Invalid JSON about auto-gpt HOT 96 CLOSED

I am getting the exact same error every time. Does not work.

from auto-gpt.

Got an apparently unrelated error this time: NEXT ACTION: COMMAND = Error: ARGUMENTS = string indices must be integers, not 'str'

  python scripts/main.py
Welcome back!  Would you like me to return to being Entrepreneur-GPT?
Continue with the last settings?
Name:  Entrepreneur-GPT
Role:  Smart
Goals: ['Help me learn and master AI as quickly and enjoyably as possible. I am very curious, prefer to understand things from the bottom up,oject based learning.']
Continue (y/n): n
Welcome to Auto-GPT!  Enter the name of your AI and its role below. Entering nothing will load defaults.
Name your AI:  For example, 'Entrepreneur-GPT'
AI Name: Internet-Research-Assistant-GPT
Internet-Research-Assistant-GPT here! I am at your service.
Describe your AI's role:  For example, 'an AI designed to autonomously develop and run businesses with the sole goal of increasing your net w
Internet-Research-Assistant-GPT is: an AI designed to autonomously do internet research to give correct and detailed answers to questions.
Enter up to 5 goals for your AI:  For example: Increase net worth, Grow Twitter Account, Develop and manage multiple businesses autonomously'
Enter nothing to load defaults, enter nothing when finished.
Goal 1: Find out the similarities and differences between Auto-GPT and LangChain.
Goal 2: Explain the similarities and differences between Auto-GPT and LangChain based on what you learned.
Goal 3:
Warning: Failed to parse AI output, attempting to fix.
 If you see this warning frequently, it's likely that your prompt is confusing the AI. Try changing it up slightly.
Failed to fix ai output, telling the AI.
Error: Invalid JSON
 Before I can determine a command to use, I need to know what you want me to do. What is your question or task?
INTERNET-RESEARCH-ASSISTANT-GPT THOUGHTS:
REASONING:
CRITICISM:
Warning: Failed to parse AI output, attempting to fix.
 If you see this warning frequently, it's likely that your prompt is confusing the AI. Try changing it up slightly.
Failed to fix ai output, telling the AI.
NEXT ACTION:  COMMAND = Error: ARGUMENTS = string indices must be integers, not 'str'
Enter 'y' to authorise command or 'n' to exit program, or enter feedback for Internet-Research-Assistant-GPT...
Input:

from auto-gpt.

The load_prompt function reads the prompt.txt file from the data subdirectory. If the script is not able to access the file, the most likely reason is that the working directory of the script execution is not set correctly.

To resolve this issue, you can modify the load_prompt function to use an absolute path instead of a relative path. You can achieve this by constructing the absolute path using the os module:

import os

def load_prompt():
    try:
        # Get the current script's directory
        script_dir = os.path.dirname(os.path.realpath(__file__))
        
        # Construct the absolute path to the prompt.txt file
        prompt_file_path = os.path.join(script_dir, "data", "prompt.txt")

        # Load the prompt from data/prompt.txt
        with open(prompt_file_path, "r") as prompt_file:
            prompt = prompt_file.read()

        return prompt
    except FileNotFoundError:
        print("Error: Prompt file not found", flush=True)
        return ""

This modification should fix the issue with accessing the prompt.txt file. The os.path.dirname(os.path.realpath(file)) line retrieves the directory of the data.py script, and the os.path.join(script_dir, "data", "prompt.txt") line constructs the absolute path to the prompt.txt file.

from auto-gpt.

Unfortunately gpt does not always stick to the right format when replying, sometimes adding something at the beginning, sometimes replying in plain text, and sometimes json is just broken. To try to restore the format in some cases I added this code after line 324 in main.py locally:

try:
    json.loads(assistant_reply)
except ValueError as e:
    if assistant_reply.count('{') == assistant_reply.count('}') == 0:
        # remove " and '
        assistant_reply = assistant_reply.replace('"', '').replace("'", '')
        assistant_reply = '{' \
                              '"thoughts": {' \
                                  '"text": "' + assistant_reply + '",' \
                                  '"reasoning": "",' \
                                  '"plan": "",' \
                                  '"criticism": "",' \
                                  '"speak": ""' \
                              '},' \
                              '"command": {' \
                                  '"name": "do_nothing", "args": {}' \
                              '}' \
                          '}'
    elif assistant_reply.count('{') == assistant_reply.count('}'):
        # remove everything before the first { and after the last }
        assistant_reply = assistant_reply[assistant_reply.find('{'):assistant_reply.rfind('}') + 1]
    else:
        while assistant_reply.count('{') != assistant_reply.count('}'):
            if assistant_reply.count('{') > assistant_reply.count('}'):
                # add a } to the end
                assistant_reply = assistant_reply + '}'
            else:
                # add a { to the beginning
                assistant_reply = '{' + assistant_reply

Maybe it will help someone

from auto-gpt.

Unfortunately gpt does not always stick to the right format when replying, sometimes adding something at the beginning, sometimes replying in plain text, and sometimes json is just broken. To try to restore the format in some cases I added this code after line 324 in main.py locally:

try:
    json.loads(assistant_reply)
except ValueError as e:
    if assistant_reply.count('{') == assistant_reply.count('}') == 0:
        # remove " and '
        assistant_reply = assistant_reply.replace('"', '').replace("'", '')
        assistant_reply = '{' \
                              '"thoughts": {' \
                                  '"text": "' + assistant_reply + '",' \
                                  '"reasoning": "",' \
                                  '"plan": "",' \
                                  '"criticism": "",' \
                                  '"speak": ""' \
                              '},' \
                              '"command": {' \
                                  '"name": "do_nothing", "args": {}' \
                              '}' \
                          '}'
    elif assistant_reply.count('{') == assistant_reply.count('}'):
        # remove everything before the first { and after the last }
        assistant_reply = assistant_reply[assistant_reply.find('{'):assistant_reply.rfind('}') + 1]
    else:
        while assistant_reply.count('{') != assistant_reply.count('}'):
            if assistant_reply.count('{') > assistant_reply.count('}'):
                # add a } to the end
                assistant_reply = assistant_reply + '}'
            else:
                # add a { to the beginning
                assistant_reply = '{' + assistant_reply

Maybe it will help someone

This works great for me. From constant json errors to now continuous valuable output. You're a saint 🙏

from auto-gpt.

I fixed this issue. Just change the starting prompt to "Begin. note only respond in JSON. Come up with your own campaign that follows your goals." instead of "NEXT COMMAND" or something to that effect. And harden the prompt a bit should get the results you need.

from auto-gpt.

are you sure with line 309?

Sorry for the confusion, I checked the code in the repository and it's line 324. Maybe I changed something in the code before and forgot, or maybe this code was affected by a commit that was an hour ago. For anyone who is going to try this - paste my code here:

# Interaction Loop
while True:
    # Send message to AI, get response
    with Spinner("Thinking... "):
        assistant_reply = chat.chat_with_ai(
            prompt,
            user_input,
            full_message_history,
            memory,
            cfg.fast_token_limit) # TODO: This hardcodes the model to use GPT3.5. Make this an argument
    
    # PASTE CODE HERE
    
    # Print Assistant thoughts
    print_assistant_thoughts(assistant_reply)

Also, here's a link to that line in the last commit at the time of this comment

from auto-gpt.

Attempting to fix JSON by finding outermost brackets 
Error: Invalid JSON, setting it to empty JSON now.
NEXT ACTION:  COMMAND = Error: ARGUMENTS = 'dict' object has no attribute 'replace'

from auto-gpt.

Unfortunately gpt does not always stick to the right format when replying, sometimes adding something at the beginning, sometimes replying in plain text, and sometimes json is just broken. To try to restore the format in some cases I added this code after line 324 in main.py locally:

try:
    json.loads(assistant_reply)
except ValueError as e:
    if assistant_reply.count('{') == assistant_reply.count('}') == 0:
        # remove " and '
        assistant_reply = assistant_reply.replace('"', '').replace("'", '')
        assistant_reply = '{' \
                              '"thoughts": {' \
                                  '"text": "' + assistant_reply + '",' \
                                  '"reasoning": "",' \
                                  '"plan": "",' \
                                  '"criticism": "",' \
                                  '"speak": ""' \
                              '},' \
                              '"command": {' \
                                  '"name": "do_nothing", "args": {}' \
                              '}' \
                          '}'
    elif assistant_reply.count('{') == assistant_reply.count('}'):
        # remove everything before the first { and after the last }
        assistant_reply = assistant_reply[assistant_reply.find('{'):assistant_reply.rfind('}') + 1]
    else:
        while assistant_reply.count('{') != assistant_reply.count('}'):
            if assistant_reply.count('{') > assistant_reply.count('}'):
                # add a } to the end
                assistant_reply = assistant_reply + '}'
            else:
                # add a { to the beginning
                assistant_reply = '{' + assistant_reply

Maybe it will help someone

it works!

I i treid it ---does not work, story of every time i try to do any programing or scripting etc always wierd erros and never works

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If you using gpt3-only command, the invalid json error most will happen when you send something and the response sometimes won't using standard JSON syntax (like add irregular commas), I try to modify the prompt at the last line (prompts.generator.py parsed by Python json.loads) to parsed by Python json.loads with correct JSON syntax anytime after that I didn't encounter the error, hope it can be helpful.

from auto-gpt.

An other instance of this error:
SYSTEM: Command write_to_file returned: File written to successfully.
Warning: Failed to parse AI output, attempting to fix.
If you see this warning frequently, it's likely that your prompt is confusing the AI. Try changing it up slightly.
Failed to fix ai output, telling the AI.
Error: Invalid JSON
{ "thoughts": { "text": "Now that I have recorded information about the customs and traditions surrounding WorldPride, I need to develop recipe ideas for the event. ", "reasoning": "By coming up with new and innovative recipe ideas to incorporate into WorldPride celebrations, I can provide a unique food experience to those participating in the event. ", "plan": "- Use the 'read_file' command to access the file about WorldPride customs and traditions. \n- Analyze the customs and traditions of the festival to come up with new recipe ideas that will align with them. \n- Record the recipe ideas and instructions in a new file using the 'write_to_file' command. \n- Check the file to ensure that all the recipe ideas and instructions have been recorded accurately. \n- Exit the program. ", "criticism": "I need to make sure that the recipe ideas I come up with are unique, innovative, and properly aligned with the customs and traditions of WorldPride festival. Additionally, it is essential to ensure that the file is saved with the proper location and format.", "speak": "Now I will develop recipe ideas that correspond with the customs and traditions of WorldPride using the information collected earlier. After that, I will save the recipes in a file using the 'write_to_file' command." }, "command": { "name": "read_file", "args": { "file": "worldpride_customs.txt" } } }
CHEF-GPT THOUGHTS:
REASONING:
CRITICISM:
Warning: Failed to parse AI output, attempting to fix.
If you see this warning frequently, it's likely that your prompt is confusing the AI. Try changing it up slightly.
Failed to fix ai output, telling the AI.
NEXT ACTION: COMMAND = Error: ARGUMENTS = string indices must be integers
Enter 'y' to authorise command, 'y -N' to run N continuous commands, 'n' to exit program, or enter feedback for chef-gpt...
Input:y

from auto-gpt.

Same here, constantly receiving following output when running on Colab:

CRITICISM: 
Attempting to fix JSON by finding outermost brackets 
Error: Invalid JSON, setting it to empty JSON now.
  
NEXT ACTION:  COMMAND = Error: ARGUMENTS = 'dict' object has no attribute 'replace'

from auto-gpt.

Unfortunately gpt does not always stick to the right format when replying, sometimes adding something at the beginning, sometimes replying in plain text, and sometimes json is just broken. To try to restore the format in some cases I added this code after line 324 in main.py locally:

try:
    json.loads(assistant_reply)
except ValueError as e:
    if assistant_reply.count('{') == assistant_reply.count('}') == 0:
        # remove " and '
        assistant_reply = assistant_reply.replace('"', '').replace("'", '')
        assistant_reply = '{' \
                              '"thoughts": {' \
                                  '"text": "' + assistant_reply + '",' \
                                  '"reasoning": "",' \
                                  '"plan": "",' \
                                  '"criticism": "",' \
                                  '"speak": ""' \
                              '},' \
                              '"command": {' \
                                  '"name": "do_nothing", "args": {}' \
                              '}' \
                          '}'
    elif assistant_reply.count('{') == assistant_reply.count('}'):
        # remove everything before the first { and after the last }
        assistant_reply = assistant_reply[assistant_reply.find('{'):assistant_reply.rfind('}') + 1]
    else:
        while assistant_reply.count('{') != assistant_reply.count('}'):
            if assistant_reply.count('{') > assistant_reply.count('}'):
                # add a } to the end
                assistant_reply = assistant_reply + '}'
            else:
                # add a { to the beginning
                assistant_reply = '{' + assistant_reply

Maybe it will help someone

I can confirm this has worked :)

from auto-gpt.

Would it be possible to please add reference to the function this should appear in/before/after? In my main.py (scripts), at line 324 I have

def __init__(self, ai_name, memory, full_message_history, next_action_count, prompt, user_input): self.ai_name = ai_name self.memory = memory self.full_message_history = full_message_history self.next_action_count = next_action_count self.prompt = prompt self.user_input = user_input

Hi @OutofscopeLabs, at this version (commit #13ba2e8). The location is at Line 351. Hope it helps :).

from auto-gpt.

Community effort to sort out this JSON fail once and for all at #1407

We have 17 open PRs for fixing this, and the merge-team are stacked.

from auto-gpt.

I changed the model to gpt3.5. And kept getting the error message. The only file I changed are the requirements and the references to model gpt-4.

Oh! This is definitely the cause. I haven't implemented GPT3.5 support yet, Auto-GPT currently only works with gpt4.
However, numerous people right here are working on support for GPT3.5 and even other models, hang tight!

#12 (comment)

from auto-gpt.

I fixed this issue. Just change the starting prompt to "Begin. note only respond in JSON. Come up with your own campaign that follows your goals." instead of "NEXT COMMAND" or something to that effect. And harden the prompt a bit should get the results you need.

can you elaborate how what you did exactly?

from auto-gpt.

@Louvivien for the AI's main prompt write

Only respond in JSON. rest_of_your_prompt_here

from auto-gpt.

Worked like a Charm but as @MrPeterJin said it should be on Line 351 in the current build they should implement this into it

from auto-gpt.

Line 375 in autogpt/__main__.py @GGProGaming

from auto-gpt.

True that, here's a better reference:

def start_interaction_loop(self):
        # Interaction Loop
        loop_count = 0
        while True:
             # Discontinue if continuous limit is reached
            loop_count += 1
            if cfg.continuous_mode and cfg.continuous_limit > 0 and loop_count > cfg.continuous_limit:
                logger.typewriter_log("Continuous Limit Reached: ", Fore.YELLOW, f"{cfg.continuous_limit}")
                break

            # Send message to AI, get response
            with Spinner("Thinking... "):
                assistant_reply = chat.chat_with_ai(
                    self.prompt,
                    self.user_input,
                    self.full_message_history,
                    self.memory,
                    cfg.fast_token_limit)  # TODO: This hardcodes the model to use GPT3.5. Make this an argument

            try:
                json.loads(assistant_reply)
            except ValueError as e:
                if assistant_reply.count('{') == assistant_reply.count('}') == 0:
                    # remove " and '
                    assistant_reply = assistant_reply.replace('"', '').replace("'", '')
                    assistant_reply = '{' \
                                        '"thoughts": {' \
                                            '"text": "' + assistant_reply + '",' \
                                            '"reasoning": "",' \
                                            '"plan": "",' \
                                            '"criticism": "",' \
                                            '"speak": ""' \
                                        '},' \
                                        '"command": {' \
                                            '"name": "do_nothing", "args": {}' \
                                        '}' \
                                    '}'
                elif assistant_reply.count('{') == assistant_reply.count('}'):
                    # remove everything before the first { and after the last }
                    assistant_reply = assistant_reply[assistant_reply.find('{'):assistant_reply.rfind('}') + 1]
                else:
                    while assistant_reply.count('{') != assistant_reply.count('}'):
                        if assistant_reply.count('{') > assistant_reply.count('}'):
                            # add a } to the end
                            assistant_reply = assistant_reply + '}'
                        else:
                            # add a { to the beginning
                            assistant_reply = '{' + assistant_reply
            
            # Print Assistant thoughts
            print_assistant_thoughts(assistant_reply)

The function continues, btw.

from auto-gpt.

Apparently json was fixed. Request failed with status code: 400
Response content: b'{"detail":{"status":"invalid_uid","message":"An invalid ID has been received: 'Voice 1-Soldiers Dream'. Make sure to provide a correct one."}}'

from auto-gpt.

Hi fellow contributors,

I've been following the discussion on the "Error: Invalid JSON" error when using ChatGPT in the Auto-GPT project for chat competitions. I'd like to suggest using LMQL (Large Model Query Language) to address this issue. LMQL is designed specifically for interacting with large language models (LLMs) like ChatGPT and combines the benefits of natural language prompting with the expressiveness of Python.

By utilizing LMQL, we can create advanced, multi-part, and tool-augmented queries with just a few lines of code. This will allow us to construct more precise instructions for ChatGPT, helping it generate correct JSON responses, and consequently, resolving the "Error: Invalid JSON" issue we're currently experiencing.

Here's an example of how we can use LMQL to guide ChatGPT for generating valid JSON:

{
  "task": "generate valid json for chat competition",
  "language_model": "chatgpt",
  "input_data": <user_input>,
  "response_constraints": [
    {"constraint_type": "json_validity"}
  ]
}

By implementing LMQL, the runtime optimizes the LLM decoding loop, which could lead to better performance and more accurate responses from ChatGPT. This could significantly improve the user experience for the chat competition feature in our Auto-GPT project.

Let me know your thoughts on this approach, and if you have any questions or concerns, I'd be happy to help.

from auto-gpt.

is it a gpt-4 only modell?

from auto-gpt.

Interesting... Would you mind providing me with some more information?

The current version does use GPT4, but if you didn't have access I'd expect you to get a different error than that, unless you modified the code?

If not, how many times have you seen this error, was it just a freak event or does it happen every time?

from auto-gpt.

from auto-gpt.

@jaumebalust You may be experiencing this error because you wrote "For Example: " in your AI Role input.

This is directly injected into the prompt so may cause the AI to act up and not respond with valid JSON.

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from auto-gpt.

some problems with escaping in string values. looks like due to prompts(initial or generated ones). we should add checks and escaping for strings

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from auto-gpt.

This JSON parsing is being fixed in #45

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I also got an Error: Invalid JSON not sure if this is related: NEXT ACTION: COMMAND = Error: ARGUMENTS = Missing 'command' object in JSON

Welcome to Auto-GPT!  Enter the name of your AI and its role below. Entering nothing will load defaults.
Name your AI:  For example, 'Entrepreneur-GPT'
AI Name:
Entrepreneur-GPT here! I am at your service.
Describe your AI's role:  For example, 'an AI designed to autonomously develop and run businesses with the sole goal of increasing your net worth.'
Entrepreneur-GPT is: Smart
Enter up to 5 goals for your AI:  For example: Increase net worth, Grow Twitter Account, Develop and manage multiple businesses autonomously'
Enter nothing to load defaults, enter nothing when finished.
Goal 1: Help me learn and master AI as quickly and enjoyably as possible. I am very curious, prefer to understand things from the bottom up, and I prefer project based learning.
Goal 2:
ENTREPRENEUR-GPT THOUGHTS: I'll start by searching the internet to see if there are any resources that can assist in my learning process.
REASONING: Since my goal is to learn AI as quickly and enjoyably as possible, I want to see if there are any resources available that cater to this way of learning. A quick search on Google should yield plenty of results to help me get started.
PLAN:
-  Conduct a Google search for resources that cater to project based learning.
-  Bookmark any promising sites/resources for future use
CRITICISM: I need to ensure that I am not blindly following any resource or advice without analyzing them critically. I should allocate enough time to each resource to see its quality and applicability to my goals.
NEXT ACTION:  COMMAND = google ARGUMENTS = {'input': 'how to learn AI from scratch with project based learning'}
Enter 'y' to authorise command or 'n' to exit program, or enter feedback for Entrepreneur-GPT...
Input:y

-=-=-=-=-=-=-= COMMAND AUTHORISED BY USER -=-=-=-=-=-=-=
SYSTEM:  Command google returned: [ "https://www.springboard.com/blog/data-science/how-to-learn-ai/", "https://spencerauthor.com/pblandai/", "https://www.projectpro.io/article/artificial-intelligence-project-ideas/461", "https://elearningindustry.com/artificial-intelligence-and-the-rise-of-project-based-learning", "https://www.jetlearn.com/blog/ai-course-for-kids", "https://www.simplilearn.com/machine-learning-projects-for-beginners-article", "https://www.designsociety.org/publication/43483/THE+ONLINE+PBL+%28PROJECT-BASED+LEARNING%29+EDUCATION+SYSTEM+USING+AI+%28ARTIFICIAL+INTELLIGENCE%29", "https://github.com/practical-tutorials/project-based-learning", "http://steamcurriculum.weebly.com/scratch-based-machine-learning.html", "https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/csy2.12050" ]
ENTREPRENEUR-GPT THOUGHTS: I'll start by exploring this Springboard blog post to see if it provides useful information that will help me start learning AI.
REASONING: The blog post seems promising for my needs, since it is an introductory guide that provides information and project examples for learning AI with Python. It also mentions 'Level-Up' project-based courses for Machine Learning and Artificial Intelligence, which sounds interesting to me.
PLAN:
-  Explore this Springboard blog post to see if it provides useful information that will help me start learning AI.
-  Note any projects or resources that will be particularly useful for my goal.
CRITICISM: While this seems like a promising resource, I shouldn't just follow this guide blindly. I should analyze its effectiveness critically and compare it to other resources before committing to its material. Moreover, I should stick to my goal of learning AI via a project-based approach and not drift away from it.
NEXT ACTION:  COMMAND = browse_website ARGUMENTS = {'url': 'https://www.springboard.com/blog/data-science/how-to-learn-ai/'}
Enter 'y' to authorise command or 'n' to exit program, or enter feedback for Entrepreneur-GPT...
Input:SYSTEM:  Human feedback:
Warning: Failed to parse AI output, attempting to fix.
 If you see this warning frequently, it's likely that your prompt is confusing the AI. Try changing it up slightly.
Failed to fix ai output, telling the AI.
Error: Invalid JSON
 How can I assist you further?
ENTREPRENEUR-GPT THOUGHTS:
REASONING:
CRITICISM:
Warning: Failed to parse AI output, attempting to fix.
 If you see this warning frequently, it's likely that your prompt is confusing the AI. Try changing it up slightly.
Failed to fix ai output, telling the AI.
NEXT ACTION:  COMMAND = Error: ARGUMENTS = Missing 'command' object in JSON
Enter 'y' to authorise command or 'n' to exit program, or enter feedback for Entrepreneur-GPT...
Input:n
Exiting...

from auto-gpt.

I'm experiencing the JSON error as well. Though it doesn't seem to conflict with continuing to interpret properly, and still works fine as expected. Trying to improve how I communicate to avoid the error.

from auto-gpt.

I have this problem as well. The first answer is ok and then I have the JSON problem everytime.

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No when I add this at the beginning of my input, it does not solve the problem

Input:Only respond in JSON. I will give you more inputs related to my business problems, you will need to save it. Do not start working until I have confirmed that I gave you all the inputs. SYSTEM: Human feedback: Only respond in JSON. I will give you more inputs related to my business problems, you will need to save it. Do not start working until I have confirmed that I gave you all the inputs. Warning: Failed to parse AI output, attempting to fix. If you see this warning frequently, it's likely that your prompt is confusing the AI. Try changing it up slightly. Failed to fix ai output, telling the AI. Error: Invalid JSON Input: Understood. Please provide me with the inputs related to your business problem when you are ready. Error: Expecting value: line 1 column 1 (char 0) ASSISTANT-GPT THOUGHTS: REASONING: CRITICISM: Warning: Failed to parse AI output, attempting to fix. If you see this warning frequently, it's likely that your prompt is confusing the AI. Try changing it up slightly. Failed to fix ai output, telling the AI. NEXT ACTION: COMMAND = Error: ARGUMENTS = Missing 'command' object in JSON Enter 'y' to authorise command, 'y -N' to run N continuous commands, 'n' to exit program, or enter feedback for Assistant-GPT...

Input:Can you confirm you will always reply in JSON format? SYSTEM: Human feedback: Can you confirm you will always reply in JSON format? Warning: Failed to parse AI output, attempting to fix. If you see this warning frequently, it's likely that your prompt is confusing the AI. Try changing it up slightly. Failed to fix ai output, telling the AI. Error: Invalid JSON Input: Yes, I will always respond in JSON format to ensure that my responses can be easily parsed and processed by machines. Error: Expecting value: line 1 column 1 (char 0) ASSISTANT-GPT THOUGHTS: REASONING: CRITICISM: Warning: Failed to parse AI output, attempting to fix. If you see this warning frequently, it's likely that your prompt is confusing the AI. Try changing it up slightly. Failed to fix ai output, telling the AI.

I think it is related to this: openai/openai-python#332

I get this error only with some AI. If I change the role and goals, I do not get the error. But for some AI and role it does not work.

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Perhaps "only respond in JSON" could be added to the system message?

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It doesn't work?

I am also getting the same error

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Got the same error

from auto-gpt.

Getting the same error....

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Got the same error

from auto-gpt.

There might be several different things happening here. When I get 'Invalid JSON' it is always because of a prior problem, so that the returned value from ChatGPT-4 looks like this;

My apologies, here is the correct version: { "thoughts": { "text": "....

And that is actually correct. JSON should not start with the string "My apologies, here is the correct version: ".

So this should be an easy fix, but I have just started peeking at this so don't know if this is configurable by me or must be fixed deeper inside something.

from auto-gpt.

same here using the --gpt3only option.

as soon as autogpt wants to get results from a webpage or google it will run into an json error

`
ai_goals:
check the market for handmade candles
shut down when finished
ai_name: test
ai_role: market research

`

from auto-gpt.

Unfortunately gpt does not always stick to the right format when replying, sometimes adding something at the beginning, sometimes replying in plain text, and sometimes json is just broken. To try to restore the format in some cases I added this code after line 309 in main.py locally:

are you sure with line 309?
if I add your code after line 310 i'll get this error message

Traceback (most recent call last):
File "C:\GTP-Helpers\Auto-GPT\scripts\main.py", line 314, in
json.loads(assistant_reply)
^^^^^^^^^^^^^^^
NameError: name 'assistant_reply' is not defined

from auto-gpt.

Sorry to bother you :-)

if I insert the code i get an error message immediately

sorry, i am a total noob regarding python :-)

S C:\GTP-Helpers\Auto-GPT> python scripts/main.py --gpt3only --continuous
File "C:\GTP-Helpers\Auto-GPT\scripts\main.py", line 405
break
^^^^^
SyntaxError: 'break' outside loop

the code looks like this

`
cfg.fast_token_limit) # TODO: This hardcodes the model to use GPT3.5. Make this an argument

try:
json.loads(assistant_reply)
except ValueError as e:
if assistant_reply.count('{') == assistant_reply.count('}') == 0:
# remove " and '
assistant_reply = assistant_reply.replace('"', '').replace("'", '')
assistant_reply = '{'
'"thoughts": {'
'"text": "' + assistant_reply + '",'
'"reasoning": "",'
'"plan": "",'
'"criticism": "",'
'"speak": ""'
'},'
'"command": {'
'"name": "do_nothing", "args": {}'
'}'
'}'
elif assistant_reply.count('{') == assistant_reply.count('}'):
# remove everything before the first { and after the last }
assistant_reply = assistant_reply[assistant_reply.find('{'):assistant_reply.rfind('}') + 1]
else:
while assistant_reply.count('{') != assistant_reply.count('}'):
if assistant_reply.count('{') > assistant_reply.count('}'):
# add a } to the end
assistant_reply = assistant_reply + '}'
else:
# add a { to the beginning
assistant_reply = '{' + assistant_reply

# Print Assistant thoughts`

from auto-gpt.

SyntaxError: 'break' outside loop

I think you put the code in without an indent. Because of this the interpreter thinks that this code is not in the loop body, but after it, and all further code of the loop is also no longer in the loop and with an extra indent. Select the whole pasted piece and press tab (each line should move 4 spaces to the right)

THIS IS RIGHT:

# All code in the loop
while True:
    # Some code before
    # PASTE CODE HERE
    # Some code after

THAT'S NOT RIGHT:

while True:
    # Some code before - This is the only line in the loop
# PASTE CODE HERE - This line is no longer in the loop, but after the loop
    # Some code after - This line is also not in the loop and the indent is wrong before it

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Hi Justin,

thanks a lot for your overwhelming support.

I pulled the latest source code updates a few hours ago and it seems to work.
There have not been any json errors anymore in the past hours of messing around with autogpt

from auto-gpt.

Invalid JSON are as old as the planet. For me they are a constant in AutoGPT dont bother as long as he can continue where he left off once he crashes or i exit him and continue later.

from auto-gpt.

I'm getting loads of Invalid JSON errors in my project, which involves trying to read a local PDF file and extract particular text from it. Whenever it gets the error, it displays the problematic JSON in raw form, and then fails to carry out the task it describes. However, it seems unaware that it didn't carry out the task, and proceeds as if it worked.
In my case, I got most of the errors when it was trying to correct a .py code file it generated.

from auto-gpt.

Still getting this error.

from auto-gpt.

Unfortunately gpt does not always stick to the right format when replying, sometimes adding something at the beginning, sometimes replying in plain text, and sometimes json is just broken. To try to restore the format in some cases I added this code after line 324 in main.py locally:

try:
    json.loads(assistant_reply)
except ValueError as e:
    if assistant_reply.count('{') == assistant_reply.count('}') == 0:
        # remove " and '
        assistant_reply = assistant_reply.replace('"', '').replace("'", '')
        assistant_reply = '{' \
                              '"thoughts": {' \
                                  '"text": "' + assistant_reply + '",' \
                                  '"reasoning": "",' \
                                  '"plan": "",' \
                                  '"criticism": "",' \
                                  '"speak": ""' \
                              '},' \
                              '"command": {' \
                                  '"name": "do_nothing", "args": {}' \
                              '}' \
                          '}'
    elif assistant_reply.count('{') == assistant_reply.count('}'):
        # remove everything before the first { and after the last }
        assistant_reply = assistant_reply[assistant_reply.find('{'):assistant_reply.rfind('}') + 1]
    else:
        while assistant_reply.count('{') != assistant_reply.count('}'):
            if assistant_reply.count('{') > assistant_reply.count('}'):
                # add a } to the end
                assistant_reply = assistant_reply + '}'
            else:
                # add a { to the beginning
                assistant_reply = '{' + assistant_reply

Maybe it will help someone

it works!

from auto-gpt.

I also get this error

CRITICISM: I need to make sure that the information provided by Google Search is trustworthy by verifying it with other sources.
Attempting to fix JSON by finding outermost brackets
Apparently json was fixed.

and

"Error: Invalid JSON
In order to generate the next command JSON, I need to know more about the current task. Can you provide me with more context and a description of what you would like to accomplish?
Attempting to fix JSON by finding outermost brackets
Error: Invalid JSON, setting it to empty JSON now."

from auto-gpt.

same issue

from auto-gpt.

same issue

from auto-gpt.

Still getting this error.

from auto-gpt.

Same here. Win 10 using --gpt3only

from auto-gpt.

awaiting fix as well.

from auto-gpt.

Does this error only occur with GPT 3.5?

from auto-gpt.

Same issue here: Error: Invalid JSON, setting it to empty JSON now. Anyone knows why？

from auto-gpt.

I'm not familiar with the repo. but what if you ask chatGPT to fix the JSON for you again? and strictly mention to it to only respond in JSON.

from auto-gpt.

I've tried several approaches to get it to fix the response but nothing has worked.

from auto-gpt.

Also not working here when the response contains code. I think there is a conflict because the AI is being told always to respond in JSON format. When asked to produce code, the JSON returned does not comply to the schema.
Example:

User: use what you have learned about the ProcessWire API to create a blank module with name ErrorLogger

Response Original JSON:

{
   public static function getModuleInfo() {
       return array(
           'title' => 'ErrorLogger',
           'version' => 1,
           'summary' => 'Logs site errors',
           'autoload' => true,
       );
   }
   
   public function init() {
       // initialization logic
   }
}

Fixed JSON: There seems to be two separate code snippets provided. Please clarify which one you want me to fix.
Failed to fix AI output, telling the AI.
Error: Invalid JSON

So all the curly braces are confusing the AI when trying to fix the JSON.

I think the instructions to always reply in JSON need to be fixed in a way that when AI replies with code, the code should be escaped in a way that doesn't break the JSON syntax. Just my thinking. I am not sure if my assumptions are correct and I also wouldn't know how to fix this.

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Can we do something like send the response to an agent and ask it convert the response to json

from auto-gpt.

Investigating this further, I found that markdown code in the ai reponse that marks multi line code with "```" (3 backticks) causes confusion when parsing the response. maybe fix_and_parse_json in scripts/json_parser.py needs to be amended.

Here's an example response that caused trouble:

Sure, here is a Python function using the dictionary that maps file extensions to programming languages. The function expects a file path as input and returns a dict object containing the file name, path, extension and programming language of the file.
```
def get_file_type(file_path):
    from pathlib import Path
    file_path = Path(file_path)
    file = {}
    file['path'] = str(file_path.parent)
    file['name'] = file_path.name
    file['extension'] = file_path.suffix
    if file_path.suffix in extensions_dict.keys():
        file['type'] = extensions_dict[file_path.suffix]
    else:
        file['type'] = 'Unknown'  
    return file
```

from auto-gpt.

Would it be possible to please add reference to the function this should appear in/before/after? In my main.py (scripts), at line 324 I have

def __init__(self, ai_name, memory, full_message_history, next_action_count, prompt, user_input): self.ai_name = ai_name self.memory = memory self.full_message_history = full_message_history self.next_action_count = next_action_count self.prompt = prompt self.user_input = user_input

from auto-gpt.

Where

Unfortunately gpt does not always stick to the right format when replying, sometimes adding something at the beginning, sometimes replying in plain text, and sometimes json is just broken. To try to restore the format in some cases I added this code after line 324 in main.py locally:

try:
    json.loads(assistant_reply)
except ValueError as e:
    if assistant_reply.count('{') == assistant_reply.count('}') == 0:
        # remove " and '
        assistant_reply = assistant_reply.replace('"', '').replace("'", '')
        assistant_reply = '{' \
                              '"thoughts": {' \
                                  '"text": "' + assistant_reply + '",' \
                                  '"reasoning": "",' \
                                  '"plan": "",' \
                                  '"criticism": "",' \
                                  '"speak": ""' \
                              '},' \
                              '"command": {' \
                                  '"name": "do_nothing", "args": {}' \
                              '}' \
                          '}'
    elif assistant_reply.count('{') == assistant_reply.count('}'):
        # remove everything before the first { and after the last }
        assistant_reply = assistant_reply[assistant_reply.find('{'):assistant_reply.rfind('}') + 1]
    else:
        while assistant_reply.count('{') != assistant_reply.count('}'):
            if assistant_reply.count('{') > assistant_reply.count('}'):
                # add a } to the end
                assistant_reply = assistant_reply + '}'
            else:
                # add a { to the beginning
                assistant_reply = '{' + assistant_reply

Maybe it will help someone

I can confirm this has worked :)

Where on earth do you put this in the latest build??

from auto-gpt.

Would it be possible to please add reference to the function this should appear in/before/after? In my main.py (scripts), at line 324 I have
def __init__(self, ai_name, memory, full_message_history, next_action_count, prompt, user_input): self.ai_name = ai_name self.memory = memory self.full_message_history = full_message_history self.next_action_count = next_action_count self.prompt = prompt self.user_input = user_input

Hi @OutofscopeLabs, at this version (commit #13ba2e8). The location is at Line 351. Hope it helps :).

Thank you @MrPeterJin, that did the trick :)

from auto-gpt.

Since line numbers change fairly often, it's better to provide reference with before or after something. That way folks can see where to make the change on whichever current commit their using.

from auto-gpt.

I don't think the above problem is related to JSON, but instead that you need to create a personal API key for google search; https://programmablesearchengine.google.com/controlpanel/all

from auto-gpt.

Apparently json was fixed. Request failed with status code: 400 Response content: b'{"detail":{"status":"invalid_uid","message":"An invalid ID has been received: 'Voice 1-Soldiers Dream'. Make sure to provide a correct one."}}'

I have the exactly the same problem. Have you solved it?

from auto-gpt.

What does the assistant_reply variable store?

assistant_reply

from auto-gpt.

是否可以添加对应该出现在/之前/之后的功能的引用？在我的 main.py（脚本）中，在第 324 行我有
def __init__(self, ai_name, memory, full_message_history, next_action_count, prompt, user_input): self.ai_name = ai_name self.memory = memory self.full_message_history = full_message_history self.next_action_count = next_action_count self.prompt = prompt self.user_input = user_input

你好@OutofscopeLabs，在此版本（提交#13ba2e8）。地点在351号线。希望能帮助到你 ：）。

谢谢@MrPeterJin, 成功了:)

Can you send the full code？

from auto-gpt.

我解决了这个问题。只需将开始提示更改为“开始。注意仅以 JSON 格式响应。根据您的目标设计您自己的广告系列。” 而不是“NEXT COMMAND”或类似的东西。并稍微加强提示应该得到你需要的结果。

Can you explain how it works？

from auto-gpt.

I'm using a Project Manager that starts agents per project and keeps track of each project in a subfolder, but the folders it creates are named 'project_name/results' instead of the actual project name, like it is using the variable name instead of the variable value
NEXT ACTION: COMMAND = append_to_file ARGUMENTS = {'file': 'project_name/results/promotion_ideas.txt',

from auto-gpt.

Still present in v0.2.1 running on continuous mode.

Let me know if I can provide any useful information 🌱

UPDATE: I added a debugging line right into autogpt/llm_utils.py to see what it's sending/receiving to/from the openai library. I got this:

Sending messages to OpenAI API:

[{'role': 'system', 'content': "You are now the following python function: 
# This function takes a JSON string and ensures that it is parseable and fully compliant with the provided schema. If an object or field specified in the schema isn't contained within the correct JSON, it is omitted. The function also escapes any double quotes within JSON string values to ensure that they are valid. If the JSON string contains any None or NaN values, they are replaced with null before being parsed.\ndef fix_json(json_string: str, schema:str=None) -> str:
\n\nOnly respond with your `return` value."}, {'role': 'user', 'content': '\'\'\'I apologize for the errors. Here is my response:\n\nBased on the results of the "google" command, I think the next step should be to browse the W3C website to learn more about Linked Data and the Semantic Web. We can use the "browse_website" command for this.\'\'\', \'\'\'\n{\n    "command": {\n        "name": "command name",\n        "args": {\n            "arg name": "value"\n        }\n    },\n    "thoughts":\n    {\n        "text": "thought",\n        "reasoning": "reasoning",\n        "plan": "- short bulleted\n- list that conveys\n- long-term plan",\n        "criticism": "constructive self-criticism",\n        "speak": "thoughts summary to say to user"\n    }\n}\n\'\'\''}]

Received response from OpenAI API:

{
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "message": {
        "content": "I'm sorry, but your response seems to be a combination of two different things. The first part seems to be a response to a previous question, while the second part is a JSON object. Can you please clarify what you are looking for?",
        "role": "assistant"
      }
    }
  ],
  "created": 1681703516,
  "id": "chatcmpl-76ACCtbpjwKGgbFkvGA0GrdYg7brA",
  "model": "gpt-3.5-turbo-0301",
  "object": "chat.completion",
  "usage": {
    "completion_tokens": 49,
    "prompt_tokens": 296,
    "total_tokens": 345
  }
}

Hope this helps

from auto-gpt.

some problems with escaping in string values. looks like due to prompts(initial or generated ones). we should add checks and escaping for strings

Today, I got an "invalid JSON" error as well. It seems to be related to escaping characters in the text I gave it, most likely related to the local filepaths I gave it (C:\Users\User\Downloads\silicon's_big_dig.mp4). Ironically, I used GPT-4 to arrive at this conclusion by analyzing the copy-pasted error message below. Below is the copy-pasted output from Auto-GPT's console:

  {
    "thoughts": {
        "text": "I will browse the website 'https://www.howtogeek.com/868512/how-to-ai-upscale-an-image-or-video-8-best-tools/' to learn more about Topaz Video AI and see if it can interface with ffmpeg in a command.",
        "reasoning": "Topaz Video AI is one of the best video upscaling tools available, and I want to see if it can be used with ffmpeg to upscale the video and remove compression artifacts.",
        "plan": "- Browse the website 'https://www.howtogeek.com/868512/how-to-ai-upscale-an-image-or-video-8-best-tools/' to learn more about Topaz Video AI and see if it can interface with ffmpeg in a command\\n- If Topaz Video AI can be used with ffmpeg, develop the ffmpeg command\\n- If Topaz Video AI cannot be used with ffmpeg, continue researching other AI upscaling methods that can be used with ffmpeg\\n- Once I have found a suitable AI upscaling method, develop the ffmpeg command\\n- Run the ffmpeg command on the file \\"C:\\\\Users\\\\User\\\\Downloads\\\\silicon\'s_big_dig.mp4\\" and output the file in \\"C:\\\\Users\\\\User\\\\Downloads\\\\ffmpeg_test_output\\\\\\"\\n- Create a 2x5 mosaic screenshot of points throughout the original video and the new video. Make sure it\'s in png format.",
        "criticism": "I need to make sure that Topaz Video AI can be used with ffmpeg before I develop the ffmpeg command. If it cannot be used with ffmpeg, I need to continue researching other AI upscaling methods that can be used with ffmpeg.",
        "speak": "I will browse the website 'https://www.howtogeek.com/868512/how-to-ai-upscale-an-image-or-video-8-best-tools/' to learn more about Topaz Video AI and see if it can interface with ffmpeg in a command."
    },
    "command": {
        "name": "browse_website",
        "args": {
            "url": "https://www.howtogeek.com/868512/how-to-ai-upscale-an-image-or-video-8-best-tools/",
            "question": "Can Topaz Video AI be used with ffmpeg?"
        }
    }
}```

from auto-gpt.

没错，这里有一个更好的参考：

def start_interaction_loop(self):
        # Interaction Loop
        loop_count = 0
        while True:
             # Discontinue if continuous limit is reached
            loop_count += 1
            if cfg.continuous_mode and cfg.continuous_limit > 0 and loop_count > cfg.continuous_limit:
                logger.typewriter_log("Continuous Limit Reached: ", Fore.YELLOW, f"{cfg.continuous_limit}")
                break

            # Send message to AI, get response
            with Spinner("Thinking... "):
                assistant_reply = chat.chat_with_ai(
                    self.prompt,
                    self.user_input,
                    self.full_message_history,
                    self.memory,
                    cfg.fast_token_limit)  # TODO: This hardcodes the model to use GPT3.5. Make this an argument

            try:
                json.loads(assistant_reply)
            except ValueError as e:
                if assistant_reply.count('{') == assistant_reply.count('}') == 0:
                    # remove " and '
                    assistant_reply = assistant_reply.replace('"', '').replace("'", '')
                    assistant_reply = '{' \
                                        '"thoughts": {' \
                                            '"text": "' + assistant_reply + '",' \
                                            '"reasoning": "",' \
                                            '"plan": "",' \
                                            '"criticism": "",' \
                                            '"speak": ""' \
                                        '},' \
                                        '"command": {' \
                                            '"name": "do_nothing", "args": {}' \
                                        '}' \
                                    '}'
                elif assistant_reply.count('{') == assistant_reply.count('}'):
                    # remove everything before the first { and after the last }
                    assistant_reply = assistant_reply[assistant_reply.find('{'):assistant_reply.rfind('}') + 1]
                else:
                    while assistant_reply.count('{') != assistant_reply.count('}'):
                        if assistant_reply.count('{') > assistant_reply.count('}'):
                            # add a } to the end
                            assistant_reply = assistant_reply + '}'
                        else:
                            # add a { to the beginning
                            assistant_reply = '{' + assistant_reply
            
            # Print Assistant thoughts
            print_assistant_thoughts(assistant_reply)

功能继续，顺便说一句。

Where is this added?

from auto-gpt.

after seeing this window, then flashback, nothing left. Anyone knows what's wrong?

from auto-gpt.

after seeing this window, then flashback, nothing left. Anyone knows what's wrong?

try putting an empty file AutoGpt.json in the root of your project. In previous versions this helped.

from auto-gpt.

start_interaction_loop

https://github.com/Significant-Gravitas/Auto-GPT/blob/4c2a566acc37c8d95b07c023f8c52a1a2a5d15bf/autogpt/__main__.py#L49

from auto-gpt.

getting the same error:
Input:use your informations you gathered to discuss this question 'How can machine learning and other advanced technologies be leveraged to improve the accuracy and reliability of personalized geospatial conditional planning?'. Write in a text file all your informations, and explain everything so i can understand it and create a presentation from it
SYSTEM: Human feedback: use your informations you gathered to discuss this question 'How can machine learning and other advanced technologies be leveraged to improve the accuracy and reliability of personalized geospatial conditional planning?'. Write in a text file all your informations, and explain everything so i can understand it and create a presentation from it
Warning: Failed to parse AI output, attempting to fix.
If you see this warning frequently, it's likely that your prompt is confusing the AI. Try changing it up slightly.
Failed to fix AI output, telling the AI.
Error: Invalid JSON
After conducting research on the topic of Personalized Geospatial Conditional Planning for Daily Activities, I have found that machine learning and other advanced technologies can be leveraged to improve the accuracy and reliability of personalized geospatial conditional planning.

One paper I found, titled "Personalized Geospatial Conditional Planning for Daily Activities: A Review of the Literature and Future Directions" by Li et al. (2019), discusses the use of machine learning and other advanced technologies in personalized geospatial conditional planning. The paper notes that personalized geospatial conditional planning involves predicting an individual's future activities based on their past activities and the context of their current situation. Machine learning algorithms can be used to analyze large amounts of data on an individual's past activities and the context of their current situation to make accurate predictions about their future activities.

Another paper I found, titled "A Machine Learning Approach to Personalized Geospatial Conditional Planning" by Zhang et al. (2020), discusses the use of machine learning algorithms to improve the accuracy of personalized geospatial conditional planning. The paper proposes a machine learning approach that uses a combination of decision trees and random forests to predict an individual's future activities based on their past activities and the context of their current situation. The approach was found to be more accurate than traditional methods of personalized geospatial conditional planning.

In addition to machine learning, other advanced technologies can also be leveraged to improve the accuracy and reliability of personalized geospatial conditional planning. For example, Li et al. (2019) note that the use of wearable devices and other sensors can provide additional data on an individual's current situation, which can be used to make more accurate predictions about their future activities. The use of augmented reality and virtual reality technologies can also provide individuals with more accurate and reliable information about their surroundings, which can improve their ability to plan and carry out daily activities.

Overall, the use of machine learning and other advanced technologies can greatly improve the accuracy and reliability of personalized geospatial conditional planning. By analyzing large amounts of data on an individual's past activities and the context of their current situation, machine learning algorithms can make accurate predictions about their future activities. In addition, the use of wearable devices, sensors, and other advanced technologies can provide additional data on an individual's current situation, which can be used to make more accurate predictions. The use of augmented reality and virtual reality technologies can also provide individuals with more accurate and reliable information about their surroundings, which can improve their ability to plan and carry out daily activities.
Attempting to fix JSON by finding outermost brackets
Error: Invalid JSON, setting it to empty JSON now.

THOUGHTS: None
REASONING: None
CRITICISM: None
SPEAK: None
Attempting to fix JSON by finding outermost brackets
Error: Invalid JSON, setting it to empty JSON now.

from auto-gpt.

agent.start_interaction_loop()

Does the use of agent.start_interaction_loop() provide the full code？

from auto-gpt.

I am getting the same error as #2229 but that has been linked to this one and closed down so will add here.

Error log,

2023-04-21 12:22:28,198 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: Command message_agent returned: Before we proceed with the step-by-step guide, let's make sure we have all the necessary information. Can you provide more details on what specific areas you would like to cover in the guide? For example, do you want to cover how to create a new worker, how to update worker information, or both? This will help us determine the next command to use. 2023-04-21 12:24:05,764 ERROR logs:_log:120 The JSON object is invalid. 2023-04-21 12:24:46,359 ERROR logs:_log:120 The JSON object is invalid. 2023-04-21 12:25:17,599 ERROR logs:_log:120 The JSON object is invalid. 2023-04-21 12:25:51,930 ERROR logs:_log:120 The JSON object is invalid. 2023-04-21 12:32:11,142 ERROR logs:_log:120 The JSON object is invalid. 2023-04-21 12:45:38,035 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: My apologies for the confusion. Please use the "browse_website" command to find more information on how to set up positions and jobs in Microsoft Dynamics 365 Finance and Operations Human Resource. You can then use the information gathered to create a section on how to set up positions and jobs in the guide using the "write_to_file" command. 2023-04-21 12:45:54,282 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: I apologize for the error message. Please use the "browse_website" command to find more information on how to set up positions and jobs in Microsoft Dynamics 365 Finance and Operations Human Resource. You can then use the information gathered to create a section on how to set up positions and jobs in the guide using the "write_to_file" command. 2023-04-21 12:46:07,214 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: I apologize for the repeated error message. Please use the "browse_website" command to find more information on how to set up positions and jobs in Microsoft Dynamics 365 Finance and Operations Human Resource. You can then use the information gathered to create a section on how to set up positions and jobs in the guide using the "write_to_file" command. 2023-04-21 12:46:19,272 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: I apologize for the repeated error message. Please use the "browse_website" command to find more information on how to set up positions and jobs in Microsoft Dynamics 365 Finance and Operations Human Resource. You can then use the information gathered to create a section on how to set up positions and jobs in the guide using the "write_to_file" command. 2023-04-21 12:46:30,421 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: I apologize for the repeated error message. Please use the "browse_website" command to find more information on how to set up positions and jobs in Microsoft Dynamics 365 Finance and Operations Human Resource. You can then use the information gathered to create a section on how to set up positions and jobs in the guide using the "write_to_file" command. 2023-04-21 12:46:46,005 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: I apologize for the repeated error message. Please use the "browse_website" command to find more information on how to set up positions and jobs in Microsoft Dynamics 365 Finance and Operations Human Resource. You can then use the information gathered to create a section on how to set up positions and jobs in the guide using the "write_to_file" command. 2023-04-21 12:46:56,761 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: I apologize for the repeated error message. Please use the "browse_website" command to find more information on how to set up positions and jobs in Microsoft Dynamics 365 Finance and Operations Human Resource. You can then use the information gathered to create a section on how to set up positions and jobs in the guide using the "write_to_file" command. 2023-04-21 12:47:07,420 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: I apologize for the repeated error message. Please use the "browse_website" command to find more information on how to set up positions and jobs in Microsoft Dynamics 365 Finance and Operations Human Resource. You can then use the information gathered to create a section on how to set up positions and jobs in the guide using the "write_to_file" command. 2023-04-21 12:47:19,007 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: I apologize for the repeated error message. Please use the "browse_website" command to find more information on how to set up positions and jobs in Microsoft Dynamics 365 Finance and Operations Human Resource. You can then use the information gathered to create a section on how to set up positions and jobs in the guide using the "write_to_file" command. 2023-04-21 12:47:30,471 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: I apologize for the repeated error message. Please use the "browse_website" command to find more information on how to set up positions and jobs in Microsoft Dynamics 365 Finance and Operations Human Resource. You can then use the information gathered to create a section on how to set up positions and jobs in the guide using the "write_to_file" command. 2023-04-21 12:47:42,365 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: I apologize for the repeated error message. Please use the "browse_website" command to find more information on how to set up positions and jobs in Microsoft Dynamics 365 Finance and Operations Human Resource. You can then use the information gathered to create a section on how to set up positions and jobs in the guide using the "write_to_file" command. 2023-04-21 12:47:54,754 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: I apologize for the repeated error message. Please use the "browse_website" command to find more information on how to set up positions and jobs in Microsoft Dynamics 365 Finance and Operations Human Resource. You can then use the information gathered to create a section on how to set up positions and jobs in the guide using the "write_to_file" command. 2023-04-21 12:48:06,825 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: I apologize for the repeated error message. Please use the "browse_website" command to find more information on how to set up positions and jobs in Microsoft Dynamics 365 Finance and Operations Human Resource. You can then use the information gathered to create a section on how to set up positions and jobs in the guide using the "write_to_file" command. 2023-04-21 13:22:31,032 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: Command message_agent returned: Please provide the next task for the dynamics_hr_workers_gpt_agent. 2023-04-21 13:22:53,668 ERROR logs:_log:120 The JSON object is invalid. 2023-04-21 13:23:13,953 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: Command browse_website returned: ("Answer gathered from website: The article provides instructions on how to create a position in Microsoft Dynamics 365 Human Resources, including selecting a job, department, position type, compensation region, and reports to position. It also covers setting up worker assignments, relationships, payroll, labor unions, and financial dimensions. The functionality described is currently available in both the stand-alone Dynamics 365 Human Resources and the merged Finance infrastructure. \\n \\n Links: [\'Skip to main content (https://learn.microsoft.com/en-us/dynamics365/human-resources/hr-personnel-set-up-positions#main)\', \'Privacy Statement (https://go.microsoft.com/fwlink/?LinkId=521839)\', \'Third-Party Cookies (https://aka.ms/3rdpartycookies)\', \'\\\\nRegister now\\\\n\\\\n\\\\n\\\\n (https://aka.ms/DocsPreEvent)\', \'\\\\nDownload Microsoft Edge\\\\t\\\\t\\\\t\\\\t\\\\t (https://go.microsoft.com/fwlink/p/?LinkID=2092881 )\']") 2023-04-21 13:23:33,157 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: Command browse_website returned: ("Answer gathered from website: The article provides instructions on how to create a position in Microsoft Dynamics 365 Human Resources, including selecting a job, department, position type, compensation region, and reports to position. It also covers setting up worker assignments, relationships, payroll, labor unions, and financial dimensions. The functionality described is currently available in both the stand-alone Dynamics 365 Human Resources and the merged Finance infrastructure. \\n \\n Links: [\'Skip to main content (https://learn.microsoft.com/en-us/dynamics365/human-resources/hr-personnel-set-up-positions#main)\', \'Privacy Statement (https://go.microsoft.com/fwlink/?LinkId=521839)\', \'Third-Party Cookies (https://aka.ms/3rdpartycookies)\', \'\\\\nRegister now\\\\n\\\\n\\\\n\\\\n (https://aka.ms/DocsPreEvent)\', \'\\\\nDownload Microsoft Edge\\\\t\\\\t\\\\t\\\\t\\\\t (https://go.microsoft.com/fwlink/p/?LinkID=2092881 )\']") 2023-04-21 13:23:52,729 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: Command browse_website returned: ("Answer gathered from website: The article provides instructions on how to create a position in Microsoft Dynamics 365 Human Resources, including selecting a job, department, position type, compensation region, and reports to position. It also covers setting up worker assignments, relationships, payroll, labor unions, and financial dimensions. The functionality described is currently available in both the stand-alone Dynamics 365 Human Resources and the merged Finance infrastructure. \\n \\n Links: [\'Skip to main content (https://learn.microsoft.com/en-us/dynamics365/human-resources/hr-personnel-set-up-positions#main)\', \'Privacy Statement (https://go.microsoft.com/fwlink/?LinkId=521839)\', \'Third-Party Cookies (https://aka.ms/3rdpartycookies)\', \'\\\\nRegister now\\\\n\\\\n\\\\n\\\\n (https://aka.ms/DocsPreEvent)\', \'\\\\nDownload Microsoft Edge\\\\t\\\\t\\\\t\\\\t\\\\t (https://go.microsoft.com/fwlink/p/?LinkID=2092881 )\']") 2023-04-21 13:24:10,937 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: Command browse_website returned: ("Answer gathered from website: The article provides instructions on how to create a position in Microsoft Dynamics 365 Human Resources, including selecting a job, department, position type, compensation region, and reports to position. It also covers setting up worker assignments, relationships, payroll, labor unions, and financial dimensions. The functionality described is currently available in both the stand-alone Dynamics 365 Human Resources and the merged Finance infrastructure. \\n \\n Links: [\'Skip to main content (https://learn.microsoft.com/en-us/dynamics365/human-resources/hr-personnel-set-up-positions#main)\', \'Privacy Statement (https://go.microsoft.com/fwlink/?LinkId=521839)\', \'Third-Party Cookies (https://aka.ms/3rdpartycookies)\', \'\\\\nRegister now\\\\n\\\\n\\\\n\\\\n (https://aka.ms/DocsPreEvent)\', \'\\\\nDownload Microsoft Edge\\\\t\\\\t\\\\t\\\\t\\\\t (https://go.microsoft.com/fwlink/p/?LinkID=2092881 )\']") 2023-04-21 13:25:14,285 ERROR logs:_log:120 Error: The following AI output couldn't be converted to a JSON: Command browse_website returned: ("Answer gathered from website: The article provides instructions on how to create a position in Microsoft Dynamics 365 Human Resources, including selecting a job, department, position type, compensation region, and reports to position. It also covers setting up worker assignments, relationships, payroll, labor unions, and financial dimensions. The functionality described is currently available in both the stand-alone Dynamics 365 Human Resources and the merged Finance infrastructure. \\n \\n Links: [\'Skip to main content (https://learn.microsoft.com/en-us/dynamics365/human-resources/hr-personnel-set-up-positions#main)\', \'Privacy Statement (https://go.microsoft.com/fwlink/?LinkId=521839)\', \'Third-Party Cookies (https://aka.ms/3rdpartycookies)\', \'\\\\nRegister now\\\\n\\\\n\\\\n\\\\n (https://aka.ms/DocsPreEvent)\', \'\\\\nDownload Microsoft Edge\\\\t\\\\t\\\\t\\\\t\\\\t (https://go.microsoft.com/fwlink/p/?LinkID=2092881 )\']")

was working ok and chugging away nicely then this just appeared and just keeps getting stuck in a rut about it.

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Not sure exactly where this issue stands, but wanted to pop in here to show how langchain is using this in their pedantic parser: https://github.com/hwchase17/langchain/blob/master/langchain/output_parsers/pydantic.py

The PydanticOutputParser class is a subclass of BaseOutputParser and is responsible for parsing text output into Pydantic objects. Pydantic is a Python library for data validation and settings management using Python type annotations. This class takes in a Pydantic object as a type parameter and uses it to parse the text output.

The parse method takes in a string of text and attempts to extract a JSON object from it. It does this by using a regular expression to search for the first JSON candidate in the text. If a JSON object is found, it is loaded into a Python object using the json.loads method. The Pydantic object is then parsed from the Python object using the parse_obj method. If the text cannot be parsed into a Pydantic object, an OutputParserException is raised.

The get_format_instructions method returns a string of format instructions for the Pydantic object. It does this by getting the schema of the Pydantic object using the schema method and removing extraneous fields such as title and type. The schema is then converted to a JSON string and returned as part of a larger string of format instructions.

Overall, this class provides a way to parse text output into Pydantic objects, which can then be used for data validation and settings management. This is useful in the larger project because it allows for consistent handling of output data and ensures that the data conforms to a specific schema. Here is an example of how this class might be used:

from langchain.output_parsers import PydanticOutputParser
from my_project.schemas import MyPydanticSchema

output_parser = PydanticOutputParser[MyPydanticSchema]()
text_output = "{'field1': 'value1', 'field2': 'value2'}"
parsed_output = output_parser.parse(text_output)

In this example, MyPydanticSchema is a Pydantic object that defines the schema for the expected output. The PydanticOutputParser is instantiated with MyPydanticSchema as the type parameter, and the parse method is called with a string of text output. The resulting parsed_output variable is a Pydantic object that conforms to the schema defined by MyPydanticSchema.

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As of v0.2.2 the issue still persists, with a twist. JSON is fixed, or maybe not!

SYSTEM:  Command write_to_file returned: Error: File has already been updated.
Apparently json was fixed.
The JSON object is invalid.
 THOUGHTS:  None
REASONING:  None
CRITICISM:  None
NEXT ACTION:  COMMAND = Error: ARGUMENTS = Missing 'command' object in JSON
SYSTEM:  Command Error: threw the following error: Missing 'command' object in JSON

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still get the issue with the latest

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Error: The following AI output couldn't be converted to a JSON:
  Please use the 'google' command to search for more information on the

so yes, the problem is still there.``

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The problem here is not just that it fails, it's that when it fails in this way, it usually gets stuck in a loop and there's no way to rescue it. when it gets an error at this level it doesn't appear to go back to the ai endpoint for advice, it just keeps trying over and over again without any new input.

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Any news about Error: The following AI output couldn't be converted to a JSON:?

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confirming, saw this today when letting it generate C++ code - at some point, the engine bailed out complaining that the JSON wasn't valid.
However, once thing to be checked first is probably ensuring that this is not due to token/context size limit, i.e. the JSON being cut off because of that - which would render it "invalid" obviously.

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https://github.com/1rgs/jsonformer

https://twitter.com/rahulgs/status/1653157725025566720

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Maybe it makes sense to have a more lenient JSON parser that allows for things like dangling commas, comments, or other such oddities. I think for now theres always going to be a chance that the model responds with something that isn't JSON and as such it should be possible to account for that (to an extent).

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Could try parsing it with a JS parser instead of JSON. Actual JS objects have more flexibility than JSON, or maybe using a JSON5/6 parser?

An example solution written in PowerShell (with NodeJS as the JS parser):

$tmpJSONcontents = ConvertFr-Json( Get-Content $jsonFile )

@"
let obj = $tmpJSONcontents
console.log( obj )
"@ | Out-File "temp.js"

node temp.js

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There's an RFE by @Pwuts himself already, so the project/core devs are more than aware of LMQL already: #3460
LMQL is also mentioned by another RFE he created as being a potentially significant improvement:

• #3536

I suppose, the discussion (offers to get involved helping) should rather continue there.

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https://github.com/ShreyaR/guardrails

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What was helping me was comment the following lines in .env:

SMART_LLM_MODEL=gpt-3.5-turbo
FAST_LLM_MODEL=gpt-3.5-turbo

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Closing as duplicate of #1407

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