githubmirror/gpt-pilot

example-config.json
104 строки3 KB
LeonOstrez
update default config.json setup and example-config.json
25 июл 2024, 15:33
25 июл 2024, 15:33f1dbd34
{
  // Configuration for the LLM providers that can be used. Pythagora supports
  // OpenAI, Azure, Anthropic and Groq. OpenRouter and local LLMs (such as LM-Studio)
  // also work, you can use "openai" provider to define these.
  "llm": {
    "openai": {
      // Base url to the provider/server, omitting the trailing "chat/completions" part.
      "base_url": null,
      "api_key": null,
      "connect_timeout": 60.0,
      "read_timeout": 10.0
    },
    // Example config for Anthropic (see https://docs.anthropic.com/docs/api-reference)
    "anthropic": {
      "base_url": "https://api.anthropic.com",
      "api_key": "your-api-key",
      "connect_timeout": 60.0,
      "read_timeout": 10.0
    },
    // Example config for Azure OpenAI (see https://learn.microsoft.com/en-us/azure/ai-services/openai/reference#chat-completions)
    "azure": {
      "base_url": "https://your-resource-name.openai.azure.com/",
      "api_key": "your-api-key",
      "connect_timeout": 60.0,
      "read_timeout": 10.0,
      "extra": {
        "azure_deployment": "your-azure-deployment-id",
        "api_version": "2024-02-01"
      }
    }
  },
  // Each agent can use a different model or configuration. The default, as before, is GPT4 Turbo
  // for most tasks and GPT3.5 Turbo to generate file descriptions. The agent name here should match
  // the Python class name.
  "agent": {
    "default": {
      "provider": "openai",
      "model": "gpt-4o-2024-05-13",
      "temperature": 0.5
    },
    "CodeMonkey": {
      "provider": "openai",
      "model": "gpt-4-0125-preview",
      "temperature": 0.0
    },
    "CodeMonkey.describe_files": {
      "provider": "openai",
      "model": "gpt-3.5-turbo",
      "temperature": 0.0
    },
    "BugHunter.check_logs": {
      "provider": "anthropic",
      "model": "claude-3-5-sonnet-20240620",
      "temperature": 0.0
    }
  },
  // Logging configuration outputs debug log to "pythagora.log" by default. If you set this to null,
  // the log will be sent to stdout.
  "log": {
    "level": "DEBUG",
    "format": "%(asctime)s %(levelname)s [%(name)s] %(message)s",
    "output": "pythagora.log"
  },
  // Database to use. Pythagora uses asyncio so asyncio-compatible database engine should be specified.
  // If "debug_sql" is set to True, all SQL queries will be logged.
  "db": {
    "url": "sqlite+aiosqlite:///pythagora.db",
    "debug_sql": false
  },
  "ui": {
    "type": "plain"
  },
  "fs": {
    "type": "local",
    // Root directory of the workspace. Pythagora will store all projects under this directory by default.
    "workspace_root": "workspace",
    // Directories, files and patterns to ignore when examining the files in the project.
    // Note that Pythagora already ignores all binary (non-text) files by default.
    "ignore_paths": [
      ".git",
      ".gpt-pilot",
      ".idea",
      ".vscode",
      ".next",
      ".DS_Store",
      "__pycache__",
      "site-packages",
      "node_modules",
      "package-lock.json",
      "venv",
      "dist",
      "build",
      "target",
      "*.min.js",
      "*.min.css",
      "*.svg",
      "*.csv",
      "*.log",
      "go.sum"
    ],
    // Files larger than 50KB will be ignored, even if they otherwise wouldn't be.
    "ignore_size_threshold": 50000
  }
}