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| import gradio as gr | |
| import game | |
| from app import format_game_result | |
| def respond( | |
| message, | |
| history: list[dict[str, str]], | |
| system_message, | |
| max_tokens, | |
| temperature, | |
| top_p, | |
| game_mode_selection, | |
| hf_token: gr.OAuthToken | None = None, | |
| ): | |
| """ | |
| For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference | |
| """ | |
| # If this is the start of a new conversation (empty history), generate a new country/state | |
| if not history: | |
| game.guess_number = 0 | |
| if game_mode_selection == game.MODE_STATES: | |
| game.current_system = game.get_system_message(game.MODE_STATES) | |
| print(f"🔍 DEBUG - New session started, selected state: {game.selected_country}") | |
| else: | |
| game.current_system = game.get_system_message(game.MODE_COUNTRIES) | |
| print(f"🔍 DEBUG - New session started, selected country: {game.selected_country}") | |
| game.guess_number += 1 | |
| messages = [{"role": "system", "content": game.current_system + str(game.guess_number)}] | |
| messages.append({"role": "user", "content": message}) | |
| # Debug: Calculate approximate input token count | |
| total_input_chars = sum(len(str(msg.get("content", ""))) for msg in messages) | |
| estimated_input_tokens = total_input_chars // 4 # Rough approximation: 4 chars per token | |
| print(f"🔍 DEBUG - Estimated input tokens: {estimated_input_tokens}") | |
| print(f"🔍 DEBUG - Messages count: {len(messages)}") | |
| print(f"🔍 DEBUG - Max tokens setting: {max_tokens}") | |
| # Debug: Show each message type and length | |
| for i, msg in enumerate(messages): | |
| role = msg.get("role", "unknown") | |
| content = str(msg.get("content", "")) | |
| print(f"🔍 DEBUG - Message {i+1} ({role}): {len(content)} chars") | |
| if role == "system": | |
| print(f"🔍 DEBUG - System message preview: ...{content[-100:]}") | |
| elif role == "user": | |
| print(f"🔍 DEBUG - User message: {content}") | |
| elif role == "assistant": | |
| print(f"🔍 DEBUG - Assistant message: {content[:50]}...") | |
| response = "" | |
| output_token_count = 0 | |
| try: | |
| for message_chunk in ai.client.chat_completion( | |
| messages, | |
| stream=True, | |
| response_format={"type": "text"}, | |
| ): | |
| choices = message_chunk.choices | |
| token = "" | |
| if len(choices) and choices[0].delta.content: | |
| token = choices[0].delta.content | |
| output_token_count += 1 | |
| response += token | |
| # Debug: Show output token statistics | |
| estimated_output_tokens = len(response) // 4 # Rough approximation | |
| print(f"🔍 DEBUG - Output token chunks received: {output_token_count}") | |
| print(f"🔍 DEBUG - Estimated output tokens (by chars): {estimated_output_tokens}") | |
| print(f"🔍 DEBUG - Response length: {len(response)} characters") | |
| print(f"🔍 DEBUG - Raw response: {response}") | |
| # Clean the response to remove unwanted artifacts | |
| response = ai.clean_response(response) | |
| print(f"🔍 DEBUG - Cleaned response: {response}") | |
| # Check if this is a game end response and format it nicely | |
| if "The country was" in response or "The state was" in response: | |
| print(f"🔍 DEBUG - Game end detected! Location extracted: {game.selected_country}") | |
| return format_game_result(response) | |
| elif game.guess_number == 20: | |
| print(f"🔍 DEBUG - Maximum guesses reached: {game.guess_number}") | |
| return format_game_result(response) | |
| else: | |
| print("🔍 DEBUG - Regular response (no game end)") | |
| return response | |
| except Exception as e: | |
| return f"Error during inference: {str(e)}" |