--- title: "使用 PDF 輸入" url: "/docs/completion/document_understanding" canonical_url: "https://docs.litellm.ai/docs/completion/document_understanding" type: "docs" last_updated: "2026-10-08" related: - "/docs/completion/audio" - "/docs/completion/image_generation_chat" --- # 使用 PDF 輸入 > Index of all LiteLLM docs: https://docs.litellm.ai/llms.txt 如何將 pdf（其他文件類型）傳送／接收至 `/chat/completions` 端點 適用於： - Vertex AI 模型（Gemini + Anthropic） - Bedrock 模型 - Anthropic API 模型 - OpenAI API 模型 - Mistral（僅使用已上傳檔案的 file ID，類似於 OpenAI file_id 輸入） ## 快速開始 {#quick-start} ### URL {#url} **SDK** ```python from litellm import completion from litellm.utils import supports_pdf_input # set aws credentials os.environ["AWS_ACCESS_KEY_ID"] = "" os.environ["AWS_SECRET_ACCESS_KEY"] = "" os.environ["AWS_REGION_NAME"] = "" # pdf url file_url = "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf" # model model = "bedrock/us.anthropic.claude-sonnet-5" file_content = [ {"type": "text", "text": "What's this file about?"}, { "type": "file", "file": { "file_id": file_url, } }, ] if not supports_pdf_input(model, None): print("Model does not support image input") response = completion( model=model, messages=[{"role": "user", "content": file_content}], ) assert response is not None ``` **PROXY** 1. 設定 config.yaml ```yaml model_list: - model_name: bedrock-model litellm_params: model: bedrock/us.anthropic.claude-sonnet-5 aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY aws_region_name: os.environ/AWS_REGION_NAME ``` 2. 啟動 proxy ```bash litellm --config /path/to/config.yaml ``` 3. 測試它！ ```bash curl -X POST 'http://0.0.0.0:4000/chat/completions' \ -H 'Content-Type: application/json' \ -H "Authorization: Bearer $LITELLM_API_KEY" \ -d '{ "model": "bedrock-model", "messages": [ {"role": "user", "content": [ {"type": "text", "text": "What's this file about?"}, { "type": "file", "file": { "file_id": "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf", } } ]}, ] }' ``` ### base64 {#base64} **SDK** ```python from litellm import completion from litellm.utils import supports_pdf_input # set aws credentials os.environ["AWS_ACCESS_KEY_ID"] = "" os.environ["AWS_SECRET_ACCESS_KEY"] = "" os.environ["AWS_REGION_NAME"] = "" # pdf url image_url = "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf" response = requests.get(url) file_data = response.content encoded_file = base64.b64encode(file_data).decode("utf-8") base64_url = f"data:application/pdf;base64,{encoded_file}" # model model = "bedrock/us.anthropic.claude-sonnet-5" file_content = [ {"type": "text", "text": "What's this file about?"}, { "type": "file", "file": { "file_data": base64_url, } }, ] if not supports_pdf_input(model, None): print("Model does not support image input") response = completion( model=model, messages=[{"role": "user", "content": file_content}], ) assert response is not None ``` **PROXY** 1. 設定 config.yaml ```yaml model_list: - model_name: bedrock-model litellm_params: model: bedrock/us.anthropic.claude-sonnet-5 aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY aws_region_name: os.environ/AWS_REGION_NAME ``` 2. 啟動 proxy ```bash litellm --config /path/to/config.yaml ``` 3. 測試它！ ```bash curl -X POST 'http://0.0.0.0:4000/chat/completions' \ -H 'Content-Type: application/json' \ -H "Authorization: Bearer $LITELLM_API_KEY" \ -d '{ "model": "bedrock-model", "messages": [ {"role": "user", "content": [ {"type": "text", "text": "What's this file about?"}, { "type": "file", "file": { "file_data": "data:application/pdf;base64...", } } ]}, ] }' ``` ## 指定格式 {#specifying-format} 若要指定文件的格式，您可以使用 `format` 參數。 **SDK** ```python from litellm import completion from litellm.utils import supports_pdf_input # set aws credentials os.environ["AWS_ACCESS_KEY_ID"] = "" os.environ["AWS_SECRET_ACCESS_KEY"] = "" os.environ["AWS_REGION_NAME"] = "" # pdf url file_url = "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf" # model model = "bedrock/us.anthropic.claude-sonnet-5" file_content = [ {"type": "text", "text": "What's this file about?"}, { "type": "file", "file": { "file_id": file_url, "format": "application/pdf", } }, ] if not supports_pdf_input(model, None): print("Model does not support image input") response = completion( model=model, messages=[{"role": "user", "content": file_content}], ) assert response is not None ``` **PROXY** 1. 設定 config.yaml ```yaml model_list: - model_name: bedrock-model litellm_params: model: bedrock/us.anthropic.claude-sonnet-5 aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY aws_region_name: os.environ/AWS_REGION_NAME ``` 2. 啟動 proxy ```bash litellm --config /path/to/config.yaml ``` 3. 測試它！ ```bash curl -X POST 'http://0.0.0.0:4000/chat/completions' \ -H 'Content-Type: application/json' \ -H "Authorization: Bearer $LITELLM_API_KEY" \ -d '{ "model": "bedrock-model", "messages": [ {"role": "user", "content": [ {"type": "text", "text": "What's this file about?"}, { "type": "file", "file": { "file_id": "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf", "format": "application/pdf", } } ]}, ] }' ``` ## Mistral 範例 {#mistral-example} 以下是使用 Mistral 模型進行文件理解的範例 payload： **SDK** ```python from litellm import completion # pdf file_id received from files endpoint file_id = "fa778e5e-46ec-4562-8418-36623fe25a71" # model model = "mistral/mistral-large-latest" file_content = [ {"type": "text", "text": "What's this file about?"}, { "type": "file", "file": { "file_id": file_id, } }, ] response = completion( model=model, messages=[{"role": "user", "content": file_content}], ) assert response is not None ``` **PROXY** ```bash curl -X POST 'http://0.0.0.0:4000/chat/completions' \ -H 'Content-Type: application/json' \ -H "Authorization: Bearer $LITELLM_API_KEY" \ -d '{ "model": "mistral/mistral-large-latest", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "What is the content of the file?" }, { "type": "file", "file": { "file_id": "fa778e5e-46ec-4562-8418-36623fe25a71" } } ] } ] } ``` ## 檢查模型是否支援 pdf 輸入 {#checking-if-a-model-supports-pdf-input} **SDK** 使用來自 `litellm.utils` 的 `supports_pdf_input(model="bedrock/us.anthropic.claude-sonnet-5")`，如果模型可以接受 pdf 輸入，則會回傳 `True`。它不會在頂層 `litellm` 模組中匯出 ```python from litellm.utils import supports_pdf_input assert supports_pdf_input(model="bedrock/us.anthropic.claude-sonnet-5") == True ``` **PROXY** 1. 在 config.yaml 中定義 bedrock 模型 ```yaml model_list: - model_name: bedrock-model # model group name litellm_params: model: bedrock/us.anthropic.claude-sonnet-5 aws_access_key_id: os.environ/AWS_ACCESS_KEY_ID aws_secret_access_key: os.environ/AWS_SECRET_ACCESS_KEY aws_region_name: os.environ/AWS_REGION_NAME model_info: # OPTIONAL - set manually supports_pdf_input: True ``` 2. 執行 proxy 伺服器 ```bash litellm --config config.yaml ``` 3. 呼叫 `/model/info` 以檢查模型是否支援 `pdf` 輸入。`/model_group/info` 不會回傳 `supports_pdf_input` ```shell curl -X 'GET' \ 'http://localhost:4000/model/info' \ -H 'accept: application/json' \ -H "x-api-key: $LITELLM_API_KEY" ``` 預期回應 ```json { "data": [ { "model_name": "bedrock-model", "litellm_params": {...}, "model_info": { "litellm_provider": "bedrock_converse", "mode": "chat", ..., "supports_pdf_input": true } } ] } ``` ## Related pages - [使用 Audio 模型](https://docs.litellm.ai/docs/completion/audio.md) - [聊天完成、Responses API 中的圖片生成](https://docs.litellm.ai/docs/completion/image_generation_chat.md)