upgrade to claude 2.0

app.py

@@ -3,7 +3,7 @@ import os
 import re
 import tarfile
 
-import anthropic
+from anthropic import AI_PROMPT, HUMAN_PROMPT, Anthropic
 import gradio as gr
 import requests
 
@@ -83,7 +83,7 @@ def download_arxiv_source(paper_id):
 
 
 class ContextualQA:
-    def __init__(self, client, model="claude-v1.3-100k"):
+    def __init__(self, client, model="claude-2.0"):
         self.client = client
         self.model = model
         self.context = ""
@@ -94,20 +94,21 @@ class ContextualQA:
         self.context = text
 
     def ask_question(self, question):
-        leading_prompt = "Here is the content of a paper:"
-        trailing_prompt = "Now, answer the following question below. You can optionally use Markdown to format your answer."
-        prompt = f"{anthropic.HUMAN_PROMPT} {leading_prompt}\n\n{self.context}\n\n{trailing_prompt}\n\n{anthropic.HUMAN_PROMPT} {question}\n\n{anthropic.AI_PROMPT}"
-        response = self.client.completion_stream(
+        leading_prompt = "Give the following paper:"
+        trailing_prompt = "Now, answer the following question based on the content of the paper above. You can optionally use Markdown to format your answer or LaTeX typesetting to improve the presentation of your answer."
+      
+        prompt = f"{HUMAN_PROMPT} {leading_prompt} {self.context} {trailing_prompt} {HUMAN_PROMPT} {question} {AI_PROMPT}"
+        response = self.client.completions.create(
             prompt=prompt,
-            stop_sequences=[anthropic.HUMAN_PROMPT],
+            stop_sequences=[HUMAN_PROMPT],
             max_tokens_to_sample=6000,
             model=self.model,
             stream=False,
         )
-        responses = [data for data in response]
+        answer = response.completion
         self.questions.append(question)
-        self.responses.append(responses)
-        return responses
+        self.responses.append(answer)
+        return answer
 
     def clear_context(self):
         self.context = ""
@@ -130,9 +131,9 @@ def load_context(paper_id):
     except Exception as e:
         return None, [(f"Error loading paper with id {paper_id}.", str(e))]
 
-    client = anthropic.Client(api_key=os.environ["ANTHROPIC_API_KEY"])
-    model = ContextualQA(client, model="claude-v1.3-100k")
-    model.load_text(latex_source)
+    client = Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"])
+    qa_model = ContextualQA(client, model="claude-2.0")
+    qa_model.load_text(latex_source)
 
     # Usage
     title, abstract = get_paper_info(paper_id)
@@ -141,7 +142,7 @@ def load_context(paper_id):
     abstract = replace_texttt(abstract)
 
     return (
-        model,
+        qa_model,
         [
             (
                 f"Load the paper with id {paper_id}.",
@@ -151,23 +152,23 @@ def load_context(paper_id):
     )
 
 
-def answer_fn(model, question, chat_history):
+def answer_fn(qa_model, question, chat_history):
     # if question is empty, tell user that they need to ask a question
     if question == "":
         chat_history.append(("No Question Asked", "Please ask a question."))
-        return model, chat_history, ""
+        return qa_model, chat_history, ""
 
-    client = anthropic.Client(api_key=os.environ["ANTHROPIC_API_KEY"])
-    model.client = client
+    client = Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"])
+    qa_model.client = client
 
     try:
-        response = model.ask_question(question)
+        answer = qa_model.ask_question(question)
     except Exception as e:
         chat_history.append(("Error Asking Question", str(e)))
-        return model, chat_history, ""
+        return qa_model, chat_history, ""
 
-    chat_history.append((question, response[0]["completion"]))
-    return model, chat_history, ""
+    chat_history.append((question, answer))
+    return qa_model, chat_history, ""
 
 
 def clear_context():
@@ -176,10 +177,10 @@ def clear_context():
 
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
     gr.Markdown(
-        "# Explore ArXiv Papers in Depth with `claude-v1.3-100k` - Ask Questions and Receive Detailed Answers Instantly"
+        "# Explore ArXiv Papers in Depth with `claude-2.0` - Ask Questions and Receive Detailed Answers Instantly"
     )
     gr.Markdown(
-        "Dive into the world of academic papers with our dynamic app, powered by the cutting-edge `claude-v1.3-100k` model. This app allows you to ask detailed questions about any ArXiv paper and receive direct answers from the paper's content. Utilizing a context length of 100k tokens, it provides an efficient and comprehensive exploration of complex research studies, making knowledge acquisition simpler and more interactive. (This text is generated by GPT-4 )"
+        "Dive into the world of academic papers with our dynamic app, powered by the cutting-edge `claude-2.0` model. This app allows you to ask detailed questions about any ArXiv paper and receive direct answers from the paper's content. Utilizing a context length of 100k tokens, it provides an efficient and comprehensive exploration of complex research studies, making knowledge acquisition simpler and more interactive. (This text is generated by GPT-4 )"
     )
 
     gr.HTML(

requirements.txt

@@ -5,4 +5,5 @@ pandas
 seaborn
 tqdm
 numpy
-arxiv
+arxiv
+tiktoken