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diff --git a/rag/generator/ollama.py b/rag/generator/ollama.py
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+import os
+from typing import Any, Generator, List
+
+import ollama
+from loguru import logger as log
+
+from .prompt import Prompt
+from .abstract import AbstractGenerator
+
+try:
+ from rag.retriever.vector import Document
+except ModuleNotFoundError:
+ from retriever.vector import Document
+
+SYSTEM_PROMPT = (
+ "# System Preamble"
+ "## Basic Rules"
+ "When you answer the user's requests, you cite your sources in your answers, according to those instructions."
+ "Answer the following question using the provided context.\n"
+ "## Style Guide"
+ "Unless the user asks for a different style of answer, you should answer "
+ "in full sentences, using proper grammar and spelling."
+)
+
+
+class Ollama(metaclass=AbstractGenerator):
+ def __init__(self) -> None:
+ self.model = os.environ["GENERATOR_MODEL"]
+
+ def __context(self, documents: List[Document]) -> str:
+ results = [
+ f"Document: {i}\ntitle: {doc.title}\n{doc.text}"
+ for i, doc in enumerate(documents)
+ ]
+ return "\n".join(results)
+
+ def __metaprompt(self, prompt: Prompt) -> str:
+ # Include sources
+ metaprompt = (
+ f'Question: "{prompt.query.strip()}"\n\n'
+ "Context:\n"
+ "<result>\n"
+ f"{self.__context(prompt.documents)}\n\n"
+ "</result>\n"
+ "Carefully perform the following instructions, in order, starting each "
+ "with a new line.\n"
+ "Firstly, Decide which of the retrieved documents are relevant to the "
+ "user's last input by writing 'Relevant Documents:' followed by "
+ "comma-separated list of document numbers.\n If none are relevant, you "
+ "should instead write 'None'.\n"
+ "Secondly, Decide which of the retrieved documents contain facts that "
+ "should be cited in a good answer to the user's last input by writing "
+ "'Cited Documents:' followed a comma-separated list of document numbers. "
+ "If you dont want to cite any of them, you should instead write 'None'.\n"
+ "Thirdly, Write 'Answer:' followed by a response to the user's last input "
+ "in high quality natural english. Use the retrieved documents to help you. "
+ "Do not insert any citations or grounding markup.\n"
+ "Finally, Write 'Grounded answer:' followed by a response to the user's "
+ "last input in high quality natural english. Use the symbols <co: doc> and "
+ "</co: doc> to indicate when a fact comes from a document in the search "
+ "result, e.g <co: 0>my fact</co: 0> for a fact from document 0."
+ )
+ return metaprompt
+
+ def generate(self, prompt: Prompt) -> Generator[Any, Any, Any]:
+ log.debug("Generating answer...")
+ metaprompt = self.__metaprompt(prompt)
+ for chunk in ollama.generate(
+ model=self.model, prompt=metaprompt, system=SYSTEM_PROMPT, stream=True
+ ):
+ yield chunk["response"]