From c470cbd285dcd4cdb64cdfe40d78f3a70d8e36d4 Mon Sep 17 00:00:00 2001
From: sanjay singh <sanjay.singh360@gmail.com>
Date: Mon, 18 May 2026 16:21:46 +0200
Subject: [PATCH] =?UTF-8?q?feat:=20Phase=202=20=E2=80=94=20add=20code=20in?=
 =?UTF-8?q?terpreter=20for=20data=20analysis=20capability?=
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---
 agents/tech-trends-agent.json |  7 ++++---
 evals/eval-config.json        |  4 ++--
 prompts/tech-trends-agent.md  | 12 ++++++++++++
 3 files changed, 18 insertions(+), 5 deletions(-)

diff --git a/agents/tech-trends-agent.json b/agents/tech-trends-agent.json
index 9d6b181..27b84c4 100644
--- a/agents/tech-trends-agent.json
+++ b/agents/tech-trends-agent.json
@@ -1,16 +1,17 @@
 {
   "agent_name": "tech-trends-agent",
-  "phase": "1",
+  "phase": "2",
   "definition": {
     "model": "${GPT_DEPLOYMENT}",
     "instructions_file": "prompts/tech-trends-agent.md",
     "tools": [
-      { "type": "web_search" }
+      { "type": "web_search" },
+      { "type": "code_interpreter" }
     ]
   },
   "eval": {
     "dataset": "evals/golden-dataset.json",
-    "phase_filter": "1",
+    "phase_filter": null,
     "config": "evals/eval-config.json"
   },
   "_model_history": [
diff --git a/evals/eval-config.json b/evals/eval-config.json
index 5cafb0a..dc7cf18 100644
--- a/evals/eval-config.json
+++ b/evals/eval-config.json
@@ -11,6 +11,6 @@
     "groundedness": 0.75,
     "coherence": 0.80
   },
-  "phase_filter": "1",
-  "notes": "Phase 1: Only web search queries evaluated. Phase 2 data analysis queries excluded."
+  "phase_filter": null,
+  "notes": "Phase 2: All queries evaluated — both web search (Phase 1) and data analysis (Phase 2)."
 }
diff --git a/prompts/tech-trends-agent.md b/prompts/tech-trends-agent.md
index e01c7e9..da79c14 100644
--- a/prompts/tech-trends-agent.md
+++ b/prompts/tech-trends-agent.md
@@ -27,3 +27,15 @@ Always structure responses as:
 ## Tone
 Professional, objective, and jargon-aware. Assume the user is a technology
 professional who does not need basic concepts explained.
+
+## Data Analysis (Phase 2)
+You now have access to a code interpreter. Use it when:
+- The user asks you to calculate, compare, or rank numerical data
+- You have retrieved structured data (tables, CSVs) and analysis would add value
+- You need to produce a formatted comparison table from raw information
+
+When using code interpreter:
+1. First retrieve the data via web search
+2. Then write and run Python code to process or compare it
+3. Present results with the code output clearly labelled
+4. Always show the source of the raw data alongside the computed result