Update app.py

app.py

@@ -1,69 +1,22 @@
-from langchain.agents import load_tools
-from langchain.agents import initialize_agent
-from langchain.agents import AgentType
-from langchain.chat_models import AzureChatOpenAI
-from langchain.llms import OpenAI
-from langchain.chains.conversation.memory import ConversationBufferWindowMemory
+# -*- coding: utf-8 -*-
 
-import os
 
-
-OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
-OPENAI_API_BASE = os.getenv("OPENAI_API_BASE")
-#llm = ChatOpenAI(openai_api_key=OPENAI_API_KEY, temperature=0, model_name='gpt-3.5-turbo',openai_api_base=OPENAI_API_BASE)
-llm = AzureChatOpenAI(deployment_name="bitservice_chat_35",openai_api_base=OPENAI_API_BASE,openai_api_key=OPENAI_API_KEY,openai_api_version="2023-03-15-preview",model_name="gpt-3.5-turbo")
-
-
-import torch
-from transformers import BlipProcessor, BlipForConditionalGeneration
-
-image_to_text_model = "Salesforce/blip-image-captioning-large"
-device = 'cuda' if torch.cuda.is_available() else 'cpu'
-
-processor = BlipProcessor.from_pretrained(image_to_text_model)
-model = BlipForConditionalGeneration.from_pretrained(image_to_text_model).to(device)
-
-from transformers.models.oneformer.modeling_oneformer import OneFormerModelOutput
-import requests
-from PIL import Image
-
-def describeImage(image_url):
-  image_object = Image.open(requests.get(image_url, stream=True).raw).convert('RGB')
-  # image
-  inputs = processor(image_object, return_tensors="pt").to(device)
-  outputs = model.generate(**inputs)
-  return processor.decode(outputs[0], skip_special_tokens=True)
-
-
-from langchain.tools import BaseTool
-
-class DescribeImageTool(BaseTool):
-    name = "Describe Image Tool"
-    description = 'use this tool to describe an image.'
-
-    def _run(self, url: str):
-        description = describeImage(url)
-        return description
+import gradio as gr
+import langChain_test
+ 
+def image_to_text(image_path,question):
+    return langChain_test.imageAnalyse(image_path,question)
     
-    def _arun(self, query: str):
-        raise NotImplementedError("Async operation not supported yet")
-
-tools = [DescribeImageTool()]
+ 
+with gr.Blocks() as demo:
+    image_path = gr.Image(type="filepath",label="请选择一张图片")
+    question = gr.Textbox(label="输入您的问题",lines=2)
+    output = gr.Textbox(label="输出答案",lines=2,placeholder="提交后将自动输出答案")
+    greet_btn = gr.Button("提交",variant="primary")
+    greet_btn.click(fn=image_to_text, inputs=[image_path,question], outputs=output, api_name="image_to_text")
 
 
-agent = initialize_agent(
-    agent='chat-conversational-react-description',
-    tools=tools,
-    llm=llm,
-    verbose=True,
-    max_iterations=3,
-    early_stopping_method='generate',
-    memory=ConversationBufferWindowMemory(
-        memory_key='chat_history',
-        k=5,
-        return_messages=True
-    )
-)
 
-image_url = 'https://images.unsplash.com/photo-1682228287072-5e23cbffd487?ixlib=rb-4.0.3&ixid=MnwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8&auto=format&fit=crop&w=987&q=80'
-agent(f"Please describe the following image:\n{image_url}")
+demo.launch() 
+ 
+#demo.launch(share=True)