Integrate GPT4

app.py

@@ -1,4 +1,148 @@
 import streamlit as st
+from langchain.memory.chat_message_histories import StreamlitChatMessageHistory
+from typing import Any, List, Mapping, Optional
+from langchain.llms.base import LLM
+from langchain.callbacks.manager import CallbackManagerForLLMRun
+import langchain
+import asyncio
+from playwright.async_api import async_playwright
+import time
+import regex
+import html2text
+import os
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+
+global CurrentAgent
+CurrentAgent = 'Structured Zero Short Agent'
+
+
+class GPTRemote(LLM):
+    n: int
+
+    @property
+    def _llm_type(self) -> str:
+        return "custom"
+    
+    def _call(
+            self, 
+            prompt: str, 
+            stop: Optional [List[str]] = None, 
+            run_manager: Optional[CallbackManagerForLLMRun] = None, 
+            **kwargs: Any
+            ) -> str:
+        print("prompt:", prompt)
+        
+        output = asyncio.run(start_playwright(prompt))
+
+        if output is None:
+            output = "No Feedback"
+        print("-" * 20)
+        print('Raw: \n', output)
+        keywords = ['Action:', 'Action Input:', 'Observation:', 'Thought:', 'Final Answer:']
+        if 'Action:' in output and 'Observation:' in output:
+            output = output.split('Observation:')[0]
+
+        global CurrentAgent
+
+        if CurrentAgent == 'Structured Zero Short Agent':
+            try:
+
+                if output.strip()[-1] == '}' and 'Action:' in output:
+                    print("valid command")
+                elif 'Action:' in output:
+                    output = output + '}'
+                    print("corrected command")
+
+                pattern = r'\{((?:[^{}]|(?R))*)\}'
+                temp = regex.search(pattern, output)
+                rrr = temp.group()
+                output = output.replace(rrr, '```'+ '\n' + rrr + '\n'+'```')
+
+            except Exception as e:
+                print("model internal error:", e)
+        print("-" * 20)
+        print("Treated output: \n", output)
+        return output
+    
+    @property
+    def _identifying_params(self) -> Mapping[str, Any]:
+        return [("n", self.n)]
+    
+    def treat_output(text):
+        
+        keywords = ['Action:', 'Action Input:', 'Observation:', 'Thought:', 'Final Answer:']
+        for item in keywords:
+            if item in text:
+                text.replace(item, '\n'+item)
+        print("treat output: ", text)
+        return text
+
+GPTfake = GPTRemote(n=0)
+
+async def start_playwright(question: str):
+    start_t = time.time()
+    pw = await async_playwright().start()
+    browser = await pw.chromium.launch(headless=True)
+    end_t = time.time()
+    print("Init Browser Done:",  end_t - start_t)
+    start_t = end_t
+    page = await browser.new_page()
+    
+    # note all methods are async (use the "await" keyword)
+    await page.goto(os.environ["Endpoint_GPT4"])
+    # print("Title of Web: ", await page.title())
+    end_t = time.time()
+    print("New Page Done:",  end_t - start_t)
+    start_t = end_t
+    await page.wait_for_timeout(200)
+    
+    await page.locator("//textarea").fill(question)
+    await page.wait_for_timeout(200)
+
+    await page.locator("//textarea").press("Enter")
+    await page.wait_for_timeout(200)
+
+    output_history = "NOTHING"
+    for i in range(100):
+        output_text_old = await page.locator("//div[@aria-label='Chat message from assistant']").last.inner_text()
+        html_content = await page.locator("//div[@aria-label='Chat message from assistant']//div[@class='stMarkdown']").last.inner_html()
+        markdown_converter = html2text.HTML2Text()
+        output_text = markdown_converter.handle(html_content)
+        print("output_text... :")
+        
+        if output_text == output_history and '▌' not in output_text and output_text != "":
+            end_t = time.time()
+            print("Output Done:",  end_t - start_t)
+            return output_text
+        else:
+            await page.wait_for_timeout(500)
+            output_history = output_text
+    print("-------- Final Answer-----------\n", output_text)
+
+    await browser.close()
+
+# GPTfake("hi")
+
+
+st.title("STLA-BABY")
+
+msgs = StreamlitChatMessageHistory()
+
+if len(msgs.messages) == 0 or st.sidebar.button("Reset Chat History"):
+    msgs.clear()
+    msgs.add_ai_message("How can I help you ?")
+    st.session_state.steps = {}
+
+avatars = {"human": "user", "ai": "assistant"}
+
+for idx, msg in enumerate(msgs.messages):
+    with st.chat_message(avatars[msg.type]):
+        st.write(msg.content)
+
+if prompt := st.chat_input(placeholder="Input Your Request"):
+    st.chat_message("user").write(prompt)
+
+    with st.chat_message("assistant"):
+        response = GPTfake(prompt)
+        st.write(response)
+        print(msgs.messages)

requirements.txt

@@ -30,3 +30,4 @@ pandas
 regex
 graphviz
 streamlit
+streamlit_chat