Merge remote-tracking branch 'origin/dev' into fix/copilot-transcript-compaction

Scenarios 4 and 6 (and parts of 5, 7) were testing Python if/for logic that
mimicked the retry tree instead of calling production code. Replaced with
direct calls to _reduce_context which exercises the actual decision path.

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

@@ -5,14 +5,12 @@ on:
     branches: [master, dev, ci-test*]
     paths:
       - ".github/workflows/platform-backend-ci.yml"
-      - ".github/workflows/scripts/get_package_version_from_lockfile.py"
       - "autogpt_platform/backend/**"
       - "autogpt_platform/autogpt_libs/**"
   pull_request:
     branches: [master, dev, release-*]
     paths:
       - ".github/workflows/platform-backend-ci.yml"
-      - ".github/workflows/scripts/get_package_version_from_lockfile.py"
       - "autogpt_platform/backend/**"
       - "autogpt_platform/autogpt_libs/**"
   merge_group:

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

@@ -120,6 +120,175 @@ jobs:
           token: ${{ secrets.GITHUB_TOKEN }}
           exitOnceUploaded: true
 
+  e2e_test:
+    name: end-to-end tests
+    runs-on: big-boi
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v6
+        with:
+          submodules: recursive
+
+      - name: Set up Platform - Copy default supabase .env
+        run: |
+          cp ../.env.default ../.env
+
+      - name: Set up Platform - Copy backend .env and set OpenAI API key
+        run: |
+          cp ../backend/.env.default ../backend/.env
+          echo "OPENAI_INTERNAL_API_KEY=${{ secrets.OPENAI_API_KEY }}" >> ../backend/.env
+        env:
+          # Used by E2E test data script to generate embeddings for approved store agents
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+
+      - name: Set up Platform - Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+        with:
+          driver: docker-container
+          driver-opts: network=host
+
+      - name: Set up Platform - Expose GHA cache to docker buildx CLI
+        uses: crazy-max/ghaction-github-runtime@v4
+
+      - name: Set up Platform - Build Docker images (with cache)
+        working-directory: autogpt_platform
+        run: |
+          pip install pyyaml
+
+          # Resolve extends and generate a flat compose file that bake can understand
+          docker compose -f docker-compose.yml config > docker-compose.resolved.yml
+
+          # Add cache configuration to the resolved compose file
+          python ../.github/workflows/scripts/docker-ci-fix-compose-build-cache.py \
+            --source docker-compose.resolved.yml \
+            --cache-from "type=gha" \
+            --cache-to "type=gha,mode=max" \
+            --backend-hash "${{ hashFiles('autogpt_platform/backend/Dockerfile', 'autogpt_platform/backend/poetry.lock', 'autogpt_platform/backend/backend') }}" \
+            --frontend-hash "${{ hashFiles('autogpt_platform/frontend/Dockerfile', 'autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/src') }}" \
+            --git-ref "${{ github.ref }}"
+
+          # Build with bake using the resolved compose file (now includes cache config)
+          docker buildx bake --allow=fs.read=.. -f docker-compose.resolved.yml --load
+        env:
+          NEXT_PUBLIC_PW_TEST: true
+
+      - name: Set up tests - Cache E2E test data
+        id: e2e-data-cache
+        uses: actions/cache@v5
+        with:
+          path: /tmp/e2e_test_data.sql
+          key: e2e-test-data-${{ hashFiles('autogpt_platform/backend/test/e2e_test_data.py', 'autogpt_platform/backend/migrations/**', '.github/workflows/platform-frontend-ci.yml') }}
+
+      - name: Set up Platform - Start Supabase DB + Auth
+        run: |
+          docker compose -f ../docker-compose.resolved.yml up -d db auth --no-build
+          echo "Waiting for database to be ready..."
+          timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done'
+          echo "Waiting for auth service to be ready..."
+          timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -c "SELECT 1 FROM auth.users LIMIT 1" 2>/dev/null; do sleep 2; done' || echo "Auth schema check timeout, continuing..."
+
+      - name: Set up Platform - Run migrations
+        run: |
+          echo "Running migrations..."
+          docker compose -f ../docker-compose.resolved.yml run --rm migrate
+          echo "✅ Migrations completed"
+        env:
+          NEXT_PUBLIC_PW_TEST: true
+
+      - name: Set up tests - Load cached E2E test data
+        if: steps.e2e-data-cache.outputs.cache-hit == 'true'
+        run: |
+          echo "✅ Found cached E2E test data, restoring..."
+          {
+            echo "SET session_replication_role = 'replica';"
+            cat /tmp/e2e_test_data.sql
+            echo "SET session_replication_role = 'origin';"
+          } | docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -b
+          # Refresh materialized views after restore
+          docker compose -f ../docker-compose.resolved.yml exec -T db \
+            psql -U postgres -d postgres -b -c "SET search_path TO platform; SELECT refresh_store_materialized_views();" || true
+
+          echo "✅ E2E test data restored from cache"
+
+      - name: Set up Platform - Start (all other services)
+        run: |
+          docker compose -f ../docker-compose.resolved.yml up -d --no-build
+          echo "Waiting for rest_server to be ready..."
+          timeout 60 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
+        env:
+          NEXT_PUBLIC_PW_TEST: true
+
+      - name: Set up tests - Create E2E test data
+        if: steps.e2e-data-cache.outputs.cache-hit != 'true'
+        run: |
+          echo "Creating E2E test data..."
+          docker cp ../backend/test/e2e_test_data.py $(docker compose -f ../docker-compose.resolved.yml ps -q rest_server):/tmp/e2e_test_data.py
+          docker compose -f ../docker-compose.resolved.yml exec -T rest_server sh -c "cd /app/autogpt_platform && python /tmp/e2e_test_data.py" || {
+            echo "❌ E2E test data creation failed!"
+            docker compose -f ../docker-compose.resolved.yml logs --tail=50 rest_server
+            exit 1
+          }
+
+          # Dump auth.users + platform schema for cache (two separate dumps)
+          echo "Dumping database for cache..."
+          {
+            docker compose -f ../docker-compose.resolved.yml exec -T db \
+              pg_dump -U postgres --data-only --column-inserts \
+              --table='auth.users' postgres
+            docker compose -f ../docker-compose.resolved.yml exec -T db \
+              pg_dump -U postgres --data-only --column-inserts \
+              --schema=platform \
+              --exclude-table='platform._prisma_migrations' \
+              --exclude-table='platform.apscheduler_jobs' \
+              --exclude-table='platform.apscheduler_jobs_batched_notifications' \
+              postgres
+          } > /tmp/e2e_test_data.sql
+
+          echo "✅ Database dump created for caching ($(wc -l < /tmp/e2e_test_data.sql) lines)"
+
+      - name: Set up tests - Enable corepack
+        run: corepack enable
+
+      - name: Set up tests - Set up Node
+        uses: actions/setup-node@v6
+        with:
+          node-version: "22.18.0"
+          cache: "pnpm"
+          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
+
+      - name: Set up tests - Install dependencies
+        run: pnpm install --frozen-lockfile
+
+      - name: Set up tests - Install browser 'chromium'
+        run: pnpm playwright install --with-deps chromium
+
+      - name: Run Playwright tests
+        run: pnpm test:no-build
+        continue-on-error: false
+
+      - name: Upload Playwright report
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          name: playwright-report
+          path: playwright-report
+          if-no-files-found: ignore
+          retention-days: 3
+
+      - name: Upload Playwright test results
+        if: always()
+        uses: actions/upload-artifact@v4
+        with:
+          name: playwright-test-results
+          path: test-results
+          if-no-files-found: ignore
+          retention-days: 3
+
+      - name: Print Final Docker Compose logs
+        if: always()
+        run: docker compose -f ../docker-compose.resolved.yml logs
+
   integration_test:
     runs-on: ubuntu-latest
     needs: setup

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

@@ -1,18 +1,14 @@
-name: AutoGPT Platform - Full-stack CI
+name: AutoGPT Platform - Frontend CI
 
 on:
   push:
     branches: [master, dev]
     paths:
       - ".github/workflows/platform-fullstack-ci.yml"
-      - ".github/workflows/scripts/docker-ci-fix-compose-build-cache.py"
-      - ".github/workflows/scripts/get_package_version_from_lockfile.py"
       - "autogpt_platform/**"
   pull_request:
     paths:
       - ".github/workflows/platform-fullstack-ci.yml"
-      - ".github/workflows/scripts/docker-ci-fix-compose-build-cache.py"
-      - ".github/workflows/scripts/get_package_version_from_lockfile.py"
       - "autogpt_platform/**"
   merge_group:
 
@@ -28,28 +24,42 @@ defaults:
 jobs:
   setup:
     runs-on: ubuntu-latest
+    outputs:
+      cache-key: ${{ steps.cache-key.outputs.key }}
 
     steps:
       - name: Checkout repository
         uses: actions/checkout@v6
 
-      - name: Enable corepack
-        run: corepack enable
-
-      - name: Set up Node
+      - name: Set up Node.js
         uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
-          cache: "pnpm"
-          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
 
-      - name: Install dependencies to populate cache
+      - name: Enable corepack
+        run: corepack enable
+
+      - name: Generate cache key
+        id: cache-key
+        run: echo "key=${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/package.json') }}" >> $GITHUB_OUTPUT
+
+      - name: Cache dependencies
+        uses: actions/cache@v5
+        with:
+          path: ~/.pnpm-store
+          key: ${{ steps.cache-key.outputs.key }}
+          restore-keys: |
+            ${{ runner.os }}-pnpm-${{ hashFiles('autogpt_platform/frontend/pnpm-lock.yaml') }}
+            ${{ runner.os }}-pnpm-
+
+      - name: Install dependencies
         run: pnpm install --frozen-lockfile
 
-  check-api-types:
-    name: check API types
-    runs-on: ubuntu-latest
+  types:
+    runs-on: big-boi
     needs: setup
+    strategy:
+      fail-fast: false
 
     steps:
       - name: Checkout repository
@@ -57,256 +67,70 @@ jobs:
         with:
           submodules: recursive
 
-      # ------------------------ Backend setup ------------------------
-
-      - name: Set up Backend - Set up Python
-        uses: actions/setup-python@v5
-        with:
-          python-version: "3.12"
-
-      - name: Set up Backend - Install Poetry
-        working-directory: autogpt_platform/backend
-        run: |
-          POETRY_VERSION=$(python ../../.github/workflows/scripts/get_package_version_from_lockfile.py poetry)
-          echo "Installing Poetry version ${POETRY_VERSION}"
-          curl -sSL https://install.python-poetry.org | POETRY_VERSION=$POETRY_VERSION python3 -
-
-      - name: Set up Backend - Set up dependency cache
-        uses: actions/cache@v5
-        with:
-          path: ~/.cache/pypoetry
-          key: poetry-${{ runner.os }}-${{ hashFiles('autogpt_platform/backend/poetry.lock') }}
-
-      - name: Set up Backend - Install dependencies
-        working-directory: autogpt_platform/backend
-        run: poetry install
-
-      - name: Set up Backend - Generate Prisma client
-        working-directory: autogpt_platform/backend
-        run: poetry run prisma generate && poetry run gen-prisma-stub
-
-      - name: Set up Frontend - Export OpenAPI schema from Backend
-        working-directory: autogpt_platform/backend
-        run: poetry run export-api-schema --output ../frontend/src/app/api/openapi.json
-
-      # ------------------------ Frontend setup ------------------------
-
-      - name: Set up Frontend - Enable corepack
-        run: corepack enable
-
-      - name: Set up Frontend - Set up Node
+      - name: Set up Node.js
         uses: actions/setup-node@v6
         with:
           node-version: "22.18.0"
-          cache: "pnpm"
-          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
 
-      - name: Set up Frontend - Install dependencies
+      - name: Enable corepack
+        run: corepack enable
+
+      - name: Copy default supabase .env
+        run: |
+          cp ../.env.default ../.env
+
+      - name: Copy backend .env
+        run: |
+          cp ../backend/.env.default ../backend/.env
+
+      - name: Run docker compose
+        run: |
+          docker compose -f ../docker-compose.yml --profile local up -d deps_backend
+
+      - name: Restore dependencies cache
+        uses: actions/cache@v5
+        with:
+          path: ~/.pnpm-store
+          key: ${{ needs.setup.outputs.cache-key }}
+          restore-keys: |
+            ${{ runner.os }}-pnpm-
+
+      - name: Install dependencies
         run: pnpm install --frozen-lockfile
 
-      - name: Set up Frontend - Format OpenAPI schema
-        id: format-schema
-        run: pnpm prettier --write ./src/app/api/openapi.json
+      - name: Setup .env
+        run: cp .env.default .env
+
+      - name: Wait for services to be ready
+        run: |
+          echo "Waiting for rest_server to be ready..."
+          timeout 60 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
+          echo "Waiting for database to be ready..."
+          timeout 60 sh -c 'until docker compose -f ../docker-compose.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done' || echo "Database ready check timeout, continuing..."
+
+      - name: Generate API queries
+        run: pnpm generate:api:force
 
       - name: Check for API schema changes
         run: |
           if ! git diff --exit-code src/app/api/openapi.json; then
             echo "❌ API schema changes detected in src/app/api/openapi.json"
             echo ""
-            echo "The openapi.json file has been modified after exporting the API schema."
+            echo "The openapi.json file has been modified after running 'pnpm generate:api-all'."
             echo "This usually means changes have been made in the BE endpoints without updating the Frontend."
             echo "The API schema is now out of sync with the Front-end queries."
             echo ""
             echo "To fix this:"
-            echo "\nIn the backend directory:"
-            echo "1. Run 'poetry run export-api-schema --output ../frontend/src/app/api/openapi.json'"
-            echo "\nIn the frontend directory:"
-            echo "2. Run 'pnpm prettier --write src/app/api/openapi.json'"
-            echo "3. Run 'pnpm generate:api'"
-            echo "4. Run 'pnpm types'"
-            echo "5. Fix any TypeScript errors that may have been introduced"
-            echo "6. Commit and push your changes"
+            echo "1. Pull the backend 'docker compose pull && docker compose up -d --build --force-recreate'"
+            echo "2. Run 'pnpm generate:api' locally"
+            echo "3. Run 'pnpm types' locally"
+            echo "4. Fix any TypeScript errors that may have been introduced"
+            echo "5. Commit and push your changes"
             echo ""
             exit 1
           else
             echo "✅ No API schema changes detected"
           fi
 
-      - name: Set up Frontend - Generate API client
-        id: generate-api-client
-        run: pnpm orval --config ./orval.config.ts
-        # Continue with type generation & check even if there are schema changes
-        if: success() || (steps.format-schema.outcome == 'success')
-
-      - name: Check for TypeScript errors
+      - name: Run Typescript checks
         run: pnpm types
-        if: success() || (steps.generate-api-client.outcome == 'success')
-
-  e2e_test:
-    name: end-to-end tests
-    runs-on: big-boi
-
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v6
-        with:
-          submodules: recursive
-
-      - name: Set up Platform - Copy default supabase .env
-        run: |
-          cp ../.env.default ../.env
-
-      - name: Set up Platform - Copy backend .env and set OpenAI API key
-        run: |
-          cp ../backend/.env.default ../backend/.env
-          echo "OPENAI_INTERNAL_API_KEY=${{ secrets.OPENAI_API_KEY }}" >> ../backend/.env
-        env:
-          # Used by E2E test data script to generate embeddings for approved store agents
-          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
-
-      - name: Set up Platform - Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
-        with:
-          driver: docker-container
-          driver-opts: network=host
-
-      - name: Set up Platform - Expose GHA cache to docker buildx CLI
-        uses: crazy-max/ghaction-github-runtime@v4
-
-      - name: Set up Platform - Build Docker images (with cache)
-        working-directory: autogpt_platform
-        run: |
-          pip install pyyaml
-
-          # Resolve extends and generate a flat compose file that bake can understand
-          docker compose -f docker-compose.yml config > docker-compose.resolved.yml
-
-          # Add cache configuration to the resolved compose file
-          python ../.github/workflows/scripts/docker-ci-fix-compose-build-cache.py \
-            --source docker-compose.resolved.yml \
-            --cache-from "type=gha" \
-            --cache-to "type=gha,mode=max" \
-            --backend-hash "${{ hashFiles('autogpt_platform/backend/Dockerfile', 'autogpt_platform/backend/poetry.lock', 'autogpt_platform/backend/backend/**') }}" \
-            --frontend-hash "${{ hashFiles('autogpt_platform/frontend/Dockerfile', 'autogpt_platform/frontend/pnpm-lock.yaml', 'autogpt_platform/frontend/src/**') }}" \
-            --git-ref "${{ github.ref }}"
-
-          # Build with bake using the resolved compose file (now includes cache config)
-          docker buildx bake --allow=fs.read=.. -f docker-compose.resolved.yml --load
-        env:
-          NEXT_PUBLIC_PW_TEST: true
-
-      - name: Set up tests - Cache E2E test data
-        id: e2e-data-cache
-        uses: actions/cache@v5
-        with:
-          path: /tmp/e2e_test_data.sql
-          key: e2e-test-data-${{ hashFiles('autogpt_platform/backend/test/e2e_test_data.py', 'autogpt_platform/backend/migrations/**', '.github/workflows/platform-fullstack-ci.yml') }}
-
-      - name: Set up Platform - Start Supabase DB + Auth
-        run: |
-          docker compose -f ../docker-compose.resolved.yml up -d db auth --no-build
-          echo "Waiting for database to be ready..."
-          timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db pg_isready -U postgres 2>/dev/null; do sleep 2; done'
-          echo "Waiting for auth service to be ready..."
-          timeout 60 sh -c 'until docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -c "SELECT 1 FROM auth.users LIMIT 1" 2>/dev/null; do sleep 2; done' || echo "Auth schema check timeout, continuing..."
-
-      - name: Set up Platform - Run migrations
-        run: |
-          echo "Running migrations..."
-          docker compose -f ../docker-compose.resolved.yml run --rm migrate
-          echo "✅ Migrations completed"
-        env:
-          NEXT_PUBLIC_PW_TEST: true
-
-      - name: Set up tests - Load cached E2E test data
-        if: steps.e2e-data-cache.outputs.cache-hit == 'true'
-        run: |
-          echo "✅ Found cached E2E test data, restoring..."
-          {
-            echo "SET session_replication_role = 'replica';"
-            cat /tmp/e2e_test_data.sql
-            echo "SET session_replication_role = 'origin';"
-          } | docker compose -f ../docker-compose.resolved.yml exec -T db psql -U postgres -d postgres -b
-          # Refresh materialized views after restore
-          docker compose -f ../docker-compose.resolved.yml exec -T db \
-            psql -U postgres -d postgres -b -c "SET search_path TO platform; SELECT refresh_store_materialized_views();" || true
-
-          echo "✅ E2E test data restored from cache"
-
-      - name: Set up Platform - Start (all other services)
-        run: |
-          docker compose -f ../docker-compose.resolved.yml up -d --no-build
-          echo "Waiting for rest_server to be ready..."
-          timeout 60 sh -c 'until curl -f http://localhost:8006/health 2>/dev/null; do sleep 2; done' || echo "Rest server health check timeout, continuing..."
-        env:
-          NEXT_PUBLIC_PW_TEST: true
-
-      - name: Set up tests - Create E2E test data
-        if: steps.e2e-data-cache.outputs.cache-hit != 'true'
-        run: |
-          echo "Creating E2E test data..."
-          docker cp ../backend/test/e2e_test_data.py $(docker compose -f ../docker-compose.resolved.yml ps -q rest_server):/tmp/e2e_test_data.py
-          docker compose -f ../docker-compose.resolved.yml exec -T rest_server sh -c "cd /app/autogpt_platform && python /tmp/e2e_test_data.py" || {
-            echo "❌ E2E test data creation failed!"
-            docker compose -f ../docker-compose.resolved.yml logs --tail=50 rest_server
-            exit 1
-          }
-
-          # Dump auth.users + platform schema for cache (two separate dumps)
-          echo "Dumping database for cache..."
-          {
-            docker compose -f ../docker-compose.resolved.yml exec -T db \
-              pg_dump -U postgres --data-only --column-inserts \
-              --table='auth.users' postgres
-            docker compose -f ../docker-compose.resolved.yml exec -T db \
-              pg_dump -U postgres --data-only --column-inserts \
-              --schema=platform \
-              --exclude-table='platform._prisma_migrations' \
-              --exclude-table='platform.apscheduler_jobs' \
-              --exclude-table='platform.apscheduler_jobs_batched_notifications' \
-              postgres
-          } > /tmp/e2e_test_data.sql
-
-          echo "✅ Database dump created for caching ($(wc -l < /tmp/e2e_test_data.sql) lines)"
-
-      - name: Set up tests - Enable corepack
-        run: corepack enable
-
-      - name: Set up tests - Set up Node
-        uses: actions/setup-node@v6
-        with:
-          node-version: "22.18.0"
-          cache: "pnpm"
-          cache-dependency-path: autogpt_platform/frontend/pnpm-lock.yaml
-
-      - name: Set up tests - Install dependencies
-        run: pnpm install --frozen-lockfile
-
-      - name: Set up tests - Install browser 'chromium'
-        run: pnpm playwright install --with-deps chromium
-
-      - name: Run Playwright tests
-        run: pnpm test:no-build
-        continue-on-error: false
-
-      - name: Upload Playwright report
-        if: always()
-        uses: actions/upload-artifact@v4
-        with:
-          name: playwright-report
-          path: playwright-report
-          if-no-files-found: ignore
-          retention-days: 3
-
-      - name: Upload Playwright test results
-        if: always()
-        uses: actions/upload-artifact@v4
-        with:
-          name: playwright-test-results
-          path: test-results
-          if-no-files-found: ignore
-          retention-days: 3
-
-      - name: Print Final Docker Compose logs
-        if: always()
-        run: docker compose -f ../docker-compose.resolved.yml logs

autogpt_platform/backend/backend/api/features/chat/routes.py

@@ -8,7 +8,7 @@ from typing import Annotated
 from uuid import uuid4
 
 from autogpt_libs import auth
-from fastapi import APIRouter, HTTPException, Query, Response, Security
+from fastapi import APIRouter, Depends, HTTPException, Query, Response, Security
 from fastapi.responses import StreamingResponse
 from prisma.models import UserWorkspaceFile
 from pydantic import BaseModel, Field, field_validator
@@ -27,12 +27,6 @@ from backend.copilot.model import (
     get_user_sessions,
     update_session_title,
 )
-from backend.copilot.rate_limit import (
-    CoPilotUsageStatus,
-    RateLimitExceeded,
-    check_rate_limit,
-    get_usage_status,
-)
 from backend.copilot.response_model import StreamError, StreamFinish, StreamHeartbeat
 from backend.copilot.tools.e2b_sandbox import kill_sandbox
 from backend.copilot.tools.models import (
@@ -126,8 +120,6 @@ class SessionDetailResponse(BaseModel):
     user_id: str | None
     messages: list[dict]
     active_stream: ActiveStreamInfo | None = None  # Present if stream is still active
-    total_prompt_tokens: int = 0
-    total_completion_tokens: int = 0
 
 
 class SessionSummaryResponse(BaseModel):
@@ -215,7 +207,7 @@ async def list_sessions(
             }
         except Exception:
             logger.warning(
-                "Failed to fetch processing status from Redis; defaulting to empty"
+                "Failed to fetch processing status from Redis; " "defaulting to empty"
             )
 
     return ListSessionsResponse(
@@ -237,7 +229,7 @@ async def list_sessions(
     "/sessions",
 )
 async def create_session(
-    user_id: Annotated[str, Security(auth.get_user_id)],
+    user_id: Annotated[str, Depends(auth.get_user_id)],
 ) -> CreateSessionResponse:
     """
     Create a new chat session.
@@ -356,7 +348,7 @@ async def update_session_title_route(
 )
 async def get_session(
     session_id: str,
-    user_id: Annotated[str, Security(auth.get_user_id)],
+    user_id: Annotated[str | None, Depends(auth.get_user_id)],
 ) -> SessionDetailResponse:
     """
     Retrieve the details of a specific chat session.
@@ -397,10 +389,6 @@ async def get_session(
             last_message_id=last_message_id,
         )
 
-    # Sum token usage from session
-    total_prompt = sum(u.prompt_tokens for u in session.usage)
-    total_completion = sum(u.completion_tokens for u in session.usage)
-
     return SessionDetailResponse(
         id=session.session_id,
         created_at=session.started_at.isoformat(),
@@ -408,25 +396,6 @@ async def get_session(
         user_id=session.user_id or None,
         messages=messages,
         active_stream=active_stream_info,
-        total_prompt_tokens=total_prompt,
-        total_completion_tokens=total_completion,
-    )
-
-
-@router.get(
-    "/usage",
-)
-async def get_copilot_usage(
-    user_id: Annotated[str, Security(auth.get_user_id)],
-) -> CoPilotUsageStatus:
-    """Get CoPilot usage status for the authenticated user.
-
-    Returns current token usage vs limits for daily and weekly windows.
-    """
-    return await get_usage_status(
-        user_id=user_id,
-        daily_token_limit=config.daily_token_limit,
-        weekly_token_limit=config.weekly_token_limit,
     )
 
 
@@ -436,7 +405,7 @@ async def get_copilot_usage(
 )
 async def cancel_session_task(
     session_id: str,
-    user_id: Annotated[str, Security(auth.get_user_id)],
+    user_id: Annotated[str | None, Depends(auth.get_user_id)],
 ) -> CancelSessionResponse:
     """Cancel the active streaming task for a session.
 
@@ -481,7 +450,7 @@ async def cancel_session_task(
 async def stream_chat_post(
     session_id: str,
     request: StreamChatRequest,
-    user_id: str = Security(auth.get_user_id),
+    user_id: str | None = Depends(auth.get_user_id),
 ):
     """
     Stream chat responses for a session (POST with context support).
@@ -498,7 +467,7 @@ async def stream_chat_post(
     Args:
         session_id: The chat session identifier to associate with the streamed messages.
         request: Request body containing message, is_user_message, and optional context.
-        user_id: Authenticated user ID.
+        user_id: Optional authenticated user ID.
     Returns:
         StreamingResponse: SSE-formatted response chunks.
 
@@ -507,7 +476,9 @@ async def stream_chat_post(
     import time
 
     stream_start_time = time.perf_counter()
-    log_meta = {"component": "ChatStream", "session_id": session_id, "user_id": user_id}
+    log_meta = {"component": "ChatStream", "session_id": session_id}
+    if user_id:
+        log_meta["user_id"] = user_id
 
     logger.info(
         f"[TIMING] stream_chat_post STARTED, session={session_id}, "
@@ -525,18 +496,6 @@ async def stream_chat_post(
         },
     )
 
-    # Pre-turn rate limit check (token-based).
-    # check_rate_limit short-circuits internally when both limits are 0.
-    if user_id:
-        try:
-            await check_rate_limit(
-                user_id=user_id,
-                daily_token_limit=config.daily_token_limit,
-                weekly_token_limit=config.weekly_token_limit,
-            )
-        except RateLimitExceeded as e:
-            raise HTTPException(status_code=429, detail=str(e)) from e
-
     # Enrich message with file metadata if file_ids are provided.
     # Also sanitise file_ids so only validated, workspace-scoped IDs are
     # forwarded downstream (e.g. to the executor via enqueue_copilot_turn).
@@ -771,7 +730,7 @@ async def stream_chat_post(
 )
 async def resume_session_stream(
     session_id: str,
-    user_id: str = Security(auth.get_user_id),
+    user_id: str | None = Depends(auth.get_user_id),
 ):
     """
     Resume an active stream for a session.

autogpt_platform/backend/backend/api/features/chat/routes_test.py

@@ -1,6 +1,5 @@
-"""Tests for chat API routes: session title update, file attachment validation, usage, rate limiting, and suggested prompts."""
+"""Tests for chat API routes: session title update, file attachment validation, and suggested prompts."""
 
-from datetime import UTC, datetime, timedelta
 from unittest.mock import AsyncMock, MagicMock
 
 import fastapi
@@ -252,156 +251,6 @@ def test_file_ids_scoped_to_workspace(mocker: pytest_mock.MockFixture):
     assert call_kwargs["where"]["isDeleted"] is False
 
 
-# ─── Rate limit → 429 ─────────────────────────────────────────────────
-
-
-def test_stream_chat_returns_429_on_daily_rate_limit(mocker: pytest_mock.MockFixture):
-    """When check_rate_limit raises RateLimitExceeded for daily limit the endpoint returns 429."""
-    from backend.copilot.rate_limit import RateLimitExceeded
-
-    _mock_stream_internals(mocker)
-    # Ensure the rate-limit branch is entered by setting a non-zero limit.
-    mocker.patch.object(chat_routes.config, "daily_token_limit", 10000)
-    mocker.patch.object(chat_routes.config, "weekly_token_limit", 50000)
-    mocker.patch(
-        "backend.api.features.chat.routes.check_rate_limit",
-        side_effect=RateLimitExceeded("daily", datetime.now(UTC) + timedelta(hours=1)),
-    )
-
-    response = client.post(
-        "/sessions/sess-1/stream",
-        json={"message": "hello"},
-    )
-    assert response.status_code == 429
-    assert "daily" in response.json()["detail"].lower()
-
-
-def test_stream_chat_returns_429_on_weekly_rate_limit(mocker: pytest_mock.MockFixture):
-    """When check_rate_limit raises RateLimitExceeded for weekly limit the endpoint returns 429."""
-    from backend.copilot.rate_limit import RateLimitExceeded
-
-    _mock_stream_internals(mocker)
-    mocker.patch.object(chat_routes.config, "daily_token_limit", 10000)
-    mocker.patch.object(chat_routes.config, "weekly_token_limit", 50000)
-    resets_at = datetime.now(UTC) + timedelta(days=3)
-    mocker.patch(
-        "backend.api.features.chat.routes.check_rate_limit",
-        side_effect=RateLimitExceeded("weekly", resets_at),
-    )
-
-    response = client.post(
-        "/sessions/sess-1/stream",
-        json={"message": "hello"},
-    )
-    assert response.status_code == 429
-    detail = response.json()["detail"].lower()
-    assert "weekly" in detail
-    assert "resets in" in detail
-
-
-def test_stream_chat_429_includes_reset_time(mocker: pytest_mock.MockFixture):
-    """The 429 response detail should include the human-readable reset time."""
-    from backend.copilot.rate_limit import RateLimitExceeded
-
-    _mock_stream_internals(mocker)
-    mocker.patch.object(chat_routes.config, "daily_token_limit", 10000)
-    mocker.patch.object(chat_routes.config, "weekly_token_limit", 50000)
-    mocker.patch(
-        "backend.api.features.chat.routes.check_rate_limit",
-        side_effect=RateLimitExceeded(
-            "daily", datetime.now(UTC) + timedelta(hours=2, minutes=30)
-        ),
-    )
-
-    response = client.post(
-        "/sessions/sess-1/stream",
-        json={"message": "hello"},
-    )
-    assert response.status_code == 429
-    detail = response.json()["detail"]
-    assert "2h" in detail
-    assert "Resets in" in detail
-
-
-# ─── Usage endpoint ───────────────────────────────────────────────────
-
-
-def _mock_usage(
-    mocker: pytest_mock.MockerFixture,
-    *,
-    daily_used: int = 500,
-    weekly_used: int = 2000,
-) -> AsyncMock:
-    """Mock get_usage_status to return a predictable CoPilotUsageStatus."""
-    from backend.copilot.rate_limit import CoPilotUsageStatus, UsageWindow
-
-    resets_at = datetime.now(UTC) + timedelta(days=1)
-    status = CoPilotUsageStatus(
-        daily=UsageWindow(used=daily_used, limit=10000, resets_at=resets_at),
-        weekly=UsageWindow(used=weekly_used, limit=50000, resets_at=resets_at),
-    )
-    return mocker.patch(
-        "backend.api.features.chat.routes.get_usage_status",
-        new_callable=AsyncMock,
-        return_value=status,
-    )
-
-
-def test_usage_returns_daily_and_weekly(
-    mocker: pytest_mock.MockerFixture,
-    test_user_id: str,
-) -> None:
-    """GET /usage returns daily and weekly usage."""
-    mock_get = _mock_usage(mocker, daily_used=500, weekly_used=2000)
-
-    mocker.patch.object(chat_routes.config, "daily_token_limit", 10000)
-    mocker.patch.object(chat_routes.config, "weekly_token_limit", 50000)
-
-    response = client.get("/usage")
-
-    assert response.status_code == 200
-    data = response.json()
-    assert data["daily"]["used"] == 500
-    assert data["weekly"]["used"] == 2000
-
-    mock_get.assert_called_once_with(
-        user_id=test_user_id,
-        daily_token_limit=10000,
-        weekly_token_limit=50000,
-    )
-
-
-def test_usage_uses_config_limits(
-    mocker: pytest_mock.MockerFixture,
-    test_user_id: str,
-) -> None:
-    """The endpoint forwards daily_token_limit and weekly_token_limit from config."""
-    mock_get = _mock_usage(mocker)
-
-    mocker.patch.object(chat_routes.config, "daily_token_limit", 99999)
-    mocker.patch.object(chat_routes.config, "weekly_token_limit", 77777)
-
-    response = client.get("/usage")
-
-    assert response.status_code == 200
-    mock_get.assert_called_once_with(
-        user_id=test_user_id,
-        daily_token_limit=99999,
-        weekly_token_limit=77777,
-    )
-
-
-def test_usage_rejects_unauthenticated_request() -> None:
-    """GET /usage should return 401 when no valid JWT is provided."""
-    unauthenticated_app = fastapi.FastAPI()
-    unauthenticated_app.include_router(chat_routes.router)
-    unauthenticated_client = fastapi.testclient.TestClient(unauthenticated_app)
-
-    response = unauthenticated_client.get("/usage")
-
-    assert response.status_code == 401
-
-
 # ─── Suggested prompts endpoint ──────────────────────────────────────
 
 

autogpt_platform/backend/backend/copilot/baseline/service.py

@@ -36,15 +36,13 @@ from backend.copilot.response_model import (
     StreamToolInputAvailable,
     StreamToolInputStart,
     StreamToolOutputAvailable,
-    StreamUsage,
 )
 from backend.copilot.service import (
     _build_system_prompt,
     _generate_session_title,
-    _get_openai_client,
+    client,
     config,
 )
-from backend.copilot.token_tracking import persist_and_record_usage
 from backend.copilot.tools import execute_tool, get_available_tools
 from backend.copilot.tracking import track_user_message
 from backend.util.exceptions import NotFoundError
@@ -91,7 +89,7 @@ async def _compress_session_messages(
         result = await compress_context(
             messages=messages_dict,
             model=config.model,
-            client=_get_openai_client(),
+            client=client,
         )
     except Exception as e:
         logger.warning("[Baseline] Context compression with LLM failed: %s", e)
@@ -223,10 +221,6 @@ async def stream_chat_completion_baseline(
     text_block_id = str(uuid.uuid4())
     text_started = False
     step_open = False
-    # Token usage accumulators — populated from streaming chunks
-    turn_prompt_tokens = 0
-    turn_completion_tokens = 0
-    _stream_error = False  # Track whether an error occurred during streaming
     try:
         for _round in range(_MAX_TOOL_ROUNDS):
             # Open a new step for each LLM round
@@ -238,31 +232,16 @@ async def stream_chat_completion_baseline(
                 model=config.model,
                 messages=openai_messages,
                 stream=True,
-                stream_options={"include_usage": True},
             )
             if tools:
                 create_kwargs["tools"] = tools
-            response = await _get_openai_client().chat.completions.create(**create_kwargs)  # type: ignore[arg-type]  # dynamic kwargs
+            response = await client.chat.completions.create(**create_kwargs)  # type: ignore[arg-type]  # dynamic kwargs
 
             # Accumulate streamed response (text + tool calls)
             round_text = ""
             tool_calls_by_index: dict[int, dict[str, str]] = {}
 
             async for chunk in response:
-                # Capture token usage from the streaming chunk.
-                # OpenRouter normalises all providers into OpenAI format
-                # where prompt_tokens already includes cached tokens
-                # (unlike Anthropic's native API). Use += to sum all
-                # tool-call rounds since each API call is independent.
-                # NOTE: stream_options={"include_usage": True} is not
-                # universally supported — some providers (Mistral, Llama
-                # via OpenRouter) always return chunk.usage=None. When
-                # that happens, tokens stay 0 and the tiktoken fallback
-                # below activates. Fail-open: one round is estimated.
-                if chunk.usage:
-                    turn_prompt_tokens += chunk.usage.prompt_tokens or 0
-                    turn_completion_tokens += chunk.usage.completion_tokens or 0
-
                 delta = chunk.choices[0].delta if chunk.choices else None
                 if not delta:
                     continue
@@ -415,7 +394,6 @@ async def stream_chat_completion_baseline(
             )
 
     except Exception as e:
-        _stream_error = True
         error_msg = str(e) or type(e).__name__
         logger.error("[Baseline] Streaming error: %s", error_msg, exc_info=True)
         # Close any open text/step before emitting error
@@ -433,49 +411,6 @@ async def stream_chat_completion_baseline(
             except Exception:
                 logger.warning("[Baseline] Langfuse trace context teardown failed")
 
-        # Fallback: estimate tokens via tiktoken when the provider does
-        # not honour stream_options={"include_usage": True}.
-        # Count the full message list (system + history + turn) since
-        # each API call sends the complete context window.
-        # NOTE: This estimates one round's prompt tokens. Multi-round tool-calling
-        # turns consume prompt tokens on each API call, so the total is underestimated.
-        # Skip fallback when an error occurred and no output was produced —
-        # charging rate-limit tokens for completely failed requests is unfair.
-        if (
-            turn_prompt_tokens == 0
-            and turn_completion_tokens == 0
-            and not (_stream_error and not assistant_text)
-        ):
-            from backend.util.prompt import (
-                estimate_token_count,
-                estimate_token_count_str,
-            )
-
-            turn_prompt_tokens = max(
-                estimate_token_count(openai_messages, model=config.model), 1
-            )
-            turn_completion_tokens = estimate_token_count_str(
-                assistant_text, model=config.model
-            )
-            logger.info(
-                "[Baseline] No streaming usage reported; estimated tokens: "
-                "prompt=%d, completion=%d",
-                turn_prompt_tokens,
-                turn_completion_tokens,
-            )
-
-        # Persist token usage to session and record for rate limiting.
-        # NOTE: OpenRouter folds cached tokens into prompt_tokens, so we
-        # cannot break out cache_read/cache_creation weights. Users on the
-        # baseline path may be slightly over-counted vs the SDK path.
-        await persist_and_record_usage(
-            session=session,
-            user_id=user_id,
-            prompt_tokens=turn_prompt_tokens,
-            completion_tokens=turn_completion_tokens,
-            log_prefix="[Baseline]",
-        )
-
         # Persist assistant response
         if assistant_text:
             session.messages.append(
@@ -486,16 +421,4 @@ async def stream_chat_completion_baseline(
         except Exception as persist_err:
             logger.error("[Baseline] Failed to persist session: %s", persist_err)
 
-    # Yield usage and finish AFTER try/finally (not inside finally).
-    # PEP 525 prohibits yielding from finally in async generators during
-    # aclose() — doing so raises RuntimeError on client disconnect.
-    # On GeneratorExit the client is already gone, so unreachable yields
-    # are harmless; on normal completion they reach the SSE stream.
-    if turn_prompt_tokens > 0 or turn_completion_tokens > 0:
-        yield StreamUsage(
-            prompt_tokens=turn_prompt_tokens,
-            completion_tokens=turn_completion_tokens,
-            total_tokens=turn_prompt_tokens + turn_completion_tokens,
-        )
-
     yield StreamFinish()

autogpt_platform/backend/backend/copilot/config.py

@@ -70,27 +70,6 @@ class ChatConfig(BaseSettings):
         description="Cache TTL in seconds for Langfuse prompt (0 to disable caching)",
     )
 
-    # Rate limiting — token-based limits per day and per week.
-    # Per-turn token cost varies with context size: ~10-15K for early turns,
-    # ~30-50K mid-session, up to ~100K pre-compaction. Average across a
-    # session with compaction cycles is ~25-35K tokens/turn, so 2.5M daily
-    # allows ~70-100 turns/day.
-    # Checked at the HTTP layer (routes.py) before each turn.
-    #
-    # TODO: These are deploy-time constants applied identically to every user.
-    #  If per-user or per-plan limits are needed (e.g., free tier vs paid), these
-    #  must move to the database (e.g., a UserPlan table) and get_usage_status /
-    #  check_rate_limit would look up each user's specific limits instead of
-    #  reading config.daily_token_limit / config.weekly_token_limit.
-    daily_token_limit: int = Field(
-        default=2_500_000,
-        description="Max tokens per day, resets at midnight UTC (0 = unlimited)",
-    )
-    weekly_token_limit: int = Field(
-        default=12_500_000,
-        description="Max tokens per week, resets Monday 00:00 UTC (0 = unlimited)",
-    )
-
     # Claude Agent SDK Configuration
     use_claude_agent_sdk: bool = Field(
         default=True,
@@ -136,7 +115,7 @@ class ChatConfig(BaseSettings):
         description="E2B sandbox template to use for copilot sessions.",
     )
     e2b_sandbox_timeout: int = Field(
-        default=300,  # 5 min safety net — explicit per-turn pause is the primary mechanism
+        default=420,  # 7 min safety net — allows headroom for compaction retries
         description="E2B sandbox running-time timeout (seconds). "
         "E2B timeout is wall-clock (not idle). Explicit per-turn pause is the primary "
         "mechanism; this is the safety net.",

autogpt_platform/backend/backend/copilot/model.py

@@ -73,9 +73,6 @@ class Usage(BaseModel):
     prompt_tokens: int
     completion_tokens: int
     total_tokens: int
-    # Cache breakdown (Anthropic-specific; zero for non-Anthropic models)
-    cache_read_tokens: int = 0
-    cache_creation_tokens: int = 0
 
 
 class ChatSessionInfo(BaseModel):
@@ -101,10 +98,7 @@ class ChatSessionInfo(BaseModel):
             prisma_session.successfulAgentSchedules, default={}
         )
 
-        # Calculate usage from token counts.
-        # NOTE: Per-turn cache_read_tokens / cache_creation_tokens breakdown
-        # is lost after persistence — the DB only stores aggregate prompt and
-        # completion totals. This is a known limitation.
+        # Calculate usage from token counts
         usage = []
         if prisma_session.totalPromptTokens or prisma_session.totalCompletionTokens:
             usage.append(

autogpt_platform/backend/backend/copilot/rate_limit.py

@@ -1,266 +0,0 @@
-"""CoPilot rate limiting based on token usage.
-
-Uses Redis fixed-window counters to track per-user token consumption
-with configurable daily and weekly limits. Daily windows reset at
-midnight UTC; weekly windows reset at ISO week boundary (Monday 00:00
-UTC). Fails open when Redis is unavailable to avoid blocking users.
-"""
-
-import asyncio
-import logging
-from datetime import UTC, datetime, timedelta
-
-from pydantic import BaseModel, Field
-from redis.exceptions import RedisError
-
-from backend.data.redis_client import get_redis_async
-
-logger = logging.getLogger(__name__)
-
-# Redis key prefixes
-_USAGE_KEY_PREFIX = "copilot:usage"
-
-
-class UsageWindow(BaseModel):
-    """Usage within a single time window."""
-
-    used: int
-    limit: int = Field(
-        description="Maximum tokens allowed in this window. 0 means unlimited."
-    )
-    resets_at: datetime
-
-
-class CoPilotUsageStatus(BaseModel):
-    """Current usage status for a user across all windows."""
-
-    daily: UsageWindow
-    weekly: UsageWindow
-
-
-class RateLimitExceeded(Exception):
-    """Raised when a user exceeds their CoPilot usage limit."""
-
-    def __init__(self, window: str, resets_at: datetime):
-        self.window = window
-        self.resets_at = resets_at
-        delta = resets_at - datetime.now(UTC)
-        total_secs = delta.total_seconds()
-        if total_secs <= 0:
-            time_str = "now"
-        else:
-            hours = int(total_secs // 3600)
-            minutes = int((total_secs % 3600) // 60)
-            time_str = f"{hours}h {minutes}m" if hours > 0 else f"{minutes}m"
-        super().__init__(
-            f"You've reached your {window} usage limit. Resets in {time_str}."
-        )
-
-
-async def get_usage_status(
-    user_id: str,
-    daily_token_limit: int,
-    weekly_token_limit: int,
-) -> CoPilotUsageStatus:
-    """Get current usage status for a user.
-
-    Args:
-        user_id: The user's ID.
-        daily_token_limit: Max tokens per day (0 = unlimited).
-        weekly_token_limit: Max tokens per week (0 = unlimited).
-
-    Returns:
-        CoPilotUsageStatus with current usage and limits.
-    """
-    now = datetime.now(UTC)
-    daily_used = 0
-    weekly_used = 0
-    try:
-        redis = await get_redis_async()
-        daily_raw, weekly_raw = await asyncio.gather(
-            redis.get(_daily_key(user_id, now=now)),
-            redis.get(_weekly_key(user_id, now=now)),
-        )
-        daily_used = int(daily_raw or 0)
-        weekly_used = int(weekly_raw or 0)
-    except (RedisError, ConnectionError, OSError):
-        logger.warning("Redis unavailable for usage status, returning zeros")
-
-    return CoPilotUsageStatus(
-        daily=UsageWindow(
-            used=daily_used,
-            limit=daily_token_limit,
-            resets_at=_daily_reset_time(now=now),
-        ),
-        weekly=UsageWindow(
-            used=weekly_used,
-            limit=weekly_token_limit,
-            resets_at=_weekly_reset_time(now=now),
-        ),
-    )
-
-
-async def check_rate_limit(
-    user_id: str,
-    daily_token_limit: int,
-    weekly_token_limit: int,
-) -> None:
-    """Check if user is within rate limits. Raises RateLimitExceeded if not.
-
-    This is a pre-turn soft check. The authoritative usage counter is updated
-    by ``record_token_usage()`` after the turn completes. Under concurrency,
-    two parallel turns may both pass this check against the same snapshot.
-    This is acceptable because token-based limits are approximate by nature
-    (the exact token count is unknown until after generation).
-
-    Fails open: if Redis is unavailable, allows the request.
-    """
-    # Short-circuit: when both limits are 0 (unlimited) skip the Redis
-    # round-trip entirely.
-    if daily_token_limit <= 0 and weekly_token_limit <= 0:
-        return
-
-    now = datetime.now(UTC)
-    try:
-        redis = await get_redis_async()
-        daily_raw, weekly_raw = await asyncio.gather(
-            redis.get(_daily_key(user_id, now=now)),
-            redis.get(_weekly_key(user_id, now=now)),
-        )
-        daily_used = int(daily_raw or 0)
-        weekly_used = int(weekly_raw or 0)
-    except (RedisError, ConnectionError, OSError):
-        logger.warning("Redis unavailable for rate limit check, allowing request")
-        return
-
-    # Worst-case overshoot: N concurrent requests × ~15K tokens each.
-    if daily_token_limit > 0 and daily_used >= daily_token_limit:
-        raise RateLimitExceeded("daily", _daily_reset_time(now=now))
-
-    if weekly_token_limit > 0 and weekly_used >= weekly_token_limit:
-        raise RateLimitExceeded("weekly", _weekly_reset_time(now=now))
-
-
-async def record_token_usage(
-    user_id: str,
-    prompt_tokens: int,
-    completion_tokens: int,
-    *,
-    cache_read_tokens: int = 0,
-    cache_creation_tokens: int = 0,
-) -> None:
-    """Record token usage for a user across all windows.
-
-    Uses cost-weighted counting so cached tokens don't unfairly penalise
-    multi-turn conversations. Anthropic's pricing:
-      - uncached input: 100%
-      - cache creation:  25%
-      - cache read:      10%
-      - output:         100%
-
-    ``prompt_tokens`` should be the *uncached* input count (``input_tokens``
-    from the API response). Cache counts are passed separately.
-
-    Args:
-        user_id: The user's ID.
-        prompt_tokens: Uncached input tokens.
-        completion_tokens: Output tokens.
-        cache_read_tokens: Tokens served from prompt cache (10% cost).
-        cache_creation_tokens: Tokens written to prompt cache (25% cost).
-    """
-    prompt_tokens = max(0, prompt_tokens)
-    completion_tokens = max(0, completion_tokens)
-    cache_read_tokens = max(0, cache_read_tokens)
-    cache_creation_tokens = max(0, cache_creation_tokens)
-
-    weighted_input = (
-        prompt_tokens
-        + round(cache_creation_tokens * 0.25)
-        + round(cache_read_tokens * 0.1)
-    )
-    total = weighted_input + completion_tokens
-    if total <= 0:
-        return
-
-    raw_total = (
-        prompt_tokens + cache_read_tokens + cache_creation_tokens + completion_tokens
-    )
-    logger.info(
-        "Recording token usage for %s: raw=%d, weighted=%d "
-        "(uncached=%d, cache_read=%d@10%%, cache_create=%d@25%%, output=%d)",
-        user_id[:8],
-        raw_total,
-        total,
-        prompt_tokens,
-        cache_read_tokens,
-        cache_creation_tokens,
-        completion_tokens,
-    )
-
-    now = datetime.now(UTC)
-    try:
-        redis = await get_redis_async()
-        # transaction=False: these are independent INCRBY+EXPIRE pairs on
-        # separate keys — no cross-key atomicity needed.  Skipping
-        # MULTI/EXEC avoids the overhead.  If the connection drops between
-        # INCRBY and EXPIRE the key survives until the next date-based key
-        # rotation (daily/weekly), so the memory-leak risk is negligible.
-        pipe = redis.pipeline(transaction=False)
-
-        # Daily counter (expires at next midnight UTC)
-        d_key = _daily_key(user_id, now=now)
-        pipe.incrby(d_key, total)
-        seconds_until_daily_reset = int(
-            (_daily_reset_time(now=now) - now).total_seconds()
-        )
-        pipe.expire(d_key, max(seconds_until_daily_reset, 1))
-
-        # Weekly counter (expires end of week)
-        w_key = _weekly_key(user_id, now=now)
-        pipe.incrby(w_key, total)
-        seconds_until_weekly_reset = int(
-            (_weekly_reset_time(now=now) - now).total_seconds()
-        )
-        pipe.expire(w_key, max(seconds_until_weekly_reset, 1))
-
-        await pipe.execute()
-    except (RedisError, ConnectionError, OSError):
-        logger.warning(
-            "Redis unavailable for recording token usage (tokens=%d)",
-            total,
-        )
-
-
-# ---------------------------------------------------------------------------
-# Private helpers
-# ---------------------------------------------------------------------------
-
-
-def _daily_key(user_id: str, now: datetime | None = None) -> str:
-    if now is None:
-        now = datetime.now(UTC)
-    return f"{_USAGE_KEY_PREFIX}:daily:{user_id}:{now.strftime('%Y-%m-%d')}"
-
-
-def _weekly_key(user_id: str, now: datetime | None = None) -> str:
-    if now is None:
-        now = datetime.now(UTC)
-    year, week, _ = now.isocalendar()
-    return f"{_USAGE_KEY_PREFIX}:weekly:{user_id}:{year}-W{week:02d}"
-
-
-def _daily_reset_time(now: datetime | None = None) -> datetime:
-    """Calculate when the current daily window resets (next midnight UTC)."""
-    if now is None:
-        now = datetime.now(UTC)
-    return now.replace(hour=0, minute=0, second=0, microsecond=0) + timedelta(days=1)
-
-
-def _weekly_reset_time(now: datetime | None = None) -> datetime:
-    """Calculate when the current weekly window resets (next Monday 00:00 UTC)."""
-    if now is None:
-        now = datetime.now(UTC)
-    days_until_monday = (7 - now.weekday()) % 7 or 7
-    return now.replace(hour=0, minute=0, second=0, microsecond=0) + timedelta(
-        days=days_until_monday
-    )

autogpt_platform/backend/backend/copilot/rate_limit_test.py

@@ -1,334 +0,0 @@
-"""Unit tests for CoPilot rate limiting."""
-
-from datetime import UTC, datetime, timedelta
-from unittest.mock import AsyncMock, MagicMock, patch
-
-import pytest
-from redis.exceptions import RedisError
-
-from .rate_limit import (
-    CoPilotUsageStatus,
-    RateLimitExceeded,
-    check_rate_limit,
-    get_usage_status,
-    record_token_usage,
-)
-
-_USER = "test-user-rl"
-
-
-# ---------------------------------------------------------------------------
-# RateLimitExceeded
-# ---------------------------------------------------------------------------
-
-
-class TestRateLimitExceeded:
-    def test_message_contains_window_name(self):
-        exc = RateLimitExceeded("daily", datetime.now(UTC) + timedelta(hours=1))
-        assert "daily" in str(exc)
-
-    def test_message_contains_reset_time(self):
-        exc = RateLimitExceeded(
-            "weekly", datetime.now(UTC) + timedelta(hours=2, minutes=30)
-        )
-        msg = str(exc)
-        # Allow for slight timing drift (29m or 30m)
-        assert "2h " in msg
-        assert "Resets in" in msg
-
-    def test_message_minutes_only_when_under_one_hour(self):
-        exc = RateLimitExceeded("daily", datetime.now(UTC) + timedelta(minutes=15))
-        msg = str(exc)
-        assert "Resets in" in msg
-        # Should not have "0h"
-        assert "0h" not in msg
-
-    def test_message_says_now_when_resets_at_is_in_the_past(self):
-        """Negative delta (clock skew / stale TTL) should say 'now', not '-1h -30m'."""
-        exc = RateLimitExceeded("daily", datetime.now(UTC) - timedelta(minutes=5))
-        assert "Resets in now" in str(exc)
-
-
-# ---------------------------------------------------------------------------
-# get_usage_status
-# ---------------------------------------------------------------------------
-
-
-class TestGetUsageStatus:
-    @pytest.mark.asyncio
-    async def test_returns_redis_values(self):
-        mock_redis = AsyncMock()
-        mock_redis.get = AsyncMock(side_effect=["500", "2000"])
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            status = await get_usage_status(
-                _USER, daily_token_limit=10000, weekly_token_limit=50000
-            )
-
-        assert isinstance(status, CoPilotUsageStatus)
-        assert status.daily.used == 500
-        assert status.daily.limit == 10000
-        assert status.weekly.used == 2000
-        assert status.weekly.limit == 50000
-
-    @pytest.mark.asyncio
-    async def test_returns_zeros_when_redis_unavailable(self):
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            side_effect=ConnectionError("Redis down"),
-        ):
-            status = await get_usage_status(
-                _USER, daily_token_limit=10000, weekly_token_limit=50000
-            )
-
-        assert status.daily.used == 0
-        assert status.weekly.used == 0
-
-    @pytest.mark.asyncio
-    async def test_partial_none_daily_counter(self):
-        """Daily counter is None (new day), weekly has usage."""
-        mock_redis = AsyncMock()
-        mock_redis.get = AsyncMock(side_effect=[None, "3000"])
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            status = await get_usage_status(
-                _USER, daily_token_limit=10000, weekly_token_limit=50000
-            )
-
-        assert status.daily.used == 0
-        assert status.weekly.used == 3000
-
-    @pytest.mark.asyncio
-    async def test_partial_none_weekly_counter(self):
-        """Weekly counter is None (start of week), daily has usage."""
-        mock_redis = AsyncMock()
-        mock_redis.get = AsyncMock(side_effect=["500", None])
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            status = await get_usage_status(
-                _USER, daily_token_limit=10000, weekly_token_limit=50000
-            )
-
-        assert status.daily.used == 500
-        assert status.weekly.used == 0
-
-    @pytest.mark.asyncio
-    async def test_resets_at_daily_is_next_midnight_utc(self):
-        mock_redis = AsyncMock()
-        mock_redis.get = AsyncMock(side_effect=["0", "0"])
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            status = await get_usage_status(
-                _USER, daily_token_limit=10000, weekly_token_limit=50000
-            )
-
-        now = datetime.now(UTC)
-        # Daily reset should be within 24h
-        assert status.daily.resets_at > now
-        assert status.daily.resets_at <= now + timedelta(hours=24, seconds=5)
-
-
-# ---------------------------------------------------------------------------
-# check_rate_limit
-# ---------------------------------------------------------------------------
-
-
-class TestCheckRateLimit:
-    @pytest.mark.asyncio
-    async def test_allows_when_under_limit(self):
-        mock_redis = AsyncMock()
-        mock_redis.get = AsyncMock(side_effect=["100", "200"])
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            # Should not raise
-            await check_rate_limit(
-                _USER, daily_token_limit=10000, weekly_token_limit=50000
-            )
-
-    @pytest.mark.asyncio
-    async def test_raises_when_daily_limit_exceeded(self):
-        mock_redis = AsyncMock()
-        mock_redis.get = AsyncMock(side_effect=["10000", "200"])
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            with pytest.raises(RateLimitExceeded) as exc_info:
-                await check_rate_limit(
-                    _USER, daily_token_limit=10000, weekly_token_limit=50000
-                )
-            assert exc_info.value.window == "daily"
-
-    @pytest.mark.asyncio
-    async def test_raises_when_weekly_limit_exceeded(self):
-        mock_redis = AsyncMock()
-        mock_redis.get = AsyncMock(side_effect=["100", "50000"])
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            with pytest.raises(RateLimitExceeded) as exc_info:
-                await check_rate_limit(
-                    _USER, daily_token_limit=10000, weekly_token_limit=50000
-                )
-            assert exc_info.value.window == "weekly"
-
-    @pytest.mark.asyncio
-    async def test_allows_when_redis_unavailable(self):
-        """Fail-open: allow requests when Redis is down."""
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            side_effect=ConnectionError("Redis down"),
-        ):
-            # Should not raise
-            await check_rate_limit(
-                _USER, daily_token_limit=10000, weekly_token_limit=50000
-            )
-
-    @pytest.mark.asyncio
-    async def test_skips_check_when_limit_is_zero(self):
-        mock_redis = AsyncMock()
-        mock_redis.get = AsyncMock(side_effect=["999999", "999999"])
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            # Should not raise — limits of 0 mean unlimited
-            await check_rate_limit(_USER, daily_token_limit=0, weekly_token_limit=0)
-
-
-# ---------------------------------------------------------------------------
-# record_token_usage
-# ---------------------------------------------------------------------------
-
-
-class TestRecordTokenUsage:
-    @staticmethod
-    def _make_pipeline_mock() -> MagicMock:
-        """Create a pipeline mock with sync methods and async execute."""
-        pipe = MagicMock()
-        pipe.execute = AsyncMock(return_value=[])
-        return pipe
-
-    @pytest.mark.asyncio
-    async def test_increments_redis_counters(self):
-        mock_pipe = self._make_pipeline_mock()
-        mock_redis = AsyncMock()
-        mock_redis.pipeline = lambda **_kw: mock_pipe
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            await record_token_usage(_USER, prompt_tokens=100, completion_tokens=50)
-
-        # Should call incrby twice (daily + weekly) with total=150
-        incrby_calls = mock_pipe.incrby.call_args_list
-        assert len(incrby_calls) == 2
-        assert incrby_calls[0].args[1] == 150  # daily
-        assert incrby_calls[1].args[1] == 150  # weekly
-
-    @pytest.mark.asyncio
-    async def test_skips_when_zero_tokens(self):
-        mock_redis = AsyncMock()
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            await record_token_usage(_USER, prompt_tokens=0, completion_tokens=0)
-
-        # Should not call pipeline at all
-        mock_redis.pipeline.assert_not_called()
-
-    @pytest.mark.asyncio
-    async def test_sets_expire_on_both_keys(self):
-        """Pipeline should call expire for both daily and weekly keys."""
-        mock_pipe = self._make_pipeline_mock()
-        mock_redis = AsyncMock()
-        mock_redis.pipeline = lambda **_kw: mock_pipe
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            await record_token_usage(_USER, prompt_tokens=100, completion_tokens=50)
-
-        expire_calls = mock_pipe.expire.call_args_list
-        assert len(expire_calls) == 2
-
-        # Daily key TTL should be positive (seconds until next midnight)
-        daily_ttl = expire_calls[0].args[1]
-        assert daily_ttl >= 1
-
-        # Weekly key TTL should be positive (seconds until next Monday)
-        weekly_ttl = expire_calls[1].args[1]
-        assert weekly_ttl >= 1
-
-    @pytest.mark.asyncio
-    async def test_handles_redis_failure_gracefully(self):
-        """Should not raise when Redis is unavailable."""
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            side_effect=ConnectionError("Redis down"),
-        ):
-            # Should not raise
-            await record_token_usage(_USER, prompt_tokens=100, completion_tokens=50)
-
-    @pytest.mark.asyncio
-    async def test_cost_weighted_counting(self):
-        """Cached tokens should be weighted: cache_read=10%, cache_create=25%."""
-        mock_pipe = self._make_pipeline_mock()
-        mock_redis = AsyncMock()
-        mock_redis.pipeline = lambda **_kw: mock_pipe
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            await record_token_usage(
-                _USER,
-                prompt_tokens=100,  # uncached → 100
-                completion_tokens=50,  # output → 50
-                cache_read_tokens=10000,  # 10% → 1000
-                cache_creation_tokens=400,  # 25% → 100
-            )
-
-        # Expected weighted total: 100 + 1000 + 100 + 50 = 1250
-        incrby_calls = mock_pipe.incrby.call_args_list
-        assert len(incrby_calls) == 2
-        assert incrby_calls[0].args[1] == 1250  # daily
-        assert incrby_calls[1].args[1] == 1250  # weekly
-
-    @pytest.mark.asyncio
-    async def test_handles_redis_error_during_pipeline_execute(self):
-        """Should not raise when pipeline.execute() fails with RedisError."""
-        mock_pipe = self._make_pipeline_mock()
-        mock_pipe.execute = AsyncMock(side_effect=RedisError("Pipeline failed"))
-        mock_redis = AsyncMock()
-        mock_redis.pipeline = lambda **_kw: mock_pipe
-
-        with patch(
-            "backend.copilot.rate_limit.get_redis_async",
-            return_value=mock_redis,
-        ):
-            # Should not raise — fail-open
-            await record_token_usage(_USER, prompt_tokens=100, completion_tokens=50)

autogpt_platform/backend/backend/copilot/response_model.py

@@ -43,6 +43,7 @@ class ResponseType(str, Enum):
     ERROR = "error"
     USAGE = "usage"
     HEARTBEAT = "heartbeat"
+    STATUS = "status"
 
 
 class StreamBaseResponse(BaseModel):
@@ -186,43 +187,12 @@ class StreamToolOutputAvailable(StreamBaseResponse):
 
 
 class StreamUsage(StreamBaseResponse):
-    """Token usage statistics.
-
-    Emitted as an SSE comment so the Vercel AI SDK parser ignores it
-    (it uses z.strictObject() and rejects unknown event types).
-    Usage data is recorded server-side (session DB + Redis counters).
-    """
+    """Token usage statistics."""
 
     type: ResponseType = ResponseType.USAGE
-    prompt_tokens: int = Field(
-        ...,
-        serialization_alias="promptTokens",
-        description="Number of uncached prompt tokens",
-    )
-    completion_tokens: int = Field(
-        ...,
-        serialization_alias="completionTokens",
-        description="Number of completion tokens",
-    )
-    total_tokens: int = Field(
-        ...,
-        serialization_alias="totalTokens",
-        description="Total number of tokens (raw, not weighted)",
-    )
-    cache_read_tokens: int = Field(
-        default=0,
-        serialization_alias="cacheReadTokens",
-        description="Prompt tokens served from cache (10% cost)",
-    )
-    cache_creation_tokens: int = Field(
-        default=0,
-        serialization_alias="cacheCreationTokens",
-        description="Prompt tokens written to cache (25% cost)",
-    )
-
-    def to_sse(self) -> str:
-        """Emit as SSE comment so the AI SDK parser ignores it."""
-        return f": usage {self.model_dump_json(exclude_none=True, by_alias=True)}\n\n"
+    promptTokens: int = Field(..., description="Number of prompt tokens")
+    completionTokens: int = Field(..., description="Number of completion tokens")
+    totalTokens: int = Field(..., description="Total number of tokens")
 
 
 class StreamError(StreamBaseResponse):
@@ -263,3 +233,26 @@ class StreamHeartbeat(StreamBaseResponse):
     def to_sse(self) -> str:
         """Convert to SSE comment format to keep connection alive."""
         return ": heartbeat\n\n"
+
+
+class StreamStatus(StreamBaseResponse):
+    """Transient status notification shown to the user during long operations.
+
+    Used to provide feedback when the backend performs behind-the-scenes work
+    (e.g., compacting conversation context on a retry) that would otherwise
+    leave the user staring at an unexplained pause.
+    """
+
+    type: ResponseType = ResponseType.STATUS
+    message: str = Field(..., description="Human-readable status message")
+
+    def to_sse(self) -> str:
+        """Encode as an SSE comment so the AI SDK stream parser ignores it.
+
+        The frontend AI SDK validates every ``data:`` line against a strict
+        Zod union of known chunk types.  ``"status"`` is not in that union,
+        so sending it as ``data:`` would cause a schema-validation error that
+        breaks the entire stream.  Using an SSE comment (``:``) keeps the
+        connection alive and is silently discarded by ``EventSource`` parsers.
+        """
+        return f": status {self.message}\n\n"

autogpt_platform/backend/backend/copilot/sdk/compaction.py

@@ -12,6 +12,7 @@ import asyncio
 import logging
 import uuid
 from dataclasses import dataclass, field
+from typing import Any
 
 from ..constants import COMPACTION_DONE_MSG, COMPACTION_TOOL_NAME
 from ..model import ChatMessage, ChatSession
@@ -119,14 +120,12 @@ def filter_compaction_messages(
     filtered: list[ChatMessage] = []
     for msg in messages:
         if msg.role == "assistant" and msg.tool_calls:
+            real_calls: list[dict[str, Any]] = []
             for tc in msg.tool_calls:
                 if tc.get("function", {}).get("name") == COMPACTION_TOOL_NAME:
                     compaction_ids.add(tc.get("id", ""))
-            real_calls = [
-                tc
-                for tc in msg.tool_calls
-                if tc.get("function", {}).get("name") != COMPACTION_TOOL_NAME
-            ]
+                else:
+                    real_calls.append(tc)
             if not real_calls and not msg.content:
                 continue
         if msg.role == "tool" and msg.tool_call_id in compaction_ids:
@@ -222,6 +221,7 @@ class CompactionTracker:
 
     def reset_for_query(self) -> None:
         """Reset per-query state before a new SDK query."""
+        self._compact_start.clear()
         self._done = False
         self._start_emitted = False
         self._tool_call_id = ""

autogpt_platform/backend/backend/copilot/sdk/conftest.py

@@ -0,0 +1,41 @@
+"""Shared test fixtures for copilot SDK tests."""
+
+from __future__ import annotations
+
+from uuid import uuid4
+
+from backend.util import json
+
+
+def build_test_transcript(pairs: list[tuple[str, str]]) -> str:
+    """Build a minimal valid JSONL transcript from (role, content) pairs.
+
+    Use this helper in any copilot SDK test that needs a well-formed
+    transcript without hitting the real storage layer.
+    """
+    lines: list[str] = []
+    last_uuid: str | None = None
+    for role, content in pairs:
+        uid = str(uuid4())
+        entry_type = "assistant" if role == "assistant" else "user"
+        msg: dict = {"role": role, "content": content}
+        if role == "assistant":
+            msg.update(
+                {
+                    "model": "",
+                    "id": f"msg_{uid[:8]}",
+                    "type": "message",
+                    "content": [{"type": "text", "text": content}],
+                    "stop_reason": "end_turn",
+                    "stop_sequence": None,
+                }
+            )
+        entry = {
+            "type": entry_type,
+            "uuid": uid,
+            "parentUuid": last_uuid,
+            "message": msg,
+        }
+        lines.append(json.dumps(entry, separators=(",", ":")))
+        last_uuid = uid
+    return "\n".join(lines) + "\n"

autogpt_platform/backend/backend/copilot/sdk/prompt_too_long_test.py

@@ -0,0 +1,552 @@
+"""Tests for retry logic and transcript compaction helpers."""
+
+from __future__ import annotations
+
+from unittest.mock import AsyncMock, patch
+from uuid import uuid4
+
+import pytest
+
+from backend.util import json
+
+from .conftest import build_test_transcript as _build_transcript
+from .service import _is_prompt_too_long
+from .transcript import (
+    _flatten_assistant_content,
+    _flatten_tool_result_content,
+    _messages_to_transcript,
+    _transcript_to_messages,
+    compact_transcript,
+    validate_transcript,
+)
+
+# ---------------------------------------------------------------------------
+# _flatten_assistant_content
+# ---------------------------------------------------------------------------
+
+
+class TestFlattenAssistantContent:
+    def test_text_blocks(self):
+        blocks = [
+            {"type": "text", "text": "Hello"},
+            {"type": "text", "text": "World"},
+        ]
+        assert _flatten_assistant_content(blocks) == "Hello\nWorld"
+
+    def test_tool_use_blocks(self):
+        blocks = [{"type": "tool_use", "name": "read_file", "input": {}}]
+        assert _flatten_assistant_content(blocks) == "[tool_use: read_file]"
+
+    def test_mixed_blocks(self):
+        blocks = [
+            {"type": "text", "text": "Let me read that."},
+            {"type": "tool_use", "name": "Read", "input": {"path": "/foo"}},
+        ]
+        result = _flatten_assistant_content(blocks)
+        assert "Let me read that." in result
+        assert "[tool_use: Read]" in result
+
+    def test_raw_strings(self):
+        assert _flatten_assistant_content(["hello", "world"]) == "hello\nworld"
+
+    def test_unknown_block_type_preserved_as_placeholder(self):
+        blocks = [
+            {"type": "text", "text": "See this image:"},
+            {"type": "image", "source": {"type": "base64", "data": "..."}},
+        ]
+        result = _flatten_assistant_content(blocks)
+        assert "See this image:" in result
+        assert "[__image__]" in result
+
+    def test_empty(self):
+        assert _flatten_assistant_content([]) == ""
+
+
+# ---------------------------------------------------------------------------
+# _flatten_tool_result_content
+# ---------------------------------------------------------------------------
+
+
+class TestFlattenToolResultContent:
+    def test_tool_result_with_text(self):
+        blocks = [
+            {
+                "type": "tool_result",
+                "tool_use_id": "123",
+                "content": [{"type": "text", "text": "file contents here"}],
+            }
+        ]
+        assert _flatten_tool_result_content(blocks) == "file contents here"
+
+    def test_tool_result_with_string_content(self):
+        blocks = [{"type": "tool_result", "tool_use_id": "123", "content": "ok"}]
+        assert _flatten_tool_result_content(blocks) == "ok"
+
+    def test_text_block(self):
+        blocks = [{"type": "text", "text": "plain text"}]
+        assert _flatten_tool_result_content(blocks) == "plain text"
+
+    def test_raw_string(self):
+        assert _flatten_tool_result_content(["raw"]) == "raw"
+
+    def test_tool_result_with_none_content(self):
+        """tool_result with content=None should produce empty string."""
+        blocks = [{"type": "tool_result", "tool_use_id": "x", "content": None}]
+        assert _flatten_tool_result_content(blocks) == ""
+
+    def test_tool_result_with_empty_list_content(self):
+        """tool_result with content=[] should produce empty string."""
+        blocks = [{"type": "tool_result", "tool_use_id": "x", "content": []}]
+        assert _flatten_tool_result_content(blocks) == ""
+
+    def test_empty(self):
+        assert _flatten_tool_result_content([]) == ""
+
+    def test_nested_dict_without_text(self):
+        """Dict blocks without text key use json.dumps fallback."""
+        blocks = [
+            {
+                "type": "tool_result",
+                "tool_use_id": "x",
+                "content": [{"type": "image", "source": "data:..."}],
+            }
+        ]
+        result = _flatten_tool_result_content(blocks)
+        assert "image" in result  # json.dumps fallback
+
+    def test_unknown_block_type_preserved_as_placeholder(self):
+        blocks = [{"type": "image", "source": {"type": "base64", "data": "..."}}]
+        result = _flatten_tool_result_content(blocks)
+        assert "[__image__]" in result
+
+
+# ---------------------------------------------------------------------------
+# _transcript_to_messages
+# ---------------------------------------------------------------------------
+
+
+def _make_entry(entry_type: str, role: str, content: str | list, **kwargs) -> str:
+    """Build a JSONL line for testing."""
+    uid = str(uuid4())
+    msg: dict = {"role": role, "content": content}
+    msg.update(kwargs)
+    entry = {
+        "type": entry_type,
+        "uuid": uid,
+        "parentUuid": None,
+        "message": msg,
+    }
+    return json.dumps(entry, separators=(",", ":"))
+
+
+class TestTranscriptToMessages:
+    def test_basic_roundtrip(self):
+        lines = [
+            _make_entry("user", "user", "Hello"),
+            _make_entry("assistant", "assistant", [{"type": "text", "text": "Hi"}]),
+        ]
+        content = "\n".join(lines) + "\n"
+        messages = _transcript_to_messages(content)
+        assert len(messages) == 2
+        assert messages[0] == {"role": "user", "content": "Hello"}
+        assert messages[1] == {"role": "assistant", "content": "Hi"}
+
+    def test_skips_strippable_types(self):
+        """Progress and metadata entries are excluded."""
+        lines = [
+            _make_entry("user", "user", "Hello"),
+            json.dumps(
+                {
+                    "type": "progress",
+                    "uuid": str(uuid4()),
+                    "parentUuid": None,
+                    "message": {"role": "assistant", "content": "..."},
+                }
+            ),
+            _make_entry("assistant", "assistant", [{"type": "text", "text": "Hi"}]),
+        ]
+        content = "\n".join(lines) + "\n"
+        messages = _transcript_to_messages(content)
+        assert len(messages) == 2
+
+    def test_empty_content(self):
+        assert _transcript_to_messages("") == []
+
+    def test_tool_result_content(self):
+        """User entries with tool_result content blocks are flattened."""
+        lines = [
+            _make_entry(
+                "user",
+                "user",
+                [
+                    {
+                        "type": "tool_result",
+                        "tool_use_id": "123",
+                        "content": "tool output",
+                    }
+                ],
+            ),
+        ]
+        content = "\n".join(lines) + "\n"
+        messages = _transcript_to_messages(content)
+        assert len(messages) == 1
+        assert messages[0]["content"] == "tool output"
+
+    def test_malformed_json_lines_skipped(self):
+        """Malformed JSON lines in transcript are silently skipped."""
+        lines = [
+            _make_entry("user", "user", "Hello"),
+            "this is not valid json",
+            _make_entry("assistant", "assistant", [{"type": "text", "text": "Hi"}]),
+        ]
+        content = "\n".join(lines) + "\n"
+        messages = _transcript_to_messages(content)
+        assert len(messages) == 2
+
+    def test_empty_lines_skipped(self):
+        """Empty lines and whitespace-only lines are skipped."""
+        lines = [
+            _make_entry("user", "user", "Hello"),
+            "",
+            "   ",
+            _make_entry("assistant", "assistant", [{"type": "text", "text": "Hi"}]),
+        ]
+        content = "\n".join(lines) + "\n"
+        messages = _transcript_to_messages(content)
+        assert len(messages) == 2
+
+    def test_unicode_content_preserved(self):
+        """Unicode characters survive transcript roundtrip."""
+        lines = [
+            _make_entry("user", "user", "Hello 你好 🌍"),
+            _make_entry(
+                "assistant",
+                "assistant",
+                [{"type": "text", "text": "Bonjour 日本語 émojis 🎉"}],
+            ),
+        ]
+        content = "\n".join(lines) + "\n"
+        messages = _transcript_to_messages(content)
+        assert messages[0]["content"] == "Hello 你好 🌍"
+        assert messages[1]["content"] == "Bonjour 日本語 émojis 🎉"
+
+    def test_entry_without_role_skipped(self):
+        """Entries with missing role in message are skipped."""
+        entry_no_role = json.dumps(
+            {
+                "type": "user",
+                "uuid": str(uuid4()),
+                "parentUuid": None,
+                "message": {"content": "no role here"},
+            }
+        )
+        lines = [
+            entry_no_role,
+            _make_entry("user", "user", "Hello"),
+        ]
+        content = "\n".join(lines) + "\n"
+        messages = _transcript_to_messages(content)
+        assert len(messages) == 1
+        assert messages[0]["content"] == "Hello"
+
+    def test_tool_use_and_result_pairs(self):
+        """Tool use + tool result pairs are properly flattened."""
+        lines = [
+            _make_entry(
+                "assistant",
+                "assistant",
+                [
+                    {"type": "text", "text": "Let me check."},
+                    {"type": "tool_use", "name": "read_file", "input": {"path": "/x"}},
+                ],
+            ),
+            _make_entry(
+                "user",
+                "user",
+                [
+                    {
+                        "type": "tool_result",
+                        "tool_use_id": "abc",
+                        "content": [{"type": "text", "text": "file contents"}],
+                    }
+                ],
+            ),
+        ]
+        content = "\n".join(lines) + "\n"
+        messages = _transcript_to_messages(content)
+        assert len(messages) == 2
+        assert "Let me check." in messages[0]["content"]
+        assert "[tool_use: read_file]" in messages[0]["content"]
+        assert messages[1]["content"] == "file contents"
+
+
+# ---------------------------------------------------------------------------
+# _messages_to_transcript
+# ---------------------------------------------------------------------------
+
+
+class TestMessagesToTranscript:
+    def test_produces_valid_jsonl(self):
+        messages = [
+            {"role": "user", "content": "Hello"},
+            {"role": "assistant", "content": "Hi there"},
+        ]
+        result = _messages_to_transcript(messages)
+        lines = result.strip().split("\n")
+        assert len(lines) == 2
+        for line in lines:
+            parsed = json.loads(line)
+            assert "type" in parsed
+            assert "uuid" in parsed
+            assert "message" in parsed
+
+    def test_assistant_has_proper_structure(self):
+        messages = [{"role": "assistant", "content": "Hello"}]
+        result = _messages_to_transcript(messages)
+        entry = json.loads(result.strip())
+        assert entry["type"] == "assistant"
+        msg = entry["message"]
+        assert msg["role"] == "assistant"
+        assert msg["type"] == "message"
+        assert msg["stop_reason"] == "end_turn"
+        assert isinstance(msg["content"], list)
+        assert msg["content"][0]["type"] == "text"
+
+    def test_user_has_plain_content(self):
+        messages = [{"role": "user", "content": "Hi"}]
+        result = _messages_to_transcript(messages)
+        entry = json.loads(result.strip())
+        assert entry["type"] == "user"
+        assert entry["message"]["content"] == "Hi"
+
+    def test_parent_uuid_chain(self):
+        messages = [
+            {"role": "user", "content": "A"},
+            {"role": "assistant", "content": "B"},
+            {"role": "user", "content": "C"},
+        ]
+        result = _messages_to_transcript(messages)
+        lines = result.strip().split("\n")
+        entries = [json.loads(line) for line in lines]
+        assert entries[0]["parentUuid"] == ""
+        assert entries[1]["parentUuid"] == entries[0]["uuid"]
+        assert entries[2]["parentUuid"] == entries[1]["uuid"]
+
+    def test_empty_messages(self):
+        assert _messages_to_transcript([]) == ""
+
+    def test_output_is_valid_transcript(self):
+        """Output should pass validate_transcript if it has assistant entries."""
+        messages = [
+            {"role": "user", "content": "Hello"},
+            {"role": "assistant", "content": "Hi"},
+        ]
+        result = _messages_to_transcript(messages)
+        assert validate_transcript(result)
+
+    def test_roundtrip_to_messages(self):
+        """Messages → transcript → messages preserves structure."""
+        original = [
+            {"role": "user", "content": "Hello"},
+            {"role": "assistant", "content": "Hi there"},
+            {"role": "user", "content": "How are you?"},
+        ]
+        transcript = _messages_to_transcript(original)
+        restored = _transcript_to_messages(transcript)
+        assert len(restored) == len(original)
+        for orig, rest in zip(original, restored):
+            assert orig["role"] == rest["role"]
+            assert orig["content"] == rest["content"]
+
+
+# ---------------------------------------------------------------------------
+# compact_transcript
+# ---------------------------------------------------------------------------
+
+
+class TestCompactTranscript:
+    @pytest.mark.asyncio
+    async def test_too_few_messages_returns_none(self):
+        """compact_transcript returns None when transcript has < 2 messages."""
+        transcript = _build_transcript([("user", "Hello")])
+        with patch(
+            "backend.copilot.config.ChatConfig",
+            return_value=type(
+                "Cfg", (), {"model": "m", "api_key": "k", "base_url": "u"}
+            )(),
+        ):
+            result = await compact_transcript(transcript, model="test-model")
+        assert result is None
+
+    @pytest.mark.asyncio
+    async def test_returns_none_when_not_compacted(self):
+        """When compress_context says no compaction needed, returns None.
+        The compressor couldn't reduce it, so retrying with the same
+        content would fail identically."""
+        transcript = _build_transcript(
+            [
+                ("user", "Hello"),
+                ("assistant", "Hi there"),
+            ]
+        )
+        mock_result = type(
+            "CompressResult",
+            (),
+            {
+                "was_compacted": False,
+                "messages": [],
+                "original_token_count": 100,
+                "token_count": 100,
+                "messages_summarized": 0,
+                "messages_dropped": 0,
+            },
+        )()
+        with (
+            patch(
+                "backend.copilot.config.ChatConfig",
+                return_value=type(
+                    "Cfg", (), {"model": "m", "api_key": "k", "base_url": "u"}
+                )(),
+            ),
+            patch(
+                "backend.copilot.sdk.transcript._run_compression",
+                new_callable=AsyncMock,
+                return_value=mock_result,
+            ),
+        ):
+            result = await compact_transcript(transcript, model="test-model")
+        assert result is None
+
+    @pytest.mark.asyncio
+    async def test_returns_compacted_transcript(self):
+        """When compaction succeeds, returns a valid compacted transcript."""
+        transcript = _build_transcript(
+            [
+                ("user", "Hello"),
+                ("assistant", "Hi"),
+                ("user", "More"),
+                ("assistant", "Details"),
+            ]
+        )
+        compacted_msgs = [
+            {"role": "user", "content": "[summary]"},
+            {"role": "assistant", "content": "Summarized response"},
+        ]
+        mock_result = type(
+            "CompressResult",
+            (),
+            {
+                "was_compacted": True,
+                "messages": compacted_msgs,
+                "original_token_count": 500,
+                "token_count": 100,
+                "messages_summarized": 2,
+                "messages_dropped": 0,
+            },
+        )()
+        with (
+            patch(
+                "backend.copilot.config.ChatConfig",
+                return_value=type(
+                    "Cfg", (), {"model": "m", "api_key": "k", "base_url": "u"}
+                )(),
+            ),
+            patch(
+                "backend.copilot.sdk.transcript._run_compression",
+                new_callable=AsyncMock,
+                return_value=mock_result,
+            ),
+        ):
+            result = await compact_transcript(transcript, model="test-model")
+        assert result is not None
+        assert validate_transcript(result)
+        msgs = _transcript_to_messages(result)
+        assert len(msgs) == 2
+        assert msgs[1]["content"] == "Summarized response"
+
+    @pytest.mark.asyncio
+    async def test_returns_none_on_compression_failure(self):
+        """When _run_compression raises, returns None."""
+        transcript = _build_transcript(
+            [
+                ("user", "Hello"),
+                ("assistant", "Hi"),
+            ]
+        )
+        with (
+            patch(
+                "backend.copilot.config.ChatConfig",
+                return_value=type(
+                    "Cfg", (), {"model": "m", "api_key": "k", "base_url": "u"}
+                )(),
+            ),
+            patch(
+                "backend.copilot.sdk.transcript._run_compression",
+                new_callable=AsyncMock,
+                side_effect=RuntimeError("LLM unavailable"),
+            ),
+        ):
+            result = await compact_transcript(transcript, model="test-model")
+        assert result is None
+
+
+# ---------------------------------------------------------------------------
+# _is_prompt_too_long
+# ---------------------------------------------------------------------------
+
+
+class TestIsPromptTooLong:
+    """Unit tests for _is_prompt_too_long pattern matching."""
+
+    def test_prompt_is_too_long(self):
+        err = RuntimeError("prompt is too long for model context")
+        assert _is_prompt_too_long(err) is True
+
+    def test_request_too_large(self):
+        err = Exception("request too large: 250000 tokens")
+        assert _is_prompt_too_long(err) is True
+
+    def test_maximum_context_length(self):
+        err = ValueError("maximum context length exceeded")
+        assert _is_prompt_too_long(err) is True
+
+    def test_context_length_exceeded(self):
+        err = Exception("context_length_exceeded")
+        assert _is_prompt_too_long(err) is True
+
+    def test_input_tokens_exceed(self):
+        err = Exception("input tokens exceed the max_tokens limit")
+        assert _is_prompt_too_long(err) is True
+
+    def test_input_is_too_long(self):
+        err = Exception("input is too long for the model")
+        assert _is_prompt_too_long(err) is True
+
+    def test_content_length_exceeds(self):
+        err = Exception("content length exceeds maximum")
+        assert _is_prompt_too_long(err) is True
+
+    def test_unrelated_error_returns_false(self):
+        err = RuntimeError("network timeout")
+        assert _is_prompt_too_long(err) is False
+
+    def test_auth_error_returns_false(self):
+        err = Exception("authentication failed: invalid API key")
+        assert _is_prompt_too_long(err) is False
+
+    def test_chained_exception_detected(self):
+        """Prompt-too-long error wrapped in another exception is detected."""
+        inner = RuntimeError("prompt is too long")
+        outer = Exception("SDK error")
+        outer.__cause__ = inner
+        assert _is_prompt_too_long(outer) is True
+
+    def test_case_insensitive(self):
+        err = Exception("PROMPT IS TOO LONG")
+        assert _is_prompt_too_long(err) is True
+
+    def test_old_max_tokens_exceeded_not_matched(self):
+        """The old broad 'max_tokens_exceeded' pattern was removed.
+        Only 'input tokens exceed' should match now."""
+        err = Exception("max_tokens_exceeded")
+        assert _is_prompt_too_long(err) is False

autogpt_platform/backend/backend/copilot/sdk/response_adapter.py

@@ -226,7 +226,7 @@ class SDKResponseAdapter:
                 responses.append(StreamFinish())
 
         else:
-            logger.debug(f"Unhandled SDK message type: {type(sdk_message).__name__}")
+            logger.debug("Unhandled SDK message type: %s", type(sdk_message).__name__)
 
         return responses
 

autogpt_platform/backend/backend/copilot/sdk/security_hooks.py

@@ -52,7 +52,7 @@ def _validate_workspace_path(
     if is_allowed_local_path(path, sdk_cwd):
         return {}
 
-    logger.warning(f"Blocked {tool_name} outside workspace: {path}")
+    logger.warning("Blocked %s outside workspace: %s", tool_name, path)
     workspace_hint = f" Allowed workspace: {sdk_cwd}" if sdk_cwd else ""
     return _deny(
         f"[SECURITY] Tool '{tool_name}' can only access files within the workspace "
@@ -71,7 +71,7 @@ def _validate_tool_access(
     """
     # Block forbidden tools
     if tool_name in BLOCKED_TOOLS:
-        logger.warning(f"Blocked tool access attempt: {tool_name}")
+        logger.warning("Blocked tool access attempt: %s", tool_name)
         return _deny(
             f"[SECURITY] Tool '{tool_name}' is blocked for security. "
             "This is enforced by the platform and cannot be bypassed. "
@@ -89,7 +89,9 @@ def _validate_tool_access(
     for pattern in DANGEROUS_PATTERNS:
         if re.search(pattern, input_str, re.IGNORECASE):
             logger.warning(
-                f"Blocked dangerous pattern in tool input: {pattern} in {tool_name}"
+                "Blocked dangerous pattern in tool input: %s in %s",
+                pattern,
+                tool_name,
             )
             return _deny(
                 "[SECURITY] Input contains a blocked pattern. "
@@ -111,7 +113,9 @@ def _validate_user_isolation(
         # the tool itself via _validate_ephemeral_path.
         path = tool_input.get("path", "") or tool_input.get("file_path", "")
         if path and ".." in path:
-            logger.warning(f"Blocked path traversal attempt: {path} by user {user_id}")
+            logger.warning(
+                "Blocked path traversal attempt: %s by user %s", path, user_id
+            )
             return {
                 "hookSpecificOutput": {
                     "hookEventName": "PreToolUse",
@@ -170,7 +174,7 @@ def create_security_hooks(
                 # Block background task execution first — denied calls
                 # should not consume a subtask slot.
                 if tool_input.get("run_in_background"):
-                    logger.info(f"[SDK] Blocked background Task, user={user_id}")
+                    logger.info("[SDK] Blocked background Task, user=%s", user_id)
                     return cast(
                         SyncHookJSONOutput,
                         _deny(
@@ -181,7 +185,9 @@ def create_security_hooks(
                     )
                 if len(task_tool_use_ids) >= max_subtasks:
                     logger.warning(
-                        f"[SDK] Task limit reached ({max_subtasks}), user={user_id}"
+                        "[SDK] Task limit reached (%d), user=%s",
+                        max_subtasks,
+                        user_id,
                     )
                     return cast(
                         SyncHookJSONOutput,
@@ -212,7 +218,7 @@ def create_security_hooks(
             if tool_name == "Task" and tool_use_id is not None:
                 task_tool_use_ids.add(tool_use_id)
 
-            logger.debug(f"[SDK] Tool start: {tool_name}, user={user_id}")
+            logger.debug("[SDK] Tool start: %s, user=%s", tool_name, user_id)
             return cast(SyncHookJSONOutput, {})
 
         def _release_task_slot(tool_name: str, tool_use_id: str | None) -> None:
@@ -282,8 +288,11 @@ def create_security_hooks(
             tool_name = cast(str, input_data.get("tool_name", ""))
             error = input_data.get("error", "Unknown error")
             logger.warning(
-                f"[SDK] Tool failed: {tool_name}, error={error}, "
-                f"user={user_id}, tool_use_id={tool_use_id}"
+                "[SDK] Tool failed: %s, error=%s, user=%s, tool_use_id=%s",
+                tool_name,
+                str(error).replace("\n", "").replace("\r", ""),
+                user_id,
+                tool_use_id,
             )
 
             _release_task_slot(tool_name, tool_use_id)
@@ -301,16 +310,19 @@ def create_security_hooks(
             This hook provides visibility into when compaction happens.
             """
             _ = context, tool_use_id
-            trigger = input_data.get("trigger", "auto")
             # Sanitize untrusted input before logging to prevent log injection
+            trigger = (
+                str(input_data.get("trigger", "auto"))
+                .replace("\n", "")
+                .replace("\r", "")
+            )
             transcript_path = (
                 str(input_data.get("transcript_path", ""))
                 .replace("\n", "")
                 .replace("\r", "")
             )
             logger.info(
-                "[SDK] Context compaction triggered: %s, user=%s, "
-                "transcript_path=%s",
+                "[SDK] Context compaction triggered: %s, user=%s, transcript_path=%s",
                 trigger,
                 user_id,
                 transcript_path,

autogpt_platform/backend/backend/copilot/sdk/service_helpers_test.py

@@ -0,0 +1,283 @@
+"""Unit tests for extracted service helpers.
+
+Covers ``_is_prompt_too_long``, ``_reduce_context``, ``_iter_sdk_messages``,
+and the ``ReducedContext`` named tuple.
+"""
+
+from __future__ import annotations
+
+import asyncio
+from collections.abc import AsyncGenerator
+from unittest.mock import AsyncMock, patch
+
+import pytest
+
+from .conftest import build_test_transcript as _build_transcript
+from .service import (
+    ReducedContext,
+    _is_prompt_too_long,
+    _iter_sdk_messages,
+    _reduce_context,
+)
+
+# ---------------------------------------------------------------------------
+# _is_prompt_too_long
+# ---------------------------------------------------------------------------
+
+
+class TestIsPromptTooLong:
+    def test_direct_match(self) -> None:
+        assert _is_prompt_too_long(Exception("prompt is too long")) is True
+
+    def test_case_insensitive(self) -> None:
+        assert _is_prompt_too_long(Exception("PROMPT IS TOO LONG")) is True
+
+    def test_no_match(self) -> None:
+        assert _is_prompt_too_long(Exception("network timeout")) is False
+
+    def test_request_too_large(self) -> None:
+        assert _is_prompt_too_long(Exception("request too large for model")) is True
+
+    def test_context_length_exceeded(self) -> None:
+        assert _is_prompt_too_long(Exception("context_length_exceeded")) is True
+
+    def test_max_tokens_exceeded_not_matched(self) -> None:
+        """'max_tokens_exceeded' is intentionally excluded (too broad)."""
+        assert _is_prompt_too_long(Exception("max_tokens_exceeded")) is False
+
+    def test_max_tokens_config_error_no_match(self) -> None:
+        """'max_tokens must be at least 1' should NOT match."""
+        assert _is_prompt_too_long(Exception("max_tokens must be at least 1")) is False
+
+    def test_chained_cause(self) -> None:
+        inner = Exception("prompt is too long")
+        outer = RuntimeError("SDK error")
+        outer.__cause__ = inner
+        assert _is_prompt_too_long(outer) is True
+
+    def test_chained_context(self) -> None:
+        inner = Exception("request too large")
+        outer = RuntimeError("wrapped")
+        outer.__context__ = inner
+        assert _is_prompt_too_long(outer) is True
+
+    def test_deep_chain(self) -> None:
+        bottom = Exception("maximum context length")
+        middle = RuntimeError("middle")
+        middle.__cause__ = bottom
+        top = ValueError("top")
+        top.__cause__ = middle
+        assert _is_prompt_too_long(top) is True
+
+    def test_chain_no_match(self) -> None:
+        inner = Exception("rate limit exceeded")
+        outer = RuntimeError("wrapped")
+        outer.__cause__ = inner
+        assert _is_prompt_too_long(outer) is False
+
+    def test_cycle_detection(self) -> None:
+        """Exception chain with a cycle should not infinite-loop."""
+        a = Exception("error a")
+        b = Exception("error b")
+        a.__cause__ = b
+        b.__cause__ = a  # cycle
+        assert _is_prompt_too_long(a) is False
+
+    def test_all_patterns(self) -> None:
+        patterns = [
+            "prompt is too long",
+            "request too large",
+            "maximum context length",
+            "context_length_exceeded",
+            "input tokens exceed",
+            "input is too long",
+            "content length exceeds",
+        ]
+        for pattern in patterns:
+            assert _is_prompt_too_long(Exception(pattern)) is True, pattern
+
+
+# ---------------------------------------------------------------------------
+# _reduce_context
+# ---------------------------------------------------------------------------
+
+
+class TestReduceContext:
+    @pytest.mark.asyncio
+    async def test_first_retry_compaction_success(self) -> None:
+        transcript = _build_transcript([("user", "hi"), ("assistant", "hello")])
+        compacted = _build_transcript([("user", "hi"), ("assistant", "[summary]")])
+
+        with (
+            patch(
+                "backend.copilot.sdk.service.compact_transcript",
+                new_callable=AsyncMock,
+                return_value=compacted,
+            ),
+            patch(
+                "backend.copilot.sdk.service.validate_transcript",
+                return_value=True,
+            ),
+            patch(
+                "backend.copilot.sdk.service.write_transcript_to_tempfile",
+                return_value="/tmp/resume.jsonl",
+            ),
+        ):
+            ctx = await _reduce_context(
+                transcript, False, "sess-123", "/tmp/cwd", "[test]"
+            )
+
+        assert isinstance(ctx, ReducedContext)
+        assert ctx.use_resume is True
+        assert ctx.resume_file == "/tmp/resume.jsonl"
+        assert ctx.transcript_lost is False
+        assert ctx.tried_compaction is True
+
+    @pytest.mark.asyncio
+    async def test_compaction_fails_drops_transcript(self) -> None:
+        transcript = _build_transcript([("user", "hi"), ("assistant", "hello")])
+
+        with patch(
+            "backend.copilot.sdk.service.compact_transcript",
+            new_callable=AsyncMock,
+            return_value=None,
+        ):
+            ctx = await _reduce_context(
+                transcript, False, "sess-123", "/tmp/cwd", "[test]"
+            )
+
+        assert ctx.use_resume is False
+        assert ctx.resume_file is None
+        assert ctx.transcript_lost is True
+        assert ctx.tried_compaction is True
+
+    @pytest.mark.asyncio
+    async def test_already_tried_compaction_skips(self) -> None:
+        transcript = _build_transcript([("user", "hi"), ("assistant", "hello")])
+
+        ctx = await _reduce_context(transcript, True, "sess-123", "/tmp/cwd", "[test]")
+
+        assert ctx.use_resume is False
+        assert ctx.transcript_lost is True
+        assert ctx.tried_compaction is True
+
+    @pytest.mark.asyncio
+    async def test_empty_transcript_drops(self) -> None:
+        ctx = await _reduce_context("", False, "sess-123", "/tmp/cwd", "[test]")
+
+        assert ctx.use_resume is False
+        assert ctx.transcript_lost is True
+
+    @pytest.mark.asyncio
+    async def test_compaction_returns_same_content_drops(self) -> None:
+        transcript = _build_transcript([("user", "hi"), ("assistant", "hello")])
+
+        with patch(
+            "backend.copilot.sdk.service.compact_transcript",
+            new_callable=AsyncMock,
+            return_value=transcript,  # same content
+        ):
+            ctx = await _reduce_context(
+                transcript, False, "sess-123", "/tmp/cwd", "[test]"
+            )
+
+        assert ctx.transcript_lost is True
+
+    @pytest.mark.asyncio
+    async def test_write_tempfile_fails_drops(self) -> None:
+        transcript = _build_transcript([("user", "hi"), ("assistant", "hello")])
+        compacted = _build_transcript([("user", "hi"), ("assistant", "[summary]")])
+
+        with (
+            patch(
+                "backend.copilot.sdk.service.compact_transcript",
+                new_callable=AsyncMock,
+                return_value=compacted,
+            ),
+            patch(
+                "backend.copilot.sdk.service.validate_transcript",
+                return_value=True,
+            ),
+            patch(
+                "backend.copilot.sdk.service.write_transcript_to_tempfile",
+                return_value=None,
+            ),
+        ):
+            ctx = await _reduce_context(
+                transcript, False, "sess-123", "/tmp/cwd", "[test]"
+            )
+
+        assert ctx.transcript_lost is True
+
+
+# ---------------------------------------------------------------------------
+# _iter_sdk_messages
+# ---------------------------------------------------------------------------
+
+
+class TestIterSdkMessages:
+    @pytest.mark.asyncio
+    async def test_yields_messages(self) -> None:
+        messages = ["msg1", "msg2", "msg3"]
+        client = AsyncMock()
+
+        async def _fake_receive() -> AsyncGenerator[str]:
+            for m in messages:
+                yield m
+
+        client.receive_response = _fake_receive
+        result = [msg async for msg in _iter_sdk_messages(client)]
+        assert result == messages
+
+    @pytest.mark.asyncio
+    async def test_heartbeat_on_timeout(self) -> None:
+        """Yields None when asyncio.wait times out."""
+        client = AsyncMock()
+        received: list = []
+
+        async def _slow_receive() -> AsyncGenerator[str]:
+            await asyncio.sleep(100)  # never completes
+            yield "never"  # pragma: no cover — unreachable, yield makes this an async generator
+
+        client.receive_response = _slow_receive
+
+        with patch("backend.copilot.sdk.service._HEARTBEAT_INTERVAL", 0.01):
+            count = 0
+            async for msg in _iter_sdk_messages(client):
+                received.append(msg)
+                count += 1
+                if count >= 3:
+                    break
+
+        assert all(m is None for m in received)
+
+    @pytest.mark.asyncio
+    async def test_exception_propagates(self) -> None:
+        client = AsyncMock()
+
+        async def _error_receive() -> AsyncGenerator[str]:
+            raise RuntimeError("SDK crash")
+            yield  # pragma: no cover — unreachable, yield makes this an async generator
+
+        client.receive_response = _error_receive
+
+        with pytest.raises(RuntimeError, match="SDK crash"):
+            async for _ in _iter_sdk_messages(client):
+                pass
+
+    @pytest.mark.asyncio
+    async def test_task_cleanup_on_break(self) -> None:
+        """Pending task is cancelled when generator is closed."""
+        client = AsyncMock()
+
+        async def _slow_receive() -> AsyncGenerator[str]:
+            yield "first"
+            await asyncio.sleep(100)
+            yield "second"
+
+        client.receive_response = _slow_receive
+
+        gen = _iter_sdk_messages(client)
+        first = await gen.__anext__()
+        assert first == "first"
+        await gen.aclose()  # should cancel pending task cleanly

autogpt_platform/backend/backend/copilot/sdk/tool_adapter.py

@@ -234,7 +234,9 @@ def create_tool_handler(base_tool: BaseTool):
         try:
             return await _execute_tool_sync(base_tool, user_id, session, args)
         except Exception as e:
-            logger.error(f"Error executing tool {base_tool.name}: {e}", exc_info=True)
+            logger.error(
+                "Error executing tool %s: %s", base_tool.name, e, exc_info=True
+            )
             return _mcp_error(f"Failed to execute {base_tool.name}: {e}")
 
     return tool_handler

autogpt_platform/backend/backend/copilot/sdk/transcript.py

@@ -10,6 +10,9 @@ Storage is handled via ``WorkspaceStorageBackend`` (GCS in prod, local
 filesystem for self-hosted) — no DB column needed.
 """
 
+from __future__ import annotations
+
+import asyncio
 import logging
 import os
 import re
@@ -17,8 +20,12 @@ import shutil
 import time
 from dataclasses import dataclass
 from pathlib import Path
+from uuid import uuid4
 
 from backend.util import json
+from backend.util.clients import get_openai_client
+from backend.util.prompt import CompressResult, compress_context
+from backend.util.workspace_storage import GCSWorkspaceStorage, get_workspace_storage
 
 logger = logging.getLogger(__name__)
 
@@ -99,7 +106,14 @@ def strip_progress_entries(content: str) -> str:
             continue
         parent = entry.get("parentUuid", "")
         original_parent = parent
-        while parent in stripped_uuids:
+        # seen_parents is local per-entry (not shared across iterations) so
+        # it can only detect cycles within a single ancestry walk, not across
+        # entries.  This is intentional: each entry's parent chain is
+        # independent, and reusing a global set would incorrectly short-circuit
+        # valid re-use of the same UUID as a parent in different subtrees.
+        seen_parents: set[str] = set()
+        while parent in stripped_uuids and parent not in seen_parents:
+            seen_parents.add(parent)
             parent = uuid_to_parent.get(parent, "")
         if parent != original_parent:
             entry["parentUuid"] = parent
@@ -327,7 +341,7 @@ def write_transcript_to_tempfile(
     # Validate cwd is under the expected sandbox prefix (CodeQL sanitizer).
     real_cwd = os.path.realpath(cwd)
     if not real_cwd.startswith(_SAFE_CWD_PREFIX):
-        logger.warning(f"[Transcript] cwd outside sandbox: {cwd}")
+        logger.warning("[Transcript] cwd outside sandbox: %s", cwd)
         return None
 
     try:
@@ -337,17 +351,17 @@ def write_transcript_to_tempfile(
             os.path.join(real_cwd, f"transcript-{safe_id}.jsonl")
         )
         if not jsonl_path.startswith(real_cwd):
-            logger.warning(f"[Transcript] Path escaped cwd: {jsonl_path}")
+            logger.warning("[Transcript] Path escaped cwd: %s", jsonl_path)
             return None
 
         with open(jsonl_path, "w") as f:
             f.write(transcript_content)
 
-        logger.info(f"[Transcript] Wrote resume file: {jsonl_path}")
+        logger.info("[Transcript] Wrote resume file: %s", jsonl_path)
         return jsonl_path
 
     except OSError as e:
-        logger.warning(f"[Transcript] Failed to write resume file: {e}")
+        logger.warning("[Transcript] Failed to write resume file: %s", e)
         return None
 
 
@@ -408,8 +422,6 @@ def _meta_storage_path_parts(user_id: str, session_id: str) -> tuple[str, str, s
 
 def _build_path_from_parts(parts: tuple[str, str, str], backend: object) -> str:
     """Build a full storage path from (workspace_id, file_id, filename) parts."""
-    from backend.util.workspace_storage import GCSWorkspaceStorage
-
     wid, fid, fname = parts
     if isinstance(backend, GCSWorkspaceStorage):
         blob = f"workspaces/{wid}/{fid}/{fname}"
@@ -448,17 +460,15 @@ async def upload_transcript(
         content: Complete JSONL transcript (from TranscriptBuilder).
         message_count: ``len(session.messages)`` at upload time.
     """
-    from backend.util.workspace_storage import get_workspace_storage
-
     # Strip metadata entries (progress, file-history-snapshot, etc.)
     # Note: SDK-built transcripts shouldn't have these, but strip for safety
     stripped = strip_progress_entries(content)
     if not validate_transcript(stripped):
         # Log entry types for debugging — helps identify why validation failed
-        entry_types: list[str] = []
-        for line in stripped.strip().split("\n"):
-            entry = json.loads(line, fallback={"type": "INVALID_JSON"})
-            entry_types.append(entry.get("type", "?"))
+        entry_types = [
+            json.loads(line, fallback={"type": "INVALID_JSON"}).get("type", "?")
+            for line in stripped.strip().split("\n")
+        ]
         logger.warning(
             "%s Skipping upload — stripped content not valid "
             "(types=%s, stripped_len=%d, raw_len=%d)",
@@ -494,11 +504,14 @@ async def upload_transcript(
             content=json.dumps(meta).encode("utf-8"),
         )
     except Exception as e:
-        logger.warning(f"{log_prefix} Failed to write metadata: {e}")
+        logger.warning("%s Failed to write metadata: %s", log_prefix, e)
 
     logger.info(
-        f"{log_prefix} Uploaded {len(encoded)}B "
-        f"(stripped from {len(content)}B, msg_count={message_count})"
+        "%s Uploaded %dB (stripped from %dB, msg_count=%d)",
+        log_prefix,
+        len(encoded),
+        len(content),
+        message_count,
     )
 
 
@@ -512,8 +525,6 @@ async def download_transcript(
     Returns a ``TranscriptDownload`` with the JSONL content and the
     ``message_count`` watermark from the upload, or ``None`` if not found.
     """
-    from backend.util.workspace_storage import get_workspace_storage
-
     storage = await get_workspace_storage()
     path = _build_storage_path(user_id, session_id, storage)
 
@@ -521,10 +532,10 @@ async def download_transcript(
         data = await storage.retrieve(path)
         content = data.decode("utf-8")
     except FileNotFoundError:
-        logger.debug(f"{log_prefix} No transcript in storage")
+        logger.debug("%s No transcript in storage", log_prefix)
         return None
     except Exception as e:
-        logger.warning(f"{log_prefix} Failed to download transcript: {e}")
+        logger.warning("%s Failed to download transcript: %s", log_prefix, e)
         return None
 
     # Try to load metadata (best-effort — old transcripts won't have it)
@@ -536,10 +547,14 @@ async def download_transcript(
         meta = json.loads(meta_data.decode("utf-8"), fallback={})
         message_count = meta.get("message_count", 0)
         uploaded_at = meta.get("uploaded_at", 0.0)
-    except (FileNotFoundError, Exception):
+    except FileNotFoundError:
         pass  # No metadata — treat as unknown (msg_count=0 → always fill gap)
+    except Exception as e:
+        logger.debug("%s Failed to load transcript metadata: %s", log_prefix, e)
 
-    logger.info(f"{log_prefix} Downloaded {len(content)}B (msg_count={message_count})")
+    logger.info(
+        "%s Downloaded %dB (msg_count=%d)", log_prefix, len(content), message_count
+    )
     return TranscriptDownload(
         content=content,
         message_count=message_count,
@@ -553,8 +568,6 @@ async def delete_transcript(user_id: str, session_id: str) -> None:
     Removes both the ``.jsonl`` transcript and the companion ``.meta.json``
     so stale ``message_count`` watermarks cannot corrupt gap-fill logic.
     """
-    from backend.util.workspace_storage import get_workspace_storage
-
     storage = await get_workspace_storage()
     path = _build_storage_path(user_id, session_id, storage)
 
@@ -571,3 +584,280 @@ async def delete_transcript(user_id: str, session_id: str) -> None:
         logger.info("[Transcript] Deleted metadata for session %s", session_id)
     except Exception as e:
         logger.warning("[Transcript] Failed to delete metadata: %s", e)
+
+
+# ---------------------------------------------------------------------------
+# Transcript compaction — LLM summarization for prompt-too-long recovery
+# ---------------------------------------------------------------------------
+
+# JSONL protocol values used in transcript serialization.
+STOP_REASON_END_TURN = "end_turn"
+COMPACT_MSG_ID_PREFIX = "msg_compact_"
+ENTRY_TYPE_MESSAGE = "message"
+
+
+def _flatten_assistant_content(blocks: list) -> str:
+    """Flatten assistant content blocks into a single plain-text string.
+
+    Structured ``tool_use`` blocks are converted to ``[tool_use: name]``
+    placeholders.  This is intentional: ``compress_context`` requires plain
+    text for token counting and LLM summarization.  The structural loss is
+    acceptable because compaction only runs when the original transcript was
+    already too large for the model — a summarized plain-text version is
+    better than no context at all.
+    """
+    parts: list[str] = []
+    for block in blocks:
+        if isinstance(block, dict):
+            btype = block.get("type", "")
+            if btype == "text":
+                parts.append(block.get("text", ""))
+            elif btype == "tool_use":
+                parts.append(f"[tool_use: {block.get('name', '?')}]")
+            else:
+                # Preserve non-text blocks (e.g. image) as placeholders.
+                # Use __prefix__ to distinguish from literal user text.
+                parts.append(f"[__{btype}__]")
+        elif isinstance(block, str):
+            parts.append(block)
+    return "\n".join(parts) if parts else ""
+
+
+def _flatten_tool_result_content(blocks: list) -> str:
+    """Flatten tool_result and other content blocks into plain text.
+
+    Handles nested tool_result structures, text blocks, and raw strings.
+    Uses ``json.dumps`` as fallback for dict blocks without a ``text`` key
+    or where ``text`` is ``None``.
+
+    Like ``_flatten_assistant_content``, structured blocks (images, nested
+    tool results) are reduced to text representations for compression.
+    """
+    str_parts: list[str] = []
+    for block in blocks:
+        if isinstance(block, dict) and block.get("type") == "tool_result":
+            inner = block.get("content") or ""
+            if isinstance(inner, list):
+                for sub in inner:
+                    if isinstance(sub, dict):
+                        sub_type = sub.get("type")
+                        if sub_type in ("image", "document"):
+                            # Avoid serializing base64 binary data into
+                            # the compaction input — use a placeholder.
+                            str_parts.append(f"[__{sub_type}__]")
+                        elif sub_type == "text" or sub.get("text") is not None:
+                            str_parts.append(str(sub.get("text", "")))
+                        else:
+                            str_parts.append(json.dumps(sub))
+                    else:
+                        str_parts.append(str(sub))
+            else:
+                str_parts.append(str(inner))
+        elif isinstance(block, dict) and block.get("type") == "text":
+            str_parts.append(str(block.get("text", "")))
+        elif isinstance(block, dict):
+            # Preserve non-text/non-tool_result blocks (e.g. image) as placeholders.
+            # Use __prefix__ to distinguish from literal user text.
+            btype = block.get("type", "unknown")
+            str_parts.append(f"[__{btype}__]")
+        elif isinstance(block, str):
+            str_parts.append(block)
+    return "\n".join(str_parts) if str_parts else ""
+
+
+def _transcript_to_messages(content: str) -> list[dict]:
+    """Convert JSONL transcript entries to plain message dicts for compression.
+
+    Parses each line of the JSONL *content*, skips strippable metadata entries
+    (progress, file-history-snapshot, etc.), and extracts the ``role`` and
+    flattened ``content`` from the ``message`` field of each remaining entry.
+
+    Structured content blocks (``tool_use``, ``tool_result``, images) are
+    flattened to plain text via ``_flatten_assistant_content`` and
+    ``_flatten_tool_result_content`` so that ``compress_context`` can
+    perform token counting and LLM summarization on uniform strings.
+
+    Returns:
+        A list of ``{"role": str, "content": str}`` dicts suitable for
+        ``compress_context``.
+    """
+    messages: list[dict] = []
+    for line in content.strip().split("\n"):
+        if not line.strip():
+            continue
+        entry = json.loads(line, fallback=None)
+        if not isinstance(entry, dict):
+            continue
+        if entry.get("type", "") in STRIPPABLE_TYPES and not entry.get(
+            "isCompactSummary"
+        ):
+            continue
+        msg = entry.get("message", {})
+        role = msg.get("role", "")
+        if not role:
+            continue
+        msg_dict: dict = {"role": role}
+        raw_content = msg.get("content")
+        if role == "assistant" and isinstance(raw_content, list):
+            msg_dict["content"] = _flatten_assistant_content(raw_content)
+        elif isinstance(raw_content, list):
+            msg_dict["content"] = _flatten_tool_result_content(raw_content)
+        else:
+            msg_dict["content"] = raw_content or ""
+        messages.append(msg_dict)
+    return messages
+
+
+def _messages_to_transcript(messages: list[dict]) -> str:
+    """Convert compressed message dicts back to JSONL transcript format.
+
+    Rebuilds a minimal JSONL transcript from the ``{"role", "content"}``
+    dicts returned by ``compress_context``.  Each message becomes one JSONL
+    line with a fresh ``uuid`` / ``parentUuid`` chain so the CLI's
+    ``--resume`` flag can reconstruct a valid conversation tree.
+
+    Assistant messages are wrapped in the full ``message`` envelope
+    (``id``, ``model``, ``stop_reason``, structured ``content`` blocks)
+    that the CLI expects.  User messages use the simpler ``{role, content}``
+    form.
+
+    Returns:
+        A newline-terminated JSONL string, or an empty string if *messages*
+        is empty.
+    """
+    lines: list[str] = []
+    last_uuid: str = ""  # root entry uses empty string, not null
+    for msg in messages:
+        role = msg.get("role", "user")
+        entry_type = "assistant" if role == "assistant" else "user"
+        uid = str(uuid4())
+        content = msg.get("content", "")
+        if role == "assistant":
+            message: dict = {
+                "role": "assistant",
+                "model": "",
+                "id": f"{COMPACT_MSG_ID_PREFIX}{uuid4().hex[:24]}",
+                "type": ENTRY_TYPE_MESSAGE,
+                "content": [{"type": "text", "text": content}] if content else [],
+                "stop_reason": STOP_REASON_END_TURN,
+                "stop_sequence": None,
+            }
+        else:
+            message = {"role": role, "content": content}
+        entry = {
+            "type": entry_type,
+            "uuid": uid,
+            "parentUuid": last_uuid,
+            "message": message,
+        }
+        lines.append(json.dumps(entry, separators=(",", ":")))
+        last_uuid = uid
+    return "\n".join(lines) + "\n" if lines else ""
+
+
+_COMPACTION_TIMEOUT_SECONDS = 60
+_TRUNCATION_TIMEOUT_SECONDS = 30
+
+
+async def _run_compression(
+    messages: list[dict],
+    model: str,
+    log_prefix: str,
+) -> CompressResult:
+    """Run LLM-based compression with truncation fallback.
+
+    Uses the shared OpenAI client from ``get_openai_client()``.
+    If no client is configured or the LLM call fails, falls back to
+    truncation-based compression which drops older messages without
+    summarization.
+
+    A 60-second timeout prevents a hung LLM call from blocking the
+    retry path indefinitely.  The truncation fallback also has a
+    30-second timeout to guard against slow tokenization on very large
+    transcripts.
+    """
+    client = get_openai_client()
+    if client is None:
+        logger.warning("%s No OpenAI client configured, using truncation", log_prefix)
+        return await asyncio.wait_for(
+            compress_context(messages=messages, model=model, client=None),
+            timeout=_TRUNCATION_TIMEOUT_SECONDS,
+        )
+    try:
+        return await asyncio.wait_for(
+            compress_context(messages=messages, model=model, client=client),
+            timeout=_COMPACTION_TIMEOUT_SECONDS,
+        )
+    except Exception as e:
+        logger.warning("%s LLM compaction failed, using truncation: %s", log_prefix, e)
+        return await asyncio.wait_for(
+            compress_context(messages=messages, model=model, client=None),
+            timeout=_TRUNCATION_TIMEOUT_SECONDS,
+        )
+
+
+async def compact_transcript(
+    content: str,
+    *,
+    model: str,
+    log_prefix: str = "[Transcript]",
+) -> str | None:
+    """Compact an oversized JSONL transcript using LLM summarization.
+
+    Converts transcript entries to plain messages, runs ``compress_context``
+    (the same compressor used for pre-query history), and rebuilds JSONL.
+
+    Structured content (``tool_use`` blocks, ``tool_result`` nesting, images)
+    is flattened to plain text for compression.  This matches the fidelity of
+    the Plan C (DB compression) fallback path, where
+    ``_format_conversation_context`` similarly renders tool calls as
+    ``You called tool: name(args)`` and results as ``Tool result: ...``.
+    Neither path preserves structured API content blocks — the compacted
+    context serves as text history for the LLM, which creates proper
+    structured tool calls going forward.
+
+    Images are per-turn attachments loaded from workspace storage by file ID
+    (via ``_prepare_file_attachments``), not part of the conversation history.
+    They are re-attached each turn and are unaffected by compaction.
+
+    Returns the compacted JSONL string, or ``None`` on failure.
+
+    See also:
+        ``_compress_messages`` in ``service.py`` — compresses ``ChatMessage``
+        lists for pre-query DB history.  Both share ``compress_context()``
+        but operate on different input formats (JSONL transcript entries
+        here vs. ChatMessage dicts there).
+    """
+    messages = _transcript_to_messages(content)
+    if len(messages) < 2:
+        logger.warning("%s Too few messages to compact (%d)", log_prefix, len(messages))
+        return None
+    try:
+        result = await _run_compression(messages, model, log_prefix)
+        if not result.was_compacted:
+            # Compressor says it's within budget, but the SDK rejected it.
+            # Return None so the caller falls through to DB fallback.
+            logger.warning(
+                "%s Compressor reports within budget but SDK rejected — "
+                "signalling failure",
+                log_prefix,
+            )
+            return None
+        logger.info(
+            "%s Compacted transcript: %d->%d tokens (%d summarized, %d dropped)",
+            log_prefix,
+            result.original_token_count,
+            result.token_count,
+            result.messages_summarized,
+            result.messages_dropped,
+        )
+        compacted = _messages_to_transcript(result.messages)
+        if not validate_transcript(compacted):
+            logger.warning("%s Compacted transcript failed validation", log_prefix)
+            return None
+        return compacted
+    except Exception as e:
+        logger.error(
+            "%s Transcript compaction failed: %s", log_prefix, e, exc_info=True
+        )
+        return None

autogpt_platform/backend/backend/copilot/sdk/transcript_builder.py

@@ -68,7 +68,7 @@ class TranscriptBuilder:
             type=entry_type,
             uuid=data.get("uuid") or str(uuid4()),
             parentUuid=data.get("parentUuid"),
-            isCompactSummary=data.get("isCompactSummary") or None,
+            isCompactSummary=data.get("isCompactSummary"),
             message=data.get("message", {}),
         )
 

autogpt_platform/backend/backend/copilot/sdk/transcript_test.py

@@ -1,7 +1,7 @@
 """Unit tests for JSONL transcript management utilities."""
 
 import os
-from unittest.mock import AsyncMock, patch
+from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 
@@ -382,7 +382,7 @@ class TestDeleteTranscript:
         mock_storage.delete = AsyncMock()
 
         with patch(
-            "backend.util.workspace_storage.get_workspace_storage",
+            "backend.copilot.sdk.transcript.get_workspace_storage",
             new_callable=AsyncMock,
             return_value=mock_storage,
         ):
@@ -402,7 +402,7 @@ class TestDeleteTranscript:
         )
 
         with patch(
-            "backend.util.workspace_storage.get_workspace_storage",
+            "backend.copilot.sdk.transcript.get_workspace_storage",
             new_callable=AsyncMock,
             return_value=mock_storage,
         ):
@@ -420,7 +420,7 @@ class TestDeleteTranscript:
         )
 
         with patch(
-            "backend.util.workspace_storage.get_workspace_storage",
+            "backend.copilot.sdk.transcript.get_workspace_storage",
             new_callable=AsyncMock,
             return_value=mock_storage,
         ):
@@ -897,3 +897,134 @@ class TestCompactionFlowIntegration:
         output2 = builder2.to_jsonl()
         lines2 = [json.loads(line) for line in output2.strip().split("\n")]
         assert lines2[-1]["parentUuid"] == "a2"
+
+
+# ---------------------------------------------------------------------------
+# _run_compression (direct tests for the 3 code paths)
+# ---------------------------------------------------------------------------
+
+
+class TestRunCompression:
+    """Direct tests for ``_run_compression`` covering all 3 code paths.
+
+    Paths:
+    (a) No OpenAI client configured → truncation fallback immediately.
+    (b) LLM success → returns LLM-compressed result.
+    (c) LLM call raises → truncation fallback.
+    """
+
+    def _make_compress_result(self, was_compacted: bool, msgs=None):
+        """Build a minimal CompressResult-like object."""
+        from types import SimpleNamespace
+
+        return SimpleNamespace(
+            was_compacted=was_compacted,
+            messages=msgs or [{"role": "user", "content": "summary"}],
+            original_token_count=500,
+            token_count=100 if was_compacted else 500,
+            messages_summarized=2 if was_compacted else 0,
+            messages_dropped=0,
+        )
+
+    @pytest.mark.asyncio
+    async def test_no_client_uses_truncation(self):
+        """Path (a): ``get_openai_client()`` returns None → truncation only."""
+        from .transcript import _run_compression
+
+        truncation_result = self._make_compress_result(
+            True, [{"role": "user", "content": "truncated"}]
+        )
+
+        with (
+            patch(
+                "backend.copilot.sdk.transcript.get_openai_client",
+                return_value=None,
+            ),
+            patch(
+                "backend.copilot.sdk.transcript.compress_context",
+                new_callable=AsyncMock,
+                return_value=truncation_result,
+            ) as mock_compress,
+        ):
+            result = await _run_compression(
+                [{"role": "user", "content": "hello"}],
+                model="test-model",
+                log_prefix="[test]",
+            )
+
+        # compress_context called with client=None (truncation mode)
+        call_kwargs = mock_compress.call_args
+        assert (
+            call_kwargs.kwargs.get("client") is None
+            or (call_kwargs.args and call_kwargs.args[2] is None)
+            or mock_compress.call_args[1].get("client") is None
+        )
+        assert result is truncation_result
+
+    @pytest.mark.asyncio
+    async def test_llm_success_returns_llm_result(self):
+        """Path (b): ``get_openai_client()`` returns a client → LLM compresses."""
+        from .transcript import _run_compression
+
+        llm_result = self._make_compress_result(
+            True, [{"role": "user", "content": "LLM summary"}]
+        )
+        mock_client = MagicMock()
+
+        with (
+            patch(
+                "backend.copilot.sdk.transcript.get_openai_client",
+                return_value=mock_client,
+            ),
+            patch(
+                "backend.copilot.sdk.transcript.compress_context",
+                new_callable=AsyncMock,
+                return_value=llm_result,
+            ) as mock_compress,
+        ):
+            result = await _run_compression(
+                [{"role": "user", "content": "long conversation"}],
+                model="test-model",
+                log_prefix="[test]",
+            )
+
+        # compress_context called with the real client
+        assert mock_compress.called
+        assert result is llm_result
+
+    @pytest.mark.asyncio
+    async def test_llm_failure_falls_back_to_truncation(self):
+        """Path (c): LLM call raises → truncation fallback used instead."""
+        from .transcript import _run_compression
+
+        truncation_result = self._make_compress_result(
+            True, [{"role": "user", "content": "truncated fallback"}]
+        )
+        mock_client = MagicMock()
+        call_count = [0]
+
+        async def _compress_side_effect(**kwargs):
+            call_count[0] += 1
+            if kwargs.get("client") is not None:
+                raise RuntimeError("LLM timeout")
+            return truncation_result
+
+        with (
+            patch(
+                "backend.copilot.sdk.transcript.get_openai_client",
+                return_value=mock_client,
+            ),
+            patch(
+                "backend.copilot.sdk.transcript.compress_context",
+                side_effect=_compress_side_effect,
+            ),
+        ):
+            result = await _run_compression(
+                [{"role": "user", "content": "long conversation"}],
+                model="test-model",
+                log_prefix="[test]",
+            )
+
+        # compress_context called twice: once for LLM (raises), once for truncation
+        assert call_count[0] == 2
+        assert result is truncation_result

autogpt_platform/backend/backend/copilot/service.py

@@ -28,24 +28,10 @@ logger = logging.getLogger(__name__)
 
 config = ChatConfig()
 settings = Settings()
-
-_client: LangfuseAsyncOpenAI | None = None
-_langfuse = None
+client = LangfuseAsyncOpenAI(api_key=config.api_key, base_url=config.base_url)
 
 
-def _get_openai_client() -> LangfuseAsyncOpenAI:
-    global _client
-    if _client is None:
-        _client = LangfuseAsyncOpenAI(api_key=config.api_key, base_url=config.base_url)
-    return _client
-
-
-def _get_langfuse():
-    global _langfuse
-    if _langfuse is None:
-        _langfuse = get_client()
-    return _langfuse
-
+langfuse = get_client()
 
 # Default system prompt used when Langfuse is not configured
 # Provides minimal baseline tone and personality - all workflow, tools, and
@@ -98,7 +84,7 @@ async def _get_system_prompt_template(context: str) -> str:
                 else "latest"
             )
             prompt = await asyncio.to_thread(
-                _get_langfuse().get_prompt,
+                langfuse.get_prompt,
                 config.langfuse_prompt_name,
                 label=label,
                 cache_ttl_seconds=config.langfuse_prompt_cache_ttl,
@@ -172,7 +158,7 @@ async def _generate_session_title(
             "environment": settings.config.app_env.value,
         }
 
-        response = await _get_openai_client().chat.completions.create(
+        response = await client.chat.completions.create(
             model=config.title_model,
             messages=[
                 {

autogpt_platform/backend/backend/copilot/token_tracking.py

@@ -1,93 +0,0 @@
-"""Shared token-usage persistence and rate-limit recording.
-
-Both the baseline (OpenRouter) and SDK (Anthropic) service layers need to:
-  1. Append a ``Usage`` record to the session.
-  2. Log the turn's token counts.
-  3. Record weighted usage in Redis for rate-limiting.
-
-This module extracts that common logic so both paths stay in sync.
-"""
-
-import logging
-
-from .model import ChatSession, Usage
-from .rate_limit import record_token_usage
-
-logger = logging.getLogger(__name__)
-
-
-async def persist_and_record_usage(
-    *,
-    session: ChatSession | None,
-    user_id: str | None,
-    prompt_tokens: int,
-    completion_tokens: int,
-    cache_read_tokens: int = 0,
-    cache_creation_tokens: int = 0,
-    log_prefix: str = "",
-    cost_usd: float | str | None = None,
-) -> int:
-    """Persist token usage to session and record for rate limiting.
-
-    Args:
-        session: The chat session to append usage to (may be None on error).
-        user_id: User ID for rate-limit counters (skipped if None).
-        prompt_tokens: Uncached input tokens.
-        completion_tokens: Output tokens.
-        cache_read_tokens: Tokens served from prompt cache (Anthropic only).
-        cache_creation_tokens: Tokens written to prompt cache (Anthropic only).
-        log_prefix: Prefix for log messages (e.g. "[SDK]", "[Baseline]").
-        cost_usd: Optional cost for logging (float from SDK, str otherwise).
-
-    Returns:
-        The computed total_tokens (prompt + completion; cache excluded).
-    """
-    prompt_tokens = max(0, prompt_tokens)
-    completion_tokens = max(0, completion_tokens)
-    cache_read_tokens = max(0, cache_read_tokens)
-    cache_creation_tokens = max(0, cache_creation_tokens)
-
-    if prompt_tokens <= 0 and completion_tokens <= 0:
-        return 0
-
-    # total_tokens = prompt + completion. Cache tokens are tracked
-    # separately and excluded from total so both baseline and SDK
-    # paths share the same semantics.
-    total_tokens = prompt_tokens + completion_tokens
-
-    if session is not None:
-        session.usage.append(
-            Usage(
-                prompt_tokens=prompt_tokens,
-                completion_tokens=completion_tokens,
-                total_tokens=total_tokens,
-                cache_read_tokens=cache_read_tokens,
-                cache_creation_tokens=cache_creation_tokens,
-            )
-        )
-
-    if cache_read_tokens or cache_creation_tokens:
-        logger.info(
-            f"{log_prefix} Turn usage: uncached={prompt_tokens}, "
-            f"cache_read={cache_read_tokens}, cache_create={cache_creation_tokens}, "
-            f"output={completion_tokens}, total={total_tokens}, cost_usd={cost_usd}"
-        )
-    else:
-        logger.info(
-            f"{log_prefix} Turn usage: prompt={prompt_tokens}, "
-            f"completion={completion_tokens}, total={total_tokens}"
-        )
-
-    if user_id:
-        try:
-            await record_token_usage(
-                user_id=user_id,
-                prompt_tokens=prompt_tokens,
-                completion_tokens=completion_tokens,
-                cache_read_tokens=cache_read_tokens,
-                cache_creation_tokens=cache_creation_tokens,
-            )
-        except Exception as usage_err:
-            logger.warning(f"{log_prefix} Failed to record token usage: {usage_err}")
-
-    return total_tokens

autogpt_platform/backend/backend/copilot/token_tracking_test.py

@@ -1,281 +0,0 @@
-"""Unit tests for token_tracking.persist_and_record_usage.
-
-Covers both the baseline (prompt+completion only) and SDK (with cache breakdown)
-calling conventions, session persistence, and rate-limit recording.
-"""
-
-from datetime import UTC, datetime
-from unittest.mock import AsyncMock, patch
-
-import pytest
-
-from .model import ChatSession, Usage
-from .token_tracking import persist_and_record_usage
-
-
-def _make_session() -> ChatSession:
-    """Return a minimal in-memory ChatSession for testing."""
-    return ChatSession(
-        session_id="sess-test",
-        user_id="user-test",
-        title=None,
-        messages=[],
-        usage=[],
-        started_at=datetime.now(UTC),
-        updated_at=datetime.now(UTC),
-    )
-
-
-# ---------------------------------------------------------------------------
-# Return value / total_tokens semantics
-# ---------------------------------------------------------------------------
-
-
-class TestTotalTokens:
-    @pytest.mark.asyncio
-    async def test_returns_prompt_plus_completion(self):
-        """total_tokens = prompt + completion (cache excluded from total)."""
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new_callable=AsyncMock,
-        ):
-            total = await persist_and_record_usage(
-                session=None,
-                user_id=None,
-                prompt_tokens=300,
-                completion_tokens=200,
-            )
-        assert total == 500
-
-    @pytest.mark.asyncio
-    async def test_returns_zero_when_no_tokens(self):
-        """Returns 0 early when both prompt and completion are zero."""
-        total = await persist_and_record_usage(
-            session=None,
-            user_id=None,
-            prompt_tokens=0,
-            completion_tokens=0,
-        )
-        assert total == 0
-
-    @pytest.mark.asyncio
-    async def test_cache_tokens_excluded_from_total(self):
-        """Cache tokens are stored separately and not added to total_tokens."""
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new_callable=AsyncMock,
-        ):
-            total = await persist_and_record_usage(
-                session=None,
-                user_id=None,
-                prompt_tokens=100,
-                completion_tokens=50,
-                cache_read_tokens=5000,
-                cache_creation_tokens=200,
-            )
-        # total = prompt + completion only (5000 + 200 cache excluded)
-        assert total == 150
-
-    @pytest.mark.asyncio
-    async def test_baseline_path_no_cache(self):
-        """Baseline (OpenRouter) path passes no cache tokens; total = prompt + completion."""
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new_callable=AsyncMock,
-        ):
-            total = await persist_and_record_usage(
-                session=None,
-                user_id="u1",
-                prompt_tokens=1000,
-                completion_tokens=400,
-                log_prefix="[Baseline]",
-            )
-        assert total == 1400
-
-    @pytest.mark.asyncio
-    async def test_sdk_path_with_cache(self):
-        """SDK (Anthropic) path passes cache tokens; total still = prompt + completion."""
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new_callable=AsyncMock,
-        ):
-            total = await persist_and_record_usage(
-                session=None,
-                user_id="u2",
-                prompt_tokens=200,
-                completion_tokens=100,
-                cache_read_tokens=8000,
-                cache_creation_tokens=400,
-                log_prefix="[SDK]",
-                cost_usd=0.0015,
-            )
-        assert total == 300
-
-
-# ---------------------------------------------------------------------------
-# Session persistence
-# ---------------------------------------------------------------------------
-
-
-class TestSessionPersistence:
-    @pytest.mark.asyncio
-    async def test_appends_usage_to_session(self):
-        session = _make_session()
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new_callable=AsyncMock,
-        ):
-            await persist_and_record_usage(
-                session=session,
-                user_id=None,
-                prompt_tokens=100,
-                completion_tokens=50,
-            )
-        assert len(session.usage) == 1
-        usage: Usage = session.usage[0]
-        assert usage.prompt_tokens == 100
-        assert usage.completion_tokens == 50
-        assert usage.total_tokens == 150
-        assert usage.cache_read_tokens == 0
-        assert usage.cache_creation_tokens == 0
-
-    @pytest.mark.asyncio
-    async def test_appends_cache_breakdown_to_session(self):
-        session = _make_session()
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new_callable=AsyncMock,
-        ):
-            await persist_and_record_usage(
-                session=session,
-                user_id=None,
-                prompt_tokens=200,
-                completion_tokens=80,
-                cache_read_tokens=3000,
-                cache_creation_tokens=500,
-            )
-        usage: Usage = session.usage[0]
-        assert usage.cache_read_tokens == 3000
-        assert usage.cache_creation_tokens == 500
-
-    @pytest.mark.asyncio
-    async def test_multiple_turns_append_multiple_records(self):
-        session = _make_session()
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new_callable=AsyncMock,
-        ):
-            await persist_and_record_usage(
-                session=session, user_id=None, prompt_tokens=100, completion_tokens=50
-            )
-            await persist_and_record_usage(
-                session=session, user_id=None, prompt_tokens=200, completion_tokens=70
-            )
-        assert len(session.usage) == 2
-
-    @pytest.mark.asyncio
-    async def test_none_session_does_not_raise(self):
-        """When session is None (e.g. error path), no exception should be raised."""
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new_callable=AsyncMock,
-        ):
-            total = await persist_and_record_usage(
-                session=None,
-                user_id=None,
-                prompt_tokens=100,
-                completion_tokens=50,
-            )
-        assert total == 150
-
-    @pytest.mark.asyncio
-    async def test_no_append_when_zero_tokens(self):
-        """When tokens are zero, function returns early — session unchanged."""
-        session = _make_session()
-        total = await persist_and_record_usage(
-            session=session,
-            user_id=None,
-            prompt_tokens=0,
-            completion_tokens=0,
-        )
-        assert total == 0
-        assert len(session.usage) == 0
-
-
-# ---------------------------------------------------------------------------
-# Rate-limit recording
-# ---------------------------------------------------------------------------
-
-
-class TestRateLimitRecording:
-    @pytest.mark.asyncio
-    async def test_calls_record_token_usage_when_user_id_present(self):
-        mock_record = AsyncMock()
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new=mock_record,
-        ):
-            await persist_and_record_usage(
-                session=None,
-                user_id="user-abc",
-                prompt_tokens=100,
-                completion_tokens=50,
-                cache_read_tokens=1000,
-                cache_creation_tokens=200,
-            )
-        mock_record.assert_awaited_once_with(
-            user_id="user-abc",
-            prompt_tokens=100,
-            completion_tokens=50,
-            cache_read_tokens=1000,
-            cache_creation_tokens=200,
-        )
-
-    @pytest.mark.asyncio
-    async def test_skips_record_when_user_id_is_none(self):
-        """Anonymous sessions should not create Redis keys."""
-        mock_record = AsyncMock()
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new=mock_record,
-        ):
-            await persist_and_record_usage(
-                session=None,
-                user_id=None,
-                prompt_tokens=100,
-                completion_tokens=50,
-            )
-        mock_record.assert_not_awaited()
-
-    @pytest.mark.asyncio
-    async def test_record_failure_does_not_raise(self):
-        """A Redis error in record_token_usage should be swallowed (fail-open)."""
-        mock_record = AsyncMock(side_effect=ConnectionError("Redis down"))
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new=mock_record,
-        ):
-            # Should not raise
-            total = await persist_and_record_usage(
-                session=None,
-                user_id="user-xyz",
-                prompt_tokens=100,
-                completion_tokens=50,
-            )
-        assert total == 150
-
-    @pytest.mark.asyncio
-    async def test_skips_record_when_zero_tokens(self):
-        """Returns 0 before calling record_token_usage when tokens are zero."""
-        mock_record = AsyncMock()
-        with patch(
-            "backend.copilot.token_tracking.record_token_usage",
-            new=mock_record,
-        ):
-            await persist_and_record_usage(
-                session=None,
-                user_id="user-abc",
-                prompt_tokens=0,
-                completion_tokens=0,
-            )
-        mock_record.assert_not_awaited()

autogpt_platform/backend/backend/copilot/tools/e2b_sandbox.py

@@ -41,8 +41,7 @@ import contextlib
 import logging
 from typing import Any, Awaitable, Callable, Literal
 
-from e2b import AsyncSandbox
-from e2b.sandbox.sandbox_api import SandboxLifecycle
+from e2b import AsyncSandbox, SandboxLifecycle
 
 from backend.data.redis_client import get_redis_async
 

autogpt_platform/backend/backend/copilot/tools/helpers.py

@@ -8,13 +8,11 @@ from pydantic_core import PydanticUndefined
 
 from backend.blocks._base import AnyBlockSchema
 from backend.copilot.constants import COPILOT_NODE_PREFIX, COPILOT_SESSION_PREFIX
-from backend.data.credit import UsageTransactionMetadata
-from backend.data.db_accessors import credit_db, workspace_db
+from backend.data.db_accessors import workspace_db
 from backend.data.execution import ExecutionContext
 from backend.data.model import CredentialsFieldInfo, CredentialsMetaInput
-from backend.executor.utils import block_usage_cost
 from backend.integrations.creds_manager import IntegrationCredentialsManager
-from backend.util.exceptions import BlockError, InsufficientBalanceError
+from backend.util.exceptions import BlockError
 from backend.util.type import coerce_inputs_to_schema
 
 from .models import BlockOutputResponse, ErrorResponse, ToolResponseBase
@@ -117,21 +115,6 @@ async def execute_block(
         # Coerce non-matching data types to the expected input schema.
         coerce_inputs_to_schema(input_data, block.input_schema)
 
-        # Pre-execution credit check (courtesy; spend_credits is atomic)
-        cost, cost_filter = block_usage_cost(block, input_data)
-        has_cost = cost > 0
-        _credit_db = credit_db()
-        if has_cost:
-            balance = await _credit_db.get_credits(user_id)
-            if balance < cost:
-                return ErrorResponse(
-                    message=(
-                        f"Insufficient credits to run '{block.name}'. "
-                        "Please top up your credits to continue."
-                    ),
-                    session_id=session_id,
-                )
-
         # Execute the block and collect outputs
         outputs: dict[str, list[Any]] = defaultdict(list)
         async for output_name, output_data in block.execute(
@@ -140,51 +123,6 @@ async def execute_block(
         ):
             outputs[output_name].append(output_data)
 
-        # Charge credits for block execution
-        if has_cost:
-            try:
-                await _credit_db.spend_credits(
-                    user_id=user_id,
-                    cost=cost,
-                    metadata=UsageTransactionMetadata(
-                        graph_exec_id=synthetic_graph_id,
-                        graph_id=synthetic_graph_id,
-                        node_id=synthetic_node_id,
-                        node_exec_id=node_exec_id,
-                        block_id=block_id,
-                        block=block.name,
-                        input=cost_filter,
-                        reason="copilot_block_execution",
-                    ),
-                )
-            except Exception as e:
-                # Block already executed (with possible side effects). Never
-                # return ErrorResponse here — the user received output and
-                # deserves it. Log the billing failure for reconciliation.
-                leak_type = (
-                    "INSUFFICIENT_BALANCE"
-                    if isinstance(e, InsufficientBalanceError)
-                    else "UNEXPECTED_ERROR"
-                )
-                logger.error(
-                    "BILLING_LEAK[%s]: block executed but credit charge failed — "
-                    "user_id=%s, block_id=%s, node_exec_id=%s, cost=%s: %s",
-                    leak_type,
-                    user_id,
-                    block_id,
-                    node_exec_id,
-                    cost,
-                    e,
-                    extra={
-                        "json_fields": {
-                            "billing_leak": True,
-                            "leak_type": leak_type,
-                            "user_id": user_id,
-                            "cost": str(cost),
-                        }
-                    },
-                )
-
         return BlockOutputResponse(
             message=f"Block '{block.name}' executed successfully",
             block_id=block_id,
@@ -195,14 +133,14 @@ async def execute_block(
         )
 
     except BlockError as e:
-        logger.warning("Block execution failed: %s", e)
+        logger.warning(f"Block execution failed: {e}")
         return ErrorResponse(
             message=f"Block execution failed: {e}",
             error=str(e),
             session_id=session_id,
         )
     except Exception as e:
-        logger.error("Unexpected error executing block: %s", e, exc_info=True)
+        logger.error(f"Unexpected error executing block: {e}", exc_info=True)
         return ErrorResponse(
             message=f"Failed to execute block: {str(e)}",
             error=str(e),

autogpt_platform/backend/backend/copilot/tools/helpers_test.py

@@ -1,197 +1,18 @@
-"""Tests for execute_block — credit charging and type coercion."""
+"""Tests for execute_block type coercion in helpers.py.
+
+Verifies that execute_block() coerces string input values to match the block's
+expected input types, mirroring the executor's validate_exec() logic.
+This is critical for @@agptfile: expansion, where file content is always a string
+but the block may expect structured types (e.g. list[list[str]]).
+"""
 
-from collections.abc import AsyncIterator
 from typing import Any
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 
-from backend.blocks._base import BlockType
 from backend.copilot.tools.helpers import execute_block
-from backend.copilot.tools.models import BlockOutputResponse, ErrorResponse
-
-_USER = "test-user-helpers"
-_SESSION = "test-session-helpers"
-
-
-def _make_block(block_id: str = "block-1", name: str = "TestBlock"):
-    """Create a minimal mock block for execute_block()."""
-    mock = MagicMock()
-    mock.id = block_id
-    mock.name = name
-    mock.block_type = BlockType.STANDARD
-
-    mock.input_schema = MagicMock()
-    mock.input_schema.get_credentials_fields_info.return_value = {}
-
-    async def _execute(
-        input_data: dict, **kwargs: Any
-    ) -> AsyncIterator[tuple[str, Any]]:
-        yield "result", "ok"
-
-    mock.execute = _execute
-    return mock
-
-
-def _patch_workspace():
-    """Patch workspace_db to return a mock workspace."""
-    mock_workspace = MagicMock()
-    mock_workspace.id = "ws-1"
-    mock_ws_db = MagicMock()
-    mock_ws_db.get_or_create_workspace = AsyncMock(return_value=mock_workspace)
-    return patch("backend.copilot.tools.helpers.workspace_db", return_value=mock_ws_db)
-
-
-def _patch_credit_db(
-    get_credits_return: int = 100,
-    spend_credits_side_effect: Any = None,
-):
-    """Patch credit_db accessor to return a mock credit adapter."""
-    mock_credit = MagicMock()
-    mock_credit.get_credits = AsyncMock(return_value=get_credits_return)
-    if spend_credits_side_effect is not None:
-        mock_credit.spend_credits = AsyncMock(side_effect=spend_credits_side_effect)
-    else:
-        mock_credit.spend_credits = AsyncMock()
-    return (
-        patch(
-            "backend.copilot.tools.helpers.credit_db",
-            return_value=mock_credit,
-        ),
-        mock_credit,
-    )
-
-
-# ---------------------------------------------------------------------------
-# Credit charging tests
-# ---------------------------------------------------------------------------
-
-
-@pytest.mark.asyncio(loop_scope="session")
-class TestExecuteBlockCreditCharging:
-    async def test_charges_credits_when_cost_is_positive(self):
-        """Block with cost > 0 should call spend_credits after execution."""
-        block = _make_block()
-        credit_patch, mock_credit = _patch_credit_db(get_credits_return=100)
-
-        with (
-            _patch_workspace(),
-            patch(
-                "backend.copilot.tools.helpers.block_usage_cost",
-                return_value=(10, {"key": "val"}),
-            ),
-            credit_patch,
-        ):
-            result = await execute_block(
-                block=block,
-                block_id="block-1",
-                input_data={"text": "hello"},
-                user_id=_USER,
-                session_id=_SESSION,
-                node_exec_id="exec-1",
-                matched_credentials={},
-            )
-
-        assert isinstance(result, BlockOutputResponse)
-        assert result.success is True
-        mock_credit.spend_credits.assert_awaited_once()
-        call_kwargs = mock_credit.spend_credits.call_args.kwargs
-        assert call_kwargs["cost"] == 10
-        assert call_kwargs["metadata"].reason == "copilot_block_execution"
-
-    async def test_returns_error_when_insufficient_credits_before_exec(self):
-        """Pre-execution check should return ErrorResponse when balance < cost."""
-        block = _make_block()
-        credit_patch, mock_credit = _patch_credit_db(get_credits_return=5)
-
-        with (
-            _patch_workspace(),
-            patch(
-                "backend.copilot.tools.helpers.block_usage_cost",
-                return_value=(10, {}),
-            ),
-            credit_patch,
-        ):
-            result = await execute_block(
-                block=block,
-                block_id="block-1",
-                input_data={},
-                user_id=_USER,
-                session_id=_SESSION,
-                node_exec_id="exec-1",
-                matched_credentials={},
-            )
-
-        assert isinstance(result, ErrorResponse)
-        assert "Insufficient credits" in result.message
-
-    async def test_no_charge_when_cost_is_zero(self):
-        """Block with cost 0 should not call spend_credits."""
-        block = _make_block()
-        credit_patch, mock_credit = _patch_credit_db()
-
-        with (
-            _patch_workspace(),
-            patch(
-                "backend.copilot.tools.helpers.block_usage_cost",
-                return_value=(0, {}),
-            ),
-            credit_patch,
-        ):
-            result = await execute_block(
-                block=block,
-                block_id="block-1",
-                input_data={},
-                user_id=_USER,
-                session_id=_SESSION,
-                node_exec_id="exec-1",
-                matched_credentials={},
-            )
-
-        assert isinstance(result, BlockOutputResponse)
-        assert result.success is True
-        # Credit functions should not be called at all for zero-cost blocks
-        mock_credit.get_credits.assert_not_awaited()
-        mock_credit.spend_credits.assert_not_awaited()
-
-    async def test_returns_output_on_post_exec_insufficient_balance(self):
-        """If charging fails after execution, output is still returned (block already ran)."""
-        from backend.util.exceptions import InsufficientBalanceError
-
-        block = _make_block()
-        credit_patch, mock_credit = _patch_credit_db(
-            get_credits_return=15,
-            spend_credits_side_effect=InsufficientBalanceError(
-                "Low balance", _USER, 5, 10
-            ),
-        )
-
-        with (
-            _patch_workspace(),
-            patch(
-                "backend.copilot.tools.helpers.block_usage_cost",
-                return_value=(10, {}),
-            ),
-            credit_patch,
-        ):
-            result = await execute_block(
-                block=block,
-                block_id="block-1",
-                input_data={},
-                user_id=_USER,
-                session_id=_SESSION,
-                node_exec_id="exec-1",
-                matched_credentials={},
-            )
-
-        # Block already executed (with side effects), so output is returned
-        assert isinstance(result, BlockOutputResponse)
-        assert result.success is True
-
-
-# ---------------------------------------------------------------------------
-# Type coercion tests
-# ---------------------------------------------------------------------------
+from backend.copilot.tools.models import BlockOutputResponse
 
 
 def _make_block_schema(annotations: dict[str, Any]) -> MagicMock:
@@ -207,7 +28,7 @@ def _make_block_schema(annotations: dict[str, Any]) -> MagicMock:
     return schema
 
 
-def _make_coerce_block(
+def _make_block(
     block_id: str,
     name: str,
     annotations: dict[str, Any],
@@ -239,7 +60,7 @@ _TEST_USER_ID = "test-user-coerce"
 @pytest.mark.asyncio(loop_scope="session")
 async def test_coerce_json_string_to_nested_list():
     """JSON string → list[list[str]] (Google Sheets CSV import case)."""
-    block = _make_coerce_block(
+    block = _make_block(
         "sheets-write",
         "Google Sheets Write",
         {"values": list[list[str]], "spreadsheet_id": str},
@@ -282,7 +103,7 @@ async def test_coerce_json_string_to_nested_list():
 @pytest.mark.asyncio(loop_scope="session")
 async def test_coerce_json_string_to_list():
     """JSON string → list[str]."""
-    block = _make_coerce_block(
+    block = _make_block(
         "list-block",
         "List Block",
         {"items": list[str]},
@@ -314,7 +135,7 @@ async def test_coerce_json_string_to_list():
 @pytest.mark.asyncio(loop_scope="session")
 async def test_coerce_json_string_to_dict():
     """JSON string → dict[str, str]."""
-    block = _make_coerce_block(
+    block = _make_block(
         "dict-block",
         "Dict Block",
         {"config": dict[str, str]},
@@ -346,7 +167,7 @@ async def test_coerce_json_string_to_dict():
 @pytest.mark.asyncio(loop_scope="session")
 async def test_no_coercion_when_type_matches():
     """Already-correct types pass through without coercion."""
-    block = _make_coerce_block(
+    block = _make_block(
         "pass-through",
         "Pass Through",
         {"values": list[list[str]], "name": str},
@@ -380,7 +201,7 @@ async def test_no_coercion_when_type_matches():
 @pytest.mark.asyncio(loop_scope="session")
 async def test_coerce_string_to_int():
     """String number → int."""
-    block = _make_coerce_block(
+    block = _make_block(
         "int-block",
         "Int Block",
         {"count": int},
@@ -413,7 +234,7 @@ async def test_coerce_string_to_int():
 @pytest.mark.asyncio(loop_scope="session")
 async def test_coerce_skips_none_values():
     """None values are not coerced (they may be optional fields)."""
-    block = _make_coerce_block(
+    block = _make_block(
         "optional-block",
         "Optional Block",
         {"data": list[str], "label": str},
@@ -446,7 +267,7 @@ async def test_coerce_skips_none_values():
 @pytest.mark.asyncio(loop_scope="session")
 async def test_coerce_union_type_preserves_valid_member():
     """Union-typed fields should not be coerced when the value matches a member."""
-    block = _make_coerce_block(
+    block = _make_block(
         "union-block",
         "Union Block",
         {"content": str | list[str]},
@@ -480,7 +301,7 @@ async def test_coerce_union_type_preserves_valid_member():
 @pytest.mark.asyncio(loop_scope="session")
 async def test_coerce_inner_elements_of_generic():
     """Inner elements of generic containers are recursively coerced."""
-    block = _make_coerce_block(
+    block = _make_block(
         "inner-coerce",
         "Inner Coerce",
         {"values": list[str]},

autogpt_platform/backend/backend/data/db_accessors.py

@@ -129,16 +129,3 @@ def review_db():
         review_db = get_database_manager_async_client()
 
     return review_db
-
-
-def credit_db():
-    if db.is_connected():
-        from backend.data import db_manager as _credit_db
-
-        credit_db = _credit_db
-    else:
-        from backend.util.clients import get_database_manager_async_client
-
-        credit_db = get_database_manager_async_client()
-
-    return credit_db

autogpt_platform/backend/backend/data/db_manager.py

@@ -148,11 +148,6 @@ async def _get_credits(user_id: str) -> int:
     return await user_credit_model.get_credits(user_id)
 
 
-# Public aliases used by db_accessors.credit_db() when Prisma is connected
-get_credits = _get_credits
-spend_credits = _spend_credits
-
-
 class DatabaseManager(AppService):
     """Database connection pooling service.
 
@@ -517,10 +512,6 @@ class DatabaseManagerAsyncClient(AppServiceClient):
     list_workspace_files = d.list_workspace_files
     soft_delete_workspace_file = d.soft_delete_workspace_file
 
-    # ============ Credits ============ #
-    spend_credits = d.spend_credits
-    get_credits = d.get_credits
-
     # ============ Understanding ============ #
     get_business_understanding = d.get_business_understanding
     upsert_business_understanding = d.upsert_business_understanding

autogpt_platform/backend/backend/util/prompt.py

@@ -70,6 +70,10 @@ def _msg_tokens(msg: dict, enc) -> int:
                 # Count tool result tokens
                 tool_call_tokens += _tok_len(item.get("tool_use_id", ""), enc)
                 tool_call_tokens += _tok_len(item.get("content", ""), enc)
+            elif isinstance(item, dict) and item.get("type") == "text":
+                # Count text block tokens (standard: "text" key, fallback: "content")
+                text_val = item.get("text") or item.get("content", "")
+                tool_call_tokens += _tok_len(text_val, enc)
             elif isinstance(item, dict) and "content" in item:
                 # Other content types with content field
                 tool_call_tokens += _tok_len(item.get("content", ""), enc)
@@ -145,10 +149,16 @@ def _truncate_middle_tokens(text: str, enc, max_tok: int) -> str:
     if len(ids) <= max_tok:
         return text  # nothing to do
 
+    # Need at least 3 tokens (head + ellipsis + tail) for meaningful truncation
+    if max_tok < 1:
+        return ""
+    mid = enc.encode(" … ")
+    if max_tok < 3:
+        return enc.decode(ids[:max_tok])
+
     # Split the allowance between the two ends:
     head = max_tok // 2 - 1  # -1 for the ellipsis
     tail = max_tok - head - 1
-    mid = enc.encode(" … ")
     return enc.decode(ids[:head] + mid + ids[-tail:])
 
 
@@ -545,6 +555,14 @@ async def _summarize_messages_llm(
                     "- Actions taken and key decisions made\n"
                     "- Technical specifics (file names, tool outputs, function signatures)\n"
                     "- Errors encountered and resolutions applied\n\n"
+                    "IMPORTANT: Preserve all concrete references verbatim — these are small but "
+                    "critical for continuing the conversation:\n"
+                    "- File paths and directory paths (e.g. /src/app/page.tsx, ./output/result.csv)\n"
+                    "- Image/media file paths from tool outputs\n"
+                    "- URLs, API endpoints, and webhook addresses\n"
+                    "- Resource IDs, session IDs, and identifiers\n"
+                    "- Tool names that were called and their key parameters\n"
+                    "- Environment variables, config keys, and credentials names (not values)\n\n"
                     "Include ONLY the sections below that have relevant content "
                     "(skip sections with nothing to report):\n\n"
                     "## 1. Primary Request and Intent\n"
@@ -552,7 +570,8 @@ async def _summarize_messages_llm(
                     "## 2. Key Technical Concepts\n"
                     "Technologies, frameworks, tools, and patterns being used or discussed.\n\n"
                     "## 3. Files and Resources Involved\n"
-                    "Specific files examined or modified, with relevant snippets and identifiers.\n\n"
+                    "Specific files examined or modified, with relevant snippets and identifiers. "
+                    "Include exact file paths, image paths from tool outputs, and resource URLs.\n\n"
                     "## 4. Errors and Fixes\n"
                     "Problems encountered, error messages, and their resolutions.\n\n"
                     "## 5. All User Messages\n"
@@ -566,7 +585,7 @@ async def _summarize_messages_llm(
             },
             {"role": "user", "content": f"Summarize:\n\n{conversation_text}"},
         ],
-        max_tokens=1500,
+        max_tokens=2000,
         temperature=0.3,
     )
 
@@ -686,11 +705,15 @@ async def compress_context(
                     msgs = [summary_msg] + recent_msgs
 
                 logger.info(
-                    f"Context summarized: {original_count} -> {total_tokens()} tokens, "
-                    f"summarized {messages_summarized} messages"
+                    "Context summarized: %d -> %d tokens, summarized %d messages",
+                    original_count,
+                    total_tokens(),
+                    messages_summarized,
                 )
             except Exception as e:
-                logger.warning(f"Summarization failed, continuing with truncation: {e}")
+                logger.warning(
+                    "Summarization failed, continuing with truncation: %s", e
+                )
                 # Fall through to content truncation
 
     # ---- STEP 2: Normalize content ----------------------------------------

autogpt_platform/frontend/src/app/(platform)/copilot/CopilotPage.tsx

@@ -1,8 +1,14 @@
 "use client";
 
+import {
+  DropdownMenu,
+  DropdownMenuContent,
+  DropdownMenuItem,
+  DropdownMenuTrigger,
+} from "@/components/molecules/DropdownMenu/DropdownMenu";
 import { SidebarProvider } from "@/components/ui/sidebar";
 import { cn } from "@/lib/utils";
-import { UploadSimple } from "@phosphor-icons/react";
+import { DotsThree, UploadSimple } from "@phosphor-icons/react";
 import { useCallback, useRef, useState } from "react";
 import { ChatContainer } from "./components/ChatContainer/ChatContainer";
 import { ChatSidebar } from "./components/ChatSidebar/ChatSidebar";
@@ -83,9 +89,10 @@ export function CopilotPage() {
     handleDrawerOpenChange,
     handleSelectSession,
     handleNewChat,
-    // Delete functionality (available via ChatSidebar context menu on all viewports)
+    // Delete functionality
     sessionToDelete,
     isDeleting,
+    handleDeleteClick,
     handleConfirmDelete,
     handleCancelDelete,
   } = useCopilotPage();
@@ -141,6 +148,38 @@ export function CopilotPage() {
             isUploadingFiles={isUploadingFiles}
             droppedFiles={droppedFiles}
             onDroppedFilesConsumed={handleDroppedFilesConsumed}
+            headerSlot={
+              isMobile && sessionId ? (
+                <div className="flex justify-end">
+                  <DropdownMenu>
+                    <DropdownMenuTrigger asChild>
+                      <button
+                        className="rounded p-1.5 hover:bg-neutral-100"
+                        aria-label="More actions"
+                      >
+                        <DotsThree className="h-5 w-5 text-neutral-600" />
+                      </button>
+                    </DropdownMenuTrigger>
+                    <DropdownMenuContent align="end">
+                      <DropdownMenuItem
+                        onClick={() => {
+                          const session = sessions.find(
+                            (s) => s.id === sessionId,
+                          );
+                          if (session) {
+                            handleDeleteClick(session.id, session.title);
+                          }
+                        }}
+                        disabled={isDeleting}
+                        className="text-red-600 focus:bg-red-50 focus:text-red-600"
+                      >
+                        Delete chat
+                      </DropdownMenuItem>
+                    </DropdownMenuContent>
+                  </DropdownMenu>
+                </div>
+              ) : undefined
+            }
           />
         </div>
       </div>

autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatContainer/ChatContainer.tsx

@@ -2,6 +2,7 @@
 import { ChatInput } from "@/app/(platform)/copilot/components/ChatInput/ChatInput";
 import { UIDataTypes, UIMessage, UITools } from "ai";
 import { LayoutGroup, motion } from "framer-motion";
+import { ReactNode } from "react";
 import { ChatMessagesContainer } from "../ChatMessagesContainer/ChatMessagesContainer";
 import { CopilotChatActionsProvider } from "../CopilotChatActionsProvider/CopilotChatActionsProvider";
 import { EmptySession } from "../EmptySession/EmptySession";
@@ -20,6 +21,7 @@ export interface ChatContainerProps {
   onSend: (message: string, files?: File[]) => void | Promise<void>;
   onStop: () => void;
   isUploadingFiles?: boolean;
+  headerSlot?: ReactNode;
   /** Files dropped onto the chat window. */
   droppedFiles?: File[];
   /** Called after droppedFiles have been consumed by ChatInput. */
@@ -38,6 +40,7 @@ export const ChatContainer = ({
   onSend,
   onStop,
   isUploadingFiles,
+  headerSlot,
   droppedFiles,
   onDroppedFilesConsumed,
 }: ChatContainerProps) => {
@@ -60,6 +63,7 @@ export const ChatContainer = ({
                 status={status}
                 error={error}
                 isLoading={isLoadingSession}
+                headerSlot={headerSlot}
                 sessionID={sessionId}
               />
               <motion.div

autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatMessagesContainer/ChatMessagesContainer.tsx

@@ -30,6 +30,7 @@ interface Props {
   status: string;
   error: Error | undefined;
   isLoading: boolean;
+  headerSlot?: React.ReactNode;
   sessionID?: string | null;
 }
 
@@ -101,6 +102,7 @@ export function ChatMessagesContainer({
   status,
   error,
   isLoading,
+  headerSlot,
   sessionID,
 }: Props) {
   const lastMessage = messages[messages.length - 1];
@@ -133,6 +135,7 @@ export function ChatMessagesContainer({
   return (
     <Conversation className="min-h-0 flex-1">
       <ConversationContent className="flex flex-1 flex-col gap-6 px-3 py-6">
+        {headerSlot}
         {isLoading && messages.length === 0 && (
           <div
             className="flex flex-1 items-center justify-center"

autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatSidebar/ChatSidebar.tsx

@@ -37,7 +37,6 @@ import { useCopilotUIStore } from "../../store";
 import { NotificationToggle } from "./components/NotificationToggle/NotificationToggle";
 import { DeleteChatDialog } from "../DeleteChatDialog/DeleteChatDialog";
 import { PulseLoader } from "../PulseLoader/PulseLoader";
-import { UsageLimits } from "../UsageLimits/UsageLimits";
 
 export function ChatSidebar() {
   const { state } = useSidebar();
@@ -257,10 +256,11 @@ export function ChatSidebar() {
                 <Text variant="h3" size="body-medium">
                   Your chats
                 </Text>
-                <div className="flex items-center">
-                  <UsageLimits />
+                <div className="relative left-5 flex items-center gap-1">
                   <NotificationToggle />
-                  <SidebarTrigger />
+                  <div className="relative left-1">
+                    <SidebarTrigger />
+                  </div>
                 </div>
               </div>
               {sessionId ? (

autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatSidebar/components/NotificationToggle/NotificationToggle.tsx

@@ -7,7 +7,6 @@ import {
   PopoverTrigger,
 } from "@/components/molecules/Popover/Popover";
 import { toast } from "@/components/molecules/Toast/use-toast";
-import { Button } from "@/components/ui/button";
 import { cn } from "@/lib/utils";
 import { Bell, BellRinging, BellSlash } from "@phosphor-icons/react";
 import { useCopilotUIStore } from "../../../../store";
@@ -49,7 +48,10 @@ export function NotificationToggle() {
   return (
     <Popover>
       <PopoverTrigger asChild>
-        <Button variant="ghost" size="icon" aria-label="Notification settings">
+        <button
+          className="rounded p-1 text-black transition-colors hover:bg-zinc-50"
+          aria-label="Notification settings"
+        >
           {!isNotificationsEnabled ? (
             <BellSlash className="!size-5" />
           ) : isSoundEnabled ? (
@@ -57,7 +59,7 @@ export function NotificationToggle() {
           ) : (
             <Bell className="!size-5" />
           )}
-        </Button>
+        </button>
       </PopoverTrigger>
       <PopoverContent align="start" className="w-56 p-3">
         <div className="flex flex-col gap-3">

autogpt_platform/frontend/src/app/(platform)/copilot/components/UsageLimits/UsageLimits.tsx

@@ -1,38 +0,0 @@
-import type { CoPilotUsageStatus } from "@/app/api/__generated__/models/coPilotUsageStatus";
-import { useGetV2GetCopilotUsage } from "@/app/api/__generated__/endpoints/chat/chat";
-import {
-  Popover,
-  PopoverContent,
-  PopoverTrigger,
-} from "@/components/molecules/Popover/Popover";
-import { Button } from "@/components/ui/button";
-import { ChartBar } from "@phosphor-icons/react";
-import { UsagePanelContent } from "./UsagePanelContent";
-
-export { UsagePanelContent, formatResetTime } from "./UsagePanelContent";
-
-export function UsageLimits() {
-  const { data: usage, isLoading } = useGetV2GetCopilotUsage({
-    query: {
-      select: (res) => res.data as CoPilotUsageStatus,
-      refetchInterval: 30000,
-      staleTime: 10000,
-    },
-  });
-
-  if (isLoading || !usage) return null;
-  if (usage.daily.limit <= 0 && usage.weekly.limit <= 0) return null;
-
-  return (
-    <Popover>
-      <PopoverTrigger asChild>
-        <Button variant="ghost" size="icon" aria-label="Usage limits">
-          <ChartBar className="!size-5" weight="light" />
-        </Button>
-      </PopoverTrigger>
-      <PopoverContent align="start" className="w-64 p-3">
-        <UsagePanelContent usage={usage} />
-      </PopoverContent>
-    </Popover>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/UsageLimits/UsagePanelContent.tsx

@@ -1,118 +0,0 @@
-import type { CoPilotUsageStatus } from "@/app/api/__generated__/models/coPilotUsageStatus";
-import Link from "next/link";
-
-export function formatResetTime(
-  resetsAt: Date | string,
-  now: Date = new Date(),
-): string {
-  const resetDate =
-    typeof resetsAt === "string" ? new Date(resetsAt) : resetsAt;
-  const diffMs = resetDate.getTime() - now.getTime();
-  if (diffMs <= 0) return "now";
-
-  const hours = Math.floor(diffMs / (1000 * 60 * 60));
-
-  // Under 24h: show relative time ("in 4h 23m")
-  if (hours < 24) {
-    const minutes = Math.floor((diffMs % (1000 * 60 * 60)) / (1000 * 60));
-    if (hours > 0) return `in ${hours}h ${minutes}m`;
-    return `in ${minutes}m`;
-  }
-
-  // Over 24h: show day and time in local timezone ("Mon 12:00 AM PST")
-  return resetDate.toLocaleString(undefined, {
-    weekday: "short",
-    hour: "numeric",
-    minute: "2-digit",
-    timeZoneName: "short",
-  });
-}
-
-function UsageBar({
-  label,
-  used,
-  limit,
-  resetsAt,
-}: {
-  label: string;
-  used: number;
-  limit: number;
-  resetsAt: Date | string;
-}) {
-  if (limit <= 0) return null;
-
-  const rawPercent = (used / limit) * 100;
-  const percent = Math.min(100, Math.round(rawPercent));
-  const isHigh = percent >= 80;
-  const percentLabel =
-    used > 0 && percent === 0 ? "<1% used" : `${percent}% used`;
-
-  return (
-    <div className="flex flex-col gap-1">
-      <div className="flex items-baseline justify-between">
-        <span className="text-xs font-medium text-neutral-700">{label}</span>
-        <span className="text-[11px] tabular-nums text-neutral-500">
-          {percentLabel}
-        </span>
-      </div>
-      <div className="text-[10px] text-neutral-400">
-        Resets {formatResetTime(resetsAt)}
-      </div>
-      <div className="h-2 w-full overflow-hidden rounded-full bg-neutral-200">
-        <div
-          className={`h-full rounded-full transition-[width] duration-300 ease-out ${
-            isHigh ? "bg-orange-500" : "bg-blue-500"
-          }`}
-          style={{ width: `${Math.max(used > 0 ? 1 : 0, percent)}%` }}
-        />
-      </div>
-    </div>
-  );
-}
-
-export function UsagePanelContent({
-  usage,
-  showBillingLink = true,
-}: {
-  usage: CoPilotUsageStatus;
-  showBillingLink?: boolean;
-}) {
-  const hasDailyLimit = usage.daily.limit > 0;
-  const hasWeeklyLimit = usage.weekly.limit > 0;
-
-  if (!hasDailyLimit && !hasWeeklyLimit) {
-    return (
-      <div className="text-xs text-neutral-500">No usage limits configured</div>
-    );
-  }
-
-  return (
-    <div className="flex flex-col gap-3">
-      <div className="text-xs font-semibold text-neutral-800">Usage limits</div>
-      {hasDailyLimit && (
-        <UsageBar
-          label="Today"
-          used={usage.daily.used}
-          limit={usage.daily.limit}
-          resetsAt={usage.daily.resets_at}
-        />
-      )}
-      {hasWeeklyLimit && (
-        <UsageBar
-          label="This week"
-          used={usage.weekly.used}
-          limit={usage.weekly.limit}
-          resetsAt={usage.weekly.resets_at}
-        />
-      )}
-      {showBillingLink && (
-        <Link
-          href="/profile/credits"
-          className="text-[11px] text-blue-600 hover:underline"
-        >
-          Learn more about usage limits
-        </Link>
-      )}
-    </div>
-  );
-}

autogpt_platform/frontend/src/app/(platform)/copilot/components/UsageLimits/__tests__/UsageLimits.test.tsx

@@ -1,124 +0,0 @@
-import { render, screen, cleanup } from "@/tests/integrations/test-utils";
-import { afterEach, describe, expect, it, vi } from "vitest";
-import { UsageLimits } from "../UsageLimits";
-
-// Mock the generated Orval hook
-const mockUseGetV2GetCopilotUsage = vi.fn();
-vi.mock("@/app/api/__generated__/endpoints/chat/chat", () => ({
-  useGetV2GetCopilotUsage: (opts: unknown) => mockUseGetV2GetCopilotUsage(opts),
-}));
-
-// Mock Popover to render children directly (Radix portals don't work in happy-dom)
-vi.mock("@/components/molecules/Popover/Popover", () => ({
-  Popover: ({ children }: { children: React.ReactNode }) => (
-    <div>{children}</div>
-  ),
-  PopoverTrigger: ({ children }: { children: React.ReactNode }) => (
-    <div>{children}</div>
-  ),
-  PopoverContent: ({ children }: { children: React.ReactNode }) => (
-    <div>{children}</div>
-  ),
-}));
-
-afterEach(() => {
-  cleanup();
-  mockUseGetV2GetCopilotUsage.mockReset();
-});
-
-function makeUsage({
-  dailyUsed = 500,
-  dailyLimit = 10000,
-  weeklyUsed = 2000,
-  weeklyLimit = 50000,
-}: {
-  dailyUsed?: number;
-  dailyLimit?: number;
-  weeklyUsed?: number;
-  weeklyLimit?: number;
-} = {}) {
-  const future = new Date(Date.now() + 3600 * 1000); // 1h from now
-  return {
-    daily: { used: dailyUsed, limit: dailyLimit, resets_at: future },
-    weekly: { used: weeklyUsed, limit: weeklyLimit, resets_at: future },
-  };
-}
-
-describe("UsageLimits", () => {
-  it("renders nothing while loading", () => {
-    mockUseGetV2GetCopilotUsage.mockReturnValue({
-      data: undefined,
-      isLoading: true,
-    });
-    const { container } = render(<UsageLimits />);
-    expect(container.innerHTML).toBe("");
-  });
-
-  it("renders nothing when no limits are configured", () => {
-    mockUseGetV2GetCopilotUsage.mockReturnValue({
-      data: makeUsage({ dailyLimit: 0, weeklyLimit: 0 }),
-      isLoading: false,
-    });
-    const { container } = render(<UsageLimits />);
-    expect(container.innerHTML).toBe("");
-  });
-
-  it("renders the usage button when limits exist", () => {
-    mockUseGetV2GetCopilotUsage.mockReturnValue({
-      data: makeUsage(),
-      isLoading: false,
-    });
-    render(<UsageLimits />);
-    expect(screen.getByRole("button", { name: /usage limits/i })).toBeDefined();
-  });
-
-  it("displays daily and weekly usage percentages", () => {
-    mockUseGetV2GetCopilotUsage.mockReturnValue({
-      data: makeUsage({ dailyUsed: 5000, dailyLimit: 10000 }),
-      isLoading: false,
-    });
-    render(<UsageLimits />);
-
-    expect(screen.getByText("50% used")).toBeDefined();
-    expect(screen.getByText("Today")).toBeDefined();
-    expect(screen.getByText("This week")).toBeDefined();
-    expect(screen.getByText("Usage limits")).toBeDefined();
-  });
-
-  it("shows only weekly bar when daily limit is 0", () => {
-    mockUseGetV2GetCopilotUsage.mockReturnValue({
-      data: makeUsage({
-        dailyLimit: 0,
-        weeklyUsed: 25000,
-        weeklyLimit: 50000,
-      }),
-      isLoading: false,
-    });
-    render(<UsageLimits />);
-
-    expect(screen.getByText("This week")).toBeDefined();
-    expect(screen.queryByText("Today")).toBeNull();
-  });
-
-  it("caps percentage at 100% when over limit", () => {
-    mockUseGetV2GetCopilotUsage.mockReturnValue({
-      data: makeUsage({ dailyUsed: 15000, dailyLimit: 10000 }),
-      isLoading: false,
-    });
-    render(<UsageLimits />);
-
-    expect(screen.getByText("100% used")).toBeDefined();
-  });
-
-  it("shows learn more link to credits page", () => {
-    mockUseGetV2GetCopilotUsage.mockReturnValue({
-      data: makeUsage(),
-      isLoading: false,
-    });
-    render(<UsageLimits />);
-
-    const link = screen.getByText("Learn more about usage limits");
-    expect(link).toBeDefined();
-    expect(link.closest("a")?.getAttribute("href")).toBe("/profile/credits");
-  });
-});

autogpt_platform/frontend/src/app/(platform)/copilot/useCopilotStream.ts

@@ -1,5 +1,4 @@
 import {
-  getGetV2GetCopilotUsageQueryKey,
   getGetV2GetSessionQueryKey,
   postV2CancelSessionTask,
 } from "@/app/api/__generated__/endpoints/chat/chat";
@@ -178,41 +177,12 @@ export function useCopilotStream({
     onError: (error) => {
       if (!sessionId) return;
 
-      // Detect rate limit (429) responses and show reset time to the user.
-      // The SDK throws a plain Error whose message is the raw response body
-      // (FastAPI returns {"detail": "...usage limit..."} for 429s).
-      let errorDetail: string = error.message;
-      try {
-        const parsed = JSON.parse(error.message) as unknown;
-        if (
-          typeof parsed === "object" &&
-          parsed !== null &&
-          "detail" in parsed &&
-          typeof (parsed as { detail: unknown }).detail === "string"
-        ) {
-          errorDetail = (parsed as { detail: string }).detail;
-        }
-      } catch {
-        // Not JSON — use message as-is
-      }
-      const isRateLimited = errorDetail.toLowerCase().includes("usage limit");
-      if (isRateLimited) {
-        toast({
-          title: "Usage limit reached",
-          description:
-            errorDetail ||
-            "You've reached your usage limit. Please try again later.",
-          variant: "destructive",
-        });
-        return;
-      }
-
       // Detect authentication failures (from getAuthHeaders or 401 responses)
       const isAuthError =
-        errorDetail.includes("Authentication failed") ||
-        errorDetail.includes("Unauthorized") ||
-        errorDetail.includes("Not authenticated") ||
-        errorDetail.toLowerCase().includes("401");
+        error.message.includes("Authentication failed") ||
+        error.message.includes("Unauthorized") ||
+        error.message.includes("Not authenticated") ||
+        error.message.toLowerCase().includes("401");
       if (isAuthError) {
         toast({
           title: "Authentication error",
@@ -337,9 +307,6 @@ export function useCopilotStream({
       queryClient.invalidateQueries({
         queryKey: getGetV2GetSessionQueryKey(sessionId),
       });
-      queryClient.invalidateQueries({
-        queryKey: getGetV2GetCopilotUsageQueryKey(),
-      });
       if (status === "ready") {
         reconnectAttemptsRef.current = 0;
         hasShownDisconnectToast.current = false;

autogpt_platform/frontend/src/app/(platform)/profile/(user)/credits/page.tsx

@@ -11,9 +11,6 @@ import {
 
 import { RefundModal } from "./RefundModal";
 import { CreditTransaction } from "@/lib/autogpt-server-api";
-import { UsagePanelContent } from "@/app/(platform)/copilot/components/UsageLimits/UsageLimits";
-import type { CoPilotUsageStatus } from "@/app/api/__generated__/models/coPilotUsageStatus";
-import { useGetV2GetCopilotUsage } from "@/app/api/__generated__/endpoints/chat/chat";
 
 import {
   Table,
@@ -24,32 +21,6 @@ import {
   TableRow,
 } from "@/components/__legacy__/ui/table";
 
-function CoPilotUsageSection() {
-  const router = useRouter();
-  const { data: usage, isLoading } = useGetV2GetCopilotUsage({
-    query: {
-      select: (res) => res.data as CoPilotUsageStatus,
-      refetchInterval: 30000,
-      staleTime: 10000,
-    },
-  });
-
-  if (isLoading || !usage) return null;
-  if (usage.daily.limit <= 0 && usage.weekly.limit <= 0) return null;
-
-  return (
-    <div className="my-6 space-y-4">
-      <h3 className="text-lg font-medium">CoPilot Usage Limits</h3>
-      <div className="rounded-lg border border-neutral-200 p-4">
-        <UsagePanelContent usage={usage} showBillingLink={false} />
-      </div>
-      <Button className="w-full" onClick={() => router.push("/copilot")}>
-        Open CoPilot
-      </Button>
-    </div>
-  );
-}
-
 export default function CreditsPage() {
   const api = useBackendAPI();
   const {
@@ -266,13 +237,11 @@ export default function CreditsPage() {
               </Button>
             )}
           </form>
-
-          {/* CoPilot Usage Limits */}
-          <CoPilotUsageSection />
         </div>
 
         <div className="my-6 space-y-4">
           {/* Payment Portal */}
+
           <h3 className="text-lg font-medium">Manage Your Payment Methods</h3>
           <p className="text-neutral-600">
             You can manage your cards and see your payment history in the

autogpt_platform/frontend/src/app/api/openapi.json

@@ -1267,7 +1267,7 @@
       "post": {
         "tags": ["v2", "chat", "chat"],
         "summary": "Stream Chat Post",
-        "description": "Stream chat responses for a session (POST with context support).\n\nStreams the AI/completion responses in real time over Server-Sent Events (SSE), including:\n  - Text fragments as they are generated\n  - Tool call UI elements (if invoked)\n  - Tool execution results\n\nThe AI generation runs in a background task that continues even if the client disconnects.\nAll chunks are written to a per-turn Redis stream for reconnection support. If the client\ndisconnects, they can reconnect using GET /sessions/{session_id}/stream to resume.\n\nArgs:\n    session_id: The chat session identifier to associate with the streamed messages.\n    request: Request body containing message, is_user_message, and optional context.\n    user_id: Authenticated user ID.\nReturns:\n    StreamingResponse: SSE-formatted response chunks.",
+        "description": "Stream chat responses for a session (POST with context support).\n\nStreams the AI/completion responses in real time over Server-Sent Events (SSE), including:\n  - Text fragments as they are generated\n  - Tool call UI elements (if invoked)\n  - Tool execution results\n\nThe AI generation runs in a background task that continues even if the client disconnects.\nAll chunks are written to a per-turn Redis stream for reconnection support. If the client\ndisconnects, they can reconnect using GET /sessions/{session_id}/stream to resume.\n\nArgs:\n    session_id: The chat session identifier to associate with the streamed messages.\n    request: Request body containing message, is_user_message, and optional context.\n    user_id: Optional authenticated user ID.\nReturns:\n    StreamingResponse: SSE-formatted response chunks.",
         "operationId": "postV2StreamChatPost",
         "security": [{ "HTTPBearerJWT": [] }],
         "parameters": [
@@ -1382,28 +1382,6 @@
         "security": [{ "HTTPBearerJWT": [] }]
       }
     },
-    "/api/chat/usage": {
-      "get": {
-        "tags": ["v2", "chat", "chat"],
-        "summary": "Get Copilot Usage",
-        "description": "Get CoPilot usage status for the authenticated user.\n\nReturns current token usage vs limits for daily and weekly windows.",
-        "operationId": "getV2GetCopilotUsage",
-        "responses": {
-          "200": {
-            "description": "Successful Response",
-            "content": {
-              "application/json": {
-                "schema": { "$ref": "#/components/schemas/CoPilotUsageStatus" }
-              }
-            }
-          },
-          "401": {
-            "$ref": "#/components/responses/HTTP401NotAuthenticatedError"
-          }
-        },
-        "security": [{ "HTTPBearerJWT": [] }]
-      }
-    },
     "/api/credits": {
       "get": {
         "tags": ["v1", "credits"],
@@ -8477,16 +8455,6 @@
         "title": "ClarifyingQuestion",
         "description": "A question that needs user clarification."
       },
-      "CoPilotUsageStatus": {
-        "properties": {
-          "daily": { "$ref": "#/components/schemas/UsageWindow" },
-          "weekly": { "$ref": "#/components/schemas/UsageWindow" }
-        },
-        "type": "object",
-        "required": ["daily", "weekly"],
-        "title": "CoPilotUsageStatus",
-        "description": "Current usage status for a user across all windows."
-      },
       "ContentType": {
         "type": "string",
         "enum": [
@@ -12222,16 +12190,6 @@
               { "$ref": "#/components/schemas/ActiveStreamInfo" },
               { "type": "null" }
             ]
-          },
-          "total_prompt_tokens": {
-            "type": "integer",
-            "title": "Total Prompt Tokens",
-            "default": 0
-          },
-          "total_completion_tokens": {
-            "type": "integer",
-            "title": "Total Completion Tokens",
-            "default": 0
           }
         },
         "type": "object",
@@ -14629,25 +14587,6 @@
         "required": ["timezone"],
         "title": "UpdateTimezoneRequest"
       },
-      "UsageWindow": {
-        "properties": {
-          "used": { "type": "integer", "title": "Used" },
-          "limit": {
-            "type": "integer",
-            "title": "Limit",
-            "description": "Maximum tokens allowed in this window. 0 means unlimited."
-          },
-          "resets_at": {
-            "type": "string",
-            "format": "date-time",
-            "title": "Resets At"
-          }
-        },
-        "type": "object",
-        "required": ["used", "limit", "resets_at"],
-        "title": "UsageWindow",
-        "description": "Usage within a single time window."
-      },
       "UserHistoryResponse": {
         "properties": {
           "history": {

autogpt_platform/frontend/src/components/ui/sidebar.tsx

@@ -288,7 +288,6 @@ const SidebarTrigger = React.forwardRef<
       ref={ref}
       data-sidebar="trigger"
       variant="ghost"
-      size="icon"
       onClick={(event) => {
         onClick?.(event);
         toggleSidebar();