Address feedbacks

app/pipeline/__init__.py

@@ -1 +1 @@
-from pipeline.pipeline import SimplePipeline
+from pipeline.pipeline import AbstractPipeline

app/pipeline/chat/__init__.py

@@ -0,0 +1 @@
+from simple_chat_pipeline import SimpleChatPipeline

app/pipeline/chat/simple_chat_pipeline.py

@@ -0,0 +1,36 @@
+from operator import itemgetter
+
+from langchain_core.output_parsers import StrOutputParser
+from langchain_core.runnables import Runnable
+
+from domain import IrisMessage, IrisMessageRole
+from llm.langchain import IrisLangchainChatModel
+from pipeline import AbstractPipeline
+
+
+class SimpleChatPipeline(AbstractPipeline):
+    """A simple chat pipeline that uses our custom langchain chat model for our own request handler"""
+
+    llm: IrisLangchainChatModel
+    pipeline: Runnable
+
+    def __init__(self, llm: IrisLangchainChatModel, name=None):
+        self.llm = llm
+        self.pipeline = {"query": itemgetter("query")} | llm | StrOutputParser()
+        super().__init__(name=name)
+
+    def __call__(self, query: IrisMessage, **kwargs):
+        return self._run(query=query, **kwargs)
+
+    def _run(self, query: IrisMessage, **kwargs) -> IrisMessage:
+        """
+        Runs the pipeline and is intended to be called by __call__
+        :param query: The query
+        :param kwargs: keyword arguments
+        :return: IrisMessage
+        """
+        if query is None:
+            raise ValueError("IrisMessage must not be None")
+        message = query.text
+        response = self.pipeline.invoke({"query": message})
+        return IrisMessage(role=IrisMessageRole.ASSISTANT, text=response)

app/pipeline/pipeline.py

@@ -1,39 +1,24 @@
 from abc import ABCMeta, abstractmethod
-from operator import itemgetter
 
-from langchain_core.output_parsers import StrOutputParser
-from domain import IrisMessage, IrisMessageRole
+from domain import IrisMessage
 
 
 class AbstractPipeline(metaclass=ABCMeta):
     """Abstract class for all pipelines"""
 
+    name: str
+
     def __init__(self, name=None):
         self.name = name
 
-    def __repr__(self):
-        return f"{self.__class__.__name__} {self.name if self.name is not None else id(self)}"
-
-    def __str__(self):
-        return f"{self.__class__.__name__} {self.name if self.name is not None else id(self)}"
+    def __call__(self, **kwargs):
+        return self._run(**kwargs)
 
     @abstractmethod
-    def run(self, *args, **kwargs) -> IrisMessage:
-        """Runs the pipeline"""
+    def _run(self, **kwargs) -> IrisMessage:
+        """
+        Runs the pipeline and is intended to be called by __call__
+        :param kwargs: keyword arguments
+        :return: IrisMessage
+        """
         raise NotImplementedError
-
-
-class SimplePipeline(AbstractPipeline):
-    """A simple pipeline that does not have any memory etc."""
-
-    def __init__(self, llm, name=None):
-        super().__init__(name=name)
-        self.llm = llm
-        self.pipeline = {"query": itemgetter("query")} | llm | StrOutputParser()
-
-    def run(self, *args, query: IrisMessage, **kwargs) -> IrisMessage:
-        if query is None:
-            raise ValueError("IrisMessage must not be None")
-        message = query.text
-        response = self.pipeline.invoke({"query": message})
-        return IrisMessage(role=IrisMessageRole.ASSISTANT, text=response)