From 98f8d1d535c30d8c1ca6c7b52e634a99b88acf10 Mon Sep 17 00:00:00 2001
From: Gustaf Rydholm <gustaf.rydholm@gmail.com>
Date: Thu, 11 Apr 2024 00:28:29 +0200
Subject: Add some prompt engineering

---
 rag/generator/ollama.py | 44 +++++++++-----------------------------------
 1 file changed, 9 insertions(+), 35 deletions(-)

(limited to 'rag/generator/ollama.py')

diff --git a/rag/generator/ollama.py b/rag/generator/ollama.py
index 87f9672..abd5599 100644
--- a/rag/generator/ollama.py
+++ b/rag/generator/ollama.py
@@ -9,16 +9,6 @@ from rag.retriever.vector import Document
 from .abstract import AbstractGenerator
 from .prompt import Prompt
 
-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:
@@ -32,37 +22,21 @@ class Ollama(metaclass=AbstractGenerator):
         return "\n".join(results)
 
     def __metaprompt(self, prompt: Prompt) -> str:
-        # Include sources
         metaprompt = (
-            f'Question: "{prompt.query.strip()}"\n\n'
-            "Context:\n"
-            "<result>\n"
+            "Answer the question based only on the following context:"
+            "<context>\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."
+            "</context>\n"
+            "Given the context information and not prior knowledge, answer the question."
+            "If the context is irrelevant to the question, answer that you do not know "
+            "the answer to the question given the context.\n"
+            f"Question: {prompt.query.strip()}\n\n"
+            "Answer:"
         )
         return metaprompt
 
     def generate(self, prompt: Prompt) -> Generator[Any, Any, Any]:
         log.debug("Generating answer with ollama...")
         metaprompt = self.__metaprompt(prompt)
-        for chunk in ollama.generate(
-            model=self.model, prompt=metaprompt, system=SYSTEM_PROMPT, stream=True
-        ):
+        for chunk in ollama.generate(model=self.model, prompt=metaprompt, stream=True):
             yield chunk["response"]
-- 
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