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app/core/prompts/evaluator_prompt.py

@@ -1,37 +1,70 @@
-# evaluator_prompt.py# # evaluator_prompt.py
-
-
-from langchain_core.prompts import PromptTemplate
-
-evaluator_prompt = PromptTemplate(
-    input_variables=["query", "answer", "context"],
-    template="""
-You are an evaluation system.
-
-Evaluate the AI response strictly based on the given context.
-
-Rules:
-- Be strict
-- Output ONLY valid JSON
-- No explanation
-- No markdown
-- No text before or after JSON
-
-Query:
-{query}
-
-Answer:
-{answer}
-
-Context:
-{context}
-
-Return ONLY this JSON:
-
-{{
-  "relevance_score": 0.0,
-  "context_usage": 0.0,
-  "hallucination": false
-}}
-"""
-)
+# # evaluator_prompt.py
+
+# from langchain_core.prompts import PromptTemplate
+
+# evaluator_prompt = PromptTemplate(
+#     input_variables=["query", "answer", "context"],
+#     template="""
+# Evaluate the AI response.
+
+# Rules:
+# - Be strict
+# - Output ONLY valid JSON
+# - No explanation
+
+# Query:
+# {query}
+
+# Answer:
+# {answer}
+
+# Context:
+# {context}
+
+# Return:
+# {
+#   "relevance_score": number (0 to 1),
+#   "context_usage": number (0 to 1),
+#   "hallucination": true/false
+# }
+# """
+# )
+
+
+
+
+
+
+
+
+
+
+
+
+
+# You are an evaluation system.
+
+# Evaluate the AI response strictly based on the given context.
+
+from langchain_core.prompts import PromptTemplate
+
+evaluator_prompt = PromptTemplate(
+    input_variables=["query", "answer", "context"],
+    template="""You are a JSON-only evaluator. Output a single JSON object. No other text.
+
+
+Query: {query}
+Answer: {answer}
+Context (first 600 chars): {context}
+
+
+Score these three fields:
+- hallucination (bool): true if answer contains facts NOT in context
+- context_usage (float 0-1): how much the answer uses the context
+- relevance_score (float 0-1): how well the answer addresses the query
+
+JSON:
+""")
+
+# Output this exact JSON and nothing else:
+# {{"relevance_score": 0.0, "context_usage": 0.0, "hallucination": false}}

app/core/prompts/rag_prompt.py

@@ -5,17 +5,15 @@ from langchain_core.prompts import PromptTemplate
 rag_prompt = PromptTemplate(
     input_variables=["context", "query"],
     template=(
-        "You are a document intelligence system.\n"
-        "Answer ONLY using the provided context.\n"
-        "If answer is not present, say: 'Not in document'.\n\n"
-
-        "Keep response concise:\n"
-        "- Short explanation\n"
-        "- Bullet points if useful\n"
-        "- Max 120 words\n\n"
-
-        "Avoid repeating the question.\n\n"
-
+        "You are a precise document assistant.\n"
+        "Your ONLY source of truth is the context below.\n"
+        "STRICT RULES:\n"
+        "- Never use outside knowledge\n"
+        "- If the answer is not in the context, respond EXACTLY: "
+        "'The document does not contain information about this.'\n"
+        "- Do not guess, infer, or expand beyond what is written\n"
+        "- Be concise: short explanation + bullet points if helpful\n\n"
+        "Conversation History:\n{history}\n\n"  # ✅ added history here
         "Context:\n{context}\n\n"
         "Question:\n{query}\n\n"
         "Answer:"