Migrate the MVP into kotaemon (#108)

- Migrate the MVP into kotaemon.
- Preliminary include the pipeline within chatbot interface.
- Organize MVP as an application.

Todo:

- Add an info panel to view the planning of agents -> Fix streaming agents' output.

Resolve: #60
Resolve: #61 
Resolve: #62

knowledgehub/llms/chats/langchain_based.py

@@ -15,15 +15,23 @@ class LCChatMixin:
             "Please return the relevant Langchain class in in _get_lc_class"
         )
 
-    def __init__(self, **params):
+    def __init__(self, stream: bool = False, **params):
         self._lc_class = self._get_lc_class()
         self._obj = self._lc_class(**params)
         self._kwargs: dict = params
+        self._stream = stream
 
         super().__init__()
 
     def run(
         self, messages: str | BaseMessage | list[BaseMessage], **kwargs
+    ) -> LLMInterface:
+        if self._stream:
+            return self.stream(messages, **kwargs)  # type: ignore
+        return self.invoke(messages, **kwargs)
+
+    def invoke(
+        self, messages: str | BaseMessage | list[BaseMessage], **kwargs
     ) -> LLMInterface:
         """Generate response from messages
 
@@ -68,6 +76,10 @@ class LCChatMixin:
             logits=[],
         )
 
+    def stream(self, messages: str | BaseMessage | list[BaseMessage], **kwargs):
+        for response in self._obj.stream(input=messages, **kwargs):
+            yield LLMInterface(content=response.content)
+
     def to_langchain_format(self):
         return self._obj
 
@@ -150,6 +162,9 @@ class AzureChatOpenAI(LCChatMixin, ChatLLM):
         )
 
     def _get_lc_class(self):
-        import langchain.chat_models
+        try:
+            from langchain_community.chat_models import AzureChatOpenAI
+        except ImportError:
+            from langchain.chat_models import AzureChatOpenAI
 
-        return langchain.chat_models.AzureChatOpenAI
+        return AzureChatOpenAI