mirror of
https://gitee.com/wanwujie/deer-flow
synced 2026-04-03 06:12:14 +08:00
feat: add environment variable injection for Docker sandbox
- Add environment field to sandbox config for injecting env vars into container - Support $VAR syntax to resolve values from host environment variables - Refactor frontend API modules to use centralized getBackendBaseURL() - Improve Doraemon skill with explicit input/output path arguments - Add .env.example file Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
11
.env.example
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11
.env.example
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@@ -0,0 +1,11 @@
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# TAVILY API Key
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TAVILY_API_KEY=your-tavily-api-key
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# Jina API Key
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JINA_API_KEY=your-jina-api-key
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# Optional:
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# VOLCENGINE_API_KEY=your-volcengine-api-key
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# OPENAI_API_KEY=your-openai-api-key
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# GEMINI_API_KEY=your-gemini-api-key
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# DEEPSEEK_API_KEY=your-deepseek-api-key
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@@ -43,6 +43,9 @@ class AioSandboxProvider(SandboxProvider):
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- host_path: /path/on/host
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container_path: /path/in/container
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read_only: false
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environment: # Environment variables to inject (values starting with $ are resolved from host env)
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NODE_ENV: production
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API_KEY: $MY_API_KEY
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"""
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def __init__(self):
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@@ -94,8 +97,29 @@ class AioSandboxProvider(SandboxProvider):
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"auto_start": sandbox_config.auto_start if sandbox_config.auto_start is not None else True,
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"container_prefix": sandbox_config.container_prefix or DEFAULT_CONTAINER_PREFIX,
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"mounts": sandbox_config.mounts or [],
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"environment": self._resolve_env_vars(sandbox_config.environment or {}),
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}
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def _resolve_env_vars(self, env_config: dict[str, str]) -> dict[str, str]:
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"""Resolve environment variable references in configuration.
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Values starting with $ are resolved from host environment variables.
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Args:
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env_config: Dictionary of environment variable names to values.
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Returns:
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Dictionary with resolved environment variable values.
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"""
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resolved = {}
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for key, value in env_config.items():
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if isinstance(value, str) and value.startswith("$"):
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env_name = value[1:] # Remove $ prefix
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resolved[key] = os.environ.get(env_name, "")
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else:
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resolved[key] = str(value)
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return resolved
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def _is_sandbox_ready(self, base_url: str, timeout: int = 30) -> bool:
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"""Check if sandbox is ready to accept connections.
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@@ -191,6 +215,10 @@ class AioSandboxProvider(SandboxProvider):
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container_name,
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]
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# Add configured environment variables
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for key, value in self._config["environment"].items():
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cmd.extend(["-e", f"{key}={value}"])
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# Add configured volume mounts
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for mount in self._config["mounts"]:
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host_path = mount.host_path
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@@ -22,6 +22,7 @@ class SandboxConfig(BaseModel):
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auto_start: Whether to automatically start Docker container (default: true)
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container_prefix: Prefix for container names (default: deer-flow-sandbox)
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mounts: List of volume mounts to share directories with the container
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environment: Environment variables to inject into the container (values starting with $ are resolved from host env)
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"""
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use: str = Field(
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@@ -52,5 +53,10 @@ class SandboxConfig(BaseModel):
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default_factory=list,
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description="List of volume mounts to share directories between host and container",
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)
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environment: dict[str, str] = Field(
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default_factory=dict,
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description="Environment variables to inject into the sandbox container. "
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"Values starting with $ will be resolved from host environment variables.",
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)
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model_config = ConfigDict(extra="allow")
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@@ -147,6 +147,14 @@ sandbox:
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# # - host_path: /path/on/host
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# # container_path: /home/user/shared
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# # read_only: false
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#
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# # Optional: Environment variables to inject into the sandbox container
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# # Values starting with $ will be resolved from host environment variables
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# # environment:
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# # NODE_ENV: production
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# # DEBUG: "false"
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# # API_KEY: $MY_API_KEY # Reads from host's MY_API_KEY env var
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# # DATABASE_URL: $DATABASE_URL # Reads from host's DATABASE_URL env var
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# ============================================================================
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# Skills Configuration
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@@ -1,17 +1,14 @@
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import { env } from "@/env";
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import { getBackendBaseURL } from "@/core/config";
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import type { MCPConfig } from "./types";
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export async function loadMCPConfig() {
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const response = await fetch(
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`${env.NEXT_PUBLIC_BACKEND_BASE_URL}/api/mcp/config`,
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);
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const response = await fetch(`${getBackendBaseURL()}/api/mcp/config`);
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return response.json() as Promise<MCPConfig>;
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}
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export async function updateMCPConfig(config: MCPConfig) {
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const response = await fetch(
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`${env.NEXT_PUBLIC_BACKEND_BASE_URL}/api/mcp/config`,
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const response = await fetch(`${getBackendBaseURL()}/api/mcp/config`,
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{
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method: "PUT",
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headers: {
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@@ -1,16 +1,16 @@
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import { env } from "@/env";
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import { getBackendBaseURL } from "@/core/config";
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import type { Skill } from "./type";
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export async function loadSkills() {
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const skills = await fetch(`${env.NEXT_PUBLIC_BACKEND_BASE_URL}/api/skills`);
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const skills = await fetch(`${getBackendBaseURL()}/api/skills`);
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const json = await skills.json();
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return json.skills as Skill[];
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}
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export async function enableSkill(skillName: string, enabled: boolean) {
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const response = await fetch(
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`${env.NEXT_PUBLIC_BACKEND_BASE_URL}/api/skills/${skillName}`,
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`${getBackendBaseURL()}/api/skills/${skillName}`,
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{
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method: "PUT",
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headers: {
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@@ -12,7 +12,7 @@ Generate JSON spec for 8 panels arranged on ONE 9:16 vertical canvas (1080x1920)
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1. Extract story context (theme, gadget, conflict, punchline)
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2. Map to 8 narrative beats
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3. Output JSON to `/mnt/user-data/outputs/prompt.json`
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4. Run `python /mnt/skills/custom/doraemon-comic-aigc/scripts/generate.py`
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4. Run `python /mnt/skills/custom/doraemon-comic-aigc/scripts/generate.py --input_path /mnt/user-data/outputs/prompt.json --output_path /mnt/user-data/outputs/doraemon.png `
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5. Directly present the output image as well as the `prompt.json` using the `present_files` tool without checking the file existence
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## Panel Layout
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@@ -1,10 +1,11 @@
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import argparse
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import base64
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import os
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import requests
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def generate_image(prompt: str) -> str:
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def generate_image(prompt: str, output_path: str) -> str:
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api_key = os.getenv("GEMINI_API_KEY")
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if not api_key:
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return "GEMINI_API_KEY is not set"
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@@ -24,22 +25,25 @@ def generate_image(prompt: str) -> str:
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if len(image_parts) == 1:
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base64_image = image_parts[0]["inlineData"]["data"]
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# Save the image to a file
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with open("/mnt/user-data/outputs/doraemon.png", "wb") as f:
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with open(output_path, "wb") as f:
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f.write(base64.b64decode(base64_image))
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return "Successfully generated image to /mnt/user-data/outputs/doraemon.png"
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return f"Successfully generated image to {output_path}"
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else:
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return "Failed to generate image"
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def main():
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def main(input_path: str, output_path: str):
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with open(
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"/mnt/user-data/outputs/prompt.json",
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input_path,
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"r",
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) as f:
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raw = f.read()
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print(generate_image(raw))
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print(generate_image(raw, output_path))
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if __name__ == "__main__":
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main()
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main()
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parser = argparse.ArgumentParser(description="Generate Doraemon comic image")
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parser.add_argument("--input_path", required=True, help="Path to the input prompt JSON file")
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parser.add_argument("--output_path", required=True, help="Path to save the output image")
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args = parser.parse_args()
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main(args.input_path, args.output_path)
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