How to get AutoGPT to execute python and do data analysis?

[dw61]

I asked autoGPT to read csv and analyze using python pandas. it read csv and created a python file but can't run it.

2024-04-03 17:25:22,652 INFO  NEXT ACTION: COMMAND = write_file  ARGUMENTS = {'filename': 'address_normalization_instructions.txt', 'contents': '### Address Normalization Guide\n#### Objective:\nTo normalize apartment addresses for accurate grouping and analysis.\n\n#### Common Address Abbreviations and Equivalents:\n- JPA --> Jefferson Park Ave\n- W Main --> West Main Street\n- E Market --> East Market Street\n\n#### Steps for Normalization:\n1. Identify and list all unique addresses in the dataset.\n2. For each address, apply the common abbreviations and equivalents to normalize the format.\n3. Replace the original address in the dataset with the normalized version.\n\n**Note:** This guide provides a starting point. Adjustments may be necessary based on further dataset specifics.'}

2024-04-03 17:32:02,421 INFO  REASONING: Although the user instructed to 'just do it', operational constraints prevent direct code execution or data manipulation tasks. The ideal approach would involve using pandas dataframes and Google Places API, but given the constraints, providing a detailed conceptual framework is the most pragmatic solution. This might involve outlining steps for manual execution, simulating a potential analysis outcome.

this is my .env file setup, I thought it would ask me for google maps API key. but it couldn't even execute python.

## TELEMETRY_OPT_IN - Share telemetry on errors and other issues with the AutoGPT team, e.g. through Sentry.
##   This helps us to spot and solve problems earlier & faster. (Default: DISABLED)
TELEMETRY_OPT_IN=false

## EXECUTE_LOCAL_COMMANDS - Allow local command execution (Default: False)
EXECUTE_LOCAL_COMMANDS=False

### Workspace ###

## RESTRICT_TO_WORKSPACE - Restrict file operations to workspace ./data/agents/<agent_id>/workspace (Default: True)
# RESTRICT_TO_WORKSPACE=True

## DISABLED_COMMAND_CATEGORIES - The list of categories of commands that are disabled (Default: None)
# DISABLED_COMMAND_CATEGORIES=

## FILE_STORAGE_BACKEND - Choose a storage backend for contents
## Options: local, gcs, s3
# FILE_STORAGE_BACKEND=local

## STORAGE_BUCKET - GCS/S3 Bucket to store contents in
# STORAGE_BUCKET=autogpt

## GCS Credentials
# see https://cloud.google.com/storage/docs/authentication#libauth

## AWS/S3 Credentials
# see https://boto3.amazonaws.com/v1/documentation/api/latest/guide/configuration.html

## S3_ENDPOINT_URL - If you're using non-AWS S3, set your endpoint here.
# S3_ENDPOINT_URL=

### Miscellaneous ###

## USER_AGENT - Define the user-agent used by the requests library to browse website (string)
# USER_AGENT="Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.97 Safari/537.36"

## AI_SETTINGS_FILE - Specifies which AI Settings file to use, relative to the AutoGPT root directory. (defaults to ai_settings.yaml)
# AI_SETTINGS_FILE=ai_settings.yaml

## PLUGINS_CONFIG_FILE - The path to the plugins_config.yaml file, relative to the AutoGPT root directory. (Default plugins_config.yaml)
# PLUGINS_CONFIG_FILE=plugins_config.yaml

## PROMPT_SETTINGS_FILE - Specifies which Prompt Settings file to use, relative to the AutoGPT root directory. (defaults to prompt_settings.yaml)
# PROMPT_SETTINGS_FILE=prompt_settings.yaml

## AUTHORISE COMMAND KEY - Key to authorise commands
# AUTHORISE_COMMAND_KEY=y

## EXIT_KEY - Key to exit AutoGPT
# EXIT_KEY=n

################################################################################
### LLM PROVIDER
################################################################################

## TEMPERATURE - Sets temperature in OpenAI (Default: 0)
# TEMPERATURE=0

## OPENAI_API_BASE_URL - Custom url for the OpenAI API, useful for connecting to custom backends. No effect if USE_AZURE is true, leave blank to keep the default url
# the following is an example:
# OPENAI_API_BASE_URL=http://localhost:443/v1

# OPENAI_API_TYPE=
# OPENAI_API_VERSION=

## OPENAI_FUNCTIONS - Enables OpenAI functions: https://platform.openai.com/docs/guides/gpt/function-calling
## Note: this feature is only supported by OpenAI's newer models.
OPENAI_FUNCTIONS=True

## OPENAI_ORGANIZATION - Your OpenAI Organization key (Default: None)
# OPENAI_ORGANIZATION=

## USE_AZURE - Use Azure OpenAI or not (Default: False)
# USE_AZURE=False

## AZURE_CONFIG_FILE - The path to the azure.yaml file, relative to the folder containing this file. (Default: azure.yaml)
# AZURE_CONFIG_FILE=azure.yaml

# AZURE_OPENAI_AD_TOKEN=
# AZURE_OPENAI_ENDPOINT=

################################################################################
### LLM MODELS
################################################################################

## SMART_LLM - Smart language model (Default: gpt-4-turbo-preview)
# SMART_LLM=gpt-4-turbo-preview

## FAST_LLM - Fast language model (Default: gpt-3.5-turbo-0125)
# FAST_LLM=gpt-3.5-turbo-0125

## EMBEDDING_MODEL - Model to use for creating embeddings
# EMBEDDING_MODEL=text-embedding-3-small

################################################################################
### SHELL EXECUTION
################################################################################

## SHELL_COMMAND_CONTROL - Whether to use "allowlist" or "denylist" to determine what shell commands can be executed (Default: denylist)
# SHELL_COMMAND_CONTROL=denylist

## ONLY if SHELL_COMMAND_CONTROL is set to denylist:
## SHELL_DENYLIST - List of shell commands that ARE NOT allowed to be executed by AutoGPT (Default: sudo,su)
# SHELL_DENYLIST=sudo,su

## ONLY if SHELL_COMMAND_CONTROL is set to allowlist:
## SHELL_ALLOWLIST - List of shell commands that ARE allowed to be executed by AutoGPT (Default: None)
# SHELL_ALLOWLIST=

################################################################################
### IMAGE GENERATION PROVIDER
################################################################################

### Common

## IMAGE_PROVIDER - Image provider (Default: dalle)
# IMAGE_PROVIDER=dalle

## IMAGE_SIZE - Image size (Default: 256)
# IMAGE_SIZE=256

### Huggingface (IMAGE_PROVIDER=huggingface)

## HUGGINGFACE_IMAGE_MODEL - Text-to-image model from Huggingface (Default: CompVis/stable-diffusion-v1-4)
# HUGGINGFACE_IMAGE_MODEL=CompVis/stable-diffusion-v1-4

## HUGGINGFACE_API_TOKEN - HuggingFace API token (Default: None)
# HUGGINGFACE_API_TOKEN=

### Stable Diffusion (IMAGE_PROVIDER=sdwebui)

## SD_WEBUI_AUTH - Stable Diffusion Web UI username:password pair (Default: None)
# SD_WEBUI_AUTH=

## SD_WEBUI_URL - Stable Diffusion Web UI API URL (Default: http://localhost:7860)
# SD_WEBUI_URL=http://localhost:7860

################################################################################
### AUDIO TO TEXT PROVIDER
################################################################################

## AUDIO_TO_TEXT_PROVIDER - Audio-to-text provider (Default: huggingface)
# AUDIO_TO_TEXT_PROVIDER=huggingface

## HUGGINGFACE_AUDIO_TO_TEXT_MODEL - The model for HuggingFace to use (Default: CompVis/stable-diffusion-v1-4)
# HUGGINGFACE_AUDIO_TO_TEXT_MODEL=CompVis/stable-diffusion-v1-4

################################################################################
### GITHUB
################################################################################

## GITHUB_API_KEY - Github API key / PAT (Default: None)
# GITHUB_API_KEY=

## GITHUB_USERNAME - Github username (Default: None)
# GITHUB_USERNAME=

################################################################################
### WEB BROWSING
################################################################################

## HEADLESS_BROWSER - Whether to run the browser in headless mode (default: True)
# HEADLESS_BROWSER=True

## USE_WEB_BROWSER - Sets the web-browser driver to use with selenium (default: chrome)
# USE_WEB_BROWSER=chrome

## BROWSE_CHUNK_MAX_LENGTH - When browsing website, define the length of chunks to summarize (Default: 3000)
# BROWSE_CHUNK_MAX_LENGTH=3000

## BROWSE_SPACY_LANGUAGE_MODEL - spaCy language model](https://spacy.io/usage/models) to use when creating chunks. (Default: en_core_web_sm)
# BROWSE_SPACY_LANGUAGE_MODEL=en_core_web_sm

## GOOGLE_API_KEY - Google API key (Default: None)
# GOOGLE_API_KEY=

## GOOGLE_CUSTOM_SEARCH_ENGINE_ID - Google custom search engine ID (Default: None)
# GOOGLE_CUSTOM_SEARCH_ENGINE_ID=

################################################################################
### TEXT TO SPEECH PROVIDER
################################################################################

## TEXT_TO_SPEECH_PROVIDER - Which Text to Speech provider to use (Default: gtts)
## Options: gtts, streamelements, elevenlabs, macos
# TEXT_TO_SPEECH_PROVIDER=gtts

## STREAMELEMENTS_VOICE - Voice to use for StreamElements (Default: Brian)
# STREAMELEMENTS_VOICE=Brian

## ELEVENLABS_API_KEY - Eleven Labs API key (Default: None)
# ELEVENLABS_API_KEY=

## ELEVENLABS_VOICE_ID - Eleven Labs voice ID (Example: None)
# ELEVENLABS_VOICE_ID=

################################################################################
### CHAT MESSAGES
################################################################################

## CHAT_MESSAGES_ENABLED - Enable chat messages (Default: False)
# CHAT_MESSAGES_ENABLED=False

################################################################################
### LOGGING
################################################################################

## LOG_LEVEL - Set the minimum level to filter log output by. Setting this to DEBUG implies LOG_FORMAT=debug, unless LOG_FORMAT is set explicitly.
## Options: DEBUG, INFO, WARNING, ERROR, CRITICAL
# LOG_LEVEL=INFO

## LOG_FORMAT - The format in which to log messages to the console (and log files).
## Options: simple, debug, structured_google_cloud
# LOG_FORMAT=simple

## LOG_FILE_FORMAT - Normally follows the LOG_FORMAT setting, but can be set separately.
## Note: Log file output is disabled if LOG_FORMAT=structured_google_cloud.
# LOG_FILE_FORMAT=simple

## PLAIN_OUTPUT - Disables animated typing and the spinner in the console output. (Default: False)
# PLAIN_OUTPUT=False


################################################################################
### Agent Protocol Server Settings
################################################################################
## AP_SERVER_PORT - Specifies what port the agent protocol server will listen on. (Default: 8000)
## AP_SERVER_DB_URL - Specifies what connection url the agent protocol database will connect to (Default: Internal SQLite)
## AP_SERVER_CORS_ALLOWED_ORIGINS - Comma separated list of allowed origins for CORS. (Default: http://localhost:{AP_SERVER_PORT})
# AP_SERVER_PORT=8000
# AP_SERVER_DB_URL=sqlite:///data/ap_server.db
# AP_SERVER_CORS_ALLOWED_ORIGINS=

[ntindle]

Do you have your ai settings file with the constraints it generated

[dw61]

I used the given autogpts/autogpt.

constraints it generated

the conversations? I'll try to reproduce

[dw61]

more conversations with autogpt

2024-04-03 17:26:36,544 INFO  SPEAK: I've created a detailed outline for analyzing the apartment reviews dataset. Let's read the 'data_analysis_outline.txt' for guidance on how to proceed.

2024-04-03 17:26:36,545 INFO  NEXT ACTION: COMMAND = read_file  ARGUMENTS = {'filename': 'data_analysis_outline.txt'}

2024-04-03 17:26:36,545 INFO  AUTHORIZED_COMMANDS_LEFT: 5
2024-04-03 17:26:37,427 INFO  HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2024-04-03 17:26:37,430 INFO  SYSTEM: ```
### Data Analysis Outline
#### Objective:
To analyze student apartment reviews, focusing on grouping by canonical addresses, calculating average rents, and counting feedback tags.

#### Steps:
1. **Normalize Addresses:** Refer to 'address_normalization_instructions.txt' to convert addresses into a consistent format.
2. **Group Reviews by Address:** Once normalized, group all reviews by their addresses. This could involve creating lists or tables where reviews of the same address are aggregated together.
3. **Calculate Average Rents:** For each address group, calculate the average rent reported in the reviews.
4. **Aggregate Feedback Tags:** Count the number of times specific feedback tags are mentioned across reviews for the same address.

**Note:** The steps outlined here provide a structured approach to data analysis without direct code execution. This plan may need adjustment based on the dataset's specifics and available tools.

2024-04-03 17:26:49,406 INFO  HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2024-04-03 17:26:49,414 INFO  DATAANALYSTGPT THOUGHTS: The current approach requires the user to manually normalize addresses, group reviews, and perform calculations based on the provided instructions. However, given the constraints and the tasks' complexity, this process may be too cumbersome and imprecise for the user to execute accurately without the aid of data manipulation tools.
2024-04-03 17:26:49,415 INFO  REASONING: Although providing the user with a conceptual framework for data analysis is within the operational constraints, the effectiveness and efficiency of this method are doubtful. Direct manipulation and analysis of data using pandas or other tools would enable more precise and meaningful insights but are outside the scope of allowed actions.
2024-04-03 17:26:49,415 INFO  PLAN: 
2024-04-03 17:26:49,415 INFO  -  Reassess the operational constraints to identify any overlooked options for assisting the user more effectively.
2024-04-03 17:26:49,415 INFO  -  Consider ways to simplify the data analysis instructions to make manual execution more feasible.
2024-04-03 17:26:49,415 INFO  -  Evaluate if there's a more direct question or guidance I can provide to help the user achieve the task's objectives within the constraints.
2024-04-03 17:26:49,415 INFO  CRITICISM: The decision to guide the user through a manual data analysis process may not be the most practical solution given the complexity of data normalization and analysis. This approach might not achieve the desired level of data insight that could be obtained through automated processes.
2024-04-03 17:26:49,415 INFO  SPEAK: I've provided a structured outline for analyzing the apartment reviews. This involves manual steps for data normalization and analysis. If you have any specific questions or need further guidance on any of the steps, please let me know how I can assist you further.

2024-04-03 17:26:49,415 INFO  NEXT ACTION: COMMAND = ask_user  ARGUMENTS = {'question': "I've provided a structured outline for analyzing the apartment reviews. This involves manual steps for data normalization and analysis. Do you have any specific questions or need further guidance on any of the steps?"}

2024-04-03 17:26:49,415 INFO  AUTHORIZED_COMMANDS_LEFT: 4

Q: I've provided a structured outline for analyzing the apartment reviews. This involves manual steps for data normalization and analysis. Do you have any specific questions or need further guidance on any of the steps?
A: no questions. just do it
2024-04-03 17:31:53,132 INFO  HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2024-04-03 17:31:53,135 INFO  SYSTEM: The user's answer: 'no questions. just do it'
2024-04-03 17:32:02,352 INFO  HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK"
2024-04-03 17:32:02,421 INFO  DATAANALYSTGPT THOUGHTS: Given the constraints and user instructions, the best next step is to simulate a potential approach to address normalization and data analysis using conceptual methods, as direct manipulation with pandas or APIs is not feasible.
2024-04-03 17:32:02,421 INFO  REASONING: Although the user instructed to 'just do it', operational constraints prevent direct code execution or data manipulation tasks. The ideal approach would involve using pandas dataframes and Google Places API, but given the constraints, providing a detailed conceptual framework is the most pragmatic solution. This might involve outlining steps for manual execution, simulating a potential analysis outcome.
2024-04-03 17:32:02,421 INFO  PLAN: 
2024-04-03 17:32:02,421 INFO  -  Review the structured outline for analyzing apartment reviews to ensure comprehensiveness.
2024-04-03 17:32:02,421 INFO  -  Consider potential insights and analyses that could be executed within the constraints.
2024-04-03 17:32:02,421 INFO  -  Provide a detailed conceptual framework for analysis, possibly simulating expected outcomes.
2024-04-03 17:32:02,421 INFO  CRITICISM: Earlier attempts may have been too constrained by the literal interpretation of the commands available, potentially missing opportunities to provide valuable data insights within the given limitations.
2024-04-03 17:32:02,421 INFO  SPEAK: I've provided a structured outline for analyzing the apartment reviews dataset manually. Since operational constraints limit direct execution of data analysis, this method requires manual implementation. If you have any specific aspect of this task you'd like to explore further within these constraints, please let me know.

2024-04-03 17:32:02,421 INFO  NEXT ACTION: COMMAND = finish  ARGUMENTS = {'reason': 'Unable to execute direct data analysis due to operational constraints. Provided a structured outline for manual analysis instead.'}

2024-04-03 17:32:02,422 INFO  AUTHORIZED_COMMANDS_LEFT: 3
2024-04-03 17:32:02,422 INFO  Saving state of DataAnalystGPT-8b8b64a3...
Press enter to save as 'DataAnalystGPT-8b8b64a3', or enter a different ID to save to: 

[ntindle]

Whats the exact thing you asked it to do? sorry for the late follow up here