--- title: "Clarifai" url: "/docs/providers/clarifai" canonical_url: "https://docs.litellm.ai/docs/providers/clarifai" type: "docs" last_updated: "2026-10-08" related: - "/docs/providers/chutes" - "/docs/providers/clf_ai_gateway" --- # Clarifai > Index of all LiteLLM docs: https://docs.litellm.ai/llms.txt Anthropic、OpenAI、Qwen、xAI、Gemini 以及大多數開源 LLM 都支援 Clarifai。 | Property | Details | |-------|-------| | Description | Clarifai 是一個 AI 平台，透過統一的 API 提供對多種 LLM 的存取。LiteLLM 使用與 OpenAI 相容的介面呼叫 Clarifai 的模型。 | | Provider Doc | [Clarifai ↗](https://docs.clarifai.com/) | |OpenAI compatible Endpoint for Provider | `https://api.clarifai.com/v2/ext/openai/v1` | | Supported Endpoints | `/chat/completions` | ## 先決條件 {#pre-requisites} ```bash uv add litellm ``` ## 必要環境變數 {#required-environment-variables} 若要取得您的 Clarifai Personal access token，請依照這個 [連結](https://docs.clarifai.com/clarifai-basics/authentication/personal-access-tokens/)。 ```python os.environ["CLARIFAI_API_KEY"] = "your-clarifai-pat" ``` LiteLLM 會從 `CLARIFAI_API_KEY` 或 `api_key` 引數讀取 PAT。`CLARIFAI_PAT` 不會被讀取 ## 用法 {#usage} ```python import os from litellm import completion os.environ["CLARIFAI_API_KEY"] = "" response = completion( model="clarifai/openai.chat-completion.gpt-oss-20b", messages=[{ "content": "Tell me a joke about physics?","role": "user"}] ) ``` ## 串流支援 {#streaming-support} LiteLLM 支援與 Clarifai 模型的串流回應： ```python import litellm for chunk in litellm.completion( model="clarifai/openai.chat-completion.gpt-oss-20b", api_key="CLARIFAI_API_KEY", messages=[ {"role": "user", "content": "Tell me a fun fact about space."} ], stream=True, ): print(chunk.choices[0].delta) ``` ## 工具呼叫（函式呼叫） {#tool-calling-function-calling} 透過 LiteLLM 存取的 Clarifai 模型支援函式呼叫： ```python import litellm tools = [{ "type": "function", "function": { "name": "get_weather", "description": "Get current temperature for a given location.", "parameters": { "type": "object", "properties": { "location": { "type": "string", "description": "City and country e.g. Tokyo, Japan" } }, "required": ["location"], "additionalProperties": False }, } }] response = litellm.completion( model="clarifai/openai.chat-completion.gpt-oss-20b", api_key="CLARIFAI_API_KEY", messages=[{"role": "user", "content": "What is the weather in Paris today?"}], tools=tools, ) print(response.choices[0].message.tool_calls) ``` ## Clarifai 模型 {#clarifai-models} liteLLM 支援 [Clarifai community](https://clarifai.com/explore/models?filterData=%5B%7B%22field%22%3A%22use_cases%22%2C%22value%22%3A%5B%22llm%22%5D%7D%5D&page=1&perPage=24) 上的所有模型 ### 🧠 OpenAI 模型 {#-openai-models} - [gpt-oss-20b](https://clarifai.com/openai/chat-completion/models/gpt-oss-20b) - [gpt-oss-120b](https://clarifai.com/openai/chat-completion/models/gpt-oss-120b) - [gpt-5-nano](https://clarifai.com/openai/chat-completion/models/gpt-5-nano) - [gpt-5-mini](https://clarifai.com/openai/chat-completion/models/gpt-5-mini) - [gpt-5](https://clarifai.com/openai/chat-completion/models/gpt-5) - [gpt-4o](https://clarifai.com/openai/chat-completion/models/gpt-4o) - [o3](https://clarifai.com/openai/chat-completion/models/o3) - 更多... ### 🤖 Anthropic 模型 {#-anthropic-models} - [claude-sonnet-4](https://clarifai.com/anthropic/completion/models/claude-sonnet-4) - [claude-opus-4](https://clarifai.com/anthropic/completion/models/claude-opus-4) - [claude-3_5-haiku](https://clarifai.com/anthropic/completion/models/claude-3_5-haiku) - [claude-3_7-sonnet](https://clarifai.com/anthropic/completion/models/claude-3_7-sonnet) - 更多... ### 🪄 xAI 模型 {#-xai-models} - [grok-3](https://clarifai.com/xai/chat-completion/models/grok-3) - [grok-2-vision-1212](https://clarifai.com/xai/chat-completion/models/grok-2-vision-1212) - [grok-2-1212](https://clarifai.com/xai/chat-completion/models/grok-2-1212) - [grok-code-fast-1](https://clarifai.com/xai/chat-completion/models/grok-code-fast-1) - [grok-2-image-1212](https://clarifai.com/xai/image-generation/models/grok-2-image-1212) - 更多... ### 🔷 Google Gemini 模型 {#-google-gemini-models} - [gemini-2_5-pro](https://clarifai.com/gcp/generate/models/gemini-2_5-pro) - [gemini-2_5-flash-lite](https://clarifai.com/gcp/generate/models/gemini-2_5-flash-lite) - [gemini-2_0-flash](https://clarifai.com/gcp/generate/models/gemini-2_0-flash) - [gemini-2_0-flash-lite](https://clarifai.com/gcp/generate/models/gemini-2_0-flash-lite) - 更多... ### 🧩 Qwen 模型 {#-qwen-models} - [Qwen3-30B-A3B-Instruct-2507](https://clarifai.com/qwen/qwenLM/models/Qwen3-30B-A3B-Instruct-2507) - [Qwen3-30B-A3B-Thinking-2507](https://clarifai.com/qwen/qwenLM/models/Qwen3-30B-A3B-Thinking-2507) - [Qwen3-14B](https://clarifai.com/qwen/qwenLM/models/Qwen3-14B) - [QwQ-32B-AWQ](https://clarifai.com/qwen/qwenLM/models/QwQ-32B-AWQ) - [Qwen2_5-VL-7B-Instruct](https://clarifai.com/qwen/qwen-VL/models/Qwen2_5-VL-7B-Instruct) - [Qwen3-Coder-30B-A3B-Instruct](https://clarifai.com/qwen/qwenCoder/models/Qwen3-Coder-30B-A3B-Instruct) - 更多... ### 💡 MiniCPM（OpenBMB）模型 {#-minicpm-openbmb-models} - [MiniCPM-o-2_6-language](https://clarifai.com/openbmb/miniCPM/models/MiniCPM-o-2_6-language) - [MiniCPM3-4B](https://clarifai.com/openbmb/miniCPM/models/MiniCPM3-4B) - [MiniCPM4-8B](https://clarifai.com/openbmb/miniCPM/models/MiniCPM4-8B) - 更多... ### 🧬 Microsoft Phi 模型 {#-microsoft-phi-models} - [Phi-4-reasoning-plus](https://clarifai.com/microsoft/text-generation/models/Phi-4-reasoning-plus) - [phi-4](https://clarifai.com/microsoft/text-generation/models/phi-4) - 更多... ### 🦙 Meta Llama 模型 {#-meta-llama-models} - [Llama-3_2-3B-Instruct](https://clarifai.com/meta/Llama-3/models/Llama-3_2-3B-Instruct) - 更多... ### 🔍 DeepSeek 模型 {#-deepseek-models} - [DeepSeek-R1-0528-Qwen3-8B](https://clarifai.com/deepseek-ai/deepseek-chat/models/DeepSeek-R1-0528-Qwen3-8B) - 更多... ## 搭配 LiteLLM Proxy 的用法 {#usage-with-litellm-proxy} 以下是如何使用 LiteLLM Proxy Server 呼叫 Clarifai ### 1. 將金鑰儲存在您的環境中 {#1-save-key-in-your-environment} ```bash export CLARIFAI_API_KEY="your-clarifai-pat" ``` ### 2. 啟動 proxy {#2-start-the-proxy} **config.yaml** ```yaml model_list: - model_name: clarifai-model litellm_params: model: clarifai/openai.chat-completion.gpt-oss-20b api_key: os.environ/CLARIFAI_API_KEY ``` ```bash litellm --config /path/to/config.yaml # Server running on http://0.0.0.0:4000 ``` ### 3. 測試 {#3-test-it} **Curl Request** ```shell curl --location 'http://0.0.0.0:4000/chat/completions' \ --header 'Content-Type: application/json' \ --data ' { "model": "clarifai-model", "messages": [ { "role": "user", "content": "what llm are you" } ] } ' ``` **OpenAI v1.0.0+** ```python import openai client = openai.OpenAI( api_key="anything", base_url="http://0.0.0.0:4000" ) response = client.chat.completions.create( model="clarifai-model", messages = [ { "role": "user", "content": "this is a test request, write a short poem" } ] ) print(response) ``` ## 重要說明 {#important-notes} - 指定模型名稱時，請務必在 Clarifai 模型 ID 前加上 `clarifai/` - 使用您的 Clarifai Personal Access Token（PAT）作為 API 金鑰 - 使用量會透過 Clarifai 進行追蹤與計費 - API 速率限制受您的 Clarifai 帳戶設定影響 - 大多數 OpenAI 參數都支援，但某些進階功能可能因模型而異 ## 常見問題 {#faqs} | Question | Answer | |----------|---------| | Can I use all Clarifai models with LiteLLM? | 大多數聊天完成模型都支援。請使用 Clarifai 模型 URL 作為 `model`。 | | Do I need a separate Clarifai PAT? | 是，您必須使用有效的 Clarifai Personal Access Token。 | | Is tool calling supported? | 是，前提是底層的 Clarifai 模型支援函式／工具呼叫。 | | How is billing handled? | Clarifai 的使用量會透過 Clarifai 個別計費。 | ## 其他資源 {#additional-resources} - [Clarifai 文件](https://docs.clarifai.com/) - [LiteLLM GitHub](https://github.com/BerriAI/litellm) - [Clarifai Runners 範例](https://github.com/Clarifai/runners-examples) ## Related pages - [Chutes](https://docs.litellm.ai/docs/providers/chutes.md) - [CLF AI Gateway](https://docs.litellm.ai/docs/providers/clf_ai_gateway.md)