update demo

configs.py

@@ -1,2 +0,0 @@
-OPENAI_KEY = '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'
-DEBUG_PRINT = False

helper.py

@@ -1,6 +1,7 @@
 from utils import get_embeddings, search_document_annoy, \
     answer_with_gpt3_with_function_calls, transform_user_question, debug_print
 
+# add input parameter: need api_key for demo
 def get_response_from_model(user_input, top_k=3, annoy_metric='dot', model_name="gpt-3.5-turbo", user_query_preprocess=False):
 
     assert top_k > 0, 'k must be an integer greater than 0'
@@ -15,7 +16,9 @@ def get_response_from_model(user_input, top_k=3, annoy_metric='dot', model_name=
         user_q_embedding = get_embeddings(chatgpt_question)
         document = search_document_annoy(user_q_embedding, top_k=top_k, metric=annoy_metric)
         reply = answer_with_gpt3_with_function_calls(document, user_input, model_name)
+        print(f"returning reply: {reply}")
         return reply
     except Exception as e:
-        print(e)
-        return "Error when trying to get embedding for the user query. Please try with a shorter question."
+        print(f"returning error: {e}")
+        return e._message
+        # return "Error when trying to get embedding for the user query. Please try with a shorter question."

main.py

@@ -4,6 +4,7 @@ from typing import List
 from fastapi.responses import HTMLResponse
 from fastapi.staticfiles import StaticFiles
 from pydantic import BaseModel
+import openai
 
 from helper import get_response_from_model
 
@@ -31,15 +32,8 @@ def chat(input_data: InputData):
     user_input = input_data.user_input
     api_key = input_data.api_key
 
-    # Here you can validate the API key, e.g., check if it exists in your database
-    # If the API key is not valid, raise an HTTPException
-    # if not validate_api_key(api_key):
-    #     raise HTTPException(status_code=400, detail="Invalid API key")
-
-    # Tokenize the user input and get model's response
-    # input_ids = tokenizer.encode(user_input, return_tensors="pt")
-    # output = model.generate(input_ids)
-    # response = tokenizer.decode(output[0], skip_special_tokens=True)
+    openai.api_key = api_key
+    
     response = get_response_from_model(user_input)
 
     return {"response": response} 

model_main.py

@@ -33,8 +33,9 @@ def main(args):
             reply = answer_with_gpt3_with_function_calls(document, user_input, args.model)
             print(reply)
         except Exception as e:
-            print(e)
-            print("Error when trying to get embedding for the user query. Please try with a shorter question.")
+            print(f"error: {e}")
+            return e
+            # print("Error when trying to get embedding for the user query. Please try with a shorter question.")
 
 
 if __name__ == "__main__":

static/script.js

@@ -2,6 +2,7 @@ const sendBtn = document.getElementById('send-btn');
 const userInput = document.getElementById('user-input');
 const apiKeyInput = document.getElementById('api-key-input');
 const chatBox = document.getElementById('chat-box');
+
 const questionButtons = document.querySelectorAll('.question_btn');
 questionButtons.forEach(btn => {
     console.log(btn)
@@ -14,6 +15,7 @@ questionButtons.forEach(btn => {
 });
 
 sendBtn.addEventListener('click', () => {
+    console.log("send clicked")
     const message = userInput.value.trim();
     const apiKey = apiKeyInput.value.trim();
     console.log("message: ", message)
@@ -39,11 +41,13 @@ sendBtn.addEventListener('click', () => {
         .then(response => {
             console.log("response: ", response)
             if (!response.ok) {
+                print(response)
                 throw new Error('Network response was not ok');
             }
             return response.json();
         })
         .then(data => {
+            console.log("data: ", data)
             console.log("reply: ", data.response)
             // Display chatbot's response
             const botMessageDiv = document.createElement('div');

static/style.css

@@ -26,11 +26,12 @@ body {
 }
 
 .demo {
-    display: flex;
+    /* display: flex;
     justify-content: flex-end;
-    align-items: center;
-    width: 20%;
-    flex-direction: column;
+    align-items: center; */
+    width: 30%;
+    /* flex-direction: column; */
+    margin-right: auto;
 }
 
 button {
@@ -40,6 +41,9 @@ button {
     padding: 10px 15px;
     border-radius: 5px;
     cursor: pointer;
+    width: 100%;
+    margin: 10px;
+
 }
 
 .user-message, .bot-message {

utils.py

@@ -11,10 +11,9 @@ from tqdm import tqdm
 from annoy import AnnoyIndex
 
 from openai_function_utils.openai_function_interface import OPENAI_AVAILABLE_FUNCTIONS, OPENAI_FUNCTIONS_DEFINITIONS
-from configs import OPENAI_KEY, DEBUG_PRINT
-
-openai.api_key = OPENAI_KEY
-openai.organization = 'org-dsEkob5KeBBq3lbBLhnCXcJt'
+DEBUG_PRINT = False
+# openai.api_key = OPENAI_KEY
+# openai.organization = 'org-dsEkob5KeBBq3lbBLhnCXcJt'
 
 
 def get_embeddings(input):