From 8ecc12ee2af7c79b5dbe6f43d1ffc05fa900c8f3 Mon Sep 17 00:00:00 2001 From: hiyouga Date: Fri, 1 Nov 2024 07:25:20 +0000 Subject: [PATCH 1/2] support multiimage inference Former-commit-id: e80a4819274d46ac9e85db7469dc59d7c4e323c7 --- src/llamafactory/api/chat.py | 17 ++++---- src/llamafactory/chat/base_engine.py | 8 ++-- src/llamafactory/chat/chat_model.py | 24 +++++------ src/llamafactory/chat/hf_engine.py | 64 ++++++++++++++++++---------- src/llamafactory/chat/vllm_engine.py | 36 +++++++++------- src/llamafactory/data/mm_plugin.py | 8 ++++ src/llamafactory/webui/chatter.py | 9 +++- 7 files changed, 103 insertions(+), 63 deletions(-) diff --git a/src/llamafactory/api/chat.py b/src/llamafactory/api/chat.py index f20e588e..ec3201c3 100644 --- a/src/llamafactory/api/chat.py +++ b/src/llamafactory/api/chat.py @@ -69,7 +69,7 @@ ROLE_MAPPING = { def _process_request( request: "ChatCompletionRequest", -) -> Tuple[List[Dict[str, str]], Optional[str], Optional[str], Optional["ImageInput"]]: +) -> Tuple[List[Dict[str, str]], Optional[str], Optional[str], Optional[List["ImageInput"]]]: logger.info(f"==== request ====\n{json.dumps(dictify(request), indent=2, ensure_ascii=False)}") if len(request.messages) == 0: @@ -84,7 +84,7 @@ def _process_request( raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Only supports u/a/u/a/u...") input_messages = [] - image = None + images = [] for i, message in enumerate(request.messages): if i % 2 == 0 and message.role not in [Role.USER, Role.TOOL]: raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Invalid role") @@ -111,10 +111,11 @@ def _process_request( else: # web uri image_stream = requests.get(image_url, stream=True).raw - image = Image.open(image_stream).convert("RGB") + images.append(Image.open(image_stream).convert("RGB")) else: input_messages.append({"role": ROLE_MAPPING[message.role], "content": message.content}) + images = None if len(images) == 0 else images tool_list = request.tools if isinstance(tool_list, list) and len(tool_list): try: @@ -124,7 +125,7 @@ def _process_request( else: tools = None - return input_messages, system, tools, image + return input_messages, system, tools, images def _create_stream_chat_completion_chunk( @@ -143,12 +144,12 @@ async def create_chat_completion_response( request: "ChatCompletionRequest", chat_model: "ChatModel" ) -> "ChatCompletionResponse": completion_id = f"chatcmpl-{uuid.uuid4().hex}" - input_messages, system, tools, image = _process_request(request) + input_messages, system, tools, images = _process_request(request) responses = await chat_model.achat( input_messages, system, tools, - image, + images, do_sample=request.do_sample, temperature=request.temperature, top_p=request.top_p, @@ -194,7 +195,7 @@ async def create_stream_chat_completion_response( request: "ChatCompletionRequest", chat_model: "ChatModel" ) -> AsyncGenerator[str, None]: completion_id = f"chatcmpl-{uuid.uuid4().hex}" - input_messages, system, tools, image = _process_request(request) + input_messages, system, tools, images = _process_request(request) if tools: raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="Cannot stream function calls.") @@ -208,7 +209,7 @@ async def create_stream_chat_completion_response( input_messages, system, tools, - image, + images, do_sample=request.do_sample, temperature=request.temperature, top_p=request.top_p, diff --git a/src/llamafactory/chat/base_engine.py b/src/llamafactory/chat/base_engine.py index 7087c4e5..700e1eef 100644 --- a/src/llamafactory/chat/base_engine.py +++ b/src/llamafactory/chat/base_engine.py @@ -66,8 +66,8 @@ class BaseEngine(ABC): messages: Sequence[Dict[str, str]], system: Optional[str] = None, tools: Optional[str] = None, - image: Optional["ImageInput"] = None, - video: Optional["VideoInput"] = None, + images: Optional[Sequence["ImageInput"]] = None, + videos: Optional[Sequence["VideoInput"]] = None, **input_kwargs, ) -> List["Response"]: r""" @@ -81,8 +81,8 @@ class BaseEngine(ABC): messages: Sequence[Dict[str, str]], system: Optional[str] = None, tools: Optional[str] = None, - image: Optional["ImageInput"] = None, - video: Optional["VideoInput"] = None, + images: Optional[Sequence["ImageInput"]] = None, + videos: Optional[Sequence["VideoInput"]] = None, **input_kwargs, ) -> AsyncGenerator[str, None]: r""" diff --git a/src/llamafactory/chat/chat_model.py b/src/llamafactory/chat/chat_model.py index 4f0e1b83..28f5e439 100644 --- a/src/llamafactory/chat/chat_model.py +++ b/src/llamafactory/chat/chat_model.py @@ -64,15 +64,15 @@ class ChatModel: messages: Sequence[Dict[str, str]], system: Optional[str] = None, tools: Optional[str] = None, - image: Optional["ImageInput"] = None, - video: Optional["VideoInput"] = None, + images: Optional[Sequence["ImageInput"]] = None, + videos: Optional[Sequence["VideoInput"]] = None, **input_kwargs, ) -> List["Response"]: r""" Gets a list of responses of the chat model. """ task = asyncio.run_coroutine_threadsafe( - self.achat(messages, system, tools, image, video, **input_kwargs), self._loop + self.achat(messages, system, tools, images, videos, **input_kwargs), self._loop ) return task.result() @@ -81,28 +81,28 @@ class ChatModel: messages: Sequence[Dict[str, str]], system: Optional[str] = None, tools: Optional[str] = None, - image: Optional["ImageInput"] = None, - video: Optional["VideoInput"] = None, + images: Optional[Sequence["ImageInput"]] = None, + videos: Optional[Sequence["VideoInput"]] = None, **input_kwargs, ) -> List["Response"]: r""" Asynchronously gets a list of responses of the chat model. """ - return await self.engine.chat(messages, system, tools, image, video, **input_kwargs) + return await self.engine.chat(messages, system, tools, images, videos, **input_kwargs) def stream_chat( self, messages: Sequence[Dict[str, str]], system: Optional[str] = None, tools: Optional[str] = None, - image: Optional["ImageInput"] = None, - video: Optional["VideoInput"] = None, + images: Optional[Sequence["ImageInput"]] = None, + videos: Optional[Sequence["VideoInput"]] = None, **input_kwargs, ) -> Generator[str, None, None]: r""" Gets the response token-by-token of the chat model. """ - generator = self.astream_chat(messages, system, tools, image, video, **input_kwargs) + generator = self.astream_chat(messages, system, tools, images, videos, **input_kwargs) while True: try: task = asyncio.run_coroutine_threadsafe(generator.__anext__(), self._loop) @@ -115,14 +115,14 @@ class ChatModel: messages: Sequence[Dict[str, str]], system: Optional[str] = None, tools: Optional[str] = None, - image: Optional["ImageInput"] = None, - video: Optional["VideoInput"] = None, + images: Optional[Sequence["ImageInput"]] = None, + videos: Optional[Sequence["VideoInput"]] = None, **input_kwargs, ) -> AsyncGenerator[str, None]: r""" Asynchronously gets the response token-by-token of the chat model. """ - async for new_token in self.engine.stream_chat(messages, system, tools, image, video, **input_kwargs): + async for new_token in self.engine.stream_chat(messages, system, tools, images, videos, **input_kwargs): yield new_token def get_scores( diff --git a/src/llamafactory/chat/hf_engine.py b/src/llamafactory/chat/hf_engine.py index 909f8161..5340587c 100644 --- a/src/llamafactory/chat/hf_engine.py +++ b/src/llamafactory/chat/hf_engine.py @@ -79,20 +79,20 @@ class HuggingfaceEngine(BaseEngine): messages: Sequence[Dict[str, str]], system: Optional[str] = None, tools: Optional[str] = None, - image: Optional["ImageInput"] = None, - video: Optional["VideoInput"] = None, + images: Optional[Sequence["ImageInput"]] = None, + videos: Optional[Sequence["VideoInput"]] = None, input_kwargs: Optional[Dict[str, Any]] = {}, ) -> Tuple[Dict[str, Any], int]: mm_input_dict = {"images": [], "videos": [], "imglens": [0], "vidlens": [0]} - if image is not None: - mm_input_dict.update({"images": [image], "imglens": [1]}) + if images is not None: + mm_input_dict.update({"images": images, "imglens": [len(images)]}) if IMAGE_PLACEHOLDER not in messages[0]["content"]: - messages[0]["content"] = IMAGE_PLACEHOLDER + messages[0]["content"] + messages[0]["content"] = IMAGE_PLACEHOLDER * len(images) + messages[0]["content"] - if video is not None: - mm_input_dict.update({"videos": [video], "vidlens": [1]}) + if videos is not None: + mm_input_dict.update({"videos": videos, "vidlens": [len(videos)]}) if VIDEO_PLACEHOLDER not in messages[0]["content"]: - messages[0]["content"] = VIDEO_PLACEHOLDER + messages[0]["content"] + messages[0]["content"] = VIDEO_PLACEHOLDER * len(videos) + messages[0]["content"] messages = template.mm_plugin.process_messages( messages, mm_input_dict["images"], mm_input_dict["videos"], processor @@ -186,12 +186,22 @@ class HuggingfaceEngine(BaseEngine): messages: Sequence[Dict[str, str]], system: Optional[str] = None, tools: Optional[str] = None, - image: Optional["ImageInput"] = None, - video: Optional["VideoInput"] = None, + images: Optional[Sequence["ImageInput"]] = None, + videos: Optional[Sequence["VideoInput"]] = None, input_kwargs: Optional[Dict[str, Any]] = {}, ) -> List["Response"]: gen_kwargs, prompt_length = HuggingfaceEngine._process_args( - model, tokenizer, processor, template, generating_args, messages, system, tools, image, video, input_kwargs + model, + tokenizer, + processor, + template, + generating_args, + messages, + system, + tools, + images, + videos, + input_kwargs, ) generate_output = model.generate(**gen_kwargs) response_ids = generate_output[:, prompt_length:] @@ -222,12 +232,22 @@ class HuggingfaceEngine(BaseEngine): messages: Sequence[Dict[str, str]], system: Optional[str] = None, tools: Optional[str] = None, - image: Optional["ImageInput"] = None, - video: Optional["VideoInput"] = None, + images: Optional[Sequence["ImageInput"]] = None, + videos: Optional[Sequence["VideoInput"]] = None, input_kwargs: Optional[Dict[str, Any]] = {}, ) -> Callable[[], str]: gen_kwargs, _ = HuggingfaceEngine._process_args( - model, tokenizer, processor, template, generating_args, messages, system, tools, image, video, input_kwargs + model, + tokenizer, + processor, + template, + generating_args, + messages, + system, + tools, + images, + videos, + input_kwargs, ) streamer = TextIteratorStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True) gen_kwargs["streamer"] = streamer @@ -270,8 +290,8 @@ class HuggingfaceEngine(BaseEngine): messages: Sequence[Dict[str, str]], system: Optional[str] = None, tools: Optional[str] = None, - image: Optional["ImageInput"] = None, - video: Optional["VideoInput"] = None, + images: Optional[Sequence["ImageInput"]] = None, + videos: Optional[Sequence["VideoInput"]] = None, **input_kwargs, ) -> List["Response"]: if not self.can_generate: @@ -287,8 +307,8 @@ class HuggingfaceEngine(BaseEngine): messages, system, tools, - image, - video, + images, + videos, input_kwargs, ) async with self.semaphore: @@ -301,8 +321,8 @@ class HuggingfaceEngine(BaseEngine): messages: Sequence[Dict[str, str]], system: Optional[str] = None, tools: Optional[str] = None, - image: Optional["ImageInput"] = None, - video: Optional["VideoInput"] = None, + images: Optional[Sequence["ImageInput"]] = None, + videos: Optional[Sequence["VideoInput"]] = None, **input_kwargs, ) -> AsyncGenerator[str, None]: if not self.can_generate: @@ -318,8 +338,8 @@ class HuggingfaceEngine(BaseEngine): messages, system, tools, - image, - video, + images, + videos, input_kwargs, ) async with self.semaphore: diff --git a/src/llamafactory/chat/vllm_engine.py b/src/llamafactory/chat/vllm_engine.py index 2b5a32b4..e228aba4 100644 --- a/src/llamafactory/chat/vllm_engine.py +++ b/src/llamafactory/chat/vllm_engine.py @@ -101,14 +101,14 @@ class VllmEngine(BaseEngine): messages: Sequence[Dict[str, str]], system: Optional[str] = None, tools: Optional[str] = None, - image: Optional["ImageInput"] = None, - video: Optional["VideoInput"] = None, + images: Optional[Sequence["ImageInput"]] = None, + videos: Optional[Sequence["VideoInput"]] = None, **input_kwargs, ) -> AsyncIterator["RequestOutput"]: request_id = f"chatcmpl-{uuid.uuid4().hex}" - if image is not None: + if images is not None: if IMAGE_PLACEHOLDER not in messages[0]["content"]: - messages[0]["content"] = IMAGE_PLACEHOLDER + messages[0]["content"] + messages[0]["content"] = IMAGE_PLACEHOLDER * len(images) + messages[0]["content"] paired_messages = messages + [{"role": "assistant", "content": ""}] system = system or self.generating_args["default_system"] @@ -157,14 +157,18 @@ class VllmEngine(BaseEngine): skip_special_tokens=True, ) - if image is not None: # add image features - if not isinstance(image, (str, ImageObject)): - raise ValueError(f"Expected image input is a path or PIL.Image, but got {type(image)}.") + if images is not None: # add image features + image_data = [] + for image in images: + if not isinstance(image, (str, ImageObject)): + raise ValueError(f"Expected image input is a path or PIL.Image, but got {type(image)}.") - if isinstance(image, str): - image = Image.open(image).convert("RGB") + if isinstance(image, str): + image = Image.open(image).convert("RGB") - multi_modal_data = {"image": image} + image_data.append(image) + + multi_modal_data = {"image": image_data} else: multi_modal_data = None @@ -182,12 +186,12 @@ class VllmEngine(BaseEngine): messages: Sequence[Dict[str, str]], system: Optional[str] = None, tools: Optional[str] = None, - image: Optional["ImageInput"] = None, - video: Optional["VideoInput"] = None, + images: Optional[Sequence["ImageInput"]] = None, + videos: Optional[Sequence["VideoInput"]] = None, **input_kwargs, ) -> List["Response"]: final_output = None - generator = await self._generate(messages, system, tools, image, video, **input_kwargs) + generator = await self._generate(messages, system, tools, images, videos, **input_kwargs) async for request_output in generator: final_output = request_output @@ -210,12 +214,12 @@ class VllmEngine(BaseEngine): messages: Sequence[Dict[str, str]], system: Optional[str] = None, tools: Optional[str] = None, - image: Optional["ImageInput"] = None, - video: Optional["VideoInput"] = None, + images: Optional[Sequence["ImageInput"]] = None, + videos: Optional[Sequence["VideoInput"]] = None, **input_kwargs, ) -> AsyncGenerator[str, None]: generated_text = "" - generator = await self._generate(messages, system, tools, image, video, **input_kwargs) + generator = await self._generate(messages, system, tools, images, videos, **input_kwargs) async for result in generator: delta_text = result.outputs[0].text[len(generated_text) :] generated_text = result.outputs[0].text diff --git a/src/llamafactory/data/mm_plugin.py b/src/llamafactory/data/mm_plugin.py index 4e096c83..f6748883 100644 --- a/src/llamafactory/data/mm_plugin.py +++ b/src/llamafactory/data/mm_plugin.py @@ -226,6 +226,14 @@ class BasePlugin: ) -> Dict[str, Union[List[int], "torch.Tensor"]]: r""" Builds batched multimodal inputs for VLMs. + + Arguments: + images: a list of image inputs, shape (num_images,) + videos: a list of video inputs, shape (num_videos,) + imglens: number of images in each sample, shape (batch_size,) + vidlens: number of videos in each sample, shape (batch_size,) + seqlens: number of tokens in each sample, shape (batch_size,) + processor: a processor for pre-processing images and videos """ self._validate_input(images, videos) return {} diff --git a/src/llamafactory/webui/chatter.py b/src/llamafactory/webui/chatter.py index 7512887b..78ef3efc 100644 --- a/src/llamafactory/webui/chatter.py +++ b/src/llamafactory/webui/chatter.py @@ -141,7 +141,14 @@ class WebChatModel(ChatModel): chatbot[-1][1] = "" response = "" for new_text in self.stream_chat( - messages, system, tools, image, video, max_new_tokens=max_new_tokens, top_p=top_p, temperature=temperature + messages, + system, + tools, + images=[image], + videos=[video], + max_new_tokens=max_new_tokens, + top_p=top_p, + temperature=temperature, ): response += new_text if tools: From 2eba98e152ff3ce5f8709612e235fb3801bab3cf Mon Sep 17 00:00:00 2001 From: hiyouga Date: Fri, 1 Nov 2024 08:41:54 +0000 Subject: [PATCH 2/2] add examples Former-commit-id: e824b715ad4bf885241b245b12d75563adab2e26 --- .github/CONTRIBUTING.md | 46 ++++++++++++++++++++ .pre-commit-config.yaml | 2 +- README.md | 2 + README_zh.md | 2 + scripts/test_image.py | 65 ++++++++++++++++++++++++++++ src/llamafactory/chat/hf_engine.py | 4 +- src/llamafactory/chat/vllm_engine.py | 2 +- 7 files changed, 119 insertions(+), 4 deletions(-) create mode 100644 scripts/test_image.py diff --git a/.github/CONTRIBUTING.md b/.github/CONTRIBUTING.md index 2e495068..507d666a 100644 --- a/.github/CONTRIBUTING.md +++ b/.github/CONTRIBUTING.md @@ -19,3 +19,49 @@ There are several ways you can contribute to LLaMA Factory: ### Style guide LLaMA Factory follows the [Google Python Style Guide](https://google.github.io/styleguide/pyguide.html), check it for details. + +### Create a Pull Request + +1. Fork the [repository](https://github.com/hiyouga/LLaMA-Factory) by clicking on the [Fork](https://github.com/hiyouga/LLaMA-Factory/fork) button on the repository's page. This creates a copy of the code under your GitHub user account. + +2. Clone your fork to your local disk, and add the base repository as a remote: + +```bash +git clone git@github.com:[username]/LLaMA-Factory.git +cd LLaMA-Factory +git remote add upstream https://github.com/hiyouga/LLaMA-Factory.git +``` + +3. Create a new branch to hold your development changes: + +```bash +git checkout -b dev_your_branch +``` + +4. Set up a development environment by running the following command in a virtual environment: + +```bash +pip install -e ".[dev]" +``` + +If LLaMA Factory was already installed in the virtual environment, remove it with `pip uninstall llamafactory` before reinstalling it in editable mode with the -e flag. + +5. Check code before commit: + +```bash +make commit +make style && make quality +make test +``` + +6. Submit changes: + +```bash +git add . +git commit -m "commit message" +git fetch upstream +git rebase upstream/main +git push -u origin dev_your_branch +``` + +7. Create a merge request from your branch `dev_your_branch` at [origin repo](https://github.com/hiyouga/LLaMA-Factory). diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index b439253c..cbe361ee 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -12,7 +12,7 @@ repos: - id: trailing-whitespace args: [--markdown-linebreak-ext=md] - id: no-commit-to-branch - args: ['--branch', 'master'] + args: ['--branch', 'main'] - repo: https://github.com/asottile/pyupgrade rev: v3.17.0 diff --git a/README.md b/README.md index a5e4ad48..cb67180c 100644 --- a/README.md +++ b/README.md @@ -584,6 +584,8 @@ API_PORT=8000 llamafactory-cli api examples/inference/llama3_vllm.yaml > [!TIP] > Visit [this page](https://platform.openai.com/docs/api-reference/chat/create) for API document. +> +> Examples: [Image understanding](scripts/test_image.py) | [Function calling](scripts/test_toolcall.py) ### Download from ModelScope Hub diff --git a/README_zh.md b/README_zh.md index 9f6f12a4..1d6596f2 100644 --- a/README_zh.md +++ b/README_zh.md @@ -585,6 +585,8 @@ API_PORT=8000 llamafactory-cli api examples/inference/llama3_vllm.yaml > [!TIP] > API 文档请查阅[这里](https://platform.openai.com/docs/api-reference/chat/create)。 +> +> 示例：[图像理解](scripts/test_image.py) | [工具调用](scripts/test_toolcall.py) ### 从魔搭社区下载 diff --git a/scripts/test_image.py b/scripts/test_image.py new file mode 100644 index 00000000..34a937e5 --- /dev/null +++ b/scripts/test_image.py @@ -0,0 +1,65 @@ +# Copyright 2024 the LlamaFactory team. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +import os + +from openai import OpenAI +from transformers.utils.versions import require_version + + +require_version("openai>=1.5.0", "To fix: pip install openai>=1.5.0") + + +def main(): + client = OpenAI( + api_key="{}".format(os.environ.get("API_KEY", "0")), + base_url="http://localhost:{}/v1".format(os.environ.get("API_PORT", 8000)), + ) + messages = [] + messages.append( + { + "role": "user", + "content": [ + {"type": "text", "text": "Output the color and number of each box."}, + { + "type": "image_url", + "image_url": {"url": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2-VL/boxes.png"}, + }, + ], + } + ) + result = client.chat.completions.create(messages=messages, model="test") + messages.append(result.choices[0].message) + print("Round 1:", result.choices[0].message.content) + # The image shows a pyramid of colored blocks with numbers on them. Here are the colors and numbers of ... + messages.append( + { + "role": "user", + "content": [ + {"type": "text", "text": "What kind of flower is this?"}, + { + "type": "image_url", + "image_url": {"url": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2-VL/flowers.jpg"}, + }, + ], + } + ) + result = client.chat.completions.create(messages=messages, model="test") + messages.append(result.choices[0].message) + print("Round 2:", result.choices[0].message.content) + # The image shows a cluster of forget-me-not flowers. Forget-me-nots are small ... + + +if __name__ == "__main__": + main() diff --git a/src/llamafactory/chat/hf_engine.py b/src/llamafactory/chat/hf_engine.py index 5340587c..258d9c82 100644 --- a/src/llamafactory/chat/hf_engine.py +++ b/src/llamafactory/chat/hf_engine.py @@ -86,12 +86,12 @@ class HuggingfaceEngine(BaseEngine): mm_input_dict = {"images": [], "videos": [], "imglens": [0], "vidlens": [0]} if images is not None: mm_input_dict.update({"images": images, "imglens": [len(images)]}) - if IMAGE_PLACEHOLDER not in messages[0]["content"]: + if not any(IMAGE_PLACEHOLDER not in message["content"] for message in messages): messages[0]["content"] = IMAGE_PLACEHOLDER * len(images) + messages[0]["content"] if videos is not None: mm_input_dict.update({"videos": videos, "vidlens": [len(videos)]}) - if VIDEO_PLACEHOLDER not in messages[0]["content"]: + if not any(VIDEO_PLACEHOLDER not in message["content"] for message in messages): messages[0]["content"] = VIDEO_PLACEHOLDER * len(videos) + messages[0]["content"] messages = template.mm_plugin.process_messages( diff --git a/src/llamafactory/chat/vllm_engine.py b/src/llamafactory/chat/vllm_engine.py index e228aba4..e122cc13 100644 --- a/src/llamafactory/chat/vllm_engine.py +++ b/src/llamafactory/chat/vllm_engine.py @@ -107,7 +107,7 @@ class VllmEngine(BaseEngine): ) -> AsyncIterator["RequestOutput"]: request_id = f"chatcmpl-{uuid.uuid4().hex}" if images is not None: - if IMAGE_PLACEHOLDER not in messages[0]["content"]: + if not any(IMAGE_PLACEHOLDER not in message["content"] for message in messages): messages[0]["content"] = IMAGE_PLACEHOLDER * len(images) + messages[0]["content"] paired_messages = messages + [{"role": "assistant", "content": ""}]