Added chain summarizer prompt

src/agentlab/analyze/error_analysis.py

@@ -1,6 +1,59 @@
 from dataclasses import dataclass
 from bgym import StepInfo
 
+CHANGE_SUMMARIZER_PROMPT = """
+You are a specialized 'change summarizer' model. At a given step in the agent's interaction with the website, 
+you will receive the following pieces of information:
+
+1. The user's MAIN GOAL (e.g., "Open a GitLab issue with label 'help wanted'").
+2. The AGENT'S PREVIOUS OBSERVATION (HTML or AX Tree snippet) or a 'DIFF' that shows what changed since the last step, and the corresponding change summaries.
+3. The AGENT'S CURRENT OBSERVATION (HTML or AX Tree snippet).
+4. The ACTION the agent just took (e.g., "Clicked the button labeled 'Show report'").
+5. (Optionally) The agent's CHAIN OF THOUGHT or short planning notes for this single step, if available.
+
+YOUR TASK (each step):
+A) SUMMARIZE THE CHANGE
+   - Describe what visibly changed between the previous observation (or diff) and the current observation. 
+     For example, did a new panel open, did the form reset, did nothing happen, etc.?
+
+B) ASSESS THE ACTION
+   - Decide whether the agent's action seems helpful or correct given the user's main goal, 
+     or if it appears incorrect/unhelpful. 
+   - Briefly explain why.
+
+OUTPUT FORMAT (per step):
+Return your analysis as a JSON-like structure, for example:
+
+{
+  "changeSummary": "A new search results panel appeared on the right side.",
+  "actionAssessment": "Correct",
+  "explanation": "Clicking 'Search' was appropriate to display the results."
+}
+
+Or for an incorrect action:
+
+{
+  "changeSummary": "The page reloaded but the date fields were reset to defaults.",
+  "actionAssessment": "Incorrect",
+  "explanation": "The agent should have fixed the date format first instead of re-clicking 'Show report'.",
+  "suggestion": "Correct the date format or check for error messages."
+}
+
+Please follow this structure at every step. Keep your responses concise and clear. Below are the details.
+
+Goal: {goal}
+
+LLM Plan: {plan}
+
+Previous Observation: {past_observation}
+
+Current Observation: {current_observation}
+
+Past summaries: {past_summaries}
+
+Action: {action}
+"""
+
 
 def _diff(past_obs, current_obs):
     """TODO: Implement the diff function.
@@ -23,14 +76,29 @@ def summarize(
         """Produces, a summary of the effect of an action."""
         past_obs_message = self.obs_formatter(past_obs)
         current_obs_message = self.obs_formatter(current_obs)
+        goal = past_obs["goal"]
+        plan = past_obs["plan"]
         if self.use_diff:
             current_obs_message = _diff(past_obs_message, current_obs_message)
 
-        return self.llm(self.make_prompt(past_obs_message, current_obs_message, action))
+        return self.llm(
+            self.make_prompt(
+                past_obs_message, action, current_obs_message, past_summaries, goal, plan
+            )
+        )
 
-    def make_prompt(self, past_obs_message, action, current_obs_message, past_summaries):
+    def make_prompt(
+        self, past_obs_message, action, current_obs_message, past_summaries, goal, plan
+    ):
         """TODO: Implement the prompt."""
-        return f"{past_obs_message} {action} {current_obs_message}"
+        return CHANGE_SUMMARIZER_PROMPT.format(
+            goal=goal,
+            plan=plan,
+            past_observation=past_obs_message,
+            current_observation=current_obs_message,
+            past_summaries=past_summaries,
+            action=action,
+        )
 
 
 @dataclass