Revert

- Add two endpoints to OAuth `integrations.py`:
  - `GET /integrations/{provider}/credentials` - list all credentials for a provider, without secrets (metadata only)
   - `GET /integrations/{provider}/credentials/{cred_id}` - retrieve a set of credentials (including secrets)

- Add `username` property to `Credentials` types
   - Add logic to populate `username` in OAuth handlers

- Expand `CredentialsMetaResponse` and remove `credentials_` prefix from properties

- Fix `autogpt_libs` dependency caching issue

- Remove accidentally duplicated OAuth handler files in `autogpt_server/integrations`

.dockerignore

@@ -23,6 +23,18 @@
 # Frontend
 !frontend/build/web/
 
+# rnd
+!rnd/
+
 # Explicitly re-ignore some folders
 .*
 **/__pycache__
+# rnd
+rnd/autogpt_builder/.next/
+rnd/autogpt_builder/node_modules
+rnd/autogpt_builder/.env.example
+rnd/autogpt_builder/.env.local
+rnd/autogpt_server/.env
+rnd/autogpt_server/.venv/
+
+rnd/market/.env

.gitattributes

@@ -3,3 +3,8 @@ frontend/build/** linguist-generated
 **/poetry.lock linguist-generated
 
 docs/_javascript/** linguist-vendored
+
+# Exclude VCR cassettes from stats
+forge/tests/vcr_cassettes/**/**.y*ml linguist-generated
+
+* text=auto

.github/CODEOWNERS

@@ -1,5 +1,7 @@
-.github/workflows/  @Significant-Gravitas/devops
-autogpt/   @Significant-Gravitas/maintainers
-forge/     @Significant-Gravitas/forge-maintainers
-benchmark/          @Significant-Gravitas/benchmark-maintainers
-frontend/           @Significant-Gravitas/frontend-maintainers
+* @Significant-Gravitas/maintainers
+.github/workflows/ @Significant-Gravitas/devops
+forge/ @Significant-Gravitas/forge-maintainers
+benchmark/ @Significant-Gravitas/benchmark-maintainers
+frontend/ @Significant-Gravitas/frontend-maintainers
+rnd/infra @Significant-Gravitas/devops
+.github/CODEOWNERS @Significant-Gravitas/admins

.github/ISSUE_TEMPLATE/1.bug.yml

@@ -88,14 +88,16 @@ body:
 
   - type: dropdown
     attributes:
-      label: Do you use OpenAI GPT-3 or GPT-4?
+      label: What LLM Provider do you use?
       description: >
         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
-        - GPT-4(32k)
+        - Azure
+        - Groq
+        - Anthropic
+        - Llamafile
+        - Other (detail in issue)
     validations:
       required: true
 
@@ -126,6 +128,13 @@ body:
             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: Describe your issue.

.github/labeler.yml

@@ -17,3 +17,11 @@ Frontend:
 documentation:
 - changed-files:
   - any-glob-to-any-file: docs/**
+
+Builder:
+- changed-files:
+  - any-glob-to-any-file: rnd/autogpt_builder/**
+
+Server:
+- changed-files:
+  - any-glob-to-any-file: rnd/autogpt_server/**

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

@@ -0,0 +1,41 @@
+name: AutoGPT Builder CI
+
+on:
+  push:
+    branches: [ master ]
+    paths:
+      - '.github/workflows/autogpt-builder-ci.yml'
+      - 'rnd/autogpt_builder/**'
+  pull_request:
+    paths:
+      - '.github/workflows/autogpt-builder-ci.yml'
+      - 'rnd/autogpt_builder/**'
+
+defaults:
+  run:
+    shell: bash
+    working-directory: rnd/autogpt_builder
+
+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: |
+        npm install
+
+    - name: Check formatting with Prettier
+      run: |
+        npx prettier --check .
+
+    - name: Run lint
+      run: |
+        npm run lint

.github/workflows/autogpt-ci.yml

@@ -6,13 +6,11 @@ on:
     paths:
       - '.github/workflows/autogpt-ci.yml'
       - 'autogpt/**'
-      - '!autogpt/tests/vcr_cassettes'
   pull_request:
     branches: [ master, development, release-* ]
     paths:
       - '.github/workflows/autogpt-ci.yml'
       - 'autogpt/**'
-      - '!autogpt/tests/vcr_cassettes'
 
 concurrency:
   group: ${{ format('autogpt-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
@@ -73,37 +71,6 @@ jobs:
           git config --global user.name "Auto-GPT-Bot"
           git config --global user.email "github-bot@agpt.co"
 
-      - 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:
@@ -163,80 +130,6 @@ jobs:
           token: ${{ secrets.CODECOV_TOKEN }}
           flags: autogpt-agent,${{ 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

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

@@ -6,13 +6,11 @@ on:
     paths:
       - '.github/workflows/autogpt-docker-ci.yml'
       - 'autogpt/**'
-      - '!autogpt/tests/vcr_cassettes'
   pull_request:
     branches: [ master, development, release-* ]
     paths:
       - '.github/workflows/autogpt-docker-ci.yml'
       - 'autogpt/**'
-      - '!autogpt/tests/vcr_cassettes'
 
 concurrency:
   group: ${{ format('autogpt-docker-ci-{0}', github.head_ref && format('pr-{0}', github.event.pull_request.number) || github.sha) }}

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

@@ -0,0 +1,56 @@
+name: AutoGPT Builder Infra
+
+on:
+  push:
+    branches: [ master ]
+    paths:
+      - '.github/workflows/autogpt-infra-ci.yml'
+      - 'rnd/infra/**'
+  pull_request:
+    paths:
+      - '.github/workflows/autogpt-infra-ci.yml'
+      - 'rnd/infra/**'
+
+defaults:
+  run:
+    shell: bash
+    working-directory: rnd/infra
+
+jobs:
+  lint:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v2
+        with:
+          fetch-depth: 0
+
+      - name: TFLint
+        uses: pauloconnor/tflint-action@v0.0.2
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        with:
+            tflint_path: terraform/
+            tflint_recurse: true
+            tflint_changed_only: false
+
+      - name: Set up Helm
+        uses: azure/setup-helm@v4.2.0
+        with:
+          version: v3.14.4
+
+      - name: Set up chart-testing
+        uses: helm/chart-testing-action@v2.6.0
+
+      - name: Run chart-testing (list-changed)
+        id: list-changed
+        run: |
+          changed=$(ct list-changed --target-branch ${{ github.event.repository.default_branch }})
+          if [[ -n "$changed" ]]; then
+            echo "changed=true" >> "$GITHUB_OUTPUT"
+          fi
+
+      - name: Run chart-testing (lint)
+        if: steps.list-changed.outputs.changed == 'true'
+        run: ct lint --target-branch ${{ github.event.repository.default_branch }}

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

@@ -6,13 +6,11 @@ on:
     paths:
       - ".github/workflows/autogpt-server-ci.yml"
       - "rnd/autogpt_server/**"
-      - "!autogpt/tests/vcr_cassettes"
   pull_request:
     branches: [master, development, release-*]
     paths:
       - ".github/workflows/autogpt-server-ci.yml"
       - "rnd/autogpt_server/**"
-      - "!autogpt/tests/vcr_cassettes"
 
 concurrency:
   group: ${{ format('autogpt-server-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}
@@ -36,6 +34,15 @@ jobs:
     runs-on: ${{ matrix.platform-os != 'macos-arm64' && format('{0}-latest', matrix.platform-os) || 'macos-14' }}
 
     steps:
+      - name: Setup PostgreSQL
+        uses: ikalnytskyi/action-setup-postgres@v6
+        with:
+          username: ${{ secrets.DB_USER || 'postgres' }}
+          password: ${{ secrets.DB_PASS || 'postgres' }}
+          database: postgres
+          port: 5432
+        id: postgres
+
       # Quite slow on macOS (2~4 minutes to set up Docker)
       # - name: Set up Docker (macOS)
       #   if: runner.os == 'macOS'
@@ -112,157 +119,37 @@ jobs:
 
       - name: Run Database Migrations
         run: poetry run prisma migrate dev --name updates
+        env:
+          CONNECTION_STR: ${{ steps.postgres.outputs.connection-uri }}
+
+      - id: lint
+        name: Run Linter
+        run: poetry run lint
 
       - name: Run pytest with coverage
         run: |
-          poetry run pytest -vv \
-            test
+          if [[ "${{ runner.debug }}" == "1" ]]; then
+            poetry run pytest -vv -o log_cli=true -o log_cli_level=DEBUG test
+          else
+            poetry run pytest -vv test
+          fi
+        if: success() || (failure() && steps.lint.outcome == 'failure')
         env:
-          CI: true
-          PLAIN_OUTPUT: True
+          LOG_LEVEL: ${{ runner.debug && 'DEBUG' || 'INFO' }}
+    env:
+      CI: true
+      PLAIN_OUTPUT: True
+      OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+      DB_USER: ${{ secrets.DB_USER || 'postgres' }}
+      DB_PASS: ${{ secrets.DB_PASS || 'postgres' }}
+      DB_NAME: postgres
+      DB_PORT: 5432
+      RUN_ENV: local
+      PORT: 8080
+      DATABASE_URL: postgresql://${{ secrets.DB_USER || 'postgres' }}:${{ secrets.DB_PASS || 'postgres' }}@localhost:5432/${{ secrets.DB_NAME || 'postgres'}}
 
       # - name: Upload coverage reports to Codecov
       #   uses: codecov/codecov-action@v4
       #   with:
       #     token: ${{ secrets.CODECOV_TOKEN }}
       #     flags: autogpt-server,${{ runner.os }}
-
-  build:
-    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:
-      - 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: ${{ matrix.python-version }}
-
-      - id: get_date
-        name: Get date
-        run: echo "date=$(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 }}-${{ hashFiles('rnd/autogpt_server/poetry.lock') }}
-
-      - name: Install Poetry (Unix)
-        if: runner.os != 'Windows'
-        run: |
-          curl -sSL https://install.python-poetry.org | python3 -
-
-          if [ "${{ 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" >> $env:GITHUB_PATH
-
-      - name: Install Python dependencies
-        run: poetry install
-
-      - name: Generate Prisma Client
-        run: poetry run prisma generate
-
-      - name: Run Database Migrations
-        run: poetry run prisma migrate dev --name updates
-
-      - name: install rpm
-        if: matrix.platform-os == 'ubuntu'
-        run: sudo apt-get install -y alien fakeroot rpm
-
-      - name: Build distribution
-        run: |
-          case "${{ matrix.platform-os }}" in
-            "macos" | "macos-arm64")
-              ${MAC_COMMAND}
-              ;;
-            "windows")
-              ${WINDOWS_COMMAND}
-              ;;
-            *)
-              ${LINUX_COMMAND}
-              ;;
-          esac
-        env:
-          MAC_COMMAND: "poetry run poe dist_dmg"
-          WINDOWS_COMMAND: "poetry run poe dist_msi"
-          LINUX_COMMAND: "poetry run poe dist_appimage"
-
-      # break this into seperate steps each with their own name that matches the file
-      - name: Upload App artifact
-        uses: actions/upload-artifact@v4
-        with:
-          name: autogptserver-app-${{ matrix.platform-os }}
-          path: /Users/runner/work/AutoGPT/AutoGPT/rnd/autogpt_server/build/*.app
-
-      - name: Upload dmg artifact
-        uses: actions/upload-artifact@v4
-        with:
-          name: autogptserver-dmg-${{ matrix.platform-os }}
-          path: /Users/runner/work/AutoGPT/AutoGPT/rnd/autogpt_server/build/AutoGPTServer.dmg
-
-      - name: Upload msi artifact
-        uses: actions/upload-artifact@v4
-        with:
-          name: autogptserver-msi-${{ matrix.platform-os }}
-          path: D:\a\AutoGPT\AutoGPT\rnd\autogpt_server\dist\*.msi
-
-      - name: Upload deb artifact
-        uses: actions/upload-artifact@v4
-        with:
-          name: autogptserver-deb-${{ matrix.platform-os }}
-          path: /Users/runner/work/AutoGPT/AutoGPT/rnd/autogpt_server/build/*.deb
-
-      - name: Upload rpm artifact
-        uses: actions/upload-artifact@v4
-        with:
-          name: autogptserver-rpm-${{ matrix.platform-os }}
-          path: /Users/runner/work/AutoGPT/AutoGPT/rnd/autogpt_server/build/*.rpm
-
-      - name: Upload tar.gz artifact
-        uses: actions/upload-artifact@v4
-        with:
-          name: autogptserver-tar.gz-${{ matrix.platform-os }}
-          path: /Users/runner/work/AutoGPT/AutoGPT/rnd/autogpt_server/build/*.tar.gz
-
-      - name: Upload zip artifact
-        uses: actions/upload-artifact@v4
-        with:
-          name: autogptserver-zip-${{ matrix.platform-os }}
-          path: /Users/runner/work/AutoGPT/AutoGPT/rnd/autogpt_server/build/*.zip
-
-      - name: Upload pkg artifact
-        uses: actions/upload-artifact@v4
-        with:
-          name: autogptserver-pkg-${{ matrix.platform-os }}
-          path: /Users/runner/work/AutoGPT/AutoGPT/rnd/autogpt_server/build/*.pkg
-
-      - name: Upload AppImage artifact
-        uses: actions/upload-artifact@v4
-        with:
-          name: autogptserver-AppImage-${{ matrix.platform-os }}
-          path: /Users/runner/work/AutoGPT/AutoGPT/rnd/autogpt_server/build/*.AppImage

.github/workflows/forge-ci.yml

@@ -6,11 +6,13 @@ on:
     paths:
       - '.github/workflows/forge-ci.yml'
       - 'forge/**'
+      - '!forge/tests/vcr_cassettes'
   pull_request:
     branches: [ master, development, release-* ]
     paths:
       - '.github/workflows/forge-ci.yml'
       - 'forge/**'
+      - '!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) }}
@@ -66,6 +68,37 @@ jobs:
           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:
@@ -121,6 +154,80 @@ jobs:
           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

.github/workflows/pr-label.yml

@@ -5,7 +5,7 @@ on:
   push:
     branches: [ master, development, release-* ]
     paths-ignore:
-      - 'autogpt/tests/vcr_cassettes'
+      - 'forge/tests/vcr_cassettes'
       - 'benchmark/reports/**'
   # So that the `dirtyLabel` is removed if conflicts are resolve
   # We recommend `pull_request_target` so that github secrets are available.

.github/workflows/python-checks.yml

@@ -9,7 +9,7 @@ on:
       - 'forge/**'
       - 'benchmark/**'
       - '**.py'
-      - '!autogpt/tests/vcr_cassettes'
+      - '!forge/tests/vcr_cassettes'
   pull_request:
     branches: [ master, development, release-* ]
     paths:
@@ -18,7 +18,7 @@ on:
       - 'forge/**'
       - 'benchmark/**'
       - '**.py'
-      - '!autogpt/tests/vcr_cassettes'
+      - '!forge/tests/vcr_cassettes'
 
 concurrency:
   group: ${{ format('lint-ci-{0}', github.head_ref && format('{0}-{1}', github.event_name, github.event.pull_request.number) || github.sha) }}

.github/workflows/workflow-checker.yml

@@ -0,0 +1,31 @@
+name: PR Status Checker
+on:
+  pull_request:
+    types: [opened, synchronize, reopened]
+
+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 check_actions_status.py
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

.gitignore

@@ -32,7 +32,6 @@ dist/
 downloads/
 eggs/
 .eggs/
-lib/
 lib64/
 parts/
 sdist/
@@ -170,3 +169,5 @@ pri*
 # ignore
 ig*
 .github_access_token
+LICENSE.rtf
+rnd/autogpt_server/settings.py

.gitmodules

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

.pre-commit-config.yaml

@@ -97,7 +97,7 @@ repos:
         alias: pyright-benchmark
         entry: poetry -C benchmark run pyright
         args: [-p, benchmark, benchmark]
-        files: ^benchmark/(agbenchmark|tests)/
+        files: ^benchmark/(agbenchmark/|tests/|poetry\.lock$)
         types: [file]
         language: system
         pass_filenames: false

.vscode/all-projects.code-workspace

@@ -0,0 +1,61 @@
+{
+  "folders": [
+    {
+      "name": "autogpt",
+      "path": "../autogpt"
+    },
+    {
+      "name": "benchmark",
+      "path": "../benchmark"
+    },
+    {
+      "name": "docs",
+      "path": "../docs"
+    },
+    {
+      "name": "forge",
+      "path": "../forge"
+    },
+    {
+      "name": "frontend",
+      "path": "../frontend"
+    },
+    {
+      "name": "autogpt_server",
+      "path": "../rnd/autogpt_server"
+    },
+    {
+      "name": "autogpt_builder",
+      "path": "../rnd/autogpt_builder"
+    },
+    {
+      "name": "market",
+      "path": "../rnd/market"
+    },
+    {
+      "name": "lib",
+      "path": "../rnd/autogpt_libs"
+    },
+    {
+      "name": "infra",
+      "path": "../rnd/infra"
+    },
+    {
+      "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"
+    ]
+  }
+}

README.md

@@ -1,17 +1,43 @@
-# AutoGPT: build & use AI agents
+# AutoGPT: Build & Use AI Agents
 
 [![Discord Follow](https://dcbadge.vercel.app/api/server/autogpt?style=flat)](https://discord.gg/autogpt)  
 [![Twitter Follow](https://img.shields.io/twitter/follow/Auto_GPT?style=social)](https://twitter.com/Auto_GPT)  
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
 
-**AutoGPT** is a generalist LLM based AI agent that can autonomously accomplish minor tasks. 
+**AutoGPT** is a powerful tool that lets you create and run intelligent agents. These agents can perform various tasks automatically, making your life easier.
 
-**Examples**:
+## How to Get Started
 
-- Look up and summarize this research paper
-- Write a marketing for food supplements
-- Write a blog post detailing the news in AI
+https://github.com/user-attachments/assets/8508f4dc-b362-4cab-900f-644964a96cdf
 
+### 🧱 AutoGPT Builder 
+
+The AutoGPT Builder is the frontend. It allows you to design agents using an easy flowchart style. You build your agent by connecting blocks, where each block performs a single action. It's simple and intuitive!
+
+[Read this guide](https://docs.agpt.co/server/new_blocks/) to learn how to build your own custom blocks.
+
+### 💽 AutoGPT Server
+
+The AutoGPT Server is the backend. This is where your agents run. Once deployed, agents can be triggered by external sources and can operate continuously.
+
+### 🐙 Example Agents
+
+Here are two examples of what you can do with AutoGPT:
+
+1. **Reddit Marketing Agent**
+   - This agent reads comments on Reddit.
+   - It looks for people asking about your product.
+   - It then automatically responds to them.
+
+2. **YouTube Content Repurposing Agent**
+   - This agent subscribes to your YouTube channel.
+   - When you post a new video, it transcribes it.
+   - It uses AI to write a search engine optimized blog post.
+   - Then, it publishes this blog post to your Medium account.
+
+These examples show just a glimpse of what you can achieve with AutoGPT!
+
+---
 Our mission is to provide the tools, so that you can focus on what matters:
 
 - 🏗️ **Building** - Lay the foundation for something amazing.
@@ -23,11 +49,13 @@ Be part of the revolution! **AutoGPT** is here to stay, at the forefront of AI i
 **📖 [Documentation](https://docs.agpt.co)**
  | 
 **🚀 [Contributing](CONTRIBUTING.md)**
- | 
-**🛠️ [Build your own Agent - Quickstart](QUICKSTART.md)**
 
-## 🧱 Building blocks
 
+---
+## 🤖 AutoGPT Classic
+> Below is information about the classic version of AutoGPT.
+
+**🛠️ [Build your own Agent - Quickstart](FORGE-QUICKSTART.md)**
 ### 🏗️ Forge
 
 **Forge your own agent!** – Forge is a ready-to-go template for your agent application. All the boilerplate code is already handled, letting you channel all your creativity into the things that set *your* agent apart. All tutorials are located [here](https://medium.com/@aiedge/autogpt-forge-e3de53cc58ec). Components from the [`forge.sdk`](/forge/forge/sdk) can also be used individually to speed up development and reduce boilerplate in your agent project.

autogpt/.env.template

@@ -11,6 +11,9 @@
 ## GROQ_API_KEY - Groq API Key (Example: gsk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx)
 # GROQ_API_KEY=
 
+## LLAMAFILE_API_BASE - Llamafile API base URL
+# LLAMAFILE_API_BASE=http://localhost:8080/v1
+
 ## TELEMETRY_OPT_IN - Share telemetry on errors and other issues with the AutoGPT team, e.g. through Sentry.
 ##   This helps us to spot and solve problems earlier & faster. (Default: DISABLED)
 # TELEMETRY_OPT_IN=true
@@ -102,6 +105,7 @@
 ## HUGGINGFACE_API_TOKEN - HuggingFace API token (Default: None)
 # HUGGINGFACE_API_TOKEN=
 
+
 ### Stable Diffusion (IMAGE_PROVIDER=sdwebui)
 
 ## SD_WEBUI_AUTH - Stable Diffusion Web UI username:password pair (Default: None)

autogpt/.gitattributes

@@ -1,5 +0,0 @@
-# Exclude VCR cassettes from stats
-tests/vcr_cassettes/**/**.y*ml linguist-generated
-
-# Mark documentation as such
-docs/**.md linguist-documentation

autogpt/.vscode/settings.json

@@ -0,0 +1,3 @@
+{
+  "python.analysis.typeCheckingMode": "basic",
+}

autogpt/autogpt/agent_factory/configurators.py

@@ -104,5 +104,5 @@ def create_agent_state(
             allow_fs_access=not app_config.restrict_to_workspace,
             use_functions_api=app_config.openai_functions,
         ),
-        history=Agent.default_settings.history.copy(deep=True),
+        history=Agent.default_settings.history.model_copy(deep=True),
     )

autogpt/autogpt/agent_factory/profile_generator.py

@@ -19,7 +19,7 @@ logger = logging.getLogger(__name__)
 
 
 class AgentProfileGeneratorConfiguration(SystemConfiguration):
-    model_classification: LanguageModelClassification = UserConfigurable(
+    llm_classification: LanguageModelClassification = UserConfigurable(
         default=LanguageModelClassification.SMART_MODEL
     )
     _example_call: object = {
@@ -137,7 +137,7 @@ class AgentProfileGeneratorConfiguration(SystemConfiguration):
                     required=True,
                 ),
             },
-        ).dict()
+        ).model_dump()
     )
 
 
@@ -148,21 +148,21 @@ class AgentProfileGenerator(PromptStrategy):
 
     def __init__(
         self,
-        model_classification: LanguageModelClassification,
+        llm_classification: LanguageModelClassification,
         system_prompt: str,
         user_prompt_template: str,
         create_agent_function: dict,
     ):
-        self._model_classification = model_classification
+        self._llm_classification = llm_classification
         self._system_prompt_message = system_prompt
         self._user_prompt_template = user_prompt_template
-        self._create_agent_function = CompletionModelFunction.parse_obj(
+        self._create_agent_function = CompletionModelFunction.model_validate(
             create_agent_function
         )
 
     @property
-    def model_classification(self) -> LanguageModelClassification:
-        return self._model_classification
+    def llm_classification(self) -> LanguageModelClassification:
+        return self._llm_classification
 
     def build_prompt(self, user_objective: str = "", **kwargs) -> ChatPrompt:
         system_message = ChatMessage.system(self._system_prompt_message)
@@ -222,7 +222,7 @@ async def generate_agent_profile_for_task(
     AIConfig: The AIConfig object tailored to the user's input
     """
     agent_profile_generator = AgentProfileGenerator(
-        **AgentProfileGenerator.default_configuration.dict()  # HACK
+        **AgentProfileGenerator.default_configuration.model_dump()  # HACK
     )
 
     prompt = agent_profile_generator.build_prompt(task)

autogpt/autogpt/agents/agent.py

@@ -100,7 +100,9 @@ class Agent(BaseAgent[OneShotAgentActionProposal], Configurable[AgentSettings]):
         super().__init__(settings)
 
         self.llm_provider = llm_provider
-        prompt_config = OneShotAgentPromptStrategy.default_configuration.copy(deep=True)
+        prompt_config = OneShotAgentPromptStrategy.default_configuration.model_copy(
+            deep=True
+        )
         prompt_config.use_functions_api = (
             settings.config.use_functions_api
             # Anthropic currently doesn't support tools + prefilling :(
@@ -111,14 +113,18 @@ class Agent(BaseAgent[OneShotAgentActionProposal], Configurable[AgentSettings]):
 
         # Components
         self.system = SystemComponent()
-        self.history = ActionHistoryComponent(
-            settings.history,
-            lambda x: self.llm_provider.count_tokens(x, self.llm.name),
-            llm_provider,
-            ActionHistoryConfiguration(
-                model_name=app_config.fast_llm, max_tokens=self.send_token_limit
-            ),
-        ).run_after(WatchdogComponent)
+        self.history = (
+            ActionHistoryComponent(
+                settings.history,
+                lambda x: self.llm_provider.count_tokens(x, self.llm.name),
+                llm_provider,
+                ActionHistoryConfiguration(
+                    llm_name=app_config.fast_llm, max_tokens=self.send_token_limit
+                ),
+            )
+            .run_after(WatchdogComponent)
+            .run_after(SystemComponent)
+        )
         if not app_config.noninteractive_mode:
             self.user_interaction = UserInteractionComponent()
         self.file_manager = FileManagerComponent(file_storage, settings)
@@ -156,7 +162,7 @@ class Agent(BaseAgent[OneShotAgentActionProposal], Configurable[AgentSettings]):
         constraints = await self.run_pipeline(DirectiveProvider.get_constraints)
         best_practices = await self.run_pipeline(DirectiveProvider.get_best_practices)
 
-        directives = self.state.directives.copy(deep=True)
+        directives = self.state.directives.model_copy(deep=True)
         directives.resources += resources
         directives.constraints += constraints
         directives.best_practices += best_practices
@@ -168,13 +174,19 @@ class Agent(BaseAgent[OneShotAgentActionProposal], Configurable[AgentSettings]):
         # Get messages
         messages = await self.run_pipeline(MessageProvider.get_messages)
 
+        include_os_info = (
+            self.code_executor.config.execute_local_commands
+            if hasattr(self, "code_executor")
+            else False
+        )
+
         prompt: ChatPrompt = self.prompt_strategy.build_prompt(
             messages=messages,
             task=self.state.task,
             ai_profile=self.state.ai_profile,
             ai_directives=directives,
             commands=function_specs_from_commands(self.commands),
-            include_os_info=self.code_executor.config.execute_local_commands,
+            include_os_info=include_os_info,
         )
 
         logger.debug(f"Executing prompt:\n{dump_prompt(prompt)}")

autogpt/autogpt/agents/prompt_strategies/one_shot.py

@@ -28,15 +28,13 @@ _RESPONSE_INTERFACE_NAME = "AssistantResponse"
 
 class AssistantThoughts(ModelWithSummary):
     observations: str = Field(
-        ..., description="Relevant observations from your last action (if any)"
+        description="Relevant observations from your last action (if any)"
     )
-    text: str = Field(..., description="Thoughts")
-    reasoning: str = Field(..., description="Reasoning behind the thoughts")
-    self_criticism: str = Field(..., description="Constructive self-criticism")
-    plan: list[str] = Field(
-        ..., description="Short list that conveys the long-term plan"
-    )
-    speak: str = Field(..., description="Summary of thoughts, to say to user")
+    text: str = Field(description="Thoughts")
+    reasoning: str = Field(description="Reasoning behind the thoughts")
+    self_criticism: str = Field(description="Constructive self-criticism")
+    plan: list[str] = Field(description="Short list that conveys the long-term plan")
+    speak: str = Field(description="Summary of thoughts, to say to user")
 
     def summary(self) -> str:
         return self.text
@@ -96,11 +94,13 @@ class OneShotAgentPromptStrategy(PromptStrategy):
         logger: Logger,
     ):
         self.config = configuration
-        self.response_schema = JSONSchema.from_dict(OneShotAgentActionProposal.schema())
+        self.response_schema = JSONSchema.from_dict(
+            OneShotAgentActionProposal.model_json_schema()
+        )
         self.logger = logger
 
     @property
-    def model_classification(self) -> LanguageModelClassification:
+    def llm_classification(self) -> LanguageModelClassification:
         return LanguageModelClassification.FAST_MODEL  # FIXME: dynamic switching
 
     def build_prompt(
@@ -182,7 +182,7 @@ class OneShotAgentPromptStrategy(PromptStrategy):
         )
 
     def response_format_instruction(self, use_functions_api: bool) -> tuple[str, str]:
-        response_schema = self.response_schema.copy(deep=True)
+        response_schema = self.response_schema.model_copy(deep=True)
         assert response_schema.properties
         if use_functions_api and "use_tool" in response_schema.properties:
             del response_schema.properties["use_tool"]
@@ -274,5 +274,8 @@ class OneShotAgentPromptStrategy(PromptStrategy):
                 raise InvalidAgentResponseError("Assistant did not use a tool")
             assistant_reply_dict["use_tool"] = response.tool_calls[0].function
 
-        parsed_response = OneShotAgentActionProposal.parse_obj(assistant_reply_dict)
+        parsed_response = OneShotAgentActionProposal.model_validate(
+            assistant_reply_dict
+        )
+        parsed_response.raw_message = response.copy()
         return parsed_response

autogpt/autogpt/app/agent_protocol_server.py

@@ -314,7 +314,7 @@ class AgentProtocolServer:
                             ""
                             if tool_result is None
                             else (
-                                orjson.loads(tool_result.json())
+                                orjson.loads(tool_result.model_dump_json())
                                 if not isinstance(tool_result, ActionErrorResult)
                                 else {
                                     "error": str(tool_result.error),
@@ -327,7 +327,7 @@ class AgentProtocolServer:
                 if last_proposal and tool_result
                 else {}
             ),
-            **assistant_response.dict(),
+            **assistant_response.model_dump(),
         }
 
         task_cumulative_cost = agent.llm_provider.get_incurred_cost()
@@ -451,7 +451,9 @@ class AgentProtocolServer:
         """
         task_llm_budget = self._task_budgets[task.task_id]
 
-        task_llm_provider_config = self.llm_provider._configuration.copy(deep=True)
+        task_llm_provider_config = self.llm_provider._configuration.model_copy(
+            deep=True
+        )
         _extra_request_headers = task_llm_provider_config.extra_request_headers
         _extra_request_headers["AP-TaskID"] = task.task_id
         if step_id:
@@ -459,7 +461,7 @@ class AgentProtocolServer:
         if task.additional_input and (user_id := task.additional_input.get("user_id")):
             _extra_request_headers["AutoGPT-UserID"] = user_id
 
-        settings = self.llm_provider._settings.copy()
+        settings = self.llm_provider._settings.model_copy()
         settings.budget = task_llm_budget
         settings.configuration = task_llm_provider_config
         task_llm_provider = self.llm_provider.__class__(

autogpt/autogpt/app/cli.py

@@ -113,7 +113,7 @@ def cli(ctx: click.Context):
 @click.option(
     "--component-config-file",
     help="Path to a json configuration file",
-    type=click.Path(exists=True, dir_okay=False, resolve_path=True),
+    type=click.Path(exists=True, dir_okay=False, resolve_path=True, path_type=Path),
 )
 def run(
     continuous: bool,

autogpt/autogpt/app/config.py

@@ -5,7 +5,7 @@ import logging
 import os
 import re
 from pathlib import Path
-from typing import Any, Optional, Union
+from typing import Optional, Union
 
 import forge
 from forge.config.base import BaseConfig
@@ -13,7 +13,7 @@ from forge.llm.providers import CHAT_MODELS, ModelName
 from forge.llm.providers.openai import OpenAICredentials, OpenAIModelName
 from forge.logging.config import LoggingConfig
 from forge.models.config import Configurable, UserConfigurable
-from pydantic import SecretStr, validator
+from pydantic import SecretStr, ValidationInfo, field_validator
 
 logger = logging.getLogger(__name__)
 
@@ -91,15 +91,15 @@ class AppConfig(BaseConfig):
         default=AZURE_CONFIG_FILE, from_env="AZURE_CONFIG_FILE"
     )
 
-    @validator("openai_functions")
-    def validate_openai_functions(cls, v: bool, values: dict[str, Any]):
-        if v:
-            smart_llm = values["smart_llm"]
+    @field_validator("openai_functions")
+    def validate_openai_functions(cls, value: bool, info: ValidationInfo):
+        if value:
+            smart_llm = info.data["smart_llm"]
             assert CHAT_MODELS[smart_llm].has_function_call_api, (
                 f"Model {smart_llm} does not support tool calling. "
                 "Please disable OPENAI_FUNCTIONS or choose a suitable model."
             )
-        return v
+        return value
 
 
 class ConfigBuilder(Configurable[AppConfig]):

autogpt/autogpt/app/configurator.py

@@ -51,8 +51,9 @@ async def apply_overrides_to_config(
         raise click.UsageError("--continuous-limit can only be used with --continuous")
 
     # Check availability of configured LLMs; fallback to other LLM if unavailable
-    config.fast_llm = await check_model(config.fast_llm, "fast_llm")
-    config.smart_llm = await check_model(config.smart_llm, "smart_llm")
+    config.fast_llm, config.smart_llm = await check_models(
+        (config.fast_llm, "fast_llm"), (config.smart_llm, "smart_llm")
+    )
 
     if skip_reprompt:
         config.skip_reprompt = True
@@ -61,17 +62,22 @@ async def apply_overrides_to_config(
         config.skip_news = True
 
 
-async def check_model(
-    model_name: ModelName, model_type: Literal["smart_llm", "fast_llm"]
-) -> ModelName:
+async def check_models(
+    *models: tuple[ModelName, Literal["smart_llm", "fast_llm"]]
+) -> tuple[ModelName, ...]:
     """Check if model is available for use. If not, return gpt-3.5-turbo."""
     multi_provider = MultiProvider()
-    models = await multi_provider.get_available_chat_models()
+    available_models = await multi_provider.get_available_chat_models()
 
-    if any(model_name == m.name for m in models):
-        return model_name
+    checked_models: list[ModelName] = []
+    for model, model_type in models:
+        if any(model == m.name for m in available_models):
+            checked_models.append(model)
+        else:
+            logger.warning(
+                f"You don't have access to {model}. "
+                f"Setting {model_type} to {GPT_3_MODEL}."
+            )
+            checked_models.append(GPT_3_MODEL)
 
-    logger.warning(
-        f"You don't have access to {model_name}. Setting {model_type} to {GPT_3_MODEL}."
-    )
-    return GPT_3_MODEL
+    return tuple(checked_models)

autogpt/poetry.lock

@@ -10,7 +10,7 @@ files = []
 develop = false
 
 [package.dependencies]
-agent-protocol-client = "^1.1.0"
+agent-protocol-client = {git = "https://github.com/Significant-Gravitas/agent-protocol.git", subdirectory = "packages/client/python"}
 click = "^8.1.3"
 click-default-group = "^1.2.4"
 colorama = "^0.4.6"
@@ -18,14 +18,16 @@ fastapi = "^0.109.1"
 gitpython = "^3.1.32"
 httpx = "^0.24.0"
 matplotlib = "^3.7.2"
+multidict = "^6.0.5"
 networkx = "^3.1"
 openai = "^1.7.2"
 pandas = "^2.0.3"
 pexpect = "^4.8.0"
 psutil = "^5.9.5"
-pydantic = "^1.10.9"
+pydantic = "^2.7.2"
+pydantic-settings = "^2.3.4"
 pytest = "^7.3.2"
-pytest-asyncio = "^0.21.1"
+pytest-asyncio = "^0.23.3"
 python-dotenv = "^1.0.0"
 python-multipart = "^0.0.7"
 pyvis = "^0.3.2"
@@ -33,8 +35,7 @@ requests = "^2.31.0"
 selenium = "^4.11.2"
 tabulate = "^0.9.0"
 toml = "^0.10.2"
-types-requests = "^2.31.0.1"
-uvicorn = "^0.23.2"
+uvicorn = ">=0.23.2,<1"
 
 [package.source]
 type = "directory"
@@ -45,17 +46,22 @@ name = "agent-protocol-client"
 version = "1.1.0"
 description = "Agent Communication Protocol Client"
 optional = true
-python-versions = ">=3.7,<4.0"
-files = [
-    {file = "agent_protocol_client-1.1.0-py3-none-any.whl", hash = "sha256:0e8c6c97244189666ed18e320410abddce8c9dfb75437da1e590bbef3b6268be"},
-    {file = "agent_protocol_client-1.1.0.tar.gz", hash = "sha256:aa7e1042de1249477fdc29c2df08a44f2233dade9c02c1279e37c98e9d3a0d72"},
-]
+python-versions = "^3.7"
+files = []
+develop = false
 
 [package.dependencies]
-aiohttp = ">=3.8.4,<4.0.0"
-pydantic = ">=1.10.5,<2.0.0"
-python-dateutil = ">=2.8.2,<3.0.0"
-urllib3 = ">=1.25.3,<2.0.0"
+aiohttp = "^3.8.4"
+pydantic = ">=1.10.5, <3.0.0"
+python-dateutil = "^2.8.2"
+urllib3 = "^1.25.3"
+
+[package.source]
+type = "git"
+url = "https://github.com/Significant-Gravitas/agent-protocol.git"
+reference = "HEAD"
+resolved_reference = "beb098517b0b9e255024d1b57df236f0329f4b1c"
+subdirectory = "packages/client/python"
 
 [[package]]
 name = "aiohttp"
@@ -167,6 +173,17 @@ files = [
 [package.dependencies]
 frozenlist = ">=1.1.0"
 
+[[package]]
+name = "annotated-types"
+version = "0.7.0"
+description = "Reusable constraint types to use with typing.Annotated"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
+    {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
+]
+
 [[package]]
 name = "anthropic"
 version = "0.25.1"
@@ -259,17 +276,6 @@ files = [
     {file = "async_timeout-4.0.3-py3-none-any.whl", hash = "sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028"},
 ]
 
-[[package]]
-name = "asynctest"
-version = "0.13.0"
-description = "Enhance the standard unittest package with features for testing asyncio libraries"
-optional = false
-python-versions = ">=3.5"
-files = [
-    {file = "asynctest-0.13.0-py3-none-any.whl", hash = "sha256:5da6118a7e6d6b54d83a8f7197769d046922a44d2a99c21382f0a6e4fadae676"},
-    {file = "asynctest-0.13.0.tar.gz", hash = "sha256:c27862842d15d83e6a34eb0b2866c323880eb3a75e4485b079ea11748fd77fac"},
-]
-
 [[package]]
 name = "attrs"
 version = "23.2.0"
@@ -289,21 +295,6 @@ tests = ["attrs[tests-no-zope]", "zope-interface"]
 tests-mypy = ["mypy (>=1.6)", "pytest-mypy-plugins"]
 tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-xdist[psutil]"]
 
-[[package]]
-name = "autoflake"
-version = "2.2.1"
-description = "Removes unused imports and unused variables"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "autoflake-2.2.1-py3-none-any.whl", hash = "sha256:265cde0a43c1f44ecfb4f30d95b0437796759d07be7706a2f70e4719234c0f79"},
-    {file = "autoflake-2.2.1.tar.gz", hash = "sha256:62b7b6449a692c3c9b0c916919bbc21648da7281e8506bcf8d3f8280e431ebc1"},
-]
-
-[package.dependencies]
-pyflakes = ">=3.0.0"
-tomli = {version = ">=2.0.1", markers = "python_version < \"3.11\""}
-
 [[package]]
 name = "autogpt-forge"
 version = "0.2.0"
@@ -318,7 +309,6 @@ aiohttp = "^3.8.5"
 anthropic = "^0.25.1"
 beautifulsoup4 = "^4.12.2"
 boto3 = "^1.33.6"
-bs4 = "^0.0.1"
 charset-normalizer = "^3.1.0"
 chromadb = "^0.4.10"
 click = "*"
@@ -326,9 +316,10 @@ colorama = "^0.4.6"
 demjson3 = "^3.0.0"
 docker = "*"
 duckduckgo-search = "^6.1.7"
+en-core-web-sm = {url = "https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.7.1/en_core_web_sm-3.7.1-py3-none-any.whl"}
 fastapi = "^0.109.1"
 gitpython = "^3.1.32"
-google-api-python-client = "*"
+google-api-python-client = "^2.116"
 google-cloud-logging = "^3.8.0"
 google-cloud-storage = "^2.13.0"
 groq = "^0.8.0"
@@ -336,10 +327,11 @@ gTTS = "^2.3.1"
 jinja2 = "^3.1.2"
 jsonschema = "*"
 litellm = "^1.17.9"
+numpy = ">=1.26.0,<2.0.0"
 openai = "^1.7.2"
 Pillow = "*"
 playsound = "~1.2.2"
-pydantic = "*"
+pydantic = "^2.7.2"
 pylatexenc = "*"
 pypdf = "^3.1.0"
 python-docx = "*"
@@ -354,12 +346,12 @@ sqlalchemy = "^2.0.19"
 tenacity = "^8.2.2"
 tiktoken = ">=0.7.0,<1.0.0"
 toml = "^0.10.2"
-uvicorn = "^0.23.2"
+uvicorn = {version = ">=0.23.2,<1", extras = ["standard"]}
 watchdog = "4.0.0"
 webdriver-manager = "^4.0.1"
 
 [package.extras]
-benchmark = ["agbenchmark @ file:///home/reinier/code/agpt/AutoGPT/benchmark"]
+benchmark = ["agbenchmark @ file:///Users/czerwinski/Projects/AutoGPT/benchmark"]
 
 [package.source]
 type = "directory"
@@ -564,19 +556,6 @@ urllib3 = {version = ">=1.25.4,<2.1", markers = "python_version >= \"3.10\""}
 [package.extras]
 crt = ["awscrt (==0.19.19)"]
 
-[[package]]
-name = "bs4"
-version = "0.0.1"
-description = "Dummy package for Beautiful Soup"
-optional = false
-python-versions = "*"
-files = [
-    {file = "bs4-0.0.1.tar.gz", hash = "sha256:36ecea1fd7cc5c0c6e4a1ff075df26d50da647b75376626cc186e2212886dd3a"},
-]
-
-[package.dependencies]
-beautifulsoup4 = "*"
-
 [[package]]
 name = "build"
 version = "1.0.3"
@@ -708,17 +687,6 @@ files = [
     {file = "cfgv-3.4.0.tar.gz", hash = "sha256:e52591d4c5f5dead8e0f673fb16db7949d2cfb3f7da4582893288f0ded8fe560"},
 ]
 
-[[package]]
-name = "chardet"
-version = "5.2.0"
-description = "Universal encoding detector for Python 3"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "chardet-5.2.0-py3-none-any.whl", hash = "sha256:e1cf59446890a00105fe7b7912492ea04b6e6f06d4b742b2c788469e34c82970"},
-    {file = "chardet-5.2.0.tar.gz", hash = "sha256:1b3b6ff479a8c414bc3fa2c0852995695c4a026dcd6d0633b2dd092ca39c1cf7"},
-]
-
 [[package]]
 name = "charset-normalizer"
 version = "3.3.2"
@@ -1120,78 +1088,33 @@ tomli = {version = "*", optional = true, markers = "python_full_version <= \"3.1
 toml = ["tomli"]
 
 [[package]]
-name = "cssselect"
-version = "1.2.0"
-description = "cssselect parses CSS3 Selectors and translates them to XPath 1.0"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "cssselect-1.2.0-py2.py3-none-any.whl", hash = "sha256:da1885f0c10b60c03ed5eccbb6b68d6eff248d91976fcde348f395d54c9fd35e"},
-    {file = "cssselect-1.2.0.tar.gz", hash = "sha256:666b19839cfaddb9ce9d36bfe4c969132c647b92fc9088c4e23f786b30f1b3dc"},
-]
-
-[[package]]
-name = "cx-freeze"
-version = "7.0.0"
+name = "cx_Freeze"
+version = "7.1.1"
 description = "Create standalone executables from Python scripts"
 optional = false
 python-versions = ">=3.8"
-files = [
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-]
+files = []
+develop = true
 
 [package.dependencies]
 cx-Logging = {version = ">=3.1", markers = "sys_platform == \"win32\""}
-filelock = {version = ">=3.11.0", markers = "sys_platform == \"linux\""}
+dmgbuild = {version = ">=1.6.1", markers = "sys_platform == \"darwin\""}
+filelock = {version = ">=3.12.3", markers = "sys_platform == \"linux\""}
 lief = {version = ">=0.12.0,<0.15.0", markers = "sys_platform == \"win32\""}
 patchelf = {version = ">=0.14", markers = "sys_platform == \"linux\" and (platform_machine == \"aarch64\" or platform_machine == \"armv7l\" or platform_machine == \"i686\" or platform_machine == \"ppc64le\" or platform_machine == \"s390x\" or platform_machine == \"x86_64\")"}
-setuptools = ">=62.6,<70"
+setuptools = ">=65.6.3,<71"
 wheel = ">=0.42.0,<=0.43.0"
 
 [package.extras]
-dev = ["bump-my-version (==0.20.1)", "cibuildwheel (==2.17.0)", "pre-commit (==3.7.0)"]
-doc = ["furo (==2024.1.29)", "myst-parser (==2.0.0)", "sphinx (==7.3.7)", "sphinx-new-tab-link (==0.4.0)", "sphinx-tabs (==3.4.5)"]
-test = ["coverage (==7.4.4)", "pluggy (==1.4.0)", "pytest (==8.1.1)", "pytest-cov (==5.0.0)", "pytest-datafiles (==3.0.0)", "pytest-mock (==3.14.0)", "pytest-timeout (==2.3.1)", "pytest-xdist[psutil] (==3.6.0)"]
+dev = ["bump-my-version (==0.24.0)", "cibuildwheel (==2.19.1)", "pre-commit (==3.5.0)", "pre-commit (==3.7.1)"]
+doc = ["furo (==2024.5.6)", "myst-parser (==3.0.1)", "sphinx (==7.3.7)", "sphinx-new-tab-link (==0.4.0)", "sphinx-tabs (==3.4.5)"]
+test = ["coverage (==7.5.4)", "pluggy (==1.5.0)", "pytest (==8.2.2)", "pytest-cov (==5.0.0)", "pytest-datafiles (==3.0.0)", "pytest-mock (==3.14.0)", "pytest-timeout (==2.3.1)", "pytest-xdist[psutil] (==3.6.1)"]
+
+[package.source]
+type = "git"
+url = "https://github.com/ntindle/cx_Freeze.git"
+reference = "main"
+resolved_reference = "876fe77c97db749b7b0aed93c12142a7226ee7e4"
 
 [[package]]
 name = "cx-logging"
@@ -1340,6 +1263,27 @@ files = [
     {file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"},
 ]
 
+[[package]]
+name = "dmgbuild"
+version = "1.6.1"
+description = "macOS command line utility to build disk images"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "dmgbuild-1.6.1-py3-none-any.whl", hash = "sha256:45dba6af4a64872c6a91eb335ebeaf5e1f4f4f39c89fd77cf40e841bd1226166"},
+    {file = "dmgbuild-1.6.1.tar.gz", hash = "sha256:7ced2603d684e29c22b4cd507d1e15a1907e91b86259924b8cfe480d80553b43"},
+]
+
+[package.dependencies]
+ds-store = ">=1.1.0"
+mac-alias = ">=2.0.1"
+
+[package.extras]
+badge-icons = ["pyobjc-framework-Quartz (>=3.0.4)"]
+dev = ["pre-commit", "tox"]
+docs = ["sphinx", "sphinx-autobuild", "sphinx-rtd-theme"]
+test = ["pytest", "pytest-cov", "pytest-tldr"]
+
 [[package]]
 name = "docker"
 version = "7.0.0"
@@ -1361,6 +1305,25 @@ urllib3 = ">=1.26.0"
 ssh = ["paramiko (>=2.4.3)"]
 websockets = ["websocket-client (>=1.3.0)"]
 
+[[package]]
+name = "ds-store"
+version = "1.3.1"
+description = "Manipulate Finder .DS_Store files from Python"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "ds_store-1.3.1-py3-none-any.whl", hash = "sha256:fbacbb0bd5193ab3e66e5a47fff63619f15e374ffbec8ae29744251a6c8f05b5"},
+    {file = "ds_store-1.3.1.tar.gz", hash = "sha256:c27d413caf13c19acb85d75da4752673f1f38267f9eb6ba81b3b5aa99c2d207c"},
+]
+
+[package.dependencies]
+mac-alias = ">=2.0.1"
+
+[package.extras]
+dev = ["pre-commit", "tox"]
+docs = ["sphinx", "sphinx-autobuild", "sphinx-rtd-theme"]
+test = ["pytest", "pytest-cov", "pytest-tldr"]
+
 [[package]]
 name = "duckduckgo-search"
 version = "6.1.7"
@@ -1688,20 +1651,6 @@ smb = ["smbprotocol"]
 ssh = ["paramiko"]
 tqdm = ["tqdm"]
 
-[[package]]
-name = "ftfy"
-version = "6.1.3"
-description = "Fixes mojibake and other problems with Unicode, after the fact"
-optional = false
-python-versions = ">=3.8,<4"
-files = [
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-    {file = "ftfy-6.1.3.tar.gz", hash = "sha256:693274aead811cff24c1e8784165aa755cd2f6e442a5ec535c7d697f6422a422"},
-]
-
-[package.dependencies]
-wcwidth = ">=0.2.12,<0.3.0"
-
 [[package]]
 name = "gitdb"
 version = "4.0.11"
@@ -1765,20 +1714,20 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-api-python-client"
-version = "2.114.0"
+version = "2.136.0"
 description = "Google API Client Library for Python"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-api-python-client-2.114.0.tar.gz", hash = "sha256:e041bbbf60e682261281e9d64b4660035f04db1cccba19d1d68eebc24d1465ed"},
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+    {file = "google-api-python-client-2.136.0.tar.gz", hash = "sha256:161c722c8864e7ed39393e2b7eea76ef4e1c933a6a59f9d7c70409b6635f225d"},
+    {file = "google_api_python_client-2.136.0-py2.py3-none-any.whl", hash = "sha256:5a554c8b5edf0a609b905d89d7ced82e8f6ac31da1e4d8d5684ef63dbc0e49f5"},
 ]
 
 [package.dependencies]
 google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0.dev0"
-google-auth = ">=1.19.0,<3.0.0.dev0"
-google-auth-httplib2 = ">=0.1.0"
-httplib2 = ">=0.15.0,<1.dev0"
+google-auth = ">=1.32.0,<2.24.0 || >2.24.0,<2.25.0 || >2.25.0,<3.0.0.dev0"
+google-auth-httplib2 = ">=0.2.0,<1.0.0"
+httplib2 = ">=0.19.0,<1.dev0"
 uritemplate = ">=3.0.1,<5"
 
 [[package]]
@@ -2519,17 +2468,6 @@ files = [
 docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
 testing = ["pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-ruff", "zipp (>=3.17)"]
 
-[[package]]
-name = "inflection"
-version = "0.5.1"
-description = "A port of Ruby on Rails inflector to Python"
-optional = false
-python-versions = ">=3.5"
-files = [
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-]
-
 [[package]]
 name = "iniconfig"
 version = "2.0.0"
@@ -3000,6 +2938,22 @@ html5 = ["html5lib"]
 htmlsoup = ["BeautifulSoup4"]
 source = ["Cython (>=3.0.7)"]
 
+[[package]]
+name = "mac-alias"
+version = "2.2.2"
+description = "Generate/parse Mac OS Alias records from Python"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "mac_alias-2.2.2-py3-none-any.whl", hash = "sha256:504ab8ac546f35bbd75ad014d6ad977c426660aa721f2cd3acf3dc2f664141bd"},
+    {file = "mac_alias-2.2.2.tar.gz", hash = "sha256:c99c728eb512e955c11f1a6203a0ffa8883b26549e8afe68804031aa5da856b7"},
+]
+
+[package.extras]
+dev = ["pre-commit", "tox"]
+docs = ["sphinx", "sphinx-autobuild", "sphinx-rtd-theme"]
+test = ["pytest", "pytest-cov", "pytest-tldr"]
+
 [[package]]
 name = "markupsafe"
 version = "2.1.3"
@@ -3572,31 +3526,6 @@ typing-extensions = ">=4.7,<5"
 [package.extras]
 datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"]
 
-[[package]]
-name = "openapi-python-client"
-version = "0.14.1"
-description = "Generate modern Python clients from OpenAPI"
-optional = false
-python-versions = ">=3.8,<4.0"
-files = [
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-]
-
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-attrs = ">=21.3.0"
-autoflake = ">=1.4,<3.0.0"
-black = ">=23"
-colorama = {version = ">=0.4.3,<0.5.0", markers = "sys_platform == \"win32\""}
-httpx = ">=0.15.4,<0.25.0"
-isort = ">=5.0.5,<6.0.0"
-jinja2 = ">=3.0.0,<4.0.0"
-pydantic = ">=1.6.1,<2.0.0"
-python-dateutil = ">=2.8.1,<3.0.0"
-PyYAML = ">=6.0,<7.0"
-shellingham = ">=1.3.2,<2.0.0"
-typer = ">0.6,<0.10"
-
 [[package]]
 name = "opentelemetry-api"
 version = "1.22.0"
@@ -4283,87 +4212,6 @@ files = [
 [package.extras]
 test = ["enum34", "ipaddress", "mock", "pywin32", "wmi"]
 
-[[package]]
-name = "psycopg2-binary"
-version = "2.9.9"
-description = "psycopg2 - Python-PostgreSQL Database Adapter"
-optional = false
-python-versions = ">=3.7"
-files = [
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 [[package]]
 name = "pyflakes"
@@ -4763,41 +4677,21 @@ testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "no
 
 [[package]]
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 [[package]]
 name = "pytest-cov"
@@ -4817,17 +4711,6 @@ pytest = ">=4.6"
 [package.extras]
 testing = ["fields", "hunter", "process-tests", "pytest-xdist", "six", "virtualenv"]
 
-[[package]]
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 [[package]]
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 [[package]]
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 version = "0.32.1"
@@ -5429,30 +5293,18 @@ tornado = ["tornado (>=5)"]
 
 [[package]]
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 description = "Easily download, build, install, upgrade, and uninstall Python packages"
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-]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "pyproject-hooks (!=1.1)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
+testing = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "importlib-metadata", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "jaraco.test", "mypy (==1.10.0)", "packaging (>=23.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.1)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-home (>=0.5)", "pytest-mypy", "pytest-perf", "pytest-ruff (>=0.3.2)", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
 
 [[package]]
 name = "six"
@@ -6214,20 +6066,6 @@ dev = ["autoflake (>=1.3.1,<2.0.0)", "flake8 (>=3.8.3,<4.0.0)", "pre-commit (>=2
 doc = ["cairosvg (>=2.5.2,<3.0.0)", "mdx-include (>=1.4.1,<2.0.0)", "mkdocs (>=1.1.2,<2.0.0)", "mkdocs-material (>=8.1.4,<9.0.0)", "pillow (>=9.3.0,<10.0.0)"]
 test = ["black (>=22.3.0,<23.0.0)", "coverage (>=6.2,<7.0)", "isort (>=5.0.6,<6.0.0)", "mypy (==0.910)", "pytest (>=4.4.0,<8.0.0)", "pytest-cov (>=2.10.0,<5.0.0)", "pytest-sugar (>=0.9.4,<0.10.0)", "pytest-xdist (>=1.32.0,<4.0.0)", "rich (>=10.11.0,<14.0.0)", "shellingham (>=1.3.0,<2.0.0)"]
 
-[[package]]
-name = "types-beautifulsoup4"
-version = "4.12.0.20240106"
-description = "Typing stubs for beautifulsoup4"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "types-beautifulsoup4-4.12.0.20240106.tar.gz", hash = "sha256:98d628985b71b140bd3bc22a8cb0ab603c2f2d08f20d37925965eb4a21739be8"},
-    {file = "types_beautifulsoup4-4.12.0.20240106-py3-none-any.whl", hash = "sha256:cbdd60ab8aeac737ac014431b6e921b43e84279c0405fdd25a6900bb0e71da5b"},
-]
-
-[package.dependencies]
-types-html5lib = "*"
-
 [[package]]
 name = "types-colorama"
 version = "0.4.15.20240106"
@@ -6239,64 +6077,6 @@ files = [
     {file = "types_colorama-0.4.15.20240106-py3-none-any.whl", hash = "sha256:18294bc18f60dc0b4895de8119964a5d895f5e180c2d1308fdd33009c0fa0f38"},
 ]
 
-[[package]]
-name = "types-html5lib"
-version = "1.1.11.20240106"
-description = "Typing stubs for html5lib"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "types-html5lib-1.1.11.20240106.tar.gz", hash = "sha256:fc3a1b18eb601b3eeaf92c900bd67675c0a4fa1dd1d2a2893ebdb46923547ee9"},
-    {file = "types_html5lib-1.1.11.20240106-py3-none-any.whl", hash = "sha256:61993cb89220107481e0f1da65c388ff8cf3d8c5f6e8483c97559639a596b697"},
-]
-
-[[package]]
-name = "types-markdown"
-version = "3.5.0.20240106"
-description = "Typing stubs for Markdown"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "types-Markdown-3.5.0.20240106.tar.gz", hash = "sha256:be47d35cbe61d458bd17aec127f1da233cd6ed96fa9a131c710378a4e8857030"},
-    {file = "types_Markdown-3.5.0.20240106-py3-none-any.whl", hash = "sha256:c23569d33718475dfae25c0036c6e6866f409e7077ee8a0728ab3db263d8e4a5"},
-]
-
-[[package]]
-name = "types-pillow"
-version = "10.2.0.20240111"
-description = "Typing stubs for Pillow"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "types-Pillow-10.2.0.20240111.tar.gz", hash = "sha256:e8d359bfdc5a149a3c90a7e153cb2d0750ddf7fc3508a20dfadabd8a9435e354"},
-    {file = "types_Pillow-10.2.0.20240111-py3-none-any.whl", hash = "sha256:1f4243b30c143b56b0646626f052e4269123e550f9096cdfb5fbd999daee7dbb"},
-]
-
-[[package]]
-name = "types-requests"
-version = "2.31.0.6"
-description = "Typing stubs for requests"
-optional = true
-python-versions = ">=3.7"
-files = [
-    {file = "types-requests-2.31.0.6.tar.gz", hash = "sha256:cd74ce3b53c461f1228a9b783929ac73a666658f223e28ed29753771477b3bd0"},
-    {file = "types_requests-2.31.0.6-py3-none-any.whl", hash = "sha256:a2db9cb228a81da8348b49ad6db3f5519452dd20a9c1e1a868c83c5fe88fd1a9"},
-]
-
-[package.dependencies]
-types-urllib3 = "*"
-
-[[package]]
-name = "types-urllib3"
-version = "1.26.25.14"
-description = "Typing stubs for urllib3"
-optional = true
-python-versions = "*"
-files = [
-    {file = "types-urllib3-1.26.25.14.tar.gz", hash = "sha256:229b7f577c951b8c1b92c1bc2b2fdb0b49847bd2af6d1cc2a2e3dd340f3bda8f"},
-    {file = "types_urllib3-1.26.25.14-py3-none-any.whl", hash = "sha256:9683bbb7fb72e32bfe9d2be6e04875fbe1b3eeec3cbb4ea231435aa7fd6b4f0e"},
-]
-
 [[package]]
 name = "typing-extensions"
 version = "4.9.0"
@@ -6605,7 +6385,7 @@ anyio = ">=3.0.0"
 name = "wcwidth"
 version = "0.2.13"
 description = "Measures the displayed width of unicode strings in a terminal"
-optional = false
+optional = true
 python-versions = "*"
 files = [
     {file = "wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859"},
@@ -6978,4 +6758,4 @@ benchmark = ["agbenchmark"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "a378031626ad6640c66c53d2b58266d7d464462b69f0b5b5b95c317bd20c6b79"
+content-hash = "b3d4efee5861b32152024dada1ec61f4241122419cb538012c00a6ed55ac8a4b"

autogpt/pyproject.toml

@@ -20,44 +20,24 @@ serve = "autogpt.app.cli:serve"
 
 [tool.poetry.dependencies]
 python = "^3.10"
-anthropic = "^0.25.1"
 autogpt-forge = { path = "../forge", develop = true }
 # autogpt-forge = {git = "https://github.com/Significant-Gravitas/AutoGPT.git", subdirectory = "forge"}
-beautifulsoup4 = "^4.12.2"
-charset-normalizer = "^3.1.0"
 click = "*"
 colorama = "^0.4.6"
 distro = "^1.8.0"
-en-core-web-sm = { url = "https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.7.1/en_core_web_sm-3.7.1-py3-none-any.whl" }
 fastapi = "^0.109.1"
-ftfy = "^6.1.1"
-google-api-python-client = "*"
+gitpython = "^3.1.32"
 hypercorn = "^0.14.4"
-inflection = "*"
-jsonschema = "*"
-numpy = "*"
 openai = "^1.7.2"
 orjson = "^3.8.10"
-Pillow = "*"
-pydantic = "*"
-python-docx = "*"
+pydantic = "^2.7.2"
 python-dotenv = "^1.0.0"
-pyyaml = "^6.0"
-readability-lxml = "^0.8.1"
 requests = "*"
 sentry-sdk = "^1.40.4"
-spacy = "^3.7.4"
-tenacity = "^8.2.2"
-
-# OpenAI and Generic plugins import
-openapi-python-client = "^0.14.0"
 
 # Benchmarking
 agbenchmark = { path = "../benchmark", optional = true }
 # agbenchmark = {git = "https://github.com/Significant-Gravitas/AutoGPT.git", subdirectory = "benchmark", optional = true}
-psycopg2-binary = "^2.9.9"
-multidict = "6.0.5"
-cx-freeze = "7.0.0"
 
 [tool.poetry.extras]
 benchmark = ["agbenchmark"]
@@ -65,27 +45,28 @@ benchmark = ["agbenchmark"]
 [tool.poetry.group.dev.dependencies]
 black = "^23.12.1"
 flake8 = "^7.0.0"
-gitpython = "^3.1.32"
 isort = "^5.13.1"
 pre-commit = "*"
 pyright = "^1.1.364"
-types-beautifulsoup4 = "*"
+
+# Type stubs
 types-colorama = "*"
-types-Markdown = "*"
-types-Pillow = "*"
 
 # Testing
-asynctest = "*"
-coverage = "*"
 pytest = "*"
 pytest-asyncio = "*"
-pytest-benchmark = "*"
 pytest-cov = "*"
-pytest-integration = "*"
 pytest-mock = "*"
 pytest-recording = "*"
 pytest-xdist = "*"
-vcrpy = { git = "https://github.com/Significant-Gravitas/vcrpy.git", rev = "master" }
+
+[tool.poetry.group.build]
+optional = true
+
+[tool.poetry.group.build.dependencies]
+cx-freeze = { git = "https://github.com/ntindle/cx_Freeze.git", rev = "main" }
+# HACK: switch to cx-freeze release package after #2442 and #2472 are merged: https://github.com/marcelotduarte/cx_Freeze/pulls?q=is:pr+%232442+OR+%232472+
+# cx-freeze = { version = "^7.2.0", optional = true }
 
 
 [build-system]
@@ -108,7 +89,3 @@ skip_glob = ["data"]
 pythonVersion = "3.10"
 exclude = ["data/**", "**/node_modules", "**/__pycache__", "**/.*"]
 ignore = ["../forge/**"]
-
-
-[tool.pytest.ini_options]
-markers = ["slow", "requires_openai_api_key", "requires_huggingface_api_key"]

autogpt/scripts/git_log_to_release_notes.py

@@ -19,7 +19,7 @@ from autogpt.app.utils import coroutine
     help="Path to the git repository",
 )
 @coroutine
-async def generate_release_notes(repo_path: Optional[Path] = None):
+async def generate_release_notes(repo_path: Optional[str | Path] = None):
     logger = logging.getLogger(generate_release_notes.name)  # pyright: ignore
 
     repo = Repo(repo_path, search_parent_directories=True)

autogpt/scripts/llamafile/.gitignore

@@ -0,0 +1,3 @@
+*.llamafile
+*.llamafile.exe
+llamafile.exe

autogpt/scripts/llamafile/serve.py

@@ -0,0 +1,165 @@
+#!/usr/bin/env python3
+"""
+Use llamafile to serve a (quantized) mistral-7b-instruct-v0.2 model
+
+Usage:
+  cd <repo-root>/autogpt
+  ./scripts/llamafile/serve.py
+"""
+
+import os
+import platform
+import subprocess
+from pathlib import Path
+from typing import Optional
+
+import click
+
+LLAMAFILE = Path("mistral-7b-instruct-v0.2.Q5_K_M.llamafile")
+LLAMAFILE_URL = f"https://huggingface.co/jartine/Mistral-7B-Instruct-v0.2-llamafile/resolve/main/{LLAMAFILE.name}"  # noqa
+LLAMAFILE_EXE = Path("llamafile.exe")
+LLAMAFILE_EXE_URL = "https://github.com/Mozilla-Ocho/llamafile/releases/download/0.8.6/llamafile-0.8.6"  # noqa
+
+
+@click.command()
+@click.option(
+    "--llamafile",
+    type=click.Path(dir_okay=False, path_type=Path),
+    help=f"Name of the llamafile to serve. Default: {LLAMAFILE.name}",
+)
+@click.option("--llamafile_url", help="Download URL for the llamafile you want to use")
+@click.option(
+    "--host", help="Specify the address for the llamafile server to listen on"
+)
+@click.option(
+    "--port", type=int, help="Specify the port for the llamafile server to listen on"
+)
+@click.option(
+    "--force-gpu",
+    is_flag=True,
+    hidden=platform.system() != "Darwin",
+    help="Run the model using only the GPU (AMD or Nvidia). "
+    "Otherwise, both CPU and GPU may be (partially) used.",
+)
+def main(
+    llamafile: Optional[Path] = None,
+    llamafile_url: Optional[str] = None,
+    host: Optional[str] = None,
+    port: Optional[int] = None,
+    force_gpu: bool = False,
+):
+    print(f"type(llamafile) = {type(llamafile)}")
+    if not llamafile:
+        if not llamafile_url:
+            llamafile = LLAMAFILE
+        else:
+            llamafile = Path(llamafile_url.rsplit("/", 1)[1])
+            if llamafile.suffix != ".llamafile":
+                click.echo(
+                    click.style(
+                        "The given URL does not end with '.llamafile' -> "
+                        "can't get filename from URL. "
+                        "Specify the filename using --llamafile.",
+                        fg="red",
+                    ),
+                    err=True,
+                )
+                return
+
+    if llamafile == LLAMAFILE and not llamafile_url:
+        llamafile_url = LLAMAFILE_URL
+    elif llamafile_url != LLAMAFILE_URL:
+        if not click.prompt(
+            click.style(
+                "You seem to have specified a different URL for the default model "
+                f"({llamafile.name}). Are you sure this is correct? "
+                "If you want to use a different model, also specify --llamafile.",
+                fg="yellow",
+            ),
+            type=bool,
+        ):
+            return
+
+    # Go to autogpt/scripts/llamafile/
+    os.chdir(Path(__file__).resolve().parent)
+
+    on_windows = platform.system() == "Windows"
+
+    if not llamafile.is_file():
+        if not llamafile_url:
+            click.echo(
+                click.style(
+                    "Please use --lamafile_url to specify a download URL for "
+                    f"'{llamafile.name}'. "
+                    "This will only be necessary once, so we can download the model.",
+                    fg="red",
+                ),
+                err=True,
+            )
+            return
+
+        download_file(llamafile_url, llamafile)
+
+        if not on_windows:
+            llamafile.chmod(0o755)
+            subprocess.run([llamafile, "--version"], check=True)
+
+    if not on_windows:
+        base_command = [f"./{llamafile}"]
+    else:
+        # Windows does not allow executables over 4GB, so we have to download a
+        # model-less llamafile.exe and run that instead.
+        if not LLAMAFILE_EXE.is_file():
+            download_file(LLAMAFILE_EXE_URL, LLAMAFILE_EXE)
+            LLAMAFILE_EXE.chmod(0o755)
+            subprocess.run([f".\\{LLAMAFILE_EXE}", "--version"], check=True)
+
+        base_command = [f".\\{LLAMAFILE_EXE}", "-m", llamafile]
+
+    if host:
+        base_command.extend(["--host", host])
+    if port:
+        base_command.extend(["--port", str(port)])
+    if force_gpu:
+        base_command.extend(["-ngl", "9999"])
+
+    subprocess.run(
+        [
+            *base_command,
+            "--server",
+            "--nobrowser",
+            "--ctx-size",
+            "0",
+            "--n-predict",
+            "1024",
+        ],
+        check=True,
+    )
+
+    # note: --ctx-size 0 means the prompt context size will be set directly from the
+    # underlying model configuration. This may cause slow response times or consume
+    # a lot of memory.
+
+
+def download_file(url: str, to_file: Path) -> None:
+    print(f"Downloading {to_file.name}...")
+    import urllib.request
+
+    urllib.request.urlretrieve(url, to_file, reporthook=report_download_progress)
+    print()
+
+
+def report_download_progress(chunk_number: int, chunk_size: int, total_size: int):
+    if total_size != -1:
+        downloaded_size = chunk_number * chunk_size
+        percent = min(1, downloaded_size / total_size)
+        bar = "#" * int(40 * percent)
+        print(
+            f"\rDownloading: [{bar:<40}] {percent:.0%}"
+            f" - {downloaded_size/1e6:.1f}/{total_size/1e6:.1f} MB",
+            end="",
+        )
+
+
+if __name__ == "__main__":
+    main()

autogpt/setup.py

@@ -1,7 +1,9 @@
+import platform
+from pathlib import Path
 from pkgutil import iter_modules
-from shutil import which
+from typing import Union
 
-from cx_Freeze import Executable, setup
+from cx_Freeze import Executable, setup  # type: ignore
 
 packages = [
     m.name
@@ -11,11 +13,47 @@ packages = [
     and ("poetry" in m.module_finder.path)  # type: ignore
 ]
 
-icon = (
-    "../../assets/gpt_dark_RGB.icns"
-    if which("sips")
-    else "../../assets/gpt_dark_RGB.ico"
-)
+# set the icon based on the platform
+icon = "../../assets/gpt_dark_RGB.ico"
+if platform.system() == "Darwin":
+    icon = "../../assets/gpt_dark_RGB.icns"
+elif platform.system() == "Linux":
+    icon = "../../assets/gpt_dark_RGB.png"
+
+
+def txt_to_rtf(input_file: Union[str, Path], output_file: Union[str, Path]) -> None:
+    """
+    Convert a text file to RTF format.
+
+    Args:
+    input_file (Union[str, Path]): Path to the input text file.
+    output_file (Union[str, Path]): Path to the output RTF file.
+
+    Returns:
+    None
+    """
+    input_path = Path(input_file)
+    output_path = Path(output_file)
+
+    with input_path.open("r", encoding="utf-8") as txt_file:
+        content = txt_file.read()
+
+    # RTF header
+    rtf = r"{\rtf1\ansi\deff0 {\fonttbl {\f0 Times New Roman;}}\f0\fs24 "
+
+    # Replace newlines with RTF newline
+    rtf += content.replace("\n", "\\par ")
+
+    # Close RTF document
+    rtf += "}"
+
+    with output_path.open("w", encoding="utf-8") as rtf_file:
+        rtf_file.write(rtf)
+
+
+# Convert LICENSE to LICENSE.rtf
+license_file = "LICENSE.rtf"
+txt_to_rtf("../LICENSE", license_file)
 
 
 setup(
@@ -55,6 +93,7 @@ setup(
             "target_name": "AutoGPT",
             "add_to_path": True,
             "install_icon": "../assets/gpt_dark_RGB.ico",
+            "license_file": license_file,
         },
     },
 )

autogpt/tests/conftest.py

@@ -20,7 +20,6 @@ from autogpt.app.main import _configure_llm_provider
 
 pytest_plugins = [
     "tests.integration.agent_factory",
-    "tests.vcr",
 ]
 
 
@@ -96,7 +95,7 @@ def agent(
             allow_fs_access=not config.restrict_to_workspace,
             use_functions_api=config.openai_functions,
         ),
-        history=Agent.default_settings.history.copy(deep=True),
+        history=Agent.default_settings.history.model_copy(deep=True),
     )
 
     agent = Agent(

autogpt/tests/integration/agent_factory.py

@@ -28,7 +28,7 @@ def dummy_agent(config: AppConfig, llm_provider: MultiProvider):
             smart_llm=config.smart_llm,
             use_functions_api=config.openai_functions,
         ),
-        history=Agent.default_settings.history.copy(deep=True),
+        history=Agent.default_settings.history.model_copy(deep=True),
     )
 
     local = config.file_storage_backend == FileStorageBackendName.LOCAL

benchmark/.vscode/settings.json

@@ -2,5 +2,5 @@
   "[python]": {
     "editor.defaultFormatter": "ms-python.black-formatter"
   },
-  "python.formatting.provider": "none"
+  "python.analysis.typeCheckingMode": "basic",
 }

benchmark/agbenchmark/__main__.py

@@ -97,7 +97,9 @@ def start():
     help="Write log output to a file instead of the terminal.",
 )
 # @click.argument(
-#     "agent_path", type=click.Path(exists=True, file_okay=False), required=False
+#     "agent_path",
+#     type=click.Path(exists=True, file_okay=False, path_type=Path),
+#     required=False,
 # )
 def run(
     maintain: bool,
@@ -276,7 +278,9 @@ def list_challenges(include_unavailable: bool, only_names: bool, output_json: bo
         return
 
     if output_json:
-        click.echo(json.dumps([json.loads(c.info.json()) for c in challenges]))
+        click.echo(
+            json.dumps([json.loads(c.info.model_dump_json()) for c in challenges])
+        )
         return
 
     headers = tuple(
@@ -324,7 +328,7 @@ def info(name: str, json: bool):
             continue
 
         if json:
-            click.echo(challenge.info.json())
+            click.echo(challenge.info.model_dump_json())
             break
 
         pretty_print_model(challenge.info)

benchmark/agbenchmark/app.py

@@ -16,7 +16,7 @@ from agent_protocol_client import AgentApi, ApiClient, ApiException, Configurati
 from agent_protocol_client.models import Task, TaskRequestBody
 from fastapi import APIRouter, FastAPI, HTTPException, Request, Response
 from fastapi.middleware.cors import CORSMiddleware
-from pydantic import BaseModel, Extra, ValidationError
+from pydantic import BaseModel, ConfigDict, ValidationError
 
 from agbenchmark.challenges import ChallengeInfo
 from agbenchmark.config import AgentBenchmarkConfig
@@ -52,7 +52,9 @@ while challenge_spec_files:
 
     logger.debug(f"Loading {challenge_relpath}...")
     try:
-        challenge_info = ChallengeInfo.parse_file(challenge_spec_file)
+        challenge_info = ChallengeInfo.model_validate_json(
+            challenge_spec_file.read_text()
+        )
     except ValidationError as e:
         if logging.getLogger().level == logging.DEBUG:
             logger.warning(f"Spec file {challenge_relpath} failed to load:\n{e}")
@@ -64,7 +66,7 @@ while challenge_spec_files:
         challenge_info.eval_id = str(uuid.uuid4())
         # this will sort all the keys of the JSON systematically
         # so that the order is always the same
-        write_pretty_json(challenge_info.dict(), challenge_spec_file)
+        write_pretty_json(challenge_info.model_dump(), challenge_spec_file)
 
     CHALLENGES[challenge_info.eval_id] = challenge_info
 
@@ -111,8 +113,7 @@ class CreateReportRequest(BaseModel):
     # category: Optional[str] = []
     mock: Optional[bool] = False
 
-    class Config:
-        extra = Extra.forbid  # this will forbid any extra fields
+    model_config = ConfigDict(extra="forbid")
 
 
 updates_list = []
@@ -153,7 +154,7 @@ def setup_fastapi_app(agbenchmark_config: AgentBenchmarkConfig) -> FastAPI:
         pids = find_agbenchmark_without_uvicorn()
         logger.info(f"pids already running with agbenchmark: {pids}")
 
-        logger.debug(f"Request to /reports: {body.dict()}")
+        logger.debug(f"Request to /reports: {body.model_dump()}")
 
         # Start the benchmark in a separate thread
         benchmark_process = Process(
@@ -326,7 +327,9 @@ def setup_fastapi_app(agbenchmark_config: AgentBenchmarkConfig) -> FastAPI:
                 config={},
             )
 
-            logger.debug(f"Returning evaluation data:\n{eval_info.json(indent=4)}")
+            logger.debug(
+                f"Returning evaluation data:\n{eval_info.model_dump_json(indent=4)}"
+            )
             return eval_info
         except ApiException as e:
             logger.error(f"Error {e} whilst trying to evaluate task: {task_id}")

benchmark/agbenchmark/challenges/builtin.py

@@ -15,7 +15,13 @@ from agent_protocol_client import Configuration as ClientConfig
 from agent_protocol_client import Step
 from colorama import Fore, Style
 from openai import _load_client as get_openai_client
-from pydantic import BaseModel, Field, constr, validator
+from pydantic import (
+    BaseModel,
+    Field,
+    StringConstraints,
+    ValidationInfo,
+    field_validator,
+)
 
 from agbenchmark.agent_api_interface import download_agent_artifacts_into_folder
 from agbenchmark.agent_interface import copy_challenge_artifacts_into_workspace
@@ -46,7 +52,9 @@ class BuiltinChallengeSpec(BaseModel):
 
     class Info(BaseModel):
         difficulty: DifficultyLevel
-        description: Annotated[str, constr(regex=r"^Tests if the agent can.*")]
+        description: Annotated[
+            str, StringConstraints(pattern=r"^Tests if the agent can.*")
+        ]
         side_effects: list[str] = Field(default_factory=list)
 
     info: Info
@@ -60,23 +68,26 @@ class BuiltinChallengeSpec(BaseModel):
 
         class Eval(BaseModel):
             type: str
-            scoring: Optional[Literal["percentage", "scale", "binary"]]
-            template: Optional[Literal["rubric", "reference", "question", "custom"]]
-            examples: Optional[str]
+            scoring: Optional[Literal["percentage", "scale", "binary"]] = None
+            template: Optional[
+                Literal["rubric", "reference", "question", "custom"]
+            ] = None
+            examples: Optional[str] = None
 
-            @validator("scoring", "template", always=True)
-            def validate_eval_fields(cls, v, values, field):
-                if "type" in values and values["type"] == "llm":
-                    if v is None:
+            @field_validator("scoring", "template")
+            def validate_eval_fields(cls, value, info: ValidationInfo):
+                field_name = info.field_name
+                if "type" in info.data and info.data["type"] == "llm":
+                    if value is None:
                         raise ValueError(
-                            f"{field.name} must be provided when eval type is 'llm'"
+                            f"{field_name} must be provided when eval type is 'llm'"
                         )
                 else:
-                    if v is not None:
+                    if value is not None:
                         raise ValueError(
-                            f"{field.name} should only exist when eval type is 'llm'"
+                            f"{field_name} should only exist when eval type is 'llm'"
                         )
-                return v
+                return value
 
         eval: Eval
 
@@ -142,7 +153,7 @@ class BuiltinChallenge(BaseChallenge):
 
     @classmethod
     def from_challenge_spec_file(cls, spec_file: Path) -> type["BuiltinChallenge"]:
-        challenge_spec = BuiltinChallengeSpec.parse_file(spec_file)
+        challenge_spec = BuiltinChallengeSpec.model_validate_json(spec_file.read_text())
         challenge_spec.spec_file = spec_file
         return cls.from_challenge_spec(challenge_spec)
 
@@ -187,7 +198,7 @@ class BuiltinChallenge(BaseChallenge):
                     task_id = step.task_id
 
                 n_steps += 1
-                steps.append(step.copy())
+                steps.append(step.model_copy())
                 if step.additional_output:
                     agent_task_cost = step.additional_output.get(
                         "task_total_cost",

benchmark/agbenchmark/challenges/verticals/code/6_battleship/artifacts_in/abstract_class.py

@@ -1,7 +1,7 @@
 from abc import ABC, abstractmethod
 from typing import Optional
 
-from pydantic import BaseModel, validator
+from pydantic import BaseModel, field_validator
 
 
 # Models for the request and response payloads
@@ -10,7 +10,7 @@ class ShipPlacement(BaseModel):
     start: dict  # {"row": int, "column": str}
     direction: str
 
-    @validator("start")
+    @field_validator("start")
     def validate_start(cls, start):
         row, column = start.get("row"), start.get("column")
 

benchmark/agbenchmark/challenges/verticals/code/6_battleship/artifacts_out/abstract_class.py

@@ -1,7 +1,7 @@
 from abc import ABC, abstractmethod
 from typing import Optional
 
-from pydantic import BaseModel, validator
+from pydantic import BaseModel, field_validator
 
 
 # Models for the request and response payloads
@@ -10,7 +10,7 @@ class ShipPlacement(BaseModel):
     start: dict  # {"row": int, "column": str}
     direction: str
 
-    @validator("start")
+    @field_validator("start")
     def validate_start(cls, start):
         row, column = start.get("row"), start.get("column")
 

benchmark/agbenchmark/challenges/webarena.py

@@ -6,7 +6,7 @@ from typing import ClassVar, Iterator, Literal
 import pytest
 import requests
 from agent_protocol_client import AgentApi, Step
-from pydantic import BaseModel, ValidationError, validator
+from pydantic import BaseModel, ValidationError, ValidationInfo, field_validator
 
 from agbenchmark.config import AgentBenchmarkConfig
 from agbenchmark.utils.data_types import Category, EvalResult
@@ -183,7 +183,7 @@ class WebArenaChallengeSpec(BaseModel):
     """The JungleGym site (base URL) at which to start"""
     require_login: bool
     require_reset: bool
-    storage_state: str | None
+    storage_state: str | None = None
 
     intent: str
     intent_template: str
@@ -195,36 +195,36 @@ class WebArenaChallengeSpec(BaseModel):
 
     class EvalSet(BaseModel):
         class StringMatchEvalSet(BaseModel):
-            exact_match: str | None
-            fuzzy_match: list[str] | None
-            must_include: list[str] | None
+            exact_match: str | None = None
+            fuzzy_match: list[str] | None = None
+            must_include: list[str] | None = None
 
-        reference_answers: StringMatchEvalSet | None
+        reference_answers: StringMatchEvalSet | None = None
         """For string_match eval, a set of criteria to judge the final answer"""
-        reference_answer_raw_annotation: str | None
-        string_note: str | None
-        annotation_note: str | None
+        reference_answer_raw_annotation: str | None = None
+        string_note: str | None = None
+        annotation_note: str | None = None
 
-        reference_url: str | None
+        reference_url: str | None = None
         """For url_match eval, the last URL that should be visited"""
-        url_note: str | None
+        url_note: str | None = None
 
         program_html: list[ProgramHtmlEval]
         """For program_html eval, a list of criteria to judge the site state by"""
 
         eval_types: list[EvalType]
 
-        @validator("eval_types")
-        def check_eval_parameters(cls, v: list[EvalType], values):
-            if "string_match" in v and not values.get("reference_answers"):
+        @field_validator("eval_types")
+        def check_eval_parameters(cls, value: list[EvalType], info: ValidationInfo):
+            if "string_match" in value and not info.data["reference_answers"]:
                 raise ValueError("'string_match' eval_type requires reference_answers")
-            if "url_match" in v and not values.get("reference_url"):
+            if "url_match" in value and not info.data["reference_url"]:
                 raise ValueError("'url_match' eval_type requires reference_url")
-            if "program_html" in v and not values.get("program_html"):
+            if "program_html" in value and not info.data["program_html"]:
                 raise ValueError(
                     "'program_html' eval_type requires at least one program_html eval"
                 )
-            return v
+            return value
 
         @property
         def evaluators(self) -> list[_Eval]:
@@ -292,7 +292,7 @@ class WebArenaChallenge(BaseChallenge):
         results = requests.get(source_url).json()["data"]
         if not results:
             raise ValueError(f"Could not fetch challenge {source_uri}")
-        return cls.from_challenge_spec(WebArenaChallengeSpec.parse_obj(results[0]))
+        return cls.from_challenge_spec(WebArenaChallengeSpec.model_validate(results[0]))
 
     @classmethod
     def from_challenge_spec(
@@ -500,7 +500,7 @@ def load_webarena_challenges(
     skipped = 0
     for entry in challenge_dicts:
         try:
-            challenge_spec = WebArenaChallengeSpec.parse_obj(entry)
+            challenge_spec = WebArenaChallengeSpec.model_validate(entry)
         except ValidationError as e:
             failed += 1
             logger.warning(f"Error validating WebArena challenge entry: {entry}")

benchmark/agbenchmark/config.py

@@ -4,7 +4,8 @@ from datetime import datetime
 from pathlib import Path
 from typing import Optional
 
-from pydantic import BaseSettings, Field, validator
+from pydantic import Field, ValidationInfo, field_validator
+from pydantic_settings import BaseSettings
 
 
 def _calculate_info_test_path(base_path: Path, benchmark_start_time: datetime) -> Path:
@@ -57,7 +58,7 @@ class AgentBenchmarkConfig(BaseSettings, extra="allow"):
     subject application exposes an Agent Protocol compliant API.
     """
 
-    agbenchmark_config_dir: Path = Field(..., exclude=True)
+    agbenchmark_config_dir: Path = Field(exclude=True)
     """Path to the agbenchmark_config folder of the subject agent application."""
 
     categories: list[str] | None = None
@@ -101,11 +102,11 @@ class AgentBenchmarkConfig(BaseSettings, extra="allow"):
     def config_file(self) -> Path:
         return self.agbenchmark_config_dir / "config.json"
 
-    @validator("reports_folder", pre=True, always=True)
-    def set_reports_folder(cls, v, values):
-        if not v:
-            return values["agbenchmark_config_dir"] / "reports"
-        return v
+    @field_validator("reports_folder", mode="before")
+    def set_reports_folder(cls, value: Path, info: ValidationInfo):
+        if not value:
+            return info.data["agbenchmark_config_dir"] / "reports"
+        return value
 
     def get_report_dir(self, benchmark_start_time: datetime) -> Path:
         return _calculate_info_test_path(self.reports_folder, benchmark_start_time)

benchmark/agbenchmark/reports/ReportManager.py

@@ -111,17 +111,19 @@ class SessionReportManager(BaseReportManager):
     def save(self) -> None:
         with self.report_file.open("w") as f:
             if self.report:
-                f.write(self.report.json(indent=4))
+                f.write(self.report.model_dump_json(indent=4))
             else:
-                json.dump({k: v.dict() for k, v in self.tests.items()}, f, indent=4)
+                json.dump(
+                    {k: v.model_dump() for k, v in self.tests.items()}, f, indent=4
+                )
 
     def load(self) -> None:
         super().load()
 
         if "tests" in self.tests:
-            self.report = Report.parse_obj(self.tests)
+            self.report = Report.model_validate(self.tests)
         else:
-            self.tests = {n: Test.parse_obj(d) for n, d in self.tests.items()}
+            self.tests = {n: Test.model_validate(d) for n, d in self.tests.items()}
 
     def add_test_report(self, test_name: str, test_report: Test) -> None:
         if self.report:
@@ -155,7 +157,7 @@ class SessionReportManager(BaseReportManager):
                 total_cost=self.get_total_costs(),
             ),
             tests=copy.copy(self.tests),
-            config=config.dict(exclude={"reports_folder"}, exclude_none=True),
+            config=config.model_dump(exclude={"reports_folder"}, exclude_none=True),
         )
 
         agent_categories = get_highest_achieved_difficulty_per_category(self.report)

benchmark/agbenchmark/reports/processing/process_report.py

@@ -27,7 +27,7 @@ def get_reports_data(report_path: str) -> dict[str, Any]:
         with open(Path(subdir) / file, "r") as f:
             # Load the JSON data from the file
             json_data = json.load(f)
-            converted_data = Report.parse_obj(json_data)
+            converted_data = Report.model_validate(json_data)
             # get the last directory name in the path as key
             reports_data[subdir_name] = converted_data
 

benchmark/agbenchmark/reports/processing/report_types.py

@@ -6,7 +6,13 @@ import logging
 from typing import Annotated, Any, Dict, List
 
 from agent_protocol_client import Step
-from pydantic import BaseModel, Field, constr, validator
+from pydantic import (
+    BaseModel,
+    Field,
+    StringConstraints,
+    ValidationInfo,
+    field_validator,
+)
 
 datetime_format = r"^\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}\+00:00$"
 logger = logging.getLogger(__name__)
@@ -30,20 +36,20 @@ class TestResult(BaseModel):
     cost: float | None = None
     """The (known) cost incurred by the run, e.g. from using paid LLM APIs"""
 
-    @validator("fail_reason")
-    def success_xor_fail_reason(cls, v: str | None, values: dict[str, Any]):
-        if bool(v) == bool(values["success"]):
+    @field_validator("fail_reason")
+    def success_xor_fail_reason(cls, value, info: ValidationInfo):
+        if bool(value) == bool(info.data["success"]):
             logger.error(
                 "Error validating `success ^ fail_reason` on TestResult: "
-                f"success = {repr(values['success'])}; "
-                f"fail_reason = {repr(v)}"
+                f"success = {repr(info.data['success'])}; "
+                f"fail_reason = {repr(value)}"
             )
-        if v:
-            success = values["success"]
+        if value:
+            success = info.data["success"]
             assert not success, "fail_reason must only be specified if success=False"
         else:
-            assert values["success"], "fail_reason is required if success=False"
-        return v
+            assert info.data["success"], "fail_reason is required if success=False"
+        return value
 
 
 class TestMetrics(BaseModel):
@@ -88,7 +94,7 @@ class Test(BaseModel):
 class ReportBase(BaseModel):
     command: str
     completion_time: str | None = None
-    benchmark_start_time: Annotated[str, constr(regex=datetime_format)]
+    benchmark_start_time: Annotated[str, StringConstraints(pattern=datetime_format)]
     metrics: MetricsOverall
     config: Dict[str, str | dict[str, str]]
     agent_git_commit_sha: str | None = None

benchmark/agbenchmark/reports/processing/report_types_v2.py

@@ -1,7 +1,7 @@
 """Model definitions for use in the API"""
 from typing import Annotated
 
-from pydantic import BaseModel, constr
+from pydantic import BaseModel, StringConstraints
 
 datetime_format = r"^\d{4}-\d{2}-\d{2}T\d{2}:\d{2}:\d{2}\+00:00$"
 
@@ -37,7 +37,7 @@ class RunDetails(BaseModel):
     run_id: str | None = None
     command: str
     completion_time: str | None = None
-    benchmark_start_time: Annotated[str, constr(regex=datetime_format)]
+    benchmark_start_time: Annotated[str, StringConstraints(pattern=datetime_format)]
 
 
 class BenchmarkRun(BaseModel):

benchmark/agbenchmark/reports/reports.py

@@ -45,7 +45,7 @@ def update_regression_tests(
         # if the last 3 tests were successful, add to the regression tests
         test_report.metrics.is_regression = True
         SingletonReportManager().REGRESSION_MANAGER.add_test(
-            test_name, test_report.dict(include={"difficulty", "data_path"})
+            test_name, test_report.model_dump(include={"difficulty", "data_path"})
         )
 
 

benchmark/agbenchmark/schema.py

@@ -7,10 +7,9 @@ from pydantic import BaseModel, Field
 
 class TaskRequestBody(BaseModel):
     input: str = Field(
-        ...,
         min_length=1,
         description="Input prompt for the task.",
-        example="Write the words you receive to the file 'output.txt'.",
+        examples=["Write the words you receive to the file 'output.txt'."],
     )
     additional_input: Optional[dict[str, Any]] = Field(default_factory=dict)
 

benchmark/agbenchmark/utils/dependencies/main.py

@@ -220,7 +220,7 @@ class DependencyManager(object):
         labels = {}
         for item in self.items:
             assert item.cls and issubclass(item.cls, BaseChallenge)
-            data = item.cls.info.dict()
+            data = item.cls.info.model_dump()
 
             node_name = get_name(item)
             data["name"] = node_name

benchmark/agbenchmark/utils/utils.py

@@ -135,7 +135,7 @@ def pretty_print_model(model: BaseModel, include_header: bool = True) -> None:
     if include_header:
         # Try to find the ID and/or name attribute of the model
         id, name = None, None
-        for attr, value in model.dict().items():
+        for attr, value in model.model_dump().items():
             if attr == "id" or attr.endswith("_id"):
                 id = value
             if attr.endswith("name"):
@@ -148,8 +148,8 @@ def pretty_print_model(model: BaseModel, include_header: bool = True) -> None:
         )
         indent = " " * 2
 
-    k_col_width = max(len(k) for k in model.dict().keys())
-    for k, v in model.dict().items():
+    k_col_width = max(len(k) for k in model.model_dump().keys())
+    for k, v in model.model_dump().items():
         v_fmt = repr(v)
         if v is None or v == "":
             v_fmt = click.style(v_fmt, fg="black")

benchmark/poetry.lock

@@ -5,17 +5,22 @@ name = "agent-protocol-client"
 version = "1.1.0"
 description = "Agent Communication Protocol Client"
 optional = false
-python-versions = ">=3.7,<4.0"
-files = [
-    {file = "agent_protocol_client-1.1.0-py3-none-any.whl", hash = "sha256:0e8c6c97244189666ed18e320410abddce8c9dfb75437da1e590bbef3b6268be"},
-    {file = "agent_protocol_client-1.1.0.tar.gz", hash = "sha256:aa7e1042de1249477fdc29c2df08a44f2233dade9c02c1279e37c98e9d3a0d72"},
-]
+python-versions = "^3.7"
+files = []
+develop = false
 
 [package.dependencies]
-aiohttp = ">=3.8.4,<4.0.0"
-pydantic = ">=1.10.5,<2.0.0"
-python-dateutil = ">=2.8.2,<3.0.0"
-urllib3 = ">=1.25.3,<2.0.0"
+aiohttp = "^3.8.4"
+pydantic = ">=1.10.5, <3.0.0"
+python-dateutil = "^2.8.2"
+urllib3 = "^1.25.3"
+
+[package.source]
+type = "git"
+url = "https://github.com/Significant-Gravitas/agent-protocol.git"
+reference = "HEAD"
+resolved_reference = "beb098517b0b9e255024d1b57df236f0329f4b1c"
+subdirectory = "packages/client/python"
 
 [[package]]
 name = "aiohttp"
@@ -127,6 +132,17 @@ files = [
 [package.dependencies]
 frozenlist = ">=1.1.0"
 
+[[package]]
+name = "annotated-types"
+version = "0.7.0"
+description = "Reusable constraint types to use with typing.Annotated"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
+    {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
+]
+
 [[package]]
 name = "anyio"
 version = "4.2.0"
@@ -1440,85 +1456,101 @@ files = [
 
 [[package]]
 name = "multidict"
-version = "6.0.4"
+version = "6.0.5"
 description = "multidict implementation"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "multidict-6.0.4-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:0b1a97283e0c85772d613878028fec909f003993e1007eafa715b24b377cb9b8"},
-    {file = "multidict-6.0.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:eeb6dcc05e911516ae3d1f207d4b0520d07f54484c49dfc294d6e7d63b734171"},
-    {file = "multidict-6.0.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:d6d635d5209b82a3492508cf5b365f3446afb65ae7ebd755e70e18f287b0adf7"},
-    {file = "multidict-6.0.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c048099e4c9e9d615545e2001d3d8a4380bd403e1a0578734e0d31703d1b0c0b"},
-    {file = "multidict-6.0.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ea20853c6dbbb53ed34cb4d080382169b6f4554d394015f1bef35e881bf83547"},
-    {file = "multidict-6.0.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:16d232d4e5396c2efbbf4f6d4df89bfa905eb0d4dc5b3549d872ab898451f569"},
-    {file = "multidict-6.0.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:36c63aaa167f6c6b04ef2c85704e93af16c11d20de1d133e39de6a0e84582a93"},
-    {file = "multidict-6.0.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:64bdf1086b6043bf519869678f5f2757f473dee970d7abf6da91ec00acb9cb98"},
-    {file = "multidict-6.0.4-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:43644e38f42e3af682690876cff722d301ac585c5b9e1eacc013b7a3f7b696a0"},
-    {file = "multidict-6.0.4-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:7582a1d1030e15422262de9f58711774e02fa80df0d1578995c76214f6954988"},
-    {file = "multidict-6.0.4-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:ddff9c4e225a63a5afab9dd15590432c22e8057e1a9a13d28ed128ecf047bbdc"},
-    {file = "multidict-6.0.4-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:ee2a1ece51b9b9e7752e742cfb661d2a29e7bcdba2d27e66e28a99f1890e4fa0"},
-    {file = "multidict-6.0.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:a2e4369eb3d47d2034032a26c7a80fcb21a2cb22e1173d761a162f11e562caa5"},
-    {file = "multidict-6.0.4-cp310-cp310-win32.whl", hash = "sha256:574b7eae1ab267e5f8285f0fe881f17efe4b98c39a40858247720935b893bba8"},
-    {file = "multidict-6.0.4-cp310-cp310-win_amd64.whl", hash = "sha256:4dcbb0906e38440fa3e325df2359ac6cb043df8e58c965bb45f4e406ecb162cc"},
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+[package.extras]
+toml = ["tomli (>=2.0.1)"]
+yaml = ["pyyaml (>=6.0.1)"]
 
 [[package]]
 name = "pyflakes"
@@ -2192,21 +2301,21 @@ testing = ["argcomplete", "attrs (>=19.2.0)", "hypothesis (>=3.56)", "mock", "no
 
 [[package]]
 name = "pytest-asyncio"
-version = "0.21.1"
+version = "0.23.7"
 description = "Pytest support for asyncio"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "pytest-asyncio-0.21.1.tar.gz", hash = "sha256:40a7eae6dded22c7b604986855ea48400ab15b069ae38116e8c01238e9eeb64d"},
-    {file = "pytest_asyncio-0.21.1-py3-none-any.whl", hash = "sha256:8666c1c8ac02631d7c51ba282e0c69a8a452b211ffedf2599099845da5c5c37b"},
+    {file = "pytest_asyncio-0.23.7-py3-none-any.whl", hash = "sha256:009b48127fbe44518a547bddd25611551b0e43ccdbf1e67d12479f569832c20b"},
+    {file = "pytest_asyncio-0.23.7.tar.gz", hash = "sha256:5f5c72948f4c49e7db4f29f2521d4031f1c27f86e57b046126654083d4770268"},
 ]
 
 [package.dependencies]
-pytest = ">=7.0.0"
+pytest = ">=7.0.0,<9"
 
 [package.extras]
 docs = ["sphinx (>=5.3)", "sphinx-rtd-theme (>=1.0)"]
-testing = ["coverage (>=6.2)", "flaky (>=3.5.0)", "hypothesis (>=5.7.1)", "mypy (>=0.931)", "pytest-trio (>=0.7.0)"]
+testing = ["coverage (>=6.2)", "hypothesis (>=5.7.1)"]
 
 [[package]]
 name = "pytest-cov"
@@ -2628,31 +2737,6 @@ exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
 trio = ">=0.11"
 wsproto = ">=0.14"
 
-[[package]]
-name = "types-requests"
-version = "2.31.0.6"
-description = "Typing stubs for requests"
-optional = false
-python-versions = ">=3.7"
-files = [
-    {file = "types-requests-2.31.0.6.tar.gz", hash = "sha256:cd74ce3b53c461f1228a9b783929ac73a666658f223e28ed29753771477b3bd0"},
-    {file = "types_requests-2.31.0.6-py3-none-any.whl", hash = "sha256:a2db9cb228a81da8348b49ad6db3f5519452dd20a9c1e1a868c83c5fe88fd1a9"},
-]
-
-[package.dependencies]
-types-urllib3 = "*"
-
-[[package]]
-name = "types-urllib3"
-version = "1.26.25.14"
-description = "Typing stubs for urllib3"
-optional = false
-python-versions = "*"
-files = [
-    {file = "types-urllib3-1.26.25.14.tar.gz", hash = "sha256:229b7f577c951b8c1b92c1bc2b2fdb0b49847bd2af6d1cc2a2e3dd340f3bda8f"},
-    {file = "types_urllib3-1.26.25.14-py3-none-any.whl", hash = "sha256:9683bbb7fb72e32bfe9d2be6e04875fbe1b3eeec3cbb4ea231435aa7fd6b4f0e"},
-]
-
 [[package]]
 name = "typing-extensions"
 version = "4.9.0"
@@ -2864,4 +2948,4 @@ multidict = ">=4.0"
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "4a980e6d8f54a2f7f6a3c55d4f40ac3a4b27b5ac6573dd2a39e11213a4b126dd"
+content-hash = "26bd75befe5223095b65be293086edf52f34f9043e49107c80a105dc0387dd6a"

benchmark/pyproject.toml

@@ -9,43 +9,47 @@ packages = [{ include = "agbenchmark" }]
 
 [tool.poetry.dependencies]
 python = "^3.10"
-pytest = "^7.3.2"
-requests = "^2.31.0"
-openai = "^1.7.2"
-pydantic = "^1.10.9"
-python-dotenv = "^1.0.0"
+agent-protocol-client = {git = "https://github.com/Significant-Gravitas/agent-protocol.git", subdirectory = "packages/client/python"}
 click = "^8.1.3"
-types-requests = "^2.31.0.1"
+click-default-group = "^1.2.4"
+colorama = "^0.4.6"
+fastapi = "^0.109.1"
+gitpython = "^3.1.32"
+httpx = "^0.24.0"
+matplotlib = "^3.7.2"
+# Multidict 6.0.4 fails to install and is a dependency of aiohttp which is a depenedency of agent-protocol-client
+multidict = "^6.0.5"
+networkx = "^3.1"
+openai = "^1.7.2"
+pandas = "^2.0.3"
 pexpect = "^4.8.0"
 psutil = "^5.9.5"
-matplotlib = "^3.7.2"
-pandas = "^2.0.3"
-gitpython = "^3.1.32"
-networkx = "^3.1"
-colorama = "^0.4.6"
-pyvis = "^0.3.2"
-selenium = "^4.11.2"
-pytest-asyncio = "^0.21.1"
-uvicorn = "^0.23.2"
-fastapi = "^0.109.1"
+pydantic = "^2.7.2"
+pydantic-settings = "^2.3.4"
+pytest = "^7.3.2"
+pytest-asyncio = "^0.23.3"
+python-dotenv = "^1.0.0"
 python-multipart = "^0.0.7"
-toml = "^0.10.2"
-# helicone = "^1.0.9"  # incompatible with openai@^1.0.0
-httpx = "^0.24.0"
-agent-protocol-client = "^1.1.0"
-click-default-group = "^1.2.4"
+pyvis = "^0.3.2"
+requests = "^2.31.0"
+selenium = "^4.11.2"
 tabulate = "^0.9.0"
+toml = "^0.10.2"
+uvicorn = ">=0.23.2,<1"
 
 [tool.poetry.group.dev.dependencies]
 black = "^23.12.1"
 flake8 = "^7.0.0"
 isort = "^5.13.1"
 pyright = "^1.1.364"
-pandas = "^2.0.3"
+pre-commit = "^3.3.3"
+
+# Testing
+pytest-cov = "^5.0.0"
+
+# Dependencies for stuff in reports/
 gspread = "^5.10.0"
 oauth2client = "^4.1.3"
-pre-commit = "^3.3.3"
-pytest-cov = "^5.0.0"
 
 [tool.poetry.scripts]
 agbenchmark = "agbenchmark.__main__:cli"

benchmark/reports/format.py

@@ -1,20 +1,24 @@
 #!/usr/bin/env python3
 
+from pathlib import Path
+
 import click
 
 from agbenchmark.reports.processing.report_types import Report
 
 
 @click.command()
-@click.argument("report_json_file", type=click.Path(exists=True, dir_okay=False))
-def print_markdown_report(report_json_file: str):
+@click.argument(
+    "report_json_file", type=click.Path(exists=True, dir_okay=False, path_type=Path)
+)
+def print_markdown_report(report_json_file: Path):
     """
     Generates a Markdown report from a given report.json file.
 
     :param report_json_file: Path to the report.json file.
     :return: A string containing the Markdown formatted report.
     """
-    report = Report.parse_file(report_json_file)
+    report = Report.model_validate_json(report_json_file.read_text())
 
     # Header and metadata
     click.echo("# Benchmark Report")

benchmark/reports/match_records.py

@@ -14,7 +14,7 @@ from pydantic import BaseModel, Field
 class Metrics(BaseModel):
     difficulty: str
     success: bool
-    success_percent: float = Field(..., alias="success_%")
+    success_percent: float = Field(alias="success_%")
     run_time: Optional[str] = None
     fail_reason: Optional[str] = None
     attempted: Optional[bool] = None
@@ -100,7 +100,7 @@ def get_reports():
                         # Load the JSON data from the file
                         json_data = json.load(f)
                         print(f"Processing {report_file}")
-                        report = Report.parse_obj(json_data)
+                        report = Report.model_validate(json_data)
 
                         for test_name, test_data in report.tests.items():
                             test_json = {

check_actions_status.py

@@ -0,0 +1,109 @@
+import json
+import os
+import requests
+import sys
+import time
+from typing import Dict, List, Tuple
+
+
+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)
+
+        sha = event["pull_request"]["head"]["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. Waiting 3 minutes before checking again..."
+        )
+        time.sleep(180)
+
+    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()

cli.py

@@ -69,6 +69,8 @@ d88P     888  "Y88888  "Y888 "Y88P"   "Y8888P88 888           888
                 bold=True,
             )
         )
+    else:
+        click.echo(click.style("🎉 Setup completed!\n", fg="green"))
 
 
 @cli.group()

docs/content/AutoGPT/configuration/options.md

@@ -1,6 +1,7 @@
 # Configuration
 
-Configuration is controlled through the `Config` object. You can set configuration variables via the `.env` file. If you don't have a `.env` file, create a copy of `.env.template` in your `AutoGPT` folder and name it `.env`.
+Configuration of sensitive settings such as API credentials is done through environment variables.
+You can set configuration variables via the `.env` file. If you don't have a `.env` file, create a copy of `.env.template` in your `AutoGPT` folder and name it `.env`.
 
 ## Environment Variables
 
@@ -8,7 +9,7 @@ Configuration is controlled through the `Config` object. You can set configurati
 - `ANTHROPIC_API_KEY`: Set this if you want to use Anthropic models with AutoGPT
 - `AZURE_CONFIG_FILE`: Location of the Azure Config file relative to the AutoGPT root directory. Default: azure.yaml
 - `COMPONENT_CONFIG_FILE`: Path to the component configuration file (json) for an agent. Optional
-- `DISABLED_COMMANDS`: Commands to disable. Use comma separated names of commands. See the list of commands from built-in components [here](../components/components.md). Default: None
+- `DISABLED_COMMANDS`: Commands to disable. Use comma separated names of commands. See the list of commands from built-in components [here](../../forge/components/components.md). Default: None
 - `ELEVENLABS_API_KEY`: ElevenLabs API Key. Optional.
 - `ELEVENLABS_VOICE_ID`: ElevenLabs Voice ID. Optional.
 - `EMBEDDING_MODEL`: LLM Model to use for embedding tasks. Default: `text-embedding-3-small`
@@ -21,7 +22,8 @@ Configuration is controlled through the `Config` object. You can set configurati
 - `GROQ_API_KEY`: Set this if you want to use Groq models with AutoGPT
 - `HUGGINGFACE_API_TOKEN`: HuggingFace API, to be used for both image generation and audio to text. Optional.
 - `HUGGINGFACE_IMAGE_MODEL`: HuggingFace model to use for image generation. Default: CompVis/stable-diffusion-v1-4
-- `OPENAI_API_KEY`: *REQUIRED*- Your [OpenAI API Key](https://platform.openai.com/account/api-keys).
+- `LLAMAFILE_API_BASE`: Llamafile API base URL. Default: `http://localhost:8080/v1`
+- `OPENAI_API_KEY`: Set this if you want to use OpenAI models; [OpenAI API Key](https://platform.openai.com/account/api-keys).
 - `OPENAI_ORGANIZATION`: Organization ID in OpenAI. Optional.
 - `PLAIN_OUTPUT`: Plain output, which disables the spinner. Default: False
 - `RESTRICT_TO_WORKSPACE`: The restrict file reading and writing to the workspace directory. Default: True
@@ -31,4 +33,3 @@ Configuration is controlled through the `Config` object. You can set configurati
 - `TEMPERATURE`: Value of temperature given to OpenAI. Value from 0 to 2. Lower is more deterministic, higher is more random. See https://platform.openai.com/docs/api-reference/completions/create#completions/create-temperature
 - `TEXT_TO_SPEECH_PROVIDER`: Text to Speech Provider. Options are `gtts`, `macos`, `elevenlabs`, and `streamelements`. Default: gtts
 - `USE_AZURE`: Use Azure's LLM Default: False
-- `WIPE_REDIS_ON_START`: Wipes data / index on start. Default: True

docs/content/AutoGPT/setup/docker.md

@@ -71,18 +71,25 @@
           - ./logs:/app/logs
           ## uncomment following lines if you want to make use of these files
           ## you must have them existing in the same folder as this docker-compose.yml
+          ## component configuration file
+          #- type: bind
+          #  source: ./config.json
+          #  target: /app/config.json
     ```
     </details>
 
 
-4. Download [`.env.template`][.env.template] and save it as `.env` in the AutoGPT folder.
-5. Follow the standard [configuration instructions](../index.md#completing-the-setup),
+1. Download [`.env.template`][.env.template] and save it as `.env` in the AutoGPT folder.
+2. Follow the standard [configuration instructions](../index.md#completing-the-setup),
    from step 3 onwards and excluding `poetry install` steps.
-6. Pull the latest image from [Docker Hub]
+3. Pull the latest image from [Docker Hub]
 
     ```shell
     docker pull significantgravitas/auto-gpt
     ```
+4. _Optional: mount configuration file._
+      If you have component configuration file, for example `config.json`, place it in `autogpt/data/` directory. Or place it in `autogpt/` and uncomment the line in `docker-compose.yml` that mounts it.
+      To learn more about configuring, see [Component configuration](../../forge/components/components.md#json-configuration)
 
 !!! note "Docker only supports headless browsing"
     AutoGPT uses a browser in headless mode by default: `HEADLESS_BROWSER=True`.

docs/content/AutoGPT/setup/index.md

@@ -50,7 +50,13 @@ Since we don't ship AutoGPT as a desktop application, you'll need to download th
 ### Completing the Setup
 
 Once you have cloned or downloaded the project, you can find the AutoGPT Agent in the
-`autogpt/` folder. In this folder:
+`autogpt/` folder.
+Inside this folder you can configure the AutoGPT application with an `.env` file and (optionally) a JSON configuration file:
+
+- `.env` for environment variables, which are mostly used for sensitive data like API keys
+- a JSON configuration file to customize certain features of AutoGPT's [Components](../../forge/components/introduction.md)
+
+See the [Configuration](../configuration/options.md) reference for a list of available environment variables.
 
 1. Find the file named `.env.template`. This file may
     be hidden by default in some operating systems due to the dot prefix. To reveal
@@ -71,6 +77,9 @@ Once you have cloned or downloaded the project, you can find the AutoGPT Agent i
 6. Save and close the `.env` file.
 7. _Optional: run `poetry install` to install all required dependencies._ The
     application also checks for and installs any required dependencies when it starts.
+8. _Optional: configure the JSON file (e.g. `config.json`) with your desired settings._
+    The application will use default settings if you don't provide a JSON configuration file.
+    Learn how to [set up the JSON configuration file](../../forge/components/components.md#json-configuration)
 
 You should now be able to explore the CLI (`./autogpt.sh --help`) and run the application.
 
@@ -79,7 +88,6 @@ See the [user guide](../usage.md) for further instructions.
 [show hidden files/Windows]: https://support.microsoft.com/en-us/windows/view-hidden-files-and-folders-in-windows-97fbc472-c603-9d90-91d0-1166d1d9f4b5
 [show hidden files/macOS]: https://www.pcmag.com/how-to/how-to-access-your-macs-hidden-files
 
-
 ## Setting up LLM providers
 
 You can use AutoGPT with any of the following LLM providers.
@@ -190,3 +198,66 @@ If you don't know which to choose, you can safely go with OpenAI*.
 
 [groq/api-keys]: https://console.groq.com/keys
 [groq/models]: https://console.groq.com/docs/models
+
+
+### Llamafile
+
+With llamafile you can run models locally, which means no need to set up billing,
+and guaranteed data privacy.
+
+For more information and in-depth documentation, check out the [llamafile documentation].
+
+!!! warning
+    At the moment, llamafile only serves one model at a time. This means you can not
+    set `SMART_LLM` and `FAST_LLM` to two different llamafile models.
+
+!!! warning
+    Due to the issues linked below, llamafiles don't work on WSL. To use a llamafile
+    with AutoGPT in WSL, you will have to run the llamafile in Windows (outside WSL).
+
+    <details>
+    <summary>Instructions</summary>
+
+    1. Get the `llamafile/serve.py` script through one of these two ways:
+        1. Clone the AutoGPT repo somewhere in your Windows environment,
+           with the script located at `autogpt/scripts/llamafile/serve.py`
+        2. Download just the [serve.py] script somewhere in your Windows environment
+    2. Make sure you have `click` installed: `pip install click`
+    3. Run `ip route | grep default | awk '{print $3}'` *inside WSL* to get the address
+       of the WSL host machine
+    4. Run `python3 serve.py --host {WSL_HOST_ADDR}`, where `{WSL_HOST_ADDR}`
+       is the address you found at step 3.
+       If port 8080 is taken, also specify a different port using `--port {PORT}`.
+    5. In WSL, set `LLAMAFILE_API_BASE=http://{WSL_HOST_ADDR}:8080/v1` in your `.env`.
+    6. Follow the rest of the regular instructions below.
+
+    [serve.py]: https://github.com/Significant-Gravitas/AutoGPT/blob/master/autogpt/scripts/llamafile/serve.py
+    </details>
+
+    * [Mozilla-Ocho/llamafile#356](https://github.com/Mozilla-Ocho/llamafile/issues/356)
+    * [Mozilla-Ocho/llamafile#100](https://github.com/Mozilla-Ocho/llamafile/issues/100)
+
+!!! note
+    These instructions will download and use `mistral-7b-instruct-v0.2.Q5_K_M.llamafile`.
+    `mistral-7b-instruct-v0.2` is currently the only tested and supported model.
+    If you want to try other models, you'll have to add them to `LlamafileModelName` in
+    [`llamafile.py`][forge/llamafile.py].
+    For optimal results, you may also have to add some logic to adapt the message format,
+    like `LlamafileProvider._adapt_chat_messages_for_mistral_instruct(..)` does.
+
+1. Run the llamafile serve script:
+   ```shell
+   python3 ./scripts/llamafile/serve.py
+   ```
+   The first time this is run, it will download a file containing the model + runtime,
+   which may take a while and a few gigabytes of disk space.
+
+   To force GPU acceleration, add `--use-gpu` to the command.
+
+3. In `.env`, set `SMART_LLM`/`FAST_LLM` or both to `mistral-7b-instruct-v0.2`
+
+4. If the server is running on different address than `http://localhost:8080/v1`,
+   set `LLAMAFILE_API_BASE` in `.env` to the right base URL
+
+[llamafile documentation]: https://github.com/Mozilla-Ocho/llamafile#readme
+[forge/llamafile.py]: https://github.com/Significant-Gravitas/AutoGPT/blob/master/forge/forge/llm/providers/llamafile/llamafile.py

docs/content/AutoGPT/usage.md

@@ -213,5 +213,5 @@ For example, to disable python coding features, set it to the value below:
 DISABLED_COMMANDS=execute_python_code,execute_python_file
 ```
 
-[components]: ./components/components.md
-[commands]: ./components/built-in-components.md
+[components]: ../forge/components/components.md
+[commands]: ../forge/components/built-in-components.md

docs/content/forge/components/built-in-components.md

@@ -1,25 +1,25 @@
 # Built-in Components
 
 This page lists all [🧩 Components](./components.md) and [⚙️ Protocols](./protocols.md) they implement that are natively provided. They are used by the AutoGPT agent.
-Some components have additional configuration options listed in the table, see [Component configuration](./components.md/#ordering-components) to learn more.
+Some components have additional configuration options listed in the table, see [Component configuration](./components.md/#component-configuration) to learn more.
 
 !!! note
-    If a configuration field uses environment variable, it still can be passed using configuration model. **Value from the configuration takes precedence over env var!** Env var will be only applied if value in the configuration is not set.
+    If a configuration field uses environment variable, it still can be passed using configuration model. ### Value from the configuration takes precedence over env var! Env var will be only applied if value in the configuration is not set.
 
 ## `SystemComponent`
 
 Essential component to allow an agent to finish.
 
-**DirectiveProvider**
+### DirectiveProvider
 
 - Constraints about API budget
-  
-**MessageProvider**
+
+### MessageProvider
 
 - Current time and date
 - Remaining API budget and warnings if budget is low
 
-**CommandProvider**
+### CommandProvider
 
 - `finish` used when task is completed
 
@@ -27,7 +27,7 @@ Essential component to allow an agent to finish.
 
 Adds ability to interact with user in CLI.
 
-**CommandProvider**
+### CommandProvider
 
 - `ask_user` used to ask user for input
 
@@ -36,18 +36,20 @@ Adds ability to interact with user in CLI.
 Adds ability to read and write persistent files to local storage, Google Cloud Storage or Amazon's S3.
 Necessary for saving and loading agent's state (preserving session).
 
+### `FileManagerConfiguration`
+
 | Config variable  | Details                                | Type  | Default                            |
 | ---------------- | -------------------------------------- | ----- | ---------------------------------- |
-| `files_path`     | Path to agent files, e.g. state        | `str` | `agents/{agent_id}/`[^1]           |
+| `storage_path`   | Path to agent files, e.g. state        | `str` | `agents/{agent_id}/`[^1]           |
 | `workspace_path` | Path to files that agent has access to | `str` | `agents/{agent_id}/workspace/`[^1] |
 
 [^1] This option is set dynamically during component construction as opposed to by default inside the configuration model, `{agent_id}` is replaced with the agent's unique identifier.
 
-**DirectiveProvider**
+### DirectiveProvider
 
 - Resource information that it's possible to read and write files
 
-**CommandProvider**
+### CommandProvider
 
 - `read_file` used to read file
 - `write_file` used to write file
@@ -57,6 +59,8 @@ Necessary for saving and loading agent's state (preserving session).
 
 Lets the agent execute non-interactive Shell commands and Python code. Python execution works only if Docker is available.
 
+### `CodeExecutorConfiguration`
+
 | Config variable          | Details                                              | Type                        | Default           |
 | ------------------------ | ---------------------------------------------------- | --------------------------- | ----------------- |
 | `execute_local_commands` | Enable shell command execution                       | `bool`                      | `False`           |
@@ -65,7 +69,9 @@ Lets the agent execute non-interactive Shell commands and Python code. Python ex
 | `shell_denylist`         | List of prohibited shell commands                    | `List[str]`                 | `[]`              |
 | `docker_container_name`  | Name of the Docker container used for code execution | `str`                       | `"agent_sandbox"` |
 
-**CommandProvider**
+All shell command configurations are expected to be for convience only. This component is not secure and should not be used in production environments. It is recommended to use more appropriate sandboxing.
+
+### CommandProvider
 
 - `execute_shell` execute shell command
 - `execute_shell_popen` execute shell command with popen
@@ -76,25 +82,28 @@ Lets the agent execute non-interactive Shell commands and Python code. Python ex
 
 Keeps track of agent's actions and their outcomes. Provides their summary to the prompt.
 
+### `ActionHistoryConfiguration`
+
 | Config variable        | Details                                                 | Type        | Default            |
 | ---------------------- | ------------------------------------------------------- | ----------- | ------------------ |
-| `model_name`           | Name of the llm model used to compress the history      | `ModelName` | `"gpt-3.5-turbo"`  |
+| `llm_name`             | Name of the llm model used to compress the history      | `ModelName` | `"gpt-3.5-turbo"`  |
 | `max_tokens`           | Maximum number of tokens to use for the history summary | `int`       | `1024`             |
 | `spacy_language_model` | Language model used for summary chunking using spacy    | `str`       | `"en_core_web_sm"` |
+| `full_message_count`   | Number of cycles to include unsummarized in the prompt  | `int`       | `4`                |
 
-**MessageProvider**
+### MessageProvider
 
 - Agent's progress summary
 
-**AfterParse**
+### AfterParse
 
 - Register agent's action
 
-**ExecutionFailure**
+### ExecutionFailure
 
 - Rewinds the agent's action, so it isn't saved
 
-**AfterExecute**
+### AfterExecute
 
 - Saves the agent's action result in the history
 
@@ -102,12 +111,14 @@ Keeps track of agent's actions and their outcomes. Provides their summary to the
 
 Adds ability to iteract with git repositories and GitHub.
 
+### `GitOperationsConfiguration`
+
 | Config variable   | Details                                   | Type  | Default |
 | ----------------- | ----------------------------------------- | ----- | ------- |
 | `github_username` | GitHub username, *ENV:* `GITHUB_USERNAME` | `str` | `None`  |
 | `github_api_key`  | GitHub API key, *ENV:* `GITHUB_API_KEY`   | `str` | `None`  |
 
-**CommandProvider**
+### CommandProvider
 
 - `clone_repository` used to clone a git repository
 
@@ -122,7 +133,9 @@ Link to the appropriate settings page: [Hugging Face > Settings > Tokens](https:
 
 ### Stable Diffusion WebUI
 
-It is possible to use your own self-hosted Stable Diffusion WebUI with AutoGPT. **Make sure you are running WebUI with `--api` enabled.**
+It is possible to use your own self-hosted Stable Diffusion WebUI with AutoGPT. ### Make sure you are running WebUI with `--api` enabled.
+
+### `ImageGeneratorConfiguration`
 
 | Config variable           | Details                                                       | Type                                    | Default                           |
 | ------------------------- | ------------------------------------------------------------- | --------------------------------------- | --------------------------------- |
@@ -134,7 +147,7 @@ It is possible to use your own self-hosted Stable Diffusion WebUI with AutoGPT.
 
 [available models]: https://huggingface.co/models?pipeline_tag=text-to-image
 
-**CommandProvider**
+### CommandProvider
 
 - `generate_image` used to generate an image given a prompt
 
@@ -142,17 +155,20 @@ It is possible to use your own self-hosted Stable Diffusion WebUI with AutoGPT.
 
 Allows agent to search the web. Google credentials aren't required for DuckDuckGo. [Instructions how to set up Google API key](../../AutoGPT/configuration/search.md)
 
-| Config variable                  | Details                                                                 | Type  | Default |
-| -------------------------------- | ----------------------------------------------------------------------- | ----- | ------- |
-| `google_api_key`                 | Google API key, *ENV:* `GOOGLE_API_KEY`                                 | `str` | `None`  |
-| `google_custom_search_engine_id` | Google Custom Search Engine ID, *ENV:* `GOOGLE_CUSTOM_SEARCH_ENGINE_ID` | `str` | `None`  |
-| `duckduckgo_max_attempts`        | Maximum number of attempts to search using DuckDuckGo                   | `int` | `3`     |
+### `WebSearchConfiguration`
 
-**DirectiveProvider**
+| Config variable                  | Details                                                                 | Type                        | Default |
+| -------------------------------- | ----------------------------------------------------------------------- | --------------------------- | ------- |
+| `google_api_key`                 | Google API key, *ENV:* `GOOGLE_API_KEY`                                 | `str`                       | `None`  |
+| `google_custom_search_engine_id` | Google Custom Search Engine ID, *ENV:* `GOOGLE_CUSTOM_SEARCH_ENGINE_ID` | `str`                       | `None`  |
+| `duckduckgo_max_attempts`        | Maximum number of attempts to search using DuckDuckGo                   | `int`                       | `3`     |
+| `duckduckgo_backend`             | Backend to be used for DDG sdk                                          | `"api" \| "html" \| "lite"` | `"api"` |
+
+### DirectiveProvider
 
 - Resource information that it's possible to search the web
 
-**CommandProvider**
+### CommandProvider
 
 - `search_web` used to search the web using DuckDuckGo
 - `google` used to search the web using Google, requires API key
@@ -161,19 +177,22 @@ Allows agent to search the web. Google credentials aren't required for DuckDuckG
 
 Allows agent to read websites using Selenium.
 
+### `WebSeleniumConfiguration`
+
 | Config variable               | Details                                     | Type                                          | Default                                                                                                                      |
 | ----------------------------- | ------------------------------------------- | --------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------- |
-| `model_name`                  | Name of the llm model used to read websites | `ModelName`                                   | `"gpt-3.5-turbo"`                                                                                                            |
+| `llm_name`                    | Name of the llm model used to read websites | `ModelName`                                   | `"gpt-3.5-turbo"`                                                                                                            |
 | `web_browser`                 | Web browser used by Selenium                | `"chrome" \| "firefox" \| "safari" \| "edge"` | `"chrome"`                                                                                                                   |
 | `headless`                    | Run browser in headless mode                | `bool`                                        | `True`                                                                                                                       |
 | `user_agent`                  | User agent used by the browser              | `str`                                         | `"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"` |
 | `browse_spacy_language_model` | Spacy language model used for chunking text | `str`                                         | `"en_core_web_sm"`                                                                                                           |
+| `selenium_proxy`              | Http proxy to use with Selenium             | `str`                                         | `None`                                                                                                                       |
 
-**DirectiveProvider**
+### DirectiveProvider
 
 - Resource information that it's possible to read websites
 
-**CommandProvider**
+### CommandProvider
 
 - `read_website` used to read a specific url and look for specific topics or answer a question
 
@@ -181,11 +200,11 @@ Allows agent to read websites using Selenium.
 
 Adds ability to keep up-to-date file and folder content in the prompt.
 
-**MessageProvider**
+### MessageProvider
 
 - Content of elements in the context
 
-**CommandProvider**
+### CommandProvider
 
 - `open_file` used to open a file into context
 - `open_folder` used to open a folder into context
@@ -195,6 +214,6 @@ Adds ability to keep up-to-date file and folder content in the prompt.
 
 Watches if agent is looping and switches to smart mode if necessary.
 
-**AfterParse**
+### AfterParse
 
 - Investigates what happened and switches to smart mode if necessary

docs/content/forge/components/creating-components.md

@@ -37,7 +37,7 @@ Since components are regular classes you can pass data (including other componen
 For example we can pass a config object and then retrieve an API key from it when needed:
 
 ```py
-class ConfigurableComponent(MessageProvider):
+class DataComponent(MessageProvider):
     def __init__(self, config: Config):
         self.config = config
 
@@ -51,6 +51,35 @@ class ConfigurableComponent(MessageProvider):
 !!! note
     Component-specific configuration handling isn't implemented yet.
 
+## Configuring components
+
+Components can be configured using a pydantic model.
+To make component configurable, it must inherit from `ConfigurableComponent[BM]` where `BM` is the configuration class inheriting from pydantic's `BaseModel`.
+You should pass the configuration instance to the `ConfigurableComponent`'s `__init__` or set its `config` property directly.
+Using configuration allows you to load confugration from a file, and also serialize and deserialize it easily for any agent.
+To learn more about configuration, including storing sensitive information and serialization see [Component Configuration](./components.md#component-configuration).
+
+```py
+# Example component configuration
+class UserGreeterConfiguration(BaseModel):
+    user_name: str
+
+class UserGreeterComponent(MessageProvider, ConfigurableComponent[UserGreeterConfiguration]):
+    def __init__(self):
+        # Creating configuration instance
+        # You could also pass it to the component constructor
+        # e.g. `def __init__(self, config: UserGreeterConfiguration):`
+        config = UserGreeterConfiguration(user_name="World")
+        # Passing the configuration instance to the parent class
+        UserGreeterComponent.__init__(self, config)
+        # This has the same effect as the line above:
+        # self.config = UserGreeterConfiguration(user_name="World")
+
+    def get_messages(self) -> Iterator[ChatMessage]:
+        # You can use the configuration like a regular model
+        yield ChatMessage.system(f"Hello, {self.config.user_name}!")
+```
+
 ## Providing commands
 
 To extend what an agent can do, you need to provide commands using `CommandProvider` protocol. For example to allow agent to multiply two numbers, you can create a component like this:

docs/content/forge/components/introduction.md

@@ -10,7 +10,7 @@ This guide explains the component-based architecture of AutoGPT agents. It's a n
 
 Agent is composed of *components*, and each *component* implements a range of *protocols* (interfaces), each one providing a specific functionality, e.g. additional commands or messages. Each *protocol* is handled in a specific order, defined by the agent. This allows for a clear separation of concerns and a more modular design.
 
-This system is simple, flexible, requires basically no configuration, and doesn't hide any data - anything can still be passed or accessed directly from or between components.
+This system is simple, flexible, and doesn't hide any data - anything can still be passed or accessed directly from or between components.
 
 ### Definitions & Guides
 

docs/content/forge/get-started.md

@@ -19,16 +19,16 @@ Forge is a ready-to-go template for *your* agent application. All the boilerplat
 
 ### 🚀 **Get Started!**
 
+The best way to get started is to fork or download the AutoGPT repository and look at the example agent in `forge/forge/agent/forge_agent.py`.
+This can work as a starting point for your own agent.
+Agents are built using *components* which provide different functionality, see the [Component Introduction](./components/introduction.md). You can find built-in components in `forge/forge/components/`.
+
+!!! warning
+    The tutorial series below is out of date.
+
 The getting started [tutorial series](https://aiedge.medium.com/autogpt-forge-e3de53cc58ec) will guide you through the process of setting up your project all the way through to building a generalist agent.  
 
 1. [AutoGPT Forge: A Comprehensive Guide to Your First Steps](https://aiedge.medium.com/autogpt-forge-a-comprehensive-guide-to-your-first-steps-a1dfdf46e3b4)
 2. [AutoGPT Forge: The Blueprint of an AI Agent](https://aiedge.medium.com/autogpt-forge-the-blueprint-of-an-ai-agent-75cd72ffde6)
 3. [AutoGPT Forge: Interacting with your Agent](https://aiedge.medium.com/autogpt-forge-interacting-with-your-agent-1214561b06b)
 4. [AutoGPT Forge: Crafting Intelligent Agent Logic](https://medium.com/@aiedge/autogpt-forge-crafting-intelligent-agent-logic-bc5197b14cb4)
-
-Coming soon:
-
-5. Interacting with and Benchmarking your Agent
-6. Abilities
-7. The Planning Loop
-8. Memories

docs/content/index.md

@@ -4,13 +4,26 @@ Welcome to the AutoGPT Documentation.
 
 The AutoGPT project consists of four main components:
 
-* The [Agent](#agent) – also known as just "AutoGPT"
-* The [Benchmark](#benchmark) – AKA `agbenchmark`
-* The [Forge](#forge)
-* The [Frontend](#frontend)
+- The [Server](#server) – known as the "AutoGPT Platform"
+- The [Agent](#agent) – also known as just "AutoGPT"
+- The [Benchmark](#benchmark) – AKA `agbenchmark`
+- The [Forge](#forge)
+- The [Frontend](#frontend)
 
 To tie these together, we also have a [CLI] at the root of the project.
 
+## 🌐 Server
+
+<!-- Setup, then Advanced, then New Blocks -->
+
+**[📖 Setup](server/setup.md)**
+&ensp;|&ensp;
+**[📖 Advanced Setup](server/advanced_setup.md)**
+&ensp;|&ensp;
+**[📖 Making New Blocks](server/new_blocks.md)**
+
+The server is the backbone of the New AutoGPT project. It provides the infrastructure for the agents to run, and the UI for you to interact with them. It integrates with the Forge, Agent, and a bespoke UI to provide a seamless experience.
+
 ---
 
 ## 🤖 Agent

docs/content/server/advanced_setup.md

@@ -0,0 +1,69 @@
+# Advanced Setup
+
+The advanced steps below are intended for people with sysadmin experience. If you are not comfortable with these steps, please refer to the [basic setup guide](setup.md).
+
+## Introduction
+
+For the advanced setup, first follow the [basic setup guide](setup.md) to get the server up and running. Once you have the server running, you can follow the steps below to configure the server for your specific needs.
+
+## Configuration
+
+### Setting config via environment variables
+
+The server uses environment variables to store configs. You can set these environment variables in a `.env` file in the root of the project. The `.env` file should look like this:
+
+```bash
+# .env
+KEY1=value1
+KEY2=value2
+```
+
+The server will automatically load the `.env` file when it starts. You can also set the environment variables directly in your shell. Refer to your operating system's documentation on how to set environment variables in the current session.
+
+The valid options are listed in `.env.example` in the root of the builder and server directories. You can copy the `.env.example` file to `.env` and modify the values as needed.
+
+```bash
+# Copy the .env.example file to .env
+cp .env.example .env
+```
+
+### Secrets directory
+
+The secret directory is located at `./secrets`. You can store any secrets you need in this directory. The server will automatically load the secrets when it starts.
+
+An example for a secret called `my_secret` would look like this:
+
+```bash
+# ./secrets/my_secret
+my_secret_value
+```
+
+This is useful when running on docker so you can copy the secrets into the container without exposing them in the Dockerfile.
+
+## Database selection
+
+### SQLite
+
+By default, the server uses SQLite as the database. SQLite is a file-based database that is easy to set up and use. However, it is not recommended for production usecases where auth is required because that subsystem requires Postgres.
+
+### PostgreSQL
+
+For production use, it is recommended to use PostgreSQL as the database. You will swap the commands you use to generate and run prisma to the following
+
+```bash
+poetry run prisma generate --schema postgres/schema.prisma
+```
+
+This will generate the Prisma client for PostgreSQL. You will also need to run the PostgreSQL database in a separate container. You can use the `docker-compose.yml` file in the `rnd` directory to run the PostgreSQL database.
+
+```bash
+cd rnd/
+docker compose up -d
+```
+
+You can then run the migrations from the `autogpt_server` directory.
+
+```bash
+cd ../autogpt_server
+prisma migrate dev --schema postgres/schema.prisma
+```

docs/content/server/d_id.md

@@ -0,0 +1,17 @@
+# Find available voices for D-ID
+
+1. **ElevenLabs**
+   - Select any voice from the voice list: https://api.elevenlabs.io/v1/voices
+   - Copy the voice_id
+   - Use it as a string in the voice_id field in the CreateTalkingAvatarClip Block
+
+2. **Microsoft Azure Voices**
+    - Select any voice from the voice gallery: https://speech.microsoft.com/portal/voicegallery
+    - Click on the "Sample code" tab on the right
+    - Copy the voice name, for example: config.SpeechSynthesisVoiceName ="en-GB-AbbiNeural"
+    - Use this string en-GB-AbbiNeural in the voice_id field in the CreateTalkingAvatarClip Block
+
+3. **Amazon Polly Voices**
+    - Select any voice from the voice list: https://docs.aws.amazon.com/polly/latest/dg/available-voices.html
+    - Copy the voice name / ID
+    - Use it as string in the voice_id field in the CreateTalkingAvatarClip Block

docs/content/server/new_blocks.md

@@ -0,0 +1,224 @@
+# Contributing to AutoGPT Agent Server: Creating and Testing Blocks
+
+This guide will walk you through the process of creating and testing a new block for the AutoGPT Agent Server, using the WikipediaSummaryBlock as an example.
+
+## Understanding Blocks and Testing
+
+Blocks are reusable components that can be connected to form a graph representing an agent's behavior. Each block has inputs, outputs, and a specific function. Proper testing is crucial to ensure blocks work correctly and consistently.
+
+## Creating and Testing a New Block
+
+Follow these steps to create and test a new block:
+
+1. **Create a new Python file** in the `autogpt_server/blocks` directory. Name it descriptively and use snake_case. For example: `get_wikipedia_summary.py`.
+
+2. **Import necessary modules and create a class that inherits from `Block`**. Make sure to include all necessary imports for your block.
+
+ Every block should contain the following:
+
+   ```python
+   from autogpt_server.data.block import Block, BlockSchema, BlockOutput
+   ```
+
+   Example for the Wikipedia summary block:
+
+   ```python
+   from autogpt_server.data.block import Block, BlockSchema, BlockOutput
+   from autogpt_server.utils.get_request import GetRequest
+   import requests
+
+   class WikipediaSummaryBlock(Block, GetRequest):
+       # Block implementation will go here
+   ```
+
+3. **Define the input and output schemas** using `BlockSchema`. These schemas specify the data structure that the block expects to receive (input) and produce (output).
+
+   - The input schema defines the structure of the data the block will process. Each field in the schema represents a required piece of input data.
+   - The output schema defines the structure of the data the block will return after processing. Each field in the schema represents a piece of output data.
+
+   Example:
+
+   ```python
+   class Input(BlockSchema):
+       topic: str  # The topic to get the Wikipedia summary for
+
+   class Output(BlockSchema):
+       summary: str  # The summary of the topic from Wikipedia
+       error: str  # Any error message if the request fails
+   ```
+
+4. **Implement the `__init__` method, including test data and mocks:**
+
+   ```python
+   def __init__(self):
+       super().__init__(
+           # Unique ID for the block, used across users for templates
+           # you can generate this with this python one liner
+           # print(__import__('uuid').uuid4())
+           id="h5e7f8g9-1b2c-3d4e-5f6g-7h8i9j0k1l2m",
+           input_schema=WikipediaSummaryBlock.Input,  # Assign input schema
+           output_schema=WikipediaSummaryBlock.Output,  # Assign output schema
+
+            # Provide sample input, output and test mock for testing the block
+
+           test_input={"topic": "Artificial Intelligence"},
+           test_output=("summary", "summary content"),
+           test_mock={"get_request": lambda url, json: {"extract": "summary content"}},
+       )
+   ```
+
+   - `id`: A unique identifier for the block.
+
+   - `input_schema` and `output_schema`: Define the structure of the input and output data.
+
+   Let's break down the testing components:
+
+   - `test_input`: This is a sample input that will be used to test the block. It should be a valid input according to your Input schema.
+
+   - `test_output`: This is the expected output when running the block with the `test_input`. It should match your Output schema. For non-deterministic outputs or when you only want to assert the type, you can use Python types instead of specific values. In this example, `("summary", str)` asserts that the output key is "summary" and its value is a string.
+
+   - `test_mock`: This is crucial for blocks that make network calls. It provides a mock function that replaces the actual network call during testing. 
+
+     In this case, we're mocking the `get_request` method to always return a dictionary with an 'extract' key, simulating a successful API response. This allows us to test the block's logic without making actual network requests, which could be slow, unreliable, or rate-limited.
+
+5. **Implement the `run` method with error handling:**, this should contain the main logic of the block:
+
+   ```python
+   def run(self, input_data: Input) -> BlockOutput:
+       try:
+           topic = input_data.topic
+           url = f"https://en.wikipedia.org/api/rest_v1/page/summary/{topic}"
+
+           response = self.get_request(url, json=True)
+           yield "summary", response['extract']
+
+       except requests.exceptions.HTTPError as http_err:
+           yield "error", f"HTTP error occurred: {http_err}"
+       except requests.RequestException as e:
+           yield "error", f"Request to Wikipedia failed: {e}"
+       except KeyError as e:
+           yield "error", f"Error parsing Wikipedia response: {e}"
+   ```
+
+   - **Try block**: Contains the main logic to fetch and process the Wikipedia summary.
+   - **API request**: Send a GET request to the Wikipedia API.
+   - **Error handling**: Handle various exceptions that might occur during the API request and data processing.
+   - **Yield**: Use `yield` to output the results.
+
+## Key Points to Remember
+
+- **Unique ID**: Give your block a unique ID in the **init** method.
+- **Input and Output Schemas**: Define clear input and output schemas.
+- **Error Handling**: Implement error handling in the `run` method.
+- **Output Results**: Use `yield` to output results in the `run` method.
+- **Testing**: Provide test input and output in the **init** method for automatic testing.
+
+## Understanding the Testing Process
+
+The testing of blocks is handled by `test_block.py`, which does the following:
+
+1. It calls the block with the provided `test_input`.
+2. If a `test_mock` is provided, it temporarily replaces the specified methods with the mock functions.
+3. It then asserts that the output matches the `test_output`.
+
+For the WikipediaSummaryBlock:
+
+- The test will call the block with the topic "Artificial Intelligence".
+- Instead of making a real API call, it will use the mock function, which returns `{"extract": "summary content"}`.
+- It will then check if the output key is "summary" and its value is a string.
+
+This approach allows us to test the block's logic comprehensively without relying on external services, while also accommodating non-deterministic outputs.
+
+## Tips for Effective Block Testing
+
+1. **Provide realistic test_input**: Ensure your test input covers typical use cases.
+
+2. **Define appropriate test_output**: 
+   - For deterministic outputs, use specific expected values.
+   - For non-deterministic outputs or when only the type matters, use Python types (e.g., `str`, `int`, `dict`).
+   - You can mix specific values and types, e.g., `("key1", str), ("key2", 42)`.
+
+3. **Use test_mock for network calls**: This prevents tests from failing due to network issues or API changes.
+
+4. **Consider omitting test_mock for blocks without external dependencies**: If your block doesn't make network calls or use external resources, you might not need a mock.
+
+5. **Consider edge cases**: Include tests for potential error conditions in your `run` method.
+
+6. **Update tests when changing block behavior**: If you modify your block, ensure the tests are updated accordingly.
+
+By following these steps, you can create new blocks that extend the functionality of the AutoGPT Agent Server.
+
+## Blocks we want to see
+
+Below is a list of blocks that we would like to see implemented in the AutoGPT Agent Server. If you're interested in contributing, feel free to pick one of these blocks or suggest your own by editing [docs/content/server/new_blocks.md](https://github.com/Significant-Gravitas/AutoGPT/edit/master/docs/content/server/new_blocks.md) and opening a pull request.
+
+If you would like to implement one of these blocks, open a pull request and we will start the review process.
+
+### Consumer Services/Platforms
+
+- Google sheets - Read/Append [Read in Progress](https://github.com/Significant-Gravitas/AutoGPT/pull/7521)
+- Email - Read/Send with Gmail, Outlook, Yahoo, Proton, etc
+- Calendar - Read/Write with Google Calendar, Outlook Calendar, etc
+- Home Assistant - Call Service, Get Status
+- Dominos - Order Pizza, Track Order
+- Uber - Book Ride, Track Ride
+- Notion - Create/Read Page, Create/Append/Read DB
+- Google drive - read/write/overwrite file/folder
+
+### Social Media
+
+- Twitter - Post, Reply, Get Replies, Get Comments, Get Followers, Get Following, Get Tweets, Get Mentions
+- Instagram - Post, Reply, Get Comments, Get Followers, Get Following, Get Posts, Get Mentions, Get Trending Posts
+- TikTok - Post, Reply, Get Comments, Get Followers, Get Following, Get Videos, Get Mentions, Get Trending Videos
+- LinkedIn - Post, Reply, Get Comments, Get Followers, Get Following, Get Posts, Get Mentions, Get Trending Posts
+- YouTube - Transcribe Videos/Shorts, Post Videos/Shorts, Read/Reply/React to Comments, Update Thumbnails, Update Description, Update Tags, Update Titles, Get Views, Get Likes, Get Dislikes, Get Subscribers, Get Comments, Get Shares, Get Watch Time, Get Revenue, Get Trending Videos, Get Top Videos, Get Top Channels
+- Reddit - Post, Reply, Get Comments, Get Followers, Get Following, Get Posts, Get Mentions, Get Trending Posts
+- Treatwell (and related Platforms) - Book, Cancel, Review, Get Recommendations
+- Substack - Read/Subscribe/Unsubscribe, Post/Reply, Get Recommendations
+- Discord - Read/Post/Reply, Moderation actions
+- GoodReads - Read/Post/Reply, Get Recommendations
+
+### E-commerce
+
+- Airbnb - Book, Cancel, Review, Get Recommendations
+- Amazon - Order, Track Order, Return, Review, Get Recommendations
+- eBay - Order, Track Order, Return, Review, Get Recommendations
+- Upwork - Post Jobs, Hire Freelancer, Review Freelancer, Fire Freelancer
+
+### Business Tools
+
+- External Agents - Call other agents similar to AutoGPT
+- Trello - Create/Read/Update/Delete Cards, Lists, Boards
+- Jira - Create/Read/Update/Delete Issues, Projects, Boards
+- Linear - Create/Read/Update/Delete Issues, Projects, Boards
+- Excel - Read/Write/Update/Delete Rows, Columns, Sheets
+- Slack - Read/Post/Reply to Messages, Create Channels, Invite Users
+- ERPNext - Create/Read/Update/Delete Invoices, Orders, Customers, Products
+- Salesforce - Create/Read/Update/Delete Leads, Opportunities, Accounts
+- HubSpot - Create/Read/Update/Delete Contacts, Deals, Companies
+- Zendesk - Create/Read/Update/Delete Tickets, Users, Organizations
+- Odoo - Create/Read/Update/Delete Sales Orders, Invoices, Customers
+- Shopify - Create/Read/Update/Delete Products, Orders, Customers
+- WooCommerce - Create/Read/Update/Delete Products, Orders, Customers
+- Squarespace - Create/Read/Update/Delete Pages, Products, Orders
+
+## Agent Templates we want to see
+
+
+### Data/Information
+
+- Summarize top news of today, of this week, this month via Apple News or other large media outlets BBC, TechCrunch, hackernews, etc
+- Create, read, and summarize substack newsletters or any newsletters (blog writer vs blog reader)
+- Get/read/summarize the most viral Twitter, Instagram, TikTok (general social media accounts) of the day, week, month
+- Get/Read any LinkedIn posts or profile that mention AI Agents
+- Read/Summarize discord (might not be able to do this because you need access)
+- Read / Get most read books in a given month, year, etc from GoodReads or Amazon Books, etc
+- Get dates for specific shows across all streaming services
+  - Suggest/Recommend/Get most watched shows in a given month, year, etc across all streaming platforms
+- Data analysis from xlsx data set
+   - Gather via Excel or Google Sheets data > Sample the data randomly (sample block takes top X, bottom X, randomly, etc) > pass that to LLM Block to generate a script for analysis of the full data > Python block to run the script> making a loop back through LLM Fix Block on error > create chart/visualization (potentially in the code block?) > show the image as output (this may require frontend changes to show)
+- Tiktok video search and download
+
+### Marketing 
+
+- Portfolio site design and enhancements

docs/content/server/ollama.md

@@ -0,0 +1,37 @@
+# Running Ollama with AutoGPT
+
+Follow these steps to set up and run Ollama and your AutoGPT project:
+
+1. **Run Ollama**
+   - Open a terminal
+   - Execute the following command:
+     ```
+     ollama run llama3
+     ```
+   - Leave this terminal running
+
+2. **Run the Backend**
+   - Open a new terminal
+   - Navigate to the backend directory in the AutoGPT project:
+     ```
+     cd rnd/autogpt_server/
+     ```
+   - Start the backend using Poetry:
+     ```
+     poetry run app
+     ```
+
+3. **Run the Frontend**
+   - Open another terminal
+   - Navigate to the frontend directory in the AutoGPT project:
+     ```
+     cd rnd/autogpt_builder/
+     ```
+   - Start the frontend development server:
+     ```
+     npm run dev
+     ```
+
+4. **Choose the Ollama Model**
+   - Add LLMBlock in the UI
+   -  Choose the last option in the model selection dropdown

docs/content/server/setup.md

@@ -0,0 +1,137 @@
+# Setting up the server
+
+- [Introduction](#introduction)
+- [Prerequisites](#prerequisites)
+
+## Introduction
+
+This guide will help you setup the server and builder for the project.
+
+<!-- The video is listed in the root Readme.md of the repo -->
+
+We also offer this in video format. You can check it out [here](https://github.com/Significant-Gravitas/AutoGPT#how-to-get-started).
+
+!!! warning
+    **DO NOT FOLLOW ANY OUTSIDE TUTORIALS AS THEY WILL LIKELY BE OUT OF DATE**
+
+## Prerequisites
+
+To setup the server, you need to have the following installed:
+
+- [Node.js](https://nodejs.org/en/)
+- [Python 3.10](https://www.python.org/downloads/)
+
+### Checking if you have Node.js and Python installed
+
+You can check if you have Node.js installed by running the following command:
+
+```bash
+node -v
+```
+
+You can check if you have Python installed by running the following command:
+
+```bash
+python --version
+```
+
+Once you have node and python installed, you can proceed to the next step.
+
+### Installing the package managers
+
+In order to install the dependencies, you need to have the appropriate package managers installed.
+
+- Installing Yarn
+
+Yarn is a package manager for Node.js. You can install it by running the following command:
+
+```bash
+npm install -g yarn
+```
+
+- Installing Poetry
+
+Poetry is a package manager for Python. You can install it by running the following command:
+
+```bash
+pip install poetry
+```
+- Installing Docker and Docker Compose
+
+Docker containerizes applications, while Docker Compose orchestrates multi-container Docker applications.
+
+You can follow the steps here:
+
+If you need assistance installing docker:
+https://docs.docker.com/desktop/
+If you need assistance installing docker compose: 
+https://docs.docker.com/compose/install/
+
+### Installing the dependencies
+
+Once you have installed Yarn and Poetry, you can run the following command to install the dependencies:
+
+```bash
+cd rnd/autogpt_server
+cp .env.example .env
+poetry install
+```
+
+**In another terminal**, run the following command to install the dependencies for the frontend:
+
+```bash
+cd rnd/autogpt_builder
+yarn install
+```
+
+Once you have installed the dependencies, you can proceed to the next step.
+
+### Setting up the database
+
+In order to setup the database, you need to run the following commands, in the same terminal you ran the `poetry install` command:
+
+   ```sh
+   docker compose up postgres redis -d
+   poetry run prisma migrate dev
+   ```
+After deploying the migration, to ensure that the database schema is correctly mapped to your codebase, allowing the application to interact with the database properly, you need to generate the Prisma database model:
+
+```bash
+poetry run prisma generate
+```
+
+Without running this command, the necessary Python modules (prisma.models) won't be available, leading to a `ModuleNotFoundError`.
+
+### Running the server without Docker
+
+To run the server, you can run the following commands in the same terminal you ran the `poetry install` command:
+
+```bash
+poetry run app
+```
+
+### Running the server within Docker
+
+To run the server, you can run the following commands in the same terminal you ran the `poetry install` command:
+
+```bash
+docker compose build
+docker compose up
+```
+
+In the other terminal from autogpt_builder, you can run the following command to start the frontend:
+
+```bash
+yarn dev
+```
+
+### Checking if the server is running
+
+You can check if the server is running by visiting [http://localhost:3000](http://localhost:3000) in your browser.
+
+### Notes: 
+By default the daemons for different services run on the following ports: 
+
+Execution Manager Daemon: 8002
+Execution Scheduler Daemon: 8003
+Rest Server Daemon: 8004

docs/mkdocs.yml

@@ -5,6 +5,13 @@ docs_dir: content
 nav:
   - Home: index.md
 
+  - The AutoGPT Server 🆕: 
+    - Build your own Blocks: server/new_blocks.md
+    - Setup: server/setup.md
+    - Advanced Setup: server/advanced_setup.md
+    - Using Ollama: server/ollama.md
+    - Using D-ID: serveer/d_id.md
+
   - AutoGPT Agent:
       - Introduction: AutoGPT/index.md
       - Setup:
@@ -40,7 +47,7 @@ nav:
       - Readme: https://github.com/Significant-Gravitas/AutoGPT/blob/master/frontend/README.md
 
   - Docs: docs/index.md
-
+    
   # - Challenges:
   #     - Introduction: challenges/introduction.md
   #     - List of Challenges:

forge/.vscode/settings.json

@@ -0,0 +1,3 @@
+{
+  "python.analysis.typeCheckingMode": "basic",
+}

forge/conftest.py

@@ -0,0 +1,41 @@
+import uuid
+from pathlib import Path
+
+import pytest
+
+from forge.file_storage.base import FileStorage, FileStorageConfiguration
+from forge.file_storage.local import LocalFileStorage
+
+pytest_plugins = [
+    "tests.vcr",
+]
+
+
+@pytest.fixture(scope="session", autouse=True)
+def load_env_vars():
+    from dotenv import load_dotenv
+
+    load_dotenv()
+
+
+@pytest.fixture()
+def tmp_project_root(tmp_path: Path) -> Path:
+    return tmp_path
+
+
+@pytest.fixture()
+def app_data_dir(tmp_project_root: Path) -> Path:
+    dir = tmp_project_root / "data"
+    dir.mkdir(parents=True, exist_ok=True)
+    return dir
+
+
+@pytest.fixture()
+def storage(app_data_dir: Path) -> FileStorage:
+    storage = LocalFileStorage(
+        FileStorageConfiguration(
+            root=Path(f"{app_data_dir}/{str(uuid.uuid4())}"), restrict_to_root=False
+        )
+    )
+    storage.initialize()
+    return storage

forge/forge/agent/base.py

@@ -2,7 +2,6 @@ from __future__ import annotations
 
 import copy
 import inspect
-import json
 import logging
 from abc import ABCMeta, abstractmethod
 from typing import (
@@ -19,7 +18,8 @@ from typing import (
 )
 
 from colorama import Fore
-from pydantic import BaseModel, Field, parse_raw_as, validator
+from pydantic import BaseModel, Field, ValidationInfo, field_validator
+from pydantic_core import from_json, to_json
 
 from forge.agent import protocols
 from forge.agent.components import (
@@ -47,11 +47,6 @@ DEFAULT_TRIGGERING_PROMPT = (
 )
 
 
-# HACK: This is a workaround wrapper to de/serialize component configs until pydantic v2
-class ModelContainer(BaseModel):
-    models: dict[str, BaseModel]
-
-
 class BaseAgentConfiguration(SystemConfiguration):
     allow_fs_access: bool = UserConfigurable(default=False)
 
@@ -77,10 +72,10 @@ class BaseAgentConfiguration(SystemConfiguration):
     `0` to stop the agent.
     """
 
-    cycles_remaining = cycle_budget
+    cycles_remaining: int = cycle_budget
     """The number of cycles remaining within the `cycle_budget`."""
 
-    cycle_count = 0
+    cycle_count: int = 0
     """The number of cycles that the agent has run since its initialization."""
 
     send_token_limit: Optional[int] = None
@@ -89,11 +84,11 @@ class BaseAgentConfiguration(SystemConfiguration):
     defaults to 75% of `llm.max_tokens`.
     """
 
-    @validator("use_functions_api")
-    def validate_openai_functions(cls, v: bool, values: dict[str, Any]):
-        if v:
-            smart_llm = values["smart_llm"]
-            fast_llm = values["fast_llm"]
+    @field_validator("use_functions_api")
+    def validate_openai_functions(cls, value: bool, info: ValidationInfo):
+        if value:
+            smart_llm = info.data["smart_llm"]
+            fast_llm = info.data["fast_llm"]
             assert all(
                 [
                     not any(s in name for s in {"-0301", "-0314"})
@@ -103,7 +98,7 @@ class BaseAgentConfiguration(SystemConfiguration):
                 f"Model {smart_llm} does not support OpenAI Functions. "
                 "Please disable OPENAI_FUNCTIONS or choose a suitable model."
             )
-        return v
+        return value
 
 
 class BaseAgentSettings(SystemSettings):
@@ -277,17 +272,15 @@ class BaseAgent(Generic[AnyProposal], metaclass=AgentMeta):
         return method_result
 
     def dump_component_configs(self) -> str:
-        configs = {}
+        configs: dict[str, Any] = {}
         for component in self.components:
             if isinstance(component, ConfigurableComponent):
                 config_type_name = component.config.__class__.__name__
                 configs[config_type_name] = component.config
-        data = ModelContainer(models=configs).json()
-        raw = parse_raw_as(dict[str, dict[str, Any]], data)
-        return json.dumps(raw["models"], indent=4)
+        return to_json(configs).decode()
 
     def load_component_configs(self, serialized_configs: str):
-        configs_dict = parse_raw_as(dict[str, dict[str, Any]], serialized_configs)
+        configs_dict: dict[str, dict[str, Any]] = from_json(serialized_configs)
 
         for component in self.components:
             if not isinstance(component, ConfigurableComponent):
@@ -297,7 +290,7 @@ class BaseAgent(Generic[AnyProposal], metaclass=AgentMeta):
             if config_type_name in configs_dict:
                 # Parse the serialized data and update the existing config
                 updated_data = configs_dict[config_type_name]
-                data = {**component.config.dict(), **updated_data}
+                data = {**component.config.model_dump(), **updated_data}
                 component.config = component.config.__class__(**data)
 
     def _collect_components(self):
@@ -353,7 +346,7 @@ class BaseAgent(Generic[AnyProposal], metaclass=AgentMeta):
                 copied_item = item.copy()
             elif isinstance(item, BaseModel):
                 # Deep copy for Pydantic models (deep=True to also copy nested models)
-                copied_item = item.copy(deep=True)
+                copied_item = item.model_copy(deep=True)
             else:
                 # Deep copy for other objects
                 copied_item = copy.deepcopy(item)

forge/forge/agent/components.py

@@ -67,7 +67,7 @@ class ConfigurableComponent(ABC, Generic[BM]):
         if not hasattr(self, "_config") or self._config is None:
             # Load configuration from environment variables
             updated = _update_user_config_from_env(config)
-            config = self.config_class(**deep_update(config.dict(), updated))
+            config = self.config_class(**deep_update(config.model_dump(), updated))
         self._config = config
 
 

forge/forge/agent/forge_agent.py

@@ -24,7 +24,7 @@ from forge.config.ai_profile import AIProfile
 from forge.file_storage.base import FileStorage
 from forge.llm.prompting.schema import ChatPrompt
 from forge.llm.prompting.utils import dump_prompt
-from forge.llm.providers.schema import AssistantFunctionCall
+from forge.llm.providers.schema import AssistantChatMessage, AssistantFunctionCall
 from forge.llm.providers.utils import function_specs_from_commands
 from forge.models.action import (
     ActionErrorResult,
@@ -149,7 +149,7 @@ class ForgeAgent(ProtocolAgent, BaseAgent):
         self.reset_trace()
 
         # Get directives
-        directives = self.state.directives.copy(deep=True)
+        directives = self.state.directives.model_copy(deep=True)
         directives.resources += await self.run_pipeline(DirectiveProvider.get_resources)
         directives.constraints += await self.run_pipeline(
             DirectiveProvider.get_constraints
@@ -178,6 +178,9 @@ class ForgeAgent(ProtocolAgent, BaseAgent):
             use_tool=AssistantFunctionCall(
                 name="finish", arguments={"reason": "Unimplemented logic"}
             ),
+            raw_message=AssistantChatMessage(
+                content="finish(reason='Unimplemented logic')"
+            ),
         )
 
         self.config.cycle_count += 1

forge/forge/agent_protocol/agent_test.py

@@ -12,9 +12,9 @@ from .models.task import StepRequestBody, Task, TaskListResponse, TaskRequestBod
 
 
 @pytest.fixture
-def agent(test_workspace: Path):
+def agent(tmp_project_root: Path):
     db = AgentDB("sqlite:///test.db")
-    config = FileStorageConfiguration(root=test_workspace)
+    config = FileStorageConfiguration(root=tmp_project_root)
     workspace = LocalFileStorage(config)
     return ProtocolAgent(db, workspace)
 

forge/forge/agent_protocol/models/artifact.py

@@ -1,38 +1,34 @@
 from datetime import datetime
 
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, ConfigDict, Field
 
 
 class Artifact(BaseModel):
     created_at: datetime = Field(
-        ...,
         description="The creation datetime of the task.",
-        example="2023-01-01T00:00:00Z",
-        json_encoders={datetime: lambda v: v.isoformat()},
+        examples=["2023-01-01T00:00:00Z"],
     )
     modified_at: datetime = Field(
-        ...,
         description="The modification datetime of the task.",
-        example="2023-01-01T00:00:00Z",
-        json_encoders={datetime: lambda v: v.isoformat()},
+        examples=["2023-01-01T00:00:00Z"],
     )
     artifact_id: str = Field(
-        ...,
         description="ID of the artifact.",
-        example="b225e278-8b4c-4f99-a696-8facf19f0e56",
+        examples=["b225e278-8b4c-4f99-a696-8facf19f0e56"],
     )
     agent_created: bool = Field(
-        ...,
         description="Whether the artifact has been created by the agent.",
-        example=False,
+        examples=[False],
     )
     relative_path: str = Field(
-        ...,
         description="Relative path of the artifact in the agents workspace.",
-        example="/my_folder/my_other_folder/",
+        examples=["/my_folder/my_other_folder/"],
     )
     file_name: str = Field(
-        ...,
         description="Filename of the artifact.",
-        example="main.py",
+        examples=["main.py"],
+    )
+
+    model_config = ConfigDict(
+        json_encoders={datetime: lambda v: v.isoformat()},
     )

forge/forge/agent_protocol/models/pagination.py

@@ -2,7 +2,7 @@ from pydantic import BaseModel, Field
 
 
 class Pagination(BaseModel):
-    total_items: int = Field(..., description="Total number of items.", example=42)
-    total_pages: int = Field(..., description="Total number of pages.", example=97)
-    current_page: int = Field(..., description="Current_page page number.", example=1)
-    page_size: int = Field(..., description="Number of items per page.", example=25)
+    total_items: int = Field(description="Total number of items.", examples=[42])
+    total_pages: int = Field(description="Total number of pages.", examples=[97])
+    current_page: int = Field(description="Current_page page number.", examples=[1])
+    page_size: int = Field(description="Number of items per page.", examples=[25])

forge/forge/agent_protocol/models/task.py

@@ -4,7 +4,7 @@ from datetime import datetime
 from enum import Enum
 from typing import Any, List, Optional
 
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, ConfigDict, Field
 
 from .artifact import Artifact
 from .pagination import Pagination
@@ -12,48 +12,48 @@ from .pagination import Pagination
 
 class TaskRequestBody(BaseModel):
     input: str = Field(
-        ...,
         min_length=1,
         description="Input prompt for the task.",
-        example="Write the words you receive to the file 'output.txt'.",
+        examples=["Write the words you receive to the file 'output.txt'."],
     )
     additional_input: dict[str, Any] = Field(default_factory=dict)
 
 
 class Task(TaskRequestBody):
     created_at: datetime = Field(
-        ...,
         description="The creation datetime of the task.",
-        example="2023-01-01T00:00:00Z",
-        json_encoders={datetime: lambda v: v.isoformat()},
+        examples=["2023-01-01T00:00:00Z"],
     )
     modified_at: datetime = Field(
-        ...,
         description="The modification datetime of the task.",
-        example="2023-01-01T00:00:00Z",
-        json_encoders={datetime: lambda v: v.isoformat()},
+        examples=["2023-01-01T00:00:00Z"],
     )
     task_id: str = Field(
-        ...,
         description="The ID of the task.",
-        example="50da533e-3904-4401-8a07-c49adf88b5eb",
+        examples=["50da533e-3904-4401-8a07-c49adf88b5eb"],
     )
     artifacts: list[Artifact] = Field(
         default_factory=list,
         description="A list of artifacts that the task has produced.",
-        example=[
+        examples=[
             "7a49f31c-f9c6-4346-a22c-e32bc5af4d8e",
             "ab7b4091-2560-4692-a4fe-d831ea3ca7d6",
         ],
     )
 
+    model_config = ConfigDict(
+        json_encoders={datetime: lambda v: v.isoformat()},
+    )
+
 
 class StepRequestBody(BaseModel):
     name: Optional[str] = Field(
-        default=None, description="The name of the task step.", example="Write to file"
+        default=None,
+        description="The name of the task step.",
+        examples=["Write to file"],
     )
     input: str = Field(
-        ..., description="Input prompt for the step.", example="Washington"
+        description="Input prompt for the step.", examples=["Washington"]
     )
     additional_input: dict[str, Any] = Field(default_factory=dict)
 
@@ -66,40 +66,44 @@ class StepStatus(Enum):
 
 class Step(StepRequestBody):
     created_at: datetime = Field(
-        ...,
         description="The creation datetime of the task.",
-        example="2023-01-01T00:00:00Z",
-        json_encoders={datetime: lambda v: v.isoformat()},
+        examples=[
+            "2023-01-01T00:00:00Z",
+        ],
     )
     modified_at: datetime = Field(
-        ...,
         description="The modification datetime of the task.",
-        example="2023-01-01T00:00:00Z",
-        json_encoders={datetime: lambda v: v.isoformat()},
+        examples=[
+            "2023-01-01T00:00:00Z",
+        ],
     )
     task_id: str = Field(
-        ...,
         description="The ID of the task this step belongs to.",
-        example="50da533e-3904-4401-8a07-c49adf88b5eb",
+        examples=[
+            "50da533e-3904-4401-8a07-c49adf88b5eb",
+        ],
     )
     step_id: str = Field(
-        ...,
         description="The ID of the task step.",
-        example="6bb1801a-fd80-45e8-899a-4dd723cc602e",
+        examples=[
+            "6bb1801a-fd80-45e8-899a-4dd723cc602e",
+        ],
     )
     name: Optional[str] = Field(
-        default=None, description="The name of the task step.", example="Write to file"
+        default=None,
+        description="The name of the task step.",
+        examples=["Write to file"],
     )
     status: StepStatus = Field(
-        ..., description="The status of the task step.", example="created"
+        description="The status of the task step.", examples=["created"]
     )
     output: Optional[str] = Field(
         default=None,
         description="Output of the task step.",
-        example=(
+        examples=[
             "I am going to use the write_to_file command and write Washington "
             "to a file called output.txt <write_to_file('output.txt', 'Washington')"
-        ),
+        ],
     )
     additional_output: Optional[dict[str, Any]] = None
     artifacts: list[Artifact] = Field(
@@ -107,7 +111,11 @@ class Step(StepRequestBody):
         description="A list of artifacts that the step has produced.",
     )
     is_last: bool = Field(
-        ..., description="Whether this is the last step in the task.", example=True
+        description="Whether this is the last step in the task.", examples=[True]
+    )
+
+    model_config = ConfigDict(
+        json_encoders={datetime: lambda v: v.isoformat()},
     )
 
 

forge/forge/components/README.md

@@ -33,7 +33,7 @@ class MyAgent(BaseAgent):
 ## Component configuration
 
 Each component can have its own configuration defined using a regular pydantic `BaseModel`.
-To ensure the configuration is loaded from the file correctly, the component must inherit from `ConfigurableComponent[T]` where `T` is the configuration model it uses.
+To ensure the configuration is loaded from the file correctly, the component must inherit from `ConfigurableComponent[BM]` where `BM` is the configuration model it uses.
 `ConfigurableComponent` provides a `config` attribute that holds the configuration instance.
 It's possible to either set the `config` attribute directly or pass the configuration instance to the component's constructor.
 Extra configuration (i.e. for components that are not part of the agent) can be passed and will be silently ignored. Extra config won't be applied even if the component is added later.
@@ -72,6 +72,73 @@ class SensitiveConfig(BaseModel):
     api_key: SecretStr = UserConfigurable(from_env="API_KEY", exclude=True)
 ```
 
+### Configuration serialization
+
+`BaseAgent` provides two methods:
+1. `dump_component_configs`: Serializes all components' configurations as json string.
+1. `load_component_configs`: Deserializes json string to configuration and applies it.
+
+### JSON configuration
+
+You can specify a JSON file (e.g. `config.json`) to use for the configuration when launching an agent.
+This file contains settings for individual [Components](../components/introduction.md) that AutoGPT uses.
+To specify the file use `--component-config-file` CLI option, for example to use `config.json`:
+
+```shell
+./autogpt.sh run --component-config-file config.json
+```
+
+!!! note
+    If you're using Docker to run AutoGPT, you need to mount or copy the configuration file to the container.
+    See [Docker Guide](../../AutoGPT/setup/docker.md) for more information.
+
+### Example JSON configuration
+
+You can copy configuration you want to change, for example to `autogpt/config.json` and modify it to your needs.
+*Most configuration has default values, it's better to set only values you want to modify.*
+You can see the available configuration fields and default values in [Build-in Components](./built-in-components.md).
+You can set sensitive variables in the `.json` file as well but it's recommended to use environment variables instead.
+
+```json
+{
+    "CodeExecutorConfiguration": {
+        "execute_local_commands": false,
+        "shell_command_control": "allowlist",
+        "shell_allowlist": ["cat", "echo"],
+        "shell_denylist": [],
+        "docker_container_name": "agent_sandbox"
+    },
+    "FileManagerConfiguration": {
+        "storage_path": "agents/AutoGPT/",
+        "workspace_path": "agents/AutoGPT/workspace"
+    },
+    "GitOperationsConfiguration": {
+        "github_username": null
+    },
+    "ActionHistoryConfiguration": {
+        "llm_name": "gpt-3.5-turbo",
+        "max_tokens": 1024,
+        "spacy_language_model": "en_core_web_sm"
+    },
+    "ImageGeneratorConfiguration": {
+        "image_provider": "dalle",
+        "huggingface_image_model": "CompVis/stable-diffusion-v1-4",
+        "sd_webui_url": "http://localhost:7860"
+    },
+    "WebSearchConfiguration": {
+        "duckduckgo_max_attempts": 3
+    },
+    "WebSeleniumConfiguration": {
+        "llm_name": "gpt-3.5-turbo",
+        "web_browser": "chrome",
+        "headless": true,
+        "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",
+        "browse_spacy_language_model": "en_core_web_sm"
+    }
+}
+
+```
+
 ## Ordering components
 
 The execution order of components is important because some may depend on the results of the previous ones.

forge/forge/components/action_history/action_history.py

@@ -10,17 +10,20 @@ from forge.llm.prompting.utils import indent
 from forge.llm.providers import ChatMessage, MultiProvider
 from forge.llm.providers.multi import ModelName
 from forge.llm.providers.openai import OpenAIModelName
+from forge.llm.providers.schema import ToolResultMessage
 
 from .model import ActionResult, AnyProposal, Episode, EpisodicActionHistory
 
 
 class ActionHistoryConfiguration(BaseModel):
-    model_name: ModelName = OpenAIModelName.GPT3
+    llm_name: ModelName = OpenAIModelName.GPT3
     """Name of the llm model used to compress the history"""
     max_tokens: int = 1024
     """Maximum number of tokens to use up with generated history messages"""
     spacy_language_model: str = "en_core_web_sm"
     """Language model used for summary chunking using spacy"""
+    full_message_count: int = 4
+    """Number of latest non-summarized messages to include in the history"""
 
 
 class ActionHistoryComponent(
@@ -46,12 +49,47 @@ class ActionHistoryComponent(
         self.llm_provider = llm_provider
 
     def get_messages(self) -> Iterator[ChatMessage]:
-        if progress := self._compile_progress(
-            self.event_history.episodes,
-            self.config.max_tokens,
-            self.count_tokens,
-        ):
-            yield ChatMessage.system(f"## Progress on your Task so far\n\n{progress}")
+        messages: list[ChatMessage] = []
+        step_summaries: list[str] = []
+        tokens: int = 0
+        n_episodes = len(self.event_history.episodes)
+
+        # Include a summary for all except a few latest steps
+        for i, episode in enumerate(reversed(self.event_history.episodes)):
+            # Use full format for a few steps, summary or format for older steps
+            if i < self.config.full_message_count:
+                messages.insert(0, episode.action.raw_message)
+                tokens += self.count_tokens(str(messages[0]))  # HACK
+                if episode.result:
+                    result_message = self._make_result_message(episode, episode.result)
+                    messages.insert(1, result_message)
+                    tokens += self.count_tokens(str(result_message))  # HACK
+                continue
+            elif episode.summary is None:
+                step_content = indent(episode.format(), 2).strip()
+            else:
+                step_content = episode.summary
+
+            step = f"* Step {n_episodes - i}: {step_content}"
+
+            if self.config.max_tokens and self.count_tokens:
+                step_tokens = self.count_tokens(step)
+                if tokens + step_tokens > self.config.max_tokens:
+                    break
+                tokens += step_tokens
+
+            step_summaries.insert(0, step)
+
+        if step_summaries:
+            step_summaries_fmt = "\n\n".join(step_summaries)
+            yield ChatMessage.system(
+                f"## Progress on your Task so far\n"
+                "Here is a summary of the steps that you have executed so far, "
+                "use this as your consideration for determining the next action!\n"
+                f"{step_summaries_fmt}"
+            )
+
+        yield from messages
 
     def after_parse(self, result: AnyProposal) -> None:
         self.event_history.register_action(result)
@@ -59,9 +97,44 @@ class ActionHistoryComponent(
     async def after_execute(self, result: ActionResult) -> None:
         self.event_history.register_result(result)
         await self.event_history.handle_compression(
-            self.llm_provider, self.config.model_name, self.config.spacy_language_model
+            self.llm_provider, self.config.llm_name, self.config.spacy_language_model
         )
 
+    @staticmethod
+    def _make_result_message(episode: Episode, result: ActionResult) -> ChatMessage:
+        if result.status == "success":
+            return (
+                ToolResultMessage(
+                    content=str(result.outputs),
+                    tool_call_id=episode.action.raw_message.tool_calls[0].id,
+                )
+                if episode.action.raw_message.tool_calls
+                else ChatMessage.user(
+                    f"{episode.action.use_tool.name} returned: "
+                    + (
+                        f"```\n{result.outputs}\n```"
+                        if "\n" in str(result.outputs)
+                        else f"`{result.outputs}`"
+                    )
+                )
+            )
+        elif result.status == "error":
+            return (
+                ToolResultMessage(
+                    content=f"{result.reason}\n\n{result.error or ''}".strip(),
+                    is_error=True,
+                    tool_call_id=episode.action.raw_message.tool_calls[0].id,
+                )
+                if episode.action.raw_message.tool_calls
+                else ChatMessage.user(
+                    f"{episode.action.use_tool.name} raised an error: ```\n"
+                    f"{result.reason}\n"
+                    "```"
+                )
+            )
+        else:
+            return ChatMessage.user(result.feedback)
+
     def _compile_progress(
         self,
         episode_history: list[Episode[AnyProposal]],
@@ -76,8 +149,8 @@ class ActionHistoryComponent(
         n_episodes = len(episode_history)
 
         for i, episode in enumerate(reversed(episode_history)):
-            # Use full format for the latest 4 steps, summary or format for older steps
-            if i < 4 or episode.summary is None:
+            # Use full format for a few latest steps, summary or format for older steps
+            if i < self.config.full_message_count or episode.summary is None:
                 step_content = indent(episode.format(), 2).strip()
             else:
                 step_content = episode.summary

forge/forge/components/action_history/model.py

@@ -3,8 +3,7 @@ from __future__ import annotations
 import asyncio
 from typing import TYPE_CHECKING, Generic
 
-from pydantic import Field
-from pydantic.generics import GenericModel
+from pydantic import BaseModel, Field
 
 from forge.content_processing.text import summarize_text
 from forge.llm.prompting.utils import format_numbered_list, indent
@@ -16,7 +15,7 @@ if TYPE_CHECKING:
     from forge.llm.providers import MultiProvider
 
 
-class Episode(GenericModel, Generic[AnyProposal]):
+class Episode(BaseModel, Generic[AnyProposal]):
     action: AnyProposal
     result: ActionResult | None
     summary: str | None = None
@@ -52,7 +51,7 @@ class Episode(GenericModel, Generic[AnyProposal]):
         return executed_action + action_result
 
 
-class EpisodicActionHistory(GenericModel, Generic[AnyProposal]):
+class EpisodicActionHistory(BaseModel, Generic[AnyProposal]):
     """Utility container for an action history"""
 
     episodes: list[Episode[AnyProposal]] = Field(default_factory=list)

forge/forge/components/code_executor/__init__.py

@@ -1,8 +1,6 @@
 from .code_executor import CodeExecutionError, CodeExecutorComponent
 
 __all__ = [
-    "ALLOWLIST_CONTROL",
-    "DENYLIST_CONTROL",
     "CodeExecutionError",
     "CodeExecutorComponent",
 ]

forge/forge/components/code_executor/code_executor.py

@@ -83,7 +83,9 @@ class CodeExecutorComponent(
 
         # Change container name if it's empty or default to prevent different agents
         # from using the same container
-        default_container_name = self.config.__fields__["docker_container_name"].default
+        default_container_name = self.config.model_fields[
+            "docker_container_name"
+        ].default
         if (
             not self.config.docker_container_name
             or self.config.docker_container_name == default_container_name

forge/forge/components/code_executor/test_code_executor.py

@@ -4,13 +4,15 @@ import tempfile
 from pathlib import Path
 
 import pytest
-from forge.components.code_executor.code_executor import (
+
+from forge.file_storage.base import FileStorage
+from forge.utils.exceptions import InvalidArgumentError, OperationNotAllowedError
+
+from .code_executor import (
     CodeExecutorComponent,
     is_docker_available,
     we_are_running_in_a_docker_container,
 )
-from forge.file_storage.base import FileStorage
-from forge.utils.exceptions import InvalidArgumentError, OperationNotAllowedError
 
 
 @pytest.fixture
@@ -103,6 +105,22 @@ def test_execute_python_file_not_found(code_executor_component: CodeExecutorComp
         code_executor_component.execute_python_file(Path("notexist.py"))
 
 
+def test_execute_shell(
+    code_executor_component: CodeExecutorComponent, random_string: str
+):
+    code_executor_component.config.shell_command_control = "allowlist"
+    code_executor_component.config.shell_allowlist = ["echo"]
+    result = code_executor_component.execute_shell(f"echo 'Hello {random_string}!'")
+    assert f"Hello {random_string}!" in result
+
+
+def test_execute_shell_local_commands_not_allowed(
+    code_executor_component: CodeExecutorComponent, random_string: str
+):
+    with pytest.raises(OperationNotAllowedError, match="not allowed"):
+        code_executor_component.execute_shell(f"echo 'Hello {random_string}!'")
+
+
 def test_execute_shell_denylist_should_deny(
     code_executor_component: CodeExecutorComponent, random_string: str
 ):

forge/forge/components/file_manager/file_manager.py

@@ -3,7 +3,7 @@ import os
 from pathlib import Path
 from typing import Iterator, Optional
 
-from pydantic import BaseModel
+from pydantic import BaseModel, ConfigDict
 
 from forge.agent import BaseAgentSettings
 from forge.agent.components import ConfigurableComponent
@@ -22,10 +22,11 @@ class FileManagerConfiguration(BaseModel):
     workspace_path: str
     """Path to files that agent has access to"""
 
-    class Config:
+    model_config = ConfigDict(
         # Prevent mutation of the configuration
         # as this wouldn't be reflected in the file storage
-        allow_mutation = False
+        frozen=False
+    )
 
 
 class FileManagerComponent(
@@ -88,7 +89,8 @@ class FileManagerComponent(
             self._file_storage.make_dir(f"agents/{save_as_id}")
             # Save state
             await self._file_storage.write_file(
-                f"agents/{save_as_id}/{self.STATE_FILE}", self.agent_state.json()
+                f"agents/{save_as_id}/{self.STATE_FILE}",
+                self.agent_state.model_dump_json(),
             )
             # Copy workspace
             self._file_storage.copy(
@@ -97,7 +99,7 @@ class FileManagerComponent(
             )
         else:
             await self.storage.write_file(
-                self.storage.root / self.STATE_FILE, self.agent_state.json()
+                self.storage.root / self.STATE_FILE, self.agent_state.model_dump_json()
             )
 
     def get_resources(self) -> Iterator[str]:

forge/forge/components/file_manager/test_file_manager.py

@@ -2,9 +2,11 @@ import os
 from pathlib import Path
 
 import pytest
+
+from forge.agent.base import BaseAgentSettings
 from forge.file_storage import FileStorage
 
-from autogpt.agents.agent import Agent
+from . import FileManagerComponent
 
 
 @pytest.fixture()
@@ -13,8 +15,13 @@ def file_content():
 
 
 @pytest.fixture
-def file_manager_component(agent: Agent):
-    return agent.file_manager
+def file_manager_component(storage: FileStorage):
+    return FileManagerComponent(
+        storage,
+        BaseAgentSettings(
+            agent_id="TestAgent", name="TestAgent", description="Test Agent description"
+        ),
+    )
 
 
 @pytest.fixture()
@@ -41,15 +48,14 @@ def test_nested_file(storage: FileStorage):
 async def test_read_file(
     test_file_path: Path,
     file_content,
-    file_manager_component,
-    agent: Agent,
+    file_manager_component: FileManagerComponent,
 ):
-    await agent.file_manager.workspace.write_file(test_file_path.name, file_content)
+    await file_manager_component.workspace.write_file(test_file_path.name, file_content)
     content = file_manager_component.read_file(test_file_path.name)
     assert content.replace("\r", "") == file_content
 
 
-def test_read_file_not_found(file_manager_component):
+def test_read_file_not_found(file_manager_component: FileManagerComponent):
     filename = "does_not_exist.txt"
     with pytest.raises(FileNotFoundError):
         file_manager_component.read_file(filename)
@@ -57,12 +63,12 @@ def test_read_file_not_found(file_manager_component):
 
 @pytest.mark.asyncio
 async def test_write_to_file_relative_path(
-    test_file_name: Path, file_manager_component, agent: Agent
+    test_file_name: Path, file_manager_component: FileManagerComponent
 ):
     new_content = "This is new content.\n"
     await file_manager_component.write_to_file(test_file_name, new_content)
     with open(
-        agent.file_manager.workspace.get_path(test_file_name), "r", encoding="utf-8"
+        file_manager_component.workspace.get_path(test_file_name), "r", encoding="utf-8"
     ) as f:
         content = f.read()
     assert content == new_content
@@ -70,7 +76,7 @@ async def test_write_to_file_relative_path(
 
 @pytest.mark.asyncio
 async def test_write_to_file_absolute_path(
-    test_file_path: Path, file_manager_component
+    test_file_path: Path, file_manager_component: FileManagerComponent
 ):
     new_content = "This is new content.\n"
     await file_manager_component.write_to_file(test_file_path, new_content)
@@ -80,18 +86,18 @@ async def test_write_to_file_absolute_path(
 
 
 @pytest.mark.asyncio
-async def test_list_files(file_manager_component, agent: Agent):
+async def test_list_files(file_manager_component: FileManagerComponent):
     # Create files A and B
     file_a_name = "file_a.txt"
     file_b_name = "file_b.txt"
     test_directory = Path("test_directory")
 
-    await agent.file_manager.workspace.write_file(file_a_name, "This is file A.")
-    await agent.file_manager.workspace.write_file(file_b_name, "This is file B.")
+    await file_manager_component.workspace.write_file(file_a_name, "This is file A.")
+    await file_manager_component.workspace.write_file(file_b_name, "This is file B.")
 
     # Create a subdirectory and place a copy of file_a in it
-    agent.file_manager.workspace.make_dir(test_directory)
-    await agent.file_manager.workspace.write_file(
+    file_manager_component.workspace.make_dir(test_directory)
+    await file_manager_component.workspace.write_file(
         test_directory / file_a_name, "This is file A in the subdirectory."
     )
 
@@ -101,10 +107,10 @@ async def test_list_files(file_manager_component, agent: Agent):
     assert os.path.join(test_directory, file_a_name) in files
 
     # Clean up
-    agent.file_manager.workspace.delete_file(file_a_name)
-    agent.file_manager.workspace.delete_file(file_b_name)
-    agent.file_manager.workspace.delete_file(test_directory / file_a_name)
-    agent.file_manager.workspace.delete_dir(test_directory)
+    file_manager_component.workspace.delete_file(file_a_name)
+    file_manager_component.workspace.delete_file(file_b_name)
+    file_manager_component.workspace.delete_file(test_directory / file_a_name)
+    file_manager_component.workspace.delete_dir(test_directory)
 
     # Case 2: Search for a file that does not exist and make sure we don't throw
     non_existent_file = "non_existent_file.txt"

forge/forge/components/git_operations/git_operations.py

@@ -14,9 +14,9 @@ from forge.utils.url_validator import validate_url
 
 
 class GitOperationsConfiguration(BaseModel):
-    github_username: Optional[str] = UserConfigurable(from_env="GITHUB_USERNAME")
+    github_username: Optional[str] = UserConfigurable(None, from_env="GITHUB_USERNAME")
     github_api_key: Optional[SecretStr] = UserConfigurable(
-        from_env="GITHUB_API_KEY", exclude=True
+        None, from_env="GITHUB_API_KEY", exclude=True
     )
 
 

forge/forge/components/git_operations/test_git_operations.py

@@ -1,11 +1,11 @@
 import pytest
-from forge.components.git_operations import GitOperationsComponent
-from forge.file_storage.base import FileStorage
-from forge.utils.exceptions import CommandExecutionError
 from git.exc import GitCommandError
 from git.repo.base import Repo
 
-from autogpt.agents.agent import Agent
+from forge.file_storage.base import FileStorage
+from forge.utils.exceptions import CommandExecutionError
+
+from . import GitOperationsComponent
 
 
 @pytest.fixture
@@ -14,15 +14,14 @@ def mock_clone_from(mocker):
 
 
 @pytest.fixture
-def git_ops_component(agent: Agent):
-    return agent.git_ops
+def git_ops_component():
+    return GitOperationsComponent()
 
 
 def test_clone_auto_gpt_repository(
     git_ops_component: GitOperationsComponent,
     storage: FileStorage,
     mock_clone_from,
-    agent: Agent,
 ):
     mock_clone_from.return_value = None
 
@@ -46,7 +45,6 @@ def test_clone_repository_error(
     git_ops_component: GitOperationsComponent,
     storage: FileStorage,
     mock_clone_from,
-    agent: Agent,
 ):
     url = "https://github.com/this-repository/does-not-exist.git"
     clone_path = storage.get_path("does-not-exist")

forge/forge/components/image_gen/image_gen.py

@@ -27,11 +27,11 @@ class ImageGeneratorConfiguration(BaseModel):
     image_provider: Literal["dalle", "huggingface", "sdwebui"] = "dalle"
     huggingface_image_model: str = "CompVis/stable-diffusion-v1-4"
     huggingface_api_token: Optional[SecretStr] = UserConfigurable(
-        from_env="HUGGINGFACE_API_TOKEN", exclude=True
+        None, from_env="HUGGINGFACE_API_TOKEN", exclude=True
     )
     sd_webui_url: str = "http://localhost:7860"
     sd_webui_auth: Optional[SecretStr] = UserConfigurable(
-        from_env="SD_WEBUI_AUTH", exclude=True
+        None, from_env="SD_WEBUI_AUTH", exclude=True
     )
 
 

forge/forge/components/image_gen/test_image_gen.py

@@ -4,17 +4,22 @@ from pathlib import Path
 from unittest.mock import patch
 
 import pytest
+from PIL import Image
+from pydantic import SecretStr, ValidationError
+
 from forge.components.image_gen import ImageGeneratorComponent
 from forge.components.image_gen.image_gen import ImageGeneratorConfiguration
 from forge.file_storage.base import FileStorage
 from forge.llm.providers.openai import OpenAICredentials
-from PIL import Image
-from pydantic import SecretStr
 
 
 @pytest.fixture
 def image_gen_component(storage: FileStorage):
-    cred = OpenAICredentials.from_env()
+    try:
+        cred = OpenAICredentials.from_env()
+    except ValidationError:
+        cred = OpenAICredentials(api_key=SecretStr("test"))
+
     return ImageGeneratorComponent(storage, openai_credentials=cred)
 
 
@@ -34,7 +39,6 @@ def image_size(request):
     return request.param
 
 
-@pytest.mark.requires_openai_api_key
 @pytest.mark.vcr
 def test_dalle(
     image_gen_component: ImageGeneratorComponent,
@@ -52,7 +56,6 @@ def test_dalle(
     reason="The image is too big to be put in a cassette for a CI pipeline. "
     "We're looking into a solution."
 )
-@pytest.mark.requires_huggingface_api_key
 @pytest.mark.parametrize(
     "image_model",
     ["CompVis/stable-diffusion-v1-4", "stabilityai/stable-diffusion-2-1"],

forge/forge/components/web/search.py

@@ -1,7 +1,7 @@
 import json
 import logging
 import time
-from typing import Iterator, Optional
+from typing import Iterator, Literal, Optional
 
 from duckduckgo_search import DDGS
 from pydantic import BaseModel, SecretStr
@@ -18,12 +18,13 @@ logger = logging.getLogger(__name__)
 
 class WebSearchConfiguration(BaseModel):
     google_api_key: Optional[SecretStr] = UserConfigurable(
-        from_env="GOOGLE_API_KEY", exclude=True
+        None, from_env="GOOGLE_API_KEY", exclude=True
     )
     google_custom_search_engine_id: Optional[SecretStr] = UserConfigurable(
-        from_env="GOOGLE_CUSTOM_SEARCH_ENGINE_ID", exclude=True
+        None, from_env="GOOGLE_CUSTOM_SEARCH_ENGINE_ID", exclude=True
     )
     duckduckgo_max_attempts: int = 3
+    duckduckgo_backend: Literal["api", "html", "lite"] = "api"
 
 
 class WebSearchComponent(
@@ -89,7 +90,9 @@ class WebSearchComponent(
             if not query:
                 return json.dumps(search_results)
 
-            search_results = DDGS().text(query, max_results=num_results)
+            search_results = DDGS().text(
+                query, max_results=num_results, backend=self.config.duckduckgo_backend
+            )
 
             if search_results:
                 break
@@ -173,7 +176,7 @@ class WebSearchComponent(
             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]
+            search_results_links = [item["link"] for item in search_results]  # type: ignore # noqa
 
         except HttpError as e:
             # Handle errors in the API call

forge/forge/components/web/selenium.py

@@ -55,7 +55,7 @@ class BrowsingError(CommandExecutionError):
 
 
 class WebSeleniumConfiguration(BaseModel):
-    model_name: ModelName = OpenAIModelName.GPT3
+    llm_name: ModelName = OpenAIModelName.GPT3
     """Name of the llm model used to read websites"""
     web_browser: Literal["chrome", "firefox", "safari", "edge"] = "chrome"
     """Web browser used by Selenium"""
@@ -68,6 +68,8 @@ class WebSeleniumConfiguration(BaseModel):
     """User agent used by the browser"""
     browse_spacy_language_model: str = "en_core_web_sm"
     """Spacy language model used for chunking text"""
+    selenium_proxy: Optional[str] = None
+    """Http proxy to use with Selenium"""
 
 
 class WebSeleniumComponent(
@@ -164,7 +166,7 @@ class WebSeleniumComponent(
             elif get_raw_content:
                 if (
                     output_tokens := self.llm_provider.count_tokens(
-                        text, self.config.model_name
+                        text, self.config.llm_name
                     )
                 ) > MAX_RAW_CONTENT_LENGTH:
                     oversize_factor = round(output_tokens / MAX_RAW_CONTENT_LENGTH, 1)
@@ -301,6 +303,9 @@ class WebSeleniumComponent(
                 options.add_argument("--headless=new")
                 options.add_argument("--disable-gpu")
 
+            if self.config.selenium_proxy:
+                options.add_argument(f"--proxy-server={self.config.selenium_proxy}")
+
             self._sideload_chrome_extensions(options, self.data_dir / "assets" / "crx")
 
             if (chromium_driver_path := Path("/usr/bin/chromedriver")).exists():
@@ -382,7 +387,7 @@ class WebSeleniumComponent(
                 text,
                 topics_of_interest=topics_of_interest,
                 llm_provider=self.llm_provider,
-                model_name=self.config.model_name,
+                model_name=self.config.llm_name,
                 spacy_model=self.config.browse_spacy_language_model,
             )
             return "\n".join(f"* {i}" for i in information)
@@ -391,7 +396,7 @@ class WebSeleniumComponent(
                 text,
                 question=question,
                 llm_provider=self.llm_provider,
-                model_name=self.config.model_name,
+                model_name=self.config.llm_name,
                 spacy_model=self.config.browse_spacy_language_model,
             )
             return result