feat(frontend): Add progress indicator during agent generation [SECRT-1883]

Add an asymptotic progress bar that appears after 10 seconds of waiting,
showing visual feedback for long-running tasks. The progress bar uses a
half-life formula where it reaches ~50% at 30s, ~75% at 60s, ~87.5% at 90s,
and so on - creating the classic "game loading bar" effect that slows down
but never reaches 100%.

autogpt_platform/backend/backend/api/features/chat/tools/utils.py

@@ -8,7 +8,12 @@ from backend.api.features.library import model as library_model
 from backend.api.features.store import db as store_db
 from backend.data import graph as graph_db
 from backend.data.graph import GraphModel
-from backend.data.model import Credentials, CredentialsFieldInfo, CredentialsMetaInput
+from backend.data.model import (
+    CredentialsFieldInfo,
+    CredentialsMetaInput,
+    HostScopedCredentials,
+    OAuth2Credentials,
+)
 from backend.integrations.creds_manager import IntegrationCredentialsManager
 from backend.util.exceptions import NotFoundError
 
@@ -273,7 +278,14 @@ async def match_user_credentials_to_graph(
                 for cred in available_creds
                 if cred.provider in credential_requirements.provider
                 and cred.type in credential_requirements.supported_types
-                and _credential_has_required_scopes(cred, credential_requirements)
+                and (
+                    cred.type != "oauth2"
+                    or _credential_has_required_scopes(cred, credential_requirements)
+                )
+                and (
+                    cred.type != "host_scoped"
+                    or _credential_is_for_host(cred, credential_requirements)
+                )
             ),
             None,
         )
@@ -318,19 +330,10 @@ async def match_user_credentials_to_graph(
 
 
 def _credential_has_required_scopes(
-    credential: Credentials,
+    credential: OAuth2Credentials,
     requirements: CredentialsFieldInfo,
 ) -> bool:
-    """
-    Check if a credential has all the scopes required by the block.
-
-    For OAuth2 credentials, verifies that the credential's scopes are a superset
-    of the required scopes. For other credential types, returns True (no scope check).
-    """
-    # Only OAuth2 credentials have scopes to check
-    if credential.type != "oauth2":
-        return True
-
+    """Check if an OAuth2 credential has all the scopes required by the input."""
     # If no scopes are required, any credential matches
     if not requirements.required_scopes:
         return True
@@ -339,6 +342,22 @@ def _credential_has_required_scopes(
     return set(credential.scopes).issuperset(requirements.required_scopes)
 
 
+def _credential_is_for_host(
+    credential: HostScopedCredentials,
+    requirements: CredentialsFieldInfo,
+) -> bool:
+    """Check if a host-scoped credential matches the host required by the input."""
+    # We need to know the host to match host-scoped credentials to.
+    # Graph.aggregate_credentials_inputs() adds the node's set URL value (if any)
+    # to discriminator_values. No discriminator_values -> no host to match against.
+    if not requirements.discriminator_values:
+        return True
+
+    # Check that credential host matches required host.
+    # Host-scoped credential inputs are grouped by host, so any item from the set works.
+    return credential.matches_url(list(requirements.discriminator_values)[0])
+
+
 async def check_user_has_required_credentials(
     user_id: str,
     required_credentials: list[CredentialsMetaInput],

autogpt_platform/backend/backend/blocks/encoder_block.py

@@ -1,77 +0,0 @@
-"""Text encoding block for converting special characters to escape sequences."""
-
-import codecs
-
-from backend.data.block import (
-    Block,
-    BlockCategory,
-    BlockOutput,
-    BlockSchemaInput,
-    BlockSchemaOutput,
-)
-from backend.data.model import SchemaField
-
-
-class TextEncoderBlock(Block):
-    """
-    Encodes a string by converting special characters into escape sequences.
-
-    This block is the inverse of TextDecoderBlock. It takes text containing
-    special characters (like newlines, tabs, etc.) and converts them into
-    their escape sequence representations (e.g., newline becomes \\n).
-    """
-
-    class Input(BlockSchemaInput):
-        """Input schema for TextEncoderBlock."""
-
-        text: str = SchemaField(
-            description="A string containing special characters to be encoded",
-            placeholder="Your text with newlines and quotes to encode",
-        )
-
-    class Output(BlockSchemaOutput):
-        """Output schema for TextEncoderBlock."""
-
-        encoded_text: str = SchemaField(
-            description="The encoded text with special characters converted to escape sequences"
-        )
-        error: str = SchemaField(description="Error message if encoding fails")
-
-    def __init__(self):
-        super().__init__(
-            id="5185f32e-4b65-4ecf-8fbb-873f003f09d6",
-            description="Encodes a string by converting special characters into escape sequences",
-            categories={BlockCategory.TEXT},
-            input_schema=TextEncoderBlock.Input,
-            output_schema=TextEncoderBlock.Output,
-            test_input={
-                "text": """Hello
-World!
-This is a "quoted" string."""
-            },
-            test_output=[
-                (
-                    "encoded_text",
-                    """Hello\\nWorld!\\nThis is a "quoted" string.""",
-                )
-            ],
-        )
-
-    async def run(self, input_data: Input, **kwargs) -> BlockOutput:
-        """
-        Encode the input text by converting special characters to escape sequences.
-
-        Args:
-            input_data: The input containing the text to encode.
-            **kwargs: Additional keyword arguments (unused).
-
-        Yields:
-            The encoded text with escape sequences, or an error message if encoding fails.
-        """
-        try:
-            encoded_text = codecs.encode(input_data.text, "unicode_escape").decode(
-                "utf-8"
-            )
-            yield "encoded_text", encoded_text
-        except Exception as e:
-            yield "error", f"Encoding error: {str(e)}"

autogpt_platform/backend/backend/blocks/linear/_api.py

@@ -162,8 +162,16 @@ class LinearClient:
                 "searchTerm": team_name,
             }
 
-            team_id = await self.query(query, variables)
-            return team_id["teams"]["nodes"][0]["id"]
+            result = await self.query(query, variables)
+            nodes = result["teams"]["nodes"]
+
+            if not nodes:
+                raise LinearAPIException(
+                    f"Team '{team_name}' not found. Check the team name or key and try again.",
+                    status_code=404,
+                )
+
+            return nodes[0]["id"]
         except LinearAPIException as e:
             raise e
 
@@ -240,17 +248,44 @@ class LinearClient:
         except LinearAPIException as e:
             raise e
 
-    async def try_search_issues(self, term: str) -> list[Issue]:
+    async def try_search_issues(
+        self,
+        term: str,
+        max_results: int = 10,
+        team_id: str | None = None,
+    ) -> list[Issue]:
         try:
             query = """
-                query SearchIssues($term: String!, $includeComments: Boolean!) {
-                    searchIssues(term: $term, includeComments: $includeComments) {
+                query SearchIssues(
+                    $term: String!,
+                    $first: Int,
+                    $teamId: String
+                ) {
+                    searchIssues(
+                        term: $term,
+                        first: $first,
+                        teamId: $teamId
+                    ) {
                         nodes {
                             id
                             identifier
                             title
                             description
                             priority
+                            createdAt
+                            state {
+                                id
+                                name
+                                type
+                            }
+                            project {
+                                id
+                                name
+                            }
+                            assignee {
+                                id
+                                name
+                            }
                         }
                     }
                 }
@@ -258,7 +293,8 @@ class LinearClient:
 
             variables: dict[str, Any] = {
                 "term": term,
-                "includeComments": True,
+                "first": max_results,
+                "teamId": team_id,
             }
 
             issues = await self.query(query, variables)

autogpt_platform/backend/backend/blocks/linear/issues.py

@@ -17,7 +17,7 @@ from ._config import (
     LinearScope,
     linear,
 )
-from .models import CreateIssueResponse, Issue
+from .models import CreateIssueResponse, Issue, State
 
 
 class LinearCreateIssueBlock(Block):
@@ -135,9 +135,20 @@ class LinearSearchIssuesBlock(Block):
             description="Linear credentials with read permissions",
             required_scopes={LinearScope.READ},
         )
+        max_results: int = SchemaField(
+            description="Maximum number of results to return",
+            default=10,
+            ge=1,
+            le=100,
+        )
+        team_name: str | None = SchemaField(
+            description="Optional team name to filter results (e.g., 'Internal', 'Open Source')",
+            default=None,
+        )
 
     class Output(BlockSchemaOutput):
         issues: list[Issue] = SchemaField(description="List of issues")
+        error: str = SchemaField(description="Error message if the search failed")
 
     def __init__(self):
         super().__init__(
@@ -145,8 +156,11 @@ class LinearSearchIssuesBlock(Block):
             description="Searches for issues on Linear",
             input_schema=self.Input,
             output_schema=self.Output,
+            categories={BlockCategory.PRODUCTIVITY, BlockCategory.ISSUE_TRACKING},
             test_input={
                 "term": "Test issue",
+                "max_results": 10,
+                "team_name": None,
                 "credentials": TEST_CREDENTIALS_INPUT_OAUTH,
             },
             test_credentials=TEST_CREDENTIALS_OAUTH,
@@ -156,10 +170,14 @@ class LinearSearchIssuesBlock(Block):
                     [
                         Issue(
                             id="abc123",
-                            identifier="abc123",
+                            identifier="TST-123",
                             title="Test issue",
                             description="Test description",
                             priority=1,
+                            state=State(
+                                id="state1", name="In Progress", type="started"
+                            ),
+                            createdAt="2026-01-15T10:00:00.000Z",
                         )
                     ],
                 )
@@ -168,10 +186,12 @@ class LinearSearchIssuesBlock(Block):
                 "search_issues": lambda *args, **kwargs: [
                     Issue(
                         id="abc123",
-                        identifier="abc123",
+                        identifier="TST-123",
                         title="Test issue",
                         description="Test description",
                         priority=1,
+                        state=State(id="state1", name="In Progress", type="started"),
+                        createdAt="2026-01-15T10:00:00.000Z",
                     )
                 ]
             },
@@ -181,10 +201,22 @@ class LinearSearchIssuesBlock(Block):
     async def search_issues(
         credentials: OAuth2Credentials | APIKeyCredentials,
         term: str,
+        max_results: int = 10,
+        team_name: str | None = None,
     ) -> list[Issue]:
         client = LinearClient(credentials=credentials)
-        response: list[Issue] = await client.try_search_issues(term=term)
-        return response
+
+        # Resolve team name to ID if provided
+        # Raises LinearAPIException with descriptive message if team not found
+        team_id: str | None = None
+        if team_name:
+            team_id = await client.try_get_team_by_name(team_name=team_name)
+
+        return await client.try_search_issues(
+            term=term,
+            max_results=max_results,
+            team_id=team_id,
+        )
 
     async def run(
         self,
@@ -196,7 +228,10 @@ class LinearSearchIssuesBlock(Block):
         """Execute the issue search"""
         try:
             issues = await self.search_issues(
-                credentials=credentials, term=input_data.term
+                credentials=credentials,
+                term=input_data.term,
+                max_results=input_data.max_results,
+                team_name=input_data.team_name,
             )
             yield "issues", issues
         except LinearAPIException as e:

autogpt_platform/backend/backend/blocks/linear/models.py

@@ -36,12 +36,21 @@ class Project(BaseModel):
     content: str | None = None
 
 
+class State(BaseModel):
+    id: str
+    name: str
+    type: str | None = (
+        None  # Workflow state type (e.g., "triage", "backlog", "started", "completed", "canceled")
+    )
+
+
 class Issue(BaseModel):
     id: str
     identifier: str
     title: str
     description: str | None
     priority: int
+    state: State | None = None
     project: Project | None = None
     createdAt: str | None = None
     comments: list[Comment] | None = None

autogpt_platform/backend/backend/blocks/test/test_text_encoder.py

@@ -1,77 +0,0 @@
-import pytest
-
-from backend.blocks.encoder_block import TextEncoderBlock
-
-
-@pytest.mark.asyncio
-async def test_text_encoder_basic():
-    """Test basic encoding of newlines and special characters."""
-    block = TextEncoderBlock()
-    result = []
-    async for output in block.run(TextEncoderBlock.Input(text="Hello\nWorld")):
-        result.append(output)
-
-    assert len(result) == 1
-    assert result[0][0] == "encoded_text"
-    assert result[0][1] == "Hello\\nWorld"
-
-
-@pytest.mark.asyncio
-async def test_text_encoder_multiple_escapes():
-    """Test encoding of multiple escape sequences."""
-    block = TextEncoderBlock()
-    result = []
-    async for output in block.run(
-        TextEncoderBlock.Input(text="Line1\nLine2\tTabbed\rCarriage")
-    ):
-        result.append(output)
-
-    assert len(result) == 1
-    assert result[0][0] == "encoded_text"
-    assert "\\n" in result[0][1]
-    assert "\\t" in result[0][1]
-    assert "\\r" in result[0][1]
-
-
-@pytest.mark.asyncio
-async def test_text_encoder_unicode():
-    """Test that unicode characters are handled correctly."""
-    block = TextEncoderBlock()
-    result = []
-    async for output in block.run(TextEncoderBlock.Input(text="Hello 世界\n")):
-        result.append(output)
-
-    assert len(result) == 1
-    assert result[0][0] == "encoded_text"
-    # Unicode characters should be escaped as \uXXXX sequences
-    assert "\\n" in result[0][1]
-
-
-@pytest.mark.asyncio
-async def test_text_encoder_empty_string():
-    """Test encoding of an empty string."""
-    block = TextEncoderBlock()
-    result = []
-    async for output in block.run(TextEncoderBlock.Input(text="")):
-        result.append(output)
-
-    assert len(result) == 1
-    assert result[0][0] == "encoded_text"
-    assert result[0][1] == ""
-
-
-@pytest.mark.asyncio
-async def test_text_encoder_error_handling():
-    """Test that encoding errors are handled gracefully."""
-    from unittest.mock import patch
-
-    block = TextEncoderBlock()
-    result = []
-
-    with patch("codecs.encode", side_effect=Exception("Mocked encoding error")):
-        async for output in block.run(TextEncoderBlock.Input(text="test")):
-            result.append(output)
-
-    assert len(result) == 1
-    assert result[0][0] == "error"
-    assert "Mocked encoding error" in result[0][1]

autogpt_platform/backend/backend/data/model.py

@@ -19,7 +19,6 @@ from typing import (
     cast,
     get_args,
 )
-from urllib.parse import urlparse
 from uuid import uuid4
 
 from prisma.enums import CreditTransactionType, OnboardingStep
@@ -42,6 +41,7 @@ from typing_extensions import TypedDict
 
 from backend.integrations.providers import ProviderName
 from backend.util.json import loads as json_loads
+from backend.util.request import parse_url
 from backend.util.settings import Secrets
 
 # Type alias for any provider name (including custom ones)
@@ -397,19 +397,25 @@ class HostScopedCredentials(_BaseCredentials):
     def matches_url(self, url: str) -> bool:
         """Check if this credential should be applied to the given URL."""
 
-        parsed_url = urlparse(url)
-        # Extract hostname without port
-        request_host = parsed_url.hostname
+        request_host, request_port = _extract_host_from_url(url)
+        cred_scope_host, cred_scope_port = _extract_host_from_url(self.host)
         if not request_host:
             return False
 
-        # Simple host matching - exact match or wildcard subdomain match
-        if self.host == request_host:
+        # If a port is specified in credential host, the request host port must match
+        if cred_scope_port is not None and request_port != cred_scope_port:
+            return False
+        # Non-standard ports are only allowed if explicitly specified in credential host
+        elif cred_scope_port is None and request_port not in (80, 443, None):
+            return False
+
+        # Simple host matching
+        if cred_scope_host == request_host:
             return True
 
         # Support wildcard matching (e.g., "*.example.com" matches "api.example.com")
-        if self.host.startswith("*."):
-            domain = self.host[2:]  # Remove "*."
+        if cred_scope_host.startswith("*."):
+            domain = cred_scope_host[2:]  # Remove "*."
             return request_host.endswith(f".{domain}") or request_host == domain
 
         return False
@@ -551,13 +557,13 @@ class CredentialsMetaInput(BaseModel, Generic[CP, CT]):
     )
 
 
-def _extract_host_from_url(url: str) -> str:
-    """Extract host from URL for grouping host-scoped credentials."""
+def _extract_host_from_url(url: str) -> tuple[str, int | None]:
+    """Extract host and port from URL for grouping host-scoped credentials."""
     try:
-        parsed = urlparse(url)
-        return parsed.hostname or url
+        parsed = parse_url(url)
+        return parsed.hostname or url, parsed.port
     except Exception:
-        return ""
+        return "", None
 
 
 class CredentialsFieldInfo(BaseModel, Generic[CP, CT]):
@@ -606,7 +612,7 @@ class CredentialsFieldInfo(BaseModel, Generic[CP, CT]):
                 providers = frozenset(
                     [cast(CP, "http")]
                     + [
-                        cast(CP, _extract_host_from_url(str(value)))
+                        cast(CP, parse_url(str(value)).netloc)
                         for value in field.discriminator_values
                     ]
                 )

autogpt_platform/backend/backend/data/model_test.py

@@ -79,10 +79,23 @@ class TestHostScopedCredentials:
             headers={"Authorization": SecretStr("Bearer token")},
         )
 
-        assert creds.matches_url("http://localhost:8080/api/v1")
+        # Non-standard ports require explicit port in credential host
+        assert not creds.matches_url("http://localhost:8080/api/v1")
         assert creds.matches_url("https://localhost:443/secure/endpoint")
         assert creds.matches_url("http://localhost/simple")
 
+    def test_matches_url_with_explicit_port(self):
+        """Test URL matching with explicit port in credential host."""
+        creds = HostScopedCredentials(
+            provider="custom",
+            host="localhost:8080",
+            headers={"Authorization": SecretStr("Bearer token")},
+        )
+
+        assert creds.matches_url("http://localhost:8080/api/v1")
+        assert not creds.matches_url("http://localhost:3000/api/v1")
+        assert not creds.matches_url("http://localhost/simple")
+
     def test_empty_headers_dict(self):
         """Test HostScopedCredentials with empty headers."""
         creds = HostScopedCredentials(
@@ -128,8 +141,20 @@ class TestHostScopedCredentials:
             ("*.example.com", "https://sub.api.example.com/test", True),
             ("*.example.com", "https://example.com/test", True),
             ("*.example.com", "https://example.org/test", False),
-            ("localhost", "http://localhost:3000/test", True),
+            # Non-standard ports require explicit port in credential host
+            ("localhost", "http://localhost:3000/test", False),
+            ("localhost:3000", "http://localhost:3000/test", True),
             ("localhost", "http://127.0.0.1:3000/test", False),
+            # IPv6 addresses (frontend stores with brackets via URL.hostname)
+            ("[::1]", "http://[::1]/test", True),
+            ("[::1]", "http://[::1]:80/test", True),
+            ("[::1]", "https://[::1]:443/test", True),
+            ("[::1]", "http://[::1]:8080/test", False),  # Non-standard port
+            ("[::1]:8080", "http://[::1]:8080/test", True),
+            ("[::1]:8080", "http://[::1]:9090/test", False),
+            ("[2001:db8::1]", "http://[2001:db8::1]/path", True),
+            ("[2001:db8::1]", "https://[2001:db8::1]:443/path", True),
+            ("[2001:db8::1]", "http://[2001:db8::ff]/path", False),
         ],
     )
     def test_url_matching_parametrized(self, host: str, test_url: str, expected: bool):

autogpt_platform/backend/backend/util/request.py

@@ -157,12 +157,7 @@ async def validate_url(
         is_trusted: Boolean indicating if the hostname is in trusted_origins
         ip_addresses: List of IP addresses for the host; empty if the host is trusted
     """
-    # Canonicalize URL
-    url = url.strip("/ ").replace("\\", "/")
-    parsed = urlparse(url)
-    if not parsed.scheme:
-        url = f"http://{url}"
-        parsed = urlparse(url)
+    parsed = parse_url(url)
 
     # Check scheme
     if parsed.scheme not in ALLOWED_SCHEMES:
@@ -220,6 +215,17 @@ async def validate_url(
     )
 
 
+def parse_url(url: str) -> URL:
+    """Canonicalizes and parses a URL string."""
+    url = url.strip("/ ").replace("\\", "/")
+
+    # Ensure scheme is present for proper parsing
+    if not re.match(r"[a-z0-9+.\-]+://", url):
+        url = f"http://{url}"
+
+    return urlparse(url)
+
+
 def pin_url(url: URL, ip_addresses: Optional[list[str]] = None) -> URL:
     """
     Pins a URL to a specific IP address to prevent DNS rebinding attacks.

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

@@ -26,8 +26,20 @@ export function buildCopilotChatUrl(prompt: string): string {
 
 export function getQuickActions(): string[] {
   return [
-    "Show me what I can automate",
-    "Design a custom workflow",
-    "Help me with content creation",
+    "I don't know where to start, just ask me stuff",
+    "I do the same thing every week and it's killing me",
+    "Help me find where I'm wasting my time",
   ];
 }
+
+export function getInputPlaceholder(width?: number) {
+  if (!width) return "What's your role and what eats up most of your day?";
+
+  if (width < 500) {
+    return "I'm a chef and I hate...";
+  }
+  if (width <= 1080) {
+    return "What's your role and what eats up most of your day?";
+  }
+  return "What's your role and what eats up most of your day? e.g. 'I'm a recruiter and I hate...'";
+}

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

@@ -6,7 +6,9 @@ import { Text } from "@/components/atoms/Text/Text";
 import { Chat } from "@/components/contextual/Chat/Chat";
 import { ChatInput } from "@/components/contextual/Chat/components/ChatInput/ChatInput";
 import { Dialog } from "@/components/molecules/Dialog/Dialog";
+import { useEffect, useState } from "react";
 import { useCopilotStore } from "./copilot-page-store";
+import { getInputPlaceholder } from "./helpers";
 import { useCopilotPage } from "./useCopilotPage";
 
 export default function CopilotPage() {
@@ -14,8 +16,25 @@ export default function CopilotPage() {
   const isInterruptModalOpen = useCopilotStore((s) => s.isInterruptModalOpen);
   const confirmInterrupt = useCopilotStore((s) => s.confirmInterrupt);
   const cancelInterrupt = useCopilotStore((s) => s.cancelInterrupt);
+
+  const [inputPlaceholder, setInputPlaceholder] = useState(
+    getInputPlaceholder(),
+  );
+
+  useEffect(() => {
+    const handleResize = () => {
+      setInputPlaceholder(getInputPlaceholder(window.innerWidth));
+    };
+
+    handleResize();
+
+    window.addEventListener("resize", handleResize);
+    return () => window.removeEventListener("resize", handleResize);
+  }, []);
+
   const { greetingName, quickActions, isLoading, hasSession, initialPrompt } =
     state;
+
   const {
     handleQuickAction,
     startChatWithPrompt,
@@ -73,7 +92,7 @@ export default function CopilotPage() {
   }
 
   return (
-    <div className="flex h-full flex-1 items-center justify-center overflow-y-auto bg-[#f8f8f9] px-6 py-10">
+    <div className="flex h-full flex-1 items-center justify-center overflow-y-auto bg-[#f8f8f9] px-3 py-5 md:px-6 md:py-10">
       <div className="w-full text-center">
         {isLoading ? (
           <div className="mx-auto max-w-2xl">
@@ -90,25 +109,25 @@ export default function CopilotPage() {
           </div>
         ) : (
           <>
-            <div className="mx-auto max-w-2xl">
+            <div className="mx-auto max-w-3xl">
               <Text
                 variant="h3"
-                className="mb-3 !text-[1.375rem] text-zinc-700"
+                className="mb-1 !text-[1.375rem] text-zinc-700"
               >
                 Hey, <span className="text-violet-600">{greetingName}</span>
               </Text>
               <Text variant="h3" className="mb-8 !font-normal">
-                What do you want to automate?
+                Tell me about your work — I&apos;ll find what to automate.
               </Text>
 
               <div className="mb-6">
                 <ChatInput
                   onSend={startChatWithPrompt}
-                  placeholder='You can search or just ask - e.g. "create a blog post outline"'
+                  placeholder={inputPlaceholder}
                 />
               </div>
             </div>
-            <div className="flex flex-nowrap items-center justify-center gap-3 overflow-x-auto [-ms-overflow-style:none] [scrollbar-width:none] [&::-webkit-scrollbar]:hidden">
+            <div className="flex flex-wrap items-center justify-center gap-3 overflow-x-auto [-ms-overflow-style:none] [scrollbar-width:none] [&::-webkit-scrollbar]:hidden">
               {quickActions.map((action) => (
                 <Button
                   key={action}
@@ -116,7 +135,7 @@ export default function CopilotPage() {
                   variant="outline"
                   size="small"
                   onClick={() => handleQuickAction(action)}
-                  className="h-auto shrink-0 border-zinc-600 !px-4 !py-2 text-[1rem] text-zinc-600"
+                  className="h-auto shrink-0 border-zinc-300 px-3 py-2 text-[.9rem] text-zinc-600"
                 >
                   {action}
                 </Button>

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatContainer/ChatContainer.tsx

@@ -2,7 +2,6 @@ import type { SessionDetailResponse } from "@/app/api/__generated__/models/sessi
 import { Button } from "@/components/atoms/Button/Button";
 import { Text } from "@/components/atoms/Text/Text";
 import { Dialog } from "@/components/molecules/Dialog/Dialog";
-import { useBreakpoint } from "@/lib/hooks/useBreakpoint";
 import { cn } from "@/lib/utils";
 import { GlobeHemisphereEastIcon } from "@phosphor-icons/react";
 import { useEffect } from "react";
@@ -56,10 +55,6 @@ export function ChatContainer({
     onStreamingChange?.(isStreaming);
   }, [isStreaming, onStreamingChange]);
 
-  const breakpoint = useBreakpoint();
-  const isMobile =
-    breakpoint === "base" || breakpoint === "sm" || breakpoint === "md";
-
   return (
     <div
       className={cn(
@@ -127,11 +122,7 @@ export function ChatContainer({
           disabled={isStreaming || !sessionId}
           isStreaming={isStreaming}
           onStop={stopStreaming}
-          placeholder={
-            isMobile
-              ? "You can search or just ask"
-              : 'You can search or just ask — e.g. "create a blog post outline"'
-          }
+          placeholder="What else can I help with?"
         />
       </div>
     </div>

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/ChatInput.tsx

@@ -74,19 +74,20 @@ export function ChatInput({
             hasMultipleLines ? "rounded-xlarge" : "rounded-full",
           )}
         >
+          {!value && !isRecording && (
+            <div
+              className="pointer-events-none absolute inset-0 top-0.5 flex items-center justify-start pl-14 text-[1rem] text-zinc-400"
+              aria-hidden="true"
+            >
+              {isTranscribing ? "Transcribing..." : placeholder}
+            </div>
+          )}
           <textarea
             id={inputId}
             aria-label="Chat message input"
             value={value}
             onChange={handleChange}
             onKeyDown={handleKeyDown}
-            placeholder={
-              isTranscribing
-                ? "Transcribing..."
-                : isRecording
-                  ? ""
-                  : placeholder
-            }
             disabled={isInputDisabled}
             rows={1}
             className={cn(
@@ -122,13 +123,14 @@ export function ChatInput({
               size="icon"
               aria-label={isRecording ? "Stop recording" : "Start recording"}
               onClick={toggleRecording}
-              disabled={disabled || isTranscribing}
+              disabled={disabled || isTranscribing || isStreaming}
               className={cn(
                 isRecording
                   ? "animate-pulse border-red-500 bg-red-500 text-white hover:border-red-600 hover:bg-red-600"
                   : isTranscribing
                     ? "border-zinc-300 bg-zinc-100 text-zinc-400"
                     : "border-zinc-300 bg-white text-zinc-500 hover:border-zinc-400 hover:bg-zinc-50 hover:text-zinc-700",
+                isStreaming && "opacity-40",
               )}
             >
               {isTranscribing ? (

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/components/AudioWaveform.tsx

@@ -38,8 +38,8 @@ export function AudioWaveform({
     // Create audio context and analyser
     const audioContext = new AudioContext();
     const analyser = audioContext.createAnalyser();
-    analyser.fftSize = 512;
-    analyser.smoothingTimeConstant = 0.8;
+    analyser.fftSize = 256;
+    analyser.smoothingTimeConstant = 0.3;
 
     // Connect the stream to the analyser
     const source = audioContext.createMediaStreamSource(stream);
@@ -73,10 +73,11 @@ export function AudioWaveform({
           maxAmplitude = Math.max(maxAmplitude, amplitude);
         }
 
-        // Map amplitude (0-128) to bar height
-        const normalized = (maxAmplitude / 128) * 255;
-        const height =
-          minBarHeight + (normalized / 255) * (maxBarHeight - minBarHeight);
+        // Normalize amplitude (0-128 range) to 0-1
+        const normalized = maxAmplitude / 128;
+        // Apply sensitivity boost (multiply by 4) and use sqrt curve to amplify quiet sounds
+        const boosted = Math.min(1, Math.sqrt(normalized) * 4);
+        const height = minBarHeight + boosted * (maxBarHeight - minBarHeight);
         newBars.push(height);
       }
 

autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/useVoiceRecording.ts

@@ -224,7 +224,7 @@ export function useVoiceRecording({
     [value, isTranscribing, toggleRecording, baseHandleKeyDown],
   );
 
-  const showMicButton = isSupported && !isStreaming;
+  const showMicButton = isSupported;
   const isInputDisabled = disabled || isStreaming || isTranscribing;
 
   // Cleanup on unmount

autogpt_platform/frontend/src/components/contextual/Chat/components/ThinkingMessage/ThinkingMessage.tsx

@@ -1,6 +1,8 @@
+import { Progress } from "@/components/atoms/Progress/Progress";
 import { cn } from "@/lib/utils";
 import { useEffect, useRef, useState } from "react";
 import { AIChatBubble } from "../AIChatBubble/AIChatBubble";
+import { useAsymptoticProgress } from "../ToolCallMessage/useAsymptoticProgress";
 
 export interface ThinkingMessageProps {
   className?: string;
@@ -11,6 +13,7 @@ export function ThinkingMessage({ className }: ThinkingMessageProps) {
   const [showCoffeeMessage, setShowCoffeeMessage] = useState(false);
   const timerRef = useRef<NodeJS.Timeout | null>(null);
   const coffeeTimerRef = useRef<NodeJS.Timeout | null>(null);
+  const progress = useAsymptoticProgress(showCoffeeMessage);
 
   useEffect(() => {
     if (timerRef.current === null) {
@@ -49,9 +52,18 @@ export function ThinkingMessage({ className }: ThinkingMessageProps) {
           <AIChatBubble>
             <div className="transition-all duration-500 ease-in-out">
               {showCoffeeMessage ? (
-                <span className="inline-block animate-shimmer bg-gradient-to-r from-neutral-400 via-neutral-600 to-neutral-400 bg-[length:200%_100%] bg-clip-text text-transparent">
-                  This could take a few minutes, grab a coffee ☕️
-                </span>
+                <div className="flex flex-col items-center gap-3">
+                  <div className="flex w-full max-w-[280px] flex-col gap-1.5">
+                    <div className="flex items-center justify-between text-xs text-neutral-500">
+                      <span>Working on it...</span>
+                      <span>{Math.round(progress)}%</span>
+                    </div>
+                    <Progress value={progress} className="h-2 w-full" />
+                  </div>
+                  <span className="inline-block animate-shimmer bg-gradient-to-r from-neutral-400 via-neutral-600 to-neutral-400 bg-[length:200%_100%] bg-clip-text text-transparent">
+                    This could take a few minutes, grab a coffee ☕️
+                  </span>
+                </div>
               ) : showSlowLoader ? (
                 <span className="inline-block animate-shimmer bg-gradient-to-r from-neutral-400 via-neutral-600 to-neutral-400 bg-[length:200%_100%] bg-clip-text text-transparent">
                   Taking a bit more time...

autogpt_platform/frontend/src/components/contextual/Chat/components/ToolCallMessage/useAsymptoticProgress.ts

@@ -0,0 +1,50 @@
+import { useEffect, useRef, useState } from "react";
+
+/**
+ * Hook that returns a progress value that starts fast and slows down,
+ * asymptotically approaching but never reaching the max value.
+ *
+ * Uses a half-life formula: progress = max * (1 - 0.5^(time/halfLife))
+ * This creates the "game loading bar" effect where:
+ * - 50% is reached at halfLifeSeconds
+ * - 75% is reached at 2 * halfLifeSeconds
+ * - 87.5% is reached at 3 * halfLifeSeconds
+ * - and so on...
+ *
+ * @param isActive - Whether the progress should be animating
+ * @param halfLifeSeconds - Time in seconds to reach 50% progress (default: 30)
+ * @param maxProgress - Maximum progress value to approach (default: 100)
+ * @param intervalMs - Update interval in milliseconds (default: 100)
+ * @returns Current progress value (0-maxProgress)
+ */
+export function useAsymptoticProgress(
+  isActive: boolean,
+  halfLifeSeconds = 30,
+  maxProgress = 100,
+  intervalMs = 100,
+) {
+  const [progress, setProgress] = useState(0);
+  const elapsedTimeRef = useRef(0);
+
+  useEffect(() => {
+    if (!isActive) {
+      setProgress(0);
+      elapsedTimeRef.current = 0;
+      return;
+    }
+
+    const interval = setInterval(() => {
+      elapsedTimeRef.current += intervalMs / 1000;
+      // Half-life approach: progress = max * (1 - 0.5^(time/halfLife))
+      // At t=halfLife: 50%, at t=2*halfLife: 75%, at t=3*halfLife: 87.5%, etc.
+      const newProgress =
+        maxProgress *
+        (1 - Math.pow(0.5, elapsedTimeRef.current / halfLifeSeconds));
+      setProgress(newProgress);
+    }, intervalMs);
+
+    return () => clearInterval(interval);
+  }, [isActive, halfLifeSeconds, maxProgress, intervalMs]);
+
+  return progress;
+}

autogpt_platform/frontend/src/components/contextual/CredentialsInput/components/HotScopedCredentialsModal/HotScopedCredentialsModal.tsx

@@ -41,7 +41,17 @@ export function HostScopedCredentialsModal({
   const currentHost = currentUrl ? getHostFromUrl(currentUrl) : "";
 
   const formSchema = z.object({
-    host: z.string().min(1, "Host is required"),
+    host: z
+      .string()
+      .min(1, "Host is required")
+      .refine((val) => !/^[a-zA-Z][a-zA-Z\d+\-.]*:\/\//.test(val), {
+        message: "Enter only the host (e.g. api.example.com), not a full URL",
+      })
+      .refine((val) => !val.includes("/"), {
+        message:
+          "Enter only the host (e.g. api.example.com), without a trailing path. " +
+          "You may specify a port (e.g. api.example.com:8080) if needed.",
+      }),
     title: z.string().optional(),
     headers: z.record(z.string()).optional(),
   });

docs/integrations/README.md

@@ -62,7 +62,6 @@ Below is a comprehensive list of all available blocks, categorized by their prim
 | [Get Store Agent Details](block-integrations/system/store_operations.md#get-store-agent-details) | Get detailed information about an agent from the store |
 | [Get Weather Information](block-integrations/basic.md#get-weather-information) | Retrieves weather information for a specified location using OpenWeatherMap API |
 | [Human In The Loop](block-integrations/basic.md#human-in-the-loop) | Pause execution and wait for human approval or modification of data |
-| [Linear Search Issues](block-integrations/linear/issues.md#linear-search-issues) | Searches for issues on Linear |
 | [List Is Empty](block-integrations/basic.md#list-is-empty) | Checks if a list is empty |
 | [List Library Agents](block-integrations/system/library_operations.md#list-library-agents) | List all agents in your personal library |
 | [Note](block-integrations/basic.md#note) | A visual annotation block that displays a sticky note in the workflow editor for documentation and organization purposes |
@@ -193,7 +192,6 @@ Below is a comprehensive list of all available blocks, categorized by their prim
 | [Get Current Time](block-integrations/text.md#get-current-time) | This block outputs the current time |
 | [Match Text Pattern](block-integrations/text.md#match-text-pattern) | Matches text against a regex pattern and forwards data to positive or negative output based on the match |
 | [Text Decoder](block-integrations/text.md#text-decoder) | Decodes a string containing escape sequences into actual text |
-| [Text Encoder](block-integrations/text.md#text-encoder) | Encodes a string by converting special characters into escape sequences |
 | [Text Replace](block-integrations/text.md#text-replace) | This block is used to replace a text with a new text |
 | [Text Split](block-integrations/text.md#text-split) | This block is used to split a text into a list of strings |
 | [Word Character Count](block-integrations/text.md#word-character-count) | Counts the number of words and characters in a given text |
@@ -572,6 +570,7 @@ Below is a comprehensive list of all available blocks, categorized by their prim
 | [Linear Create Comment](block-integrations/linear/comment.md#linear-create-comment) | Creates a new comment on a Linear issue |
 | [Linear Create Issue](block-integrations/linear/issues.md#linear-create-issue) | Creates a new issue on Linear |
 | [Linear Get Project Issues](block-integrations/linear/issues.md#linear-get-project-issues) | Gets issues from a Linear project filtered by status and assignee |
+| [Linear Search Issues](block-integrations/linear/issues.md#linear-search-issues) | Searches for issues on Linear |
 | [Linear Search Projects](block-integrations/linear/projects.md#linear-search-projects) | Searches for projects on Linear |
 
 ## Hardware

docs/integrations/block-integrations/linear/issues.md

@@ -90,9 +90,9 @@ Searches for issues on Linear
 
 ### How it works
 <!-- MANUAL: how_it_works -->
-This block searches for issues in Linear using a text query. It searches across issue titles, descriptions, and other fields to find matching issues.
+This block searches for issues in Linear using a text query. It searches across issue titles, descriptions, and other fields to find matching issues. You can limit the number of results returned using the `max_results` parameter (default: 10, max: 100) to control token consumption and response size.
 
-Returns a list of issues matching the search term.
+Optionally filter results by team name to narrow searches to specific workspaces. If a team name is provided, the block resolves it to a team ID before searching. Returns matching issues with their state, creation date, project, and assignee information. If the search or team resolution fails, an error message is returned.
 <!-- END MANUAL -->
 
 ### Inputs
@@ -100,12 +100,14 @@ Returns a list of issues matching the search term.
 | Input | Description | Type | Required |
 |-------|-------------|------|----------|
 | term | Term to search for issues | str | Yes |
+| max_results | Maximum number of results to return | int | No |
+| team_name | Optional team name to filter results (e.g., 'Internal', 'Open Source') | str | No |
 
 ### Outputs
 
 | Output | Description | Type |
 |--------|-------------|------|
-| error | Error message if the operation failed | str |
+| error | Error message if the search failed | str |
 | issues | List of issues | List[Issue] |
 
 ### Possible use case

docs/integrations/block-integrations/text.md

@@ -380,42 +380,6 @@ This is useful when working with data from APIs or files where escape sequences
 
 ---
 
-## Text Encoder
-
-### What it is
-Encodes a string by converting special characters into escape sequences
-
-### How it works
-<!-- MANUAL: how_it_works -->
-The Text Encoder takes the input string and applies Python's `unicode_escape` encoding (equivalent to `codecs.encode(text, "unicode_escape").decode("utf-8")`) to transform special characters like newlines, tabs, and backslashes into their escaped forms.
-
-The block relies on the input schema to ensure the value is a string; non-string inputs are rejected by validation, and any encoding failures surface as block errors. Non-ASCII characters are emitted as `\uXXXX` sequences, which is useful for ASCII-only payloads.
-<!-- END MANUAL -->
-
-### Inputs
-
-| Input | Description | Type | Required |
-|-------|-------------|------|----------|
-| text | A string containing special characters to be encoded | str | Yes |
-
-### Outputs
-
-| Output | Description | Type |
-|--------|-------------|------|
-| error | Error message if encoding fails | str |
-| encoded_text | The encoded text with special characters converted to escape sequences | str |
-
-### Possible use case
-<!-- MANUAL: use_case -->
-**JSON Payload Preparation**: Encode multiline or quoted text before embedding it in JSON string fields to ensure proper escaping.
-
-**Config/ENV Generation**: Convert template text into escaped strings for `.env` or YAML values that require special character handling.
-
-**Snapshot Fixtures**: Produce stable escaped strings for golden files or API tests where consistent text representation is needed.
-<!-- END MANUAL -->
-
----
-
 ## Text Replace
 
 ### What it is