proxycurl integration

Having the starting nodes of the execution marked as incomplete misled
the users.

### Changes 🏗️

Mark the starting nodes during the executions as QUEUED instead of
INCOMPLETE.

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Executed the graph, the incomplete initial starting node is no
more.

.deepsource.toml

@@ -0,0 +1,18 @@
+version = 1
+
+test_patterns = ["**/*.spec.ts","**/*_test.py","**/*_tests.py","**/test_*.py"]
+
+exclude_patterns = ["classic/**"]
+
+[[analyzers]]
+name = "javascript"
+
+[analyzers.meta]
+plugins = ["react"]
+environment = ["nodejs"]
+
+[[analyzers]]
+name = "python"
+
+[analyzers.meta]
+runtime_version = "3.x.x"

.devcontainer/docker-compose.yml

@@ -1,19 +0,0 @@
-# To boot the app run the following:
-# docker-compose run auto-gpt
-version: '3.9'
-
-services:
-  auto-gpt:
-    depends_on:
-      - redis
-    build:
-      dockerfile: .devcontainer/Dockerfile
-      context: ../
-    tty: true
-    environment:
-      MEMORY_BACKEND: ${MEMORY_BACKEND:-redis}
-      REDIS_HOST: ${REDIS_HOST:-redis}
-    volumes:
-      - ../:/workspace/Auto-GPT
-  redis:
-    image: 'redis/redis-stack-server:latest'

.dockerignore

@@ -1,8 +1,61 @@
-.*
-*.template
-*.yaml
-*.yml
+# Ignore everything by default, selectively add things to context
+*
 
-*.md
-*.png
-!BULLETIN.md
+# Platform - Libs
+!autogpt_platform/autogpt_libs/autogpt_libs/
+!autogpt_platform/autogpt_libs/pyproject.toml
+!autogpt_platform/autogpt_libs/poetry.lock
+!autogpt_platform/autogpt_libs/README.md
+
+# Platform - Backend
+!autogpt_platform/backend/backend/
+!autogpt_platform/backend/migrations/
+!autogpt_platform/backend/schema.prisma
+!autogpt_platform/backend/pyproject.toml
+!autogpt_platform/backend/poetry.lock
+!autogpt_platform/backend/README.md
+
+# Platform - Market
+!autogpt_platform/market/market/
+!autogpt_platform/market/scripts.py
+!autogpt_platform/market/schema.prisma
+!autogpt_platform/market/pyproject.toml
+!autogpt_platform/market/poetry.lock
+!autogpt_platform/market/README.md
+
+# Platform - Frontend
+!autogpt_platform/frontend/src/
+!autogpt_platform/frontend/public/
+!autogpt_platform/frontend/package.json
+!autogpt_platform/frontend/yarn.lock
+!autogpt_platform/frontend/tsconfig.json
+!autogpt_platform/frontend/README.md
+## config
+!autogpt_platform/frontend/*.config.*
+!autogpt_platform/frontend/.env.*
+
+# Classic - AutoGPT
+!classic/original_autogpt/autogpt/
+!classic/original_autogpt/pyproject.toml
+!classic/original_autogpt/poetry.lock
+!classic/original_autogpt/README.md
+!classic/original_autogpt/tests/
+
+# Classic - Benchmark
+!classic/benchmark/agbenchmark/
+!classic/benchmark/pyproject.toml
+!classic/benchmark/poetry.lock
+!classic/benchmark/README.md
+
+# Classic - Forge
+!classic/forge/
+!classic/forge/pyproject.toml
+!classic/forge/poetry.lock
+!classic/forge/README.md
+
+# Classic - Frontend
+!classic/frontend/build/web/
+
+# Explicitly re-ignore some folders
+.*
+**/__pycache__

.env.template

@@ -1,214 +0,0 @@
-################################################################################
-### AUTO-GPT - GENERAL SETTINGS
-################################################################################
-
-## EXECUTE_LOCAL_COMMANDS - Allow local command execution (Default: False)
-## RESTRICT_TO_WORKSPACE - Restrict file operations to workspace ./auto_gpt_workspace (Default: True)
-# EXECUTE_LOCAL_COMMANDS=False
-# RESTRICT_TO_WORKSPACE=True
-
-## 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 (defaults to ai_settings.yaml)
-# AI_SETTINGS_FILE=ai_settings.yaml
-
-## AUTHORISE COMMAND KEY - Key to authorise commands
-# AUTHORISE_COMMAND_KEY=y
-## EXIT_KEY - Key to exit AUTO-GPT
-# EXIT_KEY=n
-
-################################################################################
-### LLM PROVIDER
-################################################################################
-
-### OPENAI
-## OPENAI_API_KEY - OpenAI API Key (Example: my-openai-api-key)
-## TEMPERATURE - Sets temperature in OpenAI (Default: 0)
-## USE_AZURE - Use Azure OpenAI or not (Default: False)
-OPENAI_API_KEY=your-openai-api-key
-# TEMPERATURE=0
-# USE_AZURE=False
-
-### AZURE
-# moved to `azure.yaml.template`
-
-################################################################################
-### LLM MODELS
-################################################################################
-
-## SMART_LLM_MODEL - Smart language model (Default: gpt-4)
-## FAST_LLM_MODEL - Fast language model (Default: gpt-3.5-turbo)
-# SMART_LLM_MODEL=gpt-4
-# FAST_LLM_MODEL=gpt-3.5-turbo
-
-### LLM MODEL SETTINGS
-## FAST_TOKEN_LIMIT - Fast token limit for OpenAI (Default: 4000)
-## SMART_TOKEN_LIMIT - Smart token limit for OpenAI (Default: 8000)
-## When using --gpt3only this needs to be set to 4000.
-# FAST_TOKEN_LIMIT=4000
-# SMART_TOKEN_LIMIT=8000
-
-################################################################################
-### MEMORY
-################################################################################
-
-### MEMORY_BACKEND - Memory backend type
-## local - Default
-## pinecone - Pinecone (if configured)
-## redis - Redis (if configured)
-## milvus - Milvus (if configured - also works with Zilliz)
-## MEMORY_INDEX - Name of index created in Memory backend (Default: auto-gpt)
-# MEMORY_BACKEND=local
-# MEMORY_INDEX=auto-gpt
-
-### PINECONE
-## PINECONE_API_KEY - Pinecone API Key (Example: my-pinecone-api-key)
-## PINECONE_ENV - Pinecone environment (region) (Example: us-west-2)
-# PINECONE_API_KEY=your-pinecone-api-key
-# PINECONE_ENV=your-pinecone-region
-
-### REDIS
-## REDIS_HOST - Redis host (Default: localhost, use "redis" for docker-compose)
-## REDIS_PORT - Redis port (Default: 6379)
-## REDIS_PASSWORD - Redis password (Default: "")
-## WIPE_REDIS_ON_START - Wipes data / index on start (Default: True)
-# REDIS_HOST=localhost
-# REDIS_PORT=6379
-# REDIS_PASSWORD=
-# WIPE_REDIS_ON_START=True
-
-### WEAVIATE
-## MEMORY_BACKEND - Use 'weaviate' to use Weaviate vector storage
-## WEAVIATE_HOST - Weaviate host IP
-## WEAVIATE_PORT - Weaviate host port
-## WEAVIATE_PROTOCOL - Weaviate host protocol (e.g. 'http')
-## USE_WEAVIATE_EMBEDDED - Whether to use Embedded Weaviate
-## WEAVIATE_EMBEDDED_PATH - File system path were to persist data when running Embedded Weaviate
-## WEAVIATE_USERNAME - Weaviate username
-## WEAVIATE_PASSWORD - Weaviate password
-## WEAVIATE_API_KEY - Weaviate API key if using API-key-based authentication
-# WEAVIATE_HOST="127.0.0.1"
-# WEAVIATE_PORT=8080
-# WEAVIATE_PROTOCOL="http"
-# USE_WEAVIATE_EMBEDDED=False
-# WEAVIATE_EMBEDDED_PATH="/home/me/.local/share/weaviate"
-# WEAVIATE_USERNAME=
-# WEAVIATE_PASSWORD=
-# WEAVIATE_API_KEY=
-
-### MILVUS
-## MILVUS_ADDR - Milvus remote address (e.g. localhost:19530, https://xxx-xxxx.xxxx.xxxx.zillizcloud.com:443)
-## MILVUS_USERNAME - username for your Milvus database
-## MILVUS_PASSWORD - password for your Milvus database
-## MILVUS_SECURE - True to enable TLS. (Default: False)
-##   Setting MILVUS_ADDR to a `https://` URL will override this setting.
-## MILVUS_COLLECTION - Milvus collection, change it if you want to start a new memory and retain the old memory.
-# MILVUS_ADDR=localhost:19530
-# MILVUS_USERNAME=
-# MILVUS_PASSWORD=
-# MILVUS_SECURE=
-# MILVUS_COLLECTION=autogpt
-
-################################################################################
-### IMAGE GENERATION PROVIDER
-################################################################################
-
-### OPEN AI
-## IMAGE_PROVIDER - Image provider (Example: dalle)
-## IMAGE_SIZE - Image size (Example: 256)
-##   DALLE: 256, 512, 1024
-# IMAGE_PROVIDER=dalle
-# IMAGE_SIZE=256
-
-### HUGGINGFACE
-## HUGGINGFACE_IMAGE_MODEL - Text-to-image model from Huggingface (Default: CompVis/stable-diffusion-v1-4)
-## HUGGINGFACE_API_TOKEN - HuggingFace API token (Example: my-huggingface-api-token)
-# HUGGINGFACE_IMAGE_MODEL=CompVis/stable-diffusion-v1-4
-# HUGGINGFACE_API_TOKEN=your-huggingface-api-token
-
-### STABLE DIFFUSION WEBUI
-## SD_WEBUI_AUTH - Stable diffusion webui username:password pair (Example: username:password)
-## SD_WEBUI_URL - Stable diffusion webui API URL (Example: http://127.0.0.1:7860)
-# SD_WEBUI_AUTH=
-# SD_WEBUI_URL=http://127.0.0.1:7860
-
-################################################################################
-### AUDIO TO TEXT PROVIDER
-################################################################################
-
-### HUGGINGFACE
-# HUGGINGFACE_AUDIO_TO_TEXT_MODEL=facebook/wav2vec2-base-960h
-
-################################################################################
-### GIT Provider for repository actions
-################################################################################
-
-### GITHUB
-## GITHUB_API_KEY - Github API key / PAT (Example: github_pat_123)
-## GITHUB_USERNAME - Github username
-# GITHUB_API_KEY=github_pat_123
-# GITHUB_USERNAME=your-github-username
-
-################################################################################
-### WEB BROWSING
-################################################################################
-
-### BROWSER
-## HEADLESS_BROWSER - Whether to run the browser in headless mode (default: True)
-## USE_WEB_BROWSER - Sets the web-browser driver to use with selenium (default: chrome).
-##   Note: set this to either 'chrome', 'firefox', or 'safari' depending on your current browser
-# HEADLESS_BROWSER=True
-# USE_WEB_BROWSER=chrome
-## BROWSE_CHUNK_MAX_LENGTH - When browsing website, define the length of chunks to summarize (in number of tokens, excluding the response. 75 % of FAST_TOKEN_LIMIT is usually wise )
-# BROWSE_CHUNK_MAX_LENGTH=3000
-## BROWSE_SPACY_LANGUAGE_MODEL is used to split sentences. Install additional languages via pip, and set the model name here. Example Chinese:  python -m spacy download zh_core_web_sm
-# BROWSE_SPACY_LANGUAGE_MODEL=en_core_web_sm
-
-### GOOGLE
-## GOOGLE_API_KEY - Google API key (Example: my-google-api-key)
-## CUSTOM_SEARCH_ENGINE_ID - Custom search engine ID (Example: my-custom-search-engine-id)
-# GOOGLE_API_KEY=your-google-api-key
-# CUSTOM_SEARCH_ENGINE_ID=your-custom-search-engine-id
-
-################################################################################
-### TTS PROVIDER
-################################################################################
-
-### MAC OS
-## USE_MAC_OS_TTS - Use Mac OS TTS or not (Default: False)
-# USE_MAC_OS_TTS=False
-
-### STREAMELEMENTS
-## USE_BRIAN_TTS - Use Brian TTS or not (Default: False)
-# USE_BRIAN_TTS=False
-
-### ELEVENLABS
-## ELEVENLABS_API_KEY - Eleven Labs API key (Example: my-elevenlabs-api-key)
-## ELEVENLABS_VOICE_1_ID - Eleven Labs voice 1 ID (Example: my-voice-id-1)
-## ELEVENLABS_VOICE_2_ID - Eleven Labs voice 2 ID (Example: my-voice-id-2)
-# ELEVENLABS_API_KEY=your-elevenlabs-api-key
-# ELEVENLABS_VOICE_1_ID=your-voice-id-1
-# ELEVENLABS_VOICE_2_ID=your-voice-id-2
-
-################################################################################
-### TWITTER API
-################################################################################
-
-# TW_CONSUMER_KEY=
-# TW_CONSUMER_SECRET=
-# TW_ACCESS_TOKEN=
-# TW_ACCESS_TOKEN_SECRET=
-
-################################################################################
-### ALLOWLISTED PLUGINS
-################################################################################
-
-#ALLOWLISTED_PLUGINS - Sets the listed plugins that are allowed (Example: plugin1,plugin2,plugin3)
-ALLOWLISTED_PLUGINS=
-
-################################################################################
-### CHAT PLUGIN SETTINGS
-################################################################################
-# CHAT_MESSAGES_ENABLED - Enable chat messages (Default: False)
-# CHAT_MESSAGES_ENABLED=False

.gitattributes

@@ -1,5 +1,10 @@
-# Exclude VCR cassettes from stats
-tests/**/cassettes/**.y*ml linguist-generated
+classic/frontend/build/** linguist-generated
 
-# Mark documentation as such
-docs/**.md linguist-documentation
+**/poetry.lock linguist-generated
+
+docs/_javascript/** linguist-vendored
+
+# Exclude VCR cassettes from stats
+classic/forge/tests/vcr_cassettes/**/**.y*ml linguist-generated
+
+* text=auto

.github/CODEOWNERS

@@ -0,0 +1,7 @@
+* @Significant-Gravitas/maintainers
+.github/workflows/ @Significant-Gravitas/devops
+classic/forge/ @Significant-Gravitas/forge-maintainers
+classic/benchmark/ @Significant-Gravitas/benchmark-maintainers
+classic/frontend/ @Significant-Gravitas/frontend-maintainers
+autogpt_platform/infra @Significant-Gravitas/devops
+.github/CODEOWNERS @Significant-Gravitas/admins

.github/FUNDING.yml

@@ -1,3 +0,0 @@
-# These are supported funding model platforms
-
-github: Torantulino

.github/ISSUE_TEMPLATE/1.bug.yml

@@ -1,5 +1,5 @@
 name: Bug report 🐛
-description: Create a bug report for Auto-GPT.
+description: Create a bug report for AutoGPT.
 labels: ['status: needs triage']
 body:
   - type: markdown
@@ -8,45 +8,53 @@ body:
         ### ⚠️ Before you continue
         * Check out our [backlog], [roadmap] and join our [discord] to discuss what's going on
         * If you need help, you can ask in the [discussions] section or in [#tech-support]
-        * **Throughly search the [existing issues] before creating a new one**
-
+        * **Thoroughly search the [existing issues] before creating a new one**
+        * Read our [wiki page on Contributing]
         [backlog]: https://github.com/orgs/Significant-Gravitas/projects/1
         [roadmap]: https://github.com/orgs/Significant-Gravitas/projects/2  
         [discord]: https://discord.gg/autogpt
-        [discussions]: https://github.com/Significant-Gravitas/Auto-GPT/discussions
+        [discussions]: https://github.com/Significant-Gravitas/AutoGPT/discussions
         [#tech-support]: https://discord.com/channels/1092243196446249134/1092275629602394184
-        [existing issues]: https://github.com/Significant-Gravitas/Auto-GPT/issues?q=is%3Aissue
+        [existing issues]: https://github.com/Significant-Gravitas/AutoGPT/issues?q=is%3Aissue
+        [wiki page on Contributing]: https://github.com/Significant-Gravitas/AutoGPT/wiki/Contributing
+
   - type: checkboxes
     attributes:
       label: ⚠️ Search for existing issues first ⚠️
       description: >
-        Please [search the history](https://github.com/Torantulino/Auto-GPT/issues)
+        Please [search the history](https://github.com/Significant-Gravitas/AutoGPT/issues)
         to see if an issue already exists for the same problem.
       options:
         - label: I have searched the existing issues, and there is no existing issue for my problem
           required: true
+
   - type: markdown
     attributes:
       value: |
-        Please provide a searchable summary of the issue in the title above ⬆️.
-
-        ⚠️ SUPER-busy repo, please help the volunteer maintainers.
-        The less time we spend here, the more time we spend building AutoGPT.
+        Please confirm that the issue you have is described well and precise in the title above ⬆️.
+        A good rule of thumb: What would you type if you were searching for the issue?
         
-        Please help us help you:
-        - Does it work on `stable` branch (https://github.com/Torantulino/Auto-GPT/tree/stable)?
-        - Does it work on current `master` (https://github.com/Torantulino/Auto-GPT/tree/master)?
-        - Search for existing issues, "add comment" is tidier than "new issue"
-        - Ask on our Discord (https://discord.gg/autogpt)
+        For example:
+        BAD - my AutoGPT keeps looping
+        GOOD - After performing execute_python_file, AutoGPT goes into a loop where it keeps trying to execute the file.
+        
+        ⚠️ SUPER-busy repo, please help the volunteer maintainers.
+        The less time we spend here, the more time we can spend building AutoGPT.
+        
+        Please help us help you by following these steps:
+        - Search for existing issues, adding a comment when you have the same or similar issue is tidier than "new issue" and 
+          newer issues will not be reviewed earlier, this is dependent on the current priorities set by our wonderful team
+        - Ask on our Discord if your issue is known when you are unsure (https://discord.gg/autogpt)
         - Provide relevant info:
-          - Provide commit-hash (`git rev-parse HEAD` gets it)
-          - If it's a pip/packages issue, provide pip version, python version
-          - If it's a crash, provide traceback.
+          - Provide commit-hash (`git rev-parse HEAD` gets it) if possible
+          - If it's a pip/packages issue, mention this in the title and provide pip version, python version
+          - If it's a crash, provide traceback and describe the error you got as precise as possible in the title.
+
   - type: dropdown
     attributes:
       label: Which Operating System are you using?
       description: >
-        Please select the operating system you were using to run Auto-GPT when this problem occurred.
+        Please select the operating system you were using to run AutoGPT when this problem occurred.
       options:
         - Windows
         - Linux
@@ -54,78 +62,112 @@ body:
         - Docker
         - Devcontainer / Codespace
         - Windows Subsystem for Linux (WSL)
-        - Other (Please specify in your problem)
+        - Other
     validations:
       required: true
+      nested_fields:
+        - type: text
+          attributes:
+            label: Specify the system
+            description: Please specify the system you are working on.
+
   - type: dropdown
     attributes:
-      label: Which version of Auto-GPT are you using?
+      label: Which version of AutoGPT are you using?
       description: |
-        Please select which version of Auto-GPT you were using when this issue occurred.
-        If you downloaded the code from the [releases page](https://github.com/Significant-Gravitas/Auto-GPT/releases/) make sure you were using the latest code. 
-        **If you weren't please try with the [latest code](https://github.com/Significant-Gravitas/Auto-GPT/releases/)**.
-        If installed with git you can run `git branch` to see which version of Auto-GPT you are running.
+        Please select which version of AutoGPT you were using when this issue occurred.
+        If you downloaded the code from the [releases page](https://github.com/Significant-Gravitas/AutoGPT/releases/) make sure you were using the latest code. 
+        **If you weren't please try with the [latest code](https://github.com/Significant-Gravitas/AutoGPT/releases/)**.
+        If installed with git you can run `git branch` to see which version of AutoGPT you are running.
       options:
         - Latest Release
         - Stable (branch)
         - Master (branch)
     validations:
       required: true
+
   - type: dropdown
     attributes:
-      label: GPT-3 or GPT-4?
+      label: What LLM Provider do you use?
       description: >
-        If you are using Auto-GPT with `--gpt3only`, your problems may be caused by
-        the [limitations](https://github.com/Significant-Gravitas/Auto-GPT/issues?q=is%3Aissue+label%3A%22AI+model+limitation%22) of GPT-3.5.
+        If you are using AutoGPT with `SMART_LLM=gpt-3.5-turbo`, your problems may be caused by
+        the [limitations](https://github.com/Significant-Gravitas/AutoGPT/issues?q=is%3Aissue+label%3A%22AI+model+limitation%22) of GPT-3.5.
       options:
-        - GPT-3.5
-        - GPT-4
+        - Azure
+        - Groq
+        - Anthropic
+        - Llamafile
+        - Other (detail in issue)
     validations:
       required: true
-  - type: textarea
+
+  - type: dropdown
     attributes:
-      label: Steps to reproduce 🕹
-      description: |
-        **⚠️ Issues that we can't reproduce will be closed.**
-  - type: textarea
-    attributes:
-      label: Current behavior 😯
-      description: Describe what happens instead of the expected behavior.
-  - type: textarea
-    attributes:
-      label: Expected behavior 🤔
-      description: Describe what should happen.
-  - type: textarea
-    attributes:
-      label: Your prompt 📝
+      label: Which area covers your issue best?
       description: >
-        If applicable please provide the prompt you are using. Your prompt is stored in your `ai_settings.yaml` file.
-      value: |
-        ```yaml
-        # Paste your prompt here
-        ```
+        Select the area related to the issue you are reporting.
+      options:
+        - Installation and setup
+        - Memory
+        - Performance
+        - Prompt
+        - Commands
+        - Plugins
+        - AI Model Limitations
+        - Challenges
+        - Documentation
+        - Logging
+        - Agents
+        - Other
+    validations:
+      required: true
+      autolabels: true
+      nested_fields:
+        - type: text
+          attributes:
+            label: Specify the area
+            description: Please specify the area you think is best related to the issue.
+
+  - type: input
+    attributes:
+      label: What commit or version are you using?
+      description: It is helpful for us to reproduce to know what version of the software you were using when this happened. Please run `git log -n 1 --pretty=format:"%H"` to output the full commit hash.
+    validations:
+      required: true
+
   - type: textarea
     attributes:
-      label: Your Logs 📒
-      description: |
-        Please include the log showing your error and the command that caused it, if applicable.
-        You can copy it from your terminal or from `logs/activity.log`.
-        This will help us understand your issue better!
-        
-        <details>
-        <summary><i>Example</i></summary>
-        ```log
-        INFO NEXT ACTION:  COMMAND = execute_shell  ARGUMENTS = {'command_line': 'some_command'}
-        INFO -=-=-=-=-=-=-= COMMAND AUTHORISED BY USER -=-=-=-=-=-=-=
-        Traceback (most recent call last):
-        File "/home/anaconda3/lib/python3.9/site-packages/openai/api_requestor.py", line 619, in _interpret_response
-        self._interpret_response_line(
-        File "/home/anaconda3/lib/python3.9/site-packages/openai/api_requestor.py", line 682, in _interpret_response_line
-        raise self.handle_error_response(
-        openai.error.InvalidRequestError: This model's maximum context length is 8191 tokens, however you requested 10982 tokens (10982 in your prompt; 0 for the completion). Please reduce your prompt; or completion length.
-        ```
-        </details>
+      label: Describe your issue.
+      description: Describe the problem you are experiencing. Try to describe only the issue and phrase it short but clear. ⚠️ Provide NO other data in this field
+    validations:
+      required: true
+
+  #Following are optional file content uploads
+  - type: markdown
+    attributes:
       value: |
-        ```log
-        <insert your logs here>
-        ```
+        ⚠️The following is OPTIONAL, please keep in mind that the log files may contain personal information such as credentials.⚠️
+        
+        "The log files are located in the folder 'logs' inside the main AutoGPT folder."
+
+  - type: textarea
+    attributes:
+      label: Upload Activity Log Content
+      description: |
+        Upload the activity log content, this can help us understand the issue better. 
+        To do this, go to the folder logs in your main AutoGPT folder, open activity.log and copy/paste the contents to this field. 
+        ⚠️ The activity log may contain personal data given to AutoGPT by you in prompt or input as well as 
+        any personal information that AutoGPT collected out of files during last run. Do not add the activity log if you are not comfortable with sharing it. ⚠️
+    validations:
+      required: false
+
+  - type: textarea
+    attributes:
+      label: Upload Error Log Content
+      description: |
+        Upload the error log content, this will help us understand the issue better. 
+        To do this, go to the folder logs in your main AutoGPT folder, open error.log and copy/paste the contents to this field. 
+        ⚠️ The error log may contain personal data given to AutoGPT by you in prompt or input as well as 
+        any personal information that AutoGPT collected out of files during last run. Do not add the activity log if you are not comfortable with sharing it. ⚠️
+    validations:
+      required: false

.github/ISSUE_TEMPLATE/2.feature.yml

@@ -1,17 +1,16 @@
 name: Feature request 🚀
-description: Suggest a new idea for Auto-GPT.
+description: Suggest a new idea for AutoGPT!
 labels: ['status: needs triage']
 body:
   - type: markdown
     attributes:
       value: |
+        First, check out our [wiki page on Contributing](https://github.com/Significant-Gravitas/AutoGPT/wiki/Contributing)
         Please provide a searchable summary of the issue in the title above ⬆️.
-
-        Thanks for contributing by creating an issue! ❤️
   - type: checkboxes
     attributes:
       label: Duplicates
-      description: Please [search the history](https://github.com/Torantulino/Auto-GPT/issues) to see if an issue already exists for the same problem.
+      description: Please [search the history](https://github.com/Significant-Gravitas/AutoGPT/issues) to see if an issue already exists for the same problem.
       options:
         - label: I have searched the existing issues
           required: true
@@ -26,4 +25,4 @@ body:
   - type: textarea
     attributes:
       label: Motivation 🔦
-      description: What are you trying to accomplish? How has the lack of this feature affected you? Providing context helps us come up with a solution that is more useful in the real world.
+      description: What are you trying to accomplish? How has the lack of this feature affected you? Providing context helps us come up with a solution that is more useful in the real world.

.github/PULL_REQUEST_TEMPLATE.md

@@ -1,40 +1,38 @@
-<!-- ⚠️ At the moment any non-essential commands are not being merged.
-If you want to add non-essential commands to Auto-GPT, please create a plugin instead.
-We are expecting to ship plugin support within the week (PR #757).
-Resources:
-* https://github.com/Significant-Gravitas/Auto-GPT-Plugin-Template
--->
+<!-- Clearly explain the need for these changes: -->
 
-<!-- 📢 Announcement
-We've recently noticed an increase in pull requests focusing on combining multiple changes. While the intentions behind these PRs are appreciated, it's essential to maintain a clean and manageable git history. To ensure the quality of our repository, we kindly ask you to adhere to the following guidelines when submitting PRs:
+### Changes 🏗️
 
-Focus on a single, specific change.
-Do not include any unrelated or "extra" modifications.
-Provide clear documentation and explanations of the changes made.
-Ensure diffs are limited to the intended lines — no applying preferred formatting styles or line endings (unless that's what the PR is about).
-For guidance on committing only the specific lines you have changed, refer to this helpful video: https://youtu.be/8-hSNHHbiZg
+<!-- Concisely describe all of the changes made in this pull request: -->
 
-By following these guidelines, your PRs are more likely to be merged quickly after testing, as long as they align with the project's overall direction. -->
+### Checklist 📋
 
-### Background
-<!-- Provide a concise overview of the rationale behind this change. Include relevant context, prior discussions, or links to related issues. Ensure that the change aligns with the project's overall direction. -->
+#### For code changes:
+- [ ] I have clearly listed my changes in the PR description
+- [ ] I have made a test plan
+- [ ] I have tested my changes according to the test plan:
+  <!-- Put your test plan here: -->
+  - [ ] ...
 
-### Changes
-<!-- Describe the specific, focused change made in this pull request. Detail the modifications clearly and avoid any unrelated or "extra" changes. -->
+<details>
+  <summary>Example test plan</summary>
+  
+  - [ ] Create from scratch and execute an agent with at least 3 blocks
+  - [ ] Import an agent from file upload, and confirm it executes correctly
+  - [ ] Upload agent to marketplace
+  - [ ] Import an agent from marketplace and confirm it executes correctly
+  - [ ] Edit an agent from monitor, and confirm it executes correctly
+</details>
 
-### Documentation
-<!-- Explain how your changes are documented, such as in-code comments or external documentation. Ensure that the documentation is clear, concise, and easy to understand. -->
+#### For configuration changes:
+- [ ] `.env.example` is updated or already compatible with my changes
+- [ ] `docker-compose.yml` is updated or already compatible with my changes
+- [ ] I have included a list of my configuration changes in the PR description (under **Changes**)
 
-### Test Plan
-<!-- Describe how you tested this functionality. Include steps to reproduce, relevant test cases, and any other pertinent information. -->
+<details>
+  <summary>Examples of configuration changes</summary>
 
-### PR Quality Checklist
-- [ ] My pull request is atomic and focuses on a single change.
-- [ ] I have thoroughly tested my changes with multiple different prompts.
-- [ ] I have considered potential risks and mitigations for my changes.
-- [ ] I have documented my changes clearly and comprehensively.
-- [ ] I have not snuck in any "extra" small tweaks changes <!-- Submit these as separate Pull Requests, they are the easiest to merge! -->
-
-<!-- If you haven't added tests, please explain why. If you have, check the appropriate box. If you've ensured your PR is atomic and well-documented, check the corresponding boxes. -->
-
-<!-- By submitting this, I agree that my pull request should be closed if I do not fill this out or follow the guidelines. -->
+  - Changing ports
+  - Adding new services that need to communicate with each other
+  - Secrets or environment variable changes
+  - New or infrastructure changes such as databases
+</details>

.github/dependabot.yml

@@ -0,0 +1,151 @@
+version: 2
+updates:
+  # autogpt_libs (Poetry project)
+  - package-ecosystem: "pip"
+    directory: "autogpt_platform/autogpt_libs"
+    schedule:
+      interval: "weekly"
+    open-pull-requests-limit: 10
+    target-branch: "dev"
+    commit-message:
+      prefix: "chore(libs/deps)"
+      prefix-development: "chore(libs/deps-dev)"
+    groups:
+      production-dependencies:
+        dependency-type: "production"
+        update-types:
+        - "minor"
+        - "patch"
+      development-dependencies:
+        dependency-type: "development"
+        update-types:
+        - "minor"
+        - "patch"
+
+  # backend (Poetry project)
+  - package-ecosystem: "pip"
+    directory: "autogpt_platform/backend"
+    schedule:
+      interval: "weekly"
+    open-pull-requests-limit: 10
+    target-branch: "dev"
+    commit-message:
+      prefix: "chore(backend/deps)"
+      prefix-development: "chore(backend/deps-dev)"
+    groups:
+      production-dependencies:
+        dependency-type: "production"
+        update-types:
+        - "minor"
+        - "patch"
+      development-dependencies:
+        dependency-type: "development"
+        update-types:
+        - "minor"
+        - "patch"
+
+  # frontend (Next.js project)
+  - package-ecosystem: "npm"
+    directory: "autogpt_platform/frontend"
+    schedule:
+      interval: "weekly"
+    open-pull-requests-limit: 10
+    target-branch: "dev"
+    commit-message:
+      prefix: "chore(frontend/deps)"
+      prefix-development: "chore(frontend/deps-dev)"
+    groups:
+      production-dependencies:
+        dependency-type: "production"
+        update-types:
+        - "minor"
+        - "patch"
+      development-dependencies:
+        dependency-type: "development"
+        update-types:
+        - "minor"
+        - "patch"
+
+  # infra (Terraform)
+  - package-ecosystem: "terraform"
+    directory: "autogpt_platform/infra"
+    schedule:
+      interval: "weekly"
+    open-pull-requests-limit: 5
+    target-branch: "dev"
+    commit-message:
+      prefix: "chore(infra/deps)"
+      prefix-development: "chore(infra/deps-dev)"
+
+    groups:
+      production-dependencies:
+        dependency-type: "production"
+        update-types:
+        - "minor"
+        - "patch"
+      development-dependencies:
+        dependency-type: "development"
+        update-types:
+        - "minor"
+        - "patch"
+
+
+  # GitHub Actions
+  - package-ecosystem: "github-actions"
+    directory: "/"
+    schedule:
+      interval: "weekly"
+    open-pull-requests-limit: 5
+    target-branch: "dev"
+    groups:
+      production-dependencies:
+        dependency-type: "production"
+        update-types:
+        - "minor"
+        - "patch"
+      development-dependencies:
+        dependency-type: "development"
+        update-types:
+        - "minor"
+        - "patch"
+
+
+  # Docker
+  - package-ecosystem: "docker"
+    directory: "autogpt_platform/"
+    schedule:
+      interval: "weekly"
+    open-pull-requests-limit: 5
+    target-branch: "dev"
+    groups:
+      production-dependencies:
+        dependency-type: "production"
+        update-types:
+        - "minor"
+        - "patch"
+      development-dependencies:
+        dependency-type: "development"
+        update-types:
+        - "minor"
+        - "patch"
+
+  # Docs
+  - package-ecosystem: 'pip'
+    directory: "docs/"
+    schedule:
+      interval: "weekly"
+    open-pull-requests-limit: 1
+    target-branch: "dev"
+    commit-message:
+      prefix: "chore(docs/deps)"
+    groups:
+      production-dependencies:
+        dependency-type: "production"
+        update-types:
+        - "minor"
+        - "patch"
+      development-dependencies:
+        dependency-type: "development"
+        update-types:
+        - "minor"
+        - "patch"

.github/labeler.yml

@@ -0,0 +1,32 @@
+Classic AutoGPT Agent:
+- changed-files:
+  - any-glob-to-any-file: classic/original_autogpt/**
+
+Classic Benchmark:
+- changed-files:
+  - any-glob-to-any-file: classic/benchmark/**
+
+Classic Frontend:
+- changed-files:
+  - any-glob-to-any-file: classic/frontend/**
+
+Forge:
+- changed-files:
+  - any-glob-to-any-file: classic/forge/**
+
+documentation:
+- changed-files:
+  - any-glob-to-any-file: docs/**
+
+platform/frontend:
+- changed-files:
+  - any-glob-to-any-file: autogpt_platform/frontend/**
+
+platform/backend:
+- changed-files:
+  - any-glob-to-any-file: autogpt_platform/backend/**
+  - all-globs-to-all-files: '!autogpt_platform/backend/backend/blocks/**'
+
+platform/blocks:
+- changed-files:
+  - any-glob-to-any-file: autogpt_platform/backend/backend/blocks/**

.github/workflows/benchmarks.yml

@@ -1,31 +0,0 @@
-name: Run Benchmarks
-
-on:
-  workflow_dispatch:
-
-jobs:
-  build:
-    runs-on: ubuntu-latest
-
-    env:
-      python-version: '3.10'
-
-    steps:
-    - name: Checkout repository
-      uses: actions/checkout@v3
-
-    - name: Set up Python ${{ env.python-version }}
-      uses: actions/setup-python@v4
-      with:
-        python-version: ${{ env.python-version }}
-
-    - name: Install dependencies
-      run: |
-        python -m pip install --upgrade pip
-        pip install -r requirements.txt
-
-    - name: benchmark
-      env:
-        OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
-      run: |
-         python benchmark/benchmark_entrepreneur_gpt_with_undecisive_user.py

.github/workflows/ci.yml

@@ -1,77 +0,0 @@
-name: Python CI
-
-on:
-  push:
-    branches: [ master ]
-  pull_request:
-    branches: [ master ]
-
-concurrency:
-  group: ${{ format('ci-{0}', github.head_ref && format('pr-{0}', github.event.pull_request.number) || github.sha) }}
-  cancel-in-progress: ${{ github.event_name == 'pull_request' }}
-
-jobs:
-  lint:
-    runs-on: ubuntu-latest
-    env:
-      min-python-version: "3.10"
-
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v3
-
-      - name: Set up Python ${{ env.min-python-version }}
-        uses: actions/setup-python@v2
-        with:
-          python-version: ${{ env.min-python-version }}
-
-      - name: Install dependencies
-        run: |
-          python -m pip install --upgrade pip
-          pip install -r requirements.txt
-
-      - name: Lint with flake8
-        run: flake8
-
-      - name: Check black formatting
-        run: black . --check
-        if: success() || failure()
-
-      - name: Check isort formatting
-        run: isort . --check
-        if: success() || failure()
-
-  test:
-    permissions:
-      # Gives the action the necessary permissions for publishing new
-      # comments in pull requests.
-      pull-requests: write
-      # Gives the action the necessary permissions for pushing data to the
-      # python-coverage-comment-action branch, and for editing existing
-      # comments (to avoid publishing multiple comments in the same PR)
-      contents: write
-    runs-on: ubuntu-latest
-    strategy:
-      matrix:
-        python-version: ["3.10", "3.11"]
-
-    steps:
-      - name: Check out repository
-        uses: actions/checkout@v3
-
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
-        with:
-          python-version: ${{ matrix.python-version }}
-
-      - name: Install dependencies
-        run: |
-          python -m pip install --upgrade pip
-          pip install -r requirements.txt
-
-      - name: Run unittest tests with coverage
-        run: |
-          pytest --cov=autogpt --cov-report term-missing --cov-branch --cov-report xml --cov-report term
-
-      - name: Upload coverage reports to Codecov
-        uses: codecov/codecov-action@v3

.github/workflows/classic-autogpt-ci.yml

@@ -0,0 +1,145 @@
+name: Classic - AutoGPT CI
+
+on:
+  push:
+    branches: [ master, dev, ci-test* ]
+    paths:
+      - '.github/workflows/classic-autogpt-ci.yml'
+      - 'classic/original_autogpt/**'
+  pull_request:
+    branches: [ master, dev, release-* ]
+    paths:
+      - '.github/workflows/classic-autogpt-ci.yml'
+      - 'classic/original_autogpt/**'
+
+concurrency:
+  group: ${{ format('classic-autogpt-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
+  cancel-in-progress: ${{ startsWith(github.event_name, 'pull_request') }}
+
+defaults:
+  run:
+    shell: bash
+    working-directory: classic/original_autogpt
+
+jobs:
+  test:
+    permissions:
+      contents: read
+    timeout-minutes: 30
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.10"]
+        platform-os: [ubuntu, macos, macos-arm64, windows]
+    runs-on: ${{ matrix.platform-os != 'macos-arm64' && format('{0}-latest', matrix.platform-os) || 'macos-14' }}
+
+    steps:
+      # Quite slow on macOS (2~4 minutes to set up Docker)
+      # - name: Set up Docker (macOS)
+      #   if: runner.os == 'macOS'
+      #   uses: crazy-max/ghaction-setup-docker@v3
+
+      - name: Start MinIO service (Linux)
+        if: runner.os == 'Linux'
+        working-directory: '.'
+        run: |
+          docker pull minio/minio:edge-cicd
+          docker run -d -p 9000:9000 minio/minio:edge-cicd
+
+      - name: Start MinIO service (macOS)
+        if: runner.os == 'macOS'
+        working-directory: ${{ runner.temp }}
+        run: |
+          brew install minio/stable/minio
+          mkdir data
+          minio server ./data &
+
+      # No MinIO on Windows:
+      # - Windows doesn't support running Linux Docker containers
+      # - It doesn't seem possible to start background processes on Windows. They are
+      #   killed after the step returns.
+      #   See: https://github.com/actions/runner/issues/598#issuecomment-2011890429
+
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          submodules: true
+
+      - name: Configure git user Auto-GPT-Bot
+        run: |
+          git config --global user.name "Auto-GPT-Bot"
+          git config --global user.email "github-bot@agpt.co"
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - id: get_date
+        name: Get date
+        run: echo "date=$(date +'%Y-%m-%d')" >> $GITHUB_OUTPUT
+
+      - name: Set up Python dependency cache
+        # On Windows, unpacking cached dependencies takes longer than just installing them
+        if: runner.os != 'Windows'
+        uses: actions/cache@v4
+        with:
+          path: ${{ runner.os == 'macOS' && '~/Library/Caches/pypoetry' || '~/.cache/pypoetry' }}
+          key: poetry-${{ runner.os }}-${{ hashFiles('classic/original_autogpt/poetry.lock') }}
+
+      - name: Install Poetry (Unix)
+        if: runner.os != 'Windows'
+        run: |
+          curl -sSL https://install.python-poetry.org | python3 -
+
+          if [ "${{ runner.os }}" = "macOS" ]; then
+            PATH="$HOME/.local/bin:$PATH"
+            echo "$HOME/.local/bin" >> $GITHUB_PATH
+          fi
+
+      - name: Install Poetry (Windows)
+        if: runner.os == 'Windows'
+        shell: pwsh
+        run: |
+          (Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | python -
+
+          $env:PATH += ";$env:APPDATA\Python\Scripts"
+          echo "$env:APPDATA\Python\Scripts" >> $env:GITHUB_PATH
+
+      - name: Install Python dependencies
+        run: poetry install
+
+      - name: Run pytest with coverage
+        run: |
+          poetry run pytest -vv \
+            --cov=autogpt --cov-branch --cov-report term-missing --cov-report xml \
+            --numprocesses=logical --durations=10 \
+            --junitxml=junit.xml -o junit_family=legacy \
+            tests/unit tests/integration
+        env:
+          CI: true
+          PLAIN_OUTPUT: True
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+          S3_ENDPOINT_URL: ${{ runner.os != 'Windows' && 'http://127.0.0.1:9000' || '' }}
+          AWS_ACCESS_KEY_ID: minioadmin
+          AWS_SECRET_ACCESS_KEY: minioadmin
+
+      - name: Upload test results to Codecov
+        if: ${{ !cancelled() }}  # Run even if tests fail
+        uses: codecov/test-results-action@v1
+        with:
+          token: ${{ secrets.CODECOV_TOKEN }}
+
+      - name: Upload coverage reports to Codecov
+        uses: codecov/codecov-action@v5
+        with:
+          token: ${{ secrets.CODECOV_TOKEN }}
+          flags: autogpt-agent,${{ runner.os }}
+
+      - name: Upload logs to artifact
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          name: test-logs
+          path: classic/original_autogpt/logs/

.github/workflows/classic-autogpt-docker-cache-clean.yml

@@ -0,0 +1,60 @@
+name: Classic - Purge Auto-GPT Docker CI cache
+
+on:
+  schedule:
+    - cron: 20 4 * * 1,4
+
+env:
+  BASE_BRANCH: dev
+  IMAGE_NAME: auto-gpt
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        build-type: [release, dev]
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - id: build
+        name: Build image
+        uses: docker/build-push-action@v6
+        with:
+          context: classic/
+          file: classic/Dockerfile.autogpt
+          build-args: BUILD_TYPE=${{ matrix.build-type }}
+          load: true # save to docker images
+          # use GHA cache as read-only
+          cache-to: type=gha,scope=autogpt-docker-${{ matrix.build-type }},mode=max
+
+      - name: Generate build report
+        env:
+          event_name: ${{ github.event_name }}
+          event_ref: ${{ github.event.schedule }}
+
+          build_type: ${{ matrix.build-type }}
+
+          prod_branch: master
+          dev_branch: dev
+          repository: ${{ github.repository }}
+          base_branch: ${{ github.ref_name != 'master' && github.ref_name != 'dev' && 'dev' || 'master' }}
+
+          current_ref: ${{ github.ref_name }}
+          commit_hash: ${{ github.sha }}
+          source_url: ${{ format('{0}/tree/{1}', github.event.repository.url, github.sha) }}
+          push_forced_label:
+
+          new_commits_json: ${{ null }}
+          compare_url_template: ${{ format('/{0}/compare/{{base}}...{{head}}', github.repository) }}
+
+          github_context_json: ${{ toJSON(github) }}
+          job_env_json: ${{ toJSON(env) }}
+          vars_json: ${{ toJSON(vars) }}
+
+        run: .github/workflows/scripts/docker-ci-summary.sh >> $GITHUB_STEP_SUMMARY
+        continue-on-error: true

.github/workflows/classic-autogpt-docker-ci.yml

@@ -0,0 +1,166 @@
+name: Classic - AutoGPT Docker CI
+
+on:
+  push:
+    branches: [master, dev]
+    paths:
+      - '.github/workflows/classic-autogpt-docker-ci.yml'
+      - 'classic/original_autogpt/**'
+      - 'classic/forge/**'
+  pull_request:
+    branches: [ master, dev, release-* ]
+    paths:
+      - '.github/workflows/classic-autogpt-docker-ci.yml'
+      - 'classic/original_autogpt/**'
+      - 'classic/forge/**'
+
+concurrency:
+  group: ${{ format('classic-autogpt-docker-ci-{0}', github.head_ref && format('pr-{0}', github.event.pull_request.number) || github.sha) }}
+  cancel-in-progress: ${{ github.event_name == 'pull_request' }}
+
+defaults:
+  run:
+    working-directory: classic/original_autogpt
+
+env:
+  IMAGE_NAME: auto-gpt
+  DEPLOY_IMAGE_NAME: ${{ secrets.DOCKER_USER && format('{0}/', secrets.DOCKER_USER) || '' }}auto-gpt
+  DEV_IMAGE_TAG: latest-dev
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        build-type: [release, dev]
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - if: runner.debug
+        run: |
+          ls -al
+          du -hs *
+
+      - id: build
+        name: Build image
+        uses: docker/build-push-action@v6
+        with:
+          context: classic/
+          file: classic/Dockerfile.autogpt
+          build-args: BUILD_TYPE=${{ matrix.build-type }}
+          tags: ${{ env.IMAGE_NAME }}
+          labels: GIT_REVISION=${{ github.sha }}
+          load: true # save to docker images
+          # cache layers in GitHub Actions cache to speed up builds
+          cache-from: type=gha,scope=autogpt-docker-${{ matrix.build-type }}
+          cache-to: type=gha,scope=autogpt-docker-${{ matrix.build-type }},mode=max
+
+      - name: Generate build report
+        env:
+          event_name: ${{ github.event_name }}
+          event_ref: ${{ github.event.ref }}
+          event_ref_type: ${{ github.event.ref}}
+
+          build_type: ${{ matrix.build-type }}
+
+          prod_branch: master
+          dev_branch: dev
+          repository: ${{ github.repository }}
+          base_branch: ${{ github.ref_name != 'master' && github.ref_name != 'dev' && 'dev' || 'master' }}
+
+          current_ref: ${{ github.ref_name }}
+          commit_hash: ${{ github.event.after }}
+          source_url: ${{ format('{0}/tree/{1}', github.event.repository.url, github.event.release && github.event.release.tag_name || github.sha) }}
+          push_forced_label: ${{ github.event.forced && '☢️ forced' || '' }}
+
+          new_commits_json: ${{ toJSON(github.event.commits) }}
+          compare_url_template: ${{ format('/{0}/compare/{{base}}...{{head}}', github.repository) }}
+
+          github_context_json: ${{ toJSON(github) }}
+          job_env_json: ${{ toJSON(env) }}
+          vars_json: ${{ toJSON(vars) }}
+
+        run: .github/workflows/scripts/docker-ci-summary.sh >> $GITHUB_STEP_SUMMARY
+        continue-on-error: true
+
+  test:
+    runs-on: ubuntu-latest
+    timeout-minutes: 10
+
+    services:
+      minio:
+        image: minio/minio:edge-cicd
+        options: >
+          --name=minio
+          --health-interval=10s --health-timeout=5s --health-retries=3
+          --health-cmd="curl -f http://localhost:9000/minio/health/live"
+
+    steps:
+      - name: Check out repository
+        uses: actions/checkout@v4
+        with:
+          submodules: true
+
+      - if: github.event_name == 'push'
+        name: Log in to Docker hub
+        uses: docker/login-action@v3
+        with:
+          username: ${{ secrets.DOCKER_USER }}
+          password: ${{ secrets.DOCKER_PASSWORD }}
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - id: build
+        name: Build image
+        uses: docker/build-push-action@v6
+        with:
+          context: classic/
+          file: classic/Dockerfile.autogpt
+          build-args: BUILD_TYPE=dev # include pytest
+          tags: >
+            ${{ env.IMAGE_NAME }},
+            ${{ env.DEPLOY_IMAGE_NAME }}:${{ env.DEV_IMAGE_TAG }}
+          labels: GIT_REVISION=${{ github.sha }}
+          load: true # save to docker images
+          # cache layers in GitHub Actions cache to speed up builds
+          cache-from: type=gha,scope=autogpt-docker-dev
+          cache-to: type=gha,scope=autogpt-docker-dev,mode=max
+
+      - id: test
+        name: Run tests
+        env:
+          CI: true
+          PLAIN_OUTPUT: True
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+          S3_ENDPOINT_URL: http://minio:9000
+          AWS_ACCESS_KEY_ID: minioadmin
+          AWS_SECRET_ACCESS_KEY: minioadmin
+        run: |
+          set +e
+          docker run --env CI --env OPENAI_API_KEY \
+            --network container:minio \
+            --env S3_ENDPOINT_URL --env AWS_ACCESS_KEY_ID --env AWS_SECRET_ACCESS_KEY \
+            --entrypoint poetry ${{ env.IMAGE_NAME }} run \
+            pytest -v --cov=autogpt --cov-branch --cov-report term-missing \
+            --numprocesses=4 --durations=10 \
+            tests/unit tests/integration 2>&1 | tee test_output.txt
+
+          test_failure=${PIPESTATUS[0]}
+
+          cat << $EOF >> $GITHUB_STEP_SUMMARY
+          # Tests $([ $test_failure = 0 ] && echo '✅' || echo '❌')
+          \`\`\`
+          $(cat test_output.txt)
+          \`\`\`
+          $EOF
+
+          exit $test_failure
+
+      - if: github.event_name == 'push' && github.ref_name == 'master'
+        name: Push image to Docker Hub
+        run: docker push ${{ env.DEPLOY_IMAGE_NAME }}:${{ env.DEV_IMAGE_TAG }}

.github/workflows/classic-autogpt-docker-release.yml

@@ -0,0 +1,87 @@
+name: Classic - AutoGPT Docker Release
+
+on:
+  release:
+    types: [published, edited]
+
+  workflow_dispatch:
+    inputs:
+      no_cache:
+        type: boolean
+        description: 'Build from scratch, without using cached layers'
+
+env:
+  IMAGE_NAME: auto-gpt
+  DEPLOY_IMAGE_NAME: ${{ secrets.DOCKER_USER }}/auto-gpt
+
+jobs:
+  build:
+    if: startsWith(github.ref, 'refs/tags/autogpt-')
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Log in to Docker hub
+        uses: docker/login-action@v3
+        with:
+          username: ${{ secrets.DOCKER_USER }}
+          password: ${{ secrets.DOCKER_PASSWORD }}
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+        # slashes are not allowed in image tags, but can appear in git branch or tag names
+      - id: sanitize_tag
+        name: Sanitize image tag
+        run: |
+          tag=${raw_tag//\//-}
+          echo tag=${tag#autogpt-} >> $GITHUB_OUTPUT
+        env:
+          raw_tag: ${{ github.ref_name }}
+
+      - id: build
+        name: Build image
+        uses: docker/build-push-action@v6
+        with:
+          context: classic/
+          file: Dockerfile.autogpt
+          build-args: BUILD_TYPE=release
+          load: true # save to docker images
+          # push: true  # TODO: uncomment when this issue is fixed: https://github.com/moby/buildkit/issues/1555
+          tags: >
+            ${{ env.IMAGE_NAME }},
+            ${{ env.DEPLOY_IMAGE_NAME }}:latest,
+            ${{ env.DEPLOY_IMAGE_NAME }}:${{ steps.sanitize_tag.outputs.tag }}
+          labels: GIT_REVISION=${{ github.sha }}
+
+          # cache layers in GitHub Actions cache to speed up builds
+          cache-from: ${{ !inputs.no_cache && 'type=gha' || '' }},scope=autogpt-docker-release
+          cache-to: type=gha,scope=autogpt-docker-release,mode=max
+
+      - name: Push image to Docker Hub
+        run: docker push --all-tags ${{ env.DEPLOY_IMAGE_NAME }}
+
+      - name: Generate build report
+        env:
+          event_name: ${{ github.event_name }}
+          event_ref: ${{ github.event.ref }}
+          event_ref_type: ${{ github.event.ref}}
+          inputs_no_cache: ${{ inputs.no_cache }}
+
+          prod_branch: master
+          dev_branch: dev
+          repository: ${{ github.repository }}
+          base_branch: ${{ github.ref_name != 'master' && github.ref_name != 'dev' && 'dev' || 'master' }}
+
+          ref_type: ${{ github.ref_type }}
+          current_ref: ${{ github.ref_name }}
+          commit_hash: ${{ github.sha }}
+          source_url: ${{ format('{0}/tree/{1}', github.event.repository.url, github.event.release && github.event.release.tag_name || github.sha) }}
+
+          github_context_json: ${{ toJSON(github) }}
+          job_env_json: ${{ toJSON(env) }}
+          vars_json: ${{ toJSON(vars) }}
+
+        run: .github/workflows/scripts/docker-release-summary.sh >> $GITHUB_STEP_SUMMARY
+        continue-on-error: true

.github/workflows/classic-autogpts-ci.yml

@@ -0,0 +1,76 @@
+name: Classic - Agent smoke tests
+
+on:
+  workflow_dispatch:
+  schedule:
+    - cron: '0 8 * * *'
+  push:
+    branches: [ master, dev, ci-test* ]
+    paths:
+      - '.github/workflows/classic-autogpts-ci.yml'
+      - 'classic/original_autogpt/**'
+      - 'classic/forge/**'
+      - 'classic/benchmark/**'
+      - 'classic/run'
+      - 'classic/cli.py'
+      - 'classic/setup.py'
+      - '!**/*.md'
+  pull_request:
+    branches: [ master, dev, release-* ]
+    paths:
+      - '.github/workflows/classic-autogpts-ci.yml'
+      - 'classic/original_autogpt/**'
+      - 'classic/forge/**'
+      - 'classic/benchmark/**'
+      - 'classic/run'
+      - 'classic/cli.py'
+      - 'classic/setup.py'
+      - '!**/*.md'
+
+defaults:
+  run:
+    shell: bash
+    working-directory: classic
+
+jobs:
+  serve-agent-protocol:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        agent-name: [ original_autogpt ]
+      fail-fast: false
+    timeout-minutes: 20
+    env:
+      min-python-version: '3.10'
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          submodules: true
+
+      - name: Set up Python ${{ env.min-python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ env.min-python-version }}
+
+      - name: Install Poetry
+        working-directory: ./classic/${{ matrix.agent-name }}/
+        run: |
+          curl -sSL https://install.python-poetry.org | python -
+
+      - name: Run regression tests
+        run: |
+          ./run agent start ${{ matrix.agent-name }}
+          cd ${{ matrix.agent-name }}
+          poetry run agbenchmark --mock --test=BasicRetrieval --test=Battleship --test=WebArenaTask_0
+          poetry run agbenchmark --test=WriteFile
+        env:
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+          AGENT_NAME: ${{ matrix.agent-name }}
+          REQUESTS_CA_BUNDLE: /etc/ssl/certs/ca-certificates.crt
+          HELICONE_CACHE_ENABLED: false
+          HELICONE_PROPERTY_AGENT: ${{ matrix.agent-name }}
+          REPORTS_FOLDER: ${{ format('../../reports/{0}', matrix.agent-name) }}
+          TELEMETRY_ENVIRONMENT: autogpt-ci
+          TELEMETRY_OPT_IN: ${{ github.ref_name == 'master' }}

.github/workflows/classic-benchmark-ci.yml

@@ -0,0 +1,176 @@
+name: Classic - AGBenchmark CI
+
+on:
+  push:
+    branches: [ master, dev, ci-test* ]
+    paths:
+      - 'classic/benchmark/**'
+      - '!classic/benchmark/reports/**'
+      - .github/workflows/classic-benchmark-ci.yml
+  pull_request:
+    branches: [ master, dev, release-* ]
+    paths:
+      - 'classic/benchmark/**'
+      - '!classic/benchmark/reports/**'
+      - .github/workflows/classic-benchmark-ci.yml
+
+concurrency:
+  group: ${{ format('benchmark-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
+  cancel-in-progress: ${{ startsWith(github.event_name, 'pull_request') }}
+
+defaults:
+  run:
+    shell: bash
+
+env:
+  min-python-version: '3.10'
+
+jobs:
+  test:
+    permissions:
+      contents: read
+    timeout-minutes: 30
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.10"]
+        platform-os: [ubuntu, macos, macos-arm64, windows]
+    runs-on: ${{ matrix.platform-os != 'macos-arm64' && format('{0}-latest', matrix.platform-os) || 'macos-14' }}
+    defaults:
+      run:
+        shell: bash
+        working-directory: classic/benchmark
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          submodules: true
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Set up Python dependency cache
+        # On Windows, unpacking cached dependencies takes longer than just installing them
+        if: runner.os != 'Windows'
+        uses: actions/cache@v4
+        with:
+          path: ${{ runner.os == 'macOS' && '~/Library/Caches/pypoetry' || '~/.cache/pypoetry' }}
+          key: poetry-${{ runner.os }}-${{ hashFiles('classic/benchmark/poetry.lock') }}
+
+      - name: Install Poetry (Unix)
+        if: runner.os != 'Windows'
+        run: |
+          curl -sSL https://install.python-poetry.org | python3 -
+
+          if [ "${{ runner.os }}" = "macOS" ]; then
+            PATH="$HOME/.local/bin:$PATH"
+            echo "$HOME/.local/bin" >> $GITHUB_PATH
+          fi
+
+      - name: Install Poetry (Windows)
+        if: runner.os == 'Windows'
+        shell: pwsh
+        run: |
+          (Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | python -
+
+          $env:PATH += ";$env:APPDATA\Python\Scripts"
+          echo "$env:APPDATA\Python\Scripts" >> $env:GITHUB_PATH
+
+      - name: Install Python dependencies
+        run: poetry install
+
+      - name: Run pytest with coverage
+        run: |
+          poetry run pytest -vv \
+            --cov=agbenchmark --cov-branch --cov-report term-missing --cov-report xml \
+            --durations=10 \
+            --junitxml=junit.xml -o junit_family=legacy \
+            tests
+        env:
+          CI: true
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+
+      - name: Upload test results to Codecov
+        if: ${{ !cancelled() }}  # Run even if tests fail
+        uses: codecov/test-results-action@v1
+        with:
+          token: ${{ secrets.CODECOV_TOKEN }}
+
+      - name: Upload coverage reports to Codecov
+        uses: codecov/codecov-action@v5
+        with:
+          token: ${{ secrets.CODECOV_TOKEN }}
+          flags: agbenchmark,${{ runner.os }}
+
+  self-test-with-agent:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        agent-name: [forge]
+      fail-fast: false
+    timeout-minutes: 20
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          submodules: true
+
+      - name: Set up Python ${{ env.min-python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ env.min-python-version }}
+
+      - name: Install Poetry
+        run: |
+          curl -sSL https://install.python-poetry.org | python -
+
+      - name: Run regression tests
+        working-directory: classic
+        run: |
+          ./run agent start ${{ matrix.agent-name }}
+          cd ${{ matrix.agent-name }}
+
+          set +e # Ignore non-zero exit codes and continue execution
+          echo "Running the following command: poetry run agbenchmark --maintain --mock"
+          poetry run agbenchmark --maintain --mock
+          EXIT_CODE=$?
+          set -e  # Stop ignoring non-zero exit codes
+          # Check if the exit code was 5, and if so, exit with 0 instead
+          if [ $EXIT_CODE -eq 5 ]; then
+            echo "regression_tests.json is empty."
+          fi
+
+          echo "Running the following command: poetry run agbenchmark --mock"
+          poetry run agbenchmark --mock
+
+          echo "Running the following command: poetry run agbenchmark --mock --category=data"
+          poetry run agbenchmark --mock --category=data
+
+          echo "Running the following command: poetry run agbenchmark --mock --category=coding"
+          poetry run agbenchmark --mock --category=coding
+
+          # echo "Running the following command: poetry run agbenchmark --test=WriteFile"
+          # poetry run agbenchmark --test=WriteFile
+          cd ../benchmark
+          poetry install
+          echo "Adding the BUILD_SKILL_TREE environment variable. This will attempt to add new elements in the skill tree. If new elements are added, the CI fails because they should have been pushed"
+          export BUILD_SKILL_TREE=true
+
+          # poetry run agbenchmark --mock
+
+          # CHANGED=$(git diff --name-only | grep -E '(agbenchmark/challenges)|(../classic/frontend/assets)') || echo "No diffs"
+          # if [ ! -z "$CHANGED" ]; then
+          #   echo "There are unstaged changes please run agbenchmark and commit those changes since they are needed."
+          #   echo "$CHANGED"
+          #   exit 1
+          # else
+          #   echo "No unstaged changes."
+          # fi
+        env:
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+          TELEMETRY_ENVIRONMENT: autogpt-benchmark-ci
+          TELEMETRY_OPT_IN: ${{ github.ref_name == 'master' }}

.github/workflows/classic-benchmark_publish_package.yml

@@ -0,0 +1,55 @@
+name: Classic - Publish to PyPI
+
+on:
+  workflow_dispatch:
+
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: write
+    steps:
+    - name: Checkout repository
+      uses: actions/checkout@v4
+      with:
+        submodules: true
+        fetch-depth: 0
+
+    - name: Set up Python
+      uses: actions/setup-python@v5
+      with:
+        python-version: 3.8
+
+    - name: Install Poetry
+      working-directory: ./classic/benchmark/
+      run: |
+        curl -sSL https://install.python-poetry.org | python3 -
+        echo "$HOME/.poetry/bin" >> $GITHUB_PATH
+
+    - name: Build project for distribution
+      working-directory: ./classic/benchmark/
+      run: poetry build
+
+    - name: Install dependencies
+      working-directory: ./classic/benchmark/
+      run: poetry install
+
+    - name: Check Version
+      working-directory: ./classic/benchmark/
+      id: check-version
+      run: |
+        echo version=$(poetry version --short) >> $GITHUB_OUTPUT
+
+    - name: Create Release
+      uses: ncipollo/release-action@v1
+      with:
+        artifacts: "classic/benchmark/dist/*"
+        token: ${{ secrets.GITHUB_TOKEN }}
+        draft: false
+        generateReleaseNotes: false
+        tag: agbenchmark-v${{ steps.check-version.outputs.version }}
+        commit: master
+
+    - name: Build and publish
+      working-directory: ./classic/benchmark/
+      run: poetry publish -u __token__ -p ${{ secrets.PYPI_API_TOKEN }}

.github/workflows/classic-forge-ci.yml

@@ -0,0 +1,243 @@
+name: Classic - Forge CI
+
+on:
+  push:
+    branches: [ master, dev, ci-test* ]
+    paths:
+      - '.github/workflows/classic-forge-ci.yml'
+      - 'classic/forge/**'
+      - '!classic/forge/tests/vcr_cassettes'
+  pull_request:
+    branches: [ master, dev, release-* ]
+    paths:
+      - '.github/workflows/classic-forge-ci.yml'
+      - 'classic/forge/**'
+      - '!classic/forge/tests/vcr_cassettes'
+
+concurrency:
+  group: ${{ format('forge-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
+  cancel-in-progress: ${{ startsWith(github.event_name, 'pull_request') }}
+
+defaults:
+  run:
+    shell: bash
+    working-directory: classic/forge
+
+jobs:
+  test:
+    permissions:
+      contents: read
+    timeout-minutes: 30
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.10"]
+        platform-os: [ubuntu, macos, macos-arm64, windows]
+    runs-on: ${{ matrix.platform-os != 'macos-arm64' && format('{0}-latest', matrix.platform-os) || 'macos-14' }}
+
+    steps:
+      # Quite slow on macOS (2~4 minutes to set up Docker)
+      # - name: Set up Docker (macOS)
+      #   if: runner.os == 'macOS'
+      #   uses: crazy-max/ghaction-setup-docker@v3
+
+      - name: Start MinIO service (Linux)
+        if: runner.os == 'Linux'
+        working-directory: '.'
+        run: |
+          docker pull minio/minio:edge-cicd
+          docker run -d -p 9000:9000 minio/minio:edge-cicd
+
+      - name: Start MinIO service (macOS)
+        if: runner.os == 'macOS'
+        working-directory: ${{ runner.temp }}
+        run: |
+          brew install minio/stable/minio
+          mkdir data
+          minio server ./data &
+
+      # No MinIO on Windows:
+      # - Windows doesn't support running Linux Docker containers
+      # - It doesn't seem possible to start background processes on Windows. They are
+      #   killed after the step returns.
+      #   See: https://github.com/actions/runner/issues/598#issuecomment-2011890429
+
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          submodules: true
+
+      - name: Checkout cassettes
+        if: ${{ startsWith(github.event_name, 'pull_request') }}
+        env:
+          PR_BASE: ${{ github.event.pull_request.base.ref }}
+          PR_BRANCH: ${{ github.event.pull_request.head.ref }}
+          PR_AUTHOR: ${{ github.event.pull_request.user.login }}
+        run: |
+          cassette_branch="${PR_AUTHOR}-${PR_BRANCH}"
+          cassette_base_branch="${PR_BASE}"
+          cd tests/vcr_cassettes
+
+          if ! git ls-remote --exit-code --heads origin $cassette_base_branch ; then
+            cassette_base_branch="master"
+          fi
+
+          if git ls-remote --exit-code --heads origin $cassette_branch ; then
+            git fetch origin $cassette_branch
+            git fetch origin $cassette_base_branch
+
+            git checkout $cassette_branch
+
+            # Pick non-conflicting cassette updates from the base branch
+            git merge --no-commit --strategy-option=ours origin/$cassette_base_branch
+            echo "Using cassettes from mirror branch '$cassette_branch'," \
+              "synced to upstream branch '$cassette_base_branch'."
+          else
+            git checkout -b $cassette_branch
+            echo "Branch '$cassette_branch' does not exist in cassette submodule." \
+              "Using cassettes from '$cassette_base_branch'."
+          fi
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Set up Python dependency cache
+        # On Windows, unpacking cached dependencies takes longer than just installing them
+        if: runner.os != 'Windows'
+        uses: actions/cache@v4
+        with:
+          path: ${{ runner.os == 'macOS' && '~/Library/Caches/pypoetry' || '~/.cache/pypoetry' }}
+          key: poetry-${{ runner.os }}-${{ hashFiles('classic/forge/poetry.lock') }}
+
+      - name: Install Poetry (Unix)
+        if: runner.os != 'Windows'
+        run: |
+          curl -sSL https://install.python-poetry.org | python3 -
+
+          if [ "${{ runner.os }}" = "macOS" ]; then
+            PATH="$HOME/.local/bin:$PATH"
+            echo "$HOME/.local/bin" >> $GITHUB_PATH
+          fi
+
+      - name: Install Poetry (Windows)
+        if: runner.os == 'Windows'
+        shell: pwsh
+        run: |
+          (Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | python -
+
+          $env:PATH += ";$env:APPDATA\Python\Scripts"
+          echo "$env:APPDATA\Python\Scripts" >> $env:GITHUB_PATH
+
+      - name: Install Python dependencies
+        run: poetry install
+
+      - name: Run pytest with coverage
+        run: |
+          poetry run pytest -vv \
+            --cov=forge --cov-branch --cov-report term-missing --cov-report xml \
+            --durations=10 \
+            --junitxml=junit.xml -o junit_family=legacy \
+            forge
+        env:
+          CI: true
+          PLAIN_OUTPUT: True
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+          S3_ENDPOINT_URL: ${{ runner.os != 'Windows' && 'http://127.0.0.1:9000' || '' }}
+          AWS_ACCESS_KEY_ID: minioadmin
+          AWS_SECRET_ACCESS_KEY: minioadmin
+
+      - name: Upload test results to Codecov
+        if: ${{ !cancelled() }}  # Run even if tests fail
+        uses: codecov/test-results-action@v1
+        with:
+          token: ${{ secrets.CODECOV_TOKEN }}
+
+      - name: Upload coverage reports to Codecov
+        uses: codecov/codecov-action@v5
+        with:
+          token: ${{ secrets.CODECOV_TOKEN }}
+          flags: forge,${{ runner.os }}
+
+      - id: setup_git_auth
+        name: Set up git token authentication
+        # Cassettes may be pushed even when tests fail
+        if: success() || failure()
+        run: |
+          config_key="http.${{ github.server_url }}/.extraheader"
+          if [ "${{ runner.os }}" = 'macOS' ]; then
+            base64_pat=$(echo -n "pat:${{ secrets.PAT_REVIEW }}" | base64)
+          else
+            base64_pat=$(echo -n "pat:${{ secrets.PAT_REVIEW }}" | base64 -w0)
+          fi
+
+          git config "$config_key" \
+            "Authorization: Basic $base64_pat"
+
+          cd tests/vcr_cassettes
+          git config "$config_key" \
+            "Authorization: Basic $base64_pat"
+
+          echo "config_key=$config_key" >> $GITHUB_OUTPUT
+
+      - id: push_cassettes
+        name: Push updated cassettes
+        # For pull requests, push updated cassettes even when tests fail
+        if: github.event_name == 'push' || (! github.event.pull_request.head.repo.fork && (success() || failure()))
+        env:
+          PR_BRANCH: ${{ github.event.pull_request.head.ref }}
+          PR_AUTHOR: ${{ github.event.pull_request.user.login }}
+        run: |
+          if [ "${{ startsWith(github.event_name, 'pull_request') }}" = "true" ]; then
+            is_pull_request=true
+            cassette_branch="${PR_AUTHOR}-${PR_BRANCH}"
+          else
+            cassette_branch="${{ github.ref_name }}"
+          fi
+
+          cd tests/vcr_cassettes
+          # Commit & push changes to cassettes if any
+          if ! git diff --quiet; then
+            git add .
+            git commit -m "Auto-update cassettes"
+            git push origin HEAD:$cassette_branch
+            if [ ! $is_pull_request ]; then
+              cd ../..
+              git add tests/vcr_cassettes
+              git commit -m "Update cassette submodule"
+              git push origin HEAD:$cassette_branch
+            fi
+            echo "updated=true" >> $GITHUB_OUTPUT
+          else
+            echo "updated=false" >> $GITHUB_OUTPUT
+            echo "No cassette changes to commit"
+          fi
+
+      - name: Post Set up git token auth
+        if: steps.setup_git_auth.outcome == 'success'
+        run: |
+          git config --unset-all '${{ steps.setup_git_auth.outputs.config_key }}'
+          git submodule foreach git config --unset-all '${{ steps.setup_git_auth.outputs.config_key }}'
+
+      - name: Apply "behaviour change" label and comment on PR
+        if: ${{ startsWith(github.event_name, 'pull_request') }}
+        run: |
+          PR_NUMBER="${{ github.event.pull_request.number }}"
+          TOKEN="${{ secrets.PAT_REVIEW }}"
+          REPO="${{ github.repository }}"
+
+          if [[ "${{ steps.push_cassettes.outputs.updated }}" == "true" ]]; then
+            echo "Adding label and comment..."
+            echo $TOKEN | gh auth login --with-token
+            gh issue edit $PR_NUMBER --add-label "behaviour change"
+            gh issue comment $PR_NUMBER --body "You changed AutoGPT's behaviour on ${{ runner.os }}. The cassettes have been updated and will be merged to the submodule when this Pull Request gets merged."
+          fi
+
+      - name: Upload logs to artifact
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          name: test-logs
+          path: classic/forge/logs/

.github/workflows/classic-frontend-ci.yml

@@ -0,0 +1,60 @@
+name: Classic - Frontend CI/CD
+
+on:
+  push:
+    branches:
+      - master
+      - dev
+      - 'ci-test*' # This will match any branch that starts with "ci-test"
+    paths:
+      - 'classic/frontend/**'
+      - '.github/workflows/classic-frontend-ci.yml'
+  pull_request:
+    paths:
+      - 'classic/frontend/**'
+      - '.github/workflows/classic-frontend-ci.yml'
+
+jobs:
+  build:
+    permissions:
+      contents: write
+      pull-requests: write
+    runs-on: ubuntu-latest
+    env:
+      BUILD_BRANCH: ${{ format('classic-frontend-build/{0}', github.ref_name) }}
+
+    steps:
+      - name: Checkout Repo
+        uses: actions/checkout@v4
+
+      - name: Setup Flutter
+        uses: subosito/flutter-action@v2
+        with:
+          flutter-version: '3.13.2'
+
+      - name: Build Flutter to Web
+        run: |
+          cd classic/frontend
+          flutter build web --base-href /app/
+
+      # - name: Commit and Push to ${{ env.BUILD_BRANCH }}
+      #   if: github.event_name == 'push'
+      #   run: |
+      #     git config --local user.email "action@github.com"
+      #     git config --local user.name "GitHub Action"
+      #     git add classic/frontend/build/web
+      #     git checkout -B ${{ env.BUILD_BRANCH }}
+      #     git commit -m "Update frontend build to ${GITHUB_SHA:0:7}" -a
+      #     git push -f origin ${{ env.BUILD_BRANCH }}
+
+      - name: Create PR ${{ env.BUILD_BRANCH }} -> ${{ github.ref_name }}
+        if: github.event_name == 'push'
+        uses: peter-evans/create-pull-request@v7
+        with:
+          add-paths: classic/frontend/build/web
+          base: ${{ github.ref_name }}
+          branch: ${{ env.BUILD_BRANCH }}
+          delete-branch: true
+          title: "Update frontend build in `${{ github.ref_name }}`"
+          body: "This PR updates the frontend build based on commit ${{ github.sha }}."
+          commit-message: "Update frontend build based on commit ${{ github.sha }}"

.github/workflows/classic-python-checks.yml

@@ -0,0 +1,151 @@
+name: Classic - Python checks
+
+on:
+  push:
+    branches: [ master, dev, ci-test* ]
+    paths:
+      - '.github/workflows/classic-python-checks-ci.yml'
+      - 'classic/original_autogpt/**'
+      - 'classic/forge/**'
+      - 'classic/benchmark/**'
+      - '**.py'
+      - '!classic/forge/tests/vcr_cassettes'
+  pull_request:
+    branches: [ master, dev, release-* ]
+    paths:
+      - '.github/workflows/classic-python-checks-ci.yml'
+      - 'classic/original_autogpt/**'
+      - 'classic/forge/**'
+      - 'classic/benchmark/**'
+      - '**.py'
+      - '!classic/forge/tests/vcr_cassettes'
+
+concurrency:
+  group: ${{ format('classic-python-checks-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
+  cancel-in-progress: ${{ startsWith(github.event_name, 'pull_request') }}
+
+defaults:
+  run:
+    shell: bash
+
+jobs:
+  get-changed-parts:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - id: changes-in
+        name: Determine affected subprojects
+        uses: dorny/paths-filter@v3
+        with:
+          filters: |
+            original_autogpt:
+              - classic/original_autogpt/autogpt/**
+              - classic/original_autogpt/tests/**
+              - classic/original_autogpt/poetry.lock
+            forge:
+              - classic/forge/forge/**
+              - classic/forge/tests/**
+              - classic/forge/poetry.lock
+            benchmark:
+              - classic/benchmark/agbenchmark/**
+              - classic/benchmark/tests/**
+              - classic/benchmark/poetry.lock
+    outputs:
+      changed-parts: ${{ steps.changes-in.outputs.changes }}
+
+  lint:
+    needs: get-changed-parts
+    runs-on: ubuntu-latest
+    env:
+      min-python-version: "3.10"
+
+    strategy:
+      matrix:
+        sub-package: ${{ fromJson(needs.get-changed-parts.outputs.changed-parts) }}
+      fail-fast: false
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: Set up Python ${{ env.min-python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ env.min-python-version }}
+
+      - name: Set up Python dependency cache
+        uses: actions/cache@v4
+        with:
+          path: ~/.cache/pypoetry
+          key: ${{ runner.os }}-poetry-${{ hashFiles(format('{0}/poetry.lock', matrix.sub-package)) }}
+
+      - name: Install Poetry
+        run: curl -sSL https://install.python-poetry.org | python3 -
+
+      # Install dependencies
+
+      - name: Install Python dependencies
+        run: poetry -C classic/${{ matrix.sub-package }} install
+
+      # Lint
+
+      - name: Lint (isort)
+        run: poetry run isort --check .
+        working-directory: classic/${{ matrix.sub-package }}
+
+      - name: Lint (Black)
+        if: success() || failure()
+        run: poetry run black --check .
+        working-directory: classic/${{ matrix.sub-package }}
+
+      - name: Lint (Flake8)
+        if: success() || failure()
+        run: poetry run flake8 .
+        working-directory: classic/${{ matrix.sub-package }}
+
+  types:
+    needs: get-changed-parts
+    runs-on: ubuntu-latest
+    env:
+      min-python-version: "3.10"
+
+    strategy:
+      matrix:
+        sub-package: ${{ fromJson(needs.get-changed-parts.outputs.changed-parts) }}
+      fail-fast: false
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: Set up Python ${{ env.min-python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ env.min-python-version }}
+
+      - name: Set up Python dependency cache
+        uses: actions/cache@v4
+        with:
+          path: ~/.cache/pypoetry
+          key: ${{ runner.os }}-poetry-${{ hashFiles(format('{0}/poetry.lock', matrix.sub-package)) }}
+
+      - name: Install Poetry
+        run: curl -sSL https://install.python-poetry.org | python3 -
+
+      # Install dependencies
+
+      - name: Install Python dependencies
+        run: poetry -C classic/${{ matrix.sub-package }} install
+
+      # Typecheck
+
+      - name: Typecheck
+        if: success() || failure()
+        run: poetry run pyright
+        working-directory: classic/${{ matrix.sub-package }}

.github/workflows/codeql.yml

@@ -0,0 +1,98 @@
+# For most projects, this workflow file will not need changing; you simply need
+# to commit it to your repository.
+#
+# You may wish to alter this file to override the set of languages analyzed,
+# or to provide custom queries or build logic.
+#
+# ******** NOTE ********
+# We have attempted to detect the languages in your repository. Please check
+# the `language` matrix defined below to confirm you have the correct set of
+# supported CodeQL languages.
+#
+name: "CodeQL"
+
+on:
+  push:
+    branches: [ "master", "release-*", "dev" ]
+  pull_request:
+    branches: [ "master", "release-*", "dev" ]
+  merge_group:
+  schedule:
+    - cron: '15 4 * * 0'
+
+jobs:
+  analyze:
+    name: Analyze (${{ matrix.language }})
+    # Runner size impacts CodeQL analysis time. To learn more, please see:
+    #   - https://gh.io/recommended-hardware-resources-for-running-codeql
+    #   - https://gh.io/supported-runners-and-hardware-resources
+    #   - https://gh.io/using-larger-runners (GitHub.com only)
+    # Consider using larger runners or machines with greater resources for possible analysis time improvements.
+    runs-on: ${{ (matrix.language == 'swift' && 'macos-latest') || 'ubuntu-latest' }}
+    permissions:
+      # required for all workflows
+      security-events: write
+
+      # required to fetch internal or private CodeQL packs
+      packages: read
+
+      # only required for workflows in private repositories
+      actions: read
+      contents: read
+
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+        - language: typescript
+          build-mode: none
+        - language: python
+          build-mode: none
+        # CodeQL supports the following values keywords for 'language': 'c-cpp', 'csharp', 'go', 'java-kotlin', 'javascript-typescript', 'python', 'ruby', 'swift'
+        # Use `c-cpp` to analyze code written in C, C++ or both
+        # Use 'java-kotlin' to analyze code written in Java, Kotlin or both
+        # Use 'javascript-typescript' to analyze code written in JavaScript, TypeScript or both
+        # To learn more about changing the languages that are analyzed or customizing the build mode for your analysis,
+        # see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/customizing-your-advanced-setup-for-code-scanning.
+        # If you are analyzing a compiled language, you can modify the 'build-mode' for that language to customize how
+        # your codebase is analyzed, see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/codeql-code-scanning-for-compiled-languages
+    steps:
+    - name: Checkout repository
+      uses: actions/checkout@v4
+
+    # Initializes the CodeQL tools for scanning.
+    - name: Initialize CodeQL
+      uses: github/codeql-action/init@v3
+      with:
+        languages: ${{ matrix.language }}
+        build-mode: ${{ matrix.build-mode }}
+        # If you wish to specify custom queries, you can do so here or in a config file.
+        # By default, queries listed here will override any specified in a config file.
+        # Prefix the list here with "+" to use these queries and those in the config file.
+        config: |
+          paths-ignore:
+            - classic/frontend/build/**
+
+        # For more details on CodeQL's query packs, refer to: https://docs.github.com/en/code-security/code-scanning/automatically-scanning-your-code-for-vulnerabilities-and-errors/configuring-code-scanning#using-queries-in-ql-packs
+        # queries: security-extended,security-and-quality
+
+    # If the analyze step fails for one of the languages you are analyzing with
+    # "We were unable to automatically build your code", modify the matrix above
+    # to set the build mode to "manual" for that language. Then modify this step
+    # to build your code.
+    # ℹ️ Command-line programs to run using the OS shell.
+    # 📚 See https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstepsrun
+    - if: matrix.build-mode == 'manual'
+      shell: bash
+      run: |
+        echo 'If you are using a "manual" build mode for one or more of the' \
+          'languages you are analyzing, replace this with the commands to build' \
+          'your code, for example:'
+        echo '  make bootstrap'
+        echo '  make release'
+        exit 1
+
+    - name: Perform CodeQL Analysis
+      uses: github/codeql-action/analyze@v3
+      with:
+        category: "/language:${{matrix.language}}"

.github/workflows/docker-cache-clean.yml

@@ -1,58 +0,0 @@
-name: Purge Docker CI cache
-
-on:
-  schedule:
-    - cron: 20 4 * * 1,4
-
-env:
-  BASE_BRANCH: master
-  IMAGE_NAME: auto-gpt
-
-jobs:
-  build:
-    runs-on: ubuntu-latest
-    strategy:
-      matrix:
-        build-type: [release, dev]
-    steps:
-    - name: Checkout repository
-      uses: actions/checkout@v3
-
-    - name: Set up Docker Buildx
-      uses: docker/setup-buildx-action@v2
-
-    - id: build
-      name: Build image
-      uses: docker/build-push-action@v3
-      with:
-        build-args: BUILD_TYPE=${{ matrix.build-type }}
-        load: true    # save to docker images
-        # use GHA cache as read-only
-        cache-to: type=gha,scope=docker-${{ matrix.build-type }},mode=max
-
-    - name: Generate build report
-      env:
-        event_name: ${{ github.event_name }}
-        event_ref: ${{ github.event.schedule }}
-
-        build_type: ${{ matrix.build-type }}
-
-        prod_branch: stable
-        dev_branch: master
-        repository: ${{ github.repository }}
-        base_branch: ${{ github.ref_name != 'master' && github.ref_name != 'stable' && 'master' || 'stable' }}
-
-        current_ref: ${{ github.ref_name }}
-        commit_hash: ${{ github.sha }}
-        source_url: ${{ format('{0}/tree/{1}', github.event.repository.url, github.sha) }}
-        push_forced_label:
-
-        new_commits_json: ${{ null }}
-        compare_url_template: ${{ format('/{0}/compare/{{base}}...{{head}}', github.repository) }}
-
-        github_context_json: ${{ toJSON(github) }}
-        job_env_json: ${{ toJSON(env) }}
-        vars_json: ${{ toJSON(vars) }}
-
-      run: .github/workflows/scripts/docker-ci-summary.sh >> $GITHUB_STEP_SUMMARY
-      continue-on-error: true

.github/workflows/docker-ci.yml

@@ -1,115 +0,0 @@
-name: Docker CI
-
-on:
-  push:
-    branches: [ master ]
-  pull_request:
-    branches: [ master ]
-
-concurrency:
-  group: ${{ format('docker-ci-{0}', github.head_ref && format('pr-{0}', github.event.pull_request.number) || github.sha) }}
-  cancel-in-progress: ${{ github.event_name == 'pull_request' }}
-
-env:
-  IMAGE_NAME: auto-gpt
-
-jobs:
-  build:
-    runs-on: ubuntu-latest
-    strategy:
-      matrix:
-        build-type: [release, dev]
-    steps:
-    - name: Checkout repository
-      uses: actions/checkout@v3
-
-    - name: Set up Docker Buildx
-      uses: docker/setup-buildx-action@v2
-
-    - if: runner.debug
-      run: |
-        ls -al
-        du -hs *
-
-    - id: build
-      name: Build image
-      uses: docker/build-push-action@v3
-      with:
-        build-args: BUILD_TYPE=${{ matrix.build-type }}
-        tags: ${{ env.IMAGE_NAME }}
-        load: true    # save to docker images
-        # cache layers in GitHub Actions cache to speed up builds
-        cache-from: type=gha,scope=docker-${{ matrix.build-type }}
-        cache-to: type=gha,scope=docker-${{ matrix.build-type }},mode=max
-
-    - name: Generate build report
-      env:
-        event_name: ${{ github.event_name }}
-        event_ref: ${{ github.event.ref }}
-        event_ref_type: ${{ github.event.ref}}
-
-        build_type: ${{ matrix.build-type }}
-
-        prod_branch: stable
-        dev_branch: master
-        repository: ${{ github.repository }}
-        base_branch: ${{ github.ref_name != 'master' && github.ref_name != 'stable' && 'master' || 'stable' }}
-
-        current_ref: ${{ github.ref_name }}
-        commit_hash: ${{ github.event.after }}
-        source_url: ${{ format('{0}/tree/{1}', github.event.repository.url, github.event.release && github.event.release.tag_name || github.sha) }}
-        push_forced_label: ${{ github.event.forced && '☢️ forced' || '' }}
-
-        new_commits_json: ${{ toJSON(github.event.commits) }}
-        compare_url_template: ${{ format('/{0}/compare/{{base}}...{{head}}', github.repository) }}
-
-        github_context_json: ${{ toJSON(github) }}
-        job_env_json: ${{ toJSON(env) }}
-        vars_json: ${{ toJSON(vars) }}
-
-      run: .github/workflows/scripts/docker-ci-summary.sh >> $GITHUB_STEP_SUMMARY
-      continue-on-error: true
-
-  # Docker setup needs fixing before this is going to work: #1843
-  test:
-    runs-on: ubuntu-latest
-    needs: build
-    steps:
-    - name: Checkout repository
-      uses: actions/checkout@v3
-
-    - name: Set up Docker Buildx
-      uses: docker/setup-buildx-action@v2
-
-    - id: build
-      name: Build image
-      uses: docker/build-push-action@v3
-      with:
-        build-args: BUILD_TYPE=dev  # include pytest
-        tags: ${{ env.IMAGE_NAME }}
-        load: true                  # save to docker images
-        # cache layers in GitHub Actions cache to speed up builds
-        cache-from: type=gha,scope=docker-dev
-        cache-to: type=gha,scope=docker-dev,mode=max
-
-    - id: test
-      name: Run tests
-      env:
-        CI: true
-        OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
-      run: |
-        set +e
-        test_output=$(
-          docker run --env CI --env OPENAI_API_KEY --entrypoint python ${{ env.IMAGE_NAME }} -m \
-          pytest --cov=autogpt --cov-report term-missing --cov-branch --cov-report xml --cov-report term 2>&1
-        )
-        test_failure=$?
-
-        echo "$test_output"
-
-        cat << $EOF >> $GITHUB_STEP_SUMMARY
-        # Tests $([ $test_failure = 0 ] && echo '✅' || echo '❌')
-        \`\`\`
-        $test_output
-        \`\`\`
-        $EOF

.github/workflows/docker-release.yml

@@ -1,81 +0,0 @@
-name: Docker Release
-
-on:
-  release:
-    types: [ published, edited ]
-
-  workflow_dispatch:
-    inputs:
-      no_cache:
-        type: boolean
-        description: 'Build from scratch, without using cached layers'
-
-env:
-  IMAGE_NAME: auto-gpt
-  DEPLOY_IMAGE_NAME: ${{ secrets.DOCKER_USER }}/auto-gpt
-
-jobs:
-  build:
-    runs-on: ubuntu-latest
-    steps:
-    - name: Checkout repository
-      uses: actions/checkout@v3
-
-    - name: Log in to Docker hub
-      uses: docker/login-action@v2
-      with:
-        username: ${{ secrets.DOCKER_USER }}
-        password: ${{ secrets.DOCKER_PASSWORD }}
-
-    - name: Set up Docker Buildx
-      uses: docker/setup-buildx-action@v2
-
-      # slashes are not allowed in image tags, but can appear in git branch or tag names
-    - id: sanitize_tag
-      name: Sanitize image tag
-      run: echo tag=${raw_tag//\//-} >> $GITHUB_OUTPUT
-      env:
-        raw_tag: ${{ github.ref_name }}
-
-    - id: build
-      name: Build image
-      uses: docker/build-push-action@v3
-      with:
-        build-args: BUILD_TYPE=release
-        load: true    # save to docker images
-        # push: true  # TODO: uncomment when this issue is fixed: https://github.com/moby/buildkit/issues/1555
-        tags: >
-          ${{ env.IMAGE_NAME }},
-          ${{ env.DEPLOY_IMAGE_NAME }}:latest,
-          ${{ env.DEPLOY_IMAGE_NAME }}:${{ steps.sanitize_tag.outputs.tag }}
-
-        # cache layers in GitHub Actions cache to speed up builds
-        cache-from: ${{ !inputs.no_cache && 'type=gha' || '' }},scope=docker-release
-        cache-to: type=gha,scope=docker-release,mode=max
-
-    - name: Push image to Docker Hub
-      run: docker push --all-tags ${{ env.DEPLOY_IMAGE_NAME }}
-
-    - name: Generate build report
-      env:
-        event_name: ${{ github.event_name }}
-        event_ref: ${{ github.event.ref }}
-        event_ref_type: ${{ github.event.ref}}
-        inputs_no_cache: ${{ inputs.no_cache }}
-
-        prod_branch: stable
-        dev_branch: master
-        repository: ${{ github.repository }}
-        base_branch: ${{ github.ref_name != 'master' && github.ref_name != 'stable' && 'master' || 'stable' }}
-
-        ref_type: ${{ github.ref_type }}
-        current_ref: ${{ github.ref_name }}
-        commit_hash: ${{ github.sha }}
-        source_url: ${{ format('{0}/tree/{1}', github.event.repository.url, github.event.release && github.event.release.tag_name || github.sha) }}
-
-        github_context_json: ${{ toJSON(github) }}
-        job_env_json: ${{ toJSON(env) }}
-        vars_json: ${{ toJSON(vars) }}
-
-      run: .github/workflows/scripts/docker-release-summary.sh >> $GITHUB_STEP_SUMMARY
-      continue-on-error: true

.github/workflows/documentation-release.yml

@@ -1,37 +0,0 @@
-name: Docs
-
-on:
-  push:
-    branches: [ stable ]
-    paths:
-      - 'docs/**'
-      - 'mkdocs.yml'
-      - '.github/workflows/documentation.yml'
-
-  # Allows you to run this workflow manually from the Actions tab
-  workflow_dispatch:
-
-permissions:
-  contents: write
-
-jobs:
-  deploy:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v3
-
-      - name: Set up Python 3
-        uses: actions/setup-python@v4
-        with:
-          python-version: 3.x
-
-      - name: Set up workflow cache
-        uses: actions/cache@v3
-        with:
-          key: ${{ github.ref }}
-          path: .cache
-
-      - run: pip install mkdocs-material
-
-      - run: mkdocs gh-deploy --force

.github/workflows/platform-autgpt-deploy-prod.yml

@@ -0,0 +1,49 @@
+name: AutoGPT Platform - Deploy Prod Environment
+
+on:
+  release:
+    types: [published]
+
+permissions:
+  contents: 'read'
+  id-token: 'write'
+
+jobs:
+  migrate:
+    environment: production
+    name: Run migrations for AutoGPT Platform
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.11'
+
+      - name: Install Python dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install prisma
+
+      - name: Run Backend Migrations
+        working-directory: ./autogpt_platform/backend
+        run: |
+          python -m prisma migrate deploy
+        env:
+          DATABASE_URL: ${{ secrets.BACKEND_DATABASE_URL }}
+
+          
+  trigger:
+    needs: migrate
+    runs-on: ubuntu-latest
+    steps:
+      - name: Trigger deploy workflow
+        uses: peter-evans/repository-dispatch@v3
+        with:
+          token: ${{ secrets.DEPLOY_TOKEN }}
+          repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
+          event-type: build_deploy_prod
+          client-payload: '{"ref": "${{ github.ref }}", "sha": "${{ github.sha }}", "repository": "${{ github.repository }}"}'

.github/workflows/platform-autogpt-deploy-dev.yaml

@@ -0,0 +1,50 @@
+name: AutoGPT Platform - Deploy Dev Environment
+
+on:
+  push:
+    branches: [ dev ]
+    paths:
+      - 'autogpt_platform/**'
+
+permissions:
+  contents: 'read'
+  id-token: 'write'
+
+jobs:
+  migrate:
+    environment: develop
+    name: Run migrations for AutoGPT Platform
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: '3.11'
+
+      - name: Install Python dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install prisma
+
+      - name: Run Backend Migrations
+        working-directory: ./autogpt_platform/backend
+        run: |
+          python -m prisma migrate deploy
+        env:
+          DATABASE_URL: ${{ secrets.BACKEND_DATABASE_URL }}
+
+  trigger:
+    needs: migrate
+    runs-on: ubuntu-latest
+    steps:
+      - name: Trigger deploy workflow
+        uses: peter-evans/repository-dispatch@v3
+        with:
+          token: ${{ secrets.DEPLOY_TOKEN }}
+          repository: Significant-Gravitas/AutoGPT_cloud_infrastructure
+          event-type: build_deploy_dev
+          client-payload: '{"ref": "${{ github.ref }}", "sha": "${{ github.sha }}", "repository": "${{ github.repository }}"}'

.github/workflows/platform-backend-ci.yml

@@ -0,0 +1,162 @@
+name: AutoGPT Platform - Backend CI
+
+on:
+  push:
+    branches: [master, dev, ci-test*]
+    paths:
+      - ".github/workflows/platform-backend-ci.yml"
+      - "autogpt_platform/backend/**"
+      - "autogpt_platform/autogpt_libs/**"
+  pull_request:
+    branches: [master, dev, release-*]
+    paths:
+      - ".github/workflows/platform-backend-ci.yml"
+      - "autogpt_platform/backend/**"
+      - "autogpt_platform/autogpt_libs/**"
+  merge_group:
+
+concurrency:
+  group: ${{ format('backend-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
+  cancel-in-progress: ${{ startsWith(github.event_name, 'pull_request') }}
+
+defaults:
+  run:
+    shell: bash
+    working-directory: autogpt_platform/backend
+
+jobs:
+  test:
+    permissions:
+      contents: read
+    timeout-minutes: 30
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.10"]
+    runs-on: ubuntu-latest
+
+    services:
+      redis:
+        image: bitnami/redis:6.2
+        env:
+          REDIS_PASSWORD: testpassword
+        ports:
+          - 6379:6379
+      rabbitmq:
+        image: rabbitmq:3.12-management
+        ports:
+          - 5672:5672
+          - 15672:15672
+        env:
+          RABBITMQ_DEFAULT_USER: ${{ env.RABBITMQ_DEFAULT_USER }}
+          RABBITMQ_DEFAULT_PASS: ${{ env.RABBITMQ_DEFAULT_PASS }}
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          submodules: true
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Setup Supabase
+        uses: supabase/setup-cli@v1
+        with:
+          version: 1.178.1
+
+      - id: get_date
+        name: Get date
+        run: echo "date=$(date +'%Y-%m-%d')" >> $GITHUB_OUTPUT
+
+      - name: Set up Python dependency cache
+        uses: actions/cache@v4
+        with:
+          path: ~/.cache/pypoetry
+          key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
+
+      - name: Install Poetry (Unix)
+        run: |
+          curl -sSL https://install.python-poetry.org | python3 -
+
+          if [ "${{ runner.os }}" = "macOS" ]; then
+            PATH="$HOME/.local/bin:$PATH"
+            echo "$HOME/.local/bin" >> $GITHUB_PATH
+          fi
+
+      - name: Check poetry.lock
+        run: |
+          poetry lock
+
+          if ! git diff --quiet poetry.lock; then
+            echo "Error: poetry.lock not up to date."
+            echo
+            git diff poetry.lock
+            exit 1
+          fi
+
+      - name: Install Python dependencies
+        run: poetry install
+
+      - name: Generate Prisma Client
+        run: poetry run prisma generate
+
+      - id: supabase
+        name: Start Supabase
+        working-directory: .
+        run: |
+          supabase init
+          supabase start --exclude postgres-meta,realtime,storage-api,imgproxy,inbucket,studio,edge-runtime,logflare,vector,supavisor
+          supabase status -o env | sed 's/="/=/; s/"$//' >> $GITHUB_OUTPUT
+        # outputs:
+        # DB_URL, API_URL, GRAPHQL_URL, ANON_KEY, SERVICE_ROLE_KEY, JWT_SECRET
+
+      - name: Run Database Migrations
+        run: poetry run prisma migrate dev --name updates
+        env:
+          DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
+
+      - id: lint
+        name: Run Linter
+        run: poetry run lint
+
+      - name: Run pytest with coverage
+        run: |
+          if [[ "${{ runner.debug }}" == "1" ]]; then
+            poetry run pytest -s -vv -o log_cli=true -o log_cli_level=DEBUG test
+          else
+            poetry run pytest -s -vv test
+          fi
+        if: success() || (failure() && steps.lint.outcome == 'failure')
+        env:
+          LOG_LEVEL: ${{ runner.debug && 'DEBUG' || 'INFO' }}
+          DATABASE_URL: ${{ steps.supabase.outputs.DB_URL }}
+          SUPABASE_URL: ${{ steps.supabase.outputs.API_URL }}
+          SUPABASE_SERVICE_ROLE_KEY: ${{ steps.supabase.outputs.SERVICE_ROLE_KEY }}
+          SUPABASE_JWT_SECRET: ${{ steps.supabase.outputs.JWT_SECRET }}
+          REDIS_HOST: 'localhost'
+          REDIS_PORT: '6379'
+          REDIS_PASSWORD: 'testpassword'
+
+    env:
+      CI: true
+      PLAIN_OUTPUT: True
+      RUN_ENV: local
+      PORT: 8080
+      OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+      # We know these are here, don't report this as a security vulnerability
+      # This is used as the default credential for the entire system's RabbitMQ instance
+      # If you want to replace this, you can do so by making our entire system generate
+      # new credentials for each local user and update the environment variables in
+      # the backend service, docker composes, and examples
+      RABBITMQ_DEFAULT_USER: 'rabbitmq_user_default'
+      RABBITMQ_DEFAULT_PASS: 'k0VMxyIJF9S35f3x2uaw5IWAl6Y536O7'
+
+      # - name: Upload coverage reports to Codecov
+      #   uses: codecov/codecov-action@v4
+      #   with:
+      #     token: ${{ secrets.CODECOV_TOKEN }}
+      #     flags: backend,${{ runner.os }}

.github/workflows/platform-frontend-ci.yml

@@ -0,0 +1,121 @@
+name: AutoGPT Platform - Frontend CI
+
+on:
+  push:
+    branches: [master, dev]
+    paths:
+      - ".github/workflows/platform-frontend-ci.yml"
+      - "autogpt_platform/frontend/**"
+  pull_request:
+    paths:
+      - ".github/workflows/platform-frontend-ci.yml"
+      - "autogpt_platform/frontend/**"
+  merge_group:
+
+defaults:
+  run:
+    shell: bash
+    working-directory: autogpt_platform/frontend
+
+jobs:
+  lint:
+    runs-on: ubuntu-latest
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: "21"
+
+      - name: Install dependencies
+        run: |
+          yarn install --frozen-lockfile
+
+      - name: Run lint
+        run: |
+          yarn lint
+
+  type-check:
+    runs-on: ubuntu-latest
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: "21"
+
+      - name: Install dependencies
+        run: |
+          yarn install --frozen-lockfile
+
+      - name: Run tsc check
+        run: |
+          yarn type-check
+
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        browser: [chromium, webkit]
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          submodules: recursive
+
+      - name: Set up Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: "21"
+
+      - name: Free Disk Space (Ubuntu)
+        uses: jlumbroso/free-disk-space@main
+        with:
+          large-packages: false # slow
+          docker-images: false # limited benefit
+
+      - name: Copy default supabase .env
+        run: |
+          cp ../.env.example ../.env
+
+      - name: Copy backend .env
+        run: |
+          cp ../backend/.env.example ../backend/.env
+
+      - name: Run docker compose
+        run: |
+          docker compose -f ../docker-compose.yml up -d
+
+      - name: Install dependencies
+        run: |
+          yarn install --frozen-lockfile
+
+      - name: Setup Builder .env
+        run: |
+          cp .env.example .env
+
+      - name: Install Browser '${{ matrix.browser }}'
+        run: yarn playwright install --with-deps ${{ matrix.browser }}
+
+      - name: Run tests
+        timeout-minutes: 20
+        run: |
+          yarn test --project=${{ matrix.browser }}
+
+      - name: Print Final Docker Compose logs
+        if: always()
+        run: |
+          docker compose -f ../docker-compose.yml logs
+
+      - uses: actions/upload-artifact@v4
+        if: ${{ !cancelled() }}
+        with:
+          name: playwright-report-${{ matrix.browser }}
+          path: playwright-report/
+          retention-days: 30

.github/workflows/repo-close-stale-issues.yml

@@ -0,0 +1,34 @@
+name: Repo - Close stale issues
+on:
+  schedule:
+    - cron: '30 1 * * *'
+  workflow_dispatch:
+
+permissions:
+  issues: write
+
+jobs:
+  stale:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/stale@v9
+        with:
+          # operations-per-run: 5000
+          stale-issue-message: >
+            This issue has automatically been marked as _stale_ because it has not had
+            any activity in the last 50 days. You can _unstale_ it by commenting or
+            removing the label. Otherwise, this issue will be closed in 10 days.
+          stale-pr-message: >
+            This pull request has automatically been marked as _stale_ because it has
+            not had any activity in the last 50 days. You can _unstale_ it by commenting
+            or removing the label.
+          close-issue-message: >
+            This issue was closed automatically because it has been stale for 10 days
+            with no activity.
+          days-before-stale: 100
+          days-before-close: 10
+          # Do not touch meta issues:
+          exempt-issue-labels: meta,fridge,project management
+          # Do not affect pull requests:
+          days-before-pr-stale: -1
+          days-before-pr-close: -1

.github/workflows/repo-pr-enforce-base-branch.yml

@@ -0,0 +1,21 @@
+name: Repo - Enforce dev as base branch
+on:
+  pull_request_target:
+    branches: [ master ]
+    types: [ opened ]
+
+jobs:
+  check_pr_target:
+    runs-on: ubuntu-latest
+    permissions:
+      pull-requests: write
+    steps:
+      - name: Check if PR is from dev or hotfix
+        if: ${{ !(startsWith(github.event.pull_request.head.ref, 'hotfix/') || github.event.pull_request.head.ref == 'dev') }}
+        run: |
+          gh pr comment ${{ github.event.number }} --repo "$REPO" \
+            --body $'This PR targets the `master` branch but does not come from `dev` or a `hotfix/*` branch.\n\nAutomatically setting the base branch to `dev`.'
+          gh pr edit ${{ github.event.number }} --base dev --repo "$REPO"
+        env:
+          GITHUB_TOKEN: ${{ github.token }}
+          REPO: ${{ github.repository }}

.github/workflows/repo-pr-label.yml

@@ -1,9 +1,12 @@
-name: "Pull Request auto-label"
+name: Repo - Pull Request auto-label
 
 on:
   # So that PRs touching the same files as the push are updated
   push:
-    branches: [ master ]
+    branches: [ master, dev, release-* ]
+    paths-ignore:
+      - 'classic/forge/tests/vcr_cassettes'
+      - 'classic/benchmark/reports/**'
   # So that the `dirtyLabel` is removed if conflicts are resolve
   # We recommend `pull_request_target` so that github secrets are available.
   # In `pull_request` we wouldn't be able to change labels of fork PRs
@@ -45,11 +48,19 @@ jobs:
           s_label: 'size/s'
           s_max_size: 10
           m_label: 'size/m'
-          m_max_size: 50
+          m_max_size: 100
           l_label: 'size/l'
-          l_max_size: 200
+          l_max_size: 500
           xl_label: 'size/xl'
-          message_if_xl: >
-            This PR exceeds the recommended size of 200 lines.
-            Please make sure you are NOT addressing multiple issues with one PR.
-            Note this PR might be rejected due to its size  
+          message_if_xl:
+
+  scope:
+    if: ${{ github.event_name == 'pull_request_target' }}
+    permissions:
+      contents: read
+      pull-requests: write
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/labeler@v5
+        with:
+          sync-labels: true

.github/workflows/repo-stats.yml

@@ -0,0 +1,20 @@
+name: Repo - Github Stats
+
+on:
+  schedule:
+    # Run this once per day, towards the end of the day for keeping the most
+    # recent data point most meaningful (hours are interpreted in UTC).
+    - cron: "0 23 * * *"
+  workflow_dispatch: # Allow for running this manually.
+
+jobs:
+  j1:
+    name: github-repo-stats
+    runs-on: ubuntu-latest
+    steps:
+      - name: run-ghrs
+        # Use latest release.
+        uses: jgehrcke/github-repo-stats@HEAD
+        with:
+          ghtoken: ${{ secrets.ghrs_github_api_token }}
+

.github/workflows/repo-workflow-checker.yml

@@ -0,0 +1,32 @@
+name: Repo - PR Status Checker
+on:
+  pull_request:
+    types: [opened, synchronize, reopened]
+  merge_group:
+
+jobs:
+  status-check:
+    name: Check PR Status
+    runs-on: ubuntu-latest
+    steps:
+      # - name: Wait some time for all actions to start
+      #   run: sleep 30
+      - uses: actions/checkout@v4
+        # with:
+          # fetch-depth: 0
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.10"
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install requests
+      - name: Check PR Status
+        run: |
+          echo "Current directory before running Python script:"
+          pwd
+          echo "Attempting to run Python script:"
+          python .github/workflows/scripts/check_actions_status.py
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/scripts/check_actions_status.py

@@ -0,0 +1,116 @@
+import json
+import os
+import requests
+import sys
+import time
+from typing import Dict, List, Tuple
+
+CHECK_INTERVAL = 30
+
+
+def get_environment_variables() -> Tuple[str, str, str, str, str]:
+    """Retrieve and return necessary environment variables."""
+    try:
+        with open(os.environ["GITHUB_EVENT_PATH"]) as f:
+            event = json.load(f)
+
+        # Handle both PR and merge group events
+        if "pull_request" in event:
+            sha = event["pull_request"]["head"]["sha"]
+        else:
+            sha = os.environ["GITHUB_SHA"]
+
+        return (
+            os.environ["GITHUB_API_URL"],
+            os.environ["GITHUB_REPOSITORY"],
+            sha,
+            os.environ["GITHUB_TOKEN"],
+            os.environ["GITHUB_RUN_ID"],
+        )
+    except KeyError as e:
+        print(f"Error: Missing required environment variable or event data: {e}")
+        sys.exit(1)
+
+
+def make_api_request(url: str, headers: Dict[str, str]) -> Dict:
+    """Make an API request and return the JSON response."""
+    try:
+        print("Making API request to:", url)
+        response = requests.get(url, headers=headers, timeout=10)
+        response.raise_for_status()
+        return response.json()
+    except requests.RequestException as e:
+        print(f"Error: API request failed. {e}")
+        sys.exit(1)
+
+
+def process_check_runs(check_runs: List[Dict]) -> Tuple[bool, bool]:
+    """Process check runs and return their status."""
+    runs_in_progress = False
+    all_others_passed = True
+
+    for run in check_runs:
+        if str(run["name"]) != "Check PR Status":
+            status = run["status"]
+            conclusion = run["conclusion"]
+
+            if status == "completed":
+                if conclusion not in ["success", "skipped", "neutral"]:
+                    all_others_passed = False
+                    print(
+                        f"Check run {run['name']} (ID: {run['id']}) has conclusion: {conclusion}"
+                    )
+            else:
+                runs_in_progress = True
+                print(f"Check run {run['name']} (ID: {run['id']}) is still {status}.")
+                all_others_passed = False
+        else:
+            print(
+                f"Skipping check run {run['name']} (ID: {run['id']}) as it is the current run."
+            )
+
+    return runs_in_progress, all_others_passed
+
+
+def main():
+    api_url, repo, sha, github_token, current_run_id = get_environment_variables()
+
+    endpoint = f"{api_url}/repos/{repo}/commits/{sha}/check-runs"
+    headers = {
+        "Accept": "application/vnd.github.v3+json",
+    }
+    if github_token:
+        headers["Authorization"] = f"token {github_token}"
+
+    print(f"Current run ID: {current_run_id}")
+
+    while True:
+        data = make_api_request(endpoint, headers)
+
+        check_runs = data["check_runs"]
+
+        print("Processing check runs...")
+
+        print(check_runs)
+
+        runs_in_progress, all_others_passed = process_check_runs(check_runs)
+
+        if not runs_in_progress:
+            break
+
+        print(
+            "Some check runs are still in progress. "
+            f"Waiting {CHECK_INTERVAL} seconds before checking again..."
+        )
+        time.sleep(CHECK_INTERVAL)
+
+    if all_others_passed:
+        print("All other completed check runs have passed. This check passes.")
+        sys.exit(0)
+    else:
+        print("Some check runs have failed or have not completed. This check fails.")
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()

.github/workflows/sponsors_readme.yml

@@ -1,28 +0,0 @@
-name: Generate Sponsors README
-
-on:
-  workflow_dispatch:
-  schedule:
-    - cron: '0 */12 * * *'
-
-jobs:
-  deploy:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout 🛎️
-        uses: actions/checkout@v3
-
-      - name: Generate Sponsors 💖
-        uses: JamesIves/github-sponsors-readme-action@v1
-        with:
-          token: ${{ secrets.README_UPDATER_PAT }}
-          file: 'README.md'
-          minimum: 2500
-          maximum: 99999
-
-      - name: Deploy to GitHub Pages 🚀
-        uses: JamesIves/github-pages-deploy-action@v4
-        with:
-          branch: master
-          folder: '.'
-          token: ${{ secrets.README_UPDATER_PAT }}

.gitignore

@@ -1,26 +1,21 @@
 ## Original ignores
-autogpt/keys.py
-autogpt/*json
-autogpt/node_modules/
-autogpt/__pycache__/keys.cpython-310.pyc
-autogpt/auto_gpt_workspace
-package-lock.json
-*.pyc
+.github_access_token
+classic/original_autogpt/keys.py
+classic/original_autogpt/*.json
 auto_gpt_workspace/*
 *.mpeg
 .env
 azure.yaml
-ai_settings.yaml
-last_run_ai_settings.yaml
 .vscode
 .idea/*
 auto-gpt.json
 log.txt
 log-ingestion.txt
-logs
+/logs
 *.log
 *.mp3
 mem.sqlite3
+venvAutoGPT
 
 # Byte-compiled / optimized / DLL files
 __pycache__/
@@ -32,14 +27,11 @@ __pycache__/
 
 # Distribution / packaging
 .Python
-build/
 develop-eggs/
 dist/
-plugins/
 downloads/
 eggs/
 .eggs/
-lib/
 lib64/
 parts/
 sdist/
@@ -162,4 +154,25 @@ vicuna-*
 openai/
 
 # news
-CURRENT_BULLETIN.md
+CURRENT_BULLETIN.md
+
+# AgBenchmark
+classic/benchmark/agbenchmark/reports/
+
+# Nodejs
+package-lock.json
+
+
+# Allow for locally private items
+# private
+pri* 
+# ignore
+ig*
+.github_access_token
+LICENSE.rtf
+autogpt_platform/backend/settings.py
+/.auth
+/autogpt_platform/frontend/.auth
+
+*.ign.*
+.test-contents

.gitmodules

@@ -0,0 +1,3 @@
+[submodule "classic/forge/tests/vcr_cassettes"]
+	path = classic/forge/tests/vcr_cassettes
+	url = https://github.com/Significant-Gravitas/Auto-GPT-test-cassettes

.isort.cfg

@@ -1,10 +0,0 @@
-[settings]
-profile = black
-multi_line_output = 3
-include_trailing_comma = true
-force_grid_wrap = 0
-use_parentheses = true
-ensure_newline_before_comments = true
-line_length = 88
-sections = FUTURE,STDLIB,THIRDPARTY,FIRSTPARTY,LOCALFOLDER
-skip = .tox,__pycache__,*.pyc,venv*/*,reports,venv,env,node_modules,.env,.venv,dist

.pr_agent.toml

@@ -0,0 +1,6 @@
+[pr_reviewer]
+num_code_suggestions=0
+
+[pr_code_suggestions]
+commitable_code_suggestions=false
+num_code_suggestions=0

.pre-commit-config.yaml

@@ -3,30 +3,276 @@ repos:
     rev: v4.4.0
     hooks:
       - id: check-added-large-files
-        args: ['--maxkb=500']
-      - id: check-byte-order-marker
+        args: ["--maxkb=500"]
+      - id: fix-byte-order-marker
       - id: check-case-conflict
       - id: check-merge-conflict
       - id: check-symlinks
       - id: debug-statements
 
-  - repo: https://github.com/pycqa/isort
-    rev: 5.12.0
+  - repo: https://github.com/Yelp/detect-secrets
+    rev: v1.5.0
+    hooks:
+      - id: detect-secrets
+        name: Detect secrets
+        description: Detects high entropy strings that are likely to be passwords.
+        files: ^autogpt_platform/
+        stages: [push]
+
+  - repo: local
+    # For proper type checking, all dependencies need to be up-to-date.
+    # It's also a good idea to check that poetry.lock is consistent with pyproject.toml.
+    hooks:
+      - id: poetry-install
+        name: Check & Install dependencies - AutoGPT Platform - Backend
+        alias: poetry-install-platform-backend
+        entry: poetry -C autogpt_platform/backend install
+        # include autogpt_libs source (since it's a path dependency)
+        files: ^autogpt_platform/(backend|autogpt_libs)/poetry\.lock$
+        types: [file]
+        language: system
+        pass_filenames: false
+
+      - id: poetry-install
+        name: Check & Install dependencies - AutoGPT Platform - Libs
+        alias: poetry-install-platform-libs
+        entry: poetry -C autogpt_platform/autogpt_libs install
+        files: ^autogpt_platform/autogpt_libs/poetry\.lock$
+        types: [file]
+        language: system
+        pass_filenames: false
+
+      - id: poetry-install
+        name: Check & Install dependencies - Classic - AutoGPT
+        alias: poetry-install-classic-autogpt
+        entry: poetry -C classic/original_autogpt install
+        # include forge source (since it's a path dependency)
+        files: ^classic/(original_autogpt|forge)/poetry\.lock$
+        types: [file]
+        language: system
+        pass_filenames: false
+
+      - id: poetry-install
+        name: Check & Install dependencies - Classic - Forge
+        alias: poetry-install-classic-forge
+        entry: poetry -C classic/forge install
+        files: ^classic/forge/poetry\.lock$
+        types: [file]
+        language: system
+        pass_filenames: false
+
+      - id: poetry-install
+        name: Check & Install dependencies - Classic - Benchmark
+        alias: poetry-install-classic-benchmark
+        entry: poetry -C classic/benchmark install
+        files: ^classic/benchmark/poetry\.lock$
+        types: [file]
+        language: system
+        pass_filenames: false
+
+  - repo: local
+    # For proper type checking, Prisma client must be up-to-date.
+    hooks:
+      - id: prisma-generate
+        name: Prisma Generate - AutoGPT Platform - Backend
+        alias: prisma-generate-platform-backend
+        entry: bash -c 'cd autogpt_platform/backend && poetry run prisma generate'
+        # include everything that triggers poetry install + the prisma schema
+        files: ^autogpt_platform/((backend|autogpt_libs)/poetry\.lock|backend/schema.prisma)$
+        types: [file]
+        language: system
+        pass_filenames: false
+
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.7.2
+    hooks:
+      - id: ruff
+        name: Lint (Ruff) - AutoGPT Platform - Backend
+        alias: ruff-lint-platform-backend
+        files: ^autogpt_platform/backend/
+        args: [--fix]
+
+      - id: ruff
+        name: Lint (Ruff) - AutoGPT Platform - Libs
+        alias: ruff-lint-platform-libs
+        files: ^autogpt_platform/autogpt_libs/
+        args: [--fix]
+
+      - id: ruff-format
+        name: Format (Ruff) - AutoGPT Platform - Libs
+        alias: ruff-lint-platform-libs
+        files: ^autogpt_platform/autogpt_libs/
+
+  - repo: local
+    # isort needs the context of which packages are installed to function, so we
+    # can't use a vendored isort pre-commit hook (which runs in its own isolated venv).
     hooks:
       - id: isort
-        language_version: python3.10
+        name: Lint (isort) - AutoGPT Platform - Backend
+        alias: isort-platform-backend
+        entry: poetry -P autogpt_platform/backend run isort -p backend
+        files: ^autogpt_platform/backend/
+        types: [file, python]
+        language: system
+
+      - id: isort
+        name: Lint (isort) - Classic - AutoGPT
+        alias: isort-classic-autogpt
+        entry: poetry -P classic/original_autogpt run isort -p autogpt
+        files: ^classic/original_autogpt/
+        types: [file, python]
+        language: system
+
+      - id: isort
+        name: Lint (isort) - Classic - Forge
+        alias: isort-classic-forge
+        entry: poetry -P classic/forge run isort -p forge
+        files: ^classic/forge/
+        types: [file, python]
+        language: system
+
+      - id: isort
+        name: Lint (isort) - Classic - Benchmark
+        alias: isort-classic-benchmark
+        entry: poetry -P classic/benchmark run isort -p agbenchmark
+        files: ^classic/benchmark/
+        types: [file, python]
+        language: system
 
   - repo: https://github.com/psf/black
-    rev: 23.3.0
+    rev: 23.12.1
+    # Black has sensible defaults, doesn't need package context, and ignores
+    # everything in .gitignore, so it works fine without any config or arguments.
     hooks:
       - id: black
-        language_version: python3.10
+        name: Format (Black)
+
+  - repo: https://github.com/PyCQA/flake8
+    rev: 7.0.0
+    # To have flake8 load the config of the individual subprojects, we have to call
+    # them separately.
+    hooks:
+      - id: flake8
+        name: Lint (Flake8) - Classic - AutoGPT
+        alias: flake8-classic-autogpt
+        files: ^classic/original_autogpt/(autogpt|scripts|tests)/
+        args: [--config=classic/original_autogpt/.flake8]
+
+      - id: flake8
+        name: Lint (Flake8) - Classic - Forge
+        alias: flake8-classic-forge
+        files: ^classic/forge/(forge|tests)/
+        args: [--config=classic/forge/.flake8]
+
+      - id: flake8
+        name: Lint (Flake8) - Classic - Benchmark
+        alias: flake8-classic-benchmark
+        files: ^classic/benchmark/(agbenchmark|tests)/((?!reports).)*[/.]
+        args: [--config=classic/benchmark/.flake8]
 
   - repo: local
     hooks:
-      - id: pytest-check
-        name: pytest-check
-        entry: pytest --cov=autogpt --without-integration --without-slow-integration
+      - id: prettier
+        name: Format (Prettier) - AutoGPT Platform - Frontend
+        alias: format-platform-frontend
+        entry: bash -c 'cd autogpt_platform/frontend && npx prettier --write $(echo "$@" | sed "s|autogpt_platform/frontend/||g")' --
+        files: ^autogpt_platform/frontend/
+        types: [file]
+        language: system
+
+  - repo: local
+    # To have watertight type checking, we check *all* the files in an affected
+    # project. To trigger on poetry.lock we also reset the file `types` filter.
+    hooks:
+      - id: pyright
+        name: Typecheck - AutoGPT Platform - Backend
+        alias: pyright-platform-backend
+        entry: poetry -C autogpt_platform/backend run pyright
+        # include forge source (since it's a path dependency) but exclude *_test.py files:
+        files: ^autogpt_platform/(backend/((backend|test)/|(\w+\.py|poetry\.lock)$)|autogpt_libs/(autogpt_libs/.*(?<!_test)\.py|poetry\.lock)$)
+        types: [file]
+        language: system
+        pass_filenames: false
+
+      - id: pyright
+        name: Typecheck - AutoGPT Platform - Libs
+        alias: pyright-platform-libs
+        entry: poetry -C autogpt_platform/autogpt_libs run pyright
+        files: ^autogpt_platform/autogpt_libs/(autogpt_libs/|poetry\.lock$)
+        types: [file]
+        language: system
+        pass_filenames: false
+
+      - id: pyright
+        name: Typecheck - Classic - AutoGPT
+        alias: pyright-classic-autogpt
+        entry: poetry -C classic/original_autogpt run pyright
+        # include forge source (since it's a path dependency) but exclude *_test.py files:
+        files: ^(classic/original_autogpt/((autogpt|scripts|tests)/|poetry\.lock$)|classic/forge/(forge/.*(?<!_test)\.py|poetry\.lock)$)
+        types: [file]
+        language: system
+        pass_filenames: false
+
+      - id: pyright
+        name: Typecheck - Classic - Forge
+        alias: pyright-classic-forge
+        entry: poetry -C classic/forge run pyright
+        files: ^classic/forge/(forge/|poetry\.lock$)
+        types: [file]
+        language: system
+        pass_filenames: false
+
+      - id: pyright
+        name: Typecheck - Classic - Benchmark
+        alias: pyright-classic-benchmark
+        entry: poetry -C classic/benchmark run pyright
+        files: ^classic/benchmark/(agbenchmark/|tests/|poetry\.lock$)
+        types: [file]
+        language: system
+        pass_filenames: false
+
+  - repo: local
+    hooks:
+      - id: tsc
+        name: Typecheck - AutoGPT Platform - Frontend
+        entry: bash -c 'cd autogpt_platform/frontend && npm run type-check'
+        files: ^autogpt_platform/frontend/
+        types: [file]
+        language: system
+        pass_filenames: false
+
+  - repo: local
+    hooks:
+      - id: pytest
+        name: Run tests - AutoGPT Platform - Backend
+        alias: pytest-platform-backend
+        entry: bash -c 'cd autogpt_platform/backend && poetry run pytest'
+        # include autogpt_libs source (since it's a path dependency) but exclude *_test.py files:
+        files: ^autogpt_platform/(backend/((backend|test)/|poetry\.lock$)|autogpt_libs/(autogpt_libs/.*(?<!_test)\.py|poetry\.lock)$)
+        language: system
+        pass_filenames: false
+
+      - id: pytest
+        name: Run tests - Classic - AutoGPT (excl. slow tests)
+        alias: pytest-classic-autogpt
+        entry: bash -c 'cd classic/original_autogpt && poetry run pytest --cov=autogpt -m "not slow" tests/unit tests/integration'
+        # include forge source (since it's a path dependency) but exclude *_test.py files:
+        files: ^(classic/original_autogpt/((autogpt|tests)/|poetry\.lock$)|classic/forge/(forge/.*(?<!_test)\.py|poetry\.lock)$)
+        language: system
+        pass_filenames: false
+
+      - id: pytest
+        name: Run tests - Classic - Forge (excl. slow tests)
+        alias: pytest-classic-forge
+        entry: bash -c 'cd classic/forge && poetry run pytest --cov=forge -m "not slow"'
+        files: ^classic/forge/(forge/|tests/|poetry\.lock$)
+        language: system
+        pass_filenames: false
+
+      - id: pytest
+        name: Run tests - Classic - Benchmark
+        alias: pytest-classic-benchmark
+        entry: bash -c 'cd classic/benchmark && poetry run pytest --cov=benchmark'
+        files: ^classic/benchmark/(agbenchmark/|tests/|poetry\.lock$)
         language: system
         pass_filenames: false
-        always_run: true

.vscode/all-projects.code-workspace

@@ -0,0 +1,62 @@
+{
+  "folders": [
+    {
+      "name": "frontend",
+      "path": "../autogpt_platform/frontend"
+    },
+    {
+      "name": "backend",
+      "path": "../autogpt_platform/backend"
+    },
+    {
+      "name": "market",
+      "path": "../autogpt_platform/market"
+    },
+    {
+      "name": "lib",
+      "path": "../autogpt_platform/autogpt_libs"
+    },
+    {
+      "name": "infra",
+      "path": "../autogpt_platform/infra"
+    },
+    {
+      "name": "docs",
+      "path": "../docs"
+    },
+
+    {
+      "name": "classic - autogpt",
+      "path": "../classic/original_autogpt"
+    },
+    {
+      "name": "classic - benchmark",
+      "path": "../classic/benchmark"
+    },
+    {
+      "name": "classic - forge",
+      "path": "../classic/forge"
+    },
+    {
+      "name": "classic - frontend",
+      "path": "../classic/frontend"
+    },
+    {
+      "name": "[root]",
+      "path": ".."
+    }
+  ],
+  "settings": {
+    "python.analysis.typeCheckingMode": "basic"
+  },
+  "extensions": {
+    "recommendations": [
+      "charliermarsh.ruff",
+      "dart-code.flutter",
+      "ms-python.black-formatter",
+      "ms-python.vscode-pylance",
+      "prisma.prisma",
+      "qwtel.sqlite-viewer"
+    ]
+  }
+}

.vscode/launch.json

@@ -0,0 +1,67 @@
+{
+  "version": "0.2.0",
+  "configurations": [
+    {
+      "name": "Frontend: Server Side",
+      "type": "node-terminal",
+      "request": "launch",
+      "cwd": "${workspaceFolder}/autogpt_platform/frontend",
+      "command": "yarn dev"
+    },
+    {
+      "name": "Frontend: Client Side",
+      "type": "msedge",
+      "request": "launch",
+      "url": "http://localhost:3000"
+    },
+    {
+      "name": "Frontend: Full Stack",
+      "type": "node-terminal",
+
+      "request": "launch",
+      "command": "yarn dev",
+      "cwd": "${workspaceFolder}/autogpt_platform/frontend",
+      "serverReadyAction": {
+        "pattern": "- Local:.+(https?://.+)",
+        "uriFormat": "%s",
+        "action": "debugWithEdge"
+      }
+    },
+    {
+      "name": "Backend",
+      "type": "debugpy",
+      "request": "launch",
+      "module": "backend.app",
+      // "env": {
+      //   "ENV": "dev"
+      // },
+      "envFile": "${workspaceFolder}/backend/.env",
+      "justMyCode": false,
+      "cwd": "${workspaceFolder}/autogpt_platform/backend"
+    },
+    {
+      "name": "Marketplace",
+      "type": "debugpy",
+      "request": "launch",
+      "module": "autogpt_platform.market.main",
+      "env": {
+        "ENV": "dev"
+      },
+      "envFile": "${workspaceFolder}/market/.env",
+      "justMyCode": false,
+      "cwd": "${workspaceFolder}/market"
+    }
+  ],
+  "compounds": [
+    {
+      "name": "Everything",
+      "configurations": ["Backend", "Frontend: Full Stack"],
+      // "preLaunchTask": "${defaultBuildTask}",
+      "stopAll": true,
+      "presentation": {
+        "hidden": false,
+        "order": 0
+      }
+    }
+  ]
+}

BULLETIN.md

@@ -1,9 +0,0 @@
-Welcome to Auto-GPT! We'll keep you informed of the latest news and features by printing messages here.
-If you don't wish to see this message, you can run Auto-GPT with the --skip-news flag
-
-# INCLUDED COMMAND 'send_tweet' IS DEPRICATED, AND WILL BE REMOVED IN THE NEXT STABLE RELEASE
-Base Twitter functionality (and more) is now covered by plugins: https://github.com/Significant-Gravitas/Auto-GPT-Plugins
-
-## Changes to Docker configuration
-The workdir has been changed from /home/appuser to /app. Be sure to update any volume mounts accordingly.
-

CITATION.cff

@@ -0,0 +1,21 @@
+# This CITATION.cff file was generated with cffinit.
+# Visit https://bit.ly/cffinit to generate yours today!
+
+cff-version: 1.2.0
+title: AutoGPT
+message: >-
+  If you use this software, please cite it using the
+  metadata from this file.
+type: software
+authors:
+  - name: Significant Gravitas
+    website: 'https://agpt.co'
+repository-code: 'https://github.com/Significant-Gravitas/AutoGPT'
+url: 'https://agpt.co'
+abstract: >-
+  A collection of tools and experimental open-source attempts to make GPT-4 fully
+  autonomous.
+keywords:
+  - AI
+  - Agent
+license: MIT

CODE_OF_CONDUCT.md

@@ -1,12 +1,12 @@
-# Code of Conduct for Auto-GPT
+# Code of Conduct for AutoGPT
 
 ## 1. Purpose
 
-The purpose of this Code of Conduct is to provide guidelines for contributors to the auto-gpt project on GitHub. We aim to create a positive and inclusive environment where all participants can contribute and collaborate effectively. By participating in this project, you agree to abide by this Code of Conduct.
+The purpose of this Code of Conduct is to provide guidelines for contributors to the AutoGPT projects on GitHub. We aim to create a positive and inclusive environment where all participants can contribute and collaborate effectively. By participating in this project, you agree to abide by this Code of Conduct.
 
 ## 2. Scope
 
-This Code of Conduct applies to all contributors, maintainers, and users of the auto-gpt project. It extends to all project spaces, including but not limited to issues, pull requests, code reviews, comments, and other forms of communication within the project.
+This Code of Conduct applies to all contributors, maintainers, and users of the AutoGPT project. It extends to all project spaces, including but not limited to issues, pull requests, code reviews, comments, and other forms of communication within the project.
 
 ## 3. Our Standards
 
@@ -36,4 +36,5 @@ This Code of Conduct is adapted from the [Contributor Covenant](https://www.cont
 
 ## 6. Contact
 
-If you have any questions or concerns, please contact the project maintainers.
+If you have any questions or concerns, please contact the project maintainers on Discord:
+https://discord.gg/autogpt

CONTRIBUTING.md

@@ -1,148 +1,41 @@
-# Contributing to Auto-GPT
+# AutoGPT Contribution Guide
+If you are reading this, you are probably looking for the full **[contribution guide]**,
+which is part of our [wiki].
 
-First of all, thank you for considering contributing to our project! We appreciate your time and effort, and we value any contribution, whether it's reporting a bug, suggesting a new feature, or submitting a pull request.
+Also check out our [🚀 Roadmap][roadmap] for information about our priorities and associated tasks.
+<!-- You can find our immediate priorities and their progress on our public [kanban board]. -->
 
-This document provides guidelines and best practices to help you contribute effectively.
+[contribution guide]: https://github.com/Significant-Gravitas/AutoGPT/wiki/Contributing
+[wiki]: https://github.com/Significant-Gravitas/AutoGPT/wiki
+[roadmap]: https://github.com/Significant-Gravitas/AutoGPT/discussions/6971
+[kanban board]: https://github.com/orgs/Significant-Gravitas/projects/1
 
-## Code of Conduct
+## Contributing to the AutoGPT Platform Folder
+All contributions to [the autogpt_platform folder](https://github.com/Significant-Gravitas/AutoGPT/blob/master/autogpt_platform) will be under our [Contribution License Agreement](https://github.com/Significant-Gravitas/AutoGPT/blob/master/autogpt_platform/Contributor%20License%20Agreement%20(CLA).md). By making a pull request contributing to this folder, you agree to the terms of our CLA for your contribution. All contributions to other folders will be under the MIT license.
 
-By participating in this project, you agree to abide by our [Code of Conduct]. Please read it to understand the expectations we have for everyone who contributes to this project.
+## In short
+1. Avoid duplicate work, issues, PRs etc.
+2. We encourage you to collaborate with fellow community members on some of our bigger
+   [todo's][roadmap]!
+   * We highly recommend to post your idea and discuss it in the [dev channel].
+3. Create a draft PR when starting work on bigger changes.
+4. Adhere to the [Code Guidelines]
+5. Clearly explain your changes when submitting a PR.
+6. Don't submit broken code: test/validate your changes.
+7. Avoid making unnecessary changes, especially if they're purely based on your personal
+   preferences. Doing so is the maintainers' job. ;-)
+8. Please also consider contributing something other than code; see the
+   [contribution guide] for options.
 
-[Code of Conduct]: https://significant-gravitas.github.io/Auto-GPT/code-of-conduct.md
+[dev channel]: https://discord.com/channels/1092243196446249134/1095817829405704305
+[code guidelines]: https://github.com/Significant-Gravitas/AutoGPT/wiki/Contributing#code-guidelines
 
-## 📢 A Quick Word
-Right now we will not be accepting any Contributions that add non-essential commands to Auto-GPT.
+If you wish to involve with the project (beyond just contributing PRs), please read the
+wiki page about [Catalyzing](https://github.com/Significant-Gravitas/AutoGPT/wiki/Catalyzing).
 
-However, you absolutely can still add these commands to Auto-GPT in the form of plugins.
-Please check out this [template](https://github.com/Significant-Gravitas/Auto-GPT-Plugin-Template).
+In fact, why not just look through the whole wiki (it's only a few pages) and
+hop on our Discord. See you there! :-)
 
-## Getting Started
-
-1. Fork the repository and clone your fork.
-2. Create a new branch for your changes (use a descriptive name, such as `fix-bug-123` or `add-new-feature`).
-3. Make your changes in the new branch.
-4. Test your changes thoroughly.
-5. Commit and push your changes to your fork.
-6. Create a pull request following the guidelines in the [Submitting Pull Requests](#submitting-pull-requests) section.
-
-## How to Contribute
-
-### Reporting Bugs
-
-If you find a bug in the project, please create an issue on GitHub with the following information:
-
-- A clear, descriptive title for the issue.
-- A description of the problem, including steps to reproduce the issue.
-- Any relevant logs, screenshots, or other supporting information.
-
-### Suggesting Enhancements
-
-If you have an idea for a new feature or improvement, please create an issue on GitHub with the following information:
-
-- A clear, descriptive title for the issue.
-- A detailed description of the proposed enhancement, including any benefits and potential drawbacks.
-- Any relevant examples, mockups, or supporting information.
-
-### Submitting Pull Requests
-
-When submitting a pull request, please ensure that your changes meet the following criteria:
-
-- Your pull request should be atomic and focus on a single change.
-- Your pull request should include tests for your change. We automatically enforce this with [CodeCov](https://docs.codecov.com/docs/commit-status)
-- You should have thoroughly tested your changes with multiple different prompts.
-- You should have considered potential risks and mitigations for your changes.
-- You should have documented your changes clearly and comprehensively.
-- You should not include any unrelated or "extra" small tweaks or changes.
-
-## Style Guidelines
-
-### Code Formatting
-
-We use the `black` and `isort` code formatters to maintain a consistent coding style across the project. Please ensure that your code is formatted properly before submitting a pull request.
-
-To format your code, run the following commands in the project's root directory:
-
-```bash
-python -m black .
-python -m isort .
-```
-
-Or if you have these tools installed globally:
-```bash
-black .
-isort .
-```
-
-### Pre-Commit Hooks
-
-We use pre-commit hooks to ensure that code formatting and other checks are performed automatically before each commit. To set up pre-commit hooks for this project, follow these steps:
-
-Install the pre-commit package using pip:
-```bash
-pip install pre-commit
-```
-
-Run the following command in the project's root directory to install the pre-commit hooks:
-```bash
-pre-commit install
-```
-
-Now, the pre-commit hooks will run automatically before each commit, checking your code formatting and other requirements.
-
-If you encounter any issues or have questions, feel free to reach out to the maintainers or open a new issue on GitHub. We're here to help and appreciate your efforts to contribute to the project.
-
-Happy coding, and once again, thank you for your contributions!
-
-Maintainers will look at PR that have no merge conflicts when deciding what to add to the project. Make sure your PR shows up here:
-https://github.com/Significant-Gravitas/Auto-GPT/pulls?q=is%3Apr+is%3Aopen+-label%3Aconflicts
-
-## Testing your changes
-
-If you add or change code, make sure the updated code is covered by tests.
-To increase coverage if necessary, [write tests using pytest].
-
-For more info on running tests, please refer to ["Running tests"](https://significant-gravitas.github.io/Auto-GPT/testing/).
-
-[write tests using pytest]: https://realpython.com/pytest-python-testing/
-
-### API-dependent tests
-
-To run tests that involve making calls to the OpenAI API, we use VCRpy. It caches known
-requests and matching responses in so-called *cassettes*, allowing us to run the tests
-in CI without needing actual API access.
-
-When changes cause a test prompt to be generated differently, it will likely miss the
-cache and make a request to the API, updating the cassette with the new request+response.
-*Be sure to include the updated cassette in your PR!*
-
-When you run Pytest locally:
-
-- If no prompt change: you will not consume API tokens because there are no new OpenAI calls required.
-- If the prompt changes in a way that the cassettes are not reusable:
-    - If no API key, the test fails. It requires a new cassette. So, add an API key to .env.
-    - If the API key is present, the tests will make a real call to OpenAI.
-        - If the test ends up being successful, your prompt changes didn't introduce regressions. This is good. Commit your cassettes to your PR.
-        - If the test is unsuccessful:
-            - Either: Your change made Auto-GPT less capable, in that case, you have to change your code.
-            - Or: The test might be poorly written. In that case, you can make suggestions to change the test.
-
-In our CI pipeline, Pytest will use the cassettes and not call paid API providers, so we need your help to record the replays that you break.
-
-
-### Community Challenges
-Challenges are goals we need Auto-GPT to achieve. 
-To pick the challenge you like, go to the tests/integration/challenges folder and select the areas you would like to work on. 
-- a challenge is new if level_currently_beaten is None
-- a challenge is in progress if level_currently_beaten is greater or equal to 1
-- a challenge is beaten if level_currently_beaten = max_level
-
-Here is an example of how to run the memory challenge A and attempt to beat level 3.
-
-pytest -s tests/integration/challenges/memory/test_memory_challenge_a.py --level=3
-
-To beat a challenge, you're not allowed to change anything in the tests folder, you have to add code in the autogpt folder
-
-Challenges use cassettes. Cassettes allow us to replay your runs in our CI pipeline.
-Don't hesitate to delete the cassettes associated to the challenge you're working on if you need to. Otherwise it will keep replaying the last run.
-
-Once you've beaten a new level of a challenge, please create a pull request and we will analyze how you changed Auto-GPT to beat the challenge.
+❤️ & 🔆
+The team @ AutoGPT
+https://discord.gg/autogpt

Dockerfile

@@ -1,40 +0,0 @@
-# 'dev' or 'release' container build
-ARG BUILD_TYPE=dev
-
-# Use an official Python base image from the Docker Hub
-FROM python:3.10-slim AS autogpt-base
-
-# Install browsers
-RUN apt-get update && apt-get install -y \
-    chromium-driver firefox-esr \
-    ca-certificates
-
-# Install utilities
-RUN apt-get install -y curl jq wget git
-
-# Set environment variables
-ENV PIP_NO_CACHE_DIR=yes \
-    PYTHONUNBUFFERED=1 \
-    PYTHONDONTWRITEBYTECODE=1
-
-# Install the required python packages globally
-ENV PATH="$PATH:/root/.local/bin"
-COPY requirements.txt .
-
-# Set the entrypoint
-ENTRYPOINT ["python", "-m", "autogpt"]
-
-# dev build -> include everything
-FROM autogpt-base as autogpt-dev
-RUN pip install --no-cache-dir -r requirements.txt
-WORKDIR /app
-ONBUILD COPY . ./
-
-# release build -> include bare minimum
-FROM autogpt-base as autogpt-release
-RUN sed -i '/Items below this point will not be included in the Docker Image/,$d' requirements.txt && \
-	pip install --no-cache-dir -r requirements.txt
-WORKDIR /app
-ONBUILD COPY autogpt/ ./autogpt
-
-FROM autogpt-${BUILD_TYPE} AS auto-gpt

LICENSE

@@ -1,7 +1,13 @@
+All portions of this repository are under one of two licenses. The majority of the AutoGPT repository is under the MIT License below. The autogpt_platform folder is under the
+Polyform Shield License. 
+
+
 MIT License
 
+
 Copyright (c) 2023 Toran Bruce Richards
 
+
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal
 in the Software without restriction, including without limitation the rights
@@ -9,9 +15,11 @@ to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 copies of the Software, and to permit persons to whom the Software is
 furnished to do so, subject to the following conditions:
 
+
 The above copyright notice and this permission notice shall be included in all
 copies or substantial portions of the Software.
 
+
 THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE

SECURITY.md

@@ -0,0 +1,48 @@
+# Security Policy
+
+## Reporting Security Issues
+
+We take the security of our project seriously. If you believe you have found a security vulnerability, please report it to us privately. **Please do not report security vulnerabilities through public GitHub issues, discussions, or pull requests.**
+
+> **Important Note**: Any code within the `classic/` folder is considered legacy, unsupported, and out of scope for security reports. We will not address security vulnerabilities in this deprecated code.
+
+Instead, please report them via:
+- [GitHub Security Advisory](https://github.com/Significant-Gravitas/AutoGPT/security/advisories/new)
+<!--- [Huntr.dev](https://huntr.com/repos/significant-gravitas/autogpt) - where you may be eligible for a bounty-->
+
+### Reporting Process
+1. **Submit Report**: Use one of the above channels to submit your report
+2. **Response Time**: Our team will acknowledge receipt of your report within 14 business days.
+3. **Collaboration**: We will collaborate with you to understand and validate the issue
+4. **Resolution**: We will work on a fix and coordinate the release process
+
+### Disclosure Policy
+- Please provide detailed reports with reproducible steps
+- Include the version/commit hash where you discovered the vulnerability
+- Allow us a 90-day security fix window before any public disclosure
+- After patch is released, allow 30 days for users to update before public disclosure (for a total of 120 days max between update time and fix time)
+- Share any potential mitigations or workarounds if known
+
+## Supported Versions
+Only the following versions are eligible for security updates:
+
+| Version | Supported |
+|---------|-----------|
+| Latest release on master branch | ✅ |
+| Development commits (pre-master) | ✅ |
+| Classic folder (deprecated) | ❌ |
+| All other versions | ❌ |
+
+## Security Best Practices
+When using this project:
+1. Always use the latest stable version
+2. Review security advisories before updating
+3. Follow our security documentation and guidelines
+4. Keep your dependencies up to date
+5. Do not use code from the `classic/` folder as it is deprecated and unsupported
+
+## Past Security Advisories
+For a list of past security advisories, please visit our [Security Advisory Page](https://github.com/Significant-Gravitas/AutoGPT/security/advisories) and [Huntr Disclosures Page](https://huntr.com/repos/significant-gravitas/autogpt).
+
+---
+Last updated: November 2024

autogpt/__main__.py

@@ -1,5 +0,0 @@
-"""Auto-GPT: A GPT powered AI Assistant"""
-import autogpt.cli
-
-if __name__ == "__main__":
-    autogpt.cli.main()

autogpt/agent/__init__.py

@@ -1,4 +0,0 @@
-from autogpt.agent.agent import Agent
-from autogpt.agent.agent_manager import AgentManager
-
-__all__ = ["Agent", "AgentManager"]

autogpt/agent/agent.py

@@ -1,290 +0,0 @@
-from colorama import Fore, Style
-
-from autogpt.app import execute_command, get_command
-from autogpt.config import Config
-from autogpt.json_utils.json_fix_llm import fix_json_using_multiple_techniques
-from autogpt.json_utils.utilities import LLM_DEFAULT_RESPONSE_FORMAT, validate_json
-from autogpt.llm import chat_with_ai, create_chat_completion, create_chat_message
-from autogpt.logs import logger, print_assistant_thoughts
-from autogpt.speech import say_text
-from autogpt.spinner import Spinner
-from autogpt.utils import clean_input
-from autogpt.workspace import Workspace
-
-
-class Agent:
-    """Agent class for interacting with Auto-GPT.
-
-    Attributes:
-        ai_name: The name of the agent.
-        memory: The memory object to use.
-        full_message_history: The full message history.
-        next_action_count: The number of actions to execute.
-        system_prompt: The system prompt is the initial prompt that defines everything
-          the AI needs to know to achieve its task successfully.
-        Currently, the dynamic and customizable information in the system prompt are
-          ai_name, description and goals.
-
-        triggering_prompt: The last sentence the AI will see before answering.
-            For Auto-GPT, this prompt is:
-            Determine which next command to use, and respond using the format specified
-              above:
-            The triggering prompt is not part of the system prompt because between the
-              system prompt and the triggering
-            prompt we have contextual information that can distract the AI and make it
-              forget that its goal is to find the next task to achieve.
-            SYSTEM PROMPT
-            CONTEXTUAL INFORMATION (memory, previous conversations, anything relevant)
-            TRIGGERING PROMPT
-
-        The triggering prompt reminds the AI about its short term meta task
-        (defining the next task)
-    """
-
-    def __init__(
-        self,
-        ai_name,
-        memory,
-        full_message_history,
-        next_action_count,
-        command_registry,
-        config,
-        system_prompt,
-        triggering_prompt,
-        workspace_directory,
-    ):
-        cfg = Config()
-        self.ai_name = ai_name
-        self.memory = memory
-        self.summary_memory = (
-            "I was created."  # Initial memory necessary to avoid hilucination
-        )
-        self.last_memory_index = 0
-        self.full_message_history = full_message_history
-        self.next_action_count = next_action_count
-        self.command_registry = command_registry
-        self.config = config
-        self.system_prompt = system_prompt
-        self.triggering_prompt = triggering_prompt
-        self.workspace = Workspace(workspace_directory, cfg.restrict_to_workspace)
-
-    def start_interaction_loop(self):
-        # Interaction Loop
-        cfg = Config()
-        loop_count = 0
-        command_name = None
-        arguments = None
-        user_input = ""
-
-        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_with_ai(
-                    self,
-                    self.system_prompt,
-                    self.triggering_prompt,
-                    self.full_message_history,
-                    self.memory,
-                    cfg.fast_token_limit,
-                )  # TODO: This hardcodes the model to use GPT3.5. Make this an argument
-
-            assistant_reply_json = fix_json_using_multiple_techniques(assistant_reply)
-            for plugin in cfg.plugins:
-                if not plugin.can_handle_post_planning():
-                    continue
-                assistant_reply_json = plugin.post_planning(self, assistant_reply_json)
-
-            # Print Assistant thoughts
-            if assistant_reply_json != {}:
-                validate_json(assistant_reply_json, LLM_DEFAULT_RESPONSE_FORMAT)
-                # Get command name and arguments
-                try:
-                    print_assistant_thoughts(
-                        self.ai_name, assistant_reply_json, cfg.speak_mode
-                    )
-                    command_name, arguments = get_command(assistant_reply_json)
-                    if cfg.speak_mode:
-                        say_text(f"I want to execute {command_name}")
-
-                    arguments = self._resolve_pathlike_command_args(arguments)
-
-                except Exception as e:
-                    logger.error("Error: \n", str(e))
-
-            if not cfg.continuous_mode and self.next_action_count == 0:
-                # ### GET USER AUTHORIZATION TO EXECUTE COMMAND ###
-                # Get key press: Prompt the user to press enter to continue or escape
-                # to exit
-                self.user_input = ""
-                logger.typewriter_log(
-                    "NEXT ACTION: ",
-                    Fore.CYAN,
-                    f"COMMAND = {Fore.CYAN}{command_name}{Style.RESET_ALL}  "
-                    f"ARGUMENTS = {Fore.CYAN}{arguments}{Style.RESET_ALL}",
-                )
-
-                logger.info(
-                    "Enter 'y' to authorise command, 'y -N' to run N continuous commands, 's' to run self-feedback commands"
-                    "'n' to exit program, or enter feedback for "
-                    f"{self.ai_name}..."
-                )
-                while True:
-                    if cfg.chat_messages_enabled:
-                        console_input = clean_input("Waiting for your response...")
-                    else:
-                        console_input = clean_input(
-                            Fore.MAGENTA + "Input:" + Style.RESET_ALL
-                        )
-                    if console_input.lower().strip() == cfg.authorise_key:
-                        user_input = "GENERATE NEXT COMMAND JSON"
-                        break
-                    elif console_input.lower().strip() == "s":
-                        logger.typewriter_log(
-                            "-=-=-=-=-=-=-= THOUGHTS, REASONING, PLAN AND CRITICISM WILL NOW BE VERIFIED BY AGENT -=-=-=-=-=-=-=",
-                            Fore.GREEN,
-                            "",
-                        )
-                        thoughts = assistant_reply_json.get("thoughts", {})
-                        self_feedback_resp = self.get_self_feedback(
-                            thoughts, cfg.fast_llm_model
-                        )
-                        logger.typewriter_log(
-                            f"SELF FEEDBACK: {self_feedback_resp}",
-                            Fore.YELLOW,
-                            "",
-                        )
-                        if self_feedback_resp[0].lower().strip() == cfg.authorise_key:
-                            user_input = "GENERATE NEXT COMMAND JSON"
-                        else:
-                            user_input = self_feedback_resp
-                        break
-                    elif console_input.lower().strip() == "":
-                        logger.warn("Invalid input format.")
-                        continue
-                    elif console_input.lower().startswith(f"{cfg.authorise_key} -"):
-                        try:
-                            self.next_action_count = abs(
-                                int(console_input.split(" ")[1])
-                            )
-                            user_input = "GENERATE NEXT COMMAND JSON"
-                        except ValueError:
-                            logger.warn(
-                                "Invalid input format. Please enter 'y -n' where n is"
-                                " the number of continuous tasks."
-                            )
-                            continue
-                        break
-                    elif console_input.lower() == cfg.exit_key:
-                        user_input = "EXIT"
-                        break
-                    else:
-                        user_input = console_input
-                        command_name = "human_feedback"
-                        break
-
-                if user_input == "GENERATE NEXT COMMAND JSON":
-                    logger.typewriter_log(
-                        "-=-=-=-=-=-=-= COMMAND AUTHORISED BY USER -=-=-=-=-=-=-=",
-                        Fore.MAGENTA,
-                        "",
-                    )
-                elif user_input == "EXIT":
-                    logger.info("Exiting...")
-                    break
-            else:
-                # Print command
-                logger.typewriter_log(
-                    "NEXT ACTION: ",
-                    Fore.CYAN,
-                    f"COMMAND = {Fore.CYAN}{command_name}{Style.RESET_ALL}"
-                    f"  ARGUMENTS = {Fore.CYAN}{arguments}{Style.RESET_ALL}",
-                )
-
-            # Execute command
-            if command_name is not None and command_name.lower().startswith("error"):
-                result = (
-                    f"Command {command_name} threw the following error: {arguments}"
-                )
-            elif command_name == "human_feedback":
-                result = f"Human feedback: {user_input}"
-            else:
-                for plugin in cfg.plugins:
-                    if not plugin.can_handle_pre_command():
-                        continue
-                    command_name, arguments = plugin.pre_command(
-                        command_name, arguments
-                    )
-                command_result = execute_command(
-                    self.command_registry,
-                    command_name,
-                    arguments,
-                    self.config.prompt_generator,
-                )
-                result = f"Command {command_name} returned: " f"{command_result}"
-
-                for plugin in cfg.plugins:
-                    if not plugin.can_handle_post_command():
-                        continue
-                    result = plugin.post_command(command_name, result)
-                if self.next_action_count > 0:
-                    self.next_action_count -= 1
-
-            # Check if there's a result from the command append it to the message
-            # history
-            if result is not None:
-                self.full_message_history.append(create_chat_message("system", result))
-                logger.typewriter_log("SYSTEM: ", Fore.YELLOW, result)
-            else:
-                self.full_message_history.append(
-                    create_chat_message("system", "Unable to execute command")
-                )
-                logger.typewriter_log(
-                    "SYSTEM: ", Fore.YELLOW, "Unable to execute command"
-                )
-
-    def _resolve_pathlike_command_args(self, command_args):
-        if "directory" in command_args and command_args["directory"] in {"", "/"}:
-            command_args["directory"] = str(self.workspace.root)
-        else:
-            for pathlike in ["filename", "directory", "clone_path"]:
-                if pathlike in command_args:
-                    command_args[pathlike] = str(
-                        self.workspace.get_path(command_args[pathlike])
-                    )
-        return command_args
-
-    def get_self_feedback(self, thoughts: dict, llm_model: str) -> str:
-        """Generates a feedback response based on the provided thoughts dictionary.
-        This method takes in a dictionary of thoughts containing keys such as 'reasoning',
-        'plan', 'thoughts', and 'criticism'. It combines these elements into a single
-        feedback message and uses the create_chat_completion() function to generate a
-        response based on the input message.
-        Args:
-            thoughts (dict): A dictionary containing thought elements like reasoning,
-            plan, thoughts, and criticism.
-        Returns:
-            str: A feedback response generated using the provided thoughts dictionary.
-        """
-        ai_role = self.config.ai_role
-
-        feedback_prompt = f"Below is a message from an AI agent with the role of {ai_role}. Please review the provided Thought, Reasoning, Plan, and Criticism. If these elements accurately contribute to the successful execution of the assumed role, respond with the letter 'Y' followed by a space, and then explain why it is effective. If the provided information is not suitable for achieving the role's objectives, please provide one or more sentences addressing the issue and suggesting a resolution."
-        reasoning = thoughts.get("reasoning", "")
-        plan = thoughts.get("plan", "")
-        thought = thoughts.get("thoughts", "")
-        criticism = thoughts.get("criticism", "")
-        feedback_thoughts = thought + reasoning + plan + criticism
-        return create_chat_completion(
-            [{"role": "user", "content": feedback_prompt + feedback_thoughts}],
-            llm_model,
-        )

autogpt/agent/agent_manager.py

@@ -1,145 +0,0 @@
-"""Agent manager for managing GPT agents"""
-from __future__ import annotations
-
-from typing import List
-
-from autogpt.config.config import Config
-from autogpt.llm import Message, create_chat_completion
-from autogpt.singleton import Singleton
-
-
-class AgentManager(metaclass=Singleton):
-    """Agent manager for managing GPT agents"""
-
-    def __init__(self):
-        self.next_key = 0
-        self.agents = {}  # key, (task, full_message_history, model)
-        self.cfg = Config()
-
-    # Create new GPT agent
-    # TODO: Centralise use of create_chat_completion() to globally enforce token limit
-
-    def create_agent(self, task: str, prompt: str, model: str) -> tuple[int, str]:
-        """Create a new agent and return its key
-
-        Args:
-            task: The task to perform
-            prompt: The prompt to use
-            model: The model to use
-
-        Returns:
-            The key of the new agent
-        """
-        messages: List[Message] = [
-            {"role": "user", "content": prompt},
-        ]
-        for plugin in self.cfg.plugins:
-            if not plugin.can_handle_pre_instruction():
-                continue
-            if plugin_messages := plugin.pre_instruction(messages):
-                messages.extend(iter(plugin_messages))
-        # Start GPT instance
-        agent_reply = create_chat_completion(
-            model=model,
-            messages=messages,
-        )
-
-        messages.append({"role": "assistant", "content": agent_reply})
-
-        plugins_reply = ""
-        for i, plugin in enumerate(self.cfg.plugins):
-            if not plugin.can_handle_on_instruction():
-                continue
-            if plugin_result := plugin.on_instruction(messages):
-                sep = "\n" if i else ""
-                plugins_reply = f"{plugins_reply}{sep}{plugin_result}"
-
-        if plugins_reply and plugins_reply != "":
-            messages.append({"role": "assistant", "content": plugins_reply})
-        key = self.next_key
-        # This is done instead of len(agents) to make keys unique even if agents
-        # are deleted
-        self.next_key += 1
-
-        self.agents[key] = (task, messages, model)
-
-        for plugin in self.cfg.plugins:
-            if not plugin.can_handle_post_instruction():
-                continue
-            agent_reply = plugin.post_instruction(agent_reply)
-
-        return key, agent_reply
-
-    def message_agent(self, key: str | int, message: str) -> str:
-        """Send a message to an agent and return its response
-
-        Args:
-            key: The key of the agent to message
-            message: The message to send to the agent
-
-        Returns:
-            The agent's response
-        """
-        task, messages, model = self.agents[int(key)]
-
-        # Add user message to message history before sending to agent
-        messages.append({"role": "user", "content": message})
-
-        for plugin in self.cfg.plugins:
-            if not plugin.can_handle_pre_instruction():
-                continue
-            if plugin_messages := plugin.pre_instruction(messages):
-                for plugin_message in plugin_messages:
-                    messages.append(plugin_message)
-
-        # Start GPT instance
-        agent_reply = create_chat_completion(
-            model=model,
-            messages=messages,
-        )
-
-        messages.append({"role": "assistant", "content": agent_reply})
-
-        plugins_reply = agent_reply
-        for i, plugin in enumerate(self.cfg.plugins):
-            if not plugin.can_handle_on_instruction():
-                continue
-            if plugin_result := plugin.on_instruction(messages):
-                sep = "\n" if i else ""
-                plugins_reply = f"{plugins_reply}{sep}{plugin_result}"
-        # Update full message history
-        if plugins_reply and plugins_reply != "":
-            messages.append({"role": "assistant", "content": plugins_reply})
-
-        for plugin in self.cfg.plugins:
-            if not plugin.can_handle_post_instruction():
-                continue
-            agent_reply = plugin.post_instruction(agent_reply)
-
-        return agent_reply
-
-    def list_agents(self) -> list[tuple[str | int, str]]:
-        """Return a list of all agents
-
-        Returns:
-            A list of tuples of the form (key, task)
-        """
-
-        # Return a list of agent keys and their tasks
-        return [(key, task) for key, (task, _, _) in self.agents.items()]
-
-    def delete_agent(self, key: str | int) -> bool:
-        """Delete an agent from the agent manager
-
-        Args:
-            key: The key of the agent to delete
-
-        Returns:
-            True if successful, False otherwise
-        """
-
-        try:
-            del self.agents[int(key)]
-            return True
-        except KeyError:
-            return False

autogpt/app.py

@@ -1,255 +0,0 @@
-""" Command and Control """
-import json
-from typing import Dict, List, NoReturn, Union
-
-from autogpt.agent.agent_manager import AgentManager
-from autogpt.commands.command import CommandRegistry, command
-from autogpt.commands.web_requests import scrape_links, scrape_text
-from autogpt.config import Config
-from autogpt.logs import logger
-from autogpt.memory import get_memory
-from autogpt.processing.text import summarize_text
-from autogpt.prompts.generator import PromptGenerator
-from autogpt.speech import say_text
-from autogpt.url_utils.validators import validate_url
-
-CFG = Config()
-AGENT_MANAGER = AgentManager()
-
-
-def is_valid_int(value: str) -> bool:
-    """Check if the value is a valid integer
-
-    Args:
-        value (str): The value to check
-
-    Returns:
-        bool: True if the value is a valid integer, False otherwise
-    """
-    try:
-        int(value)
-        return True
-    except ValueError:
-        return False
-
-
-def get_command(response_json: Dict):
-    """Parse the response and return the command name and arguments
-
-    Args:
-        response_json (json): The response from the AI
-
-    Returns:
-        tuple: The command name and arguments
-
-    Raises:
-        json.decoder.JSONDecodeError: If the response is not valid JSON
-
-        Exception: If any other error occurs
-    """
-    try:
-        if "command" not in response_json:
-            return "Error:", "Missing 'command' object in JSON"
-
-        if not isinstance(response_json, dict):
-            return "Error:", f"'response_json' object is not dictionary {response_json}"
-
-        command = response_json["command"]
-        if not isinstance(command, dict):
-            return "Error:", "'command' object is not a dictionary"
-
-        if "name" not in command:
-            return "Error:", "Missing 'name' field in 'command' object"
-
-        command_name = command["name"]
-
-        # Use an empty dictionary if 'args' field is not present in 'command' object
-        arguments = command.get("args", {})
-
-        return command_name, arguments
-    except json.decoder.JSONDecodeError:
-        return "Error:", "Invalid JSON"
-    # All other errors, return "Error: + error message"
-    except Exception as e:
-        return "Error:", str(e)
-
-
-def map_command_synonyms(command_name: str):
-    """Takes the original command name given by the AI, and checks if the
-    string matches a list of common/known hallucinations
-    """
-    synonyms = [
-        ("write_file", "write_to_file"),
-        ("create_file", "write_to_file"),
-        ("search", "google"),
-    ]
-    for seen_command, actual_command_name in synonyms:
-        if command_name == seen_command:
-            return actual_command_name
-    return command_name
-
-
-def execute_command(
-    command_registry: CommandRegistry,
-    command_name: str,
-    arguments,
-    prompt: PromptGenerator,
-):
-    """Execute the command and return the result
-
-    Args:
-        command_name (str): The name of the command to execute
-        arguments (dict): The arguments for the command
-
-    Returns:
-        str: The result of the command
-    """
-    try:
-        cmd = command_registry.commands.get(command_name)
-
-        # If the command is found, call it with the provided arguments
-        if cmd:
-            return cmd(**arguments)
-
-        # TODO: Remove commands below after they are moved to the command registry.
-        command_name = map_command_synonyms(command_name.lower())
-
-        if command_name == "memory_add":
-            return get_memory(CFG).add(arguments["string"])
-
-        # TODO: Change these to take in a file rather than pasted code, if
-        # non-file is given, return instructions "Input should be a python
-        # filepath, write your code to file and try again
-        elif command_name == "task_complete":
-            shutdown()
-        else:
-            for command in prompt.commands:
-                if (
-                    command_name == command["label"].lower()
-                    or command_name == command["name"].lower()
-                ):
-                    return command["function"](**arguments)
-            return (
-                f"Unknown command '{command_name}'. Please refer to the 'COMMANDS'"
-                " list for available commands and only respond in the specified JSON"
-                " format."
-            )
-    except Exception as e:
-        return f"Error: {str(e)}"
-
-
-@command(
-    "get_text_summary", "Get text summary", '"url": "<url>", "question": "<question>"'
-)
-@validate_url
-def get_text_summary(url: str, question: str) -> str:
-    """Return the results of a Google search
-
-    Args:
-        url (str): The url to scrape
-        question (str): The question to summarize the text for
-
-    Returns:
-        str: The summary of the text
-    """
-    text = scrape_text(url)
-    summary = summarize_text(url, text, question)
-    return f""" "Result" : {summary}"""
-
-
-@command("get_hyperlinks", "Get text summary", '"url": "<url>"')
-@validate_url
-def get_hyperlinks(url: str) -> Union[str, List[str]]:
-    """Return the results of a Google search
-
-    Args:
-        url (str): The url to scrape
-
-    Returns:
-        str or list: The hyperlinks on the page
-    """
-    return scrape_links(url)
-
-
-def shutdown() -> NoReturn:
-    """Shut down the program"""
-    logger.info("Shutting down...")
-    quit()
-
-
-@command(
-    "start_agent",
-    "Start GPT Agent",
-    '"name": "<name>", "task": "<short_task_desc>", "prompt": "<prompt>"',
-)
-def start_agent(name: str, task: str, prompt: str, model=CFG.fast_llm_model) -> str:
-    """Start an agent with a given name, task, and prompt
-
-    Args:
-        name (str): The name of the agent
-        task (str): The task of the agent
-        prompt (str): The prompt for the agent
-        model (str): The model to use for the agent
-
-    Returns:
-        str: The response of the agent
-    """
-    # Remove underscores from name
-    voice_name = name.replace("_", " ")
-
-    first_message = f"""You are {name}.  Respond with: "Acknowledged"."""
-    agent_intro = f"{voice_name} here, Reporting for duty!"
-
-    # Create agent
-    if CFG.speak_mode:
-        say_text(agent_intro, 1)
-    key, ack = AGENT_MANAGER.create_agent(task, first_message, model)
-
-    if CFG.speak_mode:
-        say_text(f"Hello {voice_name}. Your task is as follows. {task}.")
-
-    # Assign task (prompt), get response
-    agent_response = AGENT_MANAGER.message_agent(key, prompt)
-
-    return f"Agent {name} created with key {key}. First response: {agent_response}"
-
-
-@command("message_agent", "Message GPT Agent", '"key": "<key>", "message": "<message>"')
-def message_agent(key: str, message: str) -> str:
-    """Message an agent with a given key and message"""
-    # Check if the key is a valid integer
-    if is_valid_int(key):
-        agent_response = AGENT_MANAGER.message_agent(int(key), message)
-    else:
-        return "Invalid key, must be an integer."
-
-    # Speak response
-    if CFG.speak_mode:
-        say_text(agent_response, 1)
-    return agent_response
-
-
-@command("list_agents", "List GPT Agents", "")
-def list_agents() -> str:
-    """List all agents
-
-    Returns:
-        str: A list of all agents
-    """
-    return "List of agents:\n" + "\n".join(
-        [str(x[0]) + ": " + x[1] for x in AGENT_MANAGER.list_agents()]
-    )
-
-
-@command("delete_agent", "Delete GPT Agent", '"key": "<key>"')
-def delete_agent(key: str) -> str:
-    """Delete an agent with a given key
-
-    Args:
-        key (str): The key of the agent to delete
-
-    Returns:
-        str: A message indicating whether the agent was deleted or not
-    """
-    result = AGENT_MANAGER.delete_agent(key)
-    return f"Agent {key} deleted." if result else f"Agent {key} does not exist."

autogpt/cli.py

@@ -1,109 +0,0 @@
-"""Main script for the autogpt package."""
-import click
-
-
-@click.group(invoke_without_command=True)
-@click.option("-c", "--continuous", is_flag=True, help="Enable Continuous Mode")
-@click.option(
-    "--skip-reprompt",
-    "-y",
-    is_flag=True,
-    help="Skips the re-prompting messages at the beginning of the script",
-)
-@click.option(
-    "--ai-settings",
-    "-C",
-    help="Specifies which ai_settings.yaml file to use, will also automatically skip the re-prompt.",
-)
-@click.option(
-    "-l",
-    "--continuous-limit",
-    type=int,
-    help="Defines the number of times to run in continuous mode",
-)
-@click.option("--speak", is_flag=True, help="Enable Speak Mode")
-@click.option("--debug", is_flag=True, help="Enable Debug Mode")
-@click.option("--gpt3only", is_flag=True, help="Enable GPT3.5 Only Mode")
-@click.option("--gpt4only", is_flag=True, help="Enable GPT4 Only Mode")
-@click.option(
-    "--use-memory",
-    "-m",
-    "memory_type",
-    type=str,
-    help="Defines which Memory backend to use",
-)
-@click.option(
-    "-b",
-    "--browser-name",
-    help="Specifies which web-browser to use when using selenium to scrape the web.",
-)
-@click.option(
-    "--allow-downloads",
-    is_flag=True,
-    help="Dangerous: Allows Auto-GPT to download files natively.",
-)
-@click.option(
-    "--skip-news",
-    is_flag=True,
-    help="Specifies whether to suppress the output of latest news on startup.",
-)
-@click.option(
-    # TODO: this is a hidden option for now, necessary for integration testing.
-    #   We should make this public once we're ready to roll out agent specific workspaces.
-    "--workspace-directory",
-    "-w",
-    type=click.Path(),
-    hidden=True,
-)
-@click.option(
-    "--install-plugin-deps",
-    is_flag=True,
-    help="Installs external dependencies for 3rd party plugins.",
-)
-@click.pass_context
-def main(
-    ctx: click.Context,
-    continuous: bool,
-    continuous_limit: int,
-    ai_settings: str,
-    skip_reprompt: bool,
-    speak: bool,
-    debug: bool,
-    gpt3only: bool,
-    gpt4only: bool,
-    memory_type: str,
-    browser_name: str,
-    allow_downloads: bool,
-    skip_news: bool,
-    workspace_directory: str,
-    install_plugin_deps: bool,
-) -> None:
-    """
-    Welcome to AutoGPT an experimental open-source application showcasing the capabilities of the GPT-4 pushing the boundaries of AI.
-
-    Start an Auto-GPT assistant.
-    """
-    # Put imports inside function to avoid importing everything when starting the CLI
-    from autogpt.main import run_auto_gpt
-
-    if ctx.invoked_subcommand is None:
-        run_auto_gpt(
-            continuous,
-            continuous_limit,
-            ai_settings,
-            skip_reprompt,
-            speak,
-            debug,
-            gpt3only,
-            gpt4only,
-            memory_type,
-            browser_name,
-            allow_downloads,
-            skip_news,
-            workspace_directory,
-            install_plugin_deps,
-        )
-
-
-if __name__ == "__main__":
-    main()

autogpt/commands/analyze_code.py

@@ -1,31 +0,0 @@
-"""Code evaluation module."""
-from __future__ import annotations
-
-from autogpt.commands.command import command
-from autogpt.llm import call_ai_function
-
-
-@command(
-    "analyze_code",
-    "Analyze Code",
-    '"code": "<full_code_string>"',
-)
-def analyze_code(code: str) -> list[str]:
-    """
-    A function that takes in a string and returns a response from create chat
-      completion api call.
-
-    Parameters:
-        code (str): Code to be evaluated.
-    Returns:
-        A result string from create chat completion. A list of suggestions to
-            improve the code.
-    """
-
-    function_string = "def analyze_code(code: str) -> list[str]:"
-    args = [code]
-    description_string = (
-        "Analyzes the given code and returns a list of suggestions for improvements."
-    )
-
-    return call_ai_function(function_string, args, description_string)

autogpt/commands/audio_text.py

@@ -1,61 +0,0 @@
-"""Commands for converting audio to text."""
-import json
-
-import requests
-
-from autogpt.commands.command import command
-from autogpt.config import Config
-
-CFG = Config()
-
-
-@command(
-    "read_audio_from_file",
-    "Convert Audio to text",
-    '"filename": "<filename>"',
-    CFG.huggingface_audio_to_text_model,
-    "Configure huggingface_audio_to_text_model.",
-)
-def read_audio_from_file(filename: str) -> str:
-    """
-    Convert audio to text.
-
-    Args:
-        filename (str): The path to the audio file
-
-    Returns:
-        str: The text from the audio
-    """
-    with open(filename, "rb") as audio_file:
-        audio = audio_file.read()
-    return read_audio(audio)
-
-
-def read_audio(audio: bytes) -> str:
-    """
-    Convert audio to text.
-
-    Args:
-        audio (bytes): The audio to convert
-
-    Returns:
-        str: The text from the audio
-    """
-    model = CFG.huggingface_audio_to_text_model
-    api_url = f"https://api-inference.huggingface.co/models/{model}"
-    api_token = CFG.huggingface_api_token
-    headers = {"Authorization": f"Bearer {api_token}"}
-
-    if api_token is None:
-        raise ValueError(
-            "You need to set your Hugging Face API token in the config file."
-        )
-
-    response = requests.post(
-        api_url,
-        headers=headers,
-        data=audio,
-    )
-
-    text = json.loads(response.content.decode("utf-8"))["text"]
-    return f"The audio says: {text}"

autogpt/commands/command.py

@@ -1,156 +0,0 @@
-import functools
-import importlib
-import inspect
-from typing import Any, Callable, Optional
-
-# Unique identifier for auto-gpt commands
-AUTO_GPT_COMMAND_IDENTIFIER = "auto_gpt_command"
-
-
-class Command:
-    """A class representing a command.
-
-    Attributes:
-        name (str): The name of the command.
-        description (str): A brief description of what the command does.
-        signature (str): The signature of the function that the command executes. Defaults to None.
-    """
-
-    def __init__(
-        self,
-        name: str,
-        description: str,
-        method: Callable[..., Any],
-        signature: str = "",
-        enabled: bool = True,
-        disabled_reason: Optional[str] = None,
-    ):
-        self.name = name
-        self.description = description
-        self.method = method
-        self.signature = signature if signature else str(inspect.signature(self.method))
-        self.enabled = enabled
-        self.disabled_reason = disabled_reason
-
-    def __call__(self, *args, **kwargs) -> Any:
-        if not self.enabled:
-            return f"Command '{self.name}' is disabled: {self.disabled_reason}"
-        return self.method(*args, **kwargs)
-
-    def __str__(self) -> str:
-        return f"{self.name}: {self.description}, args: {self.signature}"
-
-
-class CommandRegistry:
-    """
-    The CommandRegistry class is a manager for a collection of Command objects.
-    It allows the registration, modification, and retrieval of Command objects,
-    as well as the scanning and loading of command plugins from a specified
-    directory.
-    """
-
-    def __init__(self):
-        self.commands = {}
-
-    def _import_module(self, module_name: str) -> Any:
-        return importlib.import_module(module_name)
-
-    def _reload_module(self, module: Any) -> Any:
-        return importlib.reload(module)
-
-    def register(self, cmd: Command) -> None:
-        self.commands[cmd.name] = cmd
-
-    def unregister(self, command_name: str):
-        if command_name in self.commands:
-            del self.commands[command_name]
-        else:
-            raise KeyError(f"Command '{command_name}' not found in registry.")
-
-    def reload_commands(self) -> None:
-        """Reloads all loaded command plugins."""
-        for cmd_name in self.commands:
-            cmd = self.commands[cmd_name]
-            module = self._import_module(cmd.__module__)
-            reloaded_module = self._reload_module(module)
-            if hasattr(reloaded_module, "register"):
-                reloaded_module.register(self)
-
-    def get_command(self, name: str) -> Callable[..., Any]:
-        return self.commands[name]
-
-    def call(self, command_name: str, **kwargs) -> Any:
-        if command_name not in self.commands:
-            raise KeyError(f"Command '{command_name}' not found in registry.")
-        command = self.commands[command_name]
-        return command(**kwargs)
-
-    def command_prompt(self) -> str:
-        """
-        Returns a string representation of all registered `Command` objects for use in a prompt
-        """
-        commands_list = [
-            f"{idx + 1}. {str(cmd)}" for idx, cmd in enumerate(self.commands.values())
-        ]
-        return "\n".join(commands_list)
-
-    def import_commands(self, module_name: str) -> None:
-        """
-        Imports the specified Python module containing command plugins.
-
-        This method imports the associated module and registers any functions or
-        classes that are decorated with the `AUTO_GPT_COMMAND_IDENTIFIER` attribute
-        as `Command` objects. The registered `Command` objects are then added to the
-        `commands` dictionary of the `CommandRegistry` object.
-
-        Args:
-            module_name (str): The name of the module to import for command plugins.
-        """
-
-        module = importlib.import_module(module_name)
-
-        for attr_name in dir(module):
-            attr = getattr(module, attr_name)
-            # Register decorated functions
-            if hasattr(attr, AUTO_GPT_COMMAND_IDENTIFIER) and getattr(
-                attr, AUTO_GPT_COMMAND_IDENTIFIER
-            ):
-                self.register(attr.command)
-            # Register command classes
-            elif (
-                inspect.isclass(attr) and issubclass(attr, Command) and attr != Command
-            ):
-                cmd_instance = attr()
-                self.register(cmd_instance)
-
-
-def command(
-    name: str,
-    description: str,
-    signature: str = "",
-    enabled: bool = True,
-    disabled_reason: Optional[str] = None,
-) -> Callable[..., Any]:
-    """The command decorator is used to create Command objects from ordinary functions."""
-
-    def decorator(func: Callable[..., Any]) -> Command:
-        cmd = Command(
-            name=name,
-            description=description,
-            method=func,
-            signature=signature,
-            enabled=enabled,
-            disabled_reason=disabled_reason,
-        )
-
-        @functools.wraps(func)
-        def wrapper(*args, **kwargs) -> Any:
-            return func(*args, **kwargs)
-
-        wrapper.command = cmd
-
-        setattr(wrapper, AUTO_GPT_COMMAND_IDENTIFIER, True)
-
-        return wrapper
-
-    return decorator

autogpt/commands/execute_code.py

@@ -1,184 +0,0 @@
-"""Execute code in a Docker container"""
-import os
-import subprocess
-from pathlib import Path
-
-import docker
-from docker.errors import ImageNotFound
-
-from autogpt.commands.command import command
-from autogpt.config import Config
-from autogpt.logs import logger
-
-CFG = Config()
-
-
-@command("execute_python_file", "Execute Python File", '"filename": "<filename>"')
-def execute_python_file(filename: str) -> str:
-    """Execute a Python file in a Docker container and return the output
-
-    Args:
-        filename (str): The name of the file to execute
-
-    Returns:
-        str: The output of the file
-    """
-    logger.info(f"Executing file '{filename}'")
-
-    if not filename.endswith(".py"):
-        return "Error: Invalid file type. Only .py files are allowed."
-
-    if not os.path.isfile(filename):
-        return f"Error: File '{filename}' does not exist."
-
-    if we_are_running_in_a_docker_container():
-        result = subprocess.run(
-            f"python {filename}", capture_output=True, encoding="utf8", shell=True
-        )
-        if result.returncode == 0:
-            return result.stdout
-        else:
-            return f"Error: {result.stderr}"
-
-    try:
-        client = docker.from_env()
-        # You can replace this with the desired Python image/version
-        # You can find available Python images on Docker Hub:
-        # https://hub.docker.com/_/python
-        image_name = "python:3-alpine"
-        try:
-            client.images.get(image_name)
-            logger.warn(f"Image '{image_name}' found locally")
-        except ImageNotFound:
-            logger.info(
-                f"Image '{image_name}' not found locally, pulling from Docker Hub"
-            )
-            # Use the low-level API to stream the pull response
-            low_level_client = docker.APIClient()
-            for line in low_level_client.pull(image_name, stream=True, decode=True):
-                # Print the status and progress, if available
-                status = line.get("status")
-                progress = line.get("progress")
-                if status and progress:
-                    logger.info(f"{status}: {progress}")
-                elif status:
-                    logger.info(status)
-        container = client.containers.run(
-            image_name,
-            f"python {Path(filename).relative_to(CFG.workspace_path)}",
-            volumes={
-                CFG.workspace_path: {
-                    "bind": "/workspace",
-                    "mode": "ro",
-                }
-            },
-            working_dir="/workspace",
-            stderr=True,
-            stdout=True,
-            detach=True,
-        )
-
-        container.wait()
-        logs = container.logs().decode("utf-8")
-        container.remove()
-
-        # print(f"Execution complete. Output: {output}")
-        # print(f"Logs: {logs}")
-
-        return logs
-
-    except docker.errors.DockerException as e:
-        logger.warn(
-            "Could not run the script in a container. If you haven't already, please install Docker https://docs.docker.com/get-docker/"
-        )
-        return f"Error: {str(e)}"
-
-    except Exception as e:
-        return f"Error: {str(e)}"
-
-
-@command(
-    "execute_shell",
-    "Execute Shell Command, non-interactive commands only",
-    '"command_line": "<command_line>"',
-    CFG.execute_local_commands,
-    "You are not allowed to run local shell commands. To execute"
-    " shell commands, EXECUTE_LOCAL_COMMANDS must be set to 'True' "
-    "in your config. Do not attempt to bypass the restriction.",
-)
-def execute_shell(command_line: str) -> str:
-    """Execute a shell command and return the output
-
-    Args:
-        command_line (str): The command line to execute
-
-    Returns:
-        str: The output of the command
-    """
-
-    current_dir = Path.cwd()
-    # Change dir into workspace if necessary
-    if not current_dir.is_relative_to(CFG.workspace_path):
-        os.chdir(CFG.workspace_path)
-
-    logger.info(
-        f"Executing command '{command_line}' in working directory '{os.getcwd()}'"
-    )
-
-    result = subprocess.run(command_line, capture_output=True, shell=True)
-    output = f"STDOUT:\n{result.stdout}\nSTDERR:\n{result.stderr}"
-
-    # Change back to whatever the prior working dir was
-
-    os.chdir(current_dir)
-    return output
-
-
-@command(
-    "execute_shell_popen",
-    "Execute Shell Command, non-interactive commands only",
-    '"command_line": "<command_line>"',
-    CFG.execute_local_commands,
-    "You are not allowed to run local shell commands. To execute"
-    " shell commands, EXECUTE_LOCAL_COMMANDS must be set to 'True' "
-    "in your config. Do not attempt to bypass the restriction.",
-)
-def execute_shell_popen(command_line) -> str:
-    """Execute a shell command with Popen and returns an english description
-    of the event and the process id
-
-    Args:
-        command_line (str): The command line to execute
-
-    Returns:
-        str: Description of the fact that the process started and its id
-    """
-
-    current_dir = os.getcwd()
-    # Change dir into workspace if necessary
-    if CFG.workspace_path not in current_dir:
-        os.chdir(CFG.workspace_path)
-
-    logger.info(
-        f"Executing command '{command_line}' in working directory '{os.getcwd()}'"
-    )
-
-    do_not_show_output = subprocess.DEVNULL
-    process = subprocess.Popen(
-        command_line, shell=True, stdout=do_not_show_output, stderr=do_not_show_output
-    )
-
-    # Change back to whatever the prior working dir was
-
-    os.chdir(current_dir)
-
-    return f"Subprocess started with PID:'{str(process.pid)}'"
-
-
-def we_are_running_in_a_docker_container() -> bool:
-    """Check if we are running in a Docker container
-
-    Returns:
-        bool: True if we are running in a Docker container, False otherwise
-    """
-    return os.path.exists("/.dockerenv")

autogpt/commands/file_operations.py

@@ -1,272 +0,0 @@
-"""File operations for AutoGPT"""
-from __future__ import annotations
-
-import os
-import os.path
-from typing import Generator
-
-import requests
-from colorama import Back, Fore
-from requests.adapters import HTTPAdapter, Retry
-
-from autogpt.commands.command import command
-from autogpt.config import Config
-from autogpt.logs import logger
-from autogpt.spinner import Spinner
-from autogpt.utils import readable_file_size
-
-CFG = Config()
-
-
-def check_duplicate_operation(operation: str, filename: str) -> bool:
-    """Check if the operation has already been performed on the given file
-
-    Args:
-        operation (str): The operation to check for
-        filename (str): The name of the file to check for
-
-    Returns:
-        bool: True if the operation has already been performed on the file
-    """
-    log_content = read_file(CFG.file_logger_path)
-    log_entry = f"{operation}: {filename}\n"
-    return log_entry in log_content
-
-
-def log_operation(operation: str, filename: str) -> None:
-    """Log the file operation to the file_logger.txt
-
-    Args:
-        operation (str): The operation to log
-        filename (str): The name of the file the operation was performed on
-    """
-    log_entry = f"{operation}: {filename}\n"
-    append_to_file(CFG.file_logger_path, log_entry, should_log=False)
-
-
-def split_file(
-    content: str, max_length: int = 4000, overlap: int = 0
-) -> Generator[str, None, None]:
-    """
-    Split text into chunks of a specified maximum length with a specified overlap
-    between chunks.
-
-    :param content: The input text to be split into chunks
-    :param max_length: The maximum length of each chunk,
-        default is 4000 (about 1k token)
-    :param overlap: The number of overlapping characters between chunks,
-        default is no overlap
-    :return: A generator yielding chunks of text
-    """
-    start = 0
-    content_length = len(content)
-
-    while start < content_length:
-        end = start + max_length
-        if end + overlap < content_length:
-            chunk = content[start : end + overlap - 1]
-        else:
-            chunk = content[start:content_length]
-
-            # Account for the case where the last chunk is shorter than the overlap, so it has already been consumed
-            if len(chunk) <= overlap:
-                break
-
-        yield chunk
-        start += max_length - overlap
-
-
-@command("read_file", "Read file", '"filename": "<filename>"')
-def read_file(filename: str) -> str:
-    """Read a file and return the contents
-
-    Args:
-        filename (str): The name of the file to read
-
-    Returns:
-        str: The contents of the file
-    """
-    try:
-        with open(filename, "r", encoding="utf-8") as f:
-            content = f.read()
-        return content
-    except Exception as e:
-        return f"Error: {str(e)}"
-
-
-def ingest_file(
-    filename: str, memory, max_length: int = 4000, overlap: int = 200
-) -> None:
-    """
-    Ingest a file by reading its content, splitting it into chunks with a specified
-    maximum length and overlap, and adding the chunks to the memory storage.
-
-    :param filename: The name of the file to ingest
-    :param memory: An object with an add() method to store the chunks in memory
-    :param max_length: The maximum length of each chunk, default is 4000
-    :param overlap: The number of overlapping characters between chunks, default is 200
-    """
-    try:
-        logger.info(f"Working with file {filename}")
-        content = read_file(filename)
-        content_length = len(content)
-        logger.info(f"File length: {content_length} characters")
-
-        chunks = list(split_file(content, max_length=max_length, overlap=overlap))
-
-        num_chunks = len(chunks)
-        for i, chunk in enumerate(chunks):
-            logger.info(f"Ingesting chunk {i + 1} / {num_chunks} into memory")
-            memory_to_add = (
-                f"Filename: {filename}\n" f"Content part#{i + 1}/{num_chunks}: {chunk}"
-            )
-
-            memory.add(memory_to_add)
-
-        logger.info(f"Done ingesting {num_chunks} chunks from {filename}.")
-    except Exception as e:
-        logger.info(f"Error while ingesting file '{filename}': {str(e)}")
-
-
-@command("write_to_file", "Write to file", '"filename": "<filename>", "text": "<text>"')
-def write_to_file(filename: str, text: str) -> str:
-    """Write text to a file
-
-    Args:
-        filename (str): The name of the file to write to
-        text (str): The text to write to the file
-
-    Returns:
-        str: A message indicating success or failure
-    """
-    if check_duplicate_operation("write", filename):
-        return "Error: File has already been updated."
-    try:
-        directory = os.path.dirname(filename)
-        os.makedirs(directory, exist_ok=True)
-        with open(filename, "w", encoding="utf-8") as f:
-            f.write(text)
-        log_operation("write", filename)
-        return "File written to successfully."
-    except Exception as e:
-        return f"Error: {str(e)}"
-
-
-@command(
-    "append_to_file", "Append to file", '"filename": "<filename>", "text": "<text>"'
-)
-def append_to_file(filename: str, text: str, should_log: bool = True) -> str:
-    """Append text to a file
-
-    Args:
-        filename (str): The name of the file to append to
-        text (str): The text to append to the file
-        should_log (bool): Should log output
-
-    Returns:
-        str: A message indicating success or failure
-    """
-    try:
-        directory = os.path.dirname(filename)
-        os.makedirs(directory, exist_ok=True)
-        with open(filename, "a") as f:
-            f.write(text)
-
-        if should_log:
-            log_operation("append", filename)
-
-        return "Text appended successfully."
-    except Exception as e:
-        return f"Error: {str(e)}"
-
-
-@command("delete_file", "Delete file", '"filename": "<filename>"')
-def delete_file(filename: str) -> str:
-    """Delete a file
-
-    Args:
-        filename (str): The name of the file to delete
-
-    Returns:
-        str: A message indicating success or failure
-    """
-    if check_duplicate_operation("delete", filename):
-        return "Error: File has already been deleted."
-    try:
-        os.remove(filename)
-        log_operation("delete", filename)
-        return "File deleted successfully."
-    except Exception as e:
-        return f"Error: {str(e)}"
-
-
-@command("search_files", "Search Files", '"directory": "<directory>"')
-def search_files(directory: str) -> list[str]:
-    """Search for files in a directory
-
-    Args:
-        directory (str): The directory to search in
-
-    Returns:
-        list[str]: A list of files found in the directory
-    """
-    found_files = []
-
-    for root, _, files in os.walk(directory):
-        for file in files:
-            if file.startswith("."):
-                continue
-            relative_path = os.path.relpath(
-                os.path.join(root, file), CFG.workspace_path
-            )
-            found_files.append(relative_path)
-
-    return found_files
-
-
-@command(
-    "download_file",
-    "Download File",
-    '"url": "<url>", "filename": "<filename>"',
-    CFG.allow_downloads,
-    "Error: You do not have user authorization to download files locally.",
-)
-def download_file(url, filename):
-    """Downloads a file
-    Args:
-        url (str): URL of the file to download
-        filename (str): Filename to save the file as
-    """
-    try:
-        directory = os.path.dirname(filename)
-        os.makedirs(directory, exist_ok=True)
-        message = f"{Fore.YELLOW}Downloading file from {Back.LIGHTBLUE_EX}{url}{Back.RESET}{Fore.RESET}"
-        with Spinner(message) as spinner:
-            session = requests.Session()
-            retry = Retry(total=3, backoff_factor=1, status_forcelist=[502, 503, 504])
-            adapter = HTTPAdapter(max_retries=retry)
-            session.mount("http://", adapter)
-            session.mount("https://", adapter)
-
-            total_size = 0
-            downloaded_size = 0
-
-            with session.get(url, allow_redirects=True, stream=True) as r:
-                r.raise_for_status()
-                total_size = int(r.headers.get("Content-Length", 0))
-                downloaded_size = 0
-
-                with open(filename, "wb") as f:
-                    for chunk in r.iter_content(chunk_size=8192):
-                        f.write(chunk)
-                        downloaded_size += len(chunk)
-
-                        # Update the progress message
-                        progress = f"{readable_file_size(downloaded_size)} / {readable_file_size(total_size)}"
-                        spinner.update_message(f"{message} {progress}")
-
-            return f'Successfully downloaded and locally stored file: "{filename}"! (Size: {readable_file_size(downloaded_size)})'
-    except requests.HTTPError as e:
-        return f"Got an HTTP Error whilst trying to download file: {e}"
-    except Exception as e:
-        return "Error: " + str(e)

autogpt/commands/git_operations.py

@@ -1,35 +0,0 @@
-"""Git operations for autogpt"""
-from git.repo import Repo
-
-from autogpt.commands.command import command
-from autogpt.config import Config
-from autogpt.url_utils.validators import validate_url
-
-CFG = Config()
-
-
-@command(
-    "clone_repository",
-    "Clone Repository",
-    '"url": "<repository_url>", "clone_path": "<clone_path>"',
-    CFG.github_username and CFG.github_api_key,
-    "Configure github_username and github_api_key.",
-)
-@validate_url
-def clone_repository(url: str, clone_path: str) -> str:
-    """Clone a GitHub repository locally.
-
-    Args:
-        url (str): The URL of the repository to clone.
-        clone_path (str): The path to clone the repository to.
-
-    Returns:
-        str: The result of the clone operation.
-    """
-    split_url = url.split("//")
-    auth_repo_url = f"//{CFG.github_username}:{CFG.github_api_key}@".join(split_url)
-    try:
-        Repo.clone_from(url=auth_repo_url, to_path=clone_path)
-        return f"""Cloned {url} to {clone_path}"""
-    except Exception as e:
-        return f"Error: {str(e)}"

autogpt/commands/google_search.py

@@ -1,117 +0,0 @@
-"""Google search command for Autogpt."""
-from __future__ import annotations
-
-import json
-
-from duckduckgo_search import ddg
-
-from autogpt.commands.command import command
-from autogpt.config import Config
-
-CFG = Config()
-
-
-@command("google", "Google Search", '"query": "<query>"', not CFG.google_api_key)
-def google_search(query: str, num_results: int = 8) -> str:
-    """Return the results of a Google search
-
-    Args:
-        query (str): The search query.
-        num_results (int): The number of results to return.
-
-    Returns:
-        str: The results of the search.
-    """
-    search_results = []
-    if not query:
-        return json.dumps(search_results)
-
-    results = ddg(query, max_results=num_results)
-    if not results:
-        return json.dumps(search_results)
-
-    for j in results:
-        search_results.append(j)
-
-    results = json.dumps(search_results, ensure_ascii=False, indent=4)
-    return safe_google_results(results)
-
-
-@command(
-    "google",
-    "Google Search",
-    '"query": "<query>"',
-    bool(CFG.google_api_key),
-    "Configure google_api_key.",
-)
-def google_official_search(query: str, num_results: int = 8) -> str | list[str]:
-    """Return the results of a Google search using the official Google API
-
-    Args:
-        query (str): The search query.
-        num_results (int): The number of results to return.
-
-    Returns:
-        str: The results of the search.
-    """
-
-    from googleapiclient.discovery import build
-    from googleapiclient.errors import HttpError
-
-    try:
-        # Get the Google API key and Custom Search Engine ID from the config file
-        api_key = CFG.google_api_key
-        custom_search_engine_id = CFG.custom_search_engine_id
-
-        # Initialize the Custom Search API service
-        service = build("customsearch", "v1", developerKey=api_key)
-
-        # Send the search query and retrieve the results
-        result = (
-            service.cse()
-            .list(q=query, cx=custom_search_engine_id, num=num_results)
-            .execute()
-        )
-
-        # Extract the search result items from the response
-        search_results = result.get("items", [])
-
-        # Create a list of only the URLs from the search results
-        search_results_links = [item["link"] for item in search_results]
-
-    except HttpError as e:
-        # Handle errors in the API call
-        error_details = json.loads(e.content.decode())
-
-        # Check if the error is related to an invalid or missing API key
-        if error_details.get("error", {}).get(
-            "code"
-        ) == 403 and "invalid API key" in error_details.get("error", {}).get(
-            "message", ""
-        ):
-            return "Error: The provided Google API key is invalid or missing."
-        else:
-            return f"Error: {e}"
-    # google_result can be a list or a string depending on the search results
-
-    # Return the list of search result URLs
-    return safe_google_results(search_results_links)
-
-
-def safe_google_results(results: str | list) -> str:
-    """
-        Return the results of a google search in a safe format.
-
-    Args:
-        results (str | list): The search results.
-
-    Returns:
-        str: The results of the search.
-    """
-    if isinstance(results, list):
-        safe_message = json.dumps(
-            [result.encode("utf-8", "ignore") for result in results]
-        )
-    else:
-        safe_message = results.encode("utf-8", "ignore").decode("utf-8")
-    return safe_message

autogpt/commands/image_gen.py

@@ -1,165 +0,0 @@
-""" Image Generation Module for AutoGPT."""
-import io
-import uuid
-from base64 import b64decode
-
-import openai
-import requests
-from PIL import Image
-
-from autogpt.commands.command import command
-from autogpt.config import Config
-from autogpt.logs import logger
-
-CFG = Config()
-
-
-@command("generate_image", "Generate Image", '"prompt": "<prompt>"', CFG.image_provider)
-def generate_image(prompt: str, size: int = 256) -> str:
-    """Generate an image from a prompt.
-
-    Args:
-        prompt (str): The prompt to use
-        size (int, optional): The size of the image. Defaults to 256. (Not supported by HuggingFace)
-
-    Returns:
-        str: The filename of the image
-    """
-    filename = f"{CFG.workspace_path}/{str(uuid.uuid4())}.jpg"
-
-    # DALL-E
-    if CFG.image_provider == "dalle":
-        return generate_image_with_dalle(prompt, filename, size)
-    # HuggingFace
-    elif CFG.image_provider == "huggingface":
-        return generate_image_with_hf(prompt, filename)
-    # SD WebUI
-    elif CFG.image_provider == "sdwebui":
-        return generate_image_with_sd_webui(prompt, filename, size)
-    return "No Image Provider Set"
-
-
-def generate_image_with_hf(prompt: str, filename: str) -> str:
-    """Generate an image with HuggingFace's API.
-
-    Args:
-        prompt (str): The prompt to use
-        filename (str): The filename to save the image to
-
-    Returns:
-        str: The filename of the image
-    """
-    API_URL = (
-        f"https://api-inference.huggingface.co/models/{CFG.huggingface_image_model}"
-    )
-    if CFG.huggingface_api_token is None:
-        raise ValueError(
-            "You need to set your Hugging Face API token in the config file."
-        )
-    headers = {
-        "Authorization": f"Bearer {CFG.huggingface_api_token}",
-        "X-Use-Cache": "false",
-    }
-
-    response = requests.post(
-        API_URL,
-        headers=headers,
-        json={
-            "inputs": prompt,
-        },
-    )
-
-    image = Image.open(io.BytesIO(response.content))
-    logger.info(f"Image Generated for prompt:{prompt}")
-
-    image.save(filename)
-
-    return f"Saved to disk:{filename}"
-
-
-def generate_image_with_dalle(prompt: str, filename: str, size: int) -> str:
-    """Generate an image with DALL-E.
-
-    Args:
-        prompt (str): The prompt to use
-        filename (str): The filename to save the image to
-        size (int): The size of the image
-
-    Returns:
-        str: The filename of the image
-    """
-
-    # Check for supported image sizes
-    if size not in [256, 512, 1024]:
-        closest = min([256, 512, 1024], key=lambda x: abs(x - size))
-        logger.info(
-            f"DALL-E only supports image sizes of 256x256, 512x512, or 1024x1024. Setting to {closest}, was {size}."
-        )
-        size = closest
-
-    response = openai.Image.create(
-        prompt=prompt,
-        n=1,
-        size=f"{size}x{size}",
-        response_format="b64_json",
-        api_key=CFG.openai_api_key,
-    )
-
-    logger.info(f"Image Generated for prompt:{prompt}")
-
-    image_data = b64decode(response["data"][0]["b64_json"])
-
-    with open(filename, mode="wb") as png:
-        png.write(image_data)
-
-    return f"Saved to disk:{filename}"
-
-
-def generate_image_with_sd_webui(
-    prompt: str,
-    filename: str,
-    size: int = 512,
-    negative_prompt: str = "",
-    extra: dict = {},
-) -> str:
-    """Generate an image with Stable Diffusion webui.
-    Args:
-        prompt (str): The prompt to use
-        filename (str): The filename to save the image to
-        size (int, optional): The size of the image. Defaults to 256.
-        negative_prompt (str, optional): The negative prompt to use. Defaults to "".
-        extra (dict, optional): Extra parameters to pass to the API. Defaults to {}.
-    Returns:
-        str: The filename of the image
-    """
-    # Create a session and set the basic auth if needed
-    s = requests.Session()
-    if CFG.sd_webui_auth:
-        username, password = CFG.sd_webui_auth.split(":")
-        s.auth = (username, password or "")
-
-    # Generate the images
-    response = requests.post(
-        f"{CFG.sd_webui_url}/sdapi/v1/txt2img",
-        json={
-            "prompt": prompt,
-            "negative_prompt": negative_prompt,
-            "sampler_index": "DDIM",
-            "steps": 20,
-            "cfg_scale": 7.0,
-            "width": size,
-            "height": size,
-            "n_iter": 1,
-            **extra,
-        },
-    )
-
-    logger.info(f"Image Generated for prompt:{prompt}")
-
-    # Save the image to disk
-    response = response.json()
-    b64 = b64decode(response["images"][0].split(",", 1)[0])
-    image = Image.open(io.BytesIO(b64))
-    image.save(filename)
-
-    return f"Saved to disk:{filename}"

autogpt/commands/improve_code.py

@@ -1,35 +0,0 @@
-from __future__ import annotations
-
-import json
-
-from autogpt.commands.command import command
-from autogpt.llm import call_ai_function
-
-
-@command(
-    "improve_code",
-    "Get Improved Code",
-    '"suggestions": "<list_of_suggestions>", "code": "<full_code_string>"',
-)
-def improve_code(suggestions: list[str], code: str) -> str:
-    """
-    A function that takes in code and suggestions and returns a response from create
-      chat completion api call.
-
-    Parameters:
-        suggestions (list): A list of suggestions around what needs to be improved.
-        code (str): Code to be improved.
-    Returns:
-        A result string from create chat completion. Improved code in response.
-    """
-
-    function_string = (
-        "def generate_improved_code(suggestions: list[str], code: str) -> str:"
-    )
-    args = [json.dumps(suggestions), code]
-    description_string = (
-        "Improves the provided code based on the suggestions"
-        " provided, making no other changes."
-    )
-
-    return call_ai_function(function_string, args, description_string)

autogpt/commands/times.py

@@ -1,10 +0,0 @@
-from datetime import datetime
-
-
-def get_datetime() -> str:
-    """Return the current date and time
-
-    Returns:
-        str: The current date and time
-    """
-    return "Current date and time: " + datetime.now().strftime("%Y-%m-%d %H:%M:%S")

autogpt/commands/twitter.py

@@ -1,41 +0,0 @@
-"""A module that contains a command to send a tweet."""
-import os
-
-import tweepy
-
-from autogpt.commands.command import command
-
-
-@command(
-    "send_tweet",
-    "Send Tweet",
-    '"tweet_text": "<tweet_text>"',
-)
-def send_tweet(tweet_text: str) -> str:
-    """
-      A function that takes in a string and returns a response from create chat
-        completion api call.
-
-    Args:
-      tweet_text (str): Text to be tweeted.
-
-      Returns:
-          A result from sending the tweet.
-    """
-    consumer_key = os.environ.get("TW_CONSUMER_KEY")
-    consumer_secret = os.environ.get("TW_CONSUMER_SECRET")
-    access_token = os.environ.get("TW_ACCESS_TOKEN")
-    access_token_secret = os.environ.get("TW_ACCESS_TOKEN_SECRET")
-    # Authenticate to Twitter
-    auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
-    auth.set_access_token(access_token, access_token_secret)
-
-    # Create API object
-    api = tweepy.API(auth)
-
-    # Send tweet
-    try:
-        api.update_status(tweet_text)
-        return "Tweet sent successfully!"
-    except tweepy.TweepyException as e:
-        return f"Error sending tweet: {e.reason}"

autogpt/commands/web_playwright.py

@@ -1,82 +0,0 @@
-"""Web scraping commands using Playwright"""
-from __future__ import annotations
-
-from autogpt.logs import logger
-
-try:
-    from playwright.sync_api import sync_playwright
-except ImportError:
-    logger.info(
-        "Playwright not installed. Please install it with 'pip install playwright' to use."
-    )
-from bs4 import BeautifulSoup
-
-from autogpt.processing.html import extract_hyperlinks, format_hyperlinks
-
-
-def scrape_text(url: str) -> str:
-    """Scrape text from a webpage
-
-    Args:
-        url (str): The URL to scrape text from
-
-    Returns:
-        str: The scraped text
-    """
-    with sync_playwright() as p:
-        browser = p.chromium.launch()
-        page = browser.new_page()
-
-        try:
-            page.goto(url)
-            html_content = page.content()
-            soup = BeautifulSoup(html_content, "html.parser")
-
-            for script in soup(["script", "style"]):
-                script.extract()
-
-            text = soup.get_text()
-            lines = (line.strip() for line in text.splitlines())
-            chunks = (phrase.strip() for line in lines for phrase in line.split("  "))
-            text = "\n".join(chunk for chunk in chunks if chunk)
-
-        except Exception as e:
-            text = f"Error: {str(e)}"
-
-        finally:
-            browser.close()
-
-    return text
-
-
-def scrape_links(url: str) -> str | list[str]:
-    """Scrape links from a webpage
-
-    Args:
-        url (str): The URL to scrape links from
-
-    Returns:
-        Union[str, List[str]]: The scraped links
-    """
-    with sync_playwright() as p:
-        browser = p.chromium.launch()
-        page = browser.new_page()
-
-        try:
-            page.goto(url)
-            html_content = page.content()
-            soup = BeautifulSoup(html_content, "html.parser")
-
-            for script in soup(["script", "style"]):
-                script.extract()
-
-            hyperlinks = extract_hyperlinks(soup, url)
-            formatted_links = format_hyperlinks(hyperlinks)
-
-        except Exception as e:
-            formatted_links = f"Error: {str(e)}"
-
-        finally:
-            browser.close()
-
-    return formatted_links

autogpt/commands/web_requests.py

@@ -1,112 +0,0 @@
-"""Browse a webpage and summarize it using the LLM model"""
-from __future__ import annotations
-
-import requests
-from bs4 import BeautifulSoup
-from requests import Response
-
-from autogpt.config import Config
-from autogpt.processing.html import extract_hyperlinks, format_hyperlinks
-from autogpt.url_utils.validators import validate_url
-
-CFG = Config()
-
-session = requests.Session()
-session.headers.update({"User-Agent": CFG.user_agent})
-
-
-@validate_url
-def get_response(
-    url: str, timeout: int = 10
-) -> tuple[None, str] | tuple[Response, None]:
-    """Get the response from a URL
-
-    Args:
-        url (str): The URL to get the response from
-        timeout (int): The timeout for the HTTP request
-
-    Returns:
-        tuple[None, str] | tuple[Response, None]: The response and error message
-
-    Raises:
-        ValueError: If the URL is invalid
-        requests.exceptions.RequestException: If the HTTP request fails
-    """
-    try:
-        response = session.get(url, timeout=timeout)
-
-        # Check if the response contains an HTTP error
-        if response.status_code >= 400:
-            return None, f"Error: HTTP {str(response.status_code)} error"
-
-        return response, None
-    except ValueError as ve:
-        # Handle invalid URL format
-        return None, f"Error: {str(ve)}"
-
-    except requests.exceptions.RequestException as re:
-        # Handle exceptions related to the HTTP request
-        #  (e.g., connection errors, timeouts, etc.)
-        return None, f"Error: {str(re)}"
-
-
-def scrape_text(url: str) -> str:
-    """Scrape text from a webpage
-
-    Args:
-        url (str): The URL to scrape text from
-
-    Returns:
-        str: The scraped text
-    """
-    response, error_message = get_response(url)
-    if error_message:
-        return error_message
-    if not response:
-        return "Error: Could not get response"
-
-    soup = BeautifulSoup(response.text, "html.parser")
-
-    for script in soup(["script", "style"]):
-        script.extract()
-
-    text = soup.get_text()
-    lines = (line.strip() for line in text.splitlines())
-    chunks = (phrase.strip() for line in lines for phrase in line.split("  "))
-    text = "\n".join(chunk for chunk in chunks if chunk)
-
-    return text
-
-
-def scrape_links(url: str) -> str | list[str]:
-    """Scrape links from a webpage
-
-    Args:
-        url (str): The URL to scrape links from
-
-    Returns:
-       str | list[str]: The scraped links
-    """
-    response, error_message = get_response(url)
-    if error_message:
-        return error_message
-    if not response:
-        return "Error: Could not get response"
-    soup = BeautifulSoup(response.text, "html.parser")
-
-    for script in soup(["script", "style"]):
-        script.extract()
-
-    hyperlinks = extract_hyperlinks(soup, url)
-
-    return format_hyperlinks(hyperlinks)
-
-
-def create_message(chunk, question):
-    """Create a message for the user to summarize a chunk of text"""
-    return {
-        "role": "user",
-        "content": f'"""{chunk}""" Using the above text, answer the following'
-        f' question: "{question}" -- if the question cannot be answered using the'
-        " text, summarize the text.",
-    }

autogpt/commands/web_selenium.py

@@ -1,178 +0,0 @@
-"""Selenium web scraping module."""
-from __future__ import annotations
-
-import logging
-from pathlib import Path
-from sys import platform
-
-from bs4 import BeautifulSoup
-from selenium import webdriver
-from selenium.common.exceptions import WebDriverException
-from selenium.webdriver.chrome.options import Options as ChromeOptions
-from selenium.webdriver.common.by import By
-from selenium.webdriver.firefox.options import Options as FirefoxOptions
-from selenium.webdriver.remote.webdriver import WebDriver
-from selenium.webdriver.safari.options import Options as SafariOptions
-from selenium.webdriver.support import expected_conditions as EC
-from selenium.webdriver.support.wait import WebDriverWait
-from webdriver_manager.chrome import ChromeDriverManager
-from webdriver_manager.firefox import GeckoDriverManager
-
-import autogpt.processing.text as summary
-from autogpt.commands.command import command
-from autogpt.config import Config
-from autogpt.processing.html import extract_hyperlinks, format_hyperlinks
-from autogpt.url_utils.validators import validate_url
-
-FILE_DIR = Path(__file__).parent.parent
-CFG = Config()
-
-
-@command(
-    "browse_website",
-    "Browse Website",
-    '"url": "<url>", "question": "<what_you_want_to_find_on_website>"',
-)
-@validate_url
-def browse_website(url: str, question: str) -> tuple[str, WebDriver]:
-    """Browse a website and return the answer and links to the user
-
-    Args:
-        url (str): The url of the website to browse
-        question (str): The question asked by the user
-
-    Returns:
-        Tuple[str, WebDriver]: The answer and links to the user and the webdriver
-    """
-    try:
-        driver, text = scrape_text_with_selenium(url)
-    except WebDriverException as e:
-        # These errors are often quite long and include lots of context.
-        # Just grab the first line.
-        msg = e.msg.split("\n")[0]
-        return f"Error: {msg}", None
-
-    add_header(driver)
-    summary_text = summary.summarize_text(url, text, question, driver)
-    links = scrape_links_with_selenium(driver, url)
-
-    # Limit links to 5
-    if len(links) > 5:
-        links = links[:5]
-    close_browser(driver)
-    return f"Answer gathered from website: {summary_text} \n \n Links: {links}", driver
-
-
-def scrape_text_with_selenium(url: str) -> tuple[WebDriver, str]:
-    """Scrape text from a website using selenium
-
-    Args:
-        url (str): The url of the website to scrape
-
-    Returns:
-        Tuple[WebDriver, str]: The webdriver and the text scraped from the website
-    """
-    logging.getLogger("selenium").setLevel(logging.CRITICAL)
-
-    options_available = {
-        "chrome": ChromeOptions,
-        "safari": SafariOptions,
-        "firefox": FirefoxOptions,
-    }
-
-    options = options_available[CFG.selenium_web_browser]()
-    options.add_argument(
-        "user-agent=Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/112.0.5615.49 Safari/537.36"
-    )
-
-    if CFG.selenium_web_browser == "firefox":
-        if CFG.selenium_headless:
-            options.headless = True
-            options.add_argument("--disable-gpu")
-        driver = webdriver.Firefox(
-            executable_path=GeckoDriverManager().install(), options=options
-        )
-    elif CFG.selenium_web_browser == "safari":
-        # Requires a bit more setup on the users end
-        # See https://developer.apple.com/documentation/webkit/testing_with_webdriver_in_safari
-        driver = webdriver.Safari(options=options)
-    else:
-        if platform == "linux" or platform == "linux2":
-            options.add_argument("--disable-dev-shm-usage")
-            options.add_argument("--remote-debugging-port=9222")
-
-        options.add_argument("--no-sandbox")
-        if CFG.selenium_headless:
-            options.add_argument("--headless=new")
-            options.add_argument("--disable-gpu")
-
-        chromium_driver_path = Path("/usr/bin/chromedriver")
-
-        driver = webdriver.Chrome(
-            executable_path=chromium_driver_path
-            if chromium_driver_path.exists()
-            else ChromeDriverManager().install(),
-            options=options,
-        )
-    driver.get(url)
-
-    WebDriverWait(driver, 10).until(
-        EC.presence_of_element_located((By.TAG_NAME, "body"))
-    )
-
-    # Get the HTML content directly from the browser's DOM
-    page_source = driver.execute_script("return document.body.outerHTML;")
-    soup = BeautifulSoup(page_source, "html.parser")
-
-    for script in soup(["script", "style"]):
-        script.extract()
-
-    text = soup.get_text()
-    lines = (line.strip() for line in text.splitlines())
-    chunks = (phrase.strip() for line in lines for phrase in line.split("  "))
-    text = "\n".join(chunk for chunk in chunks if chunk)
-    return driver, text
-
-
-def scrape_links_with_selenium(driver: WebDriver, url: str) -> list[str]:
-    """Scrape links from a website using selenium
-
-    Args:
-        driver (WebDriver): The webdriver to use to scrape the links
-
-    Returns:
-        List[str]: The links scraped from the website
-    """
-    page_source = driver.page_source
-    soup = BeautifulSoup(page_source, "html.parser")
-
-    for script in soup(["script", "style"]):
-        script.extract()
-
-    hyperlinks = extract_hyperlinks(soup, url)
-
-    return format_hyperlinks(hyperlinks)
-
-
-def close_browser(driver: WebDriver) -> None:
-    """Close the browser
-
-    Args:
-        driver (WebDriver): The webdriver to close
-
-    Returns:
-        None
-    """
-    driver.quit()
-
-
-def add_header(driver: WebDriver) -> None:
-    """Add a header to the website
-
-    Args:
-        driver (WebDriver): The webdriver to use to add the header
-
-    Returns:
-        None
-    """
-    driver.execute_script(open(f"{FILE_DIR}/js/overlay.js", "r").read())

autogpt/commands/write_tests.py

@@ -1,37 +0,0 @@
-"""A module that contains a function to generate test cases for the submitted code."""
-from __future__ import annotations
-
-import json
-
-from autogpt.commands.command import command
-from autogpt.llm import call_ai_function
-
-
-@command(
-    "write_tests",
-    "Write Tests",
-    '"code": "<full_code_string>", "focus": "<list_of_focus_areas>"',
-)
-def write_tests(code: str, focus: list[str]) -> str:
-    """
-    A function that takes in code and focus topics and returns a response from create
-      chat completion api call.
-
-    Parameters:
-        focus (list): A list of suggestions around what needs to be improved.
-        code (str): Code for test cases to be generated against.
-    Returns:
-        A result string from create chat completion. Test cases for the submitted code
-          in response.
-    """
-
-    function_string = (
-        "def create_test_cases(code: str, focus: Optional[str] = None) -> str:"
-    )
-    args = [code, json.dumps(focus)]
-    description_string = (
-        "Generates test cases for the existing code, focusing on"
-        " specific areas if required."
-    )
-
-    return call_ai_function(function_string, args, description_string)

autogpt/config/__init__.py

@@ -1,11 +0,0 @@
-"""
-This module contains the configuration classes for AutoGPT.
-"""
-from autogpt.config.ai_config import AIConfig
-from autogpt.config.config import Config, check_openai_api_key
-
-__all__ = [
-    "check_openai_api_key",
-    "AIConfig",
-    "Config",
-]

autogpt/config/ai_config.py

@@ -1,168 +0,0 @@
-# sourcery skip: do-not-use-staticmethod
-"""
-A module that contains the AIConfig class object that contains the configuration
-"""
-from __future__ import annotations
-
-import os
-import platform
-from pathlib import Path
-from typing import Any, Optional, Type
-
-import distro
-import yaml
-
-from autogpt.prompts.generator import PromptGenerator
-
-# Soon this will go in a folder where it remembers more stuff about the run(s)
-SAVE_FILE = str(Path(os.getcwd()) / "ai_settings.yaml")
-
-
-class AIConfig:
-    """
-    A class object that contains the configuration information for the AI
-
-    Attributes:
-        ai_name (str): The name of the AI.
-        ai_role (str): The description of the AI's role.
-        ai_goals (list): The list of objectives the AI is supposed to complete.
-        api_budget (float): The maximum dollar value for API calls (0.0 means infinite)
-    """
-
-    def __init__(
-        self,
-        ai_name: str = "",
-        ai_role: str = "",
-        ai_goals: list | None = None,
-        api_budget: float = 0.0,
-    ) -> None:
-        """
-        Initialize a class instance
-
-        Parameters:
-            ai_name (str): The name of the AI.
-            ai_role (str): The description of the AI's role.
-            ai_goals (list): The list of objectives the AI is supposed to complete.
-            api_budget (float): The maximum dollar value for API calls (0.0 means infinite)
-        Returns:
-            None
-        """
-        if ai_goals is None:
-            ai_goals = []
-        self.ai_name = ai_name
-        self.ai_role = ai_role
-        self.ai_goals = ai_goals
-        self.api_budget = api_budget
-        self.prompt_generator = None
-        self.command_registry = None
-
-    @staticmethod
-    def load(config_file: str = SAVE_FILE) -> "AIConfig":
-        """
-        Returns class object with parameters (ai_name, ai_role, ai_goals, api_budget) loaded from
-          yaml file if yaml file exists,
-        else returns class with no parameters.
-
-        Parameters:
-           config_file (int): The path to the config yaml file.
-             DEFAULT: "../ai_settings.yaml"
-
-        Returns:
-            cls (object): An instance of given cls object
-        """
-
-        try:
-            with open(config_file, encoding="utf-8") as file:
-                config_params = yaml.load(file, Loader=yaml.FullLoader)
-        except FileNotFoundError:
-            config_params = {}
-
-        ai_name = config_params.get("ai_name", "")
-        ai_role = config_params.get("ai_role", "")
-        ai_goals = [
-            str(goal).strip("{}").replace("'", "").replace('"', "")
-            if isinstance(goal, dict)
-            else str(goal)
-            for goal in config_params.get("ai_goals", [])
-        ]
-        api_budget = config_params.get("api_budget", 0.0)
-        # type: Type[AIConfig]
-        return AIConfig(ai_name, ai_role, ai_goals, api_budget)
-
-    def save(self, config_file: str = SAVE_FILE) -> None:
-        """
-        Saves the class parameters to the specified file yaml file path as a yaml file.
-
-        Parameters:
-            config_file(str): The path to the config yaml file.
-              DEFAULT: "../ai_settings.yaml"
-
-        Returns:
-            None
-        """
-
-        config = {
-            "ai_name": self.ai_name,
-            "ai_role": self.ai_role,
-            "ai_goals": self.ai_goals,
-            "api_budget": self.api_budget,
-        }
-        with open(config_file, "w", encoding="utf-8") as file:
-            yaml.dump(config, file, allow_unicode=True)
-
-    def construct_full_prompt(
-        self, prompt_generator: Optional[PromptGenerator] = None
-    ) -> str:
-        """
-        Returns a prompt to the user with the class information in an organized fashion.
-
-        Parameters:
-            None
-
-        Returns:
-            full_prompt (str): A string containing the initial prompt for the user
-              including the ai_name, ai_role, ai_goals, and api_budget.
-        """
-
-        prompt_start = (
-            "Your decisions must always be made independently without"
-            " seeking user assistance. Play to your strengths as an LLM and pursue"
-            " simple strategies with no legal complications."
-            ""
-        )
-
-        from autogpt.config import Config
-        from autogpt.prompts.prompt import build_default_prompt_generator
-
-        cfg = Config()
-        if prompt_generator is None:
-            prompt_generator = build_default_prompt_generator()
-        prompt_generator.goals = self.ai_goals
-        prompt_generator.name = self.ai_name
-        prompt_generator.role = self.ai_role
-        prompt_generator.command_registry = self.command_registry
-        for plugin in cfg.plugins:
-            if not plugin.can_handle_post_prompt():
-                continue
-            prompt_generator = plugin.post_prompt(prompt_generator)
-
-        if cfg.execute_local_commands:
-            # add OS info to prompt
-            os_name = platform.system()
-            os_info = (
-                platform.platform(terse=True)
-                if os_name != "Linux"
-                else distro.name(pretty=True)
-            )
-
-            prompt_start += f"\nThe OS you are running on is: {os_info}"
-
-        # Construct full prompt
-        full_prompt = f"You are {prompt_generator.name}, {prompt_generator.role}\n{prompt_start}\n\nGOALS:\n\n"
-        for i, goal in enumerate(self.ai_goals):
-            full_prompt += f"{i+1}. {goal}\n"
-        if self.api_budget > 0.0:
-            full_prompt += f"\nIt takes money to let you run. Your API budget is ${self.api_budget:.3f}"
-        self.prompt_generator = prompt_generator
-        full_prompt += f"\n\n{prompt_generator.generate_prompt_string()}"
-        return full_prompt

autogpt/config/config.py

@@ -1,282 +0,0 @@
-"""Configuration class to store the state of bools for different scripts access."""
-import os
-from typing import List
-
-import openai
-import yaml
-from auto_gpt_plugin_template import AutoGPTPluginTemplate
-from colorama import Fore
-
-from autogpt.singleton import Singleton
-
-
-class Config(metaclass=Singleton):
-    """
-    Configuration class to store the state of bools for different scripts access.
-    """
-
-    def __init__(self) -> None:
-        """Initialize the Config class"""
-        self.workspace_path = None
-        self.file_logger_path = None
-
-        self.debug_mode = False
-        self.continuous_mode = False
-        self.continuous_limit = 0
-        self.speak_mode = False
-        self.skip_reprompt = False
-        self.allow_downloads = False
-        self.skip_news = False
-
-        self.authorise_key = os.getenv("AUTHORISE_COMMAND_KEY", "y")
-        self.exit_key = os.getenv("EXIT_KEY", "n")
-        self.ai_settings_file = os.getenv("AI_SETTINGS_FILE", "ai_settings.yaml")
-        self.fast_llm_model = os.getenv("FAST_LLM_MODEL", "gpt-3.5-turbo")
-        self.smart_llm_model = os.getenv("SMART_LLM_MODEL", "gpt-4")
-        self.fast_token_limit = int(os.getenv("FAST_TOKEN_LIMIT", 4000))
-        self.smart_token_limit = int(os.getenv("SMART_TOKEN_LIMIT", 8000))
-        self.browse_chunk_max_length = int(os.getenv("BROWSE_CHUNK_MAX_LENGTH", 3000))
-        self.browse_spacy_language_model = os.getenv(
-            "BROWSE_SPACY_LANGUAGE_MODEL", "en_core_web_sm"
-        )
-
-        self.openai_api_key = os.getenv("OPENAI_API_KEY")
-        self.temperature = float(os.getenv("TEMPERATURE", "0"))
-        self.use_azure = os.getenv("USE_AZURE") == "True"
-        self.execute_local_commands = (
-            os.getenv("EXECUTE_LOCAL_COMMANDS", "False") == "True"
-        )
-        self.restrict_to_workspace = (
-            os.getenv("RESTRICT_TO_WORKSPACE", "True") == "True"
-        )
-
-        if self.use_azure:
-            self.load_azure_config()
-            openai.api_type = self.openai_api_type
-            openai.api_base = self.openai_api_base
-            openai.api_version = self.openai_api_version
-
-        self.elevenlabs_api_key = os.getenv("ELEVENLABS_API_KEY")
-        self.elevenlabs_voice_1_id = os.getenv("ELEVENLABS_VOICE_1_ID")
-        self.elevenlabs_voice_2_id = os.getenv("ELEVENLABS_VOICE_2_ID")
-
-        self.use_mac_os_tts = False
-        self.use_mac_os_tts = os.getenv("USE_MAC_OS_TTS")
-
-        self.chat_messages_enabled = os.getenv("CHAT_MESSAGES_ENABLED") == "True"
-
-        self.use_brian_tts = False
-        self.use_brian_tts = os.getenv("USE_BRIAN_TTS")
-
-        self.github_api_key = os.getenv("GITHUB_API_KEY")
-        self.github_username = os.getenv("GITHUB_USERNAME")
-
-        self.google_api_key = os.getenv("GOOGLE_API_KEY")
-        self.custom_search_engine_id = os.getenv("CUSTOM_SEARCH_ENGINE_ID")
-
-        self.pinecone_api_key = os.getenv("PINECONE_API_KEY")
-        self.pinecone_region = os.getenv("PINECONE_ENV")
-
-        self.weaviate_host = os.getenv("WEAVIATE_HOST")
-        self.weaviate_port = os.getenv("WEAVIATE_PORT")
-        self.weaviate_protocol = os.getenv("WEAVIATE_PROTOCOL", "http")
-        self.weaviate_username = os.getenv("WEAVIATE_USERNAME", None)
-        self.weaviate_password = os.getenv("WEAVIATE_PASSWORD", None)
-        self.weaviate_scopes = os.getenv("WEAVIATE_SCOPES", None)
-        self.weaviate_embedded_path = os.getenv("WEAVIATE_EMBEDDED_PATH")
-        self.weaviate_api_key = os.getenv("WEAVIATE_API_KEY", None)
-        self.use_weaviate_embedded = (
-            os.getenv("USE_WEAVIATE_EMBEDDED", "False") == "True"
-        )
-
-        # milvus or zilliz cloud configuration.
-        self.milvus_addr = os.getenv("MILVUS_ADDR", "localhost:19530")
-        self.milvus_username = os.getenv("MILVUS_USERNAME")
-        self.milvus_password = os.getenv("MILVUS_PASSWORD")
-        self.milvus_collection = os.getenv("MILVUS_COLLECTION", "autogpt")
-        self.milvus_secure = os.getenv("MILVUS_SECURE") == "True"
-
-        self.image_provider = os.getenv("IMAGE_PROVIDER")
-        self.image_size = int(os.getenv("IMAGE_SIZE", 256))
-        self.huggingface_api_token = os.getenv("HUGGINGFACE_API_TOKEN")
-        self.huggingface_image_model = os.getenv(
-            "HUGGINGFACE_IMAGE_MODEL", "CompVis/stable-diffusion-v1-4"
-        )
-        self.huggingface_audio_to_text_model = os.getenv(
-            "HUGGINGFACE_AUDIO_TO_TEXT_MODEL"
-        )
-        self.sd_webui_url = os.getenv("SD_WEBUI_URL", "http://localhost:7860")
-        self.sd_webui_auth = os.getenv("SD_WEBUI_AUTH")
-
-        # Selenium browser settings
-        self.selenium_web_browser = os.getenv("USE_WEB_BROWSER", "chrome")
-        self.selenium_headless = os.getenv("HEADLESS_BROWSER", "True") == "True"
-
-        # User agent header to use when making HTTP requests
-        # Some websites might just completely deny request with an error code if
-        # no user agent was found.
-        self.user_agent = os.getenv(
-            "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",
-        )
-
-        self.redis_host = os.getenv("REDIS_HOST", "localhost")
-        self.redis_port = os.getenv("REDIS_PORT", "6379")
-        self.redis_password = os.getenv("REDIS_PASSWORD", "")
-        self.wipe_redis_on_start = os.getenv("WIPE_REDIS_ON_START", "True") == "True"
-        self.memory_index = os.getenv("MEMORY_INDEX", "auto-gpt")
-        # Note that indexes must be created on db 0 in redis, this is not configurable.
-
-        self.memory_backend = os.getenv("MEMORY_BACKEND", "local")
-
-        self.plugins_dir = os.getenv("PLUGINS_DIR", "plugins")
-        self.plugins: List[AutoGPTPluginTemplate] = []
-        self.plugins_openai = []
-
-        plugins_allowlist = os.getenv("ALLOWLISTED_PLUGINS")
-        if plugins_allowlist:
-            self.plugins_allowlist = plugins_allowlist.split(",")
-        else:
-            self.plugins_allowlist = []
-        self.plugins_denylist = []
-
-    def get_azure_deployment_id_for_model(self, model: str) -> str:
-        """
-        Returns the relevant deployment id for the model specified.
-
-        Parameters:
-            model(str): The model to map to the deployment id.
-
-        Returns:
-            The matching deployment id if found, otherwise an empty string.
-        """
-        if model == self.fast_llm_model:
-            return self.azure_model_to_deployment_id_map[
-                "fast_llm_model_deployment_id"
-            ]  # type: ignore
-        elif model == self.smart_llm_model:
-            return self.azure_model_to_deployment_id_map[
-                "smart_llm_model_deployment_id"
-            ]  # type: ignore
-        elif model == "text-embedding-ada-002":
-            return self.azure_model_to_deployment_id_map[
-                "embedding_model_deployment_id"
-            ]  # type: ignore
-        else:
-            return ""
-
-    AZURE_CONFIG_FILE = os.path.join(os.path.dirname(__file__), "../..", "azure.yaml")
-
-    def load_azure_config(self, config_file: str = AZURE_CONFIG_FILE) -> None:
-        """
-        Loads the configuration parameters for Azure hosting from the specified file
-          path as a yaml file.
-
-        Parameters:
-            config_file(str): The path to the config yaml file. DEFAULT: "../azure.yaml"
-
-        Returns:
-            None
-        """
-        with open(config_file) as file:
-            config_params = yaml.load(file, Loader=yaml.FullLoader)
-        self.openai_api_type = config_params.get("azure_api_type") or "azure"
-        self.openai_api_base = config_params.get("azure_api_base") or ""
-        self.openai_api_version = (
-            config_params.get("azure_api_version") or "2023-03-15-preview"
-        )
-        self.azure_model_to_deployment_id_map = config_params.get("azure_model_map", {})
-
-    def set_continuous_mode(self, value: bool) -> None:
-        """Set the continuous mode value."""
-        self.continuous_mode = value
-
-    def set_continuous_limit(self, value: int) -> None:
-        """Set the continuous limit value."""
-        self.continuous_limit = value
-
-    def set_speak_mode(self, value: bool) -> None:
-        """Set the speak mode value."""
-        self.speak_mode = value
-
-    def set_fast_llm_model(self, value: str) -> None:
-        """Set the fast LLM model value."""
-        self.fast_llm_model = value
-
-    def set_smart_llm_model(self, value: str) -> None:
-        """Set the smart LLM model value."""
-        self.smart_llm_model = value
-
-    def set_fast_token_limit(self, value: int) -> None:
-        """Set the fast token limit value."""
-        self.fast_token_limit = value
-
-    def set_smart_token_limit(self, value: int) -> None:
-        """Set the smart token limit value."""
-        self.smart_token_limit = value
-
-    def set_browse_chunk_max_length(self, value: int) -> None:
-        """Set the browse_website command chunk max length value."""
-        self.browse_chunk_max_length = value
-
-    def set_openai_api_key(self, value: str) -> None:
-        """Set the OpenAI API key value."""
-        self.openai_api_key = value
-
-    def set_elevenlabs_api_key(self, value: str) -> None:
-        """Set the ElevenLabs API key value."""
-        self.elevenlabs_api_key = value
-
-    def set_elevenlabs_voice_1_id(self, value: str) -> None:
-        """Set the ElevenLabs Voice 1 ID value."""
-        self.elevenlabs_voice_1_id = value
-
-    def set_elevenlabs_voice_2_id(self, value: str) -> None:
-        """Set the ElevenLabs Voice 2 ID value."""
-        self.elevenlabs_voice_2_id = value
-
-    def set_google_api_key(self, value: str) -> None:
-        """Set the Google API key value."""
-        self.google_api_key = value
-
-    def set_custom_search_engine_id(self, value: str) -> None:
-        """Set the custom search engine id value."""
-        self.custom_search_engine_id = value
-
-    def set_pinecone_api_key(self, value: str) -> None:
-        """Set the Pinecone API key value."""
-        self.pinecone_api_key = value
-
-    def set_pinecone_region(self, value: str) -> None:
-        """Set the Pinecone region value."""
-        self.pinecone_region = value
-
-    def set_debug_mode(self, value: bool) -> None:
-        """Set the debug mode value."""
-        self.debug_mode = value
-
-    def set_plugins(self, value: list) -> None:
-        """Set the plugins value."""
-        self.plugins = value
-
-    def set_temperature(self, value: int) -> None:
-        """Set the temperature value."""
-        self.temperature = value
-
-    def set_memory_backend(self, name: str) -> None:
-        """Set the memory backend name."""
-        self.memory_backend = name
-
-
-def check_openai_api_key() -> None:
-    """Check if the OpenAI API key is set in config.py or as an environment variable."""
-    cfg = Config()
-    if not cfg.openai_api_key:
-        print(
-            Fore.RED
-            + "Please set your OpenAI API key in .env or as an environment variable."
-            + Fore.RESET
-        )
-        print("You can get your key from https://platform.openai.com/account/api-keys")
-        exit(1)

autogpt/configurator.py

@@ -1,134 +0,0 @@
-"""Configurator module."""
-import click
-from colorama import Back, Fore, Style
-
-from autogpt import utils
-from autogpt.config import Config
-from autogpt.logs import logger
-from autogpt.memory import get_supported_memory_backends
-
-CFG = Config()
-
-
-def create_config(
-    continuous: bool,
-    continuous_limit: int,
-    ai_settings_file: str,
-    skip_reprompt: bool,
-    speak: bool,
-    debug: bool,
-    gpt3only: bool,
-    gpt4only: bool,
-    memory_type: str,
-    browser_name: str,
-    allow_downloads: bool,
-    skip_news: bool,
-) -> None:
-    """Updates the config object with the given arguments.
-
-    Args:
-        continuous (bool): Whether to run in continuous mode
-        continuous_limit (int): The number of times to run in continuous mode
-        ai_settings_file (str): The path to the ai_settings.yaml file
-        skip_reprompt (bool): Whether to skip the re-prompting messages at the beginning of the script
-        speak (bool): Whether to enable speak mode
-        debug (bool): Whether to enable debug mode
-        gpt3only (bool): Whether to enable GPT3.5 only mode
-        gpt4only (bool): Whether to enable GPT4 only mode
-        memory_type (str): The type of memory backend to use
-        browser_name (str): The name of the browser to use when using selenium to scrape the web
-        allow_downloads (bool): Whether to allow Auto-GPT to download files natively
-        skips_news (bool): Whether to suppress the output of latest news on startup
-    """
-    CFG.set_debug_mode(False)
-    CFG.set_continuous_mode(False)
-    CFG.set_speak_mode(False)
-
-    if debug:
-        logger.typewriter_log("Debug Mode: ", Fore.GREEN, "ENABLED")
-        CFG.set_debug_mode(True)
-
-    if continuous:
-        logger.typewriter_log("Continuous Mode: ", Fore.RED, "ENABLED")
-        logger.typewriter_log(
-            "WARNING: ",
-            Fore.RED,
-            "Continuous mode is not recommended. It is potentially dangerous and may"
-            " cause your AI to run forever or carry out actions you would not usually"
-            " authorise. Use at your own risk.",
-        )
-        CFG.set_continuous_mode(True)
-
-        if continuous_limit:
-            logger.typewriter_log(
-                "Continuous Limit: ", Fore.GREEN, f"{continuous_limit}"
-            )
-            CFG.set_continuous_limit(continuous_limit)
-
-    # Check if continuous limit is used without continuous mode
-    if continuous_limit and not continuous:
-        raise click.UsageError("--continuous-limit can only be used with --continuous")
-
-    if speak:
-        logger.typewriter_log("Speak Mode: ", Fore.GREEN, "ENABLED")
-        CFG.set_speak_mode(True)
-
-    if gpt3only:
-        logger.typewriter_log("GPT3.5 Only Mode: ", Fore.GREEN, "ENABLED")
-        CFG.set_smart_llm_model(CFG.fast_llm_model)
-
-    if gpt4only:
-        logger.typewriter_log("GPT4 Only Mode: ", Fore.GREEN, "ENABLED")
-        CFG.set_fast_llm_model(CFG.smart_llm_model)
-
-    if memory_type:
-        supported_memory = get_supported_memory_backends()
-        chosen = memory_type
-        if chosen not in supported_memory:
-            logger.typewriter_log(
-                "ONLY THE FOLLOWING MEMORY BACKENDS ARE SUPPORTED: ",
-                Fore.RED,
-                f"{supported_memory}",
-            )
-            logger.typewriter_log("Defaulting to: ", Fore.YELLOW, CFG.memory_backend)
-        else:
-            CFG.memory_backend = chosen
-
-    if skip_reprompt:
-        logger.typewriter_log("Skip Re-prompt: ", Fore.GREEN, "ENABLED")
-        CFG.skip_reprompt = True
-
-    if ai_settings_file:
-        file = ai_settings_file
-
-        # Validate file
-        (validated, message) = utils.validate_yaml_file(file)
-        if not validated:
-            logger.typewriter_log("FAILED FILE VALIDATION", Fore.RED, message)
-            logger.double_check()
-            exit(1)
-
-        logger.typewriter_log("Using AI Settings File:", Fore.GREEN, file)
-        CFG.ai_settings_file = file
-        CFG.skip_reprompt = True
-
-    if browser_name:
-        CFG.selenium_web_browser = browser_name
-
-    if allow_downloads:
-        logger.typewriter_log("Native Downloading:", Fore.GREEN, "ENABLED")
-        logger.typewriter_log(
-            "WARNING: ",
-            Fore.YELLOW,
-            f"{Back.LIGHTYELLOW_EX}Auto-GPT will now be able to download and save files to your machine.{Back.RESET} "
-            + "It is recommended that you monitor any files it downloads carefully.",
-        )
-        logger.typewriter_log(
-            "WARNING: ",
-            Fore.YELLOW,
-            f"{Back.RED + Style.BRIGHT}ALWAYS REMEMBER TO NEVER OPEN FILES YOU AREN'T SURE OF!{Style.RESET_ALL}",
-        )
-        CFG.allow_downloads = True
-
-    if skip_news:
-        CFG.skip_news = True

autogpt/js/overlay.js

@@ -1,29 +0,0 @@
-const overlay = document.createElement('div');
-Object.assign(overlay.style, {
-    position: 'fixed',
-    zIndex: 999999,
-    top: 0,
-    left: 0,
-    width: '100%',
-    height: '100%',
-    background: 'rgba(0, 0, 0, 0.7)',
-    color: '#fff',
-    fontSize: '24px',
-    fontWeight: 'bold',
-    display: 'flex',
-    justifyContent: 'center',
-    alignItems: 'center',
-});
-const textContent = document.createElement('div');
-Object.assign(textContent.style, {
-    textAlign: 'center',
-});
-textContent.textContent = 'AutoGPT Analyzing Page';
-overlay.appendChild(textContent);
-document.body.append(overlay);
-document.body.style.overflow = 'hidden';
-let dotCount = 0;
-setInterval(() => {
-    textContent.textContent = 'AutoGPT Analyzing Page' + '.'.repeat(dotCount);
-    dotCount = (dotCount + 1) % 4;
-}, 1000);

autogpt/json_utils/json_fix_general.py

@@ -1,121 +0,0 @@
-"""This module contains functions to fix JSON strings using general programmatic approaches, suitable for addressing
-common JSON formatting issues."""
-from __future__ import annotations
-
-import contextlib
-import json
-import re
-from typing import Optional
-
-from autogpt.config import Config
-from autogpt.json_utils.utilities import extract_char_position
-from autogpt.logs import logger
-
-CFG = Config()
-
-
-def fix_invalid_escape(json_to_load: str, error_message: str) -> str:
-    """Fix invalid escape sequences in JSON strings.
-
-    Args:
-        json_to_load (str): The JSON string.
-        error_message (str): The error message from the JSONDecodeError
-          exception.
-
-    Returns:
-        str: The JSON string with invalid escape sequences fixed.
-    """
-    while error_message.startswith("Invalid \\escape"):
-        bad_escape_location = extract_char_position(error_message)
-        json_to_load = (
-            json_to_load[:bad_escape_location] + json_to_load[bad_escape_location + 1 :]
-        )
-        try:
-            json.loads(json_to_load)
-            return json_to_load
-        except json.JSONDecodeError as e:
-            logger.debug("json loads error - fix invalid escape", e)
-            error_message = str(e)
-    return json_to_load
-
-
-def balance_braces(json_string: str) -> Optional[str]:
-    """
-    Balance the braces in a JSON string.
-
-    Args:
-        json_string (str): The JSON string.
-
-    Returns:
-        str: The JSON string with braces balanced.
-    """
-
-    open_braces_count = json_string.count("{")
-    close_braces_count = json_string.count("}")
-
-    while open_braces_count > close_braces_count:
-        json_string += "}"
-        close_braces_count += 1
-
-    while close_braces_count > open_braces_count:
-        json_string = json_string.rstrip("}")
-        close_braces_count -= 1
-
-    with contextlib.suppress(json.JSONDecodeError):
-        json.loads(json_string)
-        return json_string
-
-
-def add_quotes_to_property_names(json_string: str) -> str:
-    """
-    Add quotes to property names in a JSON string.
-
-    Args:
-        json_string (str): The JSON string.
-
-    Returns:
-        str: The JSON string with quotes added to property names.
-    """
-
-    def replace_func(match: re.Match) -> str:
-        return f'"{match[1]}":'
-
-    property_name_pattern = re.compile(r"(\w+):")
-    corrected_json_string = property_name_pattern.sub(replace_func, json_string)
-
-    try:
-        json.loads(corrected_json_string)
-        return corrected_json_string
-    except json.JSONDecodeError as e:
-        raise e
-
-
-def correct_json(json_to_load: str) -> str:
-    """
-    Correct common JSON errors.
-    Args:
-        json_to_load (str): The JSON string.
-    """
-
-    try:
-        logger.debug("json", json_to_load)
-        json.loads(json_to_load)
-        return json_to_load
-    except json.JSONDecodeError as e:
-        logger.debug("json loads error", e)
-        error_message = str(e)
-        if error_message.startswith("Invalid \\escape"):
-            json_to_load = fix_invalid_escape(json_to_load, error_message)
-        if error_message.startswith(
-            "Expecting property name enclosed in double quotes"
-        ):
-            json_to_load = add_quotes_to_property_names(json_to_load)
-            try:
-                json.loads(json_to_load)
-                return json_to_load
-            except json.JSONDecodeError as e:
-                logger.debug("json loads error - add quotes", e)
-                error_message = str(e)
-        if balanced_str := balance_braces(json_to_load):
-            return balanced_str
-    return json_to_load

autogpt/json_utils/json_fix_llm.py

@@ -1,239 +0,0 @@
-"""This module contains functions to fix JSON strings generated by LLM models, such as ChatGPT, using the assistance
-of the ChatGPT API or LLM models."""
-from __future__ import annotations
-
-import contextlib
-import json
-from typing import Any, Dict
-
-from colorama import Fore
-from regex import regex
-
-from autogpt.config import Config
-from autogpt.json_utils.json_fix_general import correct_json
-from autogpt.llm import call_ai_function
-from autogpt.logs import logger
-from autogpt.speech import say_text
-
-JSON_SCHEMA = """
-{
-    "command": {
-        "name": "command name",
-        "args": {
-            "arg name": "value"
-        }
-    },
-    "thoughts":
-    {
-        "text": "thought",
-        "reasoning": "reasoning",
-        "plan": "- short bulleted\n- list that conveys\n- long-term plan",
-        "criticism": "constructive self-criticism",
-        "speak": "thoughts summary to say to user"
-    }
-}
-"""
-
-CFG = Config()
-
-
-def auto_fix_json(json_string: str, schema: str) -> str:
-    """Fix the given JSON string to make it parseable and fully compliant with
-        the provided schema using GPT-3.
-
-    Args:
-        json_string (str): The JSON string to fix.
-        schema (str): The schema to use to fix the JSON.
-    Returns:
-        str: The fixed JSON string.
-    """
-    # Try to fix the JSON using GPT:
-    function_string = "def fix_json(json_string: str, schema:str=None) -> str:"
-    args = [f"'''{json_string}'''", f"'''{schema}'''"]
-    description_string = (
-        "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."
-    )
-
-    # If it doesn't already start with a "`", add one:
-    if not json_string.startswith("`"):
-        json_string = "```json\n" + json_string + "\n```"
-    result_string = call_ai_function(
-        function_string, args, description_string, model=CFG.fast_llm_model
-    )
-    logger.debug("------------ JSON FIX ATTEMPT ---------------")
-    logger.debug(f"Original JSON: {json_string}")
-    logger.debug("-----------")
-    logger.debug(f"Fixed JSON: {result_string}")
-    logger.debug("----------- END OF FIX ATTEMPT ----------------")
-
-    try:
-        json.loads(result_string)  # just check the validity
-        return result_string
-    except json.JSONDecodeError:  # noqa: E722
-        # Get the call stack:
-        # import traceback
-        # call_stack = traceback.format_exc()
-        # print(f"Failed to fix JSON: '{json_string}' "+call_stack)
-        return "failed"
-
-
-def fix_json_using_multiple_techniques(assistant_reply: str) -> Dict[Any, Any]:
-    """Fix the given JSON string to make it parseable and fully compliant with two techniques.
-
-    Args:
-        json_string (str): The JSON string to fix.
-
-    Returns:
-        str: The fixed JSON string.
-    """
-    assistant_reply = assistant_reply.strip()
-    if assistant_reply.startswith("```json"):
-        assistant_reply = assistant_reply[7:]
-    if assistant_reply.endswith("```"):
-        assistant_reply = assistant_reply[:-3]
-    try:
-        return json.loads(assistant_reply)  # just check the validity
-    except json.JSONDecodeError:  # noqa: E722
-        pass
-
-    if assistant_reply.startswith("json "):
-        assistant_reply = assistant_reply[5:]
-        assistant_reply = assistant_reply.strip()
-    try:
-        return json.loads(assistant_reply)  # just check the validity
-    except json.JSONDecodeError:  # noqa: E722
-        pass
-
-    # Parse and print Assistant response
-    assistant_reply_json = fix_and_parse_json(assistant_reply)
-    logger.debug("Assistant reply JSON: %s", str(assistant_reply_json))
-    if assistant_reply_json == {}:
-        assistant_reply_json = attempt_to_fix_json_by_finding_outermost_brackets(
-            assistant_reply
-        )
-
-    logger.debug("Assistant reply JSON 2: %s", str(assistant_reply_json))
-    if assistant_reply_json != {}:
-        return assistant_reply_json
-
-    logger.error(
-        "Error: The following AI output couldn't be converted to a JSON:\n",
-        assistant_reply,
-    )
-    if CFG.speak_mode:
-        say_text("I have received an invalid JSON response from the OpenAI API.")
-
-    return {}
-
-
-def fix_and_parse_json(
-    json_to_load: str, try_to_fix_with_gpt: bool = True
-) -> Dict[Any, Any]:
-    """Fix and parse JSON string
-
-    Args:
-        json_to_load (str): The JSON string.
-        try_to_fix_with_gpt (bool, optional): Try to fix the JSON with GPT.
-            Defaults to True.
-
-    Returns:
-        str or dict[Any, Any]: The parsed JSON.
-    """
-
-    with contextlib.suppress(json.JSONDecodeError):
-        json_to_load = json_to_load.replace("\t", "")
-        return json.loads(json_to_load)
-
-    with contextlib.suppress(json.JSONDecodeError):
-        json_to_load = correct_json(json_to_load)
-        return json.loads(json_to_load)
-    # Let's do something manually:
-    # sometimes GPT responds with something BEFORE the braces:
-    # "I'm sorry, I don't understand. Please try again."
-    # {"text": "I'm sorry, I don't understand. Please try again.",
-    #  "confidence": 0.0}
-    # So let's try to find the first brace and then parse the rest
-    #  of the string
-    try:
-        brace_index = json_to_load.index("{")
-        maybe_fixed_json = json_to_load[brace_index:]
-        last_brace_index = maybe_fixed_json.rindex("}")
-        maybe_fixed_json = maybe_fixed_json[: last_brace_index + 1]
-        return json.loads(maybe_fixed_json)
-    except (json.JSONDecodeError, ValueError) as e:
-        return try_ai_fix(try_to_fix_with_gpt, e, json_to_load)
-
-
-def try_ai_fix(
-    try_to_fix_with_gpt: bool, exception: Exception, json_to_load: str
-) -> Dict[Any, Any]:
-    """Try to fix the JSON with the AI
-
-    Args:
-        try_to_fix_with_gpt (bool): Whether to try to fix the JSON with the AI.
-        exception (Exception): The exception that was raised.
-        json_to_load (str): The JSON string to load.
-
-    Raises:
-        exception: If try_to_fix_with_gpt is False.
-
-    Returns:
-        str or dict[Any, Any]: The JSON string or dictionary.
-    """
-    if not try_to_fix_with_gpt:
-        raise exception
-    if CFG.debug_mode:
-        logger.warn(
-            "Warning: Failed to parse AI output, attempting to fix."
-            "\n If you see this warning frequently, it's likely that"
-            " your prompt is confusing the AI. Try changing it up"
-            " slightly."
-        )
-    # Now try to fix this up using the ai_functions
-    ai_fixed_json = auto_fix_json(json_to_load, JSON_SCHEMA)
-
-    if ai_fixed_json != "failed":
-        return json.loads(ai_fixed_json)
-    # This allows the AI to react to the error message,
-    #   which usually results in it correcting its ways.
-    # logger.error("Failed to fix AI output, telling the AI.")
-    return {}
-
-
-def attempt_to_fix_json_by_finding_outermost_brackets(json_string: str):
-    if CFG.speak_mode and CFG.debug_mode:
-        say_text(
-            "I have received an invalid JSON response from the OpenAI API. "
-            "Trying to fix it now."
-        )
-        logger.error("Attempting to fix JSON by finding outermost brackets\n")
-
-    try:
-        json_pattern = regex.compile(r"\{(?:[^{}]|(?R))*\}")
-        json_match = json_pattern.search(json_string)
-
-        if json_match:
-            # Extract the valid JSON object from the string
-            json_string = json_match.group(0)
-            logger.typewriter_log(
-                title="Apparently json was fixed.", title_color=Fore.GREEN
-            )
-            if CFG.speak_mode and CFG.debug_mode:
-                say_text("Apparently json was fixed.")
-        else:
-            return {}
-
-    except (json.JSONDecodeError, ValueError):
-        if CFG.debug_mode:
-            logger.error(f"Error: Invalid JSON: {json_string}\n")
-        if CFG.speak_mode:
-            say_text("Didn't work. I will have to ignore this response then.")
-        logger.error("Error: Invalid JSON, setting it to empty JSON now.\n")
-        json_string = {}
-
-    return fix_and_parse_json(json_string)

autogpt/json_utils/llm_response_format_1.json

@@ -1,31 +0,0 @@
-{
-    "$schema": "http://json-schema.org/draft-07/schema#",
-    "type": "object",
-    "properties": {
-        "thoughts": {
-            "type": "object",
-            "properties": {
-                "text": {"type": "string"},
-                "reasoning": {"type": "string"},
-                "plan": {"type": "string"},
-                "criticism": {"type": "string"},
-                "speak": {"type": "string"}
-            },
-            "required": ["text", "reasoning", "plan", "criticism", "speak"],
-            "additionalProperties": false
-        },
-        "command": {
-            "type": "object",
-            "properties": {
-                "name": {"type": "string"},
-                "args": {
-                    "type": "object"
-                }
-            },
-            "required": ["name", "args"],
-            "additionalProperties": false
-        }
-    },
-    "required": ["thoughts", "command"],
-    "additionalProperties": false
-}

autogpt/json_utils/utilities.py

@@ -1,79 +0,0 @@
-"""Utilities for the json_fixes package."""
-import json
-import re
-
-from jsonschema import Draft7Validator
-
-from autogpt.config import Config
-from autogpt.logs import logger
-
-CFG = Config()
-LLM_DEFAULT_RESPONSE_FORMAT = "llm_response_format_1"
-
-
-def extract_char_position(error_message: str) -> int:
-    """Extract the character position from the JSONDecodeError message.
-
-    Args:
-        error_message (str): The error message from the JSONDecodeError
-          exception.
-
-    Returns:
-        int: The character position.
-    """
-
-    char_pattern = re.compile(r"\(char (\d+)\)")
-    if match := char_pattern.search(error_message):
-        return int(match[1])
-    else:
-        raise ValueError("Character position not found in the error message.")
-
-
-def validate_json(json_object: object, schema_name: str) -> dict | None:
-    """
-    :type schema_name: object
-    :param schema_name: str
-    :type json_object: object
-    """
-    with open(f"autogpt/json_utils/{schema_name}.json", "r") as f:
-        schema = json.load(f)
-    validator = Draft7Validator(schema)
-
-    if errors := sorted(validator.iter_errors(json_object), key=lambda e: e.path):
-        logger.error("The JSON object is invalid.")
-        if CFG.debug_mode:
-            logger.error(
-                json.dumps(json_object, indent=4)
-            )  # Replace 'json_object' with the variable containing the JSON data
-            logger.error("The following issues were found:")
-
-            for error in errors:
-                logger.error(f"Error: {error.message}")
-    else:
-        logger.debug("The JSON object is valid.")
-
-    return json_object
-
-
-def validate_json_string(json_string: str, schema_name: str) -> dict | None:
-    """
-    :type schema_name: object
-    :param schema_name: str
-    :type json_object: object
-    """
-
-    try:
-        json_loaded = json.loads(json_string)
-        return validate_json(json_loaded, schema_name)
-    except:
-        return None
-
-
-def is_string_valid_json(json_string: str, schema_name: str) -> bool:
-    """
-    :type schema_name: object
-    :param schema_name: str
-    :type json_object: object
-    """
-
-    return validate_json_string(json_string, schema_name) is not None

autogpt/llm/__init__.py

@@ -1,38 +0,0 @@
-from autogpt.llm.api_manager import ApiManager
-from autogpt.llm.base import (
-    ChatModelInfo,
-    ChatModelResponse,
-    EmbeddingModelInfo,
-    EmbeddingModelResponse,
-    LLMResponse,
-    Message,
-    ModelInfo,
-)
-from autogpt.llm.chat import chat_with_ai, create_chat_message, generate_context
-from autogpt.llm.llm_utils import (
-    call_ai_function,
-    create_chat_completion,
-    get_ada_embedding,
-)
-from autogpt.llm.modelsinfo import COSTS
-from autogpt.llm.token_counter import count_message_tokens, count_string_tokens
-
-__all__ = [
-    "ApiManager",
-    "Message",
-    "ModelInfo",
-    "ChatModelInfo",
-    "EmbeddingModelInfo",
-    "LLMResponse",
-    "ChatModelResponse",
-    "EmbeddingModelResponse",
-    "create_chat_message",
-    "generate_context",
-    "chat_with_ai",
-    "call_ai_function",
-    "create_chat_completion",
-    "get_ada_embedding",
-    "COSTS",
-    "count_message_tokens",
-    "count_string_tokens",
-]

autogpt/llm/api_manager.py

@@ -1,128 +0,0 @@
-from __future__ import annotations
-
-import openai
-
-from autogpt.config import Config
-from autogpt.llm.modelsinfo import COSTS
-from autogpt.logs import logger
-from autogpt.singleton import Singleton
-
-
-class ApiManager(metaclass=Singleton):
-    def __init__(self):
-        self.total_prompt_tokens = 0
-        self.total_completion_tokens = 0
-        self.total_cost = 0
-        self.total_budget = 0
-
-    def reset(self):
-        self.total_prompt_tokens = 0
-        self.total_completion_tokens = 0
-        self.total_cost = 0
-        self.total_budget = 0.0
-
-    def create_chat_completion(
-        self,
-        messages: list,  # type: ignore
-        model: str | None = None,
-        temperature: float = None,
-        max_tokens: int | None = None,
-        deployment_id=None,
-    ) -> str:
-        """
-        Create a chat completion and update the cost.
-        Args:
-        messages (list): The list of messages to send to the API.
-        model (str): The model to use for the API call.
-        temperature (float): The temperature to use for the API call.
-        max_tokens (int): The maximum number of tokens for the API call.
-        Returns:
-        str: The AI's response.
-        """
-        cfg = Config()
-        if temperature is None:
-            temperature = cfg.temperature
-        if deployment_id is not None:
-            response = openai.ChatCompletion.create(
-                deployment_id=deployment_id,
-                model=model,
-                messages=messages,
-                temperature=temperature,
-                max_tokens=max_tokens,
-                api_key=cfg.openai_api_key,
-            )
-        else:
-            response = openai.ChatCompletion.create(
-                model=model,
-                messages=messages,
-                temperature=temperature,
-                max_tokens=max_tokens,
-                api_key=cfg.openai_api_key,
-            )
-        logger.debug(f"Response: {response}")
-        prompt_tokens = response.usage.prompt_tokens
-        completion_tokens = response.usage.completion_tokens
-        self.update_cost(prompt_tokens, completion_tokens, model)
-        return response
-
-    def update_cost(self, prompt_tokens, completion_tokens, model):
-        """
-        Update the total cost, prompt tokens, and completion tokens.
-
-        Args:
-        prompt_tokens (int): The number of tokens used in the prompt.
-        completion_tokens (int): The number of tokens used in the completion.
-        model (str): The model used for the API call.
-        """
-        self.total_prompt_tokens += prompt_tokens
-        self.total_completion_tokens += completion_tokens
-        self.total_cost += (
-            prompt_tokens * COSTS[model]["prompt"]
-            + completion_tokens * COSTS[model]["completion"]
-        ) / 1000
-        logger.debug(f"Total running cost: ${self.total_cost:.3f}")
-
-    def set_total_budget(self, total_budget):
-        """
-        Sets the total user-defined budget for API calls.
-
-        Args:
-        total_budget (float): The total budget for API calls.
-        """
-        self.total_budget = total_budget
-
-    def get_total_prompt_tokens(self):
-        """
-        Get the total number of prompt tokens.
-
-        Returns:
-        int: The total number of prompt tokens.
-        """
-        return self.total_prompt_tokens
-
-    def get_total_completion_tokens(self):
-        """
-        Get the total number of completion tokens.
-
-        Returns:
-        int: The total number of completion tokens.
-        """
-        return self.total_completion_tokens
-
-    def get_total_cost(self):
-        """
-        Get the total cost of API calls.
-
-        Returns:
-        float: The total cost of API calls.
-        """
-        return self.total_cost
-
-    def get_total_budget(self):
-        """
-        Get the total user-defined budget for API calls.
-
-        Returns:
-        float: The total budget for API calls.
-        """
-        return self.total_budget

autogpt/llm/base.py

@@ -1,65 +0,0 @@
-from dataclasses import dataclass, field
-from typing import List, TypedDict
-
-
-class Message(TypedDict):
-    """OpenAI Message object containing a role and the message content"""
-
-    role: str
-    content: str
-
-
-@dataclass
-class ModelInfo:
-    """Struct for model information.
-
-    Would be lovely to eventually get this directly from APIs, but needs to be scraped from
-    websites for now.
-
-    """
-
-    name: str
-    prompt_token_cost: float
-    completion_token_cost: float
-    max_tokens: int
-
-
-@dataclass
-class ChatModelInfo(ModelInfo):
-    """Struct for chat model information."""
-
-    pass
-
-
-@dataclass
-class EmbeddingModelInfo(ModelInfo):
-    """Struct for embedding model information."""
-
-    embedding_dimensions: int
-
-
-@dataclass
-class LLMResponse:
-    """Standard response struct for a response from an LLM model."""
-
-    model_info: ModelInfo
-    prompt_tokens_used: int = 0
-    completion_tokens_used: int = 0
-
-
-@dataclass
-class EmbeddingModelResponse(LLMResponse):
-    """Standard response struct for a response from an embedding model."""
-
-    embedding: List[float] = field(default_factory=list)
-
-    def __post_init__(self):
-        if self.completion_tokens_used:
-            raise ValueError("Embeddings should not have completion tokens used.")
-
-
-@dataclass
-class ChatModelResponse(LLMResponse):
-    """Standard response struct for a response from an LLM model."""
-
-    content: str = None

autogpt/llm/chat.py

@@ -1,253 +0,0 @@
-import time
-from random import shuffle
-
-from openai.error import RateLimitError
-
-from autogpt.config import Config
-from autogpt.llm.api_manager import ApiManager
-from autogpt.llm.base import Message
-from autogpt.llm.llm_utils import create_chat_completion
-from autogpt.llm.token_counter import count_message_tokens
-from autogpt.logs import logger
-from autogpt.memory_management.store_memory import (
-    save_memory_trimmed_from_context_window,
-)
-from autogpt.memory_management.summary_memory import (
-    get_newly_trimmed_messages,
-    update_running_summary,
-)
-
-cfg = Config()
-
-
-def create_chat_message(role, content) -> Message:
-    """
-    Create a chat message with the given role and content.
-
-    Args:
-    role (str): The role of the message sender, e.g., "system", "user", or "assistant".
-    content (str): The content of the message.
-
-    Returns:
-    dict: A dictionary containing the role and content of the message.
-    """
-    return {"role": role, "content": content}
-
-
-def generate_context(prompt, relevant_memory, full_message_history, model):
-    current_context = [
-        create_chat_message("system", prompt),
-        create_chat_message(
-            "system", f"The current time and date is {time.strftime('%c')}"
-        ),
-        # create_chat_message(
-        #     "system",
-        #     f"This reminds you of these events from your past:\n{relevant_memory}\n\n",
-        # ),
-    ]
-
-    # Add messages from the full message history until we reach the token limit
-    next_message_to_add_index = len(full_message_history) - 1
-    insertion_index = len(current_context)
-    # Count the currently used tokens
-    current_tokens_used = count_message_tokens(current_context, model)
-    return (
-        next_message_to_add_index,
-        current_tokens_used,
-        insertion_index,
-        current_context,
-    )
-
-
-# TODO: Change debug from hardcode to argument
-def chat_with_ai(
-    agent, prompt, user_input, full_message_history, permanent_memory, token_limit
-):
-    """Interact with the OpenAI API, sending the prompt, user input, message history,
-    and permanent memory."""
-    while True:
-        try:
-            """
-            Interact with the OpenAI API, sending the prompt, user input,
-                message history, and permanent memory.
-
-            Args:
-                prompt (str): The prompt explaining the rules to the AI.
-                user_input (str): The input from the user.
-                full_message_history (list): The list of all messages sent between the
-                    user and the AI.
-                permanent_memory (Obj): The memory object containing the permanent
-                  memory.
-                token_limit (int): The maximum number of tokens allowed in the API call.
-
-            Returns:
-            str: The AI's response.
-            """
-            model = cfg.fast_llm_model  # TODO: Change model from hardcode to argument
-            # Reserve 1000 tokens for the response
-            logger.debug(f"Token limit: {token_limit}")
-            send_token_limit = token_limit - 1000
-
-            # if len(full_message_history) == 0:
-            #     relevant_memory = ""
-            # else:
-            #     recent_history = full_message_history[-5:]
-            #     shuffle(recent_history)
-            #     relevant_memories = permanent_memory.get_relevant(
-            #         str(recent_history), 5
-            #     )
-            #     if relevant_memories:
-            #         shuffle(relevant_memories)
-            #     relevant_memory = str(relevant_memories)
-            relevant_memory = ""
-            logger.debug(f"Memory Stats: {permanent_memory.get_stats()}")
-
-            (
-                next_message_to_add_index,
-                current_tokens_used,
-                insertion_index,
-                current_context,
-            ) = generate_context(prompt, relevant_memory, full_message_history, model)
-
-            # while current_tokens_used > 2500:
-            #     # remove memories until we are under 2500 tokens
-            #     relevant_memory = relevant_memory[:-1]
-            #     (
-            #         next_message_to_add_index,
-            #         current_tokens_used,
-            #         insertion_index,
-            #         current_context,
-            #     ) = generate_context(
-            #         prompt, relevant_memory, full_message_history, model
-            #     )
-
-            current_tokens_used += count_message_tokens(
-                [create_chat_message("user", user_input)], model
-            )  # Account for user input (appended later)
-
-            current_tokens_used += 500  # Account for memory (appended later) TODO: The final memory may be less than 500 tokens
-
-            # Add Messages until the token limit is reached or there are no more messages to add.
-            while next_message_to_add_index >= 0:
-                # print (f"CURRENT TOKENS USED: {current_tokens_used}")
-                message_to_add = full_message_history[next_message_to_add_index]
-
-                tokens_to_add = count_message_tokens([message_to_add], model)
-                if current_tokens_used + tokens_to_add > send_token_limit:
-                    # save_memory_trimmed_from_context_window(
-                    #     full_message_history,
-                    #     next_message_to_add_index,
-                    #     permanent_memory,
-                    # )
-                    break
-
-                # Add the most recent message to the start of the current context,
-                #  after the two system prompts.
-                current_context.insert(
-                    insertion_index, full_message_history[next_message_to_add_index]
-                )
-
-                # Count the currently used tokens
-                current_tokens_used += tokens_to_add
-
-                # Move to the next most recent message in the full message history
-                next_message_to_add_index -= 1
-
-            # Insert Memories
-            if len(full_message_history) > 0:
-                (
-                    newly_trimmed_messages,
-                    agent.last_memory_index,
-                ) = get_newly_trimmed_messages(
-                    full_message_history=full_message_history,
-                    current_context=current_context,
-                    last_memory_index=agent.last_memory_index,
-                )
-                agent.summary_memory = update_running_summary(
-                    current_memory=agent.summary_memory,
-                    new_events=newly_trimmed_messages,
-                )
-                current_context.insert(insertion_index, agent.summary_memory)
-
-            api_manager = ApiManager()
-            # inform the AI about its remaining budget (if it has one)
-            if api_manager.get_total_budget() > 0.0:
-                remaining_budget = (
-                    api_manager.get_total_budget() - api_manager.get_total_cost()
-                )
-                if remaining_budget < 0:
-                    remaining_budget = 0
-                system_message = (
-                    f"Your remaining API budget is ${remaining_budget:.3f}"
-                    + (
-                        " BUDGET EXCEEDED! SHUT DOWN!\n\n"
-                        if remaining_budget == 0
-                        else " Budget very nearly exceeded! Shut down gracefully!\n\n"
-                        if remaining_budget < 0.005
-                        else " Budget nearly exceeded. Finish up.\n\n"
-                        if remaining_budget < 0.01
-                        else "\n\n"
-                    )
-                )
-                logger.debug(system_message)
-                current_context.append(create_chat_message("system", system_message))
-
-            # Append user input, the length of this is accounted for above
-            current_context.extend([create_chat_message("user", user_input)])
-
-            plugin_count = len(cfg.plugins)
-            for i, plugin in enumerate(cfg.plugins):
-                if not plugin.can_handle_on_planning():
-                    continue
-                plugin_response = plugin.on_planning(
-                    agent.prompt_generator, current_context
-                )
-                if not plugin_response or plugin_response == "":
-                    continue
-                tokens_to_add = count_message_tokens(
-                    [create_chat_message("system", plugin_response)], model
-                )
-                if current_tokens_used + tokens_to_add > send_token_limit:
-                    logger.debug("Plugin response too long, skipping:", plugin_response)
-                    logger.debug("Plugins remaining at stop:", plugin_count - i)
-                    break
-                current_context.append(create_chat_message("system", plugin_response))
-
-            # Calculate remaining tokens
-            tokens_remaining = token_limit - current_tokens_used
-            # assert tokens_remaining >= 0, "Tokens remaining is negative.
-            # This should never happen, please submit a bug report at
-            #  https://www.github.com/Torantulino/Auto-GPT"
-
-            # Debug print the current context
-            logger.debug(f"Token limit: {token_limit}")
-            logger.debug(f"Send Token Count: {current_tokens_used}")
-            logger.debug(f"Tokens remaining for response: {tokens_remaining}")
-            logger.debug("------------ CONTEXT SENT TO AI ---------------")
-            for message in current_context:
-                # Skip printing the prompt
-                if message["role"] == "system" and message["content"] == prompt:
-                    continue
-                logger.debug(f"{message['role'].capitalize()}: {message['content']}")
-                logger.debug("")
-            logger.debug("----------- END OF CONTEXT ----------------")
-
-            # TODO: use a model defined elsewhere, so that model can contain
-            # temperature and other settings we care about
-            assistant_reply = create_chat_completion(
-                model=model,
-                messages=current_context,
-                max_tokens=tokens_remaining,
-            )
-
-            # Update full message history
-            full_message_history.append(create_chat_message("user", user_input))
-            full_message_history.append(
-                create_chat_message("assistant", assistant_reply)
-            )
-
-            return assistant_reply
-        except RateLimitError:
-            # TODO: When we switch to langchain, this is built in
-            logger.warn("Error: ", "API Rate Limit Reached. Waiting 10 seconds...")
-            time.sleep(10)

autogpt/llm/llm_utils.py

@@ -1,258 +0,0 @@
-from __future__ import annotations
-
-import functools
-import time
-from typing import List, Optional
-
-import openai
-from colorama import Fore, Style
-from openai.error import APIError, RateLimitError, Timeout
-
-from autogpt.config import Config
-from autogpt.llm.api_manager import ApiManager
-from autogpt.llm.base import Message
-from autogpt.logs import logger
-
-
-def retry_openai_api(
-    num_retries: int = 10,
-    backoff_base: float = 2.0,
-    warn_user: bool = True,
-):
-    """Retry an OpenAI API call.
-
-    Args:
-        num_retries int: Number of retries. Defaults to 10.
-        backoff_base float: Base for exponential backoff. Defaults to 2.
-        warn_user bool: Whether to warn the user. Defaults to True.
-    """
-    retry_limit_msg = f"{Fore.RED}Error: " f"Reached rate limit, passing...{Fore.RESET}"
-    api_key_error_msg = (
-        f"Please double check that you have setup a "
-        f"{Fore.CYAN + Style.BRIGHT}PAID{Style.RESET_ALL} OpenAI API Account. You can "
-        f"read more here: {Fore.CYAN}https://significant-gravitas.github.io/Auto-GPT/setup/#getting-an-api-key{Fore.RESET}"
-    )
-    backoff_msg = (
-        f"{Fore.RED}Error: API Bad gateway. Waiting {{backoff}} seconds...{Fore.RESET}"
-    )
-
-    def _wrapper(func):
-        @functools.wraps(func)
-        def _wrapped(*args, **kwargs):
-            user_warned = not warn_user
-            num_attempts = num_retries + 1  # +1 for the first attempt
-            for attempt in range(1, num_attempts + 1):
-                try:
-                    return func(*args, **kwargs)
-
-                except RateLimitError:
-                    if attempt == num_attempts:
-                        raise
-
-                    logger.debug(retry_limit_msg)
-                    if not user_warned:
-                        logger.double_check(api_key_error_msg)
-                        user_warned = True
-
-                except APIError as e:
-                    if (e.http_status != 502) or (attempt == num_attempts):
-                        raise
-
-                backoff = backoff_base ** (attempt + 2)
-                logger.debug(backoff_msg.format(backoff=backoff))
-                time.sleep(backoff)
-
-        return _wrapped
-
-    return _wrapper
-
-
-def call_ai_function(
-    function: str, args: list, description: str, model: str | None = None
-) -> str:
-    """Call an AI function
-
-    This is a magic function that can do anything with no-code. See
-    https://github.com/Torantulino/AI-Functions for more info.
-
-    Args:
-        function (str): The function to call
-        args (list): The arguments to pass to the function
-        description (str): The description of the function
-        model (str, optional): The model to use. Defaults to None.
-
-    Returns:
-        str: The response from the function
-    """
-    cfg = Config()
-    if model is None:
-        model = cfg.smart_llm_model
-    # For each arg, if any are None, convert to "None":
-    args = [str(arg) if arg is not None else "None" for arg in args]
-    # parse args to comma separated string
-    args: str = ", ".join(args)
-    messages: List[Message] = [
-        {
-            "role": "system",
-            "content": f"You are now the following python function: ```# {description}"
-            f"\n{function}```\n\nOnly respond with your `return` value.",
-        },
-        {"role": "user", "content": args},
-    ]
-
-    return create_chat_completion(model=model, messages=messages, temperature=0)
-
-
-# Overly simple abstraction until we create something better
-# simple retry mechanism when getting a rate error or a bad gateway
-def create_chat_completion(
-    messages: List[Message],  # type: ignore
-    model: Optional[str] = None,
-    temperature: float = None,
-    max_tokens: Optional[int] = None,
-) -> str:
-    """Create a chat completion using the OpenAI API
-
-    Args:
-        messages (List[Message]): The messages to send to the chat completion
-        model (str, optional): The model to use. Defaults to None.
-        temperature (float, optional): The temperature to use. Defaults to 0.9.
-        max_tokens (int, optional): The max tokens to use. Defaults to None.
-
-    Returns:
-        str: The response from the chat completion
-    """
-    cfg = Config()
-    if temperature is None:
-        temperature = cfg.temperature
-
-    num_retries = 10
-    warned_user = False
-    logger.debug(
-        f"{Fore.GREEN}Creating chat completion with model {model}, temperature {temperature}, max_tokens {max_tokens}{Fore.RESET}"
-    )
-    for plugin in cfg.plugins:
-        if plugin.can_handle_chat_completion(
-            messages=messages,
-            model=model,
-            temperature=temperature,
-            max_tokens=max_tokens,
-        ):
-            message = plugin.handle_chat_completion(
-                messages=messages,
-                model=model,
-                temperature=temperature,
-                max_tokens=max_tokens,
-            )
-            if message is not None:
-                return message
-    api_manager = ApiManager()
-    response = None
-    for attempt in range(num_retries):
-        backoff = 2 ** (attempt + 2)
-        try:
-            if cfg.use_azure:
-                response = api_manager.create_chat_completion(
-                    deployment_id=cfg.get_azure_deployment_id_for_model(model),
-                    model=model,
-                    messages=messages,
-                    temperature=temperature,
-                    max_tokens=max_tokens,
-                )
-            else:
-                response = api_manager.create_chat_completion(
-                    model=model,
-                    messages=messages,
-                    temperature=temperature,
-                    max_tokens=max_tokens,
-                )
-            break
-        except RateLimitError:
-            logger.debug(
-                f"{Fore.RED}Error: ", f"Reached rate limit, passing...{Fore.RESET}"
-            )
-            if not warned_user:
-                logger.double_check(
-                    f"Please double check that you have setup a {Fore.CYAN + Style.BRIGHT}PAID{Style.RESET_ALL} OpenAI API Account. "
-                    + f"You can read more here: {Fore.CYAN}https://significant-gravitas.github.io/Auto-GPT/setup/#getting-an-api-key{Fore.RESET}"
-                )
-                warned_user = True
-        except (APIError, Timeout) as e:
-            if e.http_status != 502:
-                raise
-            if attempt == num_retries - 1:
-                raise
-        logger.debug(
-            f"{Fore.RED}Error: ",
-            f"API Bad gateway. Waiting {backoff} seconds...{Fore.RESET}",
-        )
-        time.sleep(backoff)
-    if response is None:
-        logger.typewriter_log(
-            "FAILED TO GET RESPONSE FROM OPENAI",
-            Fore.RED,
-            "Auto-GPT has failed to get a response from OpenAI's services. "
-            + f"Try running Auto-GPT again, and if the problem the persists try running it with `{Fore.CYAN}--debug{Fore.RESET}`.",
-        )
-        logger.double_check()
-        if cfg.debug_mode:
-            raise RuntimeError(f"Failed to get response after {num_retries} retries")
-        else:
-            quit(1)
-    resp = response.choices[0].message["content"]
-    for plugin in cfg.plugins:
-        if not plugin.can_handle_on_response():
-            continue
-        resp = plugin.on_response(resp)
-    return resp
-
-
-def get_ada_embedding(text: str) -> List[float]:
-    """Get an embedding from the ada model.
-
-    Args:
-        text (str): The text to embed.
-
-    Returns:
-        List[float]: The embedding.
-    """
-    cfg = Config()
-    model = "text-embedding-ada-002"
-    text = text.replace("\n", " ")
-
-    if cfg.use_azure:
-        kwargs = {"engine": cfg.get_azure_deployment_id_for_model(model)}
-    else:
-        kwargs = {"model": model}
-
-    embedding = create_embedding(text, **kwargs)
-    api_manager = ApiManager()
-    api_manager.update_cost(
-        prompt_tokens=embedding.usage.prompt_tokens,
-        completion_tokens=0,
-        model=model,
-    )
-    return embedding["data"][0]["embedding"]
-
-
-@retry_openai_api()
-def create_embedding(
-    text: str,
-    *_,
-    **kwargs,
-) -> openai.Embedding:
-    """Create an embedding using the OpenAI API
-
-    Args:
-        text (str): The text to embed.
-        kwargs: Other arguments to pass to the OpenAI API embedding creation call.
-
-    Returns:
-        openai.Embedding: The embedding object.
-    """
-    cfg = Config()
-    return openai.Embedding.create(
-        input=[text],
-        api_key=cfg.openai_api_key,
-        **kwargs,
-    )

autogpt/llm/modelsinfo.py

@@ -1,7 +0,0 @@
-COSTS = {
-    "gpt-3.5-turbo": {"prompt": 0.002, "completion": 0.002},
-    "gpt-3.5-turbo-0301": {"prompt": 0.002, "completion": 0.002},
-    "gpt-4-0314": {"prompt": 0.03, "completion": 0.06},
-    "gpt-4": {"prompt": 0.03, "completion": 0.06},
-    "text-embedding-ada-002": {"prompt": 0.0004, "completion": 0.0},
-}

autogpt/llm/providers/openai.py

@@ -1,37 +0,0 @@
-from autogpt.llm.base import ChatModelInfo, EmbeddingModelInfo
-
-OPEN_AI_CHAT_MODELS = {
-    "gpt-3.5-turbo": ChatModelInfo(
-        name="gpt-3.5-turbo",
-        prompt_token_cost=0.002,
-        completion_token_cost=0.002,
-        max_tokens=4096,
-    ),
-    "gpt-4": ChatModelInfo(
-        name="gpt-4",
-        prompt_token_cost=0.03,
-        completion_token_cost=0.06,
-        max_tokens=8192,
-    ),
-    "gpt-4-32k": ChatModelInfo(
-        name="gpt-4-32k",
-        prompt_token_cost=0.06,
-        completion_token_cost=0.12,
-        max_tokens=32768,
-    ),
-}
-
-OPEN_AI_EMBEDDING_MODELS = {
-    "text-embedding-ada-002": EmbeddingModelInfo(
-        name="text-embedding-ada-002",
-        prompt_token_cost=0.0004,
-        completion_token_cost=0.0,
-        max_tokens=8191,
-        embedding_dimensions=1536,
-    ),
-}
-
-OPEN_AI_MODELS = {
-    **OPEN_AI_CHAT_MODELS,
-    **OPEN_AI_EMBEDDING_MODELS,
-}

autogpt/llm/token_counter.py

@@ -1,76 +0,0 @@
-"""Functions for counting the number of tokens in a message or string."""
-from __future__ import annotations
-
-from typing import List
-
-import tiktoken
-
-from autogpt.llm.base import Message
-from autogpt.logs import logger
-
-
-def count_message_tokens(
-    messages: List[Message], model: str = "gpt-3.5-turbo-0301"
-) -> int:
-    """
-    Returns the number of tokens used by a list of messages.
-
-    Args:
-        messages (list): A list of messages, each of which is a dictionary
-            containing the role and content of the message.
-        model (str): The name of the model to use for tokenization.
-            Defaults to "gpt-3.5-turbo-0301".
-
-    Returns:
-        int: The number of tokens used by the list of messages.
-    """
-    try:
-        encoding = tiktoken.encoding_for_model(model)
-    except KeyError:
-        logger.warn("Warning: model not found. Using cl100k_base encoding.")
-        encoding = tiktoken.get_encoding("cl100k_base")
-    if model == "gpt-3.5-turbo":
-        # !Note: gpt-3.5-turbo may change over time.
-        # Returning num tokens assuming gpt-3.5-turbo-0301.")
-        return count_message_tokens(messages, model="gpt-3.5-turbo-0301")
-    elif model == "gpt-4":
-        # !Note: gpt-4 may change over time. Returning num tokens assuming gpt-4-0314.")
-        return count_message_tokens(messages, model="gpt-4-0314")
-    elif model == "gpt-3.5-turbo-0301":
-        tokens_per_message = (
-            4  # every message follows <|start|>{role/name}\n{content}<|end|>\n
-        )
-        tokens_per_name = -1  # if there's a name, the role is omitted
-    elif model == "gpt-4-0314":
-        tokens_per_message = 3
-        tokens_per_name = 1
-    else:
-        raise NotImplementedError(
-            f"num_tokens_from_messages() is not implemented for model {model}.\n"
-            " See https://github.com/openai/openai-python/blob/main/chatml.md for"
-            " information on how messages are converted to tokens."
-        )
-    num_tokens = 0
-    for message in messages:
-        num_tokens += tokens_per_message
-        for key, value in message.items():
-            num_tokens += len(encoding.encode(value))
-            if key == "name":
-                num_tokens += tokens_per_name
-    num_tokens += 3  # every reply is primed with <|start|>assistant<|message|>
-    return num_tokens
-
-
-def count_string_tokens(string: str, model_name: str) -> int:
-    """
-    Returns the number of tokens in a text string.
-
-    Args:
-        string (str): The text string.
-        model_name (str): The name of the encoding to use. (e.g., "gpt-3.5-turbo")
-
-    Returns:
-        int: The number of tokens in the text string.
-    """
-    encoding = tiktoken.encoding_for_model(model_name)
-    return len(encoding.encode(string))

autogpt/logs.py

@@ -1,256 +0,0 @@
-"""Logging module for Auto-GPT."""
-import logging
-import os
-import random
-import re
-import time
-from logging import LogRecord
-
-from colorama import Fore, Style
-
-from autogpt.singleton import Singleton
-from autogpt.speech import say_text
-
-
-class Logger(metaclass=Singleton):
-    """
-    Logger that handle titles in different colors.
-    Outputs logs in console, activity.log, and errors.log
-    For console handler: simulates typing
-    """
-
-    def __init__(self):
-        # create log directory if it doesn't exist
-        this_files_dir_path = os.path.dirname(__file__)
-        log_dir = os.path.join(this_files_dir_path, "../logs")
-        if not os.path.exists(log_dir):
-            os.makedirs(log_dir)
-
-        log_file = "activity.log"
-        error_file = "error.log"
-
-        console_formatter = AutoGptFormatter("%(title_color)s %(message)s")
-
-        # Create a handler for console which simulate typing
-        self.typing_console_handler = TypingConsoleHandler()
-        self.typing_console_handler.setLevel(logging.INFO)
-        self.typing_console_handler.setFormatter(console_formatter)
-
-        # Create a handler for console without typing simulation
-        self.console_handler = ConsoleHandler()
-        self.console_handler.setLevel(logging.DEBUG)
-        self.console_handler.setFormatter(console_formatter)
-
-        # Info handler in activity.log
-        self.file_handler = logging.FileHandler(
-            os.path.join(log_dir, log_file), "a", "utf-8"
-        )
-        self.file_handler.setLevel(logging.DEBUG)
-        info_formatter = AutoGptFormatter(
-            "%(asctime)s %(levelname)s %(title)s %(message_no_color)s"
-        )
-        self.file_handler.setFormatter(info_formatter)
-
-        # Error handler error.log
-        error_handler = logging.FileHandler(
-            os.path.join(log_dir, error_file), "a", "utf-8"
-        )
-        error_handler.setLevel(logging.ERROR)
-        error_formatter = AutoGptFormatter(
-            "%(asctime)s %(levelname)s %(module)s:%(funcName)s:%(lineno)d %(title)s"
-            " %(message_no_color)s"
-        )
-        error_handler.setFormatter(error_formatter)
-
-        self.typing_logger = logging.getLogger("TYPER")
-        self.typing_logger.addHandler(self.typing_console_handler)
-        self.typing_logger.addHandler(self.file_handler)
-        self.typing_logger.addHandler(error_handler)
-        self.typing_logger.setLevel(logging.DEBUG)
-
-        self.logger = logging.getLogger("LOGGER")
-        self.logger.addHandler(self.console_handler)
-        self.logger.addHandler(self.file_handler)
-        self.logger.addHandler(error_handler)
-        self.logger.setLevel(logging.DEBUG)
-
-        self.speak_mode = False
-
-    def typewriter_log(
-        self, title="", title_color="", content="", speak_text=False, level=logging.INFO
-    ):
-        if speak_text and self.speak_mode:
-            say_text(f"{title}. {content}")
-
-        if content:
-            if isinstance(content, list):
-                content = " ".join(content)
-        else:
-            content = ""
-
-        self.typing_logger.log(
-            level, content, extra={"title": title, "color": title_color}
-        )
-
-    def debug(
-        self,
-        message,
-        title="",
-        title_color="",
-    ):
-        self._log(title, title_color, message, logging.DEBUG)
-
-    def info(
-        self,
-        message,
-        title="",
-        title_color="",
-    ):
-        self._log(title, title_color, message, logging.INFO)
-
-    def warn(
-        self,
-        message,
-        title="",
-        title_color="",
-    ):
-        self._log(title, title_color, message, logging.WARN)
-
-    def error(self, title, message=""):
-        self._log(title, Fore.RED, message, logging.ERROR)
-
-    def _log(
-        self,
-        title: str = "",
-        title_color: str = "",
-        message: str = "",
-        level=logging.INFO,
-    ):
-        if message:
-            if isinstance(message, list):
-                message = " ".join(message)
-        self.logger.log(
-            level, message, extra={"title": str(title), "color": str(title_color)}
-        )
-
-    def set_level(self, level):
-        self.logger.setLevel(level)
-        self.typing_logger.setLevel(level)
-
-    def double_check(self, additionalText=None):
-        if not additionalText:
-            additionalText = (
-                "Please ensure you've setup and configured everything"
-                " correctly. Read https://github.com/Torantulino/Auto-GPT#readme to "
-                "double check. You can also create a github issue or join the discord"
-                " and ask there!"
-            )
-
-        self.typewriter_log("DOUBLE CHECK CONFIGURATION", Fore.YELLOW, additionalText)
-
-
-"""
-Output stream to console using simulated typing
-"""
-
-
-class TypingConsoleHandler(logging.StreamHandler):
-    def emit(self, record):
-        min_typing_speed = 0.05
-        max_typing_speed = 0.01
-
-        msg = self.format(record)
-        try:
-            words = msg.split()
-            for i, word in enumerate(words):
-                print(word, end="", flush=True)
-                if i < len(words) - 1:
-                    print(" ", end="", flush=True)
-                typing_speed = random.uniform(min_typing_speed, max_typing_speed)
-                time.sleep(typing_speed)
-                # type faster after each word
-                min_typing_speed = min_typing_speed * 0.95
-                max_typing_speed = max_typing_speed * 0.95
-            print()
-        except Exception:
-            self.handleError(record)
-
-
-class ConsoleHandler(logging.StreamHandler):
-    def emit(self, record) -> None:
-        msg = self.format(record)
-        try:
-            print(msg)
-        except Exception:
-            self.handleError(record)
-
-
-class AutoGptFormatter(logging.Formatter):
-    """
-    Allows to handle custom placeholders 'title_color' and 'message_no_color'.
-    To use this formatter, make sure to pass 'color', 'title' as log extras.
-    """
-
-    def format(self, record: LogRecord) -> str:
-        if hasattr(record, "color"):
-            record.title_color = (
-                getattr(record, "color")
-                + getattr(record, "title")
-                + " "
-                + Style.RESET_ALL
-            )
-        else:
-            record.title_color = getattr(record, "title")
-        if hasattr(record, "msg"):
-            record.message_no_color = remove_color_codes(getattr(record, "msg"))
-        else:
-            record.message_no_color = ""
-        return super().format(record)
-
-
-def remove_color_codes(s: str) -> str:
-    ansi_escape = re.compile(r"\x1B(?:[@-Z\\-_]|\[[0-?]*[ -/]*[@-~])")
-    return ansi_escape.sub("", s)
-
-
-logger = Logger()
-
-
-def print_assistant_thoughts(
-    ai_name: object,
-    assistant_reply_json_valid: object,
-    speak_mode: bool = False,
-) -> None:
-    assistant_thoughts_reasoning = None
-    assistant_thoughts_plan = None
-    assistant_thoughts_speak = None
-    assistant_thoughts_criticism = None
-
-    assistant_thoughts = assistant_reply_json_valid.get("thoughts", {})
-    assistant_thoughts_text = assistant_thoughts.get("text")
-    if assistant_thoughts:
-        assistant_thoughts_reasoning = assistant_thoughts.get("reasoning")
-        assistant_thoughts_plan = assistant_thoughts.get("plan")
-        assistant_thoughts_criticism = assistant_thoughts.get("criticism")
-        assistant_thoughts_speak = assistant_thoughts.get("speak")
-    logger.typewriter_log(
-        f"{ai_name.upper()} THOUGHTS:", Fore.YELLOW, f"{assistant_thoughts_text}"
-    )
-    logger.typewriter_log("REASONING:", Fore.YELLOW, f"{assistant_thoughts_reasoning}")
-    if assistant_thoughts_plan:
-        logger.typewriter_log("PLAN:", Fore.YELLOW, "")
-        # If it's a list, join it into a string
-        if isinstance(assistant_thoughts_plan, list):
-            assistant_thoughts_plan = "\n".join(assistant_thoughts_plan)
-        elif isinstance(assistant_thoughts_plan, dict):
-            assistant_thoughts_plan = str(assistant_thoughts_plan)
-
-        # Split the input_string using the newline character and dashes
-        lines = assistant_thoughts_plan.split("\n")
-        for line in lines:
-            line = line.lstrip("- ")
-            logger.typewriter_log("- ", Fore.GREEN, line.strip())
-    logger.typewriter_log("CRITICISM:", Fore.YELLOW, f"{assistant_thoughts_criticism}")
-    # Speak the assistant's thoughts
-    if speak_mode and assistant_thoughts_speak:
-        say_text(assistant_thoughts_speak)

autogpt/main.py

@@ -1,150 +0,0 @@
-"""The application entry point.  Can be invoked by a CLI or any other front end application."""
-import logging
-import sys
-from pathlib import Path
-
-from colorama import Fore
-
-from autogpt.agent.agent import Agent
-from autogpt.commands.command import CommandRegistry
-from autogpt.config import Config, check_openai_api_key
-from autogpt.configurator import create_config
-from autogpt.logs import logger
-from autogpt.memory import get_memory
-from autogpt.plugins import scan_plugins
-from autogpt.prompts.prompt import DEFAULT_TRIGGERING_PROMPT, construct_main_ai_config
-from autogpt.utils import get_current_git_branch, get_latest_bulletin
-from autogpt.workspace import Workspace
-from scripts.install_plugin_deps import install_plugin_dependencies
-
-
-def run_auto_gpt(
-    continuous: bool,
-    continuous_limit: int,
-    ai_settings: str,
-    skip_reprompt: bool,
-    speak: bool,
-    debug: bool,
-    gpt3only: bool,
-    gpt4only: bool,
-    memory_type: str,
-    browser_name: str,
-    allow_downloads: bool,
-    skip_news: bool,
-    workspace_directory: str,
-    install_plugin_deps: bool,
-):
-    # Configure logging before we do anything else.
-    logger.set_level(logging.DEBUG if debug else logging.INFO)
-    logger.speak_mode = speak
-
-    cfg = Config()
-    # TODO: fill in llm values here
-    check_openai_api_key()
-    create_config(
-        continuous,
-        continuous_limit,
-        ai_settings,
-        skip_reprompt,
-        speak,
-        debug,
-        gpt3only,
-        gpt4only,
-        memory_type,
-        browser_name,
-        allow_downloads,
-        skip_news,
-    )
-
-    if not cfg.skip_news:
-        motd = get_latest_bulletin()
-        if motd:
-            logger.typewriter_log("NEWS: ", Fore.GREEN, motd)
-        git_branch = get_current_git_branch()
-        if git_branch and git_branch != "stable":
-            logger.typewriter_log(
-                "WARNING: ",
-                Fore.RED,
-                f"You are running on `{git_branch}` branch "
-                "- this is not a supported branch.",
-            )
-        if sys.version_info < (3, 10):
-            logger.typewriter_log(
-                "WARNING: ",
-                Fore.RED,
-                "You are running on an older version of Python. "
-                "Some people have observed problems with certain "
-                "parts of Auto-GPT with this version. "
-                "Please consider upgrading to Python 3.10 or higher.",
-            )
-
-    if install_plugin_deps:
-        install_plugin_dependencies()
-
-    # TODO: have this directory live outside the repository (e.g. in a user's
-    #   home directory) and have it come in as a command line argument or part of
-    #   the env file.
-    if workspace_directory is None:
-        workspace_directory = Path(__file__).parent / "auto_gpt_workspace"
-    else:
-        workspace_directory = Path(workspace_directory)
-    # TODO: pass in the ai_settings file and the env file and have them cloned into
-    #   the workspace directory so we can bind them to the agent.
-    workspace_directory = Workspace.make_workspace(workspace_directory)
-    cfg.workspace_path = str(workspace_directory)
-
-    # HACK: doing this here to collect some globals that depend on the workspace.
-    file_logger_path = workspace_directory / "file_logger.txt"
-    if not file_logger_path.exists():
-        with file_logger_path.open(mode="w", encoding="utf-8") as f:
-            f.write("File Operation Logger ")
-
-    cfg.file_logger_path = str(file_logger_path)
-
-    cfg.set_plugins(scan_plugins(cfg, cfg.debug_mode))
-    # Create a CommandRegistry instance and scan default folder
-    command_registry = CommandRegistry()
-    command_registry.import_commands("autogpt.commands.analyze_code")
-    command_registry.import_commands("autogpt.commands.audio_text")
-    command_registry.import_commands("autogpt.commands.execute_code")
-    command_registry.import_commands("autogpt.commands.file_operations")
-    command_registry.import_commands("autogpt.commands.git_operations")
-    command_registry.import_commands("autogpt.commands.google_search")
-    command_registry.import_commands("autogpt.commands.image_gen")
-    command_registry.import_commands("autogpt.commands.improve_code")
-    command_registry.import_commands("autogpt.commands.twitter")
-    command_registry.import_commands("autogpt.commands.web_selenium")
-    command_registry.import_commands("autogpt.commands.write_tests")
-    command_registry.import_commands("autogpt.app")
-
-    ai_name = ""
-    ai_config = construct_main_ai_config()
-    ai_config.command_registry = command_registry
-    # print(prompt)
-    # Initialize variables
-    full_message_history = []
-    next_action_count = 0
-
-    # Initialize memory and make sure it is empty.
-    # this is particularly important for indexing and referencing pinecone memory
-    memory = get_memory(cfg, init=True)
-    logger.typewriter_log(
-        "Using memory of type:", Fore.GREEN, f"{memory.__class__.__name__}"
-    )
-    logger.typewriter_log("Using Browser:", Fore.GREEN, cfg.selenium_web_browser)
-    system_prompt = ai_config.construct_full_prompt()
-    if cfg.debug_mode:
-        logger.typewriter_log("Prompt:", Fore.GREEN, system_prompt)
-
-    agent = Agent(
-        ai_name=ai_name,
-        memory=memory,
-        full_message_history=full_message_history,
-        next_action_count=next_action_count,
-        command_registry=command_registry,
-        config=ai_config,
-        system_prompt=system_prompt,
-        triggering_prompt=DEFAULT_TRIGGERING_PROMPT,
-        workspace_directory=workspace_directory,
-    )
-    agent.start_interaction_loop()

autogpt/memory/__init__.py

@@ -1,96 +0,0 @@
-from autogpt.logs import logger
-from autogpt.memory.local import LocalCache
-from autogpt.memory.no_memory import NoMemory
-
-# List of supported memory backends
-# Add a backend to this list if the import attempt is successful
-supported_memory = ["local", "no_memory"]
-
-try:
-    from autogpt.memory.redismem import RedisMemory
-
-    supported_memory.append("redis")
-except ImportError:
-    RedisMemory = None
-
-try:
-    from autogpt.memory.pinecone import PineconeMemory
-
-    supported_memory.append("pinecone")
-except ImportError:
-    PineconeMemory = None
-
-try:
-    from autogpt.memory.weaviate import WeaviateMemory
-
-    supported_memory.append("weaviate")
-except ImportError:
-    WeaviateMemory = None
-
-try:
-    from autogpt.memory.milvus import MilvusMemory
-
-    supported_memory.append("milvus")
-except ImportError:
-    MilvusMemory = None
-
-
-def get_memory(cfg, init=False):
-    memory = None
-    if cfg.memory_backend == "pinecone":
-        if not PineconeMemory:
-            logger.warn(
-                "Error: Pinecone is not installed. Please install pinecone"
-                " to use Pinecone as a memory backend."
-            )
-        else:
-            memory = PineconeMemory(cfg)
-            if init:
-                memory.clear()
-    elif cfg.memory_backend == "redis":
-        if not RedisMemory:
-            logger.warn(
-                "Error: Redis is not installed. Please install redis-py to"
-                " use Redis as a memory backend."
-            )
-        else:
-            memory = RedisMemory(cfg)
-    elif cfg.memory_backend == "weaviate":
-        if not WeaviateMemory:
-            logger.warn(
-                "Error: Weaviate is not installed. Please install weaviate-client to"
-                " use Weaviate as a memory backend."
-            )
-        else:
-            memory = WeaviateMemory(cfg)
-    elif cfg.memory_backend == "milvus":
-        if not MilvusMemory:
-            logger.warn(
-                "Error: pymilvus sdk is not installed."
-                "Please install pymilvus to use Milvus or Zilliz Cloud as memory backend."
-            )
-        else:
-            memory = MilvusMemory(cfg)
-    elif cfg.memory_backend == "no_memory":
-        memory = NoMemory(cfg)
-
-    if memory is None:
-        memory = LocalCache(cfg)
-        if init:
-            memory.clear()
-    return memory
-
-
-def get_supported_memory_backends():
-    return supported_memory
-
-
-__all__ = [
-    "get_memory",
-    "LocalCache",
-    "RedisMemory",
-    "PineconeMemory",
-    "NoMemory",
-    "MilvusMemory",
-    "WeaviateMemory",
-]

autogpt/memory/base.py

@@ -1,31 +0,0 @@
-"""Base class for memory providers."""
-import abc
-
-from autogpt.singleton import AbstractSingleton
-
-
-class MemoryProviderSingleton(AbstractSingleton):
-    @abc.abstractmethod
-    def add(self, data):
-        """Adds to memory"""
-        pass
-
-    @abc.abstractmethod
-    def get(self, data):
-        """Gets from memory"""
-        pass
-
-    @abc.abstractmethod
-    def clear(self):
-        """Clears memory"""
-        pass
-
-    @abc.abstractmethod
-    def get_relevant(self, data, num_relevant=5):
-        """Gets relevant memory for"""
-        pass
-
-    @abc.abstractmethod
-    def get_stats(self):
-        """Get stats from memory"""
-        pass