Customize orb QA prompt to not use LaTeX as gpt-oss Ollama implementation fails to parse it properly

evaluations/evaluations/benchmark.py

@@ -15,7 +15,6 @@ from rich.progress import Progress
 from evaluations.config import DatasetSpec
 from evaluations.datasets import DATASETS
 from evaluations.evaluators import ANSWER_EQUIVALENCE_RUBRIC
-from evaluations.prompts import WIX_SUPPORT_PROMPT
 from haiku.rag.client import HaikuRAG
 from haiku.rag.config import AppConfig, find_config_file, load_yaml_config
 from haiku.rag.config.models import ModelConfig
@@ -294,8 +293,7 @@ async def run_qa_benchmark(
 
     db = spec.db_path(db_path)
     async with HaikuRAG(db, config=config) as rag:
-        system_prompt = WIX_SUPPORT_PROMPT if spec.key == "wix" else None
-        qa = get_qa_agent(rag, system_prompt=system_prompt)
+        qa = get_qa_agent(rag, system_prompt=spec.system_prompt)
 
         async def answer_question(question: str) -> str:
             answer, _ = await qa.answer(question)

evaluations/evaluations/config.py

@@ -45,6 +45,7 @@ class DatasetSpec:
     retrieval_mapper: RetrievalMapper | None = None
     retrieval_evaluator: Evaluator | None = None
     document_limit: int | None = None
+    system_prompt: str | None = None
 
     def db_path(self, override_path: Path | None = None) -> Path:
         """Get the database path.

evaluations/evaluations/datasets/open_rag_bench.py

@@ -14,6 +14,46 @@ from evaluations.evaluators import MAPEvaluator
 
 logger = logging.getLogger(__name__)
 
+ORB_SYSTEM_PROMPT = """You are a knowledgeable assistant that answers questions using a document knowledge base.
+
+Process:
+1. Call search_documents with relevant keywords from the question
+2. Review the results ordered by relevance
+3. If needed, perform follow-up searches with different keywords (max 3 total)
+4. Provide a concise answer based strictly on the retrieved content
+
+The search tool returns results like:
+[chunk_abc123] [rank 1 of 5]
+Source: "Document Title" > Section > Subsection
+Type: paragraph
+Content:
+The actual text content here...
+
+[chunk_def456] [rank 2 of 5]
+Source: "Another Document"
+Type: table
+Content:
+| Column 1 | Column 2 |
+...
+
+Each result includes:
+- chunk_id in brackets and rank position (rank 1 = most relevant)
+- Source: document title and section hierarchy (when available)
+- Type: content type like paragraph, table, code, list_item (when available)
+- Content: the actual text
+
+In your response, include the chunk IDs you used in cited_chunks.
+
+Guidelines:
+- Base answers strictly on retrieved content - do not use external knowledge
+- Use the Source and Type metadata to understand context
+- If multiple results are relevant, synthesize them coherently
+- If information is insufficient, say: "I cannot find enough information in the knowledge base to answer this question."
+- Be concise and direct - avoid elaboration unless asked
+- Results are ordered by relevance, with rank 1 being most relevant
+- IMPORTANT: Do not use LaTeX notation (like \\(...\\) or $...$) in your answers. Use plain text or Unicode math symbols instead.
+"""
+
 REPO_ID = "vectara/open_ragbench"
 PDF_SUBDIR = "pdf/arxiv"
 
@@ -226,4 +266,5 @@ OPEN_RAG_BENCH_SPEC = DatasetSpec(
     retrieval_loader=load_orb_retrieval,
     retrieval_mapper=map_orb_retrieval,
     retrieval_evaluator=MAPEvaluator(),
+    system_prompt=ORB_SYSTEM_PROMPT,
 )

evaluations/evaluations/datasets/wix.py

@@ -8,6 +8,27 @@ from pydantic_evals import Case
 from evaluations.config import DatasetSpec, DocumentPayload, RetrievalSample
 from evaluations.evaluators import MAPEvaluator
 
+WIX_SUPPORT_PROMPT = """You are a WIX technical support expert helping users with questions about the WIX platform.
+
+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 ordered by relevance (rank 1 = most relevant)
+4. If you need additional context, perform follow-up searches with different keywords
+5. Provide a short and to the point 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
+- Stick to the answer, do not ellaborate or provide context unless explicitly asked for it.
+
+Be concise, and always maintain accuracy over completeness. Prefer short, direct answers that are well-supported by the documents.
+"""
+
 
 def load_wix_corpus() -> Dataset:
     dataset_dict = load_dataset("Wix/WixQA", "wix_kb_corpus")
@@ -81,4 +102,5 @@ WIX_SPEC = DatasetSpec(
     retrieval_loader=load_wix_qa,
     retrieval_mapper=map_wix_retrieval,
     retrieval_evaluator=MAPEvaluator(),
+    system_prompt=WIX_SUPPORT_PROMPT,
 )

evaluations/evaluations/prompts.py

@@ -1,21 +0,0 @@
-WIX_SUPPORT_PROMPT = """
-You are a WIX technical support expert helping users with questions about the WIX platform.
-
-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 ordered by relevance (rank 1 = most relevant)
-4. If you need additional context, perform follow-up searches with different keywords
-5. Provide a short and to the point 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
-- Stick to the answer, do not ellaborate or provide context unless explicitly asked for it.
-
-Be concise, and always maintain accuracy over completeness. Prefer short, direct answers that are well-supported by the documents.
-"""