Move to streamlit

README.md

@@ -3,9 +3,10 @@ title: LLM ADE Dev
 emoji: 🔥
 colorFrom: pink
 colorTo: red
-sdk: docker
+sdk_version: 1.33.0
+app_file: app.py
 pinned: false
-license: unknown
+license: apache-2.0
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,42 @@
+import streamlit as st
+from vllm import LLM, SamplingParams
+
+llm = LLM(model="InvestmentResearchAI/LLM-ADE-small-v0.1.0")
+tok = llm.get_tokenizer()
+tok.eos_token = '<|eot_id|>' # Override to use turns
+
+
+template = """<|begin_of_text|><|start_header_id|>system<|end_header_id|>
+
+You are a helpful financial assistant that answers the user as accurately, truthfully, and concisely as possible.<|eot_id|><|start_header_id|>user<|end_header_id|>
+
+{user_message}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
+
+"""
+
+
+def get_response(prompt):
+    try:
+        prompts = [template.format(user_message=prompt)]
+        sampling_params = SamplingParams(temperature=0.3, top_p=0.95)
+        outputs = llm.generate(prompts, sampling_params)
+        for output in outputs:
+            return output.outputs[0].text
+    except Exception as e:
+        return f"An error occurred: {str(e)}"
+
+def main():
+    st.title("LLM-ADE 9B Demo")
+    
+    input_text = st.text_area("Enter your text here:", value="", height=200)
+    if st.button("Generate"):
+        if input_text:
+            with st.spinner('Generating response...'):
+                response_text = get_response(input_text)
+                st.write(response_text)
+        else:
+            st.warning("Please enter some text to generate a response.")
+
+if __name__ == "__main__":
+    main()
+

requirements.txt

@@ -0,0 +1,5 @@
+streamlit
+transformers
+torch
+vllm
+