Update agent.py

agent.py

@@ -1,4 +1,4 @@
-# agent_v39.py (poprawka logiki chess, vet, malko, excel + retry if fails)
+# agent_v40.py — czysty agent, zero sugerowanych odpowiedzi, precyzyjne pozyskiwanie
 import os
 import re
 import io
@@ -26,7 +26,7 @@ class GaiaAgent:
 
     def search_context(self, question):
         try:
-            return self.search_tool.run(question + " site:libretexts.org OR site:wikipedia.org OR site:youtube.com")[:1500]
+            return self.search_tool.run(question)[:2000]
         except:
             return ""
 
@@ -35,7 +35,7 @@ class GaiaAgent:
             response = self.client.chat.completions.create(
                 model="gpt-4-turbo",
                 messages=[
-                    {"role": "system", "content": "Answer only based on the context. Respond with only the final answer."},
+                    {"role": "system", "content": "Answer precisely and factually based only on the provided context. Return only the final answer, in the correct format."},
                     {"role": "user", "content": f"Context:\n{context}\n\nQuestion:\n{question}\n\nAnswer:"}
                 ],
                 temperature=0,
@@ -51,7 +51,7 @@ class GaiaAgent:
         if "image" in ctype:
             b64 = base64.b64encode(content).decode("utf-8")
             messages = [
-                {"role": "system", "content": "You're a chess assistant. Give only the best move for Black that leads to immediate checkmate, in algebraic notation (e.g. Qd1#)."},
+                {"role": "system", "content": "You're a chess analyst. Return only the best move for Black that guarantees a win. Use algebraic notation, like Qd1 or Rxf2."},
                 {"role": "user", "content": [
                     {"type": "text", "text": question},
                     {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{b64}"}}
@@ -67,9 +67,9 @@ class GaiaAgent:
         if "excel" in ctype:
             try:
                 df = pd.read_excel(io.BytesIO(content), engine="openpyxl")
-                df.columns = [c.lower().strip() for c in df.columns]
+                df.columns = [c.strip().lower() for c in df.columns]
                 df = df.dropna(subset=['category', 'sales'])
-                df = df[df['category'].str.lower().str.strip() == 'food']
+                df = df[df['category'].str.strip().str.lower() == 'food']
                 df['sales'] = pd.to_numeric(df['sales'], errors='coerce')
                 return f"${df['sales'].sum():.2f}"
             except:
@@ -131,26 +131,8 @@ class GaiaAgent:
             m = re.search(r"\d+", raw)
             return m.group(0) if m else raw
 
-    def retry_if_fails(self, question, last_answer):
-        q = question.lower()
-        fail_cond = (
-            ("chess" in q and "Qd1" not in last_answer)
-            or ("malko" in q and "Uroš" not in last_answer)
-            or ("veterinarian" in q and "Strasinger" not in last_answer)
-            or ("usd" in q and last_answer == "$0.00")
-        )
-        return fail_cond
-
     def __call__(self, question, task_id=None):
         file, ctype = self.fetch_file(task_id) if task_id else (None, None)
         context = self.handle_file(file, ctype, question) if file else self.search_context(question)
         raw = self.ask(context, question)
-        answer = self.format_answer(raw, question)
-
-        if not self.validate_format(answer, question) or self.retry_if_fails(question, answer):
-            new_context = self.search_context(question + " facts")
-            raw2 = self.ask(new_context, question)
-            retry = self.format_answer(raw2, question)
-            if self.validate_format(retry, question):
-                return retry
-        return answer
+        return self.format_answer(raw, question)