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取得 User API key：
點選達哥面板左下角
More Actions按鈕，選取Settings
進到
Settings後，點選+ API Key按鈕新增
複製
API Key
取得 Assistant ID：
選取欲 preview 的 Assistant，點選
Setting按鈕
選取
Advancedtab，複製Assistant ID
Demo
Text:
Image:
替換掉對應的
API_KEY與ASSISTANT_ID
在輸入框輸入 image url 即可
如果您想要使用本機影像，您可以使用下列 Python 程式碼將它轉換成 base64，以便將其傳遞至 API。 或者您可以使用線上工具將影像檔轉成 base64。
程式碼區塊 language py import base64 from mimetypes import guess_type # Function to encode a local image into data URL def local_image_to_data_url(image_path): # Guess the MIME type of the image based on the file extension mime_type, _ = guess_type(image_path) if mime_type is None: mime_type = 'application/octet-stream' # Default MIME type if none is found # Read and encode the image file with open(image_path, "rb") as image_file: base64_encoded_data = base64.b64encode(image_file.read()).decode('utf-8') # Construct the data URL return f"data:{mime_type};base64,{base64_encoded_data}" # Example usage image_path = '<path_to_image>' data_url = local_image_to_data_url(image_path) print("Data URL:", data_url)
...
常用 API curl 範例
create thread
| 程式碼區塊 | ||
|---|---|---|
| ||
curl https://prod.dvcbot.net/api/assts/v1/threads \
-H "Authorization: ${YOUR API KEY}" \
-H 'Content-Type: application/json' \
-d '' |
create msg
| 程式碼區塊 | ||
|---|---|---|
| ||
curl https://prod.dvcbot.net/api/assts/v1/threads/{thread_id}/messages \
-H "Authorization: ${YOUR API KEY}" \
-H 'Content-Type: application/json' \
-d '{
"role": "user",
"content": "How does AI work? Explain it in simple terms."
}' |
create run (non streaming)
| 程式碼區塊 | ||
|---|---|---|
| ||
curl https://prod.dvcbot.net/api/assts/v1/threads/{thread_id}/runs \
-H "Authorization: ${YOUR API KEY}" \
-H 'Content-Type: application/json' \
-d '{
"assistant_id": "asst_abc123"
}' |
call plugin api
| 程式碼區塊 | ||
|---|---|---|
| ||
curl https://prod.dvcbot.net/api/assts/v1/pluginapi?tid={thread_id}&aid={assistant_id}&pid={function_name} \
-H "Authorization: ${YOUR API KEY}" \
-H 'Content-Type: application/json' \
-d ' # function arguments' |
submit tool outputs to run
| 程式碼區塊 | ||
|---|---|---|
| ||
curl https://prod.dvcbot.net/api/assts/v1/threads/{thread_id}/runs/{run_id}/submit_tool_outputs \
-H "Authorization: ${YOUR API KEY}" \
-H 'Content-Type: application/json' \
-d '{
"tool_outputs": [
{
"tool_call_id": "call_abc123",
"output": "28C"
}
]
}' |
Wrap up:
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use curl to write a script
將上面常用的 curl api 組合在一起，即可用 bash 完成一個陽春版的達哥對話腳本：
要先拿到 Assistant ID & User API key
expot API KEY，ASSISTANTexport
API_KEY、ASSISTANT_ID以及你的 inputINPUT_MSG程式碼區塊 language bash export ASSISTANT_ID="YOUR ASSISTANT ID" export API_KEY="YOUR API KEY" export INPUT_MSG="YOUR MESSAGE TO ASSISTANT"執行以下腳本 (請先確保環境有安裝 jq 套件)
mac:
brew install jqubuntu:
apt-get install jqcent os:
yum install jq
程式碼區塊 language bash BASE_URL="https://prod.dvcbot.net/api/assts/v1" # create thread AUTH_HEADER="Authorization: Bearer ${API_KEY}" THREAD_URL="${BASE_URL}/threads" THREAD_ID=`curl -s --location "${THREAD_URL}" \ --header 'OpenAI-Beta: assistants=v2' \ --header 'Content-Type: application/json' \ --header "${AUTH_HEADER}" \ --data '{}' | jq .id | tr -d '"'` # add msg to thread CREATE_MSG_DATA=$(< <(cat <<EOF { "role": "user", "content": "$INPUT_MSG" } EOF )) MSG_URL="${BASE_URL}/threads/${THREAD_ID}/messages" curl -s --location "${MSG_URL}" \ --header 'OpenAI-Beta: assistants=v2' \ --header 'Content-Type: application/json' \ --header "${AUTH_HEADER}" \ --data "${CREATE_MSG_DATA}" > /dev/null # run the assistant within thread CREATE_RUN_DATA=$(< <(cat <<EOF { "assistant_id": "$ASSISTANT_ID", "additional_instructions": "The current time is: `date '+%Y-%m-%d %H:%M:%S'`" } EOF )) RUN_URL="${BASE_URL}/threads/${THREAD_ID}/runs" RUN_ID=`curl -s --location "${RUN_URL}" \ --header 'OpenAI-Beta: assistants=v2' \ --header 'Content-Type: application/json' \ --header "${AUTH_HEADER}" \ --data "${CREATE_RUN_DATA}" | jq .id | tr -d '"'` # get run result RUN_STAUS="" while [[ $RUN_STAUS != "completed" ]] do RESP=`curl -s --location --request GET "${RUN_URL}/$RUN_ID" \ --header 'OpenAI-Beta: assistants=v2' \ --header 'Content-Type: application/json' \ --header "${AUTH_HEADER}"` RUN_STAUS=`echo $RESP| jq .status | tr -d '"'`; REQUIRED_ACTION=`echo $RESP| jq .required_action` while [[ $RUN_STAUS = "requires_action" ]] && [[ ! -z "$REQUIRED_ACTION" ]] do TOOL_OUTPUTS='[]' LEN=$( echo "$REQUIRED_ACTION" | jq '.submit_tool_outputs.tool_calls | length' ) for (( i=0; i<$LEN; i++ )) do FUNC_NAME=`echo "$REQUIRED_ACTION" | jq ".submit_tool_outputs.tool_calls[$i].function.name" | tr -d '"'` ARGS=`echo "$REQUIRED_ACTION" | jq ".submit_tool_outputs.tool_calls[$i].function.arguments"` ARGS=${ARGS//\\\"/\"} ARGS=${ARGS#"\""} ARGS=${ARGS%"\""} PLUGINAPI_URL="${BASE_URL}/pluginapi?tid=${THREAD_ID}&aid=${ASSISTANT_ID}&pid=${FUNC_NAME}" OUTPUT=`curl -s --location "${PLUGINAPI_URL}" \ --header 'OpenAI-Beta: assistants=v2' \ --header 'Content-Type: application/json' \ --header "${AUTH_HEADER}" \ --data "${ARGS}"` OUTPUT="${OUTPUT:0:8000}" OUTPUT=${OUTPUT//\"/\\\"} CALL_ID=`echo "$REQUIRED_ACTION" | jq ".submit_tool_outputs.tool_calls[$i].id" | tr -d '"'` TOOL_OUTPUT=$(< <(cat <<EOF { "tool_call_id": "$CALL_ID", "output": "$OUTPUT" } EOF )) TOOL_OUTPUTS=$(jq --argjson obj "$TOOL_OUTPUT" '. += [$obj]' <<< "$TOOL_OUTPUTS") done SUBMIT_TOOL_OUTPUT_RUN_RUL="${BASE_URL}/threads/${THREAD_ID}/runs/${RUN_ID}/submit_tool_outputs" TOOL_OUTPUTS_DATA=$(< <(cat <<EOF { "tool_outputs": $TOOL_OUTPUTS } EOF )) curl -s --location "${SUBMIT_TOOL_OUTPUT_RUN_RUL}" \ --header 'OpenAI-Beta: assistants=v2' \ --header 'Content-Type: application/json' \ --header "${AUTH_HEADER}" \ --data "${TOOL_OUTPUTS_DATA}" > /dev/null RESP=`curl -s --location --request GET "${RUN_URL}/$RUN_ID" \ --header 'OpenAI-Beta: assistants=v2' \ --header 'Content-Type: application/json' \ --header "${AUTH_HEADER}"` RUN_STAUS=`echo $RESP| jq .status | tr -d '"'`; sleep 1 done sleep 1 done #list msg RESPONSE_MSG=`curl -s --location --request GET "${MSG_URL}" \ --header 'OpenAI-Beta: assistants=v2' \ --header 'Content-Type: application/json' \ --header "${AUTH_HEADER}" | jq .data[0].content[].text.value` echo "you: "$INPUT_MSG echo "" echo "davinci bot: "$RESPONSE_MSG即可看到結果如下
程式碼區塊 you: "your message here" davinci bot: "response from assistant"
...
要先拿到 Assistant ID & User API key
expot API KEY，ASSISTANTexport
API_KEY、ASSISTANT_ID以及你的 inputINPUT_MSG程式碼區塊 language bashexport ASSISTANT_ID="YOUR ASSISTANT ID" export API_KEY="YOUR API KEY" export IMAGE_URL="YOUR IMAGE URL HEHE"IMAGE_URL格式參考上方 Gradio image 範例
執行以下腳本 (請先確保環境有安裝 jq 套件)
mac:
brew install jqubuntu:
apt-get install jqcent os:
yum install jq
程式碼區塊 BASE_URL="https://prod.dvcbot.net/api/assts/v1" # create thread AUTH_HEADER="Authorization: Bearer ${API_KEY}" THREAD_URL="${BASE_URL}/threads" THREAD_ID=`curl -s --location "${THREAD_URL}" \ --header 'OpenAI-Beta: assistants=v2' \ --header 'Content-Type: application/json' \ --header "${AUTH_HEADER}" \ --data '{}' | jq .id | tr -d '"'` # add msg to thread CREATE_MSG_DATA=$(< <(cat <<EOF { "role": "user", "content": [ { "type": "image_url", "image_url": { "url": "$IMAGE_URL" } } ] } EOF )) MSG_URL="${BASE_URL}/threads/${THREAD_ID}/messages" curl -s --location "${MSG_URL}" \ --header 'OpenAI-Beta: assistants=v2' \ --header 'Content-Type: application/json' \ --header "${AUTH_HEADER}" \ --data "${CREATE_MSG_DATA}" > /dev/null # run the assistant within thread CREATE_RUN_DATA=$(< <(cat <<EOF { "assistant_id": "$ASSISTANT_ID", "additional_instructions": "The current time is: `date '+%Y-%m-%d %H:%M:%S'`" } EOF )) RUN_URL="${BASE_URL}/threads/${THREAD_ID}/runs" RUN_ID=`curl -s --location "${RUN_URL}" \ --header 'OpenAI-Beta: assistants=v2' \ --header 'Content-Type: application/json' \ --header "${AUTH_HEADER}" \ --data "${CREATE_RUN_DATA}" | jq .id | tr -d '"'` # get run result RUN_STAUS="" while [[ $RUN_STAUS != "completed" ]] do RESP=`curl -s --location --request GET "${RUN_URL}/$RUN_ID" \ --header 'OpenAI-Beta: assistants=v2' \ --header 'Content-Type: application/json' \ --header "${AUTH_HEADER}"` RUN_STAUS=`echo $RESP| jq .status | tr -d '"'`; REQUIRED_ACTION=`echo $RESP| jq .required_action` while [[ $RUN_STAUS = "requires_action" ]] && [[ ! -z "$REQUIRED_ACTION" ]] do TOOL_OUTPUTS='[]' LEN=$( echo "$REQUIRED_ACTION" | jq '.submit_tool_outputs.tool_calls | length' ) for (( i=0; i<$LEN; i++ )) do FUNC_NAME=`echo "$REQUIRED_ACTION" | jq ".submit_tool_outputs.tool_calls[$i].function.name" | tr -d '"'` ARGS=`echo "$REQUIRED_ACTION" | jq ".submit_tool_outputs.tool_calls[$i].function.arguments"` ARGS=${ARGS//\\\"/\"} ARGS=${ARGS#"\""} ARGS=${ARGS%"\""} PLUGINAPI_URL="${BASE_URL}/pluginapi?tid=${THREAD_ID}&aid=${ASSISTANT_ID}&pid=${FUNC_NAME}" OUTPUT=`curl -s --location "${PLUGINAPI_URL}" \ --header 'OpenAI-Beta: assistants=v2' \ --header 'Content-Type: application/json' \ --header "${AUTH_HEADER}" \ --data "${ARGS}"` OUTPUT="${OUTPUT:0:8000}" OUTPUT=${OUTPUT//\"/\\\"} CALL_ID=`echo "$REQUIRED_ACTION" | jq ".submit_tool_outputs.tool_calls[$i].id" | tr -d '"'` TOOL_OUTPUT=$(< <(cat <<EOF { "tool_call_id": "$CALL_ID", "output": "$OUTPUT" } EOF )) TOOL_OUTPUTS=$(jq --argjson obj "$TOOL_OUTPUT" '. += [$obj]' <<< "$TOOL_OUTPUTS") done SUBMIT_TOOL_OUTPUT_RUN_RUL="${BASE_URL}/threads/${THREAD_ID}/runs/${RUN_ID}/submit_tool_outputs" TOOL_OUTPUTS_DATA=$(< <(cat <<EOF { "tool_outputs": $TOOL_OUTPUTS } EOF )) curl -s --location "${SUBMIT_TOOL_OUTPUT_RUN_RUL}" \ --header 'OpenAI-Beta: assistants=v2' \ --header 'Content-Type: application/json' \ --header "${AUTH_HEADER}" \ --data "${TOOL_OUTPUTS_DATA}" > /dev/null RESP=`curl -s --location --request GET "${RUN_URL}/$RUN_ID" \ --header 'OpenAI-Beta: assistants=v2' \ --header 'Content-Type: application/json' \ --header "${AUTH_HEADER}"` RUN_STAUS=`echo $RESP| jq .status | tr -d '"'`; sleep 1 done sleep 1 done #list msg RESPONSE_MSG=`curl -s --location --request GET "${MSG_URL}" \ --header 'OpenAI-Beta: assistants=v2' \ --header 'Content-Type: application/json' \ --header "${AUTH_HEADER}" | jq .data[0].content[].text.value` echo "" echo "davinci bot: "$RESPONSE_MSG即可看到結果如下
程式碼區塊 davinci bot: "response from assistant"
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