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Refa: remove max toekns for image2txt models. (#6078)
### What problem does this PR solve? #6063 ### Type of change - [x] Refactoring
This commit is contained in:
Kevin Hu
GitHub
parent
42eb99554f
commit
56b228f187
@ -49,7 +49,6 @@ class Base(ABC):
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response = self.client.chat.completions.create(
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model=self.model_name,
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messages=history,
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max_tokens=gen_conf.get("max_tokens", 1000),
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temperature=gen_conf.get("temperature", 0.3),
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top_p=gen_conf.get("top_p", 0.7)
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)
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@ -71,7 +70,6 @@ class Base(ABC):
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response = self.client.chat.completions.create(
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model=self.model_name,
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messages=history,
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max_tokens=gen_conf.get("max_tokens", 1000),
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temperature=gen_conf.get("temperature", 0.3),
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top_p=gen_conf.get("top_p", 0.7),
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stream=True
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@ -157,8 +155,7 @@ class GptV4(Base):
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res = self.client.chat.completions.create(
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model=self.model_name,
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messages=prompt,
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max_tokens=max_tokens,
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messages=prompt
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)
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return res.choices[0].message.content.strip(), res.usage.total_tokens
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@ -181,8 +178,7 @@ class AzureGptV4(Base):
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res = self.client.chat.completions.create(
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model=self.model_name,
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messages=prompt,
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max_tokens=max_tokens,
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messages=prompt
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)
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return res.choices[0].message.content.strip(), res.usage.total_tokens
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@ -241,7 +237,6 @@ class QWenCV(Base):
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if his["role"] == "user":
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his["content"] = self.chat_prompt(his["content"], image)
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response = MultiModalConversation.call(model=self.model_name, messages=history,
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max_tokens=gen_conf.get("max_tokens", 1000),
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temperature=gen_conf.get("temperature", 0.3),
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top_p=gen_conf.get("top_p", 0.7))
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@ -271,7 +266,6 @@ class QWenCV(Base):
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tk_count = 0
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try:
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response = MultiModalConversation.call(model=self.model_name, messages=history,
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max_tokens=gen_conf.get("max_tokens", 1000),
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temperature=gen_conf.get("temperature", 0.3),
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top_p=gen_conf.get("top_p", 0.7),
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stream=True)
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@ -306,8 +300,7 @@ class Zhipu4V(Base):
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res = self.client.chat.completions.create(
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model=self.model_name,
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messages=prompt,
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max_tokens=max_tokens,
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messages=prompt
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)
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return res.choices[0].message.content.strip(), res.usage.total_tokens
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@ -322,7 +315,6 @@ class Zhipu4V(Base):
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response = self.client.chat.completions.create(
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model=self.model_name,
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messages=history,
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max_tokens=gen_conf.get("max_tokens", 1000),
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temperature=gen_conf.get("temperature", 0.3),
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top_p=gen_conf.get("top_p", 0.7)
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)
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@ -344,7 +336,6 @@ class Zhipu4V(Base):
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response = self.client.chat.completions.create(
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model=self.model_name,
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messages=history,
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max_tokens=gen_conf.get("max_tokens", 1000),
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temperature=gen_conf.get("temperature", 0.3),
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top_p=gen_conf.get("top_p", 0.7),
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stream=True
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@ -376,12 +367,10 @@ class OllamaCV(Base):
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def describe(self, image, max_tokens=1024):
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prompt = self.prompt("")
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try:
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options = {"num_predict": max_tokens}
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response = self.client.generate(
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model=self.model_name,
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prompt=prompt[0]["content"][1]["text"],
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images=[image],
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options=options
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images=[image]
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)
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ans = response["response"].strip()
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return ans, 128
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@ -399,8 +388,6 @@ class OllamaCV(Base):
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options = {}
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if "temperature" in gen_conf:
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options["temperature"] = gen_conf["temperature"]
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if "max_tokens" in gen_conf:
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options["num_predict"] = gen_conf["max_tokens"]
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if "top_p" in gen_conf:
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options["top_k"] = gen_conf["top_p"]
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if "presence_penalty" in gen_conf:
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@ -429,8 +416,6 @@ class OllamaCV(Base):
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options = {}
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if "temperature" in gen_conf:
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options["temperature"] = gen_conf["temperature"]
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if "max_tokens" in gen_conf:
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options["num_predict"] = gen_conf["max_tokens"]
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if "top_p" in gen_conf:
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options["top_k"] = gen_conf["top_p"]
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if "presence_penalty" in gen_conf:
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@ -480,8 +465,7 @@ class XinferenceCV(Base):
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res = self.client.chat.completions.create(
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model=self.model_name,
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messages=self.prompt(b64),
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max_tokens=max_tokens,
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messages=self.prompt(b64)
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)
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return res.choices[0].message.content.strip(), res.usage.total_tokens
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@ -497,15 +481,13 @@ class GeminiCV(Base):
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def describe(self, image, max_tokens=2048):
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from PIL.Image import open
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gen_config = {'max_output_tokens':max_tokens}
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prompt = "请用中文详细描述一下图中的内容，比如时间，地点，人物，事情，人物心情等，如果有数据请提取出数据。" if self.lang.lower() == "chinese" else \
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"Please describe the content of this picture, like where, when, who, what happen. If it has number data, please extract them out."
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b64 = self.image2base64(image)
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img = open(BytesIO(base64.b64decode(b64)))
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input = [prompt,img]
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res = self.model.generate_content(
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input,
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generation_config=gen_config,
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input
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)
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return res.text,res.usage_metadata.total_token_count
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@ -525,7 +507,7 @@ class GeminiCV(Base):
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history[-1]["parts"].append("data:image/jpeg;base64," + image)
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response = self.model.generate_content(history, generation_config=GenerationConfig(
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max_output_tokens=gen_conf.get("max_tokens", 1000), temperature=gen_conf.get("temperature", 0.3),
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temperature=gen_conf.get("temperature", 0.3),
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top_p=gen_conf.get("top_p", 0.7)))
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ans = response.text
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@ -551,7 +533,7 @@ class GeminiCV(Base):
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history[-1]["parts"].append("data:image/jpeg;base64," + image)
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response = self.model.generate_content(history, generation_config=GenerationConfig(
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max_output_tokens=gen_conf.get("max_tokens", 1000), temperature=gen_conf.get("temperature", 0.3),
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temperature=gen_conf.get("temperature", 0.3),
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top_p=gen_conf.get("top_p", 0.7)), stream=True)
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for resp in response:
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@ -618,8 +600,7 @@ class NvidiaCV(Base):
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"Authorization": f"Bearer {self.key}",
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},
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json={
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"messages": self.prompt(b64),
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"max_tokens": max_tokens,
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"messages": self.prompt(b64)
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},
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)
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response = response.json()
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