Wip memory

2 files changed, 72 insertions, 0 deletions

diff --git a/rag/retriever/memory.py b/rag/retriever/memory.py
new file mode 100644
index 0000000..c4455ed
--- /dev/null
+++ b/rag/retriever/memory.py
@@ -0,0 +1,51 @@
+from dataclasses import dataclass
+from typing import Dict, List
+
+
+@dataclass
+class Log:
+    user: Message
+    bot: Message
+
+    def get():
+        return (user, bot)
+
+
+@dataclass
+class Message:
+    role: str
+    message: str
+
+    def as_dict(self, model: str) -> Dict[str, str]:
+        if model == "cohere":
+            match self.role:
+                case "user":
+                    role = "USER"
+                case _:
+                    role = "CHATBOT"
+
+            return {"role": role, "message": self.message}
+        else:
+            return {"role": self.role, "content": self.message}
+
+
+class Memory:
+    def __init__(self, reranker) -> None:
+        self.history = []
+        self.reranker = reranker
+        self.user = "user"
+        self.bot = "assistant"
+
+    def add(self, prompt: str, response: str):
+        self.history.append(
+            Log(
+                user=Message(role=self.user, message=prompt),
+                bot=Message(role=self.bot, message=response),
+            )
+        )
+
+    def get(self) -> List[Log]:
+        return [m.as_dict() for log in self.history for m in log.get()]
+
+    def reset(self):
+        self.history = []
diff --git a/rag/retriever/rerank/local.py b/rag/retriever/rerank/local.py
index 75fedd8..8e94882 100644
--- a/rag/retriever/rerank/local.py
+++ b/rag/retriever/rerank/local.py
@@ -1,9 +1,11 @@
 import os
+from typing import List
 
 from loguru import logger as log
 from sentence_transformers import CrossEncoder
 
 from rag.generator.prompt import Prompt
+from rag.retriever.memory import Log
 from rag.retriever.rerank.abstract import AbstractReranker
 
 
@@ -33,3 +35,22 @@ class Reranker(metaclass=AbstractReranker):
                 prompt.documents[r.get("corpus_id", 0)] for r in ranking
             ]
         return prompt
+
+    def rank_memory(self, prompt: Prompt, history: List[Log]) -> List[Log]:
+        if history:
+            results = self.model.rank(
+                query=prompt.query,
+                documents=[m.bot.message for m in history],
+                return_documents=False,
+                top_k=self.top_k,
+            )
+            ranking = list(
+                filter(
+                    lambda x: x.get("score", 0.0) > self.relevance_threshold, results
+                )
+            )
+            log.debug(
+                f"Reranking gave {len(ranking)} relevant messages of {len(history)}"
+            )
+            history = [history[r.get("corpus_id", 0)] for r in ranking]
+        return history