Update app.py

Errors handled in Solve(). FlatLatex gone.

app.py

@@ -1,6 +1,6 @@
 import os
 import gradio as gr
-# import openai
+import openai
 from numpy._core.defchararray import endswith, isdecimal
 from openai import OpenAI
 from dotenv import load_dotenv
@@ -17,8 +17,6 @@ from PIL import Image
 from io import BytesIO
 from pydantic import BaseModel
 import pprint
-import flatlatex
-lconv = flatlatex.converter()
 
 load_dotenv(override=True)
 key = os.getenv('OPENAI_API_KEY')
@@ -45,6 +43,8 @@ client = OpenAI(api_key = key)
 
 abbrevs = {'St. ' : 'Saint ', 'Mr. ': 'mister ', 'Mrs. ':'mussus ', 'Mr. ':'mister ', 'Ms. ':'mizz '}
 
+special_chat_types = ['math', 'logic']
+
 class Step(BaseModel):
     explanation: str
     output: str
@@ -55,19 +55,40 @@ class MathReasoning(BaseModel):
     
 
 def solve(prompt, chatType):
+    tokens_in = 0
+    tokens_out = 0
+    tokens = 0
     if chatType == 'math':
         instruction = "You are a helpful math tutor. Guide the user through the solution step by step."
     elif chatType == "logic":
-        instruction = "you are a helpful tutor expert in logic.  Guide the user through the solution step by step"
-    completion = client.beta.chat.completions.parse(
-        model = 'gpt-4o-2024-08-06',
-        messages = [
-            {"role": "system", "content": instruction},
-            {"role": "user", "content": prompt}
-        ],
-        response_format=MathReasoning,
-    )
-    return completion
+        instruction = "you are an expert in logic and reasoning.  Guide the user through the solution step by step"
+    try:
+        completion = client.beta.chat.completions.parse(
+            model = 'gpt-4o-2024-08-06',
+            messages = [
+                {"role": "system", "content": instruction},
+                {"role": "user", "content": prompt}
+            ],
+            response_format=MathReasoning,
+            max_tokens = 2000
+        )
+
+        tokens_in = completion.usage.prompt_tokens
+        tokens_out = completion.usage.completion_tokens
+        tokens = completion.usage.total_tokens
+        msg = completion.choices[0].message 
+        if msg.parsed:
+            dr = msg.parsed.model_dump()
+            response = pprint.pformat(dr)
+        elif msg.refusal:
+            response = msg.refusal
+
+    except Exception as e:
+        if type(e) == openai.LengthFinishReasonError:
+            response = 'Too many tokens' 
+        else:
+            response = str(e)
+    return (response, tokens_in, tokens_out, tokens)
 
 def genUsageStats(do_reset=False):
     result = []
@@ -199,22 +220,23 @@ def updatePassword(txt):
     password = txt.lower().strip()
     return [password, "*********"]
 
-def parse_math(txt):
-    ref = 0
-    loc = txt.find(r'\\(')
-    if loc == -1:
-        return txt
-    while (True):
-        loc2 = txt[ref:].find(r'\\)')
-        if loc2 == -1:
-            break
-        loc = txt[ref:].find(r'\\(')
-        if loc > -1:
-            loc2 += 2
-            frag = lconv.convert(txt[ref:][loc:loc2])
-            txt = txt[:loc+ref] + frag + txt[loc2+ref:]
-            ref = len(txt[ref:loc]) + len(frag)
-    return txt
+# def parse_math(txt):
+#     ref = 0
+#     loc = txt.find(r'\(')
+#     if loc == -1:
+#         return txt
+#     while (True):
+#         loc2 = txt[ref:].find(r'\)')
+#         if loc2 == -1:
+#             break
+#         loc = txt[ref:].find(r'\(')
+#         if loc > -1:
+#             loc2 += 2
+#             slice = txt[ref:][loc:loc2]
+#             frag = lconv.convert(slice)
+#             txt = txt[:loc+ref] + frag + txt[loc2+ref:]
+#             ref = len(txt[ref:loc]) + len(frag)
+#     return txt
 
 def chat(prompt, user_window, pwd_window, past, response, gptModel, uploaded_image_file=''):
     image_gen_model = 'gpt-4o-2024-08-06'
@@ -251,8 +273,8 @@ def chat(prompt, user_window, pwd_window, past, response, gptModel, uploaded_ima
             prompt = prompt[6:]
         past.append({"role":"user", "content":prompt})
         gen_image = (uploaded_image_file != '')
-        if chatType in ['math', 'logic']:
-           completion = solve(prompt, chatType)
+        if chatType in special_chat_types:
+           (reply, tokens_in, tokens_out, tokens) = solve(prompt, chatType)
            reporting_model = image_gen_model
         elif not gen_image:
             completion = client.chat.completions.create(model=gptModel,
@@ -264,20 +286,11 @@ def chat(prompt, user_window, pwd_window, past, response, gptModel, uploaded_ima
             reporting_model = image_gen_model
             if not msg == 'ok':
                 return [past, msg, None, gptModel, uploaded_image_file]
-        if chatType in ['math', 'logic']:
-            dr = completion.choices[0].message.parsed.model_dump()
-            reply = pprint.pformat(dr)
-            # df = {'final_answer' : parse_math(dr['final_answer'])}
-            # df['steps'] = []
-            # for x in dr['steps']:
-            #     df['steps'].append({'explanation': parse_math(x['explanation']), 'output' : parse_math(x['output'])})
-
-            # reply = pprint.pformat(df)
-        else:
+        if not chatType in special_chat_types:
             reply = completion.choices[0].message.content
-        tokens_in = completion.usage.prompt_tokens
-        tokens_out = completion.usage.completion_tokens
-        tokens = completion.usage.total_tokens
+            tokens_in = completion.usage.prompt_tokens
+            tokens_out = completion.usage.completion_tokens
+            tokens = completion.usage.total_tokens
         response += "\n\nYOU: " + prompt + "\nGPT: " + reply
         if isBoss:
             response += f"\n{reporting_model}: tokens in/out = {tokens_in}/{tokens_out}"