Files
deerflow-factory/deer-flow/skills/public/claude-to-deerflow/scripts/chat.sh
DATA 6de0bf9f5b Initial commit: hardened DeerFlow factory
Vendored deer-flow upstream (bytedance/deer-flow) plus prompt-injection
hardening:

- New deerflow.security package: content_delimiter, html_cleaner,
  sanitizer (8 layers — invisible chars, control chars, symbols, NFC,
  PUA, tag chars, horizontal whitespace collapse with newline/tab
  preservation, length cap)
- New deerflow.community.searx package: web_search, web_fetch,
  image_search backed by a private SearX instance, every external
  string sanitized and wrapped in <<<EXTERNAL_UNTRUSTED_CONTENT>>>
  delimiters
- All native community web providers (ddg_search, tavily, exa,
  firecrawl, jina_ai, infoquest, image_search) replaced with hard-fail
  stubs that raise NativeWebToolDisabledError at import time, so a
  misconfigured tool.use path fails loud rather than silently falling
  back to unsanitized output
- Native client back-doors (jina_client.py, infoquest_client.py)
  stubbed too
- Native-tool tests quarantined under tests/_disabled_native/
  (collect_ignore_glob via local conftest.py)
- Sanitizer Layer 7 fix: only collapse horizontal whitespace, preserve
  newlines and tabs so list/table structure survives
- Hardened runtime config.yaml references only the searx-backed tools
- Factory overlay (backend/) kept in sync with deer-flow tree as a
  reference / source

See HARDENING.md for the full audit trail and verification steps.
2026-04-12 14:23:57 +02:00

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#!/usr/bin/env bash
# chat.sh — Send a message to DeerFlow and collect the streaming response.
#
# Usage:
# bash chat.sh "Your question here"
# bash chat.sh "Your question" <thread_id> # continue conversation
# bash chat.sh "Your question" "" pro # specify mode
# DEERFLOW_URL=http://host:2026 bash chat.sh "hi" # custom endpoint
#
# Environment variables:
# DEERFLOW_URL — Unified proxy base URL (default: http://localhost:2026)
# DEERFLOW_GATEWAY_URL — Gateway API base URL (default: $DEERFLOW_URL)
# DEERFLOW_LANGGRAPH_URL — LangGraph API base URL (default: $DEERFLOW_URL/api/langgraph)
#
# Modes: flash, standard, pro (default), ultra
set -euo pipefail
DEERFLOW_URL="${DEERFLOW_URL:-http://localhost:2026}"
GATEWAY_URL="${DEERFLOW_GATEWAY_URL:-$DEERFLOW_URL}"
LANGGRAPH_URL="${DEERFLOW_LANGGRAPH_URL:-$DEERFLOW_URL/api/langgraph}"
MESSAGE="${1:?Usage: chat.sh <message> [thread_id] [mode]}"
THREAD_ID="${2:-}"
MODE="${3:-pro}"
# --- Health check ---
HTTP_CODE=$(curl -s -o /dev/null -w "%{http_code}" "${GATEWAY_URL}/health" 2>/dev/null || echo "000")
if [ "$HTTP_CODE" = "000" ] || [ "$HTTP_CODE" -ge 400 ]; then
echo "ERROR: DeerFlow is not reachable at ${GATEWAY_URL} (HTTP ${HTTP_CODE})" >&2
echo "Make sure DeerFlow is running. Start it with: cd <deerflow-dir> && make dev" >&2
exit 1
fi
# --- Create or reuse thread ---
if [ -z "$THREAD_ID" ]; then
THREAD_RESP=$(curl -s -X POST "${LANGGRAPH_URL}/threads" \
-H "Content-Type: application/json" \
-d '{}')
THREAD_ID=$(echo "$THREAD_RESP" | python3 -c "import sys,json; print(json.load(sys.stdin)['thread_id'])" 2>/dev/null)
if [ -z "$THREAD_ID" ]; then
echo "ERROR: Failed to create thread. Response: ${THREAD_RESP}" >&2
exit 1
fi
echo "Thread: ${THREAD_ID}" >&2
fi
# --- Build context based on mode ---
case "$MODE" in
flash)
CONTEXT='{"thinking_enabled":false,"is_plan_mode":false,"subagent_enabled":false,"thread_id":"'"$THREAD_ID"'"}'
;;
standard)
CONTEXT='{"thinking_enabled":true,"is_plan_mode":false,"subagent_enabled":false,"thread_id":"'"$THREAD_ID"'"}'
;;
pro)
CONTEXT='{"thinking_enabled":true,"is_plan_mode":true,"subagent_enabled":false,"thread_id":"'"$THREAD_ID"'"}'
;;
ultra)
CONTEXT='{"thinking_enabled":true,"is_plan_mode":true,"subagent_enabled":true,"thread_id":"'"$THREAD_ID"'"}'
;;
*)
echo "ERROR: Unknown mode '${MODE}'. Use: flash, standard, pro, ultra" >&2
exit 1
;;
esac
# --- Escape message for JSON ---
ESCAPED_MSG=$(python3 -c "import json,sys; print(json.dumps(sys.argv[1]))" "$MESSAGE")
# --- Build request body ---
BODY=$(cat <<ENDJSON
{
"assistant_id": "lead_agent",
"input": {
"messages": [
{
"type": "human",
"content": [{"type": "text", "text": ${ESCAPED_MSG}}]
}
]
},
"stream_mode": ["values", "messages-tuple"],
"stream_subgraphs": true,
"config": {
"recursion_limit": 1000
},
"context": ${CONTEXT}
}
ENDJSON
)
# --- Stream the run and extract final response ---
# We collect the full SSE output, then parse the last values event to get the AI response.
TMPFILE=$(mktemp)
trap "rm -f '$TMPFILE'" EXIT
curl -s -N -X POST "${LANGGRAPH_URL}/threads/${THREAD_ID}/runs/stream" \
-H "Content-Type: application/json" \
-d "$BODY" > "$TMPFILE"
# Parse the SSE output: extract the last "event: values" data block and get the final AI message
python3 - "$TMPFILE" "$GATEWAY_URL" "$THREAD_ID" << 'PYEOF'
import json
import sys
sse_file = sys.argv[1] if len(sys.argv) > 1 else None
gateway_url = sys.argv[2].rstrip("/") if len(sys.argv) > 2 else "http://localhost:2026"
thread_id = sys.argv[3] if len(sys.argv) > 3 else ""
if not sse_file:
sys.exit(1)
with open(sse_file, "r") as f:
raw = f.read()
# Parse SSE events
events = []
current_event = None
current_data_lines = []
for line in raw.split("\n"):
if line.startswith("event:"):
if current_event and current_data_lines:
events.append((current_event, "\n".join(current_data_lines)))
current_event = line[len("event:"):].strip()
current_data_lines = []
elif line.startswith("data:"):
current_data_lines.append(line[len("data:"):].strip())
elif line == "" and current_event:
if current_data_lines:
events.append((current_event, "\n".join(current_data_lines)))
current_event = None
current_data_lines = []
# Flush remaining
if current_event and current_data_lines:
events.append((current_event, "\n".join(current_data_lines)))
import posixpath
def extract_response_text(messages):
"""Mirror manager.py _extract_response_text: handles ask_clarification interrupt + regular AI."""
for msg in reversed(messages):
if not isinstance(msg, dict):
continue
msg_type = msg.get("type")
# ask_clarification interrupt: tool message with name ask_clarification
if msg_type == "tool" and msg.get("name") == "ask_clarification":
content = msg.get("content", "")
if isinstance(content, str) and content:
return content
# Regular AI message
if msg_type == "ai":
content = msg.get("content", "")
if isinstance(content, str) and content:
return content
if isinstance(content, list):
parts = []
for block in content:
if isinstance(block, dict) and block.get("type") == "text":
parts.append(block.get("text", ""))
elif isinstance(block, str):
parts.append(block)
text = "".join(parts)
if text:
return text
return ""
def extract_artifacts(messages):
"""Mirror manager.py _extract_artifacts: only artifacts from the last response cycle."""
artifacts = []
for msg in reversed(messages):
if not isinstance(msg, dict):
continue
if msg.get("type") == "human":
break
if msg.get("type") == "ai":
for tc in msg.get("tool_calls", []):
if isinstance(tc, dict) and tc.get("name") == "present_files":
paths = tc.get("args", {}).get("filepaths", [])
if isinstance(paths, list):
artifacts.extend(p for p in paths if isinstance(p, str))
return artifacts
def artifact_url(virtual_path):
# virtual_path like /mnt/user-data/outputs/file.md
# API endpoint: {gateway}/api/threads/{thread_id}/artifacts/{path without leading slash}
path = virtual_path.lstrip("/")
return f"{gateway_url}/api/threads/{thread_id}/artifacts/{path}"
def format_artifact_text(artifacts):
urls = [artifact_url(p) for p in artifacts]
if len(urls) == 1:
return f"Created File: {urls[0]}"
return "Created Files:\n" + "\n".join(urls)
# Find the last "values" event with messages
result_messages = None
for event_type, data_str in reversed(events):
if event_type != "values":
continue
try:
data = json.loads(data_str)
except json.JSONDecodeError:
continue
if "messages" in data:
result_messages = data["messages"]
break
if result_messages is not None:
response_text = extract_response_text(result_messages)
artifacts = extract_artifacts(result_messages)
if artifacts:
artifact_text = format_artifact_text(artifacts)
response_text = (response_text + "\n\n" + artifact_text) if response_text else artifact_text
if response_text:
print(response_text)
else:
print("(No response from agent)", file=sys.stderr)
sys.exit(1)
else:
# Check for error events
for event_type, data_str in events:
if event_type == "error":
print(f"ERROR from DeerFlow: {data_str}", file=sys.stderr)
sys.exit(1)
print("No AI response found in the stream.", file=sys.stderr)
if len(raw) < 2000:
print(f"Raw SSE output:\n{raw}", file=sys.stderr)
sys.exit(1)
PYEOF
echo ""
echo "---"
echo "Thread ID: ${THREAD_ID}" >&2