PROMPT: user: this code doesnt send the user input, and keeps sending "hi". import requests import json import re  def send_post_request(post_url, headers, payload):     try:         response = requests.post(post_url, headers=headers, json=payload)          # Print the response text from the POST request         #print("POST Response Text:")         #print(response.text)  # Print the raw response text                  if response.status_code == 200:             print("POST request was successful!")         else:             print(f"POST request failed with status code: {response.status_code}")      except requests.exceptions.RequestException as e:         print(f"An error occurred during POST: {e}")  def send_get_request(get_url, headers, params):     try:         response = requests.get(get_url, headers=headers, params=params)          # Print the response text from the GET request         #print("GET Response Text:")         #print(response.text)  # Print the raw response text                  if response.status_code == 200:             #print("GET request was successful!")             return response.text  # Return the response for further processing         else:             print(f"GET request failed with status code: {response.status_code}")             return None      except requests.exceptions.RequestException as e:         print(f"An error occurred during GET: {e}")         return None  def extract_ai_response(response_text):     ai_responses = []          # Split the response based on "data: "     parts = response_text.split('data: ')          for part in parts:         if 'process_completed' in part:             try:                 # Extract the output JSON                 json_part = re.search(r'{"msg":"process_completed".*}', part)                 if json_part:                     output_data = json.loads(json_part.group(0))                     # Get the AI message from the output field                     ai_messages = output_data['output']['data']                     for message in ai_messages:                         # It seems the AI response is among the nested lists                         if isinstance(message, list) and len(message) > 0:                             # The second item in the first sub-list seems to be the response                             ai_response = message[0][1]                             ai_responses.append(ai_response)             except (ValueError, IndexError) as e:                 print(f"Error parsing response: {e}")      return ai_responses  if __name__ == "__main__":     # Prepare URLs     post_url = "https://yuntian-deng-chatgpt4.hf.space/queue/join"     get_url = "https://yuntian-deng-chatgpt4.hf.space/queue/data"      # Headers for the requests     headers = {         'Accept': 'text/event-stream',         'Accept-Encoding': 'gzip, deflate, br, zstd',         'Accept-Language': 'en-US,en;q=0.7',         'Cache-Control': 'no-cache',         'Content-Type': 'application/json',         'Pragma': 'no-cache',         'Referer': 'https://yuntian-deng-chatgpt4.hf.space/',         'Sec-CH-UA': '"Brave";v="129", "Not=A?Brand";v="8", "Chromium";v="129"',         'Sec-CH-UA-Mobile': '?0',         'Sec-CH-UA-Platform': '"Windows"',         'Sec-Fetch-Dest': 'empty',         'Sec-Fetch-Mode': 'cors',         'Sec-Fetch-Site': 'same-origin',         'Sec-GPC': '1',         'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36'     }      # User input for the payload     hi_input = input("Please enter a text input (for 'hi'): ")      # Payload for the POST request     payload = {         "data": [hi_input, 1, 1, 0, [], []],         "event_data": None,         "fn_index": 3,         "session_hash": "26vb4jk6379",         "trigger_id": 5     }      # Send the POST request first     send_post_request(post_url, headers, payload)      # Prepare parameters for the GET request, including session_hash     params = {         'session_hash': '26vb4jk6379'     }      # Then send the GET request     response_text = send_get_request(get_url, headers, params)      # Extract the AI response from the GET response     if response_text:         ai_responses = extract_ai_response(response_text)         if ai_responses:             #print("AI Responses:")             for response in ai_responses:                 print(response)         else:             print("Could not extract AI responses.")\nassistant: The code you've shared has a couple of potential issues that could lead to it not sending the user input correctly and defaulting to sending "hi". Let's walk through the code to identify any problems and improve it:\n\n1. **User Input Handling**\n   - Ensure that the user input is correctly captured and stored in the `hi_input` variable. If the program always sends "hi", it could be due to a hardcoded value or not properly assigning the value.\n\n2. **Payload Construction**\n   - Double-check that the payload is correctly including the user input. You're currently using `"data": [hi_input, 1, 1, 0, [], []]`, which should be correct provided `hi_input` contains the user input.\n\n3. **POST and GET requests**\n   - Confirm that the POST and GET requests are correctly targeting the endpoints and that the server is processing them as expected. The payload and session handling are crucial here.\n\n4. **Error Handling**\n   - Add more verbose logging to see if errors occur during the requests. It helps to know whether the requests are being sent and received correctly.\n\n5. **Response Parsing**\n   - Ensure the `extract_ai_response` function correctly identifies the structure of the response. Print and verify the raw data you receive to ascertain if your parsing logic aligns with what's expected.\n   \n6. **Debugging Approach**\n   - Print the payload being sent in the POST request to confirm the input is being included.\n   - Verify the response from the POST request to see if it returns a status or message indicating success or failure.\n   - After making the GET request, check if `response_text` is not empty or `None` and confirm the structure matches your parsing logic.\n   - Add debug print statements at various stages to track the flow and values in your code.\n\nHere's an adjusted snippet that incorporates debugging and error checking improvements:\n\n\n```python\nimport requests\nimport json\nimport re\n\ndef send_post_request(post_url, headers, payload):\n    try:\n        print(f"Sending POST request with payload: {payload}")  # Debug\n        response = requests.post(post_url, headers=headers, json=payload)\n        print(response.text)  # Print response for debugging\n\n        if response.status_code == 200:\n            print("POST request was successful!")\n        else:\n            print(f"POST request failed with status code: {response.status_code}")\n\n    except requests.exceptions.RequestException as e:\n        print(f"An error occurred during POST: {e}")\n\ndef send_get_request(get_url, headers, params):\n    try:\n        response = requests.get(get_url, headers=headers, params=params)\n        if response.status_code == 200:\n            return response.text  # Return the response for further processing\n        else:\n            print(f"GET request failed with status code: {response.status_code}")\n            return None\n\n    except requests.exceptions.RequestException as e:\n        print(f"An error occurred during GET: {e}")\n        return None\n\ndef extract_ai_response(response_text):\n    ai_responses = []\n    print("Response received for parsing:", response_text)  # Debug\n\n    parts = response_text.split('data: ')\n\n    for part in parts:\n        if 'process_completed' in part:\n            try:\n                json_part = re.search(r'{"msg":"process_completed".*}', part)\n                if json_part:\n                    output_data = json.loads(json_part.group(0))\n                    ai_messages = output_data['output']['data']\n                    for message in ai_messages:\n                        if isinstance(message, list) and len(message) > 0:\n                            ai_response = message[0][1]\n                            ai_responses.append(ai_response)\n            except (ValueError, IndexError) as e:\n                print(f"Error parsing response: {e}")\n\n    return ai_responses\n\nif __name__ == "__main__":\n    post_url = "https://yuntian-deng-chatgpt4.hf.space/queue/join"\n    get_url = "https://yuntian-deng-chatgpt4.hf.space/queue/data"\n\n    headers = {\n        'Accept': 'text/event-stream',\n        'Accept-Encoding': 'gzip, deflate, br, zstd',\n        'Accept-Language': 'en-US,en;q=0.7',\n        'Cache-Control': 'no-cache',\n        'Content-Type': 'application/json',\n        'Pragma': 'no-cache',\n        'Referer': 'https://yuntian-deng-chatgpt4.hf.space/',\n        'Sec-CH-UA': '"Brave";v="129", "Not=A?Brand";v="8", "Chromium";v="129"',\n        'Sec-CH-UA-Mobile': '?0',\n        'Sec-CH-UA-Platform': '"Windows"',\n        'Sec-Fetch-Dest': 'empty',\n        'Sec-Fetch-Mode': 'cors',\n        'Sec-Fetch-Site': 'same-origin',\n        'Sec-GPC': '1',\n        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36'\n    }\n\n    hi_input = input("Please enter a text input (for 'hi'): ")\n\n    payload = {\n        "data": [hi_input, 1, 1, 0, [], []],\n        "event_data": None,\n        "fn_index": 3,\n        "session_hash": "26vb4jk6379",\n        "trigger_id": 5\n    }\n\n    send_post_request(post_url, headers, payload)\n\n    params = {\n        'session_hash': '26vb4jk6379'\n    }\n\n    response_text = send_get_request(get_url, headers, params)\n\n    if response_text:\n        ai_responses = extract_ai_response(response_text)\n        if ai_responses:\n            for response in ai_responses:\n                print(response)\n        else:\n            print("Could not extract AI responses.")\n```\n\n\nMake sure your server endpoints and expected response formats haven't changed. If the issue persists, verifying those might shed light on why the code isn't behaving as expected.\nuser: oh i noticed, it does send the input but it gets the wrong thingy, look: data: {"msg":"process_completed","event_id":"8c24653d07c547f1a8cac979a3ece3fe","output":{"data":[[["hi","Hello! How can I assist you today?"],["hi","Hello! How can I assist you today?"],["hi","Hello! How can I assist you today?"],["hi","Hello! How can I assist you today?"],["hi whats your name","Hello! I don't have a name, but you can call me Assistant. How can I help you today?"],["hi whats your name","Hello! I don't have a personal name, but you can call me Assistant. How can I help you today?"],["hi fuck you","I'm here to help, so if you have any questions or need assistance, feel free to ask!"],["hi","Hello! How can I assist you today?"],["hi","Hello! How can I assist you today?"],["whats your name","I don’t have a personal name, but you can call me Assistant. How can I help you today?"],["repeat that","Of course! Could you please specify what you would like me to repeat?"],["hi who are you","Hello! I’m an AI language model created by OpenAI, here to help answer your questions and provide information. How can I assist you today?"],["HI","Hello! How can I assist you today?"],["how are you","I'm just a computer program, so I don't have feelings, but I'm here to help you! How can I assist you today?"],["whats your name","I don't have a personal name, but you can call me \"Assistant.\" How can I help you today?"]],null,1,"<Response [200]>",{"interactive":true,"__type__":"update"},{"interactive":true,"__type__":"update"}],"is_generating":false,"duration":0.0007545948028564453,"average_duration":0.011281762906027292,"render_config":null,"changed_state_ids":[]},"success":true}\nassistant: Based on the data you've provided, it seems that the response you are getting contains multiple AI response scenarios, which might not be filtering correctly to match your specific input. The issue lies in extracting the correct response associated with your user input. Here's a step-by-step approach to fine-tune your response extraction:\n\n1. **Identify Unique Markers:**\n   - Look for unique identifiers or markers in the response data that allow you to match your user input to the corresponding AI response.\n\n2. **Parsing Logic:**\n   - The current extraction logic seems to iterate through multiple AI responses that might not correspond directly to a single input scenario. You'll need to refine this logic.\n\n3. **Modify `extract_ai_response` Function:**\n   - Instead of appending all responses, try to match the AI response list with your input exactly or use the nearest match strategy:\n\n\n```python\ndef extract_ai_response(response_text, user_input):\n    ai_responses = []\n    try:\n        # Attempting to load the full JSON once the nested 'data' field is isolated\n        json_part = re.search(r'{"msg":"process_completed".*}', response_text)\n        if json_part:\n            output_data = json.loads(json_part.group(0))\n            ai_messages = output_data['output']['data'][0]  # Accessing the correct list level\n\n            # Iterate over messages and find the best match to user's input\n            for pair in ai_messages:\n                if pair[0].lower() == user_input.lower():\n                    ai_responses.append(pair[1])\n\n    except (ValueError, IndexError) as e:\n        print(f"Error parsing response: {e}")\n\n    return ai_responses\n```\n\n\n4. **Call Extraction with Input**:\n   - Pass your user input to the `extract_ai_response` function to find the best-match response:\n\n\n```python\n# When calling extract_ai_response\nai_responses = extract_ai_response(response_text, hi_input)\n```\n\n\n5. **Testing**: \n   - Test the above changes with different inputs to make sure the filtering logic captures the correct response by accurately matching your input.\n\n6. **Further Debugging**: \n   - Verify that the part of the response you are parsing correctly reflects the available data structure. Adjust the indices and parsing logic as necessary.\n\nBy applying these steps, you refine the extraction logic to filter out the irrelevant entries and correctly link each input to its associated output in your response data.\nuser: whole code plz