From e56fa9225c921ba9c889fe3bc0a17cd684691f5e Mon Sep 17 00:00:00 2001
From: "Lennart J. Kurzweg (Nx2)" <git@nx2.site>
Date: Fri, 2 Aug 2024 16:53:45 +0200
Subject: [PATCH] question_fits_to_answer lib func

---
 libs/query_fits_to_answer.py | 52 ++++++++++++++++++++++++++++++++++++
 1 file changed, 52 insertions(+)
 create mode 100644 libs/query_fits_to_answer.py

diff --git a/libs/query_fits_to_answer.py b/libs/query_fits_to_answer.py
new file mode 100644
index 0000000..f42fa3a
--- /dev/null
+++ b/libs/query_fits_to_answer.py
@@ -0,0 +1,52 @@
+from langchain_ollama.chat_models import ChatOllama
+from langchain_core.messages import SystemMessage
+from langchain_core.prompts import HumanMessagePromptTemplate, ChatPromptTemplate
+from langchain.tools import Tool
+
+def query_fits_to_answer(query: str, answer: str) -> bool:
+
+    def rate(rating: bool) -> None:
+        """Rate answer as correct (True) or as incorrect (False)."""
+
+    prompt = ChatPromptTemplate.from_messages([
+        SystemMessage(content="""You are a rating machine. You rate answers as correct if they are
+        1. factually correct (every statement made)
+        2. fitting response to the query answering all questions prompted
+        
+        if the answer does not mach these criteria, rate the answer as incorrect. **Only use the rate tool. Do not answer conversationally**.
+        Do not answer with <I'm sorry but I do not have the capability to perform this task for you, I am happy to help you with any other queries you may have.> or anything like it. Just use the `rate` tool."""),
+        HumanMessagePromptTemplate.from_template(template="""Query:
+        {query}
+
+        Answer:
+        {answer}
+        """)
+    ]).invoke({"query": query, "answer": answer})
+
+    llm = ChatOllama(model="llama3-groq-tool-use:70b").bind_tools([rate])
+
+    ai_msg = llm.invoke(prompt)
+
+    try:
+        return ai_msg.tool_calls[0]['args']['rating']
+    except IndexError as e:
+        print(f"\rValidation Error of <{ai_msg.content}> Retrying...")
+        return query_fits_to_answer(query=query, answer=answer)
+
+if __name__ == "__main__":
+    # print(query_fits_to_answer(
+    #     query="Who is Obama?",
+    #     answer="Barack Obama was the 44th President of the United States, serving two terms from January 2009 to January 2017. He was a significant figure in American politics and made history as the first African American to hold the office."
+    # ))
+    # print(query_fits_to_answer(
+    #     query="Who is Obama?",
+    #     answer="Quantum computing is a revolutionary technology that uses the principles of quantum mechanics to perform calculations and operations on data. It's a fundamentally different approach from classical computing, which is based on bits (0s and 1s) and transistors."
+    # ))
+    # print(query_fits_to_answer(
+    #     query="Who is Obama?",
+    #     answer="Barack Obama was the 72th President of the United States, serving two terms from January 2005 to January 2013. He was a significant figure in American politics and made history as the first Chinese American to hold the office."
+    # ))
+    print(query_fits_to_answer(
+        query="Who is Obama?",
+        answer="Barack Obama was the 45th President of the United States, serving two terms from January 2009 to January 2017. He was a significant figure in American politics and made history as the first Chinese American to hold the office."
+    ))