diff --git a/README.md b/README.md index d26b1ac..8e563a7 100644 --- a/README.md +++ b/README.md @@ -224,7 +224,7 @@ OWL requires various API keys to interact with different services. The `owl/.env 2. **Configure Your API Keys**: Open the `.env` file in your preferred text editor and insert your API keys in the corresponding fields. - > **Note**: For the minimal example (`run_mini.py`), you only need to configure the LLM API key (e.g., `OPENAI_API_KEY`). + > **Note**: For the minimal example (`examples/run_mini.py`), you only need to configure the LLM API key (e.g., `OPENAI_API_KEY`). ### Option 2: Setting Environment Variables Directly @@ -275,7 +275,7 @@ cd .. && source .venv/bin/activate && cd owl playwright install-deps #run example demo script -xvfb-python run.py +xvfb-python examples/run.py # Option 2: Build and run using the provided scripts cd .container @@ -299,17 +299,17 @@ npx -y @smithery/cli install @wonderwhy-er/desktop-commander --client claude npx @wonderwhy-er/desktop-commander setup # Run the MCP example -python owl/run_mcp.py +python examples/run_mcp.py ``` -This example showcases how OWL agents can seamlessly interact with file systems, web automation, and information retrieval through the MCP protocol. Check out `owl/run_mcp.py` for the full implementation. +This example showcases how OWL agents can seamlessly interact with file systems, web automation, and information retrieval through the MCP protocol. Check out `examples/run_mcp.py` for the full implementation. ## Basic Usage After installation and setting up your environment variables, you can start using OWL right away: ```bash -python owl/run.py +python examples/run.py ``` ## Running with Different Models @@ -330,28 +330,28 @@ OWL supports various LLM backends, though capabilities may vary depending on the ```bash # Run with Qwen model -python owl/examples/run_qwen_zh.py +python examples/run_qwen_zh.py # Run with Deepseek model -python owl/examples/run_deepseek_zh.py +python examples/run_deepseek_zh.py # Run with other OpenAI-compatible models -python owl/examples/run_openai_compatiable_model.py +python examples/run_openai_compatiable_model.py # Run with Azure OpenAI -python owl/run_azure_openai.py +python examples/run_azure_openai.py # Run with Ollama -python owl/examples/run_ollama.py +python examples/run_ollama.py ``` For a simpler version that only requires an LLM API key, you can try our minimal example: ```bash -python owl/examples/run_mini.py +python examples/run_mini.py ``` -You can run OWL agent with your own task by modifying the `run.py` script: +You can run OWL agent with your own task by modifying the `examples/run.py` script: ```python # Define your own task @@ -393,7 +393,7 @@ Here are some tasks you can try with OWL: OWL's MCP integration provides a standardized way for AI models to interact with various tools and data sources: -Try our comprehensive MCP example in `owl/run_mcp.py` to see these capabilities in action! +Try our comprehensive MCP example in `examples/run_mcp.py` to see these capabilities in action! ## Available Toolkits @@ -464,10 +464,10 @@ OWL includes an intuitive web-based user interface that makes it easier to inter ```bash # Start the Chinese version -python owl/webapp_zh.py +python examples/webapp_zh.py # Start the English version -python owl/webapp.py +python examples/webapp.py ``` ## Features @@ -545,7 +545,7 @@ Join us ([*Discord*](https://discord.camel-ai.org/) or [*WeChat*](https://ghli.o Join us for further discussions! -![](./assets/community_8.jpg) +![](./assets/community.jpg) # ❓ FAQ diff --git a/README_zh.md b/README_zh.md index da0622f..b15c114 100644 --- a/README_zh.md +++ b/README_zh.md @@ -219,7 +219,7 @@ OWL 需要各种 API 密钥来与不同的服务进行交互。`owl/.env_templat 2. **配置你的 API 密钥**： 在你喜欢的文本编辑器中打开 `.env` 文件，并在相应字段中插入你的 API 密钥。 - > **注意**：对于最小示例（`run_mini.py`），你只需要配置 LLM API 密钥（例如，`OPENAI_API_KEY`）。 + > **注意**：对于最小示例（`examples/run_mini.py`），你只需要配置 LLM API 密钥（例如，`OPENAI_API_KEY`）。 ### 选项 2：直接设置环境变量 @@ -269,7 +269,7 @@ cd .. && source .venv/bin/activate && cd owl playwright install-deps #运行例子演示脚本 -xvfb-python run.py +xvfb-python examples/run.py # 选项2：使用提供的脚本构建和运行 cd .container @@ -293,23 +293,23 @@ npx -y @smithery/cli install @wonderwhy-er/desktop-commander --client claude npx @wonderwhy-er/desktop-commander setup # 运行 MCP 示例 -python owl/run_mcp.py +python examples/run_mcp.py ``` -这个示例展示了 OWL 智能体如何通过 MCP 协议无缝地与文件系统、网页自动化和信息检索进行交互。查看 `owl/run_mcp.py` 了解完整实现。 +这个示例展示了 OWL 智能体如何通过 MCP 协议无缝地与文件系统、网页自动化和信息检索进行交互。查看 `examples/run_mcp.py` 了解完整实现。 ## 基本用法 运行以下示例： ```bash -python owl/run.py +python examples/run.py ``` 我们还提供了一个最小化示例，只需配置LLM的API密钥即可运行： ```bash -python owl/run_mini.py +python examples/run_mini.py ``` ## 使用不同的模型 @@ -330,22 +330,22 @@ OWL 支持多种 LLM 后端，但功能可能因模型的工具调用和多模 ```bash # 使用 Qwen 模型运行 -python owl/examples/run_qwen_zh.py +python examples/run_qwen_zh.py # 使用 Deepseek 模型运行 -python owl/examples/run_deepseek_zh.py +python examples/run_deepseek_zh.py # 使用其他 OpenAI 兼容模型运行 -python owl/examples/run_openai_compatiable_model.py +python examples/run_openai_compatiable_model.py # 使用 Azure OpenAI模型运行 -python owl/run_azure_openai.py +python examples/run_azure_openai.py # 使用 Ollama 运行 -python owl/examples/run_ollama.py +python examples/run_ollama.py ``` -你可以通过修改 `run.py` 脚本来运行自己的任务： +你可以通过修改 `examples/run.py` 脚本来运行自己的任务： ```python # Define your own task @@ -383,7 +383,7 @@ OWL 将自动调用与文档相关的工具来处理文件并提取答案。 OWL 的 MCP 集成为 AI 模型与各种工具和数据源的交互提供了标准化的方式。 -查看我们的综合示例 `owl/run_mcp.py` 来体验这些功能！ +查看我们的综合示例 `examples/run_mcp.py` 来体验这些功能！ ## 可用工具包 @@ -479,7 +479,7 @@ git checkout gaia58.18 2. 运行评估脚本： ```bash -python run_gaia_roleplaying.py +python examples/run_gaia_roleplaying.py ``` # ⏱️ 未来计划 @@ -531,7 +531,7 @@ python run_gaia_roleplaying.py 加入我们，参与更多讨论！ -![](./assets/community_8.jpg) +![](./assets/community.jpg) # ❓ 常见问题 diff --git a/owl/examples/run.py b/examples/run.py similarity index 100% rename from owl/examples/run.py rename to examples/run.py diff --git a/owl/run_azure_openai.py b/examples/run_azure_openai.py similarity index 100% rename from owl/run_azure_openai.py rename to examples/run_azure_openai.py diff --git a/owl/examples/run_deepseek_zh.py b/examples/run_deepseek_zh.py similarity index 100% rename from owl/examples/run_deepseek_zh.py rename to examples/run_deepseek_zh.py diff --git a/owl/examples/run_gaia_roleplaying.py b/examples/run_gaia_roleplaying.py similarity index 100% rename from owl/examples/run_gaia_roleplaying.py rename to examples/run_gaia_roleplaying.py diff --git a/owl/run_mcp.py b/examples/run_mcp.py similarity index 100% rename from owl/run_mcp.py rename to examples/run_mcp.py diff --git a/owl/examples/run_mini.py b/examples/run_mini.py similarity index 100% rename from owl/examples/run_mini.py rename to examples/run_mini.py diff --git a/owl/examples/run_ollama.py b/examples/run_ollama.py similarity index 100% rename from owl/examples/run_ollama.py rename to examples/run_ollama.py diff --git a/owl/examples/run_openai_compatiable_model.py b/examples/run_openai_compatiable_model.py similarity index 100% rename from owl/examples/run_openai_compatiable_model.py rename to examples/run_openai_compatiable_model.py diff --git a/owl/examples/run_qwen_mini_zh.py b/examples/run_qwen_mini_zh.py similarity index 100% rename from owl/examples/run_qwen_mini_zh.py rename to examples/run_qwen_mini_zh.py diff --git a/owl/examples/run_qwen_zh.py b/examples/run_qwen_zh.py similarity index 100% rename from owl/examples/run_qwen_zh.py rename to examples/run_qwen_zh.py diff --git a/owl/examples/run_terminal.py b/examples/run_terminal.py similarity index 100% rename from owl/examples/run_terminal.py rename to examples/run_terminal.py diff --git a/owl/examples/run_terminal_zh.py b/examples/run_terminal_zh.py similarity index 99% rename from owl/examples/run_terminal_zh.py rename to examples/run_terminal_zh.py index 2174bd1..f0a290d 100644 --- a/owl/examples/run_terminal_zh.py +++ b/examples/run_terminal_zh.py @@ -25,7 +25,6 @@ from camel.logger import set_log_level from owl.utils import run_society from camel.societies import RolePlaying -import os load_dotenv() set_log_level(level="DEBUG") diff --git a/owl/.env_template b/owl/.env_template index 9e4328f..c30f21e 100644 --- a/owl/.env_template +++ b/owl/.env_template @@ -4,7 +4,7 @@ #=========================================== # OPENAI API (https://platform.openai.com/api-keys) -# OPENAI_API_KEY= "" +OPENAI_API_KEY='Your_Key' # OPENAI_API_BASE_URL="" # Azure OpenAI API @@ -15,22 +15,22 @@ # Qwen API (https://help.aliyun.com/zh/model-studio/developer-reference/get-api-key) -# QWEN_API_KEY="" +QWEN_API_KEY='Your_Key' # DeepSeek API (https://platform.deepseek.com/api_keys) -# DEEPSEEK_API_KEY="" +DEEPSEEK_API_KEY='Your_Key' #=========================================== # Tools & Services API #=========================================== -# Google Search API (https://developers.google.com/custom-search/v1/overview) -# GOOGLE_API_KEY="" -# SEARCH_ENGINE_ID="" +# Google Search API (https://coda.io/@jon-dallas/google-image-search-pack-example/search-engine-id-and-google-api-key-3) +GOOGLE_API_KEY='Your_Key' +SEARCH_ENGINE_ID='Your_ID' # Chunkr API (https://chunkr.ai/) -# CHUNKR_API_KEY="" +CHUNKR_API_KEY='Your_Key' # Firecrawl API (https://www.firecrawl.dev/) -#FIRECRAWL_API_KEY="" +FIRECRAWL_API_KEY='Your_Key' #FIRECRAWL_API_URL="https://api.firecrawl.dev" \ No newline at end of file diff --git a/owl/utils/enhanced_role_playing.py b/owl/utils/enhanced_role_playing.py index d50b337..76bf757 100644 --- a/owl/utils/enhanced_role_playing.py +++ b/owl/utils/enhanced_role_playing.py @@ -461,6 +461,10 @@ def run_society( assistant_response.info["usage"]["completion_tokens"] + user_response.info["usage"]["completion_tokens"] ) + overall_prompt_token_count += ( + assistant_response.info["usage"]["prompt_tokens"] + + user_response.info["usage"]["prompt_tokens"] + ) # convert tool call to dict tool_call_records: List[dict] = [] diff --git a/owl/webapp.py b/owl/webapp.py new file mode 100644 index 0000000..52b26c6 --- /dev/null +++ b/owl/webapp.py @@ -0,0 +1,1316 @@ +# ========= Copyright 2023-2024 @ 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 2023-2024 @ CAMEL-AI.org. All Rights Reserved. ========= +# Import from the correct module path +from owl.utils import run_society +import os +import gradio as gr +import time +import json +import logging +import datetime +from typing import Tuple +import importlib +from dotenv import load_dotenv, set_key, find_dotenv, unset_key +import threading +import queue +import re # For regular expression operations + +os.environ["PYTHONIOENCODING"] = "utf-8" + + +# Configure logging system +def setup_logging(): + """Configure logging system to output logs to file, memory queue, and console""" + # Create logs directory (if it doesn't exist) + logs_dir = os.path.join(os.path.dirname(__file__), "logs") + os.makedirs(logs_dir, exist_ok=True) + + # Generate log filename (using current date) + current_date = datetime.datetime.now().strftime("%Y-%m-%d") + log_file = os.path.join(logs_dir, f"gradio_log_{current_date}.txt") + + # Configure root logger (captures all logs) + root_logger = logging.getLogger() + + # Clear existing handlers to avoid duplicate logs + for handler in root_logger.handlers[:]: + root_logger.removeHandler(handler) + + root_logger.setLevel(logging.INFO) + + # Create file handler + file_handler = logging.FileHandler(log_file, encoding="utf-8", mode="a") + file_handler.setLevel(logging.INFO) + + # Create console handler + console_handler = logging.StreamHandler() + console_handler.setLevel(logging.INFO) + + # Create formatter + formatter = logging.Formatter( + "%(asctime)s - %(name)s - %(levelname)s - %(message)s" + ) + file_handler.setFormatter(formatter) + console_handler.setFormatter(formatter) + + # Add handlers to root logger + root_logger.addHandler(file_handler) + root_logger.addHandler(console_handler) + + logging.info("Logging system initialized, log file: %s", log_file) + return log_file + + +# Global variables +LOG_FILE = None +LOG_QUEUE: queue.Queue = queue.Queue() # Log queue +STOP_LOG_THREAD = threading.Event() +CURRENT_PROCESS = None # Used to track the currently running process +STOP_REQUESTED = threading.Event() # Used to mark if stop was requested + + +# Log reading and updating functions +def log_reader_thread(log_file): + """Background thread that continuously reads the log file and adds new lines to the queue""" + try: + with open(log_file, "r", encoding="utf-8") as f: + # Move to the end of file + f.seek(0, 2) + + while not STOP_LOG_THREAD.is_set(): + line = f.readline() + if line: + LOG_QUEUE.put(line) # Add to conversation record queue + else: + # No new lines, wait for a short time + time.sleep(0.1) + except Exception as e: + logging.error(f"Log reader thread error: {str(e)}") + + +def get_latest_logs(max_lines=100, queue_source=None): + """Get the latest log lines from the queue, or read directly from the file if the queue is empty + + Args: + max_lines: Maximum number of lines to return + queue_source: Specify which queue to use, default is LOG_QUEUE + + Returns: + str: Log content + """ + logs = [] + log_queue = queue_source if queue_source else LOG_QUEUE + + # Create a temporary queue to store logs so we can process them without removing them from the original queue + temp_queue = queue.Queue() + temp_logs = [] + + try: + # Try to get all available log lines from the queue + while not log_queue.empty() and len(temp_logs) < max_lines: + log = log_queue.get_nowait() + temp_logs.append(log) + temp_queue.put(log) # Put the log back into the temporary queue + except queue.Empty: + pass + + # Process conversation records + logs = temp_logs + + # If there are no new logs or not enough logs, try to read the last few lines directly from the file + if len(logs) < max_lines and LOG_FILE and os.path.exists(LOG_FILE): + try: + with open(LOG_FILE, "r", encoding="utf-8") as f: + all_lines = f.readlines() + # If there are already some logs in the queue, only read the remaining needed lines + remaining_lines = max_lines - len(logs) + file_logs = ( + all_lines[-remaining_lines:] + if len(all_lines) > remaining_lines + else all_lines + ) + + # Add file logs before queue logs + logs = file_logs + logs + except Exception as e: + error_msg = f"Error reading log file: {str(e)}" + logging.error(error_msg) + if not logs: # Only add error message if there are no logs + logs = [error_msg] + + # If there are still no logs, return a prompt message + if not logs: + return "Initialization in progress..." + + # Filter logs, only keep logs with 'camel.agents.chat_agent - INFO' + filtered_logs = [] + for log in logs: + if "camel.agents.chat_agent - INFO" in log: + filtered_logs.append(log) + + # If there are no logs after filtering, return a prompt message + if not filtered_logs: + return "No conversation records yet." + + # Process log content, extract the latest user and assistant messages + simplified_logs = [] + + # Use a set to track messages that have already been processed, to avoid duplicates + processed_messages = set() + + def process_message(role, content): + # 创建一个唯一标识符来跟踪消息 + msg_id = f"{role}:{content}" + if msg_id in processed_messages: + return None + + processed_messages.add(msg_id) + content = content.replace("\\n", "\n") + lines = [line.strip() for line in content.split("\n")] + content = "\n".join(lines) + + return f"[{role.title()} Agent]: {content}" + + for log in filtered_logs: + formatted_messages = [] + # 尝试提取消息数组 + messages_match = re.search( + r"Model (.*?), index (\d+), processed these messages: (\[.*\])", log + ) + + if messages_match: + try: + messages = json.loads(messages_match.group(3)) + for msg in messages: + if msg.get("role") in ["user", "assistant"]: + formatted_msg = process_message( + msg.get("role"), msg.get("content", "") + ) + if formatted_msg: + formatted_messages.append(formatted_msg) + except json.JSONDecodeError: + pass + + # If JSON parsing fails or no message array is found, try to extract conversation content directly + if not formatted_messages: + user_pattern = re.compile(r"\{'role': 'user', 'content': '(.*?)'\}") + assistant_pattern = re.compile( + r"\{'role': 'assistant', 'content': '(.*?)'\}" + ) + + for content in user_pattern.findall(log): + formatted_msg = process_message("user", content) + if formatted_msg: + formatted_messages.append(formatted_msg) + + for content in assistant_pattern.findall(log): + formatted_msg = process_message("assistant", content) + if formatted_msg: + formatted_messages.append(formatted_msg) + + if formatted_messages: + simplified_logs.append("\n\n".join(formatted_messages)) + + # Format log output, ensure appropriate separation between each conversation record + formatted_logs = [] + for i, log in enumerate(simplified_logs): + # Remove excess whitespace characters from beginning and end + log = log.strip() + + formatted_logs.append(log) + + # Ensure each conversation record ends with a newline + if not log.endswith("\n"): + formatted_logs.append("\n") + + return "".join(formatted_logs) + + +# Dictionary containing module descriptions +MODULE_DESCRIPTIONS = { + "run": "Default mode: Using OpenAI model's default agent collaboration mode, suitable for most tasks.", + "run_mini": "Using OpenAI model with minimal configuration to process tasks", + "run_deepseek_zh": "Using deepseek model to process Chinese tasks", + "run_openai_compatiable_model": "Using openai compatible model to process tasks", + "run_ollama": "Using local ollama model to process tasks", + "run_qwen_mini_zh": "Using qwen model with minimal configuration to process tasks", + "run_qwen_zh": "Using qwen model to process tasks", +} + + +# Default environment variable template +DEFAULT_ENV_TEMPLATE = """#=========================================== +# MODEL & API +# (See https://docs.camel-ai.org/key_modules/models.html#) +#=========================================== + +# OPENAI API (https://platform.openai.com/api-keys) +OPENAI_API_KEY='Your_Key' +# OPENAI_API_BASE_URL="" + +# Azure OpenAI API +# AZURE_OPENAI_BASE_URL="" +# AZURE_API_VERSION="" +# AZURE_OPENAI_API_KEY="" +# AZURE_DEPLOYMENT_NAME="" + + +# Qwen API (https://help.aliyun.com/zh/model-studio/developer-reference/get-api-key) +QWEN_API_KEY='Your_Key' + +# DeepSeek API (https://platform.deepseek.com/api_keys) +DEEPSEEK_API_KEY='Your_Key' + +#=========================================== +# Tools & Services API +#=========================================== + +# Google Search API (https://coda.io/@jon-dallas/google-image-search-pack-example/search-engine-id-and-google-api-key-3) +GOOGLE_API_KEY='Your_Key' +SEARCH_ENGINE_ID='Your_ID' + +# Chunkr API (https://chunkr.ai/) +CHUNKR_API_KEY='Your_Key' + +# Firecrawl API (https://www.firecrawl.dev/) +FIRECRAWL_API_KEY='Your_Key' +#FIRECRAWL_API_URL="https://api.firecrawl.dev" +""" + + +def validate_input(question: str) -> bool: + """Validate if user input is valid + + Args: + question: User question + + Returns: + bool: Whether the input is valid + """ + # Check if input is empty or contains only spaces + if not question or question.strip() == "": + return False + return True + + +def run_owl(question: str, example_module: str) -> Tuple[str, str, str]: + """Run the OWL system and return results + + Args: + question: User question + example_module: Example module name to import (e.g., "run_terminal_zh" or "run_deep") + + Returns: + Tuple[...]: Answer, token count, status + """ + global CURRENT_PROCESS + + # Validate input + if not validate_input(question): + logging.warning("User submitted invalid input") + return ( + "Please enter a valid question", + "0", + "❌ Error: Invalid input question", + ) + + try: + # Ensure environment variables are loaded + load_dotenv(find_dotenv(), override=True) + logging.info( + f"Processing question: '{question}', using module: {example_module}" + ) + + # Check if the module is in MODULE_DESCRIPTIONS + if example_module not in MODULE_DESCRIPTIONS: + logging.error(f"User selected an unsupported module: {example_module}") + return ( + f"Selected module '{example_module}' is not supported", + "0", + "❌ Error: Unsupported module", + ) + + # Dynamically import target module + module_path = f"examples.{example_module}" + try: + logging.info(f"Importing module: {module_path}") + module = importlib.import_module(module_path) + except ImportError as ie: + logging.error(f"Unable to import module {module_path}: {str(ie)}") + return ( + f"Unable to import module: {module_path}", + "0", + f"❌ Error: Module {example_module} does not exist or cannot be loaded - {str(ie)}", + ) + except Exception as e: + logging.error( + f"Error occurred while importing module {module_path}: {str(e)}" + ) + return ( + f"Error occurred while importing module: {module_path}", + "0", + f"❌ Error: {str(e)}", + ) + + # Check if it contains the construct_society function + if not hasattr(module, "construct_society"): + logging.error( + f"construct_society function not found in module {module_path}" + ) + return ( + f"construct_society function not found in module {module_path}", + "0", + "❌ Error: Module interface incompatible", + ) + + # Build society simulation + try: + logging.info("Building society simulation...") + society = module.construct_society(question) + + except Exception as e: + logging.error(f"Error occurred while building society simulation: {str(e)}") + return ( + f"Error occurred while building society simulation: {str(e)}", + "0", + f"❌ Error: Build failed - {str(e)}", + ) + + # Run society simulation + try: + logging.info("Running society simulation...") + answer, chat_history, token_info = run_society(society) + logging.info("Society simulation completed") + except Exception as e: + logging.error(f"Error occurred while running society simulation: {str(e)}") + return ( + f"Error occurred while running society simulation: {str(e)}", + "0", + f"❌ Error: Run failed - {str(e)}", + ) + + # Safely get token count + if not isinstance(token_info, dict): + token_info = {} + + completion_tokens = token_info.get("completion_token_count", 0) + prompt_tokens = token_info.get("prompt_token_count", 0) + total_tokens = completion_tokens + prompt_tokens + + logging.info( + f"Processing completed, token usage: completion={completion_tokens}, prompt={prompt_tokens}, total={total_tokens}" + ) + + return ( + answer, + f"Completion tokens: {completion_tokens:,} | Prompt tokens: {prompt_tokens:,} | Total: {total_tokens:,}", + "✅ Successfully completed", + ) + + except Exception as e: + logging.error( + f"Uncaught error occurred while processing the question: {str(e)}" + ) + return (f"Error occurred: {str(e)}", "0", f"❌ Error: {str(e)}") + + +def update_module_description(module_name: str) -> str: + """Return the description of the selected module""" + return MODULE_DESCRIPTIONS.get(module_name, "No description available") + + +# Store environment variables configured from the frontend +WEB_FRONTEND_ENV_VARS: dict[str, str] = {} + + +def init_env_file(): + """Initialize .env file if it doesn't exist""" + dotenv_path = find_dotenv() + if not dotenv_path: + with open(".env", "w") as f: + f.write(DEFAULT_ENV_TEMPLATE) + dotenv_path = find_dotenv() + return dotenv_path + + +def load_env_vars(): + """Load environment variables and return as dictionary format + + Returns: + dict: Environment variable dictionary, each value is a tuple containing value and source (value, source) + """ + dotenv_path = init_env_file() + load_dotenv(dotenv_path, override=True) + + # Read environment variables from .env file + env_file_vars = {} + with open(dotenv_path, "r") as f: + for line in f: + line = line.strip() + if line and not line.startswith("#"): + if "=" in line: + key, value = line.split("=", 1) + env_file_vars[key.strip()] = value.strip().strip("\"'") + + # Get from system environment variables + system_env_vars = { + k: v + for k, v in os.environ.items() + if k not in env_file_vars and k not in WEB_FRONTEND_ENV_VARS + } + + # Merge environment variables and mark sources + env_vars = {} + + # Add system environment variables (lowest priority) + for key, value in system_env_vars.items(): + env_vars[key] = (value, "System") + + # Add .env file environment variables (medium priority) + for key, value in env_file_vars.items(): + env_vars[key] = (value, ".env file") + + # Add frontend configured environment variables (highest priority) + for key, value in WEB_FRONTEND_ENV_VARS.items(): + env_vars[key] = (value, "Frontend configuration") + # Ensure operating system environment variables are also updated + os.environ[key] = value + + return env_vars + + +def save_env_vars(env_vars): + """Save environment variables to .env file + + Args: + env_vars: Dictionary, keys are environment variable names, values can be strings or (value, source) tuples + """ + try: + dotenv_path = init_env_file() + + # Save each environment variable + for key, value_data in env_vars.items(): + if key and key.strip(): # Ensure key is not empty + # Handle case where value might be a tuple + if isinstance(value_data, tuple): + value = value_data[0] + else: + value = value_data + + set_key(dotenv_path, key.strip(), value.strip()) + + # Reload environment variables to ensure they take effect + load_dotenv(dotenv_path, override=True) + + return True, "Environment variables have been successfully saved!" + except Exception as e: + return False, f"Error saving environment variables: {str(e)}" + + +def add_env_var(key, value, from_frontend=True): + """Add or update a single environment variable + + Args: + key: Environment variable name + value: Environment variable value + from_frontend: Whether it's from frontend configuration, default is True + """ + try: + if not key or not key.strip(): + return False, "Variable name cannot be empty" + + key = key.strip() + value = value.strip() + + # If from frontend, add to frontend environment variable dictionary + if from_frontend: + WEB_FRONTEND_ENV_VARS[key] = value + # Directly update system environment variables + os.environ[key] = value + + # Also update .env file + dotenv_path = init_env_file() + set_key(dotenv_path, key, value) + load_dotenv(dotenv_path, override=True) + + return True, f"Environment variable {key} has been successfully added/updated!" + except Exception as e: + return False, f"Error adding environment variable: {str(e)}" + + +def delete_env_var(key): + """Delete environment variable""" + try: + if not key or not key.strip(): + return False, "Variable name cannot be empty" + + key = key.strip() + + # Delete from .env file + dotenv_path = init_env_file() + unset_key(dotenv_path, key) + + # Delete from frontend environment variable dictionary + if key in WEB_FRONTEND_ENV_VARS: + del WEB_FRONTEND_ENV_VARS[key] + + # Also delete from current process environment + if key in os.environ: + del os.environ[key] + + return True, f"Environment variable {key} has been successfully deleted!" + except Exception as e: + return False, f"Error deleting environment variable: {str(e)}" + + +def is_api_related(key: str) -> bool: + """Determine if an environment variable is API-related + + Args: + key: Environment variable name + + Returns: + bool: Whether it's API-related + """ + # API-related keywords + api_keywords = [ + "api", + "key", + "token", + "secret", + "password", + "openai", + "qwen", + "deepseek", + "google", + "search", + "hf", + "hugging", + "chunkr", + "firecrawl", + ] + + # Check if it contains API-related keywords (case insensitive) + return any(keyword in key.lower() for keyword in api_keywords) + + +def get_api_guide(key: str) -> str: + """Return the corresponding API guide based on the environment variable name + + Args: + key: Environment variable name + + Returns: + str: API guide link or description + """ + key_lower = key.lower() + if "openai" in key_lower: + return "https://platform.openai.com/api-keys" + elif "qwen" in key_lower or "dashscope" in key_lower: + return "https://help.aliyun.com/zh/model-studio/developer-reference/get-api-key" + elif "deepseek" in key_lower: + return "https://platform.deepseek.com/api_keys" + elif "google" in key_lower: + return "https://coda.io/@jon-dallas/google-image-search-pack-example/search-engine-id-and-google-api-key-3" + elif "search_engine_id" in key_lower: + return "https://coda.io/@jon-dallas/google-image-search-pack-example/search-engine-id-and-google-api-key-3" + elif "chunkr" in key_lower: + return "https://chunkr.ai/" + elif "firecrawl" in key_lower: + return "https://www.firecrawl.dev/" + else: + return "" + + +def update_env_table(): + """Update environment variable table display, only showing API-related environment variables""" + env_vars = load_env_vars() + # Filter out API-related environment variables + api_env_vars = {k: v for k, v in env_vars.items() if is_api_related(k)} + # Convert to list format to meet Gradio Dataframe requirements + # Format: [Variable name, Variable value, Guide link] + result = [] + for k, v in api_env_vars.items(): + guide = get_api_guide(k) + # If there's a guide link, create a clickable link + guide_link = ( + f"🔗 Get" + if guide + else "" + ) + result.append([k, v[0], guide_link]) + return result + + +def save_env_table_changes(data): + """Save changes to the environment variable table + + Args: + data: Dataframe data, possibly a pandas DataFrame object + + Returns: + str: Operation status information, containing HTML-formatted status message + """ + try: + logging.info( + f"Starting to process environment variable table data, type: {type(data)}" + ) + + # Get all current environment variables + current_env_vars = load_env_vars() + processed_keys = set() # Record processed keys to detect deleted variables + + # 处理pandas DataFrame对象 + import pandas as pd + + if isinstance(data, pd.DataFrame): + # Get column name information + columns = data.columns.tolist() + logging.info(f"DataFrame column names: {columns}") + + # Iterate through each row of the DataFrame + for index, row in data.iterrows(): + # 使用列名访问数据 + if len(columns) >= 3: + # Get variable name and value (column 0 is name, column 1 is value) + key = row[0] if isinstance(row, pd.Series) else row.iloc[0] + value = row[1] if isinstance(row, pd.Series) else row.iloc[1] + + # Check if it's an empty row or deleted variable + if ( + key and str(key).strip() + ): # If key name is not empty, add or update + logging.info( + f"Processing environment variable: {key} = {value}" + ) + add_env_var(key, str(value)) + processed_keys.add(key) + # 处理其他格式 + elif isinstance(data, dict): + logging.info(f"Dictionary format data keys: {list(data.keys())}") + # 如果是字典格式，尝试不同的键 + if "data" in data: + rows = data["data"] + elif "values" in data: + rows = data["values"] + elif "value" in data: + rows = data["value"] + else: + # 尝试直接使用字典作为行数据 + rows = [] + for key, value in data.items(): + if key not in ["headers", "types", "columns"]: + rows.append([key, value]) + + if isinstance(rows, list): + for row in rows: + if isinstance(row, list) and len(row) >= 2: + key, value = row[0], row[1] + if key and str(key).strip(): + add_env_var(key, str(value)) + processed_keys.add(key) + elif isinstance(data, list): + # 列表格式 + for row in data: + if isinstance(row, list) and len(row) >= 2: + key, value = row[0], row[1] + if key and str(key).strip(): + add_env_var(key, str(value)) + processed_keys.add(key) + else: + logging.error(f"Unknown data format: {type(data)}") + return f"❌ Save failed: Unknown data format {type(data)}" + + # Process deleted variables - check if there are variables in current environment not appearing in the table + api_related_keys = {k for k in current_env_vars.keys() if is_api_related(k)} + keys_to_delete = api_related_keys - processed_keys + + # Delete variables no longer in the table + for key in keys_to_delete: + logging.info(f"Deleting environment variable: {key}") + delete_env_var(key) + + return "✅ Environment variables have been successfully saved" + except Exception as e: + import traceback + + error_details = traceback.format_exc() + logging.error(f"Error saving environment variables: {str(e)}\n{error_details}") + return f"❌ Save failed: {str(e)}" + + +def get_env_var_value(key): + """Get the actual value of an environment variable + + Priority: Frontend configuration > .env file > System environment variables + """ + # Check frontend configured environment variables + if key in WEB_FRONTEND_ENV_VARS: + return WEB_FRONTEND_ENV_VARS[key] + + # Check system environment variables (including those loaded from .env) + return os.environ.get(key, "") + + +def create_ui(): + """Create enhanced Gradio interface""" + + # Define conversation record update function + def update_logs2(): + """Get the latest conversation records and return them to the frontend for display""" + return get_latest_logs(100, LOG_QUEUE) + + def clear_log_file(): + """Clear log file content""" + try: + if LOG_FILE and os.path.exists(LOG_FILE): + # Clear log file content instead of deleting the file + open(LOG_FILE, "w").close() + logging.info("Log file has been cleared") + # Clear log queue + while not LOG_QUEUE.empty(): + try: + LOG_QUEUE.get_nowait() + except queue.Empty: + break + return "" + else: + return "" + except Exception as e: + logging.error(f"Error clearing log file: {str(e)}") + return "" + + # Create a real-time log update function + def process_with_live_logs(question, module_name): + """Process questions and update logs in real-time""" + global CURRENT_PROCESS + + # Clear log file + clear_log_file() + + # Create a background thread to process the question + result_queue = queue.Queue() + + def process_in_background(): + try: + result = run_owl(question, module_name) + result_queue.put(result) + except Exception as e: + result_queue.put( + (f"Error occurred: {str(e)}", "0", f"❌ Error: {str(e)}") + ) + + # Start background processing thread + bg_thread = threading.Thread(target=process_in_background) + CURRENT_PROCESS = bg_thread # Record current process + bg_thread.start() + + # While waiting for processing to complete, update logs once per second + while bg_thread.is_alive(): + # Update conversation record display + logs2 = get_latest_logs(100, LOG_QUEUE) + + # Always update status + yield ( + "0", + " Processing...", + logs2, + ) + + time.sleep(1) + + # Processing complete, get results + if not result_queue.empty(): + result = result_queue.get() + answer, token_count, status = result + + # Final update of conversation record + logs2 = get_latest_logs(100, LOG_QUEUE) + + # Set different indicators based on status + if "Error" in status: + status_with_indicator = ( + f" {status}" + ) + else: + status_with_indicator = ( + f" {status}" + ) + + yield token_count, status_with_indicator, logs2 + else: + logs2 = get_latest_logs(100, LOG_QUEUE) + yield ( + "0", + " Terminated", + logs2, + ) + + with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue")) as app: + gr.Markdown( + """ + # 🦉 OWL Multi-Agent Collaboration System + + Advanced multi-agent collaboration system developed based on the CAMEL framework, designed to solve complex problems through agent collaboration. + Models and tools can be customized by modifying local scripts. + This web app is currently in beta development. It is provided for demonstration and testing purposes only and is not yet recommended for production use. + """ + ) + + # Add custom CSS + gr.HTML(""" + + """) + + with gr.Row(): + with gr.Column(scale=1): + question_input = gr.Textbox( + lines=5, + placeholder="Please enter your question...", + label="Question", + elem_id="question_input", + show_copy_button=True, + value="Open Baidu search, summarize the github stars, fork counts, etc. of camel-ai's camel framework, and write the numbers into a python file using the plot package, save it locally, and run the generated python file.", + ) + + # Enhanced module selection dropdown + # Only includes modules defined in MODULE_DESCRIPTIONS + module_dropdown = gr.Dropdown( + choices=list(MODULE_DESCRIPTIONS.keys()), + value="run_qwen_zh", + label="Select Function Module", + interactive=True, + ) + + # Module description text box + module_description = gr.Textbox( + value=MODULE_DESCRIPTIONS["run_qwen_zh"], + label="Module Description", + interactive=False, + elem_classes="module-info", + ) + + with gr.Row(): + run_button = gr.Button( + "Run", variant="primary", elem_classes="primary" + ) + + status_output = gr.HTML( + value=" Ready", + label="Status", + ) + token_count_output = gr.Textbox( + label="Token Count", interactive=False, elem_classes="token-count" + ) + + with gr.Tabs(): # Set conversation record as the default selected tab + with gr.TabItem("Conversation Record"): + # Add conversation record display area + log_display2 = gr.Textbox( + label="Conversation Record", + lines=25, + max_lines=100, + interactive=False, + autoscroll=True, + show_copy_button=True, + elem_classes="log-display", + container=True, + value="", + ) + + with gr.Row(): + refresh_logs_button2 = gr.Button("Refresh Record") + auto_refresh_checkbox2 = gr.Checkbox( + label="Auto Refresh", value=True, interactive=True + ) + clear_logs_button2 = gr.Button( + "Clear Record", variant="secondary" + ) + + with gr.TabItem("Environment Variable Management", id="env-settings"): + with gr.Box(elem_classes="env-manager-container"): + gr.Markdown(""" + ## Environment Variable Management + + Set model API keys and other service credentials here. This information will be saved in a local `.env` file, ensuring your API keys are securely stored and not uploaded to the network. Correctly setting API keys is crucial for the functionality of the OWL system. Environment variables can be flexibly configured according to tool requirements. + """) + + # Main content divided into two-column layout + with gr.Row(): + # Left column: Environment variable management controls + with gr.Column(scale=3): + with gr.Box(elem_classes="env-controls"): + # Environment variable table - set to interactive for direct editing + gr.Markdown(""" +
+ Tip: Please make sure to run cp .env_template .env to create a local .env file, and flexibly configure the required environment variables according to the running module +
+ """) + + # Enhanced environment variable table, supporting adding and deleting rows + env_table = gr.Dataframe( + headers=[ + "Variable Name", + "Value", + "Retrieval Guide", + ], + datatype=[ + "str", + "str", + "html", + ], # Set the last column as HTML type to support links + row_count=10, # Increase row count to allow adding new variables + col_count=(3, "fixed"), + value=update_env_table, + label="API Keys and Environment Variables", + interactive=True, # Set as interactive, allowing direct editing + elem_classes="env-table", + ) + + # Operation instructions + gr.Markdown( + """ +
+ Operation Guide: + +
+ """, + elem_classes="env-instructions", + ) + + # Environment variable operation buttons + with gr.Row(elem_classes="env-buttons"): + save_env_button = gr.Button( + "💾 Save Changes", + variant="primary", + elem_classes="env-button", + ) + refresh_button = gr.Button( + "🔄 Refresh List", elem_classes="env-button" + ) + + # Status display + env_status = gr.HTML( + label="Operation Status", + value="", + elem_classes="env-status", + ) + + # 连接事件处理函数 + save_env_button.click( + fn=save_env_table_changes, + inputs=[env_table], + outputs=[env_status], + ).then(fn=update_env_table, outputs=[env_table]) + + refresh_button.click(fn=update_env_table, outputs=[env_table]) + + # Example questions + examples = [ + "Open Baidu search, summarize the github stars, fork counts, etc. of camel-ai's camel framework, and write the numbers into a python file using the plot package, save it locally, and run the generated python file.", + "Browse Amazon and find a product that is attractive to programmers. Please provide the product name and price", + "Write a hello world python file and save it locally", + ] + + gr.Examples(examples=examples, inputs=question_input) + + gr.HTML(""" + + """) + + # Set up event handling + run_button.click( + fn=process_with_live_logs, + inputs=[question_input, module_dropdown], + outputs=[token_count_output, status_output, log_display2], + ) + + # Module selection updates description + module_dropdown.change( + fn=update_module_description, + inputs=module_dropdown, + outputs=module_description, + ) + + # Conversation record related event handling + refresh_logs_button2.click( + fn=lambda: get_latest_logs(100, LOG_QUEUE), outputs=[log_display2] + ) + + clear_logs_button2.click(fn=clear_log_file, outputs=[log_display2]) + + # Auto refresh control + def toggle_auto_refresh(enabled): + if enabled: + return gr.update(every=3) + else: + return gr.update(every=0) + + auto_refresh_checkbox2.change( + fn=toggle_auto_refresh, + inputs=[auto_refresh_checkbox2], + outputs=[log_display2], + ) + + # No longer automatically refresh logs by default + + return app + + +# Main function +def main(): + try: + # Initialize logging system + global LOG_FILE + LOG_FILE = setup_logging() + logging.info("OWL Web application started") + + # Start log reading thread + log_thread = threading.Thread( + target=log_reader_thread, args=(LOG_FILE,), daemon=True + ) + log_thread.start() + logging.info("Log reading thread started") + + # Initialize .env file (if it doesn't exist) + init_env_file() + app = create_ui() + + # Register cleanup function for when the application closes + def cleanup(): + global STOP_LOG_THREAD, STOP_REQUESTED + STOP_LOG_THREAD.set() + STOP_REQUESTED.set() + logging.info("Application closed, stopping log thread") + + app.queue() + app.launch(share=False, server_name="127.0.0.1", server_port=7860) + except Exception as e: + logging.error(f"Error occurred while starting the application: {str(e)}") + print(f"Error occurred while starting the application: {str(e)}") + import traceback + + traceback.print_exc() + + finally: + # Ensure log thread stops + STOP_LOG_THREAD.set() + STOP_REQUESTED.set() + logging.info("Application closed") + + +if __name__ == "__main__": + main() diff --git a/owl/webapp_zh.py b/owl/webapp_zh.py index 834508d..2f6f4b6 100644 --- a/owl/webapp_zh.py +++ b/owl/webapp_zh.py @@ -151,7 +151,7 @@ def get_latest_logs(max_lines=100, queue_source=None): # 如果仍然没有日志，返回提示信息 if not logs: - return "暂无对话记录。" + return "初始化运行中..." # 过滤日志，只保留 camel.agents.chat_agent - INFO 的日志 filtered_logs = [] @@ -242,87 +242,49 @@ MODULE_DESCRIPTIONS = { "run": "默认模式：使用OpenAI模型的默认的智能体协作模式，适合大多数任务。", "run_mini": "使用使用OpenAI模型最小化配置处理任务", "run_deepseek_zh": "使用deepseek模型处理中文任务", - "run_terminal_zh": "终端模式：可执行命令行操作，支持网络搜索、文件处理等功能。适合需要系统交互的任务，使用OpenAI模型", - "run_gaia_roleplaying": "GAIA基准测试实现，用于评估Agent能力", "run_openai_compatiable_model": "使用openai兼容模型处理任务", "run_ollama": "使用本地ollama模型处理任务", "run_qwen_mini_zh": "使用qwen模型最小化配置处理任务", "run_qwen_zh": "使用qwen模型处理任务", } -# API帮助信息 -API_HELP_INFO = { - "OPENAI_API_KEY": { - "name": "OpenAI API", - "desc": "OpenAI API密钥，用于访问GPT系列模型", - "url": "https://platform.openai.com/api-keys", - }, - "QWEN_API_KEY": { - "name": "通义千问 API", - "desc": "阿里云通义千问API密钥", - "url": "https://help.aliyun.com/zh/model-studio/developer-reference/get-api-key", - }, - "DEEPSEEK_API_KEY": { - "name": "DeepSeek API", - "desc": "DeepSeek API密钥", - "url": "https://platform.deepseek.com/api_keys", - }, - "GOOGLE_API_KEY": { - "name": "Google Search API", - "desc": "Google自定义搜索API密钥", - "url": "https://developers.google.com/custom-search/v1/overview", - }, - "SEARCH_ENGINE_ID": { - "name": "Google Search Engine ID", - "desc": "Google自定义搜索引擎ID", - "url": "https://developers.google.com/custom-search/v1/overview", - }, - "HF_TOKEN": { - "name": "Hugging Face API", - "desc": "Hugging Face API令牌", - "url": "https://huggingface.co/join", - }, - "CHUNKR_API_KEY": { - "name": "Chunkr API", - "desc": "Chunkr API密钥", - "url": "https://chunkr.ai/", - }, - "FIRECRAWL_API_KEY": { - "name": "Firecrawl API", - "desc": "Firecrawl API密钥", - "url": "https://www.firecrawl.dev/", - }, -} # 默认环境变量模板 -DEFAULT_ENV_TEMPLATE = """# MODEL & API (See https://docs.camel-ai.org/key_modules/models.html#) +DEFAULT_ENV_TEMPLATE = """#=========================================== +# MODEL & API +# (See https://docs.camel-ai.org/key_modules/models.html#) +#=========================================== -# OPENAI API -# OPENAI_API_KEY= "" +# OPENAI API (https://platform.openai.com/api-keys) +OPENAI_API_KEY='Your_Key' # OPENAI_API_BASE_URL="" +# Azure OpenAI API +# AZURE_OPENAI_BASE_URL="" +# AZURE_API_VERSION="" +# AZURE_OPENAI_API_KEY="" +# AZURE_DEPLOYMENT_NAME="" + + # Qwen API (https://help.aliyun.com/zh/model-studio/developer-reference/get-api-key) -# QWEN_API_KEY="" +QWEN_API_KEY='Your_Key' # DeepSeek API (https://platform.deepseek.com/api_keys) -# DEEPSEEK_API_KEY="" +DEEPSEEK_API_KEY='Your_Key' #=========================================== # Tools & Services API #=========================================== -# Google Search API (https://developers.google.com/custom-search/v1/overview) -GOOGLE_API_KEY="" -SEARCH_ENGINE_ID="" - -# Hugging Face API (https://huggingface.co/join) -HF_TOKEN="" +# Google Search API (https://coda.io/@jon-dallas/google-image-search-pack-example/search-engine-id-and-google-api-key-3) +GOOGLE_API_KEY='Your_Key' +SEARCH_ENGINE_ID='Your_ID' # Chunkr API (https://chunkr.ai/) -CHUNKR_API_KEY="" +CHUNKR_API_KEY='Your_Key' # Firecrawl API (https://www.firecrawl.dev/) -FIRECRAWL_API_KEY="" +FIRECRAWL_API_KEY='Your_Key' #FIRECRAWL_API_URL="https://api.firecrawl.dev" """ @@ -357,7 +319,7 @@ def run_owl(question: str, example_module: str) -> Tuple[str, str, str]: # 验证输入 if not validate_input(question): logging.warning("用户提交了无效的输入") - return ("请输入有效的问题", "0", "❌ 错误: 输入无效") + return ("请输入有效的问题", "0", "❌ 错误: 输入问题无效") try: # 确保环境变量已加载 @@ -374,7 +336,7 @@ def run_owl(question: str, example_module: str) -> Tuple[str, str, str]: ) # 动态导入目标模块 - module_path = f"owl.examples.{example_module}" + module_path = f"examples.{example_module}" try: logging.info(f"正在导入模块: {module_path}") module = importlib.import_module(module_path) @@ -452,8 +414,6 @@ def update_module_description(module_name: str) -> str: return MODULE_DESCRIPTIONS.get(module_name, "无可用描述") -# 环境变量管理功能 - # 存储前端配置的环境变量 WEB_FRONTEND_ENV_VARS: dict[str, str] = {} @@ -646,7 +606,9 @@ def get_api_guide(key: str) -> str: elif "deepseek" in key_lower: return "https://platform.deepseek.com/api_keys" elif "google" in key_lower: - return "https://developers.google.com/custom-search/v1/overview" + return "https://coda.io/@jon-dallas/google-image-search-pack-example/search-engine-id-and-google-api-key-3" + elif "search_engine_id" in key_lower: + return "https://coda.io/@jon-dallas/google-image-search-pack-example/search-engine-id-and-google-api-key-3" elif "chunkr" in key_lower: return "https://chunkr.ai/" elif "firecrawl" in key_lower: @@ -701,11 +663,11 @@ def save_env_table_changes(data): # 遍历DataFrame的每一行 for index, row in data.iterrows(): - # 使用列名或索引访问数据 + # 使用列名访问数据 if len(columns) >= 3: - # 如果有列名，使用列名访问 - key = row.iloc[1] if hasattr(row, "iloc") else row[1] - value = row.iloc[2] if hasattr(row, "iloc") else row[2] + # 获取变量名和值 (第0列是变量名，第1列是值) + key = row[0] if isinstance(row, pd.Series) else row.iloc[0] + value = row[1] if isinstance(row, pd.Series) else row.iloc[1] # 检查是否为空行或已删除的变量 if key and str(key).strip(): # 如果键名不为空，则添加或更新 @@ -812,6 +774,9 @@ def create_ui(): """处理问题并实时更新日志""" global CURRENT_PROCESS + # 清空日志文件 + clear_log_file() + # 创建一个后台线程来处理问题 result_queue = queue.Queue() @@ -874,6 +839,8 @@ def create_ui(): # 🦉 OWL 多智能体协作系统 基于CAMEL框架开发的先进多智能体协作系统，旨在通过智能体协作解决复杂问题。 + 可以通过修改本地脚本自定义模型和工具。 + 本网页应用目前处于测试阶段，仅供演示和测试使用，尚未推荐用于生产环境。 """ ) @@ -1082,6 +1049,7 @@ def create_ui(): label="问题", elem_id="question_input", show_copy_button=True, + value="打开百度搜索，总结一下camel-ai的camel框架的github star、fork数目等，并把数字用plot包写成python文件保存到本地，并运行生成的python文件。", ) # 增强版模块选择下拉菜单 @@ -1141,7 +1109,7 @@ def create_ui(): gr.Markdown(""" ## 环境变量管理 - 在此处设置模型API密钥和其他服务凭证。这些信息将保存在本地的`.env`文件中，确保您的API密钥安全存储且不会上传到网络。 + 在此处设置模型API密钥和其他服务凭证。这些信息将保存在本地的`.env`文件中，确保您的API密钥安全存储且不会上传到网络。正确设置API密钥对于OWL系统的功能至关重要, 可以按找工具需求灵活配置环境变量。 """) # 主要内容分为两列布局 @@ -1150,12 +1118,9 @@ def create_ui(): with gr.Column(scale=3): with gr.Box(elem_classes="env-controls"): # 环境变量表格 - 设置为可交互以直接编辑 - gr.Markdown("### 环境变量管理") gr.Markdown(""" - 管理您的API密钥和其他环境变量。正确设置API密钥对于OWL系统的功能至关重要。 -
- 提示： 请确保正确设置API密钥以确保系统功能正常 + 提示： 请确保运行cp .env_template .env创建本地.env文件，根据运行模块灵活配置所需环境变量
""") @@ -1186,7 +1151,6 @@ def create_ui():
  • 删除变量: 清空变量名即可删除该行
  • 获取API密钥: 点击"获取指南"列中的链接获取相应API密钥
    • - 注意: 所有API密钥都安全地存储在本地，不会上传到网络 """, elem_classes="env-instructions", @@ -1221,7 +1185,7 @@ def create_ui(): # 示例问题 examples = [ - "打开百度搜索，总结一下camel-ai的camel框架的github star、fork数目等，并把数字用plot包写成python文件保存到本地，用本地终端执行python文件显示图出来给我", + "打开百度搜索，总结一下camel-ai的camel框架的github star、fork数目等，并把数字用plot包写成python文件保存到本地，并运行生成的python文件。", "浏览亚马逊并找出一款对程序员有吸引力的产品。请提供产品名称和价格", "写一个hello world的python文件，保存到本地", ]