Update app.py

app.py

@@ -163,19 +163,21 @@ class Reviewer:
                     retrieval_content += f"Relevant Paper {str(cnt)}:\n"
                     retrieval_content += f"Title: {paper['title']}\n{paper['content']}\n\n"
                     formatted_citation = format_bibtex(paper, 'unsrt')
-                    retrieved_papers += f"{str(cnt)}. {formatted_citation} ({paper['url']})\n\n"
+                    retrieved_papers += f"{str(cnt)}. {formatted_citation}\n({paper['url']})\n\n"
                     cnt += 1
                 text = retrieval_content + content
-                chat_review_text = self.chat_review(text=text)  
+                chat_review_limitations = self.chat_review(text=text)  
             else:
                 text = content
-                chat_review_text = self.chat_review(text=text)   
+                chat_review_limitations = self.chat_review(text=text)   
                 retrieved_papers = "" 
         else:
             text = content
-            chat_review_text = self.chat_review(text=text)   
+            chat_review_limitations = self.chat_review(text=text)   
             retrieved_papers = ""   
 
+        text = f"Paper:\n{paper['content']}\n\n"
+        chat_review_text = self.chat_refine(text=text, limitations=chat_review_limitations)
         return chat_review_text, retrieved_papers
 
     def query_gen(self, abstract):
@@ -358,59 +360,81 @@ Organize the result in JSON format as follows:
                     {"role": "system", "content": f"Read the following scientific paper and generate {str(self.limit_num)} major limitations in this paper about its {self.aspect}. Do not include any limitation explicitly mentioned in the paper itself. Return only the limitations in the following JSON format: {{\"limitations\": <a list of limitations>"} ,
                     {"role": "user", "content": text},
                 ]
+        
+        responses = asyncio.run(
+            generate_from_openai_chat_completion(
+                client,
+                messages=[messages], 
+                engine_name=self.model_name, # gpt-3.5-turbo
+                max_tokens=1000, # 32
+                requests_per_minute = 20,
+                # response_format={"type":"json_object"},
+            )
+        )            
         try:
+            limitations = json.loads(responses[0])["limitations"][:self.limit_num]
+            result = ""
+            limit_cnt = 1
+            for limitation in limitations:
+                result += f"{str(limit_cnt)}. {limitation}\n"
+                limit_cnt += 1
+        except:
+            SYSTEM_INPUT = f"Below is an output from an LLM about several limitations of a scientific paper. Please extract the list of limitations and DO NOT make any modification to the original limitations. Return the limitations in the following JSON format: {{\"limitations\": <a list of limitations>}}. If there is no valid response inthe output, return {{\"limitations\": {{}}}}"
+            messages=[
+                {"role": "system", "content": SYSTEM_INPUT},
+                {"role": "user", "content": responses[0]},
+            ]
+            os.environ["OPENAI_BASE_URL"] = PRIVATE_API_BASE
+            os.environ["OPENAI_API_KEY"] = PRIVATE_API_KEY
+            client = AsyncOpenAI()
             responses = asyncio.run(
                 generate_from_openai_chat_completion(
                     client,
                     messages=[messages], 
-                    engine_name=self.model_name, # gpt-3.5-turbo
+                    engine_name="gpt-4o-mini", # gpt-3.5-turbo
                     max_tokens=1000, # 32
                     requests_per_minute = 20,
-                    # response_format={"type":"json_object"},
+                    response_format={"type":"json_object"},
                 )
-            )            
-            try:
-                limitations = json.loads(responses[0])["limitations"][:self.limit_num]
-                result = ""
-                limit_cnt = 1
-                for limitation in limitations:
-                    result += f"{str(limit_cnt)}. {limitation}\n"
-                    limit_cnt += 1
-            except:
-                SYSTEM_INPUT = f"Below is an output from an LLM about several limitations of a scientific paper. Please extract the list of limitations and DO NOT make any modification to the original limitations. Return the limitations in the following JSON format: {{\"limitations\": <a list of limitations>}}. If there is no valid response inthe output, return {{\"limitations\": {{}}}}"
-                messages=[
-                    {"role": "system", "content": SYSTEM_INPUT},
-                    {"role": "user", "content": responses[0]},
+            )  
+            limitations = json.loads(responses[0])["limitations"][:self.limit_num]
+                
+    
+        return limitations
+
+    def chat_refine(self, text, limitations):
+        os.environ["OPENAI_BASE_URL"] = self.api_base
+        os.environ["OPENAI_API_KEY"] = self.api
+        client = AsyncOpenAI()
+
+        messages = []
+        for limitation in limitations:
+            message=[
+                    {"role": "system", "content": f"Read the following scientific paper and a limitation of the paper. Provide a specific, actionable suggestion to address the limitation in no more than 50 words."} ,
+                    {"role": "user", "content": f"{text}\nLimitation: {limitation}"},
                 ]
-                os.environ["OPENAI_BASE_URL"] = PRIVATE_API_BASE
-                os.environ["OPENAI_API_KEY"] = PRIVATE_API_KEY
-                client = AsyncOpenAI()
-                responses = asyncio.run(
-                    generate_from_openai_chat_completion(
-                        client,
-                        messages=[messages], 
-                        engine_name="gpt-4o-mini", # gpt-3.5-turbo
-                        max_tokens=1000, # 32
-                        requests_per_minute = 20,
-                        response_format={"type":"json_object"},
-                    )
-                )  
-                limitations = json.loads(responses[0])["limitations"][:self.limit_num]
-                result = ""
-                limit_cnt = 1
-                for limitation in limitations:
-                    result += f"{str(limit_cnt)}. {limitation}\n\n"
-                    limit_cnt += 1
-            # for choice in response.choices:
-            #     result += choice.message.content 
-            # result = insert_sentence(result, '**Generated by ChatGPT, no copying allowed!**', 50)
-        except Exception as e:  
-            result = "Error: "+ str(e)
-            # usage  = 'xxxxx'
+            messages.append(message)
+
+        responses = asyncio.run(
+            generate_from_openai_chat_completion(
+                client,
+                messages=messages, 
+                engine_name=self.model_name, # gpt-3.5-turbo
+                max_tokens=1000, # 32
+                requests_per_minute = 20,
+                # response_format={"type":"json_object"},
+            )
+        )     
+
+        result = ""
+        limit_cnt = 1
+        for limitation, response in zip(limitations, responses):
+            result += f"{str(limit_cnt)}. {limitation} {response}\n\n"
+            limit_cnt += 1
         print("********"*10)
         print(result)
-        print("********"*10)      
-        return result    
+        print("********"*10)  
+        return result
 
 
     def retrieve_papers(self, title, abstract):