Update app.py

app.py

@@ -7,36 +7,47 @@ import time
 anyscale_base_url = "https://api.endpoints.anyscale.com/v1"
 multilingual_embeddings = embedding_functions.SentenceTransformerEmbeddingFunction(model_name="jost/multilingual-e5-base-politics-de")
 
-def predict(api_key, user_input):
-    client = chromadb.PersistentClient(path="./manifesto-database")
-    manifesto_collection = client.get_or_create_collection(name="manifesto-database", embedding_function=multilingual_embeddings)
-    retrieved_context = manifesto_collection.query(query_texts=[user_input], n_results=3, where={"ideology": "Authoritarian-right"})
-    contexts = [context for context in retrieved_context['documents']]
-    print(contexts[0])
+def predict(api_key, user_input, model1, model2):
+    # client = chromadb.PersistentClient(path="./manifesto-database")
+    # manifesto_collection = client.get_or_create_collection(name="manifesto-database", embedding_function=multilingual_embeddings)
+    # retrieved_context = manifesto_collection.query(query_texts=[user_input], n_results=3, where={"ideology": "Authoritarian-right"})
+    # contexts = [context for context in retrieved_context['documents']]
+    # print(contexts[0])
     
     prompt = f"""[INST] {user_input} [/INST]"""
     
     client = OpenAI(base_url=anyscale_base_url, api_key=api_key)
-    completion = client.completions.create(
-        model="mistralai/Mixtral-8x7B-Instruct-v0.1",
+    
+    response1 = client.completions.create(
+        model=model1,
         prompt=prompt,
         temperature=0.7,
-        max_tokens=1000)
+        max_tokens=1000).choices[0].text
     
-    response = completion.choices[0].text
-    return response
+    response2 = client.completions.create(
+        model=model2,
+        prompt=prompt,
+        temperature=0.7,
+        max_tokens=1000).choices[0].text
 
+    return response1, response2
+
+    
 def main():
     description = "This is a simple interface to interact with OpenAI’s Chat Completion API. Please enter your API key and your message."
     with gr.Blocks() as demo:
         with gr.Row():
             api_key_input = gr.Textbox(label="API Key", placeholder="Enter your API key here", show_label=True, type="password")
             user_input = gr.Textbox(label="Your Message", placeholder="Enter your message here")
+            model_selector1 = gr.Dropdown(label="Model 1", choices=["mistralai/Mixtral-8x7B-Instruct-v0.1", "mistralai/Mixtral-8x22B-Instruct-v0.1"])
+            model_selector2 = gr.Dropdown(label="Model 2", choices=["mistralai/Mixtral-8x7B-Instruct-v0.1", "mistralai/Mixtral-8x22B-Instruct-v0.1"])
             submit_btn = gr.Button("Submit")
             
-        output = gr.Textbox(label="LLM Response")
+        output1 = gr.Textbox(label="Model 1 Response")
+        output2 = gr.Textbox(label="Model 2 Response")
+        
         
-        submit_btn.click(fn=predict, inputs=[api_key_input, user_input], outputs=output)
+        submit_btn.click(fn=predict, inputs=[api_key_input, user_input, model_selector1, model_selector2], outputs=[output1, output2])
 
     demo.launch()