Fixes and improvements.
This commit is contained in:
+74
-58
@@ -1,6 +1,6 @@
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import logging
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from functools import cache
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from typing import Any, Dict, List, Optional, Union
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from typing import Any, Dict, List, Optional
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import requests
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@@ -99,33 +99,43 @@ class IGDBQuery(object):
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"""
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if not query or not query.strip():
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return None
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try:
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# Search for games with fuzzy matching
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games = self.generalized_igdb_query(
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{"name": query.strip()},
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"games",
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[
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"id", "name", "summary", "storyline", "rating", "aggregated_rating",
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"first_release_date", "genres.name", "platforms.name", "developers.name",
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"publishers.name", "game_modes.name", "themes.name", "cover.url"
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"id",
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"name",
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"summary",
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"storyline",
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"rating",
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"aggregated_rating",
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"first_release_date",
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"genres.name",
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"platforms.name",
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"involved_companies.company.name",
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"game_modes.name",
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"themes.name",
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"cover.url",
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],
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additional_filters={"category": "= 0"}, # Main games only
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limit=limit
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limit=limit,
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)
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if not games:
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return None
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# Format games for AI consumption
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formatted_games = []
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for game in games:
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formatted_game = self._format_game_for_ai(game)
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if formatted_game:
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formatted_games.append(formatted_game)
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return formatted_games if formatted_games else None
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except Exception as e:
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logging.error(f"Error searching games for query '{query}': {e}")
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return None
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@@ -139,22 +149,37 @@ class IGDBQuery(object):
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{},
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"games",
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[
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"id", "name", "summary", "storyline", "rating", "aggregated_rating",
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"first_release_date", "genres.name", "platforms.name", "developers.name",
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"publishers.name", "game_modes.name", "themes.name", "keywords.name",
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"similar_games.name", "cover.url", "screenshots.url", "videos.video_id",
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"release_dates.date", "release_dates.platform.name", "age_ratings.rating"
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"id",
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"name",
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"summary",
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"storyline",
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"rating",
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"aggregated_rating",
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"first_release_date",
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"genres.name",
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"platforms.name",
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"involved_companies.company.name",
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"game_modes.name",
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"themes.name",
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"keywords.name",
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"similar_games.name",
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"cover.url",
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"screenshots.url",
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"videos.video_id",
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"release_dates.date",
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"release_dates.platform.name",
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"age_ratings.rating",
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],
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additional_filters={"id": f"= {game_id}"},
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limit=1
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limit=1,
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)
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if games and len(games) > 0:
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return self._format_game_for_ai(games[0], detailed=True)
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except Exception as e:
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logging.error(f"Error getting game details for ID {game_id}: {e}")
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return None
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def _format_game_for_ai(self, game_data: Dict[str, Any], detailed: bool = False) -> Dict[str, Any]:
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@@ -162,60 +187,56 @@ class IGDBQuery(object):
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Format game data in a way that's easy for AI to understand and present to users.
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"""
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try:
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formatted = {
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"name": game_data.get("name", "Unknown"),
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"summary": game_data.get("summary", "No summary available")
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}
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formatted = {"name": game_data.get("name", "Unknown"), "summary": game_data.get("summary", "No summary available")}
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# Add basic info
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if "rating" in game_data:
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formatted["rating"] = f"{game_data['rating']:.1f}/100"
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if "aggregated_rating" in game_data:
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formatted["user_rating"] = f"{game_data['aggregated_rating']:.1f}/100"
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# Release information
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if "first_release_date" in game_data:
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import datetime
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release_date = datetime.datetime.fromtimestamp(game_data["first_release_date"])
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formatted["release_year"] = release_date.year
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if detailed:
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formatted["release_date"] = release_date.strftime("%Y-%m-%d")
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# Platforms
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if "platforms" in game_data and game_data["platforms"]:
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platforms = [p.get("name", "") for p in game_data["platforms"] if p.get("name")]
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formatted["platforms"] = platforms[:5] # Limit to prevent overflow
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# Genres
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# Genres
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if "genres" in game_data and game_data["genres"]:
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genres = [g.get("name", "") for g in game_data["genres"] if g.get("name")]
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formatted["genres"] = genres
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# Developers
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if "developers" in game_data and game_data["developers"]:
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developers = [d.get("name", "") for d in game_data["developers"] if d.get("name")]
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formatted["developers"] = developers[:3] # Limit for readability
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# Publishers
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if "publishers" in game_data and game_data["publishers"]:
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publishers = [p.get("name", "") for p in game_data["publishers"] if p.get("name")]
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formatted["publishers"] = publishers[:2]
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# Companies (developers/publishers)
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if "involved_companies" in game_data and game_data["involved_companies"]:
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companies = []
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for company_data in game_data["involved_companies"]:
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if "company" in company_data and "name" in company_data["company"]:
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companies.append(company_data["company"]["name"])
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formatted["companies"] = companies[:5] # Limit for readability
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if detailed:
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# Add more detailed info for specific requests
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if "storyline" in game_data and game_data["storyline"]:
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formatted["storyline"] = game_data["storyline"]
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if "game_modes" in game_data and game_data["game_modes"]:
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modes = [m.get("name", "") for m in game_data["game_modes"] if m.get("name")]
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formatted["game_modes"] = modes
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if "themes" in game_data and game_data["themes"]:
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themes = [t.get("name", "") for t in game_data["themes"] if t.get("name")]
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formatted["themes"] = themes
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return formatted
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except Exception as e:
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logging.error(f"Error formatting game data: {e}")
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return {"name": game_data.get("name", "Unknown"), "summary": "Error retrieving game information"}
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@@ -234,30 +255,25 @@ class IGDBQuery(object):
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"properties": {
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"query": {
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"type": "string",
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"description": "The game name or search query (e.g., 'Elden Ring', 'Mario', 'Zelda Breath of the Wild')"
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"description": "The game name or search query (e.g., 'Elden Ring', 'Mario', 'Zelda Breath of the Wild')",
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},
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"limit": {
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"type": "integer",
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"type": "integer",
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"description": "Maximum number of games to return (default: 5, max: 10)",
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"minimum": 1,
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"maximum": 10
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}
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"maximum": 10,
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},
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},
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"required": ["query"]
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}
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"required": ["query"],
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},
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},
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{
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"name": "get_game_details",
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"description": "Get detailed information about a specific game when you have its ID from a previous search.",
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"parameters": {
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"type": "object",
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"properties": {
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"game_id": {
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"type": "integer",
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"description": "The IGDB game ID from a previous search result"
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}
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},
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"required": ["game_id"]
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}
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}
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"properties": {"game_id": {"type": "integer", "description": "The IGDB game ID from a previous search result"}},
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"required": ["game_id"],
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},
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},
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]
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@@ -68,7 +68,5 @@ class LeonardoAIDrawMixIn(AIResponderBase):
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return image_bytes
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except Exception as err:
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logging.warning(f"Failed to generate image, sleep for {error_sleep}s: {repr(description)}\n{repr(err)}")
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else:
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logging.warning(f"Failed to generate image, sleep for {error_sleep}s: {repr(description)}")
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await asyncio.sleep(error_sleep)
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raise RuntimeError(f"Failed to generate image {repr(description)}")
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@@ -29,21 +29,25 @@ class OpenAIResponder(AIResponder, LeonardoAIDrawMixIn):
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def __init__(self, config: Dict[str, Any], channel: Optional[str] = None) -> None:
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super().__init__(config, channel)
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self.client = openai.AsyncOpenAI(api_key=self.config.get("openai-token", self.config.get("openai-key", "")))
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# Initialize IGDB if enabled
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self.igdb = None
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if (self.config.get("enable-game-info", False) and
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self.config.get("igdb-client-id") and
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self.config.get("igdb-access-token")):
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logging.info("IGDB Configuration Check:")
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logging.info(f" enable-game-info: {self.config.get('enable-game-info', 'NOT SET')}")
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logging.info(f" igdb-client-id: {'SET' if self.config.get('igdb-client-id') else 'NOT SET'}")
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logging.info(f" igdb-access-token: {'SET' if self.config.get('igdb-access-token') else 'NOT SET'}")
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if self.config.get("enable-game-info", False) and self.config.get("igdb-client-id") and self.config.get("igdb-access-token"):
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try:
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self.igdb = IGDBQuery(
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self.config["igdb-client-id"],
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self.config["igdb-access-token"]
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)
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logging.info("IGDB integration enabled for game information")
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self.igdb = IGDBQuery(self.config["igdb-client-id"], self.config["igdb-access-token"])
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logging.info("✅ IGDB integration SUCCESSFULLY enabled for game information")
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logging.info(f" Client ID: {self.config['igdb-client-id'][:8]}...")
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logging.info(f" Available functions: {len(self.igdb.get_openai_functions())}")
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except Exception as e:
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logging.warning(f"Failed to initialize IGDB: {e}")
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logging.error(f"❌ Failed to initialize IGDB: {e}")
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self.igdb = None
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else:
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logging.warning("❌ IGDB integration DISABLED - missing configuration or disabled in config")
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async def draw_openai(self, description: str) -> BytesIO:
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for _ in range(3):
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@@ -56,69 +60,146 @@ class OpenAIResponder(AIResponder, LeonardoAIDrawMixIn):
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raise RuntimeError(f"Failed to generate image {repr(description)} after multiple retries")
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async def chat(self, messages: List[Dict[str, Any]], limit: int) -> Tuple[Optional[Dict[str, Any]], int]:
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if isinstance(messages[-1]["content"], str):
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model = self.config["model"]
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elif "model-vision" in self.config:
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model = self.config["model-vision"]
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else:
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messages[-1]["content"] = messages[-1]["content"][0]["text"]
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# Safety check for mock objects in tests
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if not isinstance(messages, list) or len(messages) == 0:
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logging.warning("Invalid messages format in chat method")
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return None, limit
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try:
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# Clean up any orphaned tool messages from previous conversations
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clean_messages = []
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for i, msg in enumerate(messages):
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if msg.get("role") == "tool":
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# Skip tool messages that don't have a corresponding assistant message with tool_calls
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if i == 0 or messages[i - 1].get("role") != "assistant" or not messages[i - 1].get("tool_calls"):
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logging.debug(f"Removing orphaned tool message at position {i}")
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continue
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clean_messages.append(msg)
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messages = clean_messages
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last_message_content = messages[-1]["content"]
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if isinstance(last_message_content, str):
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model = self.config["model"]
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elif "model-vision" in self.config:
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model = self.config["model-vision"]
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else:
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messages[-1]["content"] = messages[-1]["content"][0]["text"]
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except (KeyError, IndexError, TypeError) as e:
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logging.warning(f"Error accessing message content: {e}")
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return None, limit
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try:
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# Prepare function calls if IGDB is enabled
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chat_kwargs = {
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"model": model,
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"messages": messages,
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}
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if self.igdb and self.config.get("enable-game-info", False):
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chat_kwargs["tools"] = [
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{"type": "function", "function": func}
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for func in self.igdb.get_openai_functions()
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]
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chat_kwargs["tool_choice"] = "auto"
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try:
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igdb_functions = self.igdb.get_openai_functions()
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if igdb_functions and isinstance(igdb_functions, list):
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chat_kwargs["tools"] = [{"type": "function", "function": func} for func in igdb_functions]
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chat_kwargs["tool_choice"] = "auto"
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logging.info(f"🎮 IGDB functions available to AI: {[f['name'] for f in igdb_functions]}")
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logging.debug(f" Full chat_kwargs with tools: {list(chat_kwargs.keys())}")
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except (TypeError, AttributeError) as e:
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logging.warning(f"Error setting up IGDB functions: {e}")
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else:
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logging.debug(
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"🎮 IGDB not available for this request (igdb={}, enabled={})".format(
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self.igdb is not None, self.config.get("enable-game-info", False)
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)
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)
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result = await openai_chat(self.client, **chat_kwargs)
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# Handle function calls if present
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message = result.choices[0].message
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# Log what we received from OpenAI
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logging.debug(f"📨 OpenAI Response: content={bool(message.content)}, has_tool_calls={hasattr(message, 'tool_calls')}")
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if hasattr(message, "tool_calls") and message.tool_calls:
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tool_names = [tc.function.name for tc in message.tool_calls]
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logging.info(f"🔧 OpenAI requested function calls: {tool_names}")
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# Check if we have function/tool calls and IGDB is enabled
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has_tool_calls = (hasattr(message, 'tool_calls') and message.tool_calls and
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self.igdb and self.config.get("enable-game-info", False))
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has_tool_calls = (
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hasattr(message, "tool_calls") and message.tool_calls and self.igdb and self.config.get("enable-game-info", False)
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)
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# Clean up any existing tool messages in the history to avoid conflicts
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if has_tool_calls:
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messages = [msg for msg in messages if msg.get("role") != "tool"]
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if has_tool_calls:
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logging.info(f"🎮 Processing {len(message.tool_calls)} IGDB function call(s)...")
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try:
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# Process function calls
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messages.append({
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"role": "assistant",
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"content": message.content or "",
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"tool_calls": [tc.dict() if hasattr(tc, 'dict') else tc for tc in message.tool_calls]
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})
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# Process function calls - serialize tool_calls properly
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tool_calls_data = []
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for tc in message.tool_calls:
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tool_calls_data.append(
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{"id": tc.id, "type": "function", "function": {"name": tc.function.name, "arguments": tc.function.arguments}}
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)
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messages.append({"role": "assistant", "content": message.content or "", "tool_calls": tool_calls_data})
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# Execute function calls
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for tool_call in message.tool_calls:
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function_name = tool_call.function.name
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function_args = json.loads(tool_call.function.arguments)
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logging.info(f"🎮 Executing IGDB function: {function_name} with args: {function_args}")
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# Execute IGDB function
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function_result = await self._execute_igdb_function(function_name, function_args)
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messages.append({
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"role": "tool",
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"tool_call_id": tool_call.id,
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"content": json.dumps(function_result) if function_result else "No results found"
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})
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# Get final response after function execution
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final_result = await openai_chat(self.client, **chat_kwargs)
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logging.info(f"🎮 IGDB function result: {type(function_result)} - {str(function_result)[:200]}...")
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messages.append(
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{
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"role": "tool",
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"tool_call_id": tool_call.id,
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"content": json.dumps(function_result) if function_result else "No results found",
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}
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)
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# Get final response after function execution - remove tools for final call
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final_chat_kwargs = {
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"model": model,
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"messages": messages,
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}
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logging.debug(f"🔧 Sending final request to OpenAI with {len(messages)} messages (no tools)")
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logging.debug(f"🔧 Last few messages: {messages[-3:] if len(messages) > 3 else messages}")
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final_result = await openai_chat(self.client, **final_chat_kwargs)
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answer_obj = final_result.choices[0].message
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logging.debug(
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f"🔧 Final OpenAI response: content_length={len(answer_obj.content) if answer_obj.content else 0}, has_tool_calls={hasattr(answer_obj, 'tool_calls') and answer_obj.tool_calls}"
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)
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if answer_obj.content:
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logging.debug(f"🔧 Response preview: {answer_obj.content[:200]}")
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else:
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logging.warning(f"🔧 OpenAI returned NULL content despite {final_result.usage.completion_tokens} completion tokens")
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# If OpenAI returns null content after function calling, use empty string
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if not answer_obj.content and function_result:
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logging.warning("OpenAI returned null after function calling, using empty string")
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answer_obj.content = ""
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except Exception as e:
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# If function calling fails, fall back to regular response
|
||||
logging.warning(f"Function calling failed, using regular response: {e}")
|
||||
answer_obj = message
|
||||
else:
|
||||
answer_obj = message
|
||||
|
||||
answer = {"content": answer_obj.content, "role": answer_obj.role}
|
||||
|
||||
# Handle null content from OpenAI
|
||||
content = answer_obj.content
|
||||
if content is None:
|
||||
logging.warning("OpenAI returned null content, using empty string")
|
||||
content = ""
|
||||
|
||||
answer = {"content": content, "role": answer_obj.role}
|
||||
self.rate_limit_backoff = exponential_backoff()
|
||||
logging.info(f"generated response {result.usage}: {repr(answer)}")
|
||||
return answer, limit
|
||||
@@ -135,12 +216,20 @@ class OpenAIResponder(AIResponder, LeonardoAIDrawMixIn):
|
||||
logging.warning(f"got an rate limit error, sleep for {rate_limit_sleep} seconds: {str(err)}")
|
||||
await asyncio.sleep(rate_limit_sleep)
|
||||
except Exception as err:
|
||||
import traceback
|
||||
|
||||
logging.warning(f"failed to generate response: {repr(err)}")
|
||||
logging.debug(f"Full traceback: {traceback.format_exc()}")
|
||||
return None, limit
|
||||
|
||||
async def fix(self, answer: str) -> str:
|
||||
if "fix-model" not in self.config:
|
||||
return answer
|
||||
|
||||
# Handle null/empty answer
|
||||
if not answer:
|
||||
logging.warning("Fix called with null/empty answer")
|
||||
return '{"answer": "I apologize, I encountered an error processing your request.", "answer_needed": true, "channel": null, "staff": null, "picture": null, "picture_edit": false, "hack": false}'
|
||||
messages = [{"role": "system", "content": self.config["fix-description"]}, {"role": "user", "content": answer}]
|
||||
try:
|
||||
result = await openai_chat(self.client, model=self.config["fix-model"], messages=messages)
|
||||
@@ -206,37 +295,50 @@ class OpenAIResponder(AIResponder, LeonardoAIDrawMixIn):
|
||||
"""
|
||||
Execute IGDB function calls from OpenAI.
|
||||
"""
|
||||
logging.info(f"🎮 _execute_igdb_function called: {function_name}")
|
||||
|
||||
if not self.igdb:
|
||||
return None
|
||||
|
||||
logging.error("🎮 IGDB function called but self.igdb is None!")
|
||||
return {"error": "IGDB not available"}
|
||||
|
||||
try:
|
||||
if function_name == "search_games":
|
||||
query = function_args.get("query", "")
|
||||
limit = function_args.get("limit", 5)
|
||||
|
||||
|
||||
logging.info(f"🎮 Searching IGDB for: '{query}' (limit: {limit})")
|
||||
|
||||
if not query:
|
||||
logging.warning("🎮 No search query provided to search_games")
|
||||
return {"error": "No search query provided"}
|
||||
|
||||
|
||||
results = self.igdb.search_games(query, limit)
|
||||
if results:
|
||||
logging.info(f"🎮 IGDB search returned: {len(results) if results and isinstance(results, list) else 0} results")
|
||||
|
||||
if results and isinstance(results, list) and len(results) > 0:
|
||||
return {"games": results}
|
||||
else:
|
||||
return {"games": [], "message": f"No games found matching '{query}'"}
|
||||
|
||||
|
||||
elif function_name == "get_game_details":
|
||||
game_id = function_args.get("game_id")
|
||||
|
||||
|
||||
logging.info(f"🎮 Getting IGDB details for game ID: {game_id}")
|
||||
|
||||
if not game_id:
|
||||
logging.warning("🎮 No game ID provided to get_game_details")
|
||||
return {"error": "No game ID provided"}
|
||||
|
||||
|
||||
result = self.igdb.get_game_details(game_id)
|
||||
logging.info(f"🎮 IGDB game details returned: {bool(result)}")
|
||||
|
||||
if result:
|
||||
return {"game": result}
|
||||
else:
|
||||
return {"error": f"Game with ID {game_id} not found"}
|
||||
else:
|
||||
return {"error": f"Unknown function: {function_name}"}
|
||||
|
||||
|
||||
except Exception as e:
|
||||
logging.error(f"Error executing IGDB function {function_name}: {e}")
|
||||
return {"error": f"Failed to execute {function_name}: {str(e)}"}
|
||||
|
||||
Reference in New Issue
Block a user