Is there a way to set detailed requirements for the software to be created?

[vanetreg]

Detailed requirements:

• what programming language, libraries and versions to be used ( eg. Langchain and Python)
• what features do we need, in details
• etc.

[giorgosn]

If you try a more detailed prompt?

[vanetreg]

You mean there's no better way to set detailed requirements but here: python3 run.py --task "[description_of_your_idea]" --name "[project_name]" the "[description_of_your_idea]" ?

[GitSimply]

Use this run2.py save it to your directory now you can use a txt file as a prompt just make sure the text file is in the same directory as run2.py run2.py. the text file and run.py should all be in the same directory so you can run it I've used very detailed Product Requirement Documents that I made on GPT4 as prompts with good results

python run2.py --task Your_Idea.txt --name "Your_Idea"

# =========== 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 logging
import os
import sys

from camel.typing import ModelType

root = os.path.dirname(__file__)
sys.path.append(root)

from chatdev.chat_chain import ChatChain

def get_config(company):
    """
    return configuration json files for ChatChain
    user can customize only parts of configuration json files, other files will be left for default
    Args:
        company: customized configuration name under CompanyConfig/

    Returns:
        path to three configuration jsons: [config_path, config_phase_path, config_role_path]
    """
    config_dir = os.path.join(root, "CompanyConfig", company)
    default_config_dir = os.path.join(root, "CompanyConfig", "Default")

    config_files = [
        "ChatChainConfig.json",
        "PhaseConfig.json",
        "RoleConfig.json"
    ]

    config_paths = []

    for config_file in config_files:
        company_config_path = os.path.join(config_dir, config_file)
        default_config_path = os.path.join(default_config_dir, config_file)

        if os.path.exists(company_config_path):
            config_paths.append(company_config_path)
        else:
            config_paths.append(default_config_path)

    return tuple(config_paths)

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="GPT_3_5_TURBO",
                    help="GPT Model, choose from {'GPT_3_5_TURBO','GPT_4','GPT_4_32K'}")
args = parser.parse_args()
# Read the content of the task file
with open(args.task, 'r') as f:
    task_content = f.read()
args.task = task_content

# Start ChatDev

# ----------------------------------------
#          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_32K': ModelType.GPT_4_32k}
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[args.model])

# ----------------------------------------
#          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
# ----------------------------------------

chat_chain.pre_processing()

# ----------------------------------------
#          Personnel Recruitment
# ----------------------------------------

chat_chain.make_recruitment()

# ----------------------------------------
#          Chat Chain
# ----------------------------------------

chat_chain.execute_chain()

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

chat_chain.post_processing()

[vanetreg]

@GitSimply OK, thanks a lot! :)

[qianc62]

Thank you for your attention & solution, and hope you can enjoy ChatDev! 😀