feat: Added Podcast Feature and its actually fast.

- Fully Async

surfsense_backend/app/tasks/podcast_tasks.py

@@ -0,0 +1,94 @@
+from sqlalchemy.ext.asyncio import AsyncSession
+from app.schemas import PodcastGenerateRequest
+from typing import List
+from sqlalchemy import select
+from app.db import Chat, Podcast
+from app.agents.podcaster.graph import graph as podcaster_graph
+from surfsense_backend.app.agents.podcaster.state import State
+
+
+async def generate_document_podcast(
+    session: AsyncSession,
+    document_id: int,
+    search_space_id: int,
+    user_id: int
+):
+    # TODO: Need to fetch the document chunks, then concatenate them and pass them to the podcast generation model
+    pass
+
+
+
+async def generate_chat_podcast(
+    session: AsyncSession,
+    chat_id: int,
+    search_space_id: int,
+    podcast_title: str
+):
+    # Fetch the chat with the specified ID
+    query = select(Chat).filter(
+        Chat.id == chat_id,
+        Chat.search_space_id == search_space_id
+    )
+    
+    result = await session.execute(query)
+    chat = result.scalars().first()
+    
+    if not chat:
+        raise ValueError(f"Chat with id {chat_id} not found in search space {search_space_id}")
+    
+    # Create chat history structure
+    chat_history_str = "<chat_history>"
+    
+    for message in chat.messages:
+        if message["role"] == "user":
+            chat_history_str += f"<user_message>{message['content']}</user_message>"
+        elif message["role"] == "assistant":
+            # Last annotation type will always be "ANSWER" here
+            answer_annotation = message["annotations"][-1]
+            answer_text = ""
+            if answer_annotation["type"] == "ANSWER":
+                answer_text = answer_annotation["content"]
+                # If content is a list, join it into a single string
+                if isinstance(answer_text, list):
+                    answer_text = "\n".join(answer_text)
+                chat_history_str += f"<assistant_message>{answer_text}</assistant_message>"
+                
+    chat_history_str += "</chat_history>"
+    
+    # Pass it to the SurfSense Podcaster
+    config = {
+        "configurable": {
+            "podcast_title" : "Surfsense",
+        }
+    }
+    # Initialize state with database session and streaming service
+    initial_state = State(
+        source_content=chat_history_str,
+    )
+    
+    # Run the graph directly
+    result = await podcaster_graph.ainvoke(initial_state, config=config)
+    
+    # Convert podcast transcript entries to serializable format
+    serializable_transcript = []
+    for entry in result["podcast_transcript"]:
+        serializable_transcript.append({
+            "speaker_id": entry.speaker_id,
+            "dialog": entry.dialog
+        })
+    
+    # Create a new podcast entry
+    podcast = Podcast(
+        title=f"{podcast_title}",
+        podcast_transcript=serializable_transcript,
+        file_location=result["final_podcast_file_path"],
+        search_space_id=search_space_id
+    )
+    
+    # Add to session and commit
+    session.add(podcast)
+    await session.commit()
+    await session.refresh(podcast)
+    
+    return podcast
+