summaryrefslogtreecommitdiff
path: root/rag/generator/ollama.py
diff options
context:
space:
mode:
Diffstat (limited to 'rag/generator/ollama.py')
-rw-r--r--rag/generator/ollama.py36
1 files changed, 10 insertions, 26 deletions
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"]