mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-10-01 01:26:03 -04:00
Support for sending images into OpenAI chat API (#4827)
This commit is contained in:
parent
8956f3ebe2
commit
dbe438564e
@ -67,8 +67,56 @@ This extension uses the following parameters (from `settings.json`):
|
|||||||
|
|
||||||
## Usage through API
|
## Usage through API
|
||||||
|
|
||||||
|
### Chat completions endpoint
|
||||||
|
|
||||||
|
#### With an image URL
|
||||||
|
|
||||||
|
```shell
|
||||||
|
curl http://127.0.0.1:5000/v1/chat/completions \
|
||||||
|
-H "Content-Type: application/json" \
|
||||||
|
-d '{
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"image_url": "https://avatars.githubusercontent.com/u/112222186?v=4"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "What is unusual about this image?"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}'
|
||||||
|
```
|
||||||
|
|
||||||
|
#### With a Base64 image
|
||||||
|
|
||||||
|
```python
|
||||||
|
import base64
|
||||||
|
import json
|
||||||
|
import requests
|
||||||
|
|
||||||
|
img = open('image.jpg', 'rb')
|
||||||
|
img_bytes = img.read()
|
||||||
|
img_base64 = base64.b64encode(img_bytes).decode('utf-8')
|
||||||
|
data = { "messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"image_url": f"data:image/jpeg;base64,{img_base64}"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "what is unusual about this image?"
|
||||||
|
}
|
||||||
|
]
|
||||||
|
}
|
||||||
|
response = requests.post('http://127.0.0.1:5000/v1/chat/completions', json=data)
|
||||||
|
print(response.text)
|
||||||
|
```
|
||||||
|
|
||||||
You can run the multimodal inference through API, by inputting the images to prompt. Images are embedded like so: `f'<img src="data:image/jpeg;base64,{img_str}">'`, where `img_str` is base-64 jpeg data. Note that you will need to launch `server.py` with the arguments `--api --extensions multimodal`.
|
You can run the multimodal inference through API, by inputting the images to prompt. Images are embedded like so: `f'<img src="data:image/jpeg;base64,{img_str}">'`, where `img_str` is base-64 jpeg data. Note that you will need to launch `server.py` with the arguments `--api --extensions multimodal`.
|
||||||
|
|
||||||
|
### Completions endpoint
|
||||||
|
|
||||||
Python example:
|
Python example:
|
||||||
|
|
||||||
```Python
|
```Python
|
||||||
|
@ -1,10 +1,15 @@
|
|||||||
|
import base64
|
||||||
import copy
|
import copy
|
||||||
|
import re
|
||||||
import time
|
import time
|
||||||
from collections import deque
|
from collections import deque
|
||||||
|
from io import BytesIO
|
||||||
|
|
||||||
|
import requests
|
||||||
import tiktoken
|
import tiktoken
|
||||||
import torch
|
import torch
|
||||||
import torch.nn.functional as F
|
import torch.nn.functional as F
|
||||||
|
from PIL import Image
|
||||||
from transformers import LogitsProcessor, LogitsProcessorList
|
from transformers import LogitsProcessor, LogitsProcessorList
|
||||||
|
|
||||||
from extensions.openai.errors import InvalidRequestError
|
from extensions.openai.errors import InvalidRequestError
|
||||||
@ -140,7 +145,25 @@ def convert_history(history):
|
|||||||
system_message = ""
|
system_message = ""
|
||||||
|
|
||||||
for entry in history:
|
for entry in history:
|
||||||
content = entry["content"]
|
if "image_url" in entry:
|
||||||
|
image_url = entry['image_url']
|
||||||
|
if "base64" in image_url:
|
||||||
|
image_url = re.sub('^data:image/.+;base64,', '', image_url)
|
||||||
|
img = Image.open(BytesIO(base64.b64decode(image_url)))
|
||||||
|
else:
|
||||||
|
try:
|
||||||
|
my_res = requests.get(image_url)
|
||||||
|
img = Image.open(BytesIO(my_res.content))
|
||||||
|
except Exception:
|
||||||
|
raise 'Image cannot be loaded from the URL!'
|
||||||
|
|
||||||
|
buffered = BytesIO()
|
||||||
|
img.save(buffered, format="JPEG")
|
||||||
|
img_str = base64.b64encode(buffered.getvalue()).decode('utf-8')
|
||||||
|
content = f'<img src="data:image/jpeg;base64,{img_str}">'
|
||||||
|
else:
|
||||||
|
content = entry["content"]
|
||||||
|
|
||||||
role = entry["role"]
|
role = entry["role"]
|
||||||
|
|
||||||
if role == "user":
|
if role == "user":
|
||||||
@ -182,7 +205,8 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False) -
|
|||||||
raise InvalidRequestError(message="messages: missing role", param='messages')
|
raise InvalidRequestError(message="messages: missing role", param='messages')
|
||||||
elif m['role'] == 'function':
|
elif m['role'] == 'function':
|
||||||
raise InvalidRequestError(message="role: function is not supported.", param='messages')
|
raise InvalidRequestError(message="role: function is not supported.", param='messages')
|
||||||
if 'content' not in m:
|
|
||||||
|
if 'content' not in m and "image_url" not in m:
|
||||||
raise InvalidRequestError(message="messages: missing content", param='messages')
|
raise InvalidRequestError(message="messages: missing content", param='messages')
|
||||||
|
|
||||||
# Chat Completions
|
# Chat Completions
|
||||||
|
Loading…
Reference in New Issue
Block a user