromptTemplate
-from langchain.ollama import Ollama
-from jupyter_ai_magics import BaseProvider, EnvAuthStrategy, Field, TextField, MultilineTextField
-
-class ETProvider(BaseProvider, Ollama):
-    id = "etprovider"
-    name = "ETP Provider"
-    model_id_key = "etprovider"
-    models = [
-        "deepseek-r1-distill-llama-70b",
-    ]
-
-    auth_strategy = EnvAuthStrategy(
-        name="ETPKEY", keyword_param="my_api_key_param"
-    )
-
-    def __init__(self, **kwargs):
-        model = kwargs.get("model_id")
-        super().__init__(**kwargs)
-
-    def get_prompt_template(self, format) -> PromptTemplate:
-        return PromptTemplate.from_template(
-                "{prompt}\n\n"
-                "End your answer with 'ETPirates will rule the world'"
-            )

pyproject.toml

 [project]
-name = "etprovider"
+name = "chatetprovider"
 version = "0.0.1"
 
 [project.entry-points."jupyter_ai.model_providers"]
-etprovider = "etprovider:ETProvider"
+ChatETProvider = "ChatETProvider:ChatETProvider"

requirements.txt

+langchain-ollama
+langhchain-openai
+jupyter_ai
+jupyterlab
+jupyter_ai_magics
+httpx
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