From 79bf33ca1ccd47e3680e912aebe8bcd243578507 Mon Sep 17 00:00:00 2001
From: Andris Reinman <andris@reinman.eu>
Date: Mon, 2 Oct 2023 15:30:17 +0300
Subject: [PATCH] fix(chat): Include the name and email of the person asking
 the question in the prompt for context

---
 lib/embeddings-query.js | 14 ++++++++++----
 1 file changed, 10 insertions(+), 4 deletions(-)

diff --git a/lib/embeddings-query.js b/lib/embeddings-query.js
index 69fcbfb..8a61771 100644
--- a/lib/embeddings-query.js
+++ b/lib/embeddings-query.js
@@ -21,7 +21,9 @@ You are an automated system designed to extract and provide information based on
 const SCHEMA_PROMPT = `
 **Input Information:**
 
-- **Question Format:** The query is presented using the JSON schema: \`{"question":"What was the date of our last meeting?"}\`
+- **Question Format:** The query is presented using the JSON schema: \`{"name": "John Doe", "email": "john@example.com", "question":"What was the date of our last meeting?"}\`
+
+  - **Question Structure** The question format includes the asked question, and the name and the email address of the user who asked the question, if available.
 
 - **Email Context:** We are provided with a series of emails to analyze.
 
@@ -55,6 +57,10 @@ const SCHEMA_PROMPT = `
    - On a new line, begin with \`Message-ID:\` and cite the unique Message-ID(s) of the emails you sourced your answer from. 
 5. Ensure that the Message-ID is never embedded within the main body of your response.
 6. Avoid including any additional commentary or annotations. 
+
+**Context**:
+
+- The current time is '${new Date().toUTCString()}'.
 `.trim();
 
 const QUESTION_PROMPT = `
@@ -128,10 +134,10 @@ async function embeddingsQuery(apiToken, opts) {
     while (true) {
         prompt = `${SCHEMA_PROMPT}
 
-Input:
-${JSON.stringify({ question })}
+**Input**:
+${JSON.stringify({ name: opts?.userData?.name, email: opts?.userData?.email, question })}
 
-Context emails:
+**Context emails**:
 
 ${promptText}
 `;