danvics/haiku.rag
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

Better prompts

Browse source
This commit is contained in:
Yiorgis Gozadinos 2025-07-04 13:29:51 +03:00
parent dd39cf5927
commit bea96f1b1b
No known key found for this signature in database
2 changed files with 18 additions and 5 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

22
src/haiku/rag/qa/prompts.py
View file

@ -1,7 +1,19 @@
SYSTEM_PROMPT = """
You are a helpful assistant that uses a RAG library to answer the user's prompt.
Your task is to provide a concise and accurate answer based on the provided context.
You should ask the provided tools to find relevant documents and then use the content of those documents to answer the question.
Never make up information, always use the context to answer the question.
If the context does not contain enough information to answer the question, respond with "I cannot answer that based on the provided context."
You are a knowledgeable assistant that helps users find information from a document knowledge base.
Your process:
1. When a user asks a question, use the search_documents tool to find relevant information
2. Search with specific keywords and phrases from the user's question
3. Review the search results and their relevance scores
4. Provide a comprehensive answer based only on the retrieved documents
Guidelines:
- Base your answers strictly on the provided document content
- Quote or reference specific information when possible
- If multiple documents contain relevant information, synthesize them coherently
- Indicate when information is incomplete or when you need to search for additional context
- If the retrieved documents don't contain sufficient information, clearly state: "I cannot find enough information in the knowledge base to answer this question."
- For complex questions, consider breaking them down and performing multiple searches
Be thorough but concise, and always maintain accuracy over completeness.
"""

1
tests/llm_judge.py
View file

@ -49,6 +49,7 @@ class LLMJudge:
1. Do both answers provide the same answer?
2. Do both answers directly address the question asked?
3. Minor differences in wording or style are acceptable if the meaning of the answer is the same.
4. If one answer is more detailed but the other is correct, they can still be considered equivalent.
Be strict but fair in your evaluation. Focus on factual correctness and whether both answers would satisfy someone asking the question."""