tutorial88

tutorial88/main.py

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+import streamlit as st
+from PIL import Image
+import base64
+from langchain_openai import ChatOpenAI
+from langchain.schema.messages import HumanMessage,AIMessage
+
+llm=ChatOpenAI(model="gpt-4o")
+
+
+def encode_image(upload_file):
+    image_bytes=upload_file.getvalue()
+    base64_image=base64.b64encode(image_bytes).decode("utf-8")
+    return base64_image
+
+
+def gen_response(base64_image,input):
+    response=llm.invoke(
+        [
+            AIMessage(
+                content="you are an useful & intelligent bot who is very good at image reading related ocr tassks to get insights from images uploaded by user"
+            ),
+            HumanMessage(
+                content=[
+                    {"type":"text","text":input},
+                    {"type":"image_url",
+                     "image_url":{
+                         "url":"data:image/jpg;base64,"+base64_image,
+                         "detail":"auto"
+                     }
+                     }
+                ]
+            )
+        ]
+
+    )
+    return response.content
+
+def main():
+    st.title("OBJECT DETECTION & ANALYSIS APP")
+    upload_file=st.file_uploader("upload your image here",type=["jpg"])
+    if upload_file is not None:
+        image=Image.open(upload_file)
+        st.image(image,caption="your image",use_column_width=True)
+        st.success("image uploaded successfully")
+        base64_image=encode_image(upload_file)
+        input=st.text_area("ask your question here")
+        btn=st.button("submit")
+        if btn:
+            response=gen_response(base64_image,input)
+            st.write(response)
+
+
+
+if __name__=="__main__":
+    main()