run.py

# =========== Copyright 2023 @ CAMEL-AI.org. All Rights Reserved. ===========
# Licensed under the Apache License, Version 2.0 (the “License”);
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an “AS IS” BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# =========== Copyright 2023 @ CAMEL-AI.org. All Rights Reserved. ===========
import argparse
import json
import logging
import os
import sys
import webbrowser


from chatdev.chat_chain import ChatChain
from chatdev.utils import log_arguments, get_config, check_bool

from camel.typing import ModelType # <--- AGGIUNTA IMPORT
from camel.configs import ChatGPTConfig # <--- AGGIUNTA IMPORT

# === Imposta variabili d'ambiente per ChatDev/ChatChain in base a llm_config.json ===
try:
    with open("llm_config.json", "r") as f:
        llm_config = json.load(f)
    llm_url = llm_config.get("url")
    llm_api_key = llm_config.get("api_key", "")
    llm_model = llm_config.get("model", "")
    if llm_url:
        os.environ["OPENAI_API_BASE"] = llm_url
    if llm_api_key is not None:
        os.environ["OPENAI_API_KEY"] = llm_api_key
    if llm_model:
        os.environ["OPENAI_MODEL"] = llm_model
except Exception as e:
    print(f"[WARN] Impossibile caricare la configurazione LLM: {e}")

root = os.path.dirname(__file__)
sys.path.append(root)
try:
    from openai.types.chat.chat_completion_message_tool_call import ChatCompletionMessageToolCall
    from openai.types.chat.chat_completion_message import FunctionCall

    openai_new_api = True  # new openai api version
except ImportError:
    openai_new_api = False  # old openai api version
    print(
        "Warning: Your OpenAI version is outdated. \n "
        "Please update as specified in requirement.txt. \n "
        "The old API interface is deprecated and will no longer be supported.")


def main():
    # === Carica la configurazione LLM scelta dall'utente ===
    try:
        with open("llm_config.json", "r") as f:
            llm_config = json.load(f)
        LLM_TYPE = llm_config.get("type", "local")
        LLM_MODEL = llm_config.get("model", "GPT_3_5_TURBO")
        LLM_URL = llm_config.get("url")
        LLM_API_KEY = llm_config.get("api_key")
    except Exception:
        LLM_TYPE = "local"
        LLM_MODEL = "GPT_3_5_TURBO"
        LLM_URL = None
        LLM_API_KEY = None

    parser = argparse.ArgumentParser(description='argparse')
    parser.add_argument('--config', type=str, default="Default",
                        help="Name of config, which is used to load configuration under CompanyConfig/")
    parser.add_argument('--org', type=str, default="DefaultOrganization",
                        help="Name of organization, your software will be generated in WareHouse/name_org_timestamp")
    parser.add_argument('--task', type=str, default="Develop a basic Gomoku game.",
                        help="Prompt of software")
    parser.add_argument('--name', type=str, default="Gomoku",
                        help="Name of software, your software will be generated in WareHouse/name_org_timestamp")
    parser.add_argument('--model', type=str, default=LLM_MODEL,
                        help="GPT Model, choose from {'GPT_3_5_TURBO', 'GPT_4', 'GPT_4_TURBO', 'GPT_4O', 'GPT_4O_MINI'}")
    parser.add_argument('--path', type=str, default="",
                        help="Your file directory, ChatDev will build upon your software in the Incremental mode")
    parser.add_argument('--max_tokens_output_agents', type=int, default=20000,
                        help="Maximum number of output tokens for agents in ChatChain.")

    args = parser.parse_args()

    # Se ChatDev/ChatChain supporta endpoint e api_key, passarli come variabili d'ambiente
    if LLM_URL:
        os.environ["CHATDEV_API_URL"] = LLM_URL
    if LLM_API_KEY:
        os.environ["CHATDEV_API_KEY"] = LLM_API_KEY

    # Start ChatDev

    # ----------------------------------------
    #          Init Model Config
    # ----------------------------------------
    # Configurazione del modello per ChatDev.
    # LM Studio gestisce la temperatura e repetition_penalty a livello di server.
    # Qui impostiamo max_tokens che ChatDev usa per limitare l'output degli agenti.

    # Il valore di max_tokens_output_agents è già nel parser, usiamolo.
    # Se non è definito, usa un default ragionevole.
    max_tokens_for_chain = getattr(args, 'max_tokens_output_agents', 100000) # <--- NUOVA LOGICA
    if max_tokens_for_chain is None: # Aggiunto controllo per None
        max_tokens_for_chain = 100000


    # Creiamo una ChatGPTConfig che ChatChain userà per i suoi agenti.
    # La temperatura qui potrebbe essere un placeholder se LM Studio la sovrascrive sempre.
    # È comunque buona pratica averla definita.
    chat_model_config = ChatGPTConfig( # <--- NUOVA LOGICA
        temperature=0.3, # Bassa temperatura per risposte più deterministiche
        max_tokens=max_tokens_for_chain
    )

    # ----------------------------------------
    #          Init ChatChain
    # ----------------------------------------
    config_path, config_phase_path, config_role_path = get_config(args.config)
    args2type = {'GPT_3_5_TURBO': ModelType.GPT_3_5_TURBO,
                 'GPT_4': ModelType.GPT_4,
                 'GPT_4_TURBO': ModelType.GPT_4_TURBO,
                 'GPT_4O': ModelType.GPT_4O,
                 'GPT_4O_MINI': ModelType.GPT_4O_MINI,
                 }
    # La gestione di openai_new_api per args2type['GPT_3_5_TURBO'] sembra corretta.
    if openai_new_api and 'GPT_3_5_TURBO' in args2type: # Aggiunto controllo esistenza chiave
        args2type['GPT_3_5_TURBO'] = ModelType.GPT_3_5_TURBO_NEW


    chat_chain = ChatChain(config_path=config_path,
                           config_phase_path=config_phase_path,
                           config_role_path=config_role_path,
                           task_prompt=args.task,
                           project_name=args.name,
                           org_name=args.org,
                           model_type=args2type.get(args.model, ModelType.GPT_3_5_TURBO), # Aggiunto .get con fallback
                           code_path=args.path,
                           model_config_override=chat_model_config # <--- MODIFICA: Passa la config creata
                           )

    # ----------------------------------------
    #          Init Log
    # ----------------------------------------
    logging.basicConfig(filename=chat_chain.log_filepath, level=logging.INFO,
                        format='[%(asctime)s %(levelname)s] %(message)s',
                        datefmt='%Y-%d-%m %H:%M:%S', encoding="utf-8")

    # ----------------------------------------
    #          Pre Processing
    # ----------------------------------------
    print("Starting pre processing...")
    chat_chain.pre_processing()

    # ----------------------------------------
    #          Personnel Recruitment
    # ----------------------------------------
    print("Starting recruitment...")

    chat_chain.make_recruitment()

    # ----------------------------------------
    #          Chat Chain
    # ----------------------------------------
    print("Starting execute chain...")

    chat_chain.execute_chain()

    # ----------------------------------------
    #          Post Processing
    # ----------------------------------------

    chat_chain.post_processing()

    # --- Print project path for the interactive editor ---
    # This line is specifically for the script that calls this one.
    project_path = chat_chain.chat_env.env_dict.get("directory", "")
    print(f"PROJECT_PATH_FOR_EDITOR:{project_path}")

if __name__ == "__main__":
    main()