Update app.py

app.py

@@ -100,14 +100,26 @@ def load_recommender(path, start_page=1):
 
 def generate_text(openAI_key, prompt, model="gpt-3.5-turbo"):
     openai.api_key = openAI_key
-    message = openai.ChatCompletion.create(
-        model=model,
-        messages=[
-            {"role": "system", "content": "You are a helpful assistant."},
-            {"role": "user", "content": prompt}
-        ]
-    )
-    return message.choices[0].message['content']
+    if model == "text-davinci-003":
+        completions = openai.Completion.create(
+            engine=model,
+            prompt=prompt,
+            max_tokens=512,
+            n=1,
+            stop=None,
+            temperature=0.7,
+        )
+        message = completions.choices[0].text
+    else:
+        message = openai.ChatCompletion.create(
+            model=model,
+            messages=[
+                {"role": "system", "content": "You are a helpful assistant."},
+                {"role": "user", "content": prompt}
+            ]
+        ).choices[0].message['content']
+    return message
+
 
 def generate_answer(question, openAI_key):
     topn_chunks = recommender(question)
@@ -129,22 +141,19 @@ def generate_answer(question, openAI_key):
     answer = generate_text(openAI_key, prompt, "gpt-3.5-turbo")
     return answer
 
-
-
-def question_answer(url, file, question,openAI_key):
+def question_answer(url, file, question, openAI_key, model):
     if openAI_key.strip()=='':
         return '[ERROR]: Please enter you Open AI Key. Get your key here : https://platform.openai.com/account/api-keys'
     if url.strip() == '' and file == None:
-        return '[ERROR]: Both URL and PDF is empty. Provide atleast one.'
+        return '[ERROR]: Both URL and PDF is empty. Provide at least one.'
     
     if url.strip() != '' and file != None:
-        return '[ERROR]: Both URL and PDF is provided. Please provide only one (eiter URL or PDF).'
+        return '[ERROR]: Both URL and PDF is provided. Please provide only one (either URL or PDF).'
 
     if url.strip() != '':
         glob_url = url
         download_pdf(glob_url, 'corpus.pdf')
         load_recommender('corpus.pdf')
-
     else:
         old_file_name = file.name
         file_name = file.name
@@ -155,7 +164,45 @@ def question_answer(url, file, question,openAI_key):
     if question.strip() == '':
         return '[ERROR]: Question field is empty'
 
-    return generate_answer(question,openAI_key)
+    if model == "text-davinci-003":
+        return generate_answer_text-davinci-003(question, openAI_key)
+    else:
+        return generate_answer(question, openAI_key, model)
+
+
+def generate_text_text_davinci_003(openAI_key,prompt, engine="text-davinci-003"):
+    openai.api_key = openAI_key
+    completions = openai.Completion.create(
+        engine=engine,
+        prompt=prompt,
+        max_tokens=512,
+        n=1,
+        stop=None,
+        temperature=0.7,
+    )
+    message = completions.choices[0].text
+    return message
+
+
+def generate_answer_text_davinci_003(question,openAI_key):
+    topn_chunks = recommender(question)
+    prompt = ""
+    prompt += 'search results:\n\n'
+    for c in topn_chunks:
+        prompt += c + '\n\n'
+        
+    prompt += "Instructions: Compose a comprehensive reply to the query using the search results given. "\
+              "Cite each reference using [ Page Number] notation (every result has this number at the beginning). "\
+              "Citation should be done at the end of each sentence. If the search results mention multiple subjects "\
+              "with the same name, create separate answers for each. Only include information found in the results and "\
+              "don't add any additional information. Make sure the answer is correct and don't output false content. "\
+              "If the text does not relate to the query, simply state 'Found Nothing'. Ignore outlier "\
+              "search results which has nothing to do with the question. Only answer what is asked. The "\
+              "answer should be short and concise. \n\nQuery: {question}\nAnswer: "
+    
+    prompt += f"Query: {question}\nAnswer:"
+    answer = generate_text(openAI_key, prompt,"text-davinci-003")
+    return answer
 
 
 recommender = SemanticSearch()
@@ -178,13 +225,15 @@ with gr.Blocks() as demo:
             gr.Markdown("<center><h4>OR<h4></center>")
             file = gr.File(label='Upload your PDF/ Research Paper / Book here', file_types=['.pdf'])
             question = gr.Textbox(label='Enter your question here')
+            model = gr.Radio(['gpt-3.5-turbo', 'gpt-3.5-turbo-16k', 'gpt-3.5-turbo-0613', 'gpt-3.5-turbo-16k-0613', 'text-davinci-003'], label='Select Model', default='gpt-3.5-turbo')
             btn = gr.Button(value='Submit')
             btn.style(full_width=True)
 
         with gr.Group():
             answer = gr.Textbox(label='The answer to your question is :')
 
-        btn.click(question_answer, inputs=[url, file, question,openAI_key], outputs=[answer])
+        #btn.click(question_answer, inputs=[url, file, question,openAI_key], outputs=[answer])
+        btn.click(question_answer, inputs=[url, file, question, openAI_key, model], outputs=[answer])
 #openai.api_key = os.getenv('Your_Key_Here') 
 demo.launch()