One API Calling GenAI

Unified interface for all providers and all modalities: use the genai-calling skill to operate the published genai-calling CLI/SDK across text/image/audio/video/embedding workflows, with support for authenticated local MCP workflows.

genai-calling

This skill is named genai-calling in this repository.

The runtime package is genai-calling, the Python import path is gravtice.genai, and the environment variable prefix is GENAI_CALLING_*.

Quick Start

IMPORTANT: If you rely on project-local .env.* files, run commands in the directory that contains those files (typically this skill base directory). If no project-local env file is present, the runtime also falls back to ~/.genai-calling/.env. If you pass runtime env vars (inline/export), working directory is not restricted.

bash

# 1) Create `.env.local` in this skill directory
(cd "<SKILL_BASE_DIR>" && { test -f .env.local || touch .env.local; })

# 2) Edit `<SKILL_BASE_DIR>/.env.local` and set at least one provider key (see "Configuration Templates" and "Supported Environment Variables").
# Example (OpenAI):
#   OPENAI_API_KEY=...

# 3) Text
(cd "<SKILL_BASE_DIR>" && uvx --from genai-calling genai --model openai:gpt-4o-mini --prompt "Hello")

# 4) See what you can use (requires at least one provider key configured)
(cd "<SKILL_BASE_DIR>" && uvx --from genai-calling genai model available --all)

For user-wide defaults shared across projects, create ~/.genai-calling/.env and put provider credentials there. Project-local .env.* files still win.

If uvx is unavailable, install once and use genai directly:

bash

python -m pip install --upgrade genai-calling
(cd "<SKILL_BASE_DIR>" && genai --model openai:gpt-4o-mini --prompt "Hello")

Configuration (Env Vars, Zero-parameter)

Configuration is managed via environment variables.

You can set env vars in two ways:

1. Runtime env vars (inline before command, or export in shell)
2. Env files (.env.local, .env.production, .env.development, .env.test, ~/.genai-calling/.env)

Recommended for this skill:

• Put reusable provider credentials in ~/.genai-calling/.env
• Put project-level overrides in <SKILL_BASE_DIR>/.env.local
• Use runtime env vars for one-off overrides

Runtime example (inline):

bash

(cd "<SKILL_BASE_DIR>" && OPENAI_API_KEY=... uvx --from genai-calling genai --model openai:gpt-4o-mini --prompt "Hello")

When env files are used, SDK/CLI/MCP loads them automatically with priority (high -> low):

• .env.local > .env.production > .env.development > .env.test > ~/.genai-calling/.env

Process env vars override file-based config.

Minimal .env.local (OpenAI text only):

bash

OPENAI_API_KEY=...
GENAI_CALLING_TIMEOUT_MS=120000

Minimal ~/.genai-calling/.env:

bash

OPENAI_API_KEY=...
GOOGLE_API_KEY=
ANTHROPIC_API_KEY=

Notes:

• Do not commit .env.local (add it to .gitignore if needed).
• ~/.genai-calling/.env is user-level config and should hold only values you want shared across projects.
• Provider credentials should use the shorter provider-specific variable names such as OPENAI_API_KEY.

Configuration Templates

Project-local .env.local example:

bash

# Copy only what you need. Do not commit `.env.local`.

# --------------------
# Common
# --------------------
GENAI_CALLING_TIMEOUT_MS=120000
GENAI_CALLING_URL_DOWNLOAD_MAX_BYTES=134217728
# GENAI_CALLING_ALLOW_PRIVATE_URLS=1
# GENAI_CALLING_TRANSPORT=

# --------------------
# Providers
# --------------------
OPENAI_API_KEY=
GOOGLE_API_KEY=
ANTHROPIC_API_KEY=

ALIYUN_API_KEY=
ALIYUN_OAI_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1

VOLCENGINE_API_KEY=
VOLCENGINE_OAI_BASE_URL=https://ark.cn-beijing.volces.com/api/v3

TUZI_BASE_URL=https://api.tu-zi.com
# TUZI_OAI_BASE_URL=https://api.tu-zi.com/v1
# TUZI_GOOGLE_BASE_URL=https://api.tu-zi.com
# TUZI_ANTHROPIC_BASE_URL=https://api.tu-zi.com
TUZI_WEB_API_KEY=
TUZI_OPENAI_API_KEY=
TUZI_GOOGLE_API_KEY=
TUZI_ANTHROPIC_API_KEY=

# --------------------
# MCP Server
# --------------------
GENAI_CALLING_MCP_HOST=127.0.0.1
GENAI_CALLING_MCP_PORT=6001
GENAI_CALLING_MCP_PUBLIC_BASE_URL=
# GENAI_CALLING_MCP_BEARER_TOKEN=
# GENAI_CALLING_MCP_TOKEN_RULES=token1: [openai google]; token2: [openai:gpt-4o-mini]

User-wide ~/.genai-calling/.env example:

bash

OPENAI_API_KEY=
GOOGLE_API_KEY=
ANTHROPIC_API_KEY=

Recommended usage:

• Put shared provider credentials in ~/.genai-calling/.env
• Put project-specific overrides and MCP settings in <SKILL_BASE_DIR>/.env.local
• Keep only the providers and options you actually use

Supported Environment Variables

Common runtime

• GENAI_CALLING_TIMEOUT_MS (default: 120000)
• GENAI_CALLING_URL_DOWNLOAD_MAX_BYTES (default: 134217728)
• GENAI_CALLING_ALLOW_PRIVATE_URLS (1/true/yes to allow private/loopback URL download)
• GENAI_CALLING_TRANSPORT (internal transport marker; MCP server uses mcp, legacy sse is accepted)

Provider credentials

• OpenAI: OPENAI_API_KEY
• Google (Gemini): GOOGLE_API_KEY
• Anthropic (Claude): ANTHROPIC_API_KEY
• Aliyun (DashScope/百炼): ALIYUN_API_KEY
• Volcengine (Ark/豆包): VOLCENGINE_API_KEY

Provider base URL overrides

• ALIYUN_OAI_BASE_URL (default: https://dashscope.aliyuncs.com/compatible-mode/v1)
• VOLCENGINE_OAI_BASE_URL (default: https://ark.cn-beijing.volces.com/api/v3)
• TUZI_BASE_URL (default: https://api.tu-zi.com)
• TUZI_OAI_BASE_URL (optional override)
• TUZI_GOOGLE_BASE_URL (optional override)
• TUZI_ANTHROPIC_BASE_URL (optional override)

Tuzi credentials

• TUZI_WEB_API_KEY
• TUZI_OPENAI_API_KEY
• TUZI_GOOGLE_API_KEY
• TUZI_ANTHROPIC_API_KEY

MCP server

• GENAI_CALLING_MCP_HOST (default: 127.0.0.1)
• GENAI_CALLING_MCP_PORT (default: 6001)
• GENAI_CALLING_MCP_PUBLIC_BASE_URL
• GENAI_CALLING_MCP_BEARER_TOKEN
• GENAI_CALLING_MCP_TOKEN_RULES

Quick guidance:

• Most users only need one provider key plus GENAI_CALLING_TIMEOUT_MS
• Only set GENAI_CALLING_ALLOW_PRIVATE_URLS if you explicitly want to bypass private URL protection
• Only set MCP variables when you run genai-mcp-server

Model Format

Model string is {provider}:{model_id} (example: openai:gpt-4o-mini).

Use this to pick a model by output modality:

bash

(cd "<SKILL_BASE_DIR>" && uvx --from genai-calling genai model available --all)
# Look for: out=text / out=image / out=audio / out=video / out=embedding

If you have not configured any keys yet, you can still view the SDK curated list:

bash

(cd "<SKILL_BASE_DIR>" && uvx --from genai-calling genai model sdk)

Common Scenarios

Image understanding

bash

(cd "<SKILL_BASE_DIR>" && uvx --from genai-calling genai --model openai:gpt-4o-mini --prompt "Describe this image" --image-path "/path/to/image.png")

Image generation (save to file)

bash

(cd "<SKILL_BASE_DIR>" && uvx --from genai-calling genai --model openai:gpt-image-1 --prompt "A red square, minimal" --output-path "/tmp/out.png")

Speech-to-text (transcription)

bash

(cd "<SKILL_BASE_DIR>" && uvx --from genai-calling genai --model openai:whisper-1 --audio-path "/path/to/audio.wav")

Text-to-speech (save to file)

bash

(cd "<SKILL_BASE_DIR>" && uvx --from genai-calling genai --model openai:tts-1 --prompt "你好" --output-path "/tmp/tts.mp3")

Python SDK

Install:

bash

python -m pip install --upgrade genai-calling

Minimal example:

python

from gravtice.genai import Client, GenerateRequest, Message, OutputSpec, Part

client = Client()
resp = client.generate(
    GenerateRequest(
        model="openai:gpt-4o-mini",
        input=[Message(role="user", content=[Part.from_text("Hello")])],
        output=OutputSpec(modalities=["text"]),
    )
)
print(resp.output[0].content[0].text)

Note: Client() loads project-local .env.* from the current working directory and then falls back to ~/.genai-calling/.env; run your script in the directory that contains your project env files, or export env vars in the process environment.

MCP Server

Start server (Streamable HTTP: /mcp, SSE: /sse):

bash

(cd "<SKILL_BASE_DIR>" && uvx --from genai-calling genai-mcp-server)

Recommended: set auth via runtime env vars, .env.local, or ~/.genai-calling/.env before exposing the server:

bash

# GENAI_CALLING_MCP_BEARER_TOKEN=sk-...

Debug with MCP CLI:

bash

(cd "<SKILL_BASE_DIR>" && uvx --from genai-calling genai-mcp-cli env)
(cd "<SKILL_BASE_DIR>" && uvx --from genai-calling genai-mcp-cli tools)
(cd "<SKILL_BASE_DIR>" && uvx --from genai-calling genai-mcp-cli call list_providers)
(cd "<SKILL_BASE_DIR>" && uvx --from genai-calling genai-mcp-cli call generate --args '{"request":{"model":"openai:gpt-4o-mini","input":"Hello","output":{"modalities":["text"]}}}')

Troubleshooting

Missing/invalid API key (401/403)

Set provider credentials via runtime env vars, <SKILL_BASE_DIR>/.env.local, or ~/.genai-calling/.env (see "Supported Environment Variables"), then retry.

File input errors (mime type)

If you see cannot detect ... mime type, verify the path exists and is a valid image/audio/video file.

Timeout / long-running jobs

Increase GENAI_CALLING_TIMEOUT_MS (runtime env var, .env.local, or ~/.genai-calling/.env) and retry.

URL download blocked / SSRF protection

Binary outputs may be returned as URLs. Private/loopback URLs are rejected by default. Only if you understand the risk, set GENAI_CALLING_ALLOW_PRIVATE_URLS=1.

MCP auth (401 Unauthorized)

Set GENAI_CALLING_MCP_BEARER_TOKEN (or GENAI_CALLING_MCP_TOKEN_RULES) via runtime env var, .env.local, or ~/.genai-calling/.env, and ensure genai-mcp-cli uses the same token.