go

main_agent.py

@@ -158,6 +158,79 @@ async def get_match_performances(match_date: Optional[str] = None, opponent: Opt
         return "\n".join(out)
     except Exception as e:
         return f"❌ Erro: {str(e)}"
+    
+@one_player_agent.tool_plain()
+async def show_available_tables() -> str:
+    query = """
+        SELECT table_name
+        FROM information_schema.tables
+        WHERE table_schema = 'public'
+        ORDER BY table_name
+    """  # listar tabelas via information_schema [web:61]
+    try:
+        results = await db.execute_query_async(query)
+        if not results:
+            return "❌ Nenhuma tabela encontrada no schema public."
+        return "📚 TABELAS:\n" + "\n".join([f"- {r['table_name']}" for r in results])
+    except Exception as e:
+        return f"❌ Erro: {str(e)}"
+    
+@one_player_agent.tool_plain()
+async def get_goal_events(player_scorer: str = None,
+                          assist_from: str = None,
+                          opponent: str = None,
+                          only_crosses: bool = False,
+                          only_high_crosses: bool = False,
+                          limit: int = 50) -> str:
+    # IMPORTANT: troque player_goals_stats pelo nome REAL da sua tabela
+    table = "player_goals_stats"
+
+    where = ["team = 'Barcelona'"]
+    params = []
+
+    if player_scorer:
+        where.append("player_scorer_nick ILIKE %s"); params.append(f"%{player_scorer}%")
+    if assist_from:
+        where.append("pass_from_nick ILIKE %s"); params.append(f"%{assist_from}%")
+    if opponent:
+        where.append("opponent ILIKE %s"); params.append(f"%{opponent}%")
+    if only_crosses:
+        where.append("is_cross_pass = TRUE")
+    if only_high_crosses:
+        where.append("is_cross_pass_high = TRUE")
+
+    params.append(limit)
+    where_sql = " AND ".join(where)
+
+    query = f"""
+        SELECT match_date, opponent, home_away,
+               minute, second,
+               player_scorer_nick, pass_from_nick,
+               is_cross_pass, is_cross_pass_high,
+               play_pattern, shot_type, shot_body_part,
+               xg
+        FROM {table}
+        WHERE {where_sql}
+        ORDER BY match_date DESC, minute DESC, second DESC
+        LIMIT %s
+    """
+    try:
+        results = await db.execute_query_async(query, tuple(params))
+        if not results:
+            return "❌ Sem gols encontrados para esse filtro."
+        out = ["⚽ EVENTOS DE GOL\n"]
+        for i, r in enumerate(results, 1):
+            out.append(
+                f"{i}. {r['match_date']} vs {r['opponent']} ({r['home_away']}) "
+                f"{r.get('minute')}:{r.get('second')} - "
+                f"{r.get('player_scorer_nick')} (assist: {r.get('pass_from_nick')}) | "
+                f"cross={r.get('is_cross_pass')} high_cross={r.get('is_cross_pass_high')} | "
+                f"{r.get('shot_body_part')} | xG={r.get('xg')}"
+            )
+        return "\n".join(out)
+    except Exception as e:
+        return f"❌ Erro: {str(e)}"
+
 
 @one_player_agent.tool_plain()
 async def get_top_performances(metric: str = "goals", limit: int = 10) -> str:
@@ -186,6 +259,7 @@ last_chart_image = None
 # Funções de response (já sem MCP)
 async def agent_conventional_response(user_query: str) -> str:
     res = await one_player_agent.run(user_prompt=user_query)
+    #print(res.output)
     return res.output
 
 async def stream_agent_response_safe(user_query: str) -> str:
@@ -193,6 +267,7 @@ async def stream_agent_response_safe(user_query: str) -> str:
         async with one_player_agent.iter(user_query) as agent_run:
             async for node in agent_run:
                 if isinstance(node, End) and agent_run.result:
+                    print(str(agent_run.result.output))
                     return str(agent_run.result.output)
     except Exception as e:
         import traceback
@@ -205,4 +280,5 @@ async def shutdown():
     db.close()
 
 if __name__ == "__main__":
-    asyncio.run(one_player_agent.run("Teste: top performances goals limit 5"))
+    _ = asyncio.run(agent_conventional_response("quantos sao os gols baseados em cruzamentos?"))
+    print(_)

prompts/player_matchid_prompt.py

@@ -14,6 +14,20 @@ Respond back in the user's language.
 - If it is suitable for visualizations, graphs, or charts, (or if the user asks for it) you can use the create_chart tool 
 
 ## Database Structure:
+### Table: goals_stats
+One row per goal scored by Barcelona in a match.
+
+Columns (as provided):
+- goal_event_id (TEXT) UNIQUE-ish identifier
+- match_id (BIGINT), season_id (BIGINT), team (TEXT)
+- player_scorer (TEXT), player_scorer_nick (TEXT)
+- pass_from (TEXT), pass_from_nick (TEXT)
+- is_cross_pass (BOOL), is_cross_pass_high (BOOL)
+- minute (BIGINT), second (BIGINT), period (BIGINT)
+- play_pattern (TEXT), shot_type (TEXT), shot_body_part (TEXT)
+- xg (DOUBLE), possession (BIGINT)
+- match_date (TEXT), opponent (TEXT), home_away (TEXT), home_team (TEXT), away_team (TEXT)
+
 ### Table: player_match_stats
 Contains one row per player per match with 40 metrics:
 **Identification (8 columns):**
@@ -188,6 +202,12 @@ WHERE match_date = '2020-10-24'
 ORDER BY (goals + assists) DESC
 ```
 
+## Join guidelines:
+- player_match_stats <-> goals_stats:
+  - Join by match_id AND (player_match_stats.player_nickname = goals_stats.player_scorer_nick OR = goals_stats.pass_from_nick) when needed.
+- match_stats <-> goals_stats:
+  - Join by match_id (and optionally team='Barcelona').
+
 ## Key Metrics Explained:
 - **xG (Expected Goals)**: Statistical model predicting goal probability per shot
 - **npxG (Non-Penalty xG)**: Expected Goals excluding penalties
@@ -218,7 +238,7 @@ ORDER BY (goals + assists) DESC
 - get_consistency_stats(player_name)
 - get_home_away_comparison(player_name)
 - show_available_columns()
-**Remember:** All analyses must be based on SQL queries against the 'player_match_stats' table. This table provides MATCH-LEVEL granularity, allowing you to track individual performances game by game.
+**Remember:** All analyses must be based on SQL queries against the tables.
 Players of the season: Lionel Messi, Antoine Griezmann, Ousmane Dembélé, Ansu Fati, Martin Braithwaite
 Sergio Busquets, Frenkie de Jong, Pedri, Riqui Puig, Miralem Pjanić, Philippe Coutinho
 Gerard Piqué, Jordi Alba, Clément Lenglet, Sergi Roberto, Sergiño Dest, Ronald Araújo, Óscar Mingueza, Samuel Umtiti, Junior Firpo