4 files changed, 46 insertions, 33 deletions
diff --git a/rag/generator/abstract.py b/rag/generator/abstract.py
index 1beacfb..995e937 100644
--- a/rag/generator/abstract.py
+++ b/rag/generator/abstract.py
@@ -1,6 +1,8 @@
 from abc import abstractmethod
 from typing import Any, Generator
 
+from rag.rag import Message
+
 from .prompt import Prompt
 
 
@@ -14,5 +16,7 @@ class AbstractGenerator(type):
         return cls._instances[cls]
 
     @abstractmethod
-    def generate(self, prompt: Prompt) -> Generator[Any, Any, Any]:
+    def generate(
+        self, prompt: Prompt, messages: List[Message]
+    ) -> Generator[Any, Any, Any]:
         pass
diff --git a/rag/generator/cohere.py b/rag/generator/cohere.py
index fb0cc5b..f30fe69 100644
--- a/rag/generator/cohere.py
+++ b/rag/generator/cohere.py
@@ -1,12 +1,14 @@
 import os
 from dataclasses import asdict
-from typing import Any, Dict, Generator, List, Optional
+from typing import Any, Generator, List
 
 import cohere
 from loguru import logger as log
 
+from rag.rag import Message
+
 from .abstract import AbstractGenerator
-from .prompt import ANSWER_INSTRUCTION, Prompt
+from .prompt import Prompt
 
 
 class Cohere(metaclass=AbstractGenerator):
@@ -14,14 +16,13 @@ class Cohere(metaclass=AbstractGenerator):
         self.client = cohere.Client(os.environ["COHERE_API_KEY"])
 
     def generate(
-        self, prompt: Prompt, history: Optional[List[Dict[str, str]]]
+        self, prompt: Prompt, messages: List[Message]
     ) -> Generator[Any, Any, Any]:
         log.debug("Generating answer from cohere...")
-        query = f"{prompt.query}\n\n{ANSWER_INSTRUCTION}"
         for event in self.client.chat_stream(
-            message=query,
+            message=prompt.to_str(),
             documents=[asdict(d) for d in prompt.documents],
-            chat_history=history,
+            chat_history=[m.as_dict() for m in messages],
             prompt_truncation="AUTO",
         ):
             if event.event_type == "text-generation":
diff --git a/rag/generator/ollama.py b/rag/generator/ollama.py
index 9bf551a..ff5402b 100644
--- a/rag/generator/ollama.py
+++ b/rag/generator/ollama.py
@@ -4,10 +4,10 @@ from typing import Any, Generator, List
 import ollama
 from loguru import logger as log
 
-from rag.retriever.vector import Document
+from rag.rag import Message
 
 from .abstract import AbstractGenerator
-from .prompt import ANSWER_INSTRUCTION, Prompt
+from .prompt import Prompt
 
 
 class Ollama(metaclass=AbstractGenerator):
@@ -15,29 +15,13 @@ class Ollama(metaclass=AbstractGenerator):
         self.model = os.environ["GENERATOR_MODEL"]
         log.debug(f"Using {self.model} for generator...")
 
-    def __context(self, documents: List[Document]) -> str:
-        results = [
-            f"Document: {i}\ntitle: {doc.title}\ntext: {doc.text}"
-            for i, doc in enumerate(documents)
-        ]
-        return "\n".join(results)
-
-    def __metaprompt(self, prompt: Prompt) -> str:
-        metaprompt = (
-            "Context information is below.\n"
-            "---------------------\n"
-            f"{self.__context(prompt.documents)}\n\n"
-            "---------------------\n"
-            f"{ANSWER_INSTRUCTION}"
-            "Do not attempt to answer the query without relevant context and do not use"
-            " prior knowledge or training data!\n"
-            f"Query: {prompt.query.strip()}\n\n"
-            "Answer:"
-        )
-        return metaprompt
-
-    def generate(self, prompt: Prompt, memory: Memory) -> Generator[Any, Any, Any]:
+    def generate(
+        self, prompt: Prompt, messages: List[Message]
+    ) -> Generator[Any, Any, Any]:
         log.debug("Generating answer with ollama...")
-        metaprompt = self.__metaprompt(prompt)
-        for chunk in ollama.chat(model=self.model, messages=memory.append(metaprompt), stream=True):
+        messages = messages.append(
+            Message(role="user", content=prompt.to_str(), client="ollama")
+        )
+        messages = [m.as_dict() for m in messages]
+        for chunk in ollama.chat(model=self.model, messages=messages, stream=True):
             yield chunk["response"]
diff --git a/rag/generator/prompt.py b/rag/generator/prompt.py
index 6523842..4840fdc 100644
--- a/rag/generator/prompt.py
+++ b/rag/generator/prompt.py
@@ -15,3 +15,27 @@ ANSWER_INSTRUCTION = (
 class Prompt:
     query: str
     documents: List[Document]
+    generator_model: str
+
+    def __context(self, documents: List[Document]) -> str:
+        results = [
+            f"Document: {i}\ntitle: {doc.title}\ntext: {doc.text}"
+            for i, doc in enumerate(documents)
+        ]
+        return "\n".join(results)
+
+    def to_str(self) -> str:
+        if self.generator_model == "cohere":
+            return f"{self.query}\n\n{ANSWER_INSTRUCTION}"
+        else:
+            return (
+                "Context information is below.\n"
+                "---------------------\n"
+                f"{self.__context(self.documents)}\n\n"
+                "---------------------\n"
+                f"{ANSWER_INSTRUCTION}"
+                "Do not attempt to answer the query without relevant context and do not use"
+                " prior knowledge or training data!\n"
+                f"Query: {self.query.strip()}\n\n"
+                "Answer:"
+            )