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sarvam-ai-entity-normalisation

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Dark-O-Ether commited on Feb 16

Commit

aa1c0b3

1 Parent(s): da6615b

testing (final versions) v-0.1.1

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Files changed (1) hide show

app.py +95 -22

app.py CHANGED Viewed

@@ -1,6 +1,7 @@
 import subprocess
 import json
 import streamlit as st
 import os
 import stat
 import socket
@@ -83,10 +84,6 @@ else:
             # st.write("An error occurred:")
             # st.write(e.stderr)
-end_time = time.time()
-elapsed = end_time - start_time
-print(f"Elapsed time till setup: {elapsed:.2f} seconds")
 prompt_format = \
 '''Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
@@ -107,27 +104,103 @@ Just as entities like dates, currencies, and scientific units have been normaliz
 ## Response:
 {}'''
-prompt = "हा अहवाल 30 pages लांब आणि 10 MB आकाराचा आहे."
-prompt = prompt_format.format (
-    prompt, # input
-        "", # output - leave this blank for generation!
-)
-prompt = prompt.replace('\n','\\n')
-command = \
-'''curl --request POST \
-    --url http://localhost:8081/completion \
-    --header "Content-Type: application/json" \
-    --data '{"prompt": "'''+prompt+'''", "n_predict": 256}\''''
-# print(command)
-# Display the variable on the page
-st.write("executing command ... \n")
-result = subprocess.run(command, shell=True, capture_output=True, text=True)
-output = json.loads(result.stdout)['content']
-print(output)
 # output = "hello me tasmay!"
 # time.sleep(5)
-st.write(f"Output:\n{output}")

 import subprocess
 import json
 import streamlit as st
+import streamlit.components.v1 as components
 import os
 import stat
 import socket
             # st.write("An error occurred:")
             # st.write(e.stderr)
 prompt_format = \
 '''Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
 ## Response:
 {}'''
+def infer(prompt):
+    print(f"Prompt:\n{prompt}\n")
+    # st.write(command)
+    prompt = prompt_format.format (
+        prompt, # input
+            "", # output - leave this blank for generation!
+    )
+    prompt = prompt.replace('\n','\\n')
+    command = \
+    '''curl --request POST \
+        --url http://localhost:8081/completion \
+        --header "Content-Type: application/json" \
+        --data '{"prompt": "'''+prompt+'''", "n_predict": 256}\''''
+    print("executing llm run command ... \n")
+    # st.write("executing llm run command ... \n")
+    print(f"Command:\n{command}\n")
+    # st.write(f"Command: {command}")
+    # Display the variable on the page
+    result = subprocess.run(command, shell=True, capture_output=True, text=True)
+    output = json.loads(result.stdout)['content']
+    print(f"LLM run command Output:\n{output}\n")
+    return output
+_ = infer("हा अहवाल 30 pages लांब आणि 10 MB आकाराचा आहे.")
 # output = "hello me tasmay!"
 # time.sleep(5)
+# st.write(f"Output:\n{output}")
+print("All execution is completed.")
+end_time = time.time()
+elapsed = end_time - start_time
+print(f"Elapsed time till complete setup: {elapsed:.2f} seconds")
+def main():
+    st.title("Sarvam AI - Entity Normalisation App")
+    # Use a form so that pressing Enter in the text input triggers submission.
+    with st.form(key="llm_form"):
+        user_input = st.text_input("Enter your text:")
+        submit = st.form_submit_button("Submit")
+    if submit:
+        # Display a loading spinner for 5 seconds to simulate processing delay.
+        with st.spinner('Loading output...'):
+            output_text = infer(user_input)
+        st.subheader("Output:")
+        # Show uneditable output text area.
+        st.text_area("Model generated response", output_text, height=150, key="output_area", disabled=True)
+        # Safely dump the output text as a JSON string for JS.
+        output_json = json.dumps(output_text)
+        # HTML/JavaScript code for the copy button.
+        html_code = f"""
+        <!DOCTYPE html>
+        <html>
+        <head>
+          <meta charset="UTF-8">
+          <script>
+            function copyText() {{
+                var text = {output_json};
+                navigator.clipboard.writeText(text).then(function() {{
+                    var btn = document.getElementById('copy_btn');
+                    btn.innerText = 'Copied!';
+                    setTimeout(function() {{
+                        btn.innerText = 'Copy Output';
+                    }}, 2000);
+                }}, function(err) {{
+                    console.error('Failed to copy text: ', err);
+                }});
+            }}
+          </script>
+        </head>
+        <body>
+          <button id="copy_btn" onclick="copyText()" style="
+            padding: 0.5em 1em;
+            font-size: 1em;
+            margin-top: 0.5em;
+            border: none;
+            border-radius: 4px;
+            background-color: #4CAF50;
+            color: white;
+            cursor: pointer;
+          ">
+            Copy Output
+          </button>
+        </body>
+        </html>
+        """
+        # Embed the HTML. Adjust the height as needed.
+        components.html(html_code, height=120)
+if __name__ == "__main__":
+    main()