Upload app.py

app.py

@@ -0,0 +1,57 @@
+import gradio as gr
+import json
+from langchain.chains import create_extraction_chain
+from langchain.chains import create_tagging_chain
+from langchain.chat_models import ChatOpenAI
+from langchain.prompts import ChatPromptTemplate
+from langchain.schema.output_parser import StrOutputParser
+
+
+def process_inputs(input_text, schema_prompt, radio_choice):
+    if radio_choice == "Extraction":
+        return process_extract(input_text, schema_prompt)
+    elif radio_choice == "Tagging":
+        return process_tag(input_text, schema_prompt)
+    else:
+        return process_custom(input_text, schema_prompt)
+
+
+def process_extract(input_text, schema_prompt):
+    schema_json = json.loads(schema_prompt)
+    chain = create_extraction_chain(schema_json, chat_model)
+    llm_response = chain.run(input_text)
+    pretty_json_string = json.dumps(llm_response, indent=4)
+    return pretty_json_string
+
+
+def process_tag(input_text, schema_prompt):
+    schema_json = json.loads(schema_prompt)
+    chain = create_tagging_chain(schema_json, chat_model)
+    llm_response = chain.run(input_text)
+    pretty_json_string = json.dumps(llm_response, indent=4)
+    return pretty_json_string
+
+
+def process_custom(input_text, schema_prompt):
+    prompt = ChatPromptTemplate.from_template(schema_prompt)
+    output_parser = StrOutputParser()
+    chain = prompt | chat_model | output_parser
+    invocation_dict = {"input_text": input_text}
+    llm_response = chain.invoke(invocation_dict)
+    pretty_json_string = json.dumps(json.loads(llm_response), indent=4)
+    return pretty_json_string
+
+
+chat_model = ChatOpenAI(temperature=0, model_name='gpt-3.5-turbo')
+
+with gr.Blocks() as demo:
+    input_text = gr.Textbox(label="Input Text")
+    schema_prompt = gr.Textbox(label="Schema / Prompt")
+    radio_choice = gr.Radio(["Extraction", "Tagging", "Custom Prompt"], label="Task")
+    output = gr.Textbox(label="Result")
+    analyze_btn = gr.Button("Analyze")
+    analyze_btn.click(fn=process_inputs, inputs=[input_text, schema_prompt, radio_choice], outputs=output,
+                      api_name="process_inputs")
+
+if __name__ == "__main__":
+    demo.launch(show_api=False, debug=True, share=True)