diff --git a/conf/llm_factories.json b/conf/llm_factories.json
index fdc3f37a9..046436bda 100644
--- a/conf/llm_factories.json
+++ b/conf/llm_factories.json
@@ -3169,34 +3169,28 @@
"status": "1",
"llm": [
{
- "llm_name": "claude-3-5-sonnet-20240620",
- "tags": "LLM,CHAT,200k",
+ "llm_name": "claude-3-7-sonnet-20250219",
+ "tags": "LLM,IMAGE2TEXT,200k",
"max_tokens": 204800,
- "model_type": "chat"
+ "model_type": "image2text"
},
{
"llm_name": "claude-3-5-sonnet-20241022",
- "tags": "LLM,CHAT,200k",
+ "tags": "LLM,IMAGE2TEXT,200k",
"max_tokens": 204800,
"model_type": "chat"
},
{
"llm_name": "claude-3-opus-20240229",
- "tags": "LLM,CHAT,200k",
- "max_tokens": 204800,
- "model_type": "chat"
- },
- {
- "llm_name": "claude-3-sonnet-20240229",
- "tags": "LLM,CHAT,200k",
+ "tags": "LLM,IMAGE2TEXT,200k",
"max_tokens": 204800,
"model_type": "chat"
},
{
"llm_name": "claude-3-haiku-20240307",
- "tags": "LLM,CHAT,200k",
+ "tags": "LLM,IMAGE2TEXT,200k",
"max_tokens": 204800,
- "model_type": "chat"
+ "model_type": "image2text"
},
{
"llm_name": "claude-2.1",
@@ -3209,12 +3203,6 @@
"tags": "LLM,CHAT,100k",
"max_tokens": 102400,
"model_type": "chat"
- },
- {
- "llm_name": "claude-3-5-sonnet-20241022",
- "tags": "LLM,CHAT,200k",
- "max_tokens": 102400,
- "model_type": "chat"
}
]
},
diff --git a/rag/llm/__init__.py b/rag/llm/__init__.py
index 649599f10..c7790a986 100644
--- a/rag/llm/__init__.py
+++ b/rag/llm/__init__.py
@@ -106,6 +106,7 @@ from .cv_model import (
TogetherAICV,
YiCV,
HunyuanCV,
+ AnthropicCV
)
from .rerank_model import (
@@ -198,6 +199,7 @@ CvModel = {
"TogetherAI": TogetherAICV,
"01.AI": YiCV,
"Tencent Hunyuan": HunyuanCV,
+ "Anthropic": AnthropicCV,
}
ChatModel = {
diff --git a/rag/llm/chat_model.py b/rag/llm/chat_model.py
index a4dcf2db3..ebcce26a7 100644
--- a/rag/llm/chat_model.py
+++ b/rag/llm/chat_model.py
@@ -1443,6 +1443,9 @@ class AnthropicChat(Base):
del gen_conf["presence_penalty"]
if "frequency_penalty" in gen_conf:
del gen_conf["frequency_penalty"]
+ gen_conf["max_tokens"] = 8196
+ if "haiku" in self.model_name or "opus" in self.model_name:
+ gen_conf["max_tokens"] = 4096
ans = ""
try:
@@ -1474,6 +1477,9 @@ class AnthropicChat(Base):
del gen_conf["presence_penalty"]
if "frequency_penalty" in gen_conf:
del gen_conf["frequency_penalty"]
+ gen_conf["max_tokens"] = 8196
+ if "haiku" in self.model_name or "opus" in self.model_name:
+ gen_conf["max_tokens"] = 4096
ans = ""
total_tokens = 0
@@ -1481,15 +1487,21 @@ class AnthropicChat(Base):
response = self.client.messages.create(
model=self.model_name,
messages=history,
- system=self.system,
+ system=system,
stream=True,
**gen_conf,
)
for res in response:
if res.type == 'content_block_delta':
- text = res.delta.text
- ans += text
- total_tokens += num_tokens_from_string(text)
+ if res.delta.type == "thinking_delta" and res.delta.thinking:
+ if ans.find("") < 0:
+ ans += ""
+ ans = ans.replace("", "")
+ ans += res.delta.thinking + ""
+ else:
+ text = res.delta.text
+ ans += text
+ total_tokens += num_tokens_from_string(text)
yield ans
except Exception as e:
yield ans + "\n**ERROR**: " + str(e)
diff --git a/rag/llm/cv_model.py b/rag/llm/cv_model.py
index da52e75ba..50b7d1a39 100644
--- a/rag/llm/cv_model.py
+++ b/rag/llm/cv_model.py
@@ -31,6 +31,7 @@ from api.utils import get_uuid
from api.utils.file_utils import get_project_base_directory
from rag.nlp import is_english
from rag.prompts import vision_llm_describe_prompt
+from rag.utils import num_tokens_from_string
class Base(ABC):
@@ -899,3 +900,125 @@ class HunyuanCV(Base):
],
}
]
+
+
+class AnthropicCV(Base):
+ def __init__(self, key, model_name, base_url=None):
+ import anthropic
+
+ self.client = anthropic.Anthropic(api_key=key)
+ self.model_name = model_name
+ self.system = ""
+ self.max_tokens = 8192
+ if "haiku" in self.model_name or "opus" in self.model_name:
+ self.max_tokens = 4096
+
+ def prompt(self, b64, prompt):
+ return [
+ {
+ "role": "user",
+ "content": [
+ {
+ "type": "image",
+ "source": {
+ "type": "base64",
+ "media_type": "image/jpeg",
+ "data": b64,
+ },
+ },
+ {
+ "type": "text",
+ "text": prompt
+ }
+ ],
+ }
+ ]
+
+ def describe(self, image):
+ b64 = self.image2base64(image)
+ prompt = self.prompt(b64,
+ "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
+ "Please describe the content of this picture, like where, when, who, what happen. If it has number data, please extract them out."
+ )
+
+ response = self.client.messages.create(
+ model=self.model_name,
+ max_tokens=self.max_tokens,
+ messages=prompt
+ )
+ return response["content"][0]["text"].strip(), response["usage"]["input_tokens"]+response["usage"]["output_tokens"]
+
+ def describe_with_prompt(self, image, prompt=None):
+ b64 = self.image2base64(image)
+ prompt = self.prompt(b64, prompt if prompt else vision_llm_describe_prompt())
+
+ response = self.client.messages.create(
+ model=self.model_name,
+ max_tokens=self.max_tokens,
+ messages=prompt
+ )
+ return response["content"][0]["text"].strip(), response["usage"]["input_tokens"]+response["usage"]["output_tokens"]
+
+ def chat(self, system, history, gen_conf):
+ if "presence_penalty" in gen_conf:
+ del gen_conf["presence_penalty"]
+ if "frequency_penalty" in gen_conf:
+ del gen_conf["frequency_penalty"]
+ gen_conf["max_tokens"] = self.max_tokens
+
+ ans = ""
+ try:
+ response = self.client.messages.create(
+ model=self.model_name,
+ messages=history,
+ system=system,
+ stream=False,
+ **gen_conf,
+ ).to_dict()
+ ans = response["content"][0]["text"]
+ if response["stop_reason"] == "max_tokens":
+ ans += (
+ "...\nFor the content length reason, it stopped, continue?"
+ if is_english([ans])
+ else "······\n由于长度的原因，回答被截断了，要继续吗？"
+ )
+ return (
+ ans,
+ response["usage"]["input_tokens"] + response["usage"]["output_tokens"],
+ )
+ except Exception as e:
+ return ans + "\n**ERROR**: " + str(e), 0
+
+ def chat_streamly(self, system, history, gen_conf):
+ if "presence_penalty" in gen_conf:
+ del gen_conf["presence_penalty"]
+ if "frequency_penalty" in gen_conf:
+ del gen_conf["frequency_penalty"]
+ gen_conf["max_tokens"] = self.max_tokens
+
+ ans = ""
+ total_tokens = 0
+ try:
+ response = self.client.messages.create(
+ model=self.model_name,
+ messages=history,
+ system=system,
+ stream=True,
+ **gen_conf,
+ )
+ for res in response:
+ if res.type == 'content_block_delta':
+ if res.delta.type == "thinking_delta" and res.delta.thinking:
+ if ans.find("") < 0:
+ ans += ""
+ ans = ans.replace("", "")
+ ans += res.delta.thinking + ""
+ else:
+ text = res.delta.text
+ ans += text
+ total_tokens += num_tokens_from_string(text)
+ yield ans
+ except Exception as e:
+ yield ans + "\n**ERROR**: " + str(e)
+
+ yield total_tokens
\ No newline at end of file