From c46dece609ee5fbb3e2c4028a7d5ddeb671e080e Mon Sep 17 00:00:00 2001 From: sanjay singh Date: Tue, 19 May 2026 17:04:40 +0200 Subject: [PATCH] =?UTF-8?q?feat:=20Phase=201=20=E2=80=94=20tech=20trends?= =?UTF-8?q?=20agent=20with=20web=20search?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- agents/tech-trends-agent.json | 12 +++++++++--- evals/eval-config.json | 12 ++++++------ prompts/tech-trends-agent.md | 12 ------------ 3 files changed, 15 insertions(+), 21 deletions(-) diff --git a/agents/tech-trends-agent.json b/agents/tech-trends-agent.json index 502f138..9d6b181 100644 --- a/agents/tech-trends-agent.json +++ b/agents/tech-trends-agent.json @@ -1,13 +1,19 @@ { "agent_name": "tech-trends-agent", + "phase": "1", "definition": { "model": "${GPT_DEPLOYMENT}", "instructions_file": "prompts/tech-trends-agent.md", - "tools": [] + "tools": [ + { "type": "web_search" } + ] }, "eval": { "dataset": "evals/golden-dataset.json", - "phase_filter": null, + "phase_filter": "1", "config": "evals/eval-config.json" - } + }, + "_model_history": [ + { "model": "gpt-4o-2024-11-20", "from": "2025-01-10", "to": null, "reason": "initial" } + ] } diff --git a/evals/eval-config.json b/evals/eval-config.json index 832031e..5cafb0a 100644 --- a/evals/eval-config.json +++ b/evals/eval-config.json @@ -1,9 +1,9 @@ { "evaluators": [ - "TaskAdherenceEvaluator", - "RelevanceEvaluator", - "GroundednessEvaluator", - "CoherenceEvaluator" + "builtin.task_adherence", + "builtin.relevance", + "builtin.groundedness", + "builtin.coherence" ], "thresholds": { "task_adherence": 0.80, @@ -11,6 +11,6 @@ "groundedness": 0.75, "coherence": 0.80 }, - "phase_filter": null, - "notes": "Phase 2: All queries evaluated — both web search (Phase 1) and data analysis (Phase 2)." + "phase_filter": "1", + "notes": "Phase 1: Only web search queries evaluated. Phase 2 data analysis queries excluded." } diff --git a/prompts/tech-trends-agent.md b/prompts/tech-trends-agent.md index da79c14..e01c7e9 100644 --- a/prompts/tech-trends-agent.md +++ b/prompts/tech-trends-agent.md @@ -27,15 +27,3 @@ 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