update app with chatgpt

app.py

@@ -72,7 +72,6 @@ system_template = {
 
 # if file key.key exist read the key if note read the env variable OPENAI_TOKEN
 if os.path.isfile("key.key"):
-
     # read key.key file and set openai api key
     with open("key.key", "r") as f:
         key = f.read()
@@ -198,15 +197,17 @@ def chat(
     Yields:
         tuple: chat gradio format, chat openai format, sources used.
     """
-    reformulated_query = openai.Completion.create(
-        model="text-davinci-002",
-        prompt=get_reformulation_prompt(query),
-        temperature=0,
-        max_tokens=128,
+    reformulated_query = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=[
+            {"role": "system", "content": "You are a helpful assistant."},
+            {"role": "user", "content": get_reformulation_prompt(query)},
+        ],
         stop=["\n---\n", "<|im_end|>"],
     )
+    
 
-    reformulated_query = reformulated_query["choices"][0]["text"]
+    reformulated_query = reformulated_query["choices"][0]["message"]["content"]
     language = "francais"
 
     sources = retrieve_with_summaries(
@@ -235,14 +236,24 @@ def chat(
         )
         messages.append(
             {
-                "role": "system",
-                "content": f"{sources_prompt}\n\n{docs_string}\n\nAnswer in {language}:",
+                "role": "user",
+                "content": f"{sources_prompt}\n\n{docs_string}\n\Réponds en {language}:",
             }
         )
 
-        response = openai.Completion.create(
-            model="text-davinci-002",
-            prompt=to_completion(messages),
+        # quick message preprocessing
+        def cleaning_message(message):
+            if isinstance(message["content"], tuple):
+                message["content"] = "\n".join(message["content"])
+
+            return message
+            
+        messages = [cleaning_message(message) for message in messages]
+        
+
+        response = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo-16k",
+            messages=messages,
             temperature=0,  # deterministic
             stream=True,
             max_tokens=1024,
@@ -256,13 +267,14 @@ def chat(
         file = user_id[0] + timestamp + ".json"
 
         for chunk in response:
-            if (
-                chunk_message := chunk["choices"][0].get("text")
-            ) and chunk_message != "<|im_end|>":
-                complete_response += chunk_message
-                messages[-1]["content"] = complete_response
-                gradio_format = make_pairs([a["content"] for a in messages[1:]])
-                yield gradio_format, messages, docs_html
+            if "content" in chunk["choices"][0]["delta"]:
+                if (
+                    chunk_message := chunk["choices"][0]["delta"]["content"]
+                ) and chunk_message != "<|im_end|>":
+                    complete_response += chunk_message
+                    messages[-1]["content"] = complete_response
+                    gradio_format = make_pairs([a["content"] for a in messages[1:]])
+                    yield gradio_format, messages, docs_html
 
     else:
         docs_string = "Pas d'élements juridique trouvé dans les codes de loi"
@@ -330,8 +342,6 @@ with gr.Blocks(title="LoiLibre Q&A", css="style.css", theme=theme) as demo:
         with gr.Column(scale=1, variant="panel"):
             gr.Markdown("### Sources")
             sources_textbox = gr.Markdown(show_label=False)
-            
-        
 
     ask.submit(
         fn=chat,
@@ -354,11 +364,13 @@ with gr.Blocks(title="LoiLibre Q&A", css="style.css", theme=theme) as demo:
                 Version 0.1-beta - This tool is under active development
                 
                 </div>
-                """)
+                """
+            )
             gr.Markdown(
                 """
                 
-                """)
+                """
+            )
 
     demo.queue(concurrency_count=16)