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devin/1762
| Author | SHA1 | Date | |
|---|---|---|---|
|
8c0da6c129 |
18
.github/workflows/tests.yml
vendored
18
.github/workflows/tests.yml
vendored
@@ -5,6 +5,18 @@ on: [pull_request]
|
||||
permissions:
|
||||
contents: read
|
||||
|
||||
env:
|
||||
OPENAI_API_KEY: fake-api-key
|
||||
PYTHONUNBUFFERED: 1
|
||||
BRAVE_API_KEY: fake-brave-key
|
||||
SNOWFLAKE_USER: fake-snowflake-user
|
||||
SNOWFLAKE_PASSWORD: fake-snowflake-password
|
||||
SNOWFLAKE_ACCOUNT: fake-snowflake-account
|
||||
SNOWFLAKE_WAREHOUSE: fake-snowflake-warehouse
|
||||
SNOWFLAKE_DATABASE: fake-snowflake-database
|
||||
SNOWFLAKE_SCHEMA: fake-snowflake-schema
|
||||
EMBEDCHAIN_DB_URI: sqlite:///test.db
|
||||
|
||||
jobs:
|
||||
tests:
|
||||
name: tests (${{ matrix.python-version }})
|
||||
@@ -72,20 +84,26 @@ jobs:
|
||||
# fi
|
||||
|
||||
cd lib/crewai && uv run pytest \
|
||||
--block-network \
|
||||
--timeout=30 \
|
||||
-vv \
|
||||
--splits 8 \
|
||||
--group ${{ matrix.group }} \
|
||||
$DURATIONS_ARG \
|
||||
--durations=10 \
|
||||
-n auto \
|
||||
--maxfail=3
|
||||
|
||||
- name: Run tool tests (group ${{ matrix.group }} of 8)
|
||||
run: |
|
||||
cd lib/crewai-tools && uv run pytest \
|
||||
--block-network \
|
||||
--timeout=30 \
|
||||
-vv \
|
||||
--splits 8 \
|
||||
--group ${{ matrix.group }} \
|
||||
--durations=10 \
|
||||
-n auto \
|
||||
--maxfail=3
|
||||
|
||||
|
||||
|
||||
138
conftest.py
138
conftest.py
@@ -1,138 +0,0 @@
|
||||
"""Pytest configuration for crewAI workspace."""
|
||||
|
||||
import os
|
||||
from pathlib import Path
|
||||
import tempfile
|
||||
from typing import Any
|
||||
|
||||
import pytest
|
||||
|
||||
|
||||
# Load .env.test for consistent test environment
|
||||
# env_test_path = Path(__file__).parent / ".env.test"
|
||||
# load_dotenv(env_test_path, override=True)
|
||||
# load_dotenv(override=True)
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True, scope="function")
|
||||
def setup_test_environment() -> None: # type: ignore
|
||||
"""Set up test environment with a temporary directory for SQLite storage."""
|
||||
with tempfile.TemporaryDirectory() as temp_dir:
|
||||
# Create the directory with proper permissions
|
||||
storage_dir = Path(temp_dir) / "crewai_test_storage"
|
||||
storage_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
# Validate that the directory was created successfully
|
||||
if not storage_dir.exists() or not storage_dir.is_dir():
|
||||
raise RuntimeError(
|
||||
f"Failed to create test storage directory: {storage_dir}"
|
||||
)
|
||||
|
||||
# Verify directory permissions
|
||||
try:
|
||||
# Try to create a test file to verify write permissions
|
||||
test_file = storage_dir / ".permissions_test"
|
||||
test_file.touch()
|
||||
test_file.unlink()
|
||||
except (OSError, IOError) as e:
|
||||
raise RuntimeError(
|
||||
f"Test storage directory {storage_dir} is not writable: {e}"
|
||||
) from e
|
||||
|
||||
os.environ["CREWAI_STORAGE_DIR"] = str(storage_dir)
|
||||
os.environ["CREWAI_TESTING"] = "true"
|
||||
yield
|
||||
|
||||
os.environ.pop("CREWAI_TESTING", None)
|
||||
# Cleanup is handled automatically when tempfile context exits
|
||||
|
||||
|
||||
HEADERS_TO_FILTER = {
|
||||
"authorization": "AUTHORIZATION-XXX",
|
||||
"content-security-policy": "CSP-FILTERED",
|
||||
"cookie": "COOKIE-XXX",
|
||||
"set-cookie": "SET-COOKIE-XXX",
|
||||
"permissions-policy": "PERMISSIONS-POLICY-XXX",
|
||||
"referrer-policy": "REFERRER-POLICY-XXX",
|
||||
"strict-transport-security": "STS-XXX",
|
||||
"x-content-type-options": "X-CONTENT-TYPE-XXX",
|
||||
"x-frame-options": "X-FRAME-OPTIONS-XXX",
|
||||
"x-permitted-cross-domain-policies": "X-PERMITTED-XXX",
|
||||
"x-request-id": "X-REQUEST-ID-XXX",
|
||||
"x-runtime": "X-RUNTIME-XXX",
|
||||
"x-xss-protection": "X-XSS-PROTECTION-XXX",
|
||||
"x-stainless-arch": "X-STAINLESS-ARCH-XXX",
|
||||
"x-stainless-os": "X-STAINLESS-OS-XXX",
|
||||
"x-stainless-read-timeout": "X-STAINLESS-READ-TIMEOUT-XXX",
|
||||
"cf-ray": "CF-RAY-XXX",
|
||||
"etag": "ETAG-XXX",
|
||||
"Strict-Transport-Security": "STS-XXX",
|
||||
"access-control-expose-headers": "ACCESS-CONTROL-XXX",
|
||||
"openai-organization": "OPENAI-ORG-XXX",
|
||||
"openai-project": "OPENAI-PROJECT-XXX",
|
||||
"x-ratelimit-limit-requests": "X-RATELIMIT-LIMIT-REQUESTS-XXX",
|
||||
"x-ratelimit-limit-tokens": "X-RATELIMIT-LIMIT-TOKENS-XXX",
|
||||
"x-ratelimit-remaining-requests": "X-RATELIMIT-REMAINING-REQUESTS-XXX",
|
||||
"x-ratelimit-remaining-tokens": "X-RATELIMIT-REMAINING-TOKENS-XXX",
|
||||
"x-ratelimit-reset-requests": "X-RATELIMIT-RESET-REQUESTS-XXX",
|
||||
"x-ratelimit-reset-tokens": "X-RATELIMIT-RESET-TOKENS-XXX",
|
||||
}
|
||||
|
||||
|
||||
def _filter_response_headers(response) -> dict[str, Any]: # type: ignore
|
||||
"""Filter sensitive headers from response before recording."""
|
||||
for header_name, replacement in HEADERS_TO_FILTER.items():
|
||||
for variant in [header_name, header_name.upper(), header_name.title()]:
|
||||
if variant in response["headers"]:
|
||||
response["headers"][variant] = [replacement]
|
||||
return response # type: ignore
|
||||
|
||||
|
||||
@pytest.fixture(scope="module")
|
||||
def vcr_cassette_dir(request: Any) -> str:
|
||||
"""Generate cassette directory path based on test module location.
|
||||
|
||||
Organizes cassettes to mirror test directory structure within each package:
|
||||
lib/crewai/tests/llms/google/test_google.py -> lib/crewai/tests/cassettes/llms/google/
|
||||
lib/crewai-tools/tests/tools/test_search.py -> lib/crewai-tools/tests/cassettes/tools/
|
||||
"""
|
||||
test_file = Path(request.fspath)
|
||||
|
||||
# Find the package root (lib/crewai or lib/crewai-tools)
|
||||
for parent in test_file.parents:
|
||||
if parent.name in ("crewai", "crewai-tools") and parent.parent.name == "lib":
|
||||
package_root = parent
|
||||
break
|
||||
else:
|
||||
# Fallback to old behavior if we can't find package root
|
||||
package_root = test_file.parent
|
||||
|
||||
tests_root = package_root / "tests"
|
||||
test_dir = test_file.parent
|
||||
|
||||
# Get relative path from tests root
|
||||
if test_dir != tests_root:
|
||||
relative_path = test_dir.relative_to(tests_root)
|
||||
cassette_dir = tests_root / "cassettes" / relative_path
|
||||
else:
|
||||
cassette_dir = tests_root / "cassettes"
|
||||
|
||||
cassette_dir.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
return str(cassette_dir)
|
||||
|
||||
|
||||
@pytest.fixture(scope="module")
|
||||
def vcr_config(vcr_cassette_dir: str) -> dict[str, Any]:
|
||||
"""Configure VCR with organized cassette storage."""
|
||||
config = {
|
||||
"cassette_library_dir": vcr_cassette_dir,
|
||||
"record_mode": os.getenv("PYTEST_VCR_RECORD_MODE") or "once",
|
||||
"filter_headers": [(k, v) for k, v in HEADERS_TO_FILTER.items()],
|
||||
"before_record_response": _filter_response_headers,
|
||||
}
|
||||
|
||||
if os.getenv("GITHUB_ACTIONS") == "true":
|
||||
config["record_mode"] = "none"
|
||||
|
||||
return config
|
||||
@@ -1200,52 +1200,6 @@ Learn how to get the most out of your LLM configuration:
|
||||
)
|
||||
```
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="Transport Interceptors">
|
||||
CrewAI provides message interceptors for several providers, allowing you to hook into request/response cycles at the transport layer.
|
||||
|
||||
**Supported Providers:**
|
||||
- ✅ OpenAI
|
||||
- ✅ Anthropic
|
||||
|
||||
**Basic Usage:**
|
||||
```python
|
||||
import httpx
|
||||
from crewai import LLM
|
||||
from crewai.llms.hooks import BaseInterceptor
|
||||
|
||||
class CustomInterceptor(BaseInterceptor[httpx.Request, httpx.Response]):
|
||||
"""Custom interceptor to modify requests and responses."""
|
||||
|
||||
def on_outbound(self, request: httpx.Request) -> httpx.Request:
|
||||
"""Print request before sending to the LLM provider."""
|
||||
print(request)
|
||||
return request
|
||||
|
||||
def on_inbound(self, response: httpx.Response) -> httpx.Response:
|
||||
"""Process response after receiving from the LLM provider."""
|
||||
print(f"Status: {response.status_code}")
|
||||
print(f"Response time: {response.elapsed}")
|
||||
return response
|
||||
|
||||
# Use the interceptor with an LLM
|
||||
llm = LLM(
|
||||
model="openai/gpt-4o",
|
||||
interceptor=CustomInterceptor()
|
||||
)
|
||||
```
|
||||
|
||||
**Important Notes:**
|
||||
- Both methods must return the received object or type of object.
|
||||
- Modifying received objects may result in unexpected behavior or application crashes.
|
||||
- Not all providers support interceptors - check the supported providers list above
|
||||
|
||||
<Info>
|
||||
Interceptors operate at the transport layer. This is particularly useful for:
|
||||
- Message transformation and filtering
|
||||
- Debugging API interactions
|
||||
</Info>
|
||||
</Accordion>
|
||||
</AccordionGroup>
|
||||
|
||||
## Common Issues and Solutions
|
||||
|
||||
@@ -11,13 +11,9 @@ The [Model Context Protocol](https://modelcontextprotocol.io/introduction) (MCP)
|
||||
|
||||
CrewAI offers **two approaches** for MCP integration:
|
||||
|
||||
### 🚀 **Simple DSL Integration** (Recommended)
|
||||
### Simple DSL Integration** (Recommended)
|
||||
|
||||
Use the `mcps` field directly on agents for seamless MCP tool integration. The DSL supports both **string references** (for quick setup) and **structured configurations** (for full control).
|
||||
|
||||
#### String-Based References (Quick Setup)
|
||||
|
||||
Perfect for remote HTTPS servers and CrewAI AMP marketplace:
|
||||
Use the `mcps` field directly on agents for seamless MCP tool integration:
|
||||
|
||||
```python
|
||||
from crewai import Agent
|
||||
@@ -36,46 +32,6 @@ agent = Agent(
|
||||
# MCP tools are now automatically available to your agent!
|
||||
```
|
||||
|
||||
#### Structured Configurations (Full Control)
|
||||
|
||||
For complete control over connection settings, tool filtering, and all transport types:
|
||||
|
||||
```python
|
||||
from crewai import Agent
|
||||
from crewai.mcp import MCPServerStdio, MCPServerHTTP, MCPServerSSE
|
||||
from crewai.mcp.filters import create_static_tool_filter
|
||||
|
||||
agent = Agent(
|
||||
role="Advanced Research Analyst",
|
||||
goal="Research with full control over MCP connections",
|
||||
backstory="Expert researcher with advanced tool access",
|
||||
mcps=[
|
||||
# Stdio transport for local servers
|
||||
MCPServerStdio(
|
||||
command="npx",
|
||||
args=["-y", "@modelcontextprotocol/server-filesystem"],
|
||||
env={"API_KEY": "your_key"},
|
||||
tool_filter=create_static_tool_filter(
|
||||
allowed_tool_names=["read_file", "list_directory"]
|
||||
),
|
||||
cache_tools_list=True,
|
||||
),
|
||||
# HTTP/Streamable HTTP transport for remote servers
|
||||
MCPServerHTTP(
|
||||
url="https://api.example.com/mcp",
|
||||
headers={"Authorization": "Bearer your_token"},
|
||||
streamable=True,
|
||||
cache_tools_list=True,
|
||||
),
|
||||
# SSE transport for real-time streaming
|
||||
MCPServerSSE(
|
||||
url="https://stream.example.com/mcp/sse",
|
||||
headers={"Authorization": "Bearer your_token"},
|
||||
),
|
||||
]
|
||||
)
|
||||
```
|
||||
|
||||
### 🔧 **Advanced: MCPServerAdapter** (For Complex Scenarios)
|
||||
|
||||
For advanced use cases requiring manual connection management, the `crewai-tools` library provides the `MCPServerAdapter` class.
|
||||
@@ -112,14 +68,12 @@ uv pip install 'crewai-tools[mcp]'
|
||||
|
||||
## Quick Start: Simple DSL Integration
|
||||
|
||||
The easiest way to integrate MCP servers is using the `mcps` field on your agents. You can use either string references or structured configurations.
|
||||
|
||||
### Quick Start with String References
|
||||
The easiest way to integrate MCP servers is using the `mcps` field on your agents:
|
||||
|
||||
```python
|
||||
from crewai import Agent, Task, Crew
|
||||
|
||||
# Create agent with MCP tools using string references
|
||||
# Create agent with MCP tools
|
||||
research_agent = Agent(
|
||||
role="Research Analyst",
|
||||
goal="Find and analyze information using advanced search tools",
|
||||
@@ -142,53 +96,13 @@ crew = Crew(agents=[research_agent], tasks=[research_task])
|
||||
result = crew.kickoff()
|
||||
```
|
||||
|
||||
### Quick Start with Structured Configurations
|
||||
|
||||
```python
|
||||
from crewai import Agent, Task, Crew
|
||||
from crewai.mcp import MCPServerStdio, MCPServerHTTP, MCPServerSSE
|
||||
|
||||
# Create agent with structured MCP configurations
|
||||
research_agent = Agent(
|
||||
role="Research Analyst",
|
||||
goal="Find and analyze information using advanced search tools",
|
||||
backstory="Expert researcher with access to multiple data sources",
|
||||
mcps=[
|
||||
# Local stdio server
|
||||
MCPServerStdio(
|
||||
command="python",
|
||||
args=["local_server.py"],
|
||||
env={"API_KEY": "your_key"},
|
||||
),
|
||||
# Remote HTTP server
|
||||
MCPServerHTTP(
|
||||
url="https://api.research.com/mcp",
|
||||
headers={"Authorization": "Bearer your_token"},
|
||||
),
|
||||
]
|
||||
)
|
||||
|
||||
# Create task
|
||||
research_task = Task(
|
||||
description="Research the latest developments in AI agent frameworks",
|
||||
expected_output="Comprehensive research report with citations",
|
||||
agent=research_agent
|
||||
)
|
||||
|
||||
# Create and run crew
|
||||
crew = Crew(agents=[research_agent], tasks=[research_task])
|
||||
result = crew.kickoff()
|
||||
```
|
||||
|
||||
That's it! The MCP tools are automatically discovered and available to your agent.
|
||||
|
||||
## MCP Reference Formats
|
||||
|
||||
The `mcps` field supports both **string references** (for quick setup) and **structured configurations** (for full control). You can mix both formats in the same list.
|
||||
The `mcps` field supports various reference formats for maximum flexibility:
|
||||
|
||||
### String-Based References
|
||||
|
||||
#### External MCP Servers
|
||||
### External MCP Servers
|
||||
|
||||
```python
|
||||
mcps=[
|
||||
@@ -203,7 +117,7 @@ mcps=[
|
||||
]
|
||||
```
|
||||
|
||||
#### CrewAI AMP Marketplace
|
||||
### CrewAI AMP Marketplace
|
||||
|
||||
```python
|
||||
mcps=[
|
||||
@@ -219,166 +133,17 @@ mcps=[
|
||||
]
|
||||
```
|
||||
|
||||
### Structured Configurations
|
||||
|
||||
#### Stdio Transport (Local Servers)
|
||||
|
||||
Perfect for local MCP servers that run as processes:
|
||||
|
||||
```python
|
||||
from crewai.mcp import MCPServerStdio
|
||||
from crewai.mcp.filters import create_static_tool_filter
|
||||
|
||||
mcps=[
|
||||
MCPServerStdio(
|
||||
command="npx",
|
||||
args=["-y", "@modelcontextprotocol/server-filesystem"],
|
||||
env={"API_KEY": "your_key"},
|
||||
tool_filter=create_static_tool_filter(
|
||||
allowed_tool_names=["read_file", "write_file"]
|
||||
),
|
||||
cache_tools_list=True,
|
||||
),
|
||||
# Python-based server
|
||||
MCPServerStdio(
|
||||
command="python",
|
||||
args=["path/to/server.py"],
|
||||
env={"UV_PYTHON": "3.12", "API_KEY": "your_key"},
|
||||
),
|
||||
]
|
||||
```
|
||||
|
||||
#### HTTP/Streamable HTTP Transport (Remote Servers)
|
||||
|
||||
For remote MCP servers over HTTP/HTTPS:
|
||||
|
||||
```python
|
||||
from crewai.mcp import MCPServerHTTP
|
||||
|
||||
mcps=[
|
||||
# Streamable HTTP (default)
|
||||
MCPServerHTTP(
|
||||
url="https://api.example.com/mcp",
|
||||
headers={"Authorization": "Bearer your_token"},
|
||||
streamable=True,
|
||||
cache_tools_list=True,
|
||||
),
|
||||
# Standard HTTP
|
||||
MCPServerHTTP(
|
||||
url="https://api.example.com/mcp",
|
||||
headers={"Authorization": "Bearer your_token"},
|
||||
streamable=False,
|
||||
),
|
||||
]
|
||||
```
|
||||
|
||||
#### SSE Transport (Real-Time Streaming)
|
||||
|
||||
For remote servers using Server-Sent Events:
|
||||
|
||||
```python
|
||||
from crewai.mcp import MCPServerSSE
|
||||
|
||||
mcps=[
|
||||
MCPServerSSE(
|
||||
url="https://stream.example.com/mcp/sse",
|
||||
headers={"Authorization": "Bearer your_token"},
|
||||
cache_tools_list=True,
|
||||
),
|
||||
]
|
||||
```
|
||||
|
||||
### Mixed References
|
||||
|
||||
You can combine string references and structured configurations:
|
||||
|
||||
```python
|
||||
from crewai.mcp import MCPServerStdio, MCPServerHTTP
|
||||
|
||||
mcps=[
|
||||
# String references
|
||||
"https://external-api.com/mcp", # External server
|
||||
"https://weather.service.com/mcp#forecast", # Specific external tool
|
||||
"crewai-amp:financial-insights", # AMP service
|
||||
|
||||
# Structured configurations
|
||||
MCPServerStdio(
|
||||
command="npx",
|
||||
args=["-y", "@modelcontextprotocol/server-filesystem"],
|
||||
),
|
||||
MCPServerHTTP(
|
||||
url="https://api.example.com/mcp",
|
||||
headers={"Authorization": "Bearer token"},
|
||||
),
|
||||
"crewai-amp:data-analysis#sentiment_tool" # Specific AMP tool
|
||||
]
|
||||
```
|
||||
|
||||
### Tool Filtering
|
||||
|
||||
Structured configurations support advanced tool filtering:
|
||||
|
||||
```python
|
||||
from crewai.mcp import MCPServerStdio
|
||||
from crewai.mcp.filters import create_static_tool_filter, create_dynamic_tool_filter, ToolFilterContext
|
||||
|
||||
# Static filtering (allow/block lists)
|
||||
static_filter = create_static_tool_filter(
|
||||
allowed_tool_names=["read_file", "write_file"],
|
||||
blocked_tool_names=["delete_file"],
|
||||
)
|
||||
|
||||
# Dynamic filtering (context-aware)
|
||||
def dynamic_filter(context: ToolFilterContext, tool: dict) -> bool:
|
||||
# Block dangerous tools for certain agent roles
|
||||
if context.agent.role == "Code Reviewer":
|
||||
if "delete" in tool.get("name", "").lower():
|
||||
return False
|
||||
return True
|
||||
|
||||
mcps=[
|
||||
MCPServerStdio(
|
||||
command="npx",
|
||||
args=["-y", "@modelcontextprotocol/server-filesystem"],
|
||||
tool_filter=static_filter, # or dynamic_filter
|
||||
),
|
||||
]
|
||||
```
|
||||
|
||||
## Configuration Parameters
|
||||
|
||||
Each transport type supports specific configuration options:
|
||||
|
||||
### MCPServerStdio Parameters
|
||||
|
||||
- **`command`** (required): Command to execute (e.g., `"python"`, `"node"`, `"npx"`, `"uvx"`)
|
||||
- **`args`** (optional): List of command arguments (e.g., `["server.py"]` or `["-y", "@mcp/server"]`)
|
||||
- **`env`** (optional): Dictionary of environment variables to pass to the process
|
||||
- **`tool_filter`** (optional): Tool filter function for filtering available tools
|
||||
- **`cache_tools_list`** (optional): Whether to cache the tool list for faster subsequent access (default: `False`)
|
||||
|
||||
### MCPServerHTTP Parameters
|
||||
|
||||
- **`url`** (required): Server URL (e.g., `"https://api.example.com/mcp"`)
|
||||
- **`headers`** (optional): Dictionary of HTTP headers for authentication or other purposes
|
||||
- **`streamable`** (optional): Whether to use streamable HTTP transport (default: `True`)
|
||||
- **`tool_filter`** (optional): Tool filter function for filtering available tools
|
||||
- **`cache_tools_list`** (optional): Whether to cache the tool list for faster subsequent access (default: `False`)
|
||||
|
||||
### MCPServerSSE Parameters
|
||||
|
||||
- **`url`** (required): Server URL (e.g., `"https://api.example.com/mcp/sse"`)
|
||||
- **`headers`** (optional): Dictionary of HTTP headers for authentication or other purposes
|
||||
- **`tool_filter`** (optional): Tool filter function for filtering available tools
|
||||
- **`cache_tools_list`** (optional): Whether to cache the tool list for faster subsequent access (default: `False`)
|
||||
|
||||
### Common Parameters
|
||||
|
||||
All transport types support:
|
||||
- **`tool_filter`**: Filter function to control which tools are available. Can be:
|
||||
- `None` (default): All tools are available
|
||||
- Static filter: Created with `create_static_tool_filter()` for allow/block lists
|
||||
- Dynamic filter: Created with `create_dynamic_tool_filter()` for context-aware filtering
|
||||
- **`cache_tools_list`**: When `True`, caches the tool list after first discovery to improve performance on subsequent connections
|
||||
|
||||
## Key Features
|
||||
|
||||
- 🔄 **Automatic Tool Discovery**: Tools are automatically discovered and integrated
|
||||
@@ -387,47 +152,26 @@ All transport types support:
|
||||
- 🛡️ **Error Resilience**: Graceful handling of unavailable servers
|
||||
- ⏱️ **Timeout Protection**: Built-in timeouts prevent hanging connections
|
||||
- 📊 **Transparent Integration**: Works seamlessly with existing CrewAI features
|
||||
- 🔧 **Full Transport Support**: Stdio, HTTP/Streamable HTTP, and SSE transports
|
||||
- 🎯 **Advanced Filtering**: Static and dynamic tool filtering capabilities
|
||||
- 🔐 **Flexible Authentication**: Support for headers, environment variables, and query parameters
|
||||
|
||||
## Error Handling
|
||||
|
||||
The MCP DSL integration is designed to be resilient and handles failures gracefully:
|
||||
The MCP DSL integration is designed to be resilient:
|
||||
|
||||
```python
|
||||
from crewai import Agent
|
||||
from crewai.mcp import MCPServerStdio, MCPServerHTTP
|
||||
|
||||
agent = Agent(
|
||||
role="Resilient Agent",
|
||||
goal="Continue working despite server issues",
|
||||
backstory="Agent that handles failures gracefully",
|
||||
mcps=[
|
||||
# String references
|
||||
"https://reliable-server.com/mcp", # Will work
|
||||
"https://unreachable-server.com/mcp", # Will be skipped gracefully
|
||||
"crewai-amp:working-service", # Will work
|
||||
|
||||
# Structured configs
|
||||
MCPServerStdio(
|
||||
command="python",
|
||||
args=["reliable_server.py"], # Will work
|
||||
),
|
||||
MCPServerHTTP(
|
||||
url="https://slow-server.com/mcp", # Will timeout gracefully
|
||||
),
|
||||
"https://slow-server.com/mcp", # Will timeout gracefully
|
||||
"crewai-amp:working-service" # Will work
|
||||
]
|
||||
)
|
||||
# Agent will use tools from working servers and log warnings for failing ones
|
||||
```
|
||||
|
||||
All connection errors are handled gracefully:
|
||||
- **Connection failures**: Logged as warnings, agent continues with available tools
|
||||
- **Timeout errors**: Connections timeout after 30 seconds (configurable)
|
||||
- **Authentication errors**: Logged clearly for debugging
|
||||
- **Invalid configurations**: Validation errors are raised at agent creation time
|
||||
|
||||
## Advanced: MCPServerAdapter
|
||||
|
||||
For complex scenarios requiring manual connection management, use the `MCPServerAdapter` class from `crewai-tools`. Using a Python context manager (`with` statement) is the recommended approach as it automatically handles starting and stopping the connection to the MCP server.
|
||||
|
||||
@@ -7,12 +7,11 @@ from pathlib import Path
|
||||
from typing import Any, cast
|
||||
|
||||
from crewai.tools.base_tool import BaseTool, EnvVar
|
||||
from crewai_tools import tools
|
||||
from pydantic import BaseModel
|
||||
from pydantic.json_schema import GenerateJsonSchema
|
||||
from pydantic_core import PydanticOmit
|
||||
|
||||
from crewai_tools import tools
|
||||
|
||||
|
||||
class SchemaGenerator(GenerateJsonSchema):
|
||||
def handle_invalid_for_json_schema(self, schema, error_info):
|
||||
@@ -12,7 +12,7 @@ dependencies = [
|
||||
"pytube>=15.0.0",
|
||||
"requests>=2.32.5",
|
||||
"docker>=7.1.0",
|
||||
"crewai==1.4.1",
|
||||
"crewai==1.3.0",
|
||||
"lancedb>=0.5.4",
|
||||
"tiktoken>=0.8.0",
|
||||
"beautifulsoup4>=4.13.4",
|
||||
|
||||
@@ -287,4 +287,4 @@ __all__ = [
|
||||
"ZapierActionTools",
|
||||
]
|
||||
|
||||
__version__ = "1.4.1"
|
||||
__version__ = "1.3.0"
|
||||
|
||||
@@ -229,7 +229,6 @@ class CrewAIRagAdapter(Adapter):
|
||||
continue
|
||||
else:
|
||||
metadata: dict[str, Any] = base_metadata.copy()
|
||||
source_content = SourceContent(source_ref)
|
||||
|
||||
if data_type in [
|
||||
DataType.PDF_FILE,
|
||||
@@ -240,12 +239,13 @@ class CrewAIRagAdapter(Adapter):
|
||||
DataType.XML,
|
||||
DataType.MDX,
|
||||
]:
|
||||
if not source_content.is_url() and not source_content.path_exists():
|
||||
if not os.path.isfile(source_ref):
|
||||
raise FileNotFoundError(f"File does not exist: {source_ref}")
|
||||
|
||||
loader = data_type.get_loader()
|
||||
chunker = data_type.get_chunker()
|
||||
|
||||
source_content = SourceContent(source_ref)
|
||||
loader_result: LoaderResult = loader.load(source_content)
|
||||
|
||||
chunks = chunker.chunk(loader_result.content)
|
||||
|
||||
@@ -91,7 +91,7 @@ class EmbeddingService:
|
||||
"azure": "AZURE_OPENAI_API_KEY",
|
||||
"amazon-bedrock": "AWS_ACCESS_KEY_ID", # or AWS_PROFILE
|
||||
"cohere": "COHERE_API_KEY",
|
||||
"google-generativeai": "GEMINI_API_KEY",
|
||||
"google-generativeai": "GOOGLE_API_KEY",
|
||||
"google-vertex": "GOOGLE_APPLICATION_CREDENTIALS",
|
||||
"huggingface": "HUGGINGFACE_API_KEY",
|
||||
"jina": "JINA_API_KEY",
|
||||
|
||||
@@ -247,7 +247,7 @@ class StagehandTool(BaseTool):
|
||||
if "claude" in model_str.lower() or "anthropic" in model_str.lower():
|
||||
return self.model_api_key or os.getenv("ANTHROPIC_API_KEY")
|
||||
if "gemini" in model_str.lower():
|
||||
return self.model_api_key or os.getenv("GEMINI_API_KEY")
|
||||
return self.model_api_key or os.getenv("GOOGLE_API_KEY")
|
||||
# Default to trying OpenAI, then Anthropic
|
||||
return (
|
||||
self.model_api_key
|
||||
@@ -313,7 +313,7 @@ class StagehandTool(BaseTool):
|
||||
|
||||
if not model_api_key:
|
||||
raise ValueError(
|
||||
"No appropriate API key found for model. Please set OPENAI_API_KEY, ANTHROPIC_API_KEY, or GEMINI_API_KEY"
|
||||
"No appropriate API key found for model. Please set OPENAI_API_KEY, ANTHROPIC_API_KEY, or GOOGLE_API_KEY"
|
||||
)
|
||||
|
||||
# Build the StagehandConfig with proper parameter names
|
||||
|
||||
21
lib/crewai-tools/tests/it/tools/conftest.py
Normal file
21
lib/crewai-tools/tests/it/tools/conftest.py
Normal file
@@ -0,0 +1,21 @@
|
||||
import pytest
|
||||
|
||||
|
||||
def pytest_configure(config):
|
||||
"""Register custom markers."""
|
||||
config.addinivalue_line("markers", "integration: mark test as an integration test")
|
||||
config.addinivalue_line("markers", "asyncio: mark test as an async test")
|
||||
|
||||
# Set the asyncio loop scope through ini configuration
|
||||
config.inicfg["asyncio_mode"] = "auto"
|
||||
|
||||
|
||||
@pytest.fixture(scope="function")
|
||||
def event_loop():
|
||||
"""Create an instance of the default event loop for each test case."""
|
||||
import asyncio
|
||||
|
||||
loop = asyncio.new_event_loop()
|
||||
asyncio.set_event_loop(loop)
|
||||
yield loop
|
||||
loop.close()
|
||||
@@ -2,7 +2,7 @@ import json
|
||||
from unittest import mock
|
||||
|
||||
from crewai.tools.base_tool import BaseTool, EnvVar
|
||||
from crewai_tools.generate_tool_specs import ToolSpecExtractor
|
||||
from generate_tool_specs import ToolSpecExtractor
|
||||
from pydantic import BaseModel, Field
|
||||
import pytest
|
||||
|
||||
@@ -61,8 +61,8 @@ def test_unwrap_schema(extractor):
|
||||
@pytest.fixture
|
||||
def mock_tool_extractor(extractor):
|
||||
with (
|
||||
mock.patch("crewai_tools.generate_tool_specs.dir", return_value=["MockTool"]),
|
||||
mock.patch("crewai_tools.generate_tool_specs.getattr", return_value=MockTool),
|
||||
mock.patch("generate_tool_specs.dir", return_value=["MockTool"]),
|
||||
mock.patch("generate_tool_specs.getattr", return_value=MockTool),
|
||||
):
|
||||
extractor.extract_all_tools()
|
||||
assert len(extractor.tools_spec) == 1
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,289 @@
|
||||
interactions:
|
||||
- request:
|
||||
body: '{"url": "https://firecrawl.dev", "includeTags": [], "excludeTags": [],
|
||||
"onlyMainContent": true, "waitFor": 0, "skipTlsVerification": true, "removeBase64Images":
|
||||
true, "fastMode": false, "blockAds": true, "storeInCache": true, "maxAge": 172800000,
|
||||
"formats": ["markdown"], "headers": {}, "mobile": false, "proxy": "auto", "origin":
|
||||
"python-sdk@4.5.0"}'
|
||||
headers:
|
||||
Accept:
|
||||
- '*/*'
|
||||
Accept-Encoding:
|
||||
- gzip, deflate, zstd
|
||||
Connection:
|
||||
- keep-alive
|
||||
Content-Length:
|
||||
- '350'
|
||||
Content-Type:
|
||||
- application/json
|
||||
User-Agent:
|
||||
- python-requests/2.32.5
|
||||
method: POST
|
||||
uri: https://api.firecrawl.dev/v2/scrape
|
||||
response:
|
||||
body:
|
||||
string: "{\"success\":true,\"data\":{\"markdown\":\"We just raised our Series
|
||||
A and shipped Firecrawl /v2 \U0001F389. [Read the blog.](https://www.firecrawl.dev/blog/firecrawl-v2-series-a-announcement)\\n\\n[2
|
||||
Months Free \u2014 Annually](https://www.firecrawl.dev/pricing)\\n\\n# Turn
|
||||
websites into LLM-ready data\\n\\nPower your AI apps with clean web data\\n\\nfrom
|
||||
any website. [It's also open source.](https://github.com/firecrawl/firecrawl)\\n\\nScrape\\n\\nSearch\\nNew\\n\\nMap\\n\\nCrawl\\n\\nScrape\\n\\nLogo\\n\\nNavigation\\n\\nButton\\n\\nH1
|
||||
Title\\n\\nDescription\\n\\nCTA Button\\n\\n\\\\[ .JSON \\\\]\\n\\n```json\\n1[\\\\\\n2
|
||||
\ {\\\\\\n3 \\\"url\\\": \\\"https://example.com\\\",\\\\\\n4 \\\"markdown\\\":
|
||||
\\\"# Getting Started...\\\",\\\\\\n5 \\\"json\\\": { \\\"title\\\": \\\"Guide\\\",
|
||||
\\\"docs\\\": \\\"...\\\" },\\\\\\n6 \\\"screenshot\\\": \\\"https://example.com/hero.png\\\"\\\\\\n7
|
||||
\ }\\\\\\n8]\\n```\\n\\nScrape Completed\\n\\nTrusted by5000+\\n\\ncompaniesof
|
||||
all sizes\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\\\[01/
|
||||
07 \\\\]\\n\\n\xB7\\n\\nMain Features\\n\\n//\\n\\nDeveloper First\\n\\n//\\n\\n##
|
||||
Startscraping today\\n\\nEnhance your apps with industry leading web scraping
|
||||
and crawling capabilities.\\n\\nScrape\\n\\nGet llm-ready data from websites.
|
||||
Markdown, JSON, screenshot, etc.\\n\\nSearch\\n\\nNew\\n\\nSearch the web
|
||||
and get full content from results.\\n\\nCrawl\\n\\nCrawl all the pages on
|
||||
a website and get data for each page.\\n\\nPython\\n\\nNode.js\\n\\nCurl\\n\\nCopy
|
||||
code\\n\\n```python\\n1# pip install firecrawl-py\\n2from firecrawl import
|
||||
Firecrawl\\n3\\n4app = Firecrawl(api_key=\\\"fc-YOUR_API_KEY\\\")\\n5\\n6#
|
||||
Scrape a website:\\n7app.scrape('firecrawl.dev')\\n8\\n9\\n10\\n```\\n\\n\\\\[
|
||||
.MD \\\\]\\n\\n```markdown\\n1# Firecrawl\\n2\\n3Firecrawl is a powerful web
|
||||
scraping\\n4library that makes it easy to extract\\n5data from websites.\\n6\\n7##
|
||||
Installation\\n8\\n9To install Firecrawl, run:\\n10\\n11\\n```\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\nIntegrations\\n\\n###
|
||||
Use well-known tools\\n\\nAlready fully integrated with the greatest existing
|
||||
tools and workflows.\\n\\n[See all integrations](https://www.firecrawl.dev/app)\\n\\n\\n\\nmendableai/firecrawl\\n\\nPublic\\n\\nStar\\n\\n65.3K\\n\\n\\\\[python-SDK\\\\]
|
||||
improvs/async\\n\\n#1337\\n\\n\xB7\\n\\nApr 18, 2025\\n\\n\xB7\\n\\n\\n\\nrafaelsideguide\\n\\nfeat(extract):
|
||||
cost limit\\n\\n#1473\\n\\n\xB7\\n\\nApr 17, 2025\\n\\n\xB7\\n\\n\\n\\nmogery\\n\\nfeat(scrape):
|
||||
get job result from GCS, avoid Redis\\n\\n#1461\\n\\n\xB7\\n\\nApr 15, 2025\\n\\n\xB7\\n\\n\\n\\nmogery\\n\\nExtract
|
||||
v2/rerank improvs\\n\\n#1437\\n\\n\xB7\\n\\nApr 11, 2025\\n\\n\xB7\\n\\n\\n\\nrafaelsideguide\\n\\n\\n\\n\\n\\n+90\\n\\nOpen
|
||||
Source\\n\\n### Code you can trust\\n\\nDeveloped transparently and collaboratively.
|
||||
Join our community of contributors.\\n\\n[Check out our repo](https://github.com/firecrawl/firecrawl)\\n\\n\\\\[02/
|
||||
07 \\\\]\\n\\n\xB7\\n\\nCore\\n\\n//\\n\\nBuilt to outperform\\n\\n//\\n\\n##
|
||||
Core principles, provenperformance\\n\\nBuilt from the ground up to outperform
|
||||
traditional scrapers.\\n\\nNo proxy headaches\\n\\nReliable.Covers 96% of
|
||||
the web,\\n\\nincluding JS-heavy and protected pages. No proxies, no puppets,
|
||||
just clean data.\\n\\nFirecrawl\\n\\n96%\\n\\n\\n\\nPuppeteer\\n\\n79%\\n\\ncURL\\n\\n75%\\n\\nSpeed
|
||||
that feels invisible\\n\\nBlazingly fast.Delivers results in less than 1 second,
|
||||
fast for real-time agents\\n\\nand dynamic apps.\\n\\nURL\\n\\nCrawl\\n\\nScrape\\n\\nfirecrawl.dev/docs\\n\\n50ms\\n\\n51ms\\n\\nfirecrawl.dev/templates\\n\\n52ms\\n\\n50ms\\n\\nfirecrawl.dev/changelog\\n\\n49ms\\n\\n52ms\\n\\nfirecrawl.dev/about\\n\\n52ms\\n\\n50ms\\n\\nfirecrawl.dev/changelog\\n\\n50ms\\n\\n52ms\\n\\nfirecrawl.dev/playground\\n\\n51ms\\n\\n49ms\\n\\n\\\\[
|
||||
CTA \\\\]\\n\\n\\\\[ CRAWL \\\\]\\n\\n\\\\[ SCRAPE \\\\]\\n\\n\\\\[ CTA \\\\]\\n\\n//\\n\\nGet
|
||||
started\\n\\n//\\n\\nReady to build?\\n\\nStart getting Web Data for free
|
||||
and scale seamlessly as your project expands. No credit card needed.\\n\\n[Start
|
||||
for free](https://www.firecrawl.dev/signin) [See our plans](https://www.firecrawl.dev/pricing)\\n\\n\\\\[03/
|
||||
07 \\\\]\\n\\n\xB7\\n\\nFeatures\\n\\n//\\n\\nZero configuration\\n\\n//\\n\\n##
|
||||
We handle the hard stuff\\n\\nRotating proxies, orchestration, rate limits,
|
||||
js-blocked content and more.\\n\\nDocs to data\\n\\nMedia parsing.Firecrawl
|
||||
can parse and output content from web hosted pdfs, docx, and more.\\n\\nhttps://example.com/docs/report.pdf\\n\\nhttps://example.com/files/brief.docx\\n\\nhttps://example.com/docs/guide.html\\n\\ndocx\\n\\nParsing...\\n\\nKnows
|
||||
the moment\\n\\nSmart wait.Firecrawl intelligently waits for content to load,
|
||||
making scraping faster and more reliable.\\n\\nhttps://example-spa.com\\n\\nRequest
|
||||
Sent\\n\\nScrapes the real thing\\n\\nCached, when you need it.Selective caching,
|
||||
you choose your caching patterns, growing web index.\\n\\n\\n\\nUser\\n\\nFirecrawl\\n\\nCache\\n\\nInvisible
|
||||
access\\n\\nStealth mode.Crawls the web without\\n\\nbeing blocked, mimics
|
||||
real users to access protected or dynamic content.\\n\\nInteractive scraping\\n\\nActions.Click,
|
||||
scroll, write, wait, press and more before extracting content.\\n\\nhttps://example.com\\n\\nNavigate\\n\\nClick\\n\\nType\\n\\nWait\\n\\nScroll\\n\\nPress\\n\\nScreenshot\\n\\nScrape\\n\\n\\\\[04/
|
||||
07 \\\\]\\n\\n\xB7\\n\\nPricing\\n\\n//\\n\\nTransparent\\n\\n//\\n\\n## Flexible
|
||||
pricing\\n\\nExplore transparent pricing built for real-world scraping. Start
|
||||
for free, then scale as you grow.\\n\\n\U0001F1FA\U0001F1F8USD\\n\\nFree Plan\\n\\nA
|
||||
lightweight way to try scraping.\\n\\nNo cost, no card, no hassle.\\n\\n500
|
||||
credits\\n\\n$0123456789\\n\\none-time\\n\\nGet started\\n\\nScrape 500 pages\\n\\n2
|
||||
concurrent requests\\n\\nLow rate limits\\n\\nHobby\\n\\nGreat for side projects
|
||||
and small tools.\\n\\nFast, simple, no overkill.\\n\\n3,000 credits\\n\\n$01234567890123456789\\n\\n/monthly\\n\\nBilled
|
||||
yearly\\n\\n2 months free\\n\\nSubscribe\\n\\nScrape 3,000 pages\\n\\n5 concurrent
|
||||
requests\\n\\nBasic support\\n\\n$9 per extra 1k credits\\n\\nStandard\\n\\nMost
|
||||
popular\\n\\nPerfect for scaling with less effort.\\n\\nSimple, solid, dependable.\\n\\n100,000
|
||||
credits\\n\\n$01234567890123456789\\n\\n/monthly\\n\\nBilled yearly\\n\\n2
|
||||
months free\\n\\nSubscribe\\n\\nScrape 100,000 pages\\n\\n50 concurrent requests\\n\\nStandard
|
||||
support\\n\\n$47 per extra 35k credits\\n\\nGrowth\\n\\nBuilt for high volume
|
||||
and speed.\\n\\nFirecrawl at full force.\\n\\n500,000 credits\\n\\n$012345678901234567890123456789\\n\\n/monthly\\n\\nBilled
|
||||
yearly\\n\\n2 months free\\n\\nSubscribe\\n\\nScrape 500,000 pages\\n\\n100
|
||||
concurrent requests\\n\\nPriority support\\n\\n$177 per extra 175k credits\\n\\nExtra
|
||||
credits are available via auto-recharge packs. [Enable](https://www.firecrawl.dev/signin/signup)\\n\\nEnterprise\\n\\nPower
|
||||
at your pace\\n\\nUnlimited credits. Custom RPMs.\\n\\n[Contact sales](https://fk4bvu0n5qp.typeform.com/to/Ej6oydlg)
|
||||
[More details](https://www.firecrawl.dev/enterprise)\\n\\nBulk discounts\\n\\nTop
|
||||
priority support\\n\\nCustom concurrency limits\\n\\nImproved stealth proxies\\n\\nSLAs\\n\\nAdvanced
|
||||
security & controls\\n\\n\\\\[05/ 07 \\\\]\\n\\n\xB7\\n\\nTestimonials\\n\\n//\\n\\nCommunity\\n\\n//\\n\\n##
|
||||
People love building withFirecrawl\\n\\nDiscover why developers choose
|
||||
Firecrawl every day.\\n\\n[Morgan
|
||||
Linton@morganlinton\\\"If you're coding with AI, and haven't discovered @firecrawl\\\\_dev
|
||||
yet, prepare to have your mind blown \U0001F92F\\\"](https://x.com/morganlinton/status/1839454165703204955)
|
||||
[Chris
|
||||
DeWeese@chrisdeweese\\\\_\\\"Started using @firecrawl\\\\_dev for a project,
|
||||
I wish I used this sooner.\\\"](https://x.com/chrisdeweese_/status/1853587120406876601)
|
||||
[Alex
|
||||
Reibman@AlexReibman\\\"Moved our internal agent's web scraping tool from Apify
|
||||
to Firecrawl because it benchmarked 50x faster with AgentOps.\\\"](https://x.com/AlexReibman/status/1780299595484131836)
|
||||
[Tom
|
||||
- Morpho@TomReppelin\\\"I found gold today. Thank you @firecrawl\\\\_dev\\\"](https://x.com/TomReppelin/status/1844382491014201613)\\n\\n[Morgan
|
||||
Linton@morganlinton\\\"If you're coding with AI, and haven't discovered @firecrawl\\\\_dev
|
||||
yet, prepare to have your mind blown \U0001F92F\\\"](https://x.com/morganlinton/status/1839454165703204955)
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[Chris
|
||||
DeWeese@chrisdeweese\\\\_\\\"Started using @firecrawl\\\\_dev for a project,
|
||||
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[Alex
|
||||
Reibman@AlexReibman\\\"Moved our internal agent's web scraping tool from Apify
|
||||
to Firecrawl because it benchmarked 50x faster with AgentOps.\\\"](https://x.com/AlexReibman/status/1780299595484131836)
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[Tom
|
||||
- Morpho@TomReppelin\\\"I found gold today. Thank you @firecrawl\\\\_dev\\\"](https://x.com/TomReppelin/status/1844382491014201613)\\n\\n[Bardia@thepericulum\\\"The
|
||||
Firecrawl team ships. I wanted types for their node SDK, and less than an
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hour later, I got them.\\\"](https://x.com/thepericulum/status/1781397799487078874)
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||||
[Matt
|
||||
Busigin@mbusigin\\\"Firecrawl is dope. Congrats guys \U0001F44F\\\"](https://x.com/mbusigin/status/1836065372010656069)
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||||
[Sumanth@Sumanth\\\\_077\\\"Web
|
||||
scraping will never be the same!\\\\\\\\\\n\\\\\\\\\\nFirecrawl is an open-source
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framework that takes a URL, crawls it, and conver...\\\"](https://x.com/Sumanth_077/status/1940049003074478511)
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[Steven
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||||
Firecrawl team ships. I wanted types for their node SDK, and less than an
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[Matt
|
||||
Busigin@mbusigin\\\"Firecrawl is dope. Congrats guys \U0001F44F\\\"](https://x.com/mbusigin/status/1836065372010656069)
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[Sumanth@Sumanth\\\\_077\\\"Web
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scraping will never be the same!\\\\\\\\\\n\\\\\\\\\\nFirecrawl is an open-source
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[Steven
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Tey@steventey\\\"Open-source Clay alternative just dropped\\\\\\\\\\n\\\\\\\\\\nUpload
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a CSV of emails and...\\\"](https://x.com/steventey/status/1932945651761098889)\\n\\n\\\\[06/
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07 \\\\]\\n\\n\xB7\\n\\nUse Cases\\n\\n//\\n\\nUse cases\\n\\n//\\n\\n## Transform
|
||||
\ web data into AI-powered solutions\\n\\nDiscover how Firecrawl customers
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||||
are getting the most out of our API.\\n\\n[View all use cases](https://docs.firecrawl.dev/use-cases/overview)\\n\\nChat
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with context\\n\\nSmarter AI chats\\n\\nPower your AI assistants with real-time,
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accurate web content.\\n\\n[View docs](https://docs.firecrawl.dev/introduction)\\n\\n\\n\\nAI Assistant\\n\\nwithFirecrawl\\n\\nReal-time\xB7Updated
|
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2 min ago\\n\\nAsk anything...\\n\\nKnow your leads\\n\\nLead enrichment\\n\\nEnhance
|
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your sales data with\\n\\nweb information.\\n\\n[Check out Extract](https://www.firecrawl.dev/extract)\\n\\nExtracting
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\\\\]\\n\\n\\\\[ SCRAPE \\\\]\\n\\n\\\\[ CTA \\\\]\\n\\n//\\n\\nGet started\\n\\n//\\n\\nReady
|
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|
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|
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|
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||||
Firecrawl open-source?\\n\\nWhat is the difference between Firecrawl and other
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||||
web scrapers?\\n\\nWhat is the difference between the open-source version
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|
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|
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Firecrawl crawl websites without a sitemap?\\n\\nWhat formats can Firecrawl
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||||
crawling cost?\\n\\nDo you charge for failed requests?\\n\\nWhat payment methods
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||||
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||||
[Extract](https://www.firecrawl.dev/extract) [Pricing](https://www.firecrawl.dev/pricing)
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[Templates](https://www.firecrawl.dev/templates) [Changelog](https://www.firecrawl.dev/changelog)\\n\\nUse
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|
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07 \\\\]\\n\\n\xB7\\n\\nMain Features\\n\\n//\\n\\nDeveloper First\\n\\n//\\n\\n##
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||||
Startscraping today\\n\\nEnhance your apps with industry leading web scraping
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|
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|
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|
||||
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|
||||
Scrape a website:\\n7app.scrape('firecrawl.dev')\\n8\\n9\\n10\\n```\\n\\n\\\\[
|
||||
.MD \\\\]\\n\\n```markdown\\n1# Firecrawl\\n2\\n3Firecrawl is a powerful web
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|
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|
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|
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|
||||
started\\n\\n//\\n\\nReady to build?\\n\\nStart getting Web Data for free
|
||||
and scale seamlessly as your project expands. No credit card needed.\\n\\n[Start
|
||||
for free](https://www.firecrawl.dev/signin) [See our plans](https://www.firecrawl.dev/pricing)\\n\\n\\\\[03/
|
||||
07 \\\\]\\n\\n\xB7\\n\\nFeatures\\n\\n//\\n\\nZero configuration\\n\\n//\\n\\n##
|
||||
We handle the hard stuff\\n\\nRotating proxies, orchestration, rate limits,
|
||||
js-blocked content and more.\\n\\nDocs to data\\n\\nMedia parsing.Firecrawl
|
||||
can parse and output content from web hosted pdfs, docx, and more.\\n\\nhttps://example.com/docs/report.pdf\\n\\nhttps://example.com/files/brief.docx\\n\\nhttps://example.com/docs/guide.html\\n\\ndocx\\n\\nParsing...\\n\\nKnows
|
||||
the moment\\n\\nSmart wait.Firecrawl intelligently waits for content to load,
|
||||
making scraping faster and more reliable.\\n\\nhttps://example-spa.com\\n\\nRequest
|
||||
Sent\\n\\nScrapes the real thing\\n\\nCached, when you need it.Selective caching,
|
||||
you choose your caching patterns, growing web index.\\n\\n\\n\\nUser\\n\\nFirecrawl\\n\\nCache\\n\\nInvisible
|
||||
access\\n\\nStealth mode.Crawls the web without\\n\\nbeing blocked, mimics
|
||||
real users to access protected or dynamic content.\\n\\nInteractive scraping\\n\\nActions.Click,
|
||||
scroll, write, wait, press and more before extracting content.\\n\\nhttps://example.com\\n\\nNavigate\\n\\nClick\\n\\nType\\n\\nWait\\n\\nScroll\\n\\nPress\\n\\nScreenshot\\n\\nScrape\\n\\n\\\\[04/
|
||||
07 \\\\]\\n\\n\xB7\\n\\nPricing\\n\\n//\\n\\nTransparent\\n\\n//\\n\\n## Flexible
|
||||
pricing\\n\\nExplore transparent pricing built for real-world scraping. Start
|
||||
for free, then scale as you grow.\\n\\n\U0001F1FA\U0001F1F8USD\\n\\nFree Plan\\n\\nA
|
||||
lightweight way to try scraping.\\n\\nNo cost, no card, no hassle.\\n\\n500
|
||||
credits\\n\\n$0123456789\\n\\none-time\\n\\nGet started\\n\\nScrape 500 pages\\n\\n2
|
||||
concurrent requests\\n\\nLow rate limits\\n\\nHobby\\n\\nGreat for side projects
|
||||
and small tools.\\n\\nFast, simple, no overkill.\\n\\n3,000 credits\\n\\n$01234567890123456789\\n\\n/monthly\\n\\nBilled
|
||||
yearly\\n\\n2 months free\\n\\nSubscribe\\n\\nScrape 3,000 pages\\n\\n5 concurrent
|
||||
requests\\n\\nBasic support\\n\\n$9 per extra 1k credits\\n\\nStandard\\n\\nMost
|
||||
popular\\n\\nPerfect for scaling with less effort.\\n\\nSimple, solid, dependable.\\n\\n100,000
|
||||
credits\\n\\n$01234567890123456789\\n\\n/monthly\\n\\nBilled yearly\\n\\n2
|
||||
months free\\n\\nSubscribe\\n\\nScrape 100,000 pages\\n\\n50 concurrent requests\\n\\nStandard
|
||||
support\\n\\n$47 per extra 35k credits\\n\\nGrowth\\n\\nBuilt for high volume
|
||||
and speed.\\n\\nFirecrawl at full force.\\n\\n500,000 credits\\n\\n$012345678901234567890123456789\\n\\n/monthly\\n\\nBilled
|
||||
yearly\\n\\n2 months free\\n\\nSubscribe\\n\\nScrape 500,000 pages\\n\\n100
|
||||
concurrent requests\\n\\nPriority support\\n\\n$177 per extra 175k credits\\n\\nExtra
|
||||
credits are available via auto-recharge packs. [Enable](https://www.firecrawl.dev/signin/signup)\\n\\nEnterprise\\n\\nPower
|
||||
at your pace\\n\\nUnlimited credits. Custom RPMs.\\n\\n[Contact sales](https://fk4bvu0n5qp.typeform.com/to/Ej6oydlg)
|
||||
[More details](https://www.firecrawl.dev/enterprise)\\n\\nBulk discounts\\n\\nTop
|
||||
priority support\\n\\nCustom concurrency limits\\n\\nImproved stealth proxies\\n\\nSLAs\\n\\nAdvanced
|
||||
security & controls\\n\\n\\\\[05/ 07 \\\\]\\n\\n\xB7\\n\\nTestimonials\\n\\n//\\n\\nCommunity\\n\\n//\\n\\n##
|
||||
People love building withFirecrawl\\n\\nDiscover why developers choose
|
||||
Firecrawl every day.\\n\\n[Morgan
|
||||
Linton@morganlinton\\\"If you're coding with AI, and haven't discovered @firecrawl\\\\_dev
|
||||
yet, prepare to have your mind blown \U0001F92F\\\"](https://x.com/morganlinton/status/1839454165703204955)
|
||||
[Chris
|
||||
DeWeese@chrisdeweese\\\\_\\\"Started using @firecrawl\\\\_dev for a project,
|
||||
I wish I used this sooner.\\\"](https://x.com/chrisdeweese_/status/1853587120406876601)
|
||||
[Alex
|
||||
Reibman@AlexReibman\\\"Moved our internal agent's web scraping tool from Apify
|
||||
to Firecrawl because it benchmarked 50x faster with AgentOps.\\\"](https://x.com/AlexReibman/status/1780299595484131836)
|
||||
[Tom
|
||||
- Morpho@TomReppelin\\\"I found gold today. Thank you @firecrawl\\\\_dev\\\"](https://x.com/TomReppelin/status/1844382491014201613)\\n\\n[Morgan
|
||||
Linton@morganlinton\\\"If you're coding with AI, and haven't discovered @firecrawl\\\\_dev
|
||||
yet, prepare to have your mind blown \U0001F92F\\\"](https://x.com/morganlinton/status/1839454165703204955)
|
||||
[Chris
|
||||
DeWeese@chrisdeweese\\\\_\\\"Started using @firecrawl\\\\_dev for a project,
|
||||
I wish I used this sooner.\\\"](https://x.com/chrisdeweese_/status/1853587120406876601)
|
||||
[Alex
|
||||
Reibman@AlexReibman\\\"Moved our internal agent's web scraping tool from Apify
|
||||
to Firecrawl because it benchmarked 50x faster with AgentOps.\\\"](https://x.com/AlexReibman/status/1780299595484131836)
|
||||
[Tom
|
||||
- Morpho@TomReppelin\\\"I found gold today. Thank you @firecrawl\\\\_dev\\\"](https://x.com/TomReppelin/status/1844382491014201613)\\n\\n[Bardia@thepericulum\\\"The
|
||||
Firecrawl team ships. I wanted types for their node SDK, and less than an
|
||||
hour later, I got them.\\\"](https://x.com/thepericulum/status/1781397799487078874)
|
||||
[Matt
|
||||
Busigin@mbusigin\\\"Firecrawl is dope. Congrats guys \U0001F44F\\\"](https://x.com/mbusigin/status/1836065372010656069)
|
||||
[Sumanth@Sumanth\\\\_077\\\"Web
|
||||
scraping will never be the same!\\\\\\\\\\n\\\\\\\\\\nFirecrawl is an open-source
|
||||
framework that takes a URL, crawls it, and conver...\\\"](https://x.com/Sumanth_077/status/1940049003074478511)
|
||||
[Steven
|
||||
Tey@steventey\\\"Open-source Clay alternative just dropped\\\\\\\\\\n\\\\\\\\\\nUpload
|
||||
a CSV of emails and...\\\"](https://x.com/steventey/status/1932945651761098889)\\n\\n[Bardia@thepericulum\\\"The
|
||||
Firecrawl team ships. I wanted types for their node SDK, and less than an
|
||||
hour later, I got them.\\\"](https://x.com/thepericulum/status/1781397799487078874)
|
||||
[Matt
|
||||
Busigin@mbusigin\\\"Firecrawl is dope. Congrats guys \U0001F44F\\\"](https://x.com/mbusigin/status/1836065372010656069)
|
||||
[Sumanth@Sumanth\\\\_077\\\"Web
|
||||
scraping will never be the same!\\\\\\\\\\n\\\\\\\\\\nFirecrawl is an open-source
|
||||
framework that takes a URL, crawls it, and conver...\\\"](https://x.com/Sumanth_077/status/1940049003074478511)
|
||||
[Steven
|
||||
Tey@steventey\\\"Open-source Clay alternative just dropped\\\\\\\\\\n\\\\\\\\\\nUpload
|
||||
a CSV of emails and...\\\"](https://x.com/steventey/status/1932945651761098889)\\n\\n\\\\[06/
|
||||
07 \\\\]\\n\\n\xB7\\n\\nUse Cases\\n\\n//\\n\\nUse cases\\n\\n//\\n\\n## Transform
|
||||
\ web data into AI-powered solutions\\n\\nDiscover how Firecrawl customers
|
||||
are getting the most out of our API.\\n\\n[View all use cases](https://docs.firecrawl.dev/use-cases/overview)\\n\\nChat
|
||||
with context\\n\\nSmarter AI chats\\n\\nPower your AI assistants with real-time,
|
||||
accurate web content.\\n\\n[View docs](https://docs.firecrawl.dev/introduction)\\n\\n\\n\\nAI Assistant\\n\\nwithFirecrawl\\n\\nReal-time\xB7Updated
|
||||
2 min ago\\n\\nAsk anything...\\n\\nKnow your leads\\n\\nLead enrichment\\n\\nEnhance
|
||||
your sales data with\\n\\nweb information.\\n\\n[Check out Extract](https://www.firecrawl.dev/extract)\\n\\nExtracting
|
||||
leads from directory...\\n\\nTech startups\\n\\nWith contact info\\n\\nDecision
|
||||
makers\\n\\nFunding stage\\n\\nReady to engage\\n\\n\\n\\n\\n\\n\\n\\n\\n\\nKnow your leads\\n\\nMCPs\\n\\nAdd
|
||||
powerful scraping to your\\n\\ncode editors.\\n\\n[Get started](https://docs.firecrawl.dev/mcp-server)\\n\\n\\n\\nClaude Code\\n\\n\\n\\nCursor\\n\\n\\n\\nWindsurf\\n\\n\u273B\\n\\nWelcome
|
||||
to Claude Code!\\n\\n/help for help, /status for your current setup\\n\\n>Try
|
||||
\\\"how do I log an error?\\\"\\n\\nBuild with context\\n\\nAI platforms\\n\\nLet
|
||||
your customers build AI apps\\n\\nwith web data.\\n\\n[Check out Map](https://docs.firecrawl.dev/features/map)\\n\\n\\n\\n\\n\\n\\n\\n\\n\\nExtracting
|
||||
text...\\n\\nNo insight missed\\n\\nDeep research\\n\\nExtract comprehensive
|
||||
information for\\n\\nin-depth research.\\n\\n[Build your own with Search](https://docs.firecrawl.dev/features/search)\\n\\nDeep
|
||||
research in progress...\\n\\nAcademic papers\\n\\n0 found\\n\\nNews articles\\n\\n0
|
||||
found\\n\\nExpert opinions\\n\\n0 found\\n\\nResearch reports\\n\\n0 found\\n\\nIndustry
|
||||
data\\n\\n0 found\\n\\nAsk anything...\\n\\n\\\\[ CTA \\\\]\\n\\n\\\\[ CRAWL
|
||||
\\\\]\\n\\n\\\\[ SCRAPE \\\\]\\n\\n\\\\[ CTA \\\\]\\n\\n//\\n\\nGet started\\n\\n//\\n\\nReady
|
||||
to build?\\n\\nStart getting Web Data for free and scale seamlessly as your
|
||||
project expands. No credit card needed.\\n\\n[Start for free](https://www.firecrawl.dev/signin)
|
||||
[See our plans](https://www.firecrawl.dev/pricing)\\n\\n\\\\[07/ 07 \\\\]\\n\\n\xB7\\n\\nFAQ\\n\\n//\\n\\nFAQ\\n\\n//\\n\\n##
|
||||
Frequently askedquestions\\n\\nEverything you need to know about Firecrawl.\\n\\nGeneral\\n\\nWhat
|
||||
is Firecrawl?\\n\\nWhat sites work?\\n\\nWho can benefit from using Firecrawl?\\n\\nIs
|
||||
Firecrawl open-source?\\n\\nWhat is the difference between Firecrawl and other
|
||||
web scrapers?\\n\\nWhat is the difference between the open-source version
|
||||
and the hosted version?\\n\\nScraping & Crawling\\n\\nHow does Firecrawl handle
|
||||
dynamic content on websites?\\n\\nWhy is it not crawling all the pages?\\n\\nCan
|
||||
Firecrawl crawl websites without a sitemap?\\n\\nWhat formats can Firecrawl
|
||||
convert web data into?\\n\\nHow does Firecrawl ensure the cleanliness of the
|
||||
data?\\n\\nIs Firecrawl suitable for large-scale data scraping projects?\\n\\nDoes
|
||||
it respect robots.txt?\\n\\nWhat measures does Firecrawl take to handle web
|
||||
scraping challenges like rate limits and caching?\\n\\nDoes Firecrawl handle
|
||||
captcha or authentication?\\n\\nAPI Related\\n\\nWhere can I find my API key?\\n\\nBilling\\n\\nIs
|
||||
Firecrawl free?\\n\\nIs there a pay-per-use plan instead of monthly?\\n\\nDo
|
||||
credits roll over to the next month?\\n\\nHow many credits do scraping and
|
||||
crawling cost?\\n\\nDo you charge for failed requests?\\n\\nWhat payment methods
|
||||
do you accept?\\n\\nFOOTER\\n\\nThe easiest way to extract\\n\\ndata from
|
||||
the web\\n\\nBacked by\\n\\nY Combinator\\n\\n[Linkedin](https://www.linkedin.com/company/firecrawl)
|
||||
[Github](https://github.com/firecrawl/firecrawl)\\n\\nSOC II \xB7 Type 2\\n\\nAICPA\\n\\nSOC
|
||||
2\\n\\n[X (Twitter)](https://x.com/firecrawl_dev) [Discord](https://discord.gg/gSmWdAkdwd)\\n\\nProducts\\n\\n[Playground](https://www.firecrawl.dev/playground)
|
||||
[Extract](https://www.firecrawl.dev/extract) [Pricing](https://www.firecrawl.dev/pricing)
|
||||
[Templates](https://www.firecrawl.dev/templates) [Changelog](https://www.firecrawl.dev/changelog)\\n\\nUse
|
||||
Cases\\n\\n[AI Platforms](https://docs.firecrawl.dev/use-cases/ai-platforms)
|
||||
[Lead Enrichment](https://docs.firecrawl.dev/use-cases/lead-enrichment) [SEO
|
||||
Platforms](https://docs.firecrawl.dev/use-cases/seo-platforms) [Deep Research](https://docs.firecrawl.dev/use-cases/deep-research)\\n\\nDocumentation\\n\\n[Getting
|
||||
started](https://docs.firecrawl.dev/introduction) [API Reference](https://docs.firecrawl.dev/api-reference/introduction)
|
||||
[Integrations](https://www.firecrawl.dev/app) [Examples](https://docs.firecrawl.dev/use-cases/overview)
|
||||
[SDKs](https://docs.firecrawl.dev/sdks/overview)\\n\\nCompany\\n\\n[Blog](https://www.firecrawl.dev/blog)
|
||||
[Careers](https://www.firecrawl.dev/careers) [Creator & OSS program](https://www.firecrawl.dev/creator-oss-program)
|
||||
[Student program](https://www.firecrawl.dev/student-program)\\n\\n\xA9 2025
|
||||
Firecrawl\\n\\n[Terms of Service](https://www.firecrawl.dev/terms-of-service)
|
||||
[Privacy Policy](https://www.firecrawl.dev/privacy-policy) [Report Abuse](mailto:help@firecrawl.com?subject=Issue:)\\n\\n[All
|
||||
systems normal](https://status.firecrawl.dev/)\\n\\nStripeM-Inner\",\"metadata\":{\"favicon\":\"https://www.firecrawl.dev/favicon.png\",\"ogUrl\":\"https://www.firecrawl.dev\",\"ogImage\":\"https://www.firecrawl.dev/og.png\",\"referrer\":\"origin-when-cross-origin\",\"ogDescription\":\"The
|
||||
web crawling, scraping, and search API for AI. Built for scale. Firecrawl
|
||||
delivers the entire internet to AI agents and builders. Clean, structured,
|
||||
and ready to reason with.\",\"robots\":\"follow, index\",\"twitter:card\":\"summary_large_image\",\"og:site_name\":\"Firecrawl
|
||||
- The Web Data API for AI\",\"twitter:title\":\"Firecrawl - The Web Data API
|
||||
for AI\",\"og:image\":\"https://www.firecrawl.dev/og.png\",\"title\":\"Firecrawl
|
||||
- The Web Data API for AI\",\"og:description\":\"The web crawling, scraping,
|
||||
and search API for AI. Built for scale. Firecrawl delivers the entire internet
|
||||
to AI agents and builders. Clean, structured, and ready to reason with.\",\"twitter:image\":\"https://www.firecrawl.dev/og.png\",\"viewport\":\"width=device-width,
|
||||
initial-scale=1, maximum-scale=1, user-scalable=no\",\"ogSiteName\":\"Firecrawl
|
||||
- The Web Data API for AI\",\"keywords\":\"Firecrawl,Markdown,Data,Mendable,Langchain\",\"author\":\"Firecrawl\",\"og:title\":\"Firecrawl
|
||||
- The Web Data API for AI\",\"twitter:description\":\"The web crawling, scraping,
|
||||
and search API for AI. Built for scale. Firecrawl delivers the entire internet
|
||||
to AI agents and builders. Clean, structured, and ready to reason with.\",\"description\":\"The
|
||||
web crawling, scraping, and search API for AI. Built for scale. Firecrawl
|
||||
delivers the entire internet to AI agents and builders. Clean, structured,
|
||||
and ready to reason with.\",\"twitter:site\":\"@Vercel\",\"og:url\":\"https://www.firecrawl.dev\",\"og:type\":\"website\",\"ogTitle\":\"Firecrawl
|
||||
- The Web Data API for AI\",\"language\":\"en\",\"creator\":\"Firecrawl\",\"publisher\":\"Firecrawl\",\"twitter:creator\":\"@Vercel\",\"scrapeId\":\"57b0586f-36e8-4923-aaa2-88ff58c03999\",\"sourceURL\":\"https://www.firecrawl.dev/\",\"url\":\"https://www.firecrawl.dev/\",\"statusCode\":200,\"contentType\":\"text/html;
|
||||
charset=utf-8\",\"proxyUsed\":\"basic\",\"cacheState\":\"hit\",\"cachedAt\":\"2025-10-29T13:09:07.713Z\"}},{\"url\":\"https://github.com/firecrawl/firecrawl\",\"title\":\"firecrawl/firecrawl:
|
||||
The Web Data API for AI - Turn entire ... - GitHub\",\"description\":\"Firecrawl
|
||||
is an API service that takes a URL, crawls it, and converts it into clean
|
||||
markdown or structured data. We crawl all accessible subpages and give you
|
||||
...\",\"position\":2,\"category\":\"github\",\"markdown\":\"[Skip to content](https://github.com/firecrawl/firecrawl#start-of-content)\\n\\nYou
|
||||
signed in with another tab or window. [Reload](https://github.com/firecrawl/firecrawl)
|
||||
to refresh your session.You signed out in another tab or window. [Reload](https://github.com/firecrawl/firecrawl)
|
||||
to refresh your session.You switched accounts on another tab or window. [Reload](https://github.com/firecrawl/firecrawl)
|
||||
to refresh your session.Dismiss alert\\n\\n{{ message }}\\n\\n[firecrawl](https://github.com/firecrawl)/
|
||||
**[firecrawl](https://github.com/firecrawl/firecrawl)** Public\\n\\n- Couldn't
|
||||
load subscription status.\\nRetry\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n### Uh
|
||||
oh!\\n\\n\\n\\n\\n\\n\\n\\nThere was an error while loading. [Please reload
|
||||
this page](https://github.com/firecrawl/firecrawl).\\n\\n- [Fork\\\\\\\\\\n5.1k](https://github.com/login?return_to=%2Ffirecrawl%2Ffirecrawl)\\n-
|
||||
[Star\\\\\\\\\\n65.2k](https://github.com/login?return_to=%2Ffirecrawl%2Ffirecrawl)\\n\\n\\n\U0001F525
|
||||
The Web Data API for AI - Turn entire websites into LLM-ready markdown or
|
||||
structured data\\n\\n\\n[firecrawl.dev](https://firecrawl.dev/ \\\"https://firecrawl.dev\\\")\\n\\n###
|
||||
License\\n\\n[AGPL-3.0 license](https://github.com/firecrawl/firecrawl/blob/main/LICENSE)\\n\\n[65.2k\\\\\\\\\\nstars](https://github.com/firecrawl/firecrawl/stargazers)
|
||||
[5.1k\\\\\\\\\\nforks](https://github.com/firecrawl/firecrawl/forks) [Branches](https://github.com/firecrawl/firecrawl/branches)
|
||||
[Tags](https://github.com/firecrawl/firecrawl/tags) [Activity](https://github.com/firecrawl/firecrawl/activity)\\n\\n[Star](https://github.com/login?return_to=%2Ffirecrawl%2Ffirecrawl)\\n\\nCouldn't
|
||||
load subscription status.\\nRetry\\n\\n### Uh oh!\\n\\nThere was an error
|
||||
while loading. [Please reload this page](https://github.com/firecrawl/firecrawl).\\n\\n#
|
||||
firecrawl/firecrawl\\n\\nmain\\n\\n[**887** Branches](https://github.com/firecrawl/firecrawl/branches)
|
||||
[**28** Tags](https://github.com/firecrawl/firecrawl/tags)\\n\\n[Go to Branches
|
||||
page](https://github.com/firecrawl/firecrawl/branches)[Go to Tags page](https://github.com/firecrawl/firecrawl/tags)\\n\\nGo
|
||||
to file\\n\\nCode\\n\\nOpen more actions menu\\n\\n## Folders and files\\n\\n|
|
||||
Name | Name | Last commit message | Last commit date |\\n| --- | --- | ---
|
||||
| --- |\\n| ## Latest commit<br>[](https://github.com/amplitudesxd)[amplitudesxd](https://github.com/firecrawl/firecrawl/commits?author=amplitudesxd)<br>[chore:
|
||||
update last scrape rpc (](https://github.com/firecrawl/firecrawl/commit/37de2877fab4bae2de297e37bad3c9bcd49a64bc)
|
||||
[#2339](https://github.com/firecrawl/firecrawl/pull/2339) [)](https://github.com/firecrawl/firecrawl/commit/37de2877fab4bae2de297e37bad3c9bcd49a64bc)<br>success<br>20
|
||||
hours agoOct 27, 2025<br>[37de287](https://github.com/firecrawl/firecrawl/commit/37de2877fab4bae2de297e37bad3c9bcd49a64bc)\_\xB7\_20
|
||||
hours agoOct 27, 2025<br>## History<br>[4,487 Commits](https://github.com/firecrawl/firecrawl/commits/main/)
|
||||
<br>Open commit details<br>[View commit history for this file.](https://github.com/firecrawl/firecrawl/commits/main/)
|
||||
|\\n| [.github](https://github.com/firecrawl/firecrawl/tree/main/.github \\\".github\\\")
|
||||
| [.github](https://github.com/firecrawl/firecrawl/tree/main/.github \\\".github\\\")
|
||||
| [fix(ci): temp disabled prod env tests](https://github.com/firecrawl/firecrawl/commit/42fc149c1ab738da0e15e772817774aa35273f8e
|
||||
\\\"fix(ci): temp disabled prod env tests\\\") | 5 days agoOct 23, 2025 |\\n|
|
||||
[apps](https://github.com/firecrawl/firecrawl/tree/main/apps \\\"apps\\\")
|
||||
| [apps](https://github.com/firecrawl/firecrawl/tree/main/apps \\\"apps\\\")
|
||||
| [chore: update last scrape rpc (](https://github.com/firecrawl/firecrawl/commit/37de2877fab4bae2de297e37bad3c9bcd49a64bc
|
||||
\\\"chore: update last scrape rpc (#2339)\\\") [#2339](https://github.com/firecrawl/firecrawl/pull/2339)
|
||||
[)](https://github.com/firecrawl/firecrawl/commit/37de2877fab4bae2de297e37bad3c9bcd49a64bc
|
||||
\\\"chore: update last scrape rpc (#2339)\\\") | 20 hours agoOct 27, 2025
|
||||
|\\n| [examples](https://github.com/firecrawl/firecrawl/tree/main/examples
|
||||
\\\"examples\\\") | [examples](https://github.com/firecrawl/firecrawl/tree/main/examples
|
||||
\\\"examples\\\") | [Merge pull request](https://github.com/firecrawl/firecrawl/commit/7ad57003b4ad8b230ba8252129e52bafa62dfae9
|
||||
\\\"Merge pull request #2172 from MAVRICK-1/firecrawl-gemini-screenshot-editor
|
||||
\ feat: Add Firecrawl + Gemini 2.5 Flash Image CLI Editor\\\") [#2172](https://github.com/firecrawl/firecrawl/pull/2172)
|
||||
[from MAVRICK-1/firecrawl-gemini-screenshot-e\u2026](https://github.com/firecrawl/firecrawl/commit/7ad57003b4ad8b230ba8252129e52bafa62dfae9
|
||||
\\\"Merge pull request #2172 from MAVRICK-1/firecrawl-gemini-screenshot-editor
|
||||
\ feat: Add Firecrawl + Gemini 2.5 Flash Image CLI Editor\\\") | last monthSep
|
||||
23, 2025 |\\n| [img](https://github.com/firecrawl/firecrawl/tree/main/img
|
||||
\\\"img\\\") | [img](https://github.com/firecrawl/firecrawl/tree/main/img
|
||||
\\\"img\\\") | [updated readme](https://github.com/firecrawl/firecrawl/commit/4f904e774831dc598681d3e998d0e5e15abcec27
|
||||
\\\"updated readme\\\") | 2 months agoAug 18, 2025 |\\n| [.gitattributes](https://github.com/firecrawl/firecrawl/blob/main/.gitattributes
|
||||
\\\".gitattributes\\\") | [.gitattributes](https://github.com/firecrawl/firecrawl/blob/main/.gitattributes
|
||||
\\\".gitattributes\\\") | [Initial commit](https://github.com/firecrawl/firecrawl/commit/a6c2a878119321a196f720cce4195e086f1c6b46
|
||||
\\\"Initial commit\\\") | last yearApr 15, 2024 |\\n| [.gitignore](https://github.com/firecrawl/firecrawl/blob/main/.gitignore
|
||||
\\\".gitignore\\\") | [.gitignore](https://github.com/firecrawl/firecrawl/blob/main/.gitignore
|
||||
\\\".gitignore\\\") | [Nick: init](https://github.com/firecrawl/firecrawl/commit/ab3fa4838458c8303a67dd30fdd75a16b89cc20b
|
||||
\\\"Nick: init\\\") | 3 weeks agoOct 10, 2025 |\\n| [.gitmodules](https://github.com/firecrawl/firecrawl/blob/main/.gitmodules
|
||||
\\\".gitmodules\\\") | [.gitmodules](https://github.com/firecrawl/firecrawl/blob/main/.gitmodules
|
||||
\\\".gitmodules\\\") | [mendableai -> firecrawl](https://github.com/firecrawl/firecrawl/commit/2f3bc4e7a7b1a67a29c06df629f79402ee1aad1b
|
||||
\\\"mendableai -> firecrawl\\\") | 2 months agoAug 18, 2025 |\\n| [CLAUDE.md](https://github.com/firecrawl/firecrawl/blob/main/CLAUDE.md
|
||||
\\\"CLAUDE.md\\\") | [CLAUDE.md](https://github.com/firecrawl/firecrawl/blob/main/CLAUDE.md
|
||||
\\\"CLAUDE.md\\\") | [add claude file](https://github.com/firecrawl/firecrawl/commit/3f0873c788823258a7d9f55d1c8772aed4e1a8de
|
||||
\\\"add claude file\\\") | 2 months agoAug 6, 2025 |\\n| [CONTRIBUTING.md](https://github.com/firecrawl/firecrawl/blob/main/CONTRIBUTING.md
|
||||
\\\"CONTRIBUTING.md\\\") | [CONTRIBUTING.md](https://github.com/firecrawl/firecrawl/blob/main/CONTRIBUTING.md
|
||||
\\\"CONTRIBUTING.md\\\") | [Add Rust to CONTRIBUTING (](https://github.com/firecrawl/firecrawl/commit/f396cb20b54c3c2d7e64882642c5df6310a01002
|
||||
\\\"Add Rust to CONTRIBUTING (#2180)\\\") [#2180](https://github.com/firecrawl/firecrawl/pull/2180)
|
||||
[)](https://github.com/firecrawl/firecrawl/commit/f396cb20b54c3c2d7e64882642c5df6310a01002
|
||||
\\\"Add Rust to CONTRIBUTING (#2180)\\\") | last monthSep 18, 2025 |\\n| [LICENSE](https://github.com/firecrawl/firecrawl/blob/main/LICENSE
|
||||
\\\"LICENSE\\\") | [LICENSE](https://github.com/firecrawl/firecrawl/blob/main/LICENSE
|
||||
\\\"LICENSE\\\") | [Update SDKs to MIT license](https://github.com/firecrawl/firecrawl/commit/afb49e21e7cff595ebad9ce0b7aba13b88f39cf8
|
||||
\\\"Update SDKs to MIT license\\\") | last yearJul 8, 2024 |\\n| [README.md](https://github.com/firecrawl/firecrawl/blob/main/README.md
|
||||
\\\"README.md\\\") | [README.md](https://github.com/firecrawl/firecrawl/blob/main/README.md
|
||||
\\\"README.md\\\") | [Update README.md](https://github.com/firecrawl/firecrawl/commit/a21430e97818d95099bb365be711d9227bd75590
|
||||
\\\"Update README.md\\\") | 3 weeks agoOct 6, 2025 |\\n| [SELF\\\\_HOST.md](https://github.com/firecrawl/firecrawl/blob/main/SELF_HOST.md
|
||||
\\\"SELF_HOST.md\\\") | [SELF\\\\_HOST.md](https://github.com/firecrawl/firecrawl/blob/main/SELF_HOST.md
|
||||
\\\"SELF_HOST.md\\\") | [Allow self-hosted webhook delivery to private IP
|
||||
addresses (](https://github.com/firecrawl/firecrawl/commit/5756b834884d481382ce1f5674836a56b7fee33d
|
||||
\\\"Allow self-hosted webhook delivery to private IP addresses (#2232)\\\")
|
||||
[#2232](https://github.com/firecrawl/firecrawl/pull/2232) [)](https://github.com/firecrawl/firecrawl/commit/5756b834884d481382ce1f5674836a56b7fee33d
|
||||
\\\"Allow self-hosted webhook delivery to private IP addresses (#2232)\\\")
|
||||
| 27 days agoOct 1, 2025 |\\n| [docker-compose.yaml](https://github.com/firecrawl/firecrawl/blob/main/docker-compose.yaml
|
||||
\\\"docker-compose.yaml\\\") | [docker-compose.yaml](https://github.com/firecrawl/firecrawl/blob/main/docker-compose.yaml
|
||||
\\\"docker-compose.yaml\\\") | [Fix a self-hosted docker-compose.yaml bug
|
||||
caused by a recent firecraw\u2026](https://github.com/firecrawl/firecrawl/commit/7d4100b274889977fa1ba26344532d9d8747494c
|
||||
\\\"Fix a self-hosted docker-compose.yaml bug caused by a recent firecrawl
|
||||
change (#2252) Add EXTRACT_WORKER_PORT to docker-compose environment\\\")
|
||||
| 3 weeks agoOct 4, 2025 |\\n| View all files |\\n\\n## Repository files navigation\\n\\n###
|
||||
[](https://raw.githubusercontent.com/firecrawl/firecrawl/main/img/firecrawl_logo.png)\\n\\n[Permalink:
|
||||
](https://github.com/firecrawl/firecrawl#----)\\n\\n[](https://github.com/firecrawl/firecrawl/blob/main/LICENSE)[](https://pepy.tech/project/firecrawl-py)[](https://github.com/firecrawl/firecrawl/graphs/contributors)[](https://firecrawl.dev/)\\n\\n[](https://twitter.com/firecrawl_dev)[](https://www.linkedin.com/company/104100957)[](https://discord.com/invite/gSmWdAkdwd)\\n\\n#
|
||||
\U0001F525 Firecrawl\\n\\n[Permalink: \U0001F525 Firecrawl](https://github.com/firecrawl/firecrawl#-firecrawl)\\n\\nEmpower
|
||||
your AI apps with clean data from any website. Featuring advanced scraping,
|
||||
crawling, and data extraction capabilities.\\n\\n_This repository is in development,
|
||||
and we\u2019re still integrating custom modules into the mono repo. It's not
|
||||
fully ready for self-hosted deployment yet, but you can run it locally._\\n\\n##
|
||||
What is Firecrawl?\\n\\n[Permalink: What is Firecrawl?](https://github.com/firecrawl/firecrawl#what-is-firecrawl)\\n\\n[Firecrawl](https://firecrawl.dev/?ref=github)
|
||||
is an API service that takes a URL, crawls it, and converts it into clean
|
||||
markdown or structured data. We crawl all accessible subpages and give you
|
||||
clean data for each. No sitemap required. Check out our [documentation](https://docs.firecrawl.dev/).\\n\\nLooking
|
||||
for our MCP? Check out the [repo here](https://github.com/firecrawl/firecrawl-mcp-server).\\n\\n_Pst.
|
||||
hey, you, join our stargazers :)_\\n\\n[](https://github.com/firecrawl/firecrawl)\\n\\n##
|
||||
How to use it?\\n\\n[Permalink: How to use it?](https://github.com/firecrawl/firecrawl#how-to-use-it)\\n\\nWe
|
||||
provide an easy to use API with our hosted version. You can find the playground
|
||||
and documentation [here](https://firecrawl.dev/playground). You can also self
|
||||
host the backend if you'd like.\\n\\nCheck out the following resources to
|
||||
get started:\\n\\n- [x] **API**: [Documentation](https://docs.firecrawl.dev/api-reference/introduction)\\n-
|
||||
[x] **SDKs**: [Python](https://docs.firecrawl.dev/sdks/python), [Node](https://docs.firecrawl.dev/sdks/node)\\n-
|
||||
[x] **LLM Frameworks**: [Langchain (python)](https://python.langchain.com/docs/integrations/document_loaders/firecrawl/),
|
||||
[Langchain (js)](https://js.langchain.com/docs/integrations/document_loaders/web_loaders/firecrawl),
|
||||
[Llama Index](https://docs.llamaindex.ai/en/latest/examples/data_connectors/WebPageDemo/#using-firecrawl-reader),
|
||||
[Crew.ai](https://docs.crewai.com/), [Composio](https://composio.dev/tools/firecrawl/all),
|
||||
[PraisonAI](https://docs.praison.ai/firecrawl/), [Superinterface](https://superinterface.ai/docs/assistants/functions/firecrawl),
|
||||
[Vectorize](https://docs.vectorize.io/integrations/source-connectors/firecrawl)\\n-
|
||||
[x] **Low-code Frameworks**: [Dify](https://dify.ai/blog/dify-ai-blog-integrated-with-firecrawl),
|
||||
[Langflow](https://docs.langflow.org/), [Flowise AI](https://docs.flowiseai.com/integrations/langchain/document-loaders/firecrawl),
|
||||
[Cargo](https://docs.getcargo.io/integration/firecrawl), [Pipedream](https://pipedream.com/apps/firecrawl/)\\n-
|
||||
[x] **Community SDKs**: [Go](https://docs.firecrawl.dev/sdks/go), [Rust](https://docs.firecrawl.dev/sdks/rust)\\n-
|
||||
[x] **Others**: [Zapier](https://zapier.com/apps/firecrawl/integrations),
|
||||
[Pabbly Connect](https://www.pabbly.com/connect/integrations/firecrawl/)\\n-
|
||||
[ ] Want an SDK or Integration? Let us know by opening an issue.\\n\\nTo
|
||||
run locally, refer to guide [here](https://github.com/firecrawl/firecrawl/blob/main/CONTRIBUTING.md).\\n\\n###
|
||||
API Key\\n\\n[Permalink: API Key](https://github.com/firecrawl/firecrawl#api-key)\\n\\nTo
|
||||
use the API, you need to sign up on [Firecrawl](https://firecrawl.dev/) and
|
||||
get an API key.\\n\\n### Features\\n\\n[Permalink: Features](https://github.com/firecrawl/firecrawl#features)\\n\\n-
|
||||
[**Scrape**](https://github.com/firecrawl/firecrawl#scraping): scrapes a URL
|
||||
and get its content in LLM-ready format (markdown, structured data via [LLM
|
||||
Extract](https://github.com/firecrawl/firecrawl#llm-extraction-beta), screenshot,
|
||||
html)\\n- [**Crawl**](https://github.com/firecrawl/firecrawl#crawling): scrapes
|
||||
all the URLs of a web page and return content in LLM-ready format\\n- [**Map**](https://github.com/firecrawl/firecrawl#map):
|
||||
input a website and get all the website urls - extremely fast\\n- [**Search**](https://github.com/firecrawl/firecrawl#search):
|
||||
search the web and get full content from results\\n- [**Extract**](https://github.com/firecrawl/firecrawl#extract):
|
||||
get structured data from single page, multiple pages or entire websites with
|
||||
AI.\\n\\n### Powerful Capabilities\\n\\n[Permalink: Powerful Capabilities](https://github.com/firecrawl/firecrawl#powerful-capabilities)\\n\\n-
|
||||
**LLM-ready formats**: markdown, structured data, screenshot, HTML, links,
|
||||
metadata\\n- **The hard stuff**: proxies, anti-bot mechanisms, dynamic content
|
||||
(js-rendered), output parsing, orchestration\\n- **Customizability**: exclude
|
||||
tags, crawl behind auth walls with custom headers, max crawl depth, etc...\\n-
|
||||
**Media parsing**: pdfs, docx, images\\n- **Reliability first**: designed
|
||||
to get the data you need - no matter how hard it is\\n- **Actions**: click,
|
||||
scroll, input, wait and more before extracting data\\n- **Batching**: scrape
|
||||
thousands of URLs at the same time with a new async endpoint\\n- **Change
|
||||
Tracking**: monitor and detect changes in website content over time\\n\\nYou
|
||||
can find all of Firecrawl's capabilities and how to use them in our [documentation](https://docs.firecrawl.dev/)\\n\\n###
|
||||
Crawling\\n\\n[Permalink: Crawling](https://github.com/firecrawl/firecrawl#crawling)\\n\\nUsed
|
||||
to crawl a URL and all accessible subpages. This submits a crawl job and returns
|
||||
a job ID to check the status of the crawl.\\n\\n```\\ncurl -X POST https://api.firecrawl.dev/v2/crawl
|
||||
\\\\\\n -H 'Content-Type: application/json' \\\\\\n -H 'Authorization:
|
||||
Bearer fc-YOUR_API_KEY' \\\\\\n -d '{\\n \\\"url\\\": \\\"https://docs.firecrawl.dev\\\",\\n
|
||||
\ \\\"limit\\\": 10,\\n \\\"scrapeOptions\\\": {\\n \\\"formats\\\":
|
||||
[\\\"markdown\\\", \\\"html\\\"]\\n }\\n }'\\n```\\n\\nReturns a crawl
|
||||
job id and the url to check the status of the crawl.\\n\\n```\\n{\\n \\\"success\\\":
|
||||
true,\\n \\\"id\\\": \\\"123-456-789\\\",\\n \\\"url\\\": \\\"https://api.firecrawl.dev/v2/crawl/123-456-789\\\"\\n}\\n```\\n\\n###
|
||||
Check Crawl Job\\n\\n[Permalink: Check Crawl Job](https://github.com/firecrawl/firecrawl#check-crawl-job)\\n\\nUsed
|
||||
to check the status of a crawl job and get its result.\\n\\n```\\ncurl -X
|
||||
GET https://api.firecrawl.dev/v2/crawl/123-456-789 \\\\\\n -H 'Content-Type:
|
||||
application/json' \\\\\\n -H 'Authorization: Bearer YOUR_API_KEY'\\n```\\n\\n```\\n{\\n
|
||||
\ \\\"status\\\": \\\"completed\\\",\\n \\\"total\\\": 36,\\n \\\"creditsUsed\\\":
|
||||
36,\\n \\\"expiresAt\\\": \\\"2024-00-00T00:00:00.000Z\\\",\\n \\\"data\\\":
|
||||
[\\\\\\n {\\\\\\n \\\"markdown\\\": \\\"[Firecrawl Docs home page!...\\\",\\\\\\n
|
||||
\ \\\"html\\\": \\\"<!DOCTYPE html><html lang=\\\\\\\"en\\\\\\\" class=\\\\\\\"js-focus-visible
|
||||
lg:[--scroll-mt:9.5rem]\\\\\\\" data-js-focus-visible=\\\\\\\"\\\\\\\">...\\\",\\\\\\n
|
||||
\ \\\"metadata\\\": {\\\\\\n \\\"title\\\": \\\"Build a 'Chat with
|
||||
website' using Groq Llama 3 | Firecrawl\\\",\\\\\\n \\\"language\\\":
|
||||
\\\"en\\\",\\\\\\n \\\"sourceURL\\\": \\\"https://docs.firecrawl.dev/learn/rag-llama3\\\",\\\\\\n
|
||||
\ \\\"description\\\": \\\"Learn how to use Firecrawl, Groq Llama 3,
|
||||
and Langchain to build a 'Chat with your website' bot.\\\",\\\\\\n \\\"ogLocaleAlternate\\\":
|
||||
[],\\\\\\n \\\"statusCode\\\": 200\\\\\\n }\\\\\\n }\\\\\\n
|
||||
\ ]\\\\\\n}\\\\\\n```\\\\\\n\\\\\\n### Scraping\\\\\\n\\\\\\n[Permalink: Scraping](https://github.com/firecrawl/firecrawl#scraping)\\\\\\n\\\\\\nUsed
|
||||
to scrape a URL and get its content in the specified formats.\\\\\\n\\\\\\n```\\\\\\ncurl
|
||||
-X POST https://api.firecrawl.dev/v2/scrape \\\\\\\\\\n -H 'Content-Type:
|
||||
application/json' \\\\\\\\\\n -H 'Authorization: Bearer YOUR_API_KEY' \\\\\\\\\\n
|
||||
\ -d '{\\\\\\n \\\"url\\\": \\\"https://docs.firecrawl.dev\\\",\\\\\\n
|
||||
\ \\\"formats\\\" : [\\\"markdown\\\", \\\"html\\\"]\\\\\\n }'\\\\\\n```\\\\\\n\\\\\\nResponse:\\\\\\n\\\\\\n```\\\\\\n{\\\\\\n
|
||||
\ \\\"success\\\": true,\\\\\\n \\\"data\\\": {\\\\\\n \\\"markdown\\\":
|
||||
\\\"Launch Week I is here! [See our Day 2 Release \U0001F680](https://www.firecrawl.dev/blog/launch-week-i-day-2-doubled-rate-limits)[\U0001F4A5
|
||||
Get 2 months free...\\\",\\\\\\n \\\"html\\\": \\\"<!DOCTYPE html><html
|
||||
lang=\\\\\\\"en\\\\\\\" class=\\\\\\\"light\\\\\\\" style=\\\\\\\"color-scheme:
|
||||
light;\\\\\\\"><body class=\\\\\\\"__variable_36bd41 __variable_d7dc5d font-inter
|
||||
...\\\",\\\\\\n \\\"metadata\\\": {\\\\\\n \\\"title\\\": \\\"Home
|
||||
- Firecrawl\\\",\\\\\\n \\\"description\\\": \\\"Firecrawl crawls and
|
||||
converts any website into clean markdown.\\\",\\\\\\n \\\"language\\\":
|
||||
\\\"en\\\",\\\\\\n \\\"keywords\\\": \\\"Firecrawl,Markdown,Data,Mendable,Langchain\\\",\\\\\\n
|
||||
\ \\\"robots\\\": \\\"follow, index\\\",\\\\\\n \\\"ogTitle\\\":
|
||||
\\\"Firecrawl\\\",\\\\\\n \\\"ogDescription\\\": \\\"Turn any website
|
||||
into LLM-ready data.\\\",\\\\\\n \\\"ogUrl\\\": \\\"https://www.firecrawl.dev/\\\",\\\\\\n
|
||||
\ \\\"ogImage\\\": \\\"https://www.firecrawl.dev/og.png?123\\\",\\\\\\n
|
||||
\ \\\"ogLocaleAlternate\\\": [],\\\\\\n \\\"ogSiteName\\\": \\\"Firecrawl\\\",\\\\\\n
|
||||
\ \\\"sourceURL\\\": \\\"https://firecrawl.dev\\\",\\\\\\n \\\"statusCode\\\":
|
||||
200\\\\\\n }\\\\\\n }\\\\\\n}\\\\\\n```\\\\\\n\\\\\\n### Map\\\\\\n\\\\\\n[Permalink:
|
||||
Map](https://github.com/firecrawl/firecrawl#map)\\\\\\n\\\\\\nUsed to map
|
||||
a URL and get urls of the website. This returns most links present on the
|
||||
website.\\\\\\n\\\\\\n```\\\\\\ncurl -X POST https://api.firecrawl.dev/v2/map
|
||||
\\\\\\\\\\n -H 'Content-Type: application/json' \\\\\\\\\\n -H 'Authorization:
|
||||
Bearer YOUR_API_KEY' \\\\\\\\\\n -d '{\\\\\\n \\\"url\\\": \\\"https://firecrawl.dev\\\"\\\\\\n
|
||||
\ }'\\\\\\n```\\\\\\n\\\\\\nResponse:\\\\\\n\\\\\\n```\\\\\\n{\\\\\\n \\\"success\\\":
|
||||
true,\\\\\\n \\\"links\\\": [\\\\\\n { \\\"url\\\": \\\"https://firecrawl.dev\\\",
|
||||
\\\"title\\\": \\\"Firecrawl\\\", \\\"description\\\": \\\"Firecrawl is a
|
||||
tool that allows you to crawl a website and get the data you need.\\\" },\\\\\\n
|
||||
\ { \\\"url\\\": \\\"https://www.firecrawl.dev/pricing\\\", \\\"title\\\":
|
||||
\\\"Firecrawl Pricing\\\", \\\"description\\\": \\\"Firecrawl Pricing\\\"
|
||||
},\\\\\\n { \\\"url\\\": \\\"https://www.firecrawl.dev/blog\\\", \\\"title\\\":
|
||||
\\\"Firecrawl Blog\\\", \\\"description\\\": \\\"Firecrawl Blog\\\" },\\\\\\n
|
||||
\ { \\\"url\\\": \\\"https://www.firecrawl.dev/playground\\\", \\\"title\\\":
|
||||
\\\"Firecrawl Playground\\\", \\\"description\\\": \\\"Firecrawl Playground\\\"
|
||||
},\\\\\\n { \\\"url\\\": \\\"https://www.firecrawl.dev/smart-crawl\\\",
|
||||
\\\"title\\\": \\\"Firecrawl Smart Crawl\\\", \\\"description\\\": \\\"Firecrawl
|
||||
Smart Crawl\\\" }\\\\\\n ]\\\\\\n}\\\\\\n```\\\\\\n\\\\\\n#### Map with search\\\\\\n\\\\\\n[Permalink:
|
||||
Map with search](https://github.com/firecrawl/firecrawl#map-with-search)\\\\\\n\\\\\\nMap
|
||||
with `search` param allows you to search for specific urls inside a website.\\\\\\n\\\\\\n```\\\\\\ncurl
|
||||
-X POST https://api.firecrawl.dev/v2/map \\\\\\\\\\n -H 'Content-Type:
|
||||
application/json' \\\\\\\\\\n -H 'Authorization: Bearer YOUR_API_KEY' \\\\\\\\\\n
|
||||
\ -d '{\\\\\\n \\\"url\\\": \\\"https://firecrawl.dev\\\",\\\\\\n \\\"search\\\":
|
||||
\\\"docs\\\"\\\\\\n }'\\\\\\n```\\\\\\n\\\\\\nResponse will be an ordered
|
||||
list from the most relevant to the least relevant.\\\\\\n\\\\\\n```\\\\\\n{\\\\\\n
|
||||
\ \\\"success\\\": true,\\\\\\n \\\"links\\\": [\\\\\\n { \\\"url\\\":
|
||||
\\\"https://docs.firecrawl.dev\\\", \\\"title\\\": \\\"Firecrawl Docs\\\",
|
||||
\\\"description\\\": \\\"Firecrawl Docs\\\" },\\\\\\n { \\\"url\\\": \\\"https://docs.firecrawl.dev/sdks/python\\\",
|
||||
\\\"title\\\": \\\"Firecrawl Python SDK\\\", \\\"description\\\": \\\"Firecrawl
|
||||
Python SDK\\\" },\\\\\\n { \\\"url\\\": \\\"https://docs.firecrawl.dev/learn/rag-llama3\\\",
|
||||
\\\"title\\\": \\\"Firecrawl RAG Llama 3\\\", \\\"description\\\": \\\"Firecrawl
|
||||
RAG Llama 3\\\" }\\\\\\n ]\\\\\\n}\\\\\\n```\\\\\\n\\\\\\n### Search\\\\\\n\\\\\\n[Permalink:
|
||||
Search](https://github.com/firecrawl/firecrawl#search)\\\\\\n\\\\\\nSearch
|
||||
the web and get full content from results\\\\\\n\\\\\\nFirecrawl\u2019s search
|
||||
API allows you to perform web searches and optionally scrape the search results
|
||||
in one operation.\\\\\\n\\\\\\n- Choose specific output formats (markdown,
|
||||
HTML, links, screenshots)\\\\\\n- Search the web with customizable parameters
|
||||
(language, country, etc.)\\\\\\n- Optionally retrieve content from search
|
||||
results in various formats\\\\\\n- Control the number of results and set timeouts\\\\\\n\\\\\\n```\\\\\\ncurl
|
||||
-X POST https://api.firecrawl.dev/v2/search \\\\\\\\\\n -H \\\"Content-Type:
|
||||
application/json\\\" \\\\\\\\\\n -H \\\"Authorization: Bearer fc-YOUR_API_KEY\\\"
|
||||
\\\\\\\\\\n -d '{\\\\\\n \\\"query\\\": \\\"what is firecrawl?\\\",\\\\\\n
|
||||
\ \\\"limit\\\": 5\\\\\\n }'\\\\\\n```\\\\\\n\\\\\\n#### Response\\\\\\n\\\\\\n[Permalink:
|
||||
Response](https://github.com/firecrawl/firecrawl#response)\\\\\\n\\\\\\n```\\\\\\n{\\\\\\n
|
||||
\ \\\"success\\\": true,\\\\\\n \\\"data\\\": [\\\\\\n {\\\\\\n \\\"url\\\":
|
||||
\\\"https://firecrawl.dev\\\",\\\\\\n \\\"title\\\": \\\"Firecrawl |
|
||||
Home Page\\\",\\\\\\n \\\"description\\\": \\\"Turn websites into LLM-ready
|
||||
data with Firecrawl\\\"\\\\\\n },\\\\\\n {\\\\\\n \\\"url\\\":
|
||||
\\\"https://docs.firecrawl.dev\\\",\\\\\\n \\\"title\\\": \\\"Documentation
|
||||
| Firecrawl\\\",\\\\\\n \\\"description\\\": \\\"Learn how to use Firecrawl
|
||||
in your own applications\\\"\\\\\\n }\\\\\\n ]\\\\\\n}\\\\\\n```\\\\\\n\\\\\\n####
|
||||
With content scraping\\\\\\n\\\\\\n[Permalink: With content scraping](https://github.com/firecrawl/firecrawl#with-content-scraping)\\\\\\n\\\\\\n```\\\\\\ncurl
|
||||
-X POST https://api.firecrawl.dev/v2/search \\\\\\\\\\n -H \\\"Content-Type:
|
||||
application/json\\\" \\\\\\\\\\n -H \\\"Authorization: Bearer fc-YOUR_API_KEY\\\"
|
||||
\\\\\\\\\\n -d '{\\\\\\n \\\"query\\\": \\\"what is firecrawl?\\\",\\\\\\n
|
||||
\ \\\"limit\\\": 5,\\\\\\n \\\"scrapeOptions\\\": {\\\\\\n \\\"formats\\\":
|
||||
[\\\"markdown\\\", \\\"links\\\"]\\\\\\n }\\\\\\n }'\\\\\\n```\\\\\\n\\\\\\n###
|
||||
Extract (Beta)\\\\\\n\\\\\\n[Permalink: Extract (Beta)](https://github.com/firecrawl/firecrawl#extract-beta)\\\\\\n\\\\\\nGet
|
||||
structured data from entire websites with a prompt and/or a schema.\\\\\\n\\\\\\nYou
|
||||
can extract structured data from one or multiple URLs, including wildcards:\\\\\\n\\\\\\nSingle
|
||||
Page:\\\\\\nExample: [https://firecrawl.dev/some-page](https://firecrawl.dev/some-page)\\\\\\n\\\\\\nMultiple
|
||||
Pages / Full Domain\\\\\\nExample: [https://firecrawl.dev/](https://firecrawl.dev/)\\\\*\\\\\\n\\\\\\nWhen
|
||||
you use /\\\\*, Firecrawl will automatically crawl and parse all URLs it can
|
||||
discover in that domain, then extract the requested data.\\\\\\n\\\\\\n```\\\\\\ncurl
|
||||
-X POST https://api.firecrawl.dev/v2/extract \\\\\\\\\\n -H 'Content-Type:
|
||||
application/json' \\\\\\\\\\n -H 'Authorization: Bearer YOUR_API_KEY' \\\\\\\\\\n
|
||||
\ -d '{\\\\\\n \\\"urls\\\": [\\\\\\n \\\"https://firecrawl.dev/*\\\",\\\\\\n
|
||||
\ \\\"https://docs.firecrawl.dev/\\\",\\\\\\n \\\"https://www.ycombinator.com/companies\\\"\\\\\\n
|
||||
\ ],\\\\\\n \\\"prompt\\\": \\\"Extract the company mission, whether
|
||||
it is open source, and whether it is in Y Combinator from the page.\\\",\\\\\\n
|
||||
\ \\\"schema\\\": {\\\\\\n \\\"type\\\": \\\"object\\\",\\\\\\n
|
||||
\ \\\"properties\\\": {\\\\\\n \\\"company_mission\\\": {\\\\\\n
|
||||
\ \\\"type\\\": \\\"string\\\"\\\\\\n },\\\\\\n \\\"is_open_source\\\":
|
||||
{\\\\\\n \\\"type\\\": \\\"boolean\\\"\\\\\\n },\\\\\\n
|
||||
\ \\\"is_in_yc\\\": {\\\\\\n \\\"type\\\": \\\"boolean\\\"\\\\\\n
|
||||
\ }\\\\\\n },\\\\\\n \\\"required\\\": [\\\\\\n \\\"company_mission\\\",\\\\\\n
|
||||
\ \\\"is_open_source\\\",\\\\\\n \\\"is_in_yc\\\"\\\\\\n
|
||||
\ ]\\\\\\n }\\\\\\n }'\\\\\\n```\\\\\\n\\\\\\n```\\\\\\n{\\\\\\n
|
||||
\ \\\"success\\\": true,\\\\\\n \\\"id\\\": \\\"44aa536d-f1cb-4706-ab87-ed0386685740\\\",\\\\\\n
|
||||
\ \\\"urlTrace\\\": []\\\\\\n}\\\\\\n```\\\\\\n\\\\\\nIf you are using the
|
||||
sdks, it will auto pull the response for you:\\\\\\n\\\\\\n```\\\\\\n{\\\\\\n
|
||||
\ \\\"success\\\": true,\\\\\\n \\\"data\\\": {\\\\\\n \\\"company_mission\\\":
|
||||
\\\"Firecrawl is the easiest way to extract data from the web. Developers
|
||||
use us to reliably convert URLs into LLM-ready markdown or structured data
|
||||
with a single API call.\\\",\\\\\\n \\\"supports_sso\\\": false,\\\\\\n
|
||||
\ \\\"is_open_source\\\": true,\\\\\\n \\\"is_in_yc\\\": true\\\\\\n
|
||||
\ }\\\\\\n}\\\\\\n```\\\\\\n\\\\\\n### LLM Extraction (Beta)\\\\\\n\\\\\\n[Permalink:
|
||||
LLM Extraction (Beta)](https://github.com/firecrawl/firecrawl#llm-extraction-beta)\\\\\\n\\\\\\nUsed
|
||||
to extract structured data from scraped pages.\\\\\\n\\\\\\n```\\\\\\ncurl
|
||||
-X POST https://api.firecrawl.dev/v2/scrape \\\\\\\\\\n -H 'Content-Type:
|
||||
application/json' \\\\\\\\\\n -H 'Authorization: Bearer YOUR_API_KEY' \\\\\\\\\\n
|
||||
\ -d '{\\\\\\n \\\"url\\\": \\\"https://www.mendable.ai/\\\",\\\\\\n \\\"formats\\\":
|
||||
[\\\\\\n {\\\\\\n \\\"type\\\": \\\"json\\\",\\\\\\n \\\"schema\\\":
|
||||
{\\\\\\n \\\"type\\\": \\\"object\\\",\\\\\\n \\\"properties\\\":
|
||||
{\\\\\\n \\\"company_mission\\\": { \\\"type\\\": \\\"string\\\"
|
||||
},\\\\\\n \\\"supports_sso\\\": { \\\"type\\\": \\\"boolean\\\"
|
||||
},\\\\\\n \\\"is_open_source\\\": { \\\"type\\\": \\\"boolean\\\"
|
||||
},\\\\\\n \\\"is_in_yc\\\": { \\\"type\\\": \\\"boolean\\\" }\\\\\\n
|
||||
\ }\\\\\\n }\\\\\\n }\\\\\\n ]\\\\\\n }'\\\\\\n```\\\\\\n\\\\\\n```\\\\\\n{\\\\\\n
|
||||
\ \\\"success\\\": true,\\\\\\n \\\"data\\\": {\\\\\\n \\\"content\\\":
|
||||
\\\"Raw Content\\\",\\\\\\n \\\"metadata\\\": {\\\\\\n \\\"title\\\":
|
||||
\\\"Mendable\\\",\\\\\\n \\\"description\\\": \\\"Mendable allows you
|
||||
to easily build AI chat applications. Ingest, customize, then deploy with
|
||||
one line of code anywhere you want. Brought to you by SideGuide\\\",\\\\\\n
|
||||
\ \\\"robots\\\": \\\"follow, index\\\",\\\\\\n \\\"ogTitle\\\":
|
||||
\\\"Mendable\\\",\\\\\\n \\\"ogDescription\\\": \\\"Mendable allows you
|
||||
to easily build AI chat applications. Ingest, customize, then deploy with
|
||||
one line of code anywhere you want. Brought to you by SideGuide\\\",\\\\\\n
|
||||
\ \\\"ogUrl\\\": \\\"https://mendable.ai/\\\",\\\\\\n \\\"ogImage\\\":
|
||||
\\\"https://mendable.ai/mendable_new_og1.png\\\",\\\\\\n \\\"ogLocaleAlternate\\\":
|
||||
[],\\\\\\n \\\"ogSiteName\\\": \\\"Mendable\\\",\\\\\\n \\\"sourceURL\\\":
|
||||
\\\"https://mendable.ai/\\\"\\\\\\n },\\\\\\n \\\"json\\\": {\\\\\\n
|
||||
\ \\\"company_mission\\\": \\\"Train a secure AI on your technical resources
|
||||
that answers customer and employee questions so your team doesn't have to\\\",\\\\\\n
|
||||
\ \\\"supports_sso\\\": true,\\\\\\n \\\"is_open_source\\\": false,\\\\\\n
|
||||
\ \\\"is_in_yc\\\": true\\\\\\n }\\\\\\n }\\\\\\n}\\\\\\n```\\\\\\n\\\\\\n###
|
||||
Extracting without a schema (New)\\\\\\n\\\\\\n[Permalink: Extracting without
|
||||
a schema (New)](https://github.com/firecrawl/firecrawl#extracting-without-a-schema-new)\\\\\\n\\\\\\nYou
|
||||
can now extract without a schema by just passing a `prompt` to the endpoint.
|
||||
The llm chooses the structure of the data.\\\\\\n\\\\\\n```\\\\\\ncurl -X
|
||||
POST https://api.firecrawl.dev/v2/scrape \\\\\\\\\\n -H 'Content-Type:
|
||||
application/json' \\\\\\\\\\n -H 'Authorization: Bearer YOUR_API_KEY' \\\\\\\\\\n
|
||||
\ -d '{\\\\\\n \\\"url\\\": \\\"https://docs.firecrawl.dev/\\\",\\\\\\n
|
||||
\ \\\"formats\\\": [\\\\\\n {\\\\\\n \\\"type\\\": \\\"json\\\",\\\\\\n
|
||||
\ \\\"prompt\\\": \\\"Extract the company mission from the page.\\\"\\\\\\n
|
||||
\ }\\\\\\n ]\\\\\\n }'\\\\\\n```\\\\\\n\\\\\\n### Interacting
|
||||
with the page with Actions (Cloud-only)\\\\\\n\\\\\\n[Permalink: Interacting
|
||||
with the page with Actions (Cloud-only)](https://github.com/firecrawl/firecrawl#interacting-with-the-page-with-actions-cloud-only)\\\\\\n\\\\\\nFirecrawl
|
||||
allows you to perform various actions on a web page before scraping its content.
|
||||
This is particularly useful for interacting with dynamic content, navigating
|
||||
through pages, or accessing content that requires user interaction.\\\\\\n\\\\\\nHere
|
||||
is an example of how to use actions to navigate to google.com, search for
|
||||
Firecrawl, click on the first result, and take a screenshot.\\\\\\n\\\\\\n```\\\\\\ncurl
|
||||
-X POST https://api.firecrawl.dev/v2/scrape \\\\\\\\\\n -H 'Content-Type:
|
||||
application/json' \\\\\\\\\\n -H 'Authorization: Bearer YOUR_API_KEY' \\\\\\\\\\n
|
||||
\ -d '{\\\\\\n \\\"url\\\": \\\"google.com\\\",\\\\\\n \\\"formats\\\":
|
||||
[\\\"markdown\\\"],\\\\\\n \\\"actions\\\": [\\\\\\n {\\\"type\\\":
|
||||
\\\"wait\\\", \\\"milliseconds\\\": 2000},\\\\\\n {\\\"type\\\":
|
||||
\\\"click\\\", \\\"selector\\\": \\\"textarea[title=\\\\\\\"Search\\\\\\\"]\\\"},\\\\\\n
|
||||
\ {\\\"type\\\": \\\"wait\\\", \\\"milliseconds\\\": 2000},\\\\\\n
|
||||
\ {\\\"type\\\": \\\"write\\\", \\\"text\\\": \\\"firecrawl\\\"},\\\\\\n
|
||||
\ {\\\"type\\\": \\\"wait\\\", \\\"milliseconds\\\": 2000},\\\\\\n
|
||||
\ {\\\"type\\\": \\\"press\\\", \\\"key\\\": \\\"ENTER\\\"},\\\\\\n
|
||||
\ {\\\"type\\\": \\\"wait\\\", \\\"milliseconds\\\": 3000},\\\\\\n
|
||||
\ {\\\"type\\\": \\\"click\\\", \\\"selector\\\": \\\"h3\\\"},\\\\\\n
|
||||
\ {\\\"type\\\": \\\"wait\\\", \\\"milliseconds\\\": 3000},\\\\\\n
|
||||
\ {\\\"type\\\": \\\"screenshot\\\"}\\\\\\n ]\\\\\\n }'\\\\\\n```\\\\\\n\\\\\\n###
|
||||
Batch Scraping Multiple URLs (New)\\\\\\n\\\\\\n[Permalink: Batch Scraping
|
||||
Multiple URLs (New)](https://github.com/firecrawl/firecrawl#batch-scraping-multiple-urls-new)\\\\\\n\\\\\\nYou
|
||||
can now batch scrape multiple URLs at the same time. It is very similar to
|
||||
how the /crawl endpoint works. It submits a batch scrape job and returns a
|
||||
job ID to check the status of the batch scrape.\\\\\\n\\\\\\n```\\\\\\ncurl
|
||||
-X POST https://api.firecrawl.dev/v2/batch/scrape \\\\\\\\\\n -H 'Content-Type:
|
||||
application/json' \\\\\\\\\\n -H 'Authorization: Bearer YOUR_API_KEY' \\\\\\\\\\n
|
||||
\ -d '{\\\\\\n \\\"urls\\\": [\\\"https://docs.firecrawl.dev\\\", \\\"https://docs.firecrawl.dev/sdks/overview\\\"],\\\\\\n
|
||||
\ \\\"formats\\\" : [\\\"markdown\\\", \\\"html\\\"]\\\\\\n }'\\\\\\n```\\\\\\n\\\\\\n##
|
||||
Using Python SDK\\\\\\n\\\\\\n[Permalink: Using Python SDK](https://github.com/firecrawl/firecrawl#using-python-sdk)\\\\\\n\\\\\\n###
|
||||
Installing Python SDK\\\\\\n\\\\\\n[Permalink: Installing Python SDK](https://github.com/firecrawl/firecrawl#installing-python-sdk)\\\\\\n\\\\\\n```\\\\\\npip
|
||||
install firecrawl-py\\\\\\n```\\\\\\n\\\\\\n### Crawl a website\\\\\\n\\\\\\n[Permalink:
|
||||
Crawl a website](https://github.com/firecrawl/firecrawl#crawl-a-website)\\\\\\n\\\\\\n```\\\\\\nfrom
|
||||
firecrawl import Firecrawl\\\\\\n\\\\\\nfirecrawl = Firecrawl(api_key=\\\"fc-YOUR_API_KEY\\\")\\\\\\n\\\\\\n#
|
||||
Scrape a website (returns a Document)\\\\\\ndoc = firecrawl.scrape(\\\\\\n
|
||||
\ \\\"https://firecrawl.dev\\\",\\\\\\n formats=[\\\"markdown\\\", \\\"html\\\"],\\\\\\n)\\\\\\nprint(doc.markdown)\\\\\\n\\\\\\n#
|
||||
Crawl a website\\\\\\nresponse = firecrawl.crawl(\\\\\\n \\\"https://firecrawl.dev\\\",\\\\\\n
|
||||
\ limit=100,\\\\\\n scrape_options={\\\"formats\\\": [\\\"markdown\\\",
|
||||
\\\"html\\\"]},\\\\\\n poll_interval=30,\\\\\\n)\\\\\\nprint(response)\\\\\\n```\\\\\\n\\\\\\n###
|
||||
Extracting structured data from a URL\\\\\\n\\\\\\n[Permalink: Extracting
|
||||
structured data from a URL](https://github.com/firecrawl/firecrawl#extracting-structured-data-from-a-url)\\\\\\n\\\\\\nWith
|
||||
LLM extraction, you can easily extract structured data from any URL. We support
|
||||
pydantic schemas to make it easier for you too. Here is how you to use it:\\\\\\n\\\\\\n```\\\\\\nfrom
|
||||
pydantic import BaseModel, Field\\\\\\nfrom typing import List\\\\\\n\\\\\\nclass
|
||||
Article(BaseModel):\\\\\\n title: str\\\\\\n points: int\\\\\\n by:
|
||||
str\\\\\\n commentsURL: str\\\\\\n\\\\\\nclass TopArticles(BaseModel):\\\\\\n
|
||||
\ top: List[Article] = Field(..., description=\\\"Top 5 stories\\\")\\\\\\n\\\\\\n#
|
||||
Use JSON format with a Pydantic schema\\\\\\ndoc = firecrawl.scrape(\\\\\\n
|
||||
\ \\\"https://news.ycombinator.com\\\",\\\\\\n formats=[{\\\"type\\\":
|
||||
\\\"json\\\", \\\"schema\\\": TopArticles}],\\\\\\n)\\\\\\nprint(doc.json)\\\\\\n```\\\\\\n\\\\\\n##
|
||||
Using the Node SDK\\\\\\n\\\\\\n[Permalink: Using the Node SDK](https://github.com/firecrawl/firecrawl#using-the-node-sdk)\\\\\\n\\\\\\n###
|
||||
Installation\\\\\\n\\\\\\n[Permalink: Installation](https://github.com/firecrawl/firecrawl#installation)\\\\\\n\\\\\\nTo
|
||||
install the Firecrawl Node SDK, you can use npm:\\\\\\n\\\\\\n```\\\\\\nnpm
|
||||
install @mendable/firecrawl-js\\\\\\n```\\\\\\n\\\\\\n### Usage\\\\\\n\\\\\\n[Permalink:
|
||||
Usage](https://github.com/firecrawl/firecrawl#usage)\\\\\\n\\\\\\n1. Get an
|
||||
API key from [firecrawl.dev](https://firecrawl.dev/)\\\\\\n2. Set the API
|
||||
key as an environment variable named `FIRECRAWL_API_KEY` or pass it as a parameter
|
||||
to the `Firecrawl` class.\\\\\\n\\\\\\n```\\\\\\nimport Firecrawl from '@mendable/firecrawl-js';\\\\\\n\\\\\\nconst
|
||||
firecrawl = new Firecrawl({ apiKey: 'fc-YOUR_API_KEY' });\\\\\\n\\\\\\n//
|
||||
Scrape a website\\\\\\nconst doc = await firecrawl.scrape('https://firecrawl.dev',
|
||||
{\\\\\\n formats: ['markdown', 'html'],\\\\\\n});\\\\\\nconsole.log(doc);\\\\\\n\\\\\\n//
|
||||
Crawl a website\\\\\\nconst response = await firecrawl.crawl('https://firecrawl.dev',
|
||||
{\\\\\\n limit: 100,\\\\\\n scrapeOptions: { formats: ['markdown', 'html']
|
||||
},\\\\\\n});\\\\\\nconsole.log(response);\\\\\\n```\\\\\\n\\\\\\n### Extracting
|
||||
structured data from a URL\\\\\\n\\\\\\n[Permalink: Extracting structured
|
||||
data from a URL](https://github.com/firecrawl/firecrawl#extracting-structured-data-from-a-url-1)\\\\\\n\\\\\\nWith
|
||||
LLM extraction, you can easily extract structured data from any URL. We support
|
||||
zod schema to make it easier for you too. Here is how to use it:\\\\\\n\\\\\\n```\\\\\\nimport
|
||||
Firecrawl from '@mendable/firecrawl-js';\\\\\\nimport { z } from 'zod';\\\\\\n\\\\\\nconst
|
||||
firecrawl = new Firecrawl({ apiKey: 'fc-YOUR_API_KEY' });\\\\\\n\\\\\\n//
|
||||
Define schema to extract contents into\\\\\\nconst schema = z.object({\\\\\\n
|
||||
\ top: z\\\\\\n .array(\\\\\\n z.object({\\\\\\n title: z.string(),\\\\\\n
|
||||
\ points: z.number(),\\\\\\n by: z.string(),\\\\\\n commentsURL:
|
||||
z.string(),\\\\\\n })\\\\\\n )\\\\\\n .length(5)\\\\\\n .describe('Top
|
||||
5 stories on Hacker News'),\\\\\\n});\\\\\\n\\\\\\n// Use the v2 extract API
|
||||
with direct Zod schema support\\\\\\nconst extractRes = await firecrawl.extract({\\\\\\n
|
||||
\ urls: ['https://news.ycombinator.com'],\\\\\\n schema,\\\\\\n prompt:
|
||||
'Extract the top 5 stories',\\\\\\n});\\\\\\n\\\\\\nconsole.log(extractRes);\\\\\\n```\\\\\\n\\\\\\n##
|
||||
Open Source vs Cloud Offering\\\\\\n\\\\\\n[Permalink: Open Source vs Cloud
|
||||
Offering](https://github.com/firecrawl/firecrawl#open-source-vs-cloud-offering)\\\\\\n\\\\\\nFirecrawl
|
||||
is open source available under the AGPL-3.0 license.\\\\\\n\\\\\\nTo deliver
|
||||
the best possible product, we offer a hosted version of Firecrawl alongside
|
||||
our open-source offering. The cloud solution allows us to continuously innovate
|
||||
and maintain a high-quality, sustainable service for all users.\\\\\\n\\\\\\nFirecrawl
|
||||
Cloud is available at [firecrawl.dev](https://firecrawl.dev/) and offers a
|
||||
range of features that are not available in the open source version:\\\\\\n\\\\\\n[](https://raw.githubusercontent.com/firecrawl/firecrawl/main/img/open-source-cloud.png)\\\\\\n\\\\\\n##
|
||||
Contributing\\\\\\n\\\\\\n[Permalink: Contributing](https://github.com/firecrawl/firecrawl#contributing)\\\\\\n\\\\\\nWe
|
||||
love contributions! Please read our [contributing guide](https://github.com/firecrawl/firecrawl/blob/main/CONTRIBUTING.md)
|
||||
before submitting a pull request. If you'd like to self-host, refer to the
|
||||
[self-hosting guide](https://github.com/firecrawl/firecrawl/blob/main/SELF_HOST.md).\\\\\\n\\\\\\n_It
|
||||
is the sole responsibility of the end users to respect websites' policies
|
||||
when scraping, searching and crawling with Firecrawl. Users are advised to
|
||||
adhere to the applicable privacy policies and terms of use of the websites
|
||||
prior to initiating any scraping activities. By default, Firecrawl respects
|
||||
the directives specified in the websites' robots.txt files when crawling.
|
||||
By utilizing Firecrawl, you expressly agree to comply with these conditions._\\\\\\n\\\\\\n##
|
||||
Contributors\\\\\\n\\\\\\n[Permalink: Contributors](https://github.com/firecrawl/firecrawl#contributors)\\\\\\n\\\\\\n[](https://github.com/firecrawl/firecrawl/graphs/contributors)\\\\\\n\\\\\\n##
|
||||
License Disclaimer\\\\\\n\\\\\\n[Permalink: License Disclaimer](https://github.com/firecrawl/firecrawl#license-disclaimer)\\\\\\n\\\\\\nThis
|
||||
project is primarily licensed under the GNU Affero General Public License
|
||||
v3.0 (AGPL-3.0), as specified in the LICENSE file in the root directory of
|
||||
this repository. However, certain components of this project are licensed
|
||||
under the MIT License. Refer to the LICENSE files in these specific directories
|
||||
for details.\\\\\\n\\\\\\nPlease note:\\\\\\n\\\\\\n- The AGPL-3.0 license
|
||||
applies to all parts of the project unless otherwise specified.\\\\\\n- The
|
||||
SDKs and some UI components are licensed under the MIT License. Refer to the
|
||||
LICENSE files in these specific directories for details.\\\\\\n- When using
|
||||
or contributing to this project, ensure you comply with the appropriate license
|
||||
terms for the specific component you are working with.\\\\\\n\\\\\\nFor more
|
||||
details on the licensing of specific components, please refer to the LICENSE
|
||||
files in the respective directories or contact the project maintainers.\\\\\\n\\\\\\n[\u2191
|
||||
Back to Top \u2191](https://github.com/firecrawl/firecrawl#readme-top)\\\\\\n\\\\\\n##
|
||||
About\\\\\\n\\\\\\n\U0001F525 The Web Data API for AI - Turn entire websites
|
||||
into LLM-ready markdown or structured data\\\\\\n\\\\\\n\\\\\\n[firecrawl.dev](https://firecrawl.dev/
|
||||
\\\"https://firecrawl.dev\\\")\\\\\\n\\\\\\n### Topics\\\\\\n\\\\\\n[markdown](https://github.com/topics/markdown
|
||||
\\\"Topic: markdown\\\") [crawler](https://github.com/topics/crawler \\\"Topic:
|
||||
crawler\\\") [scraper](https://github.com/topics/scraper \\\"Topic: scraper\\\")
|
||||
[ai](https://github.com/topics/ai \\\"Topic: ai\\\") [html-to-markdown](https://github.com/topics/html-to-markdown
|
||||
\\\"Topic: html-to-markdown\\\") [web-crawler](https://github.com/topics/web-crawler
|
||||
\\\"Topic: web-crawler\\\") [scraping](https://github.com/topics/scraping
|
||||
\\\"Topic: scraping\\\") [web-scraper](https://github.com/topics/web-scraper
|
||||
\\\"Topic: web-scraper\\\") [web-scraping](https://github.com/topics/web-scraping
|
||||
\\\"Topic: web-scraping\\\") [data-extraction](https://github.com/topics/data-extraction
|
||||
\\\"Topic: data-extraction\\\") [webscraping](https://github.com/topics/webscraping
|
||||
\\\"Topic: webscraping\\\") [web-data-extraction](https://github.com/topics/web-data-extraction
|
||||
\\\"Topic: web-data-extraction\\\") [ai-agents](https://github.com/topics/ai-agents
|
||||
\\\"Topic: ai-agents\\\") [web-search](https://github.com/topics/web-search
|
||||
\\\"Topic: web-search\\\") [ai-search](https://github.com/topics/ai-search
|
||||
\\\"Topic: ai-search\\\") [web-data](https://github.com/topics/web-data \\\"Topic:
|
||||
web-data\\\") [llm](https://github.com/topics/llm \\\"Topic: llm\\\") [ai-crawler](https://github.com/topics/ai-crawler
|
||||
\\\"Topic: ai-crawler\\\") [ai-scraping](https://github.com/topics/ai-scraping
|
||||
\\\"Topic: ai-scraping\\\")\\\\\\n\\\\\\n### Resources\\\\\\n\\\\\\n[Readme](https://github.com/firecrawl/firecrawl#readme-ov-file)\\\\\\n\\\\\\n###
|
||||
License\\\\\\n\\\\\\n[AGPL-3.0 license](https://github.com/firecrawl/firecrawl#AGPL-3.0-1-ov-file)\\\\\\n\\\\\\n###
|
||||
Contributing\\\\\\n\\\\\\n[Contributing](https://github.com/firecrawl/firecrawl#contributing-ov-file)\\\\\\n\\\\\\n###
|
||||
Uh oh!\\\\\\n\\\\\\nThere was an error while loading. [Please reload this
|
||||
page](https://github.com/firecrawl/firecrawl).\\\\\\n\\\\\\n[Activity](https://github.com/firecrawl/firecrawl/activity)\\\\\\n\\\\\\n[Custom
|
||||
properties](https://github.com/firecrawl/firecrawl/custom-properties)\\\\\\n\\\\\\n###
|
||||
Stars\\\\\\n\\\\\\n[**65.2k**\\\\\\\\\\nstars](https://github.com/firecrawl/firecrawl/stargazers)\\\\\\n\\\\\\n###
|
||||
Watchers\\\\\\n\\\\\\n[**256**\\\\\\\\\\nwatching](https://github.com/firecrawl/firecrawl/watchers)\\\\\\n\\\\\\n###
|
||||
Forks\\\\\\n\\\\\\n[**5.1k**\\\\\\\\\\nforks](https://github.com/firecrawl/firecrawl/forks)\\\\\\n\\\\\\n[Report
|
||||
repository](https://github.com/contact/report-content?content_url=https%3A%2F%2Fgithub.com%2Ffirecrawl%2Ffirecrawl&report=firecrawl+%28user%29)\\\\\\n\\\\\\n##
|
||||
[Releases\\\\ 28](https://github.com/firecrawl/firecrawl/releases)\\\\\\n\\\\\\n[v2.4.0\\\\\\\\\\nLatest\\\\\\\\\\n\\\\\\\\\\n2
|
||||
weeks agoOct 13, 2025](https://github.com/firecrawl/firecrawl/releases/tag/v2.4.0)\\\\\\n\\\\\\n[\\\\+
|
||||
27 releases](https://github.com/firecrawl/firecrawl/releases)\\\\\\n\\\\\\n##
|
||||
[Packages\\\\ 3](https://github.com/orgs/firecrawl/packages?repo_name=firecrawl)\\\\\\n\\\\\\n-
|
||||
[firecrawl](https://github.com/orgs/firecrawl/packages/container/package/firecrawl)\\\\\\n-
|
||||
[playwright-service](https://github.com/orgs/firecrawl/packages/container/package/playwright-service)\\\\\\n-
|
||||
[nuq-postgres](https://github.com/orgs/firecrawl/packages/container/package/nuq-postgres)\\\\\\n\\\\\\n##
|
||||
[Contributors\\\\ 121](https://github.com/firecrawl/firecrawl/graphs/contributors)\\\\\\n\\\\\\n[\\\\+
|
||||
107 contributors](https://github.com/firecrawl/firecrawl/graphs/contributors)\\\\\\n\\\\\\n##
|
||||
Languages\\\\\\n\\\\\\n- [TypeScript73.5%](https://github.com/firecrawl/firecrawl/search?l=typescript)\\\\\\n-
|
||||
[Python18.9%](https://github.com/firecrawl/firecrawl/search?l=python)\\\\\\n-
|
||||
[Rust6.0%](https://github.com/firecrawl/firecrawl/search?l=rust)\\\\\\n- [Astro0.6%](https://github.com/firecrawl/firecrawl/search?l=astro)\\\\\\n-
|
||||
[JavaScript0.3%](https://github.com/firecrawl/firecrawl/search?l=javascript)\\\\\\n-
|
||||
[Jupyter Notebook0.2%](https://github.com/firecrawl/firecrawl/search?l=jupyter-notebook)\\\\\\n-
|
||||
Other0.5%\",\"metadata\":{\"octolytics-dimension-repository_network_root_id\":\"787076358\",\"visitor-hmac\":\"163b2538b2335f7d4000a770785477e15881e1101708ca5ff1e8c021095f6ca1\",\"og:type\":\"object\",\"language\":\"en\",\"route-action\":\"disambiguate\",\"og:title\":\"GitHub
|
||||
- firecrawl/firecrawl: \U0001F525 The Web Data API for AI - Turn entire websites
|
||||
into LLM-ready markdown or structured data\",\"octolytics-dimension-repository_public\":\"true\",\"octolytics-dimension-repository_network_root_nwo\":\"firecrawl/firecrawl\",\"browser-errors-url\":\"https://api.github.com/_private/browser/errors\",\"browser-stats-url\":\"https://api.github.com/_private/browser/stats\",\"twitter:title\":\"GitHub
|
||||
- firecrawl/firecrawl: \U0001F525 The Web Data API for AI - Turn entire websites
|
||||
into LLM-ready markdown or structured data\",\"ui-target\":\"full\",\"og:image\":\"https://repository-images.githubusercontent.com/787076358/f9616c09-3701-41ef-b5a6-fdf912ffb15b\",\"google-site-verification\":\"Apib7-x98H0j5cPqHWwSMm6dNU4GmODRoqxLiDzdx9I\",\"ogSiteName\":\"GitHub\",\"route-pattern\":\"/:user_id/:repository\",\"visitor-payload\":\"eyJyZWZlcnJlciI6IiIsInJlcXVlc3RfaWQiOiJBMTVGOjE3OUI0RDo2MzdFQUREOjg3MzEwOTM6NjkwMTE4MjUiLCJ2aXNpdG9yX2lkIjoiNDkyNzk2MzExNjg5OTIxMTMwMSIsInJlZ2lvbl9lZGdlIjoiaWFkIiwicmVnaW9uX3JlbmRlciI6ImlhZCJ9\",\"og:description\":\"\U0001F525
|
||||
The Web Data API for AI - Turn entire websites into LLM-ready markdown or
|
||||
structured data - firecrawl/firecrawl\",\"expected-hostname\":\"github.com\",\"release\":\"66136a30a16cc69206f1249b6ba072daa2174535\",\"title\":\"GitHub
|
||||
- firecrawl/firecrawl: \U0001F525 The Web Data API for AI - Turn entire websites
|
||||
into LLM-ready markdown or structured data\",\"ogDescription\":\"\U0001F525
|
||||
The Web Data API for AI - Turn entire websites into LLM-ready markdown or
|
||||
structured data - firecrawl/firecrawl\",\"twitter:card\":\"summary_large_image\",\"fb:app_id\":\"1401488693436528\",\"color-scheme\":\"light
|
||||
dark\",\"twitter:description\":\"\U0001F525 The Web Data API for AI - Turn
|
||||
entire websites into LLM-ready markdown or structured data - firecrawl/firecrawl\",\"favicon\":\"https://github.githubassets.com/favicons/favicon.svg\",\"viewport\":\"width=device-width\",\"twitter:image\":\"https://repository-images.githubusercontent.com/787076358/f9616c09-3701-41ef-b5a6-fdf912ffb15b\",\"user-login\":\"\",\"description\":\"\U0001F525
|
||||
The Web Data API for AI - Turn entire websites into LLM-ready markdown or
|
||||
structured data - firecrawl/firecrawl\",\"octolytics-dimension-repository_nwo\":\"firecrawl/firecrawl\",\"octolytics-dimension-user_id\":\"135057108\",\"twitter:site\":\"@github\",\"og:url\":\"https://github.com/firecrawl/firecrawl\",\"octolytics-dimension-user_login\":\"firecrawl\",\"hostname\":\"github.com\",\"current-catalog-service-hash\":\"f3abb0cc802f3d7b95fc8762b94bdcb13bf39634c40c357301c4aa1d67a256fb\",\"html-safe-nonce\":\"e5653da3800db7de2c8b4a64ff6367242043a9e452608e9a6941a1c9e8346cfc\",\"apple-itunes-app\":\"app-id=1477376905,
|
||||
app-argument=https://github.com/firecrawl/firecrawl\",\"turbo-cache-control\":\"no-preview\",\"og:site_name\":\"GitHub\",\"request-id\":\"A15F:179B4D:637EADD:8731093:69011825\",\"octolytics-url\":\"https://collector.github.com/github/collect\",\"octolytics-dimension-repository_is_fork\":\"false\",\"fetch-nonce\":\"v2:bc80e85b-edaf-e746-9f2c-ffdc75854b07\",\"og:image:alt\":\"\U0001F525
|
||||
The Web Data API for AI - Turn entire websites into LLM-ready markdown or
|
||||
structured data - firecrawl/firecrawl\",\"github-keyboard-shortcuts\":\"repository,copilot\",\"ogTitle\":\"GitHub
|
||||
- firecrawl/firecrawl: \U0001F525 The Web Data API for AI - Turn entire websites
|
||||
into LLM-ready markdown or structured data\",\"ogImage\":\"https://repository-images.githubusercontent.com/787076358/f9616c09-3701-41ef-b5a6-fdf912ffb15b\",\"analytics-location\":\"/<user-name>/<repo-name>\",\"route-controller\":\"files\",\"octolytics-dimension-repository_id\":\"787076358\",\"ogUrl\":\"https://github.com/firecrawl/firecrawl\",\"go-import\":\"github.com/firecrawl/firecrawl
|
||||
git https://github.com/firecrawl/firecrawl.git\",\"hovercard-subject-tag\":\"repository:787076358\",\"theme-color\":\"#1e2327\",\"turbo-body-classes\":\"logged-out
|
||||
env-production page-responsive\",\"scrapeId\":\"ec4d99a0-4c4f-4d1a-9fd2-08b8f891f883\",\"sourceURL\":\"https://github.com/firecrawl/firecrawl\",\"url\":\"https://github.com/firecrawl/firecrawl\",\"statusCode\":200,\"contentType\":\"text/html;
|
||||
charset=utf-8\",\"proxyUsed\":\"basic\",\"cacheState\":\"hit\",\"cachedAt\":\"2025-10-28T19:23:20.106Z\"}},{\"url\":\"https://x.com/firecrawl_dev?lang=en\",\"title\":\"Firecrawl
|
||||
(@firecrawl_dev) / Posts / X\",\"description\":\"Firecrawl (@firecrawl_dev)
|
||||
- Posts - Turn websites into LLM-ready data. Built by @mendableai team Open
|
||||
source: | X (formerly Twitter)\",\"position\":3},{\"url\":\"https://github.com/firecrawl\",\"title\":\"Firecrawl
|
||||
- GitHub\",\"description\":\"Building AI applications? You need clean, structured
|
||||
data from the web. Firecrawl handles the complexity of modern web scraping
|
||||
so you can focus on building ...\",\"position\":4,\"category\":\"github\",\"markdown\":\"[Skip
|
||||
to content](https://github.com/firecrawl#start-of-content)\\n\\nYou signed
|
||||
in with another tab or window. [Reload](https://github.com/firecrawl) to refresh
|
||||
your session.You signed out in another tab or window. [Reload](https://github.com/firecrawl)
|
||||
to refresh your session.You switched accounts on another tab or window. [Reload](https://github.com/firecrawl)
|
||||
to refresh your session.Dismiss alert\\n\\n{{ message }}\\n\\n[README.md](https://github.com/firecrawl/.github/tree/main/profile/README.md)\\n\\n#
|
||||
\U0001F525 Firecrawl\\n\\n[Permalink: \U0001F525 Firecrawl](https://github.com/firecrawl#-firecrawl)\\n\\n[](https://raw.githubusercontent.com/mendableai/firecrawl/main/img/firecrawl_logo.png)\\n\\n###
|
||||
Transform any website into LLM-ready data\\n\\n[Permalink: Transform any website
|
||||
into LLM-ready data](https://github.com/firecrawl#transform-any-website-into-llm-ready-data)\\n\\nAdvanced
|
||||
web scraping, crawling, and data extraction infrastructure for AI applications\\n\\n[](https://firecrawl.dev/)
|
||||
[](https://docs.firecrawl.dev/)
|
||||
[](https://discord.com/invite/gSmWdAkdwd)\\n\\n[](https://github.com/mendableai/firecrawl/blob/main/LICENSE)[](https://github.com/mendableai/firecrawl/stargazers)[](https://pepy.tech/project/firecrawl-py)[](https://x.com/firecrawl_dev)\\n\\n*
|
||||
* *\\n\\n## Why Firecrawl?\\n\\n[Permalink: Why Firecrawl?](https://github.com/firecrawl#why-firecrawl)\\n\\n**Building
|
||||
AI applications?** You need clean, structured data from the web. Firecrawl
|
||||
handles the complexity of modern web scraping so you can focus on building
|
||||
great products.\\n\\n## Our Core Ecosystem\\n\\n[Permalink: Our Core Ecosystem](https://github.com/firecrawl#our-core-ecosystem)\\n\\n###
|
||||
Main Repository\\n\\n[Permalink: Main Repository](https://github.com/firecrawl#main-repository)\\n\\n[](https://github.com/mendableai/firecrawl)\\n\\n**[firecrawl](https://github.com/mendableai/firecrawl)**
|
||||
\\\\- Core API & SDK\\n\\nTurn entire websites into LLM-ready markdown or
|
||||
structured data. Our flagship product with 40k+ stars.\\n\\n### Cloud API\\n\\n[Permalink:
|
||||
Cloud API](https://github.com/firecrawl#cloud-api)\\n\\n[](https://firecrawl.dev/)\\n\\n**[Firecrawl](https://firecrawl.dev/)**
|
||||
\\\\- Hosted API Service\\n\\nProduction-ready web scraping without infrastructure
|
||||
management. Get your API key and start scraping in minutes with our reliable,
|
||||
scalable cloud service.\\n\\n### MCP Integration\\n\\n[Permalink: MCP Integration](https://github.com/firecrawl#mcp-integration)\\n\\n[](https://github.com/mendableai/firecrawl-mcp-server)\\n\\n**[firecrawl-mcp-server](https://github.com/mendableai/firecrawl-mcp-server)**
|
||||
\\\\- Model Context Protocol Server\\n\\nAdd powerful web scraping capabilities
|
||||
to Claude, Cursor, and any MCP-compatible LLM client.\\n\\n## Community &
|
||||
Support\\n\\n[Permalink: Community & Support](https://github.com/firecrawl#community--support)\\n\\n[](https://discord.com/invite/gSmWdAkdwd)[](https://x.com/firecrawl_dev)[](https://www.linkedin.com/company/104100957/)[](https://github.com/mendableai/firecrawl/discussions)[](https://docs.firecrawl.dev/)\\n\\n##
|
||||
Built By Mendable\\n\\n[Permalink: Built By Mendable](https://github.com/firecrawl#built-by-mendable)\\n\\nWe're
|
||||
the team behind [Mendable.ai](https://mendable.ai/), passionate about making
|
||||
web data accessible for AI applications. Firecrawl powers thousands of AI
|
||||
products worldwide.\\n\\n* * *\\n\\n**Ready to build something amazing?**\\n\\n[Get
|
||||
your API key](https://firecrawl.dev/) and start scraping in minutes\\n\\n\\n[Star
|
||||
our main repo](https://github.com/mendableai/firecrawl) \u2022\\n[Try the
|
||||
playground](https://firecrawl.dev/playground) \u2022\\n[Read the docs](https://docs.firecrawl.dev/)\\n\\n##
|
||||
Pinned Loading\\n\\n1. [firecrawl](https://github.com/firecrawl/firecrawl)
|
||||
firecrawlPublic\\n\\n\\n\\n\\n\\n\\n\U0001F525 The Web Data API for AI - Turn
|
||||
entire websites into LLM-ready markdown or structured data\\n\\n\\n\\n\\nTypeScript[64.9k](https://github.com/firecrawl/firecrawl/stargazers)
|
||||
[5.1k](https://github.com/firecrawl/firecrawl/forks)\\n\\n2. [mendable-nextjs-chatbot](https://github.com/firecrawl/mendable-nextjs-chatbot)
|
||||
mendable-nextjs-chatbotPublic template\\n\\n\\n\\n\\n\\n\\nNext.js Starter
|
||||
Template for building chatbots with Mendable\\n\\n\\n\\n\\nTypeScript[256](https://github.com/firecrawl/mendable-nextjs-chatbot/stargazers)
|
||||
[52](https://github.com/firecrawl/mendable-nextjs-chatbot/forks)\\n\\n3. [rag-arena](https://github.com/firecrawl/rag-arena)
|
||||
rag-arenaPublic\\n\\n\\n\\n\\n\\n\\nOpen-source RAG evaluation through users'
|
||||
feedback\\n\\n\\n\\n\\nTypeScript[206](https://github.com/firecrawl/rag-arena/stargazers)
|
||||
[32](https://github.com/firecrawl/rag-arena/forks)\\n\\n4. [QA\\\\_clustering](https://github.com/firecrawl/QA_clustering)
|
||||
QA\\\\_clusteringPublic\\n\\n\\n\\n\\n\\n\\nAnalyzing chat interactions w/
|
||||
LLMs to improve \U0001F99C\U0001F517 Langchain docs\\n\\n\\n\\n\\nJupyter
|
||||
Notebook[80](https://github.com/firecrawl/QA_clustering/stargazers) [12](https://github.com/firecrawl/QA_clustering/forks)\\n\\n5.
|
||||
[data-connectors](https://github.com/firecrawl/data-connectors) data-connectorsPublic\\n\\n\\n\\n\\n\\n\\nLLM-ready
|
||||
data connectors\\n\\n\\n\\n\\nTypeScript[95](https://github.com/firecrawl/data-connectors/stargazers)
|
||||
[23](https://github.com/firecrawl/data-connectors/forks)\\n\\n6. [mendable-py](https://github.com/firecrawl/mendable-py)
|
||||
mendable-pyPublic\\n\\n\\n\\n\\n\\n\\nBuild Production Ready LLM Chat Apps
|
||||
in Minutes\\n\\n\\n\\n\\nPython[33](https://github.com/firecrawl/mendable-py/stargazers)
|
||||
[7](https://github.com/firecrawl/mendable-py/forks)\\n\\n\\n### Repositories\\n\\nLoading\\n\\nType\\n\\nAllPublicSourcesForksArchivedMirrorsTemplates\\n\\nLanguage\\n\\nAllCSSGoJavaJavaScriptJupyter
|
||||
NotebookMDXPythonRustTypeScript\\n\\nSort\\n\\nLast updatedNameStars\\n\\nShowing
|
||||
10 of 61 repositories\\n\\n- [firecrawl](https://github.com/firecrawl/firecrawl)\\nPublic\\n\\n\\n\\n\U0001F525
|
||||
The Web Data API for AI - Turn entire websites into LLM-ready markdown or
|
||||
structured data\\n\\n\\n\\n\\n\\n\\nfirecrawl/firecrawl\u2019s past year of
|
||||
commit activity\\n\\n\\n\\nTypeScript[64,949](https://github.com/firecrawl/firecrawl/stargazers)AGPL-3.0\\n[5,132](https://github.com/firecrawl/firecrawl/forks)
|
||||
[27](https://github.com/firecrawl/firecrawl/issues) [(2 issues need help)](https://github.com/firecrawl/firecrawl/issues?q=label%3A%22good+first+issue%22+is%3Aissue+is%3Aopen)
|
||||
[85](https://github.com/firecrawl/firecrawl/pulls)\\nUpdated 2 hours agoOct
|
||||
27, 2025\\n\\n- [firecrawl-docs](https://github.com/firecrawl/firecrawl-docs)\\nPublic\\n\\n\\n\\nDocumentation
|
||||
for Firecrawl.\\n\\n\\n\\n\\n\\n\\nfirecrawl/firecrawl-docs\u2019s past year
|
||||
of commit activity\\n\\n\\n\\nMDX[17](https://github.com/firecrawl/firecrawl-docs/stargazers)
|
||||
[35](https://github.com/firecrawl/firecrawl-docs/forks) [10](https://github.com/firecrawl/firecrawl-docs/issues)
|
||||
[5](https://github.com/firecrawl/firecrawl-docs/pulls)\\nUpdated 20 hours
|
||||
agoOct 26, 2025\\n\\n- [open-agent-builder](https://github.com/firecrawl/open-agent-builder)\\nPublic\\n\\n\\n\\n\U0001F525
|
||||
Visual workflow builder for AI agents powered by Firecrawl - drag-and-drop
|
||||
web scraping pipelines with real-time execution\\n\\n\\n\\n\\n\\n\\nfirecrawl/open-agent-builder\u2019s
|
||||
past year of commit activity\\n\\n\\n\\nTypeScript[1,673](https://github.com/firecrawl/open-agent-builder/stargazers)
|
||||
[274](https://github.com/firecrawl/open-agent-builder/forks) [4](https://github.com/firecrawl/open-agent-builder/issues)
|
||||
[2](https://github.com/firecrawl/open-agent-builder/pulls)\\nUpdated last
|
||||
weekOct 20, 2025\\n\\n- [firecrawl-mcp-server](https://github.com/firecrawl/firecrawl-mcp-server)\\nPublic\\n\\n\\n\\n\U0001F525
|
||||
Official Firecrawl MCP Server - Adds powerful web scraping and search to Cursor,
|
||||
Claude and any other LLM clients.\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n[**Uh
|
||||
oh!**](https://github.com/firecrawl/firecrawl-mcp-server/graphs/commit-activity)\\n\\n[There
|
||||
was an error while loading.](https://github.com/firecrawl/firecrawl-mcp-server/graphs/commit-activity)
|
||||
[Please reload this page](https://github.com/firecrawl).\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\nfirecrawl/firecrawl-mcp-server\u2019s
|
||||
past year of commit activity\\n\\n\\n\\nJavaScript[4,794](https://github.com/firecrawl/firecrawl-mcp-server/stargazers)MIT\\n[519](https://github.com/firecrawl/firecrawl-mcp-server/forks)
|
||||
[44](https://github.com/firecrawl/firecrawl-mcp-server/issues) [17](https://github.com/firecrawl/firecrawl-mcp-server/pulls)\\nUpdated
|
||||
last weekOct 19, 2025\\n\\n- [n8n-nodes-firecrawl](https://github.com/firecrawl/n8n-nodes-firecrawl)\\nPublic\\n\\n\\n\\nn8n
|
||||
node to interact with Firecrawl\\n\\n\\n\\n\\n\\n\\nfirecrawl/n8n-nodes-firecrawl\u2019s
|
||||
past year of commit activity\\n\\n\\n\\nTypeScript[21](https://github.com/firecrawl/n8n-nodes-firecrawl/stargazers)MIT\\n[13](https://github.com/firecrawl/n8n-nodes-firecrawl/forks)
|
||||
[3](https://github.com/firecrawl/n8n-nodes-firecrawl/issues) [0](https://github.com/firecrawl/n8n-nodes-firecrawl/pulls)\\nUpdated
|
||||
2 weeks agoOct 17, 2025\\n\\n- [.github](https://github.com/firecrawl/.github)\\nPublic\\n\\n\\n\\n\\nfirecrawl/.github\u2019s
|
||||
past year of commit activity\\n\\n\\n\\n0\\n[1](https://github.com/firecrawl/.github/forks)
|
||||
[0](https://github.com/firecrawl/.github/issues) [0](https://github.com/firecrawl/.github/pulls)\\nUpdated
|
||||
2 weeks agoOct 12, 2025\\n\\n- [fire-enrich](https://github.com/firecrawl/fire-enrich)\\nPublic\\n\\n\\n\\n\U0001F525
|
||||
AI-powered data enrichment tool that transforms emails into rich datasets
|
||||
with company profiles, funding data, tech stacks, and more using Firecrawl
|
||||
and multi-agent AI\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n[**Uh oh!**](https://github.com/firecrawl/fire-enrich/graphs/commit-activity)\\n\\n[There
|
||||
was an error while loading.](https://github.com/firecrawl/fire-enrich/graphs/commit-activity)
|
||||
[Please reload this page](https://github.com/firecrawl).\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\nfirecrawl/fire-enrich\u2019s
|
||||
past year of commit activity\\n\\n\\n\\nTypeScript[953](https://github.com/firecrawl/fire-enrich/stargazers)MIT\\n[239](https://github.com/firecrawl/fire-enrich/forks)
|
||||
[12](https://github.com/firecrawl/fire-enrich/issues) [3](https://github.com/firecrawl/fire-enrich/pulls)\\nUpdated
|
||||
3 weeks agoOct 8, 2025\\n\\n- [firecrawl-java-sdk](https://github.com/firecrawl/firecrawl-java-sdk)\\nPublic\\n\\n\\n\\n\\nfirecrawl/firecrawl-java-sdk\u2019s
|
||||
past year of commit activity\\n\\n\\n\\nJava[11](https://github.com/firecrawl/firecrawl-java-sdk/stargazers)MIT\\n[4](https://github.com/firecrawl/firecrawl-java-sdk/forks)
|
||||
[0](https://github.com/firecrawl/firecrawl-java-sdk/issues) [0](https://github.com/firecrawl/firecrawl-java-sdk/pulls)\\nUpdated
|
||||
last monthSep 28, 2025\\n\\n- [open-lovable](https://github.com/firecrawl/open-lovable)\\nPublic\\n\\n\\n\\n\U0001F525
|
||||
Clone and recreate any website as a modern React app in seconds\\n\\n\\n\\n\\n\\n\\nfirecrawl/open-lovable\u2019s
|
||||
past year of commit activity\\n\\n\\n\\nTypeScript[21,320](https://github.com/firecrawl/open-lovable/stargazers)MIT\\n[3,986](https://github.com/firecrawl/open-lovable/forks)
|
||||
[70](https://github.com/firecrawl/open-lovable/issues) [33](https://github.com/firecrawl/open-lovable/pulls)\\nUpdated
|
||||
last monthSep 27, 2025\\n\\n- [mineru-api](https://github.com/firecrawl/mineru-api)\\nPublic\\n\\n\\n\\n\\nfirecrawl/mineru-api\u2019s
|
||||
past year of commit activity\\n\\n\\n\\nPython[12](https://github.com/firecrawl/mineru-api/stargazers)AGPL-3.0\\n[2](https://github.com/firecrawl/mineru-api/forks)
|
||||
[1](https://github.com/firecrawl/mineru-api/issues) [1](https://github.com/firecrawl/mineru-api/pulls)\\nUpdated
|
||||
on Sep 26Sep 26, 2025\\n\\n\\n[View all repositories](https://github.com/orgs/firecrawl/repositories?type=all)\\n\\n[**People**](https://github.com/orgs/firecrawl/people)\\n\\n[](https://github.com/alexnucci)[](https://github.com/micahstairs)[](https://github.com/nickscamara)[](https://github.com/mogery)[](https://github.com/developersdigest)\\n\\n####
|
||||
Top languages\\n\\n[TypeScript](https://github.com/orgs/firecrawl/repositories?language=typescript&type=all)
|
||||
[Python](https://github.com/orgs/firecrawl/repositories?language=python&type=all)
|
||||
[JavaScript](https://github.com/orgs/firecrawl/repositories?language=javascript&type=all)
|
||||
[Go](https://github.com/orgs/firecrawl/repositories?language=go&type=all)
|
||||
[MDX](https://github.com/orgs/firecrawl/repositories?language=mdx&type=all)\\n\\n####
|
||||
Most used topics\\n\\n[ai](https://github.com/search?q=topic%3Aai+org%3Afirecrawl+fork%3Atrue&type=repositories
|
||||
\\\"Topic: ai\\\") [firecrawl](https://github.com/search?q=topic%3Afirecrawl+org%3Afirecrawl+fork%3Atrue&type=repositories
|
||||
\\\"Topic: firecrawl\\\") [llm](https://github.com/search?q=topic%3Allm+org%3Afirecrawl+fork%3Atrue&type=repositories
|
||||
\\\"Topic: llm\\\") [web-crawler](https://github.com/search?q=topic%3Aweb-crawler+org%3Afirecrawl+fork%3Atrue&type=repositories
|
||||
\\\"Topic: web-crawler\\\") [web-scraping](https://github.com/search?q=topic%3Aweb-scraping+org%3Afirecrawl+fork%3Atrue&type=repositories
|
||||
\\\"Topic: web-scraping\\\")\\n\\nYou can\u2019t perform that action at this
|
||||
time.\",\"metadata\":{\"analytics-location\":\"/<org-login>\",\"apple-itunes-app\":\"app-id=1477376905,
|
||||
app-argument=https://github.com/firecrawl\",\"twitter:card\":\"summary_large_image\",\"google-site-verification\":\"Apib7-x98H0j5cPqHWwSMm6dNU4GmODRoqxLiDzdx9I\",\"description\":\"Web
|
||||
data API for AI. Firecrawl has 61 repositories available. Follow their code
|
||||
on GitHub.\",\"og:image\":\"https://avatars.githubusercontent.com/u/135057108?s=280&v=4\",\"og:type\":\"profile\",\"visitor-payload\":\"eyJyZWZlcnJlciI6IiIsInJlcXVlc3RfaWQiOiI5REFEOjIzM0ExMzo4RDgzNEI6QzQ5OUNCOjY4RkYzODlGIiwidmlzaXRvcl9pZCI6IjQwMDQ0MTI5MTkxMDA5NDY1OTEiLCJyZWdpb25fZWRnZSI6ImlhZCIsInJlZ2lvbl9yZW5kZXIiOiJpYWQifQ==\",\"github-keyboard-shortcuts\":\"copilot\",\"user-login\":\"\",\"viewport\":\"width=device-width\",\"og:description\":\"Web
|
||||
data API for AI. Firecrawl has 61 repositories available. Follow their code
|
||||
on GitHub.\",\"turbo-cache-control\":\"no-preview\",\"fetch-nonce\":\"v2:35a2e032-0081-3f6b-595e-967e32025c6f\",\"og:url\":\"https://github.com/firecrawl\",\"title\":\"Firecrawl
|
||||
\xB7 GitHub\",\"route-pattern\":\"/:user_id(.:format)\",\"route-action\":\"show\",\"octolytics-url\":\"https://collector.github.com/github/collect\",\"og:site_name\":\"GitHub\",\"twitter:title\":\"Firecrawl\",\"request-id\":\"9DAD:233A13:8D834B:C499CB:68FF389F\",\"ogSiteName\":\"GitHub\",\"fb:app_id\":\"1401488693436528\",\"language\":\"en\",\"twitter:image\":\"https://avatars.githubusercontent.com/u/135057108?s=280&v=4\",\"ogImage\":\"https://avatars.githubusercontent.com/u/135057108?s=280&v=4\",\"release\":\"c44b7f7aa5c70f3296484971978c9f4b1b473352\",\"theme-color\":\"#1e2327\",\"color-scheme\":\"light
|
||||
dark\",\"html-safe-nonce\":\"2d932295da6aa360d861f16279839ab109dc4e977a51bc99204477969d7d12c6\",\"ogTitle\":\"Firecrawl\",\"hovercard-subject-tag\":\"organization:135057108\",\"twitter:description\":\"Web
|
||||
data API for AI. Firecrawl has 61 repositories available. Follow their code
|
||||
on GitHub.\",\"hostname\":\"github.com\",\"ogUrl\":\"https://github.com/firecrawl\",\"ogDescription\":\"Web
|
||||
data API for AI. Firecrawl has 61 repositories available. Follow their code
|
||||
on GitHub.\",\"route-controller\":\"profiles\",\"favicon\":\"https://github.githubassets.com/favicons/favicon.svg\",\"visitor-hmac\":\"43cf3bbb9c57a3bcf0b1857fbcabcc78c274e7082e0d28c76cd6d4651bc2a920\",\"twitter:site\":\"@github\",\"ui-target\":\"full\",\"og:title\":\"Firecrawl\",\"expected-hostname\":\"github.com\",\"og:image:alt\":\"Web
|
||||
data API for AI. Firecrawl has 61 repositories available. Follow their code
|
||||
on GitHub.\",\"profile:username\":\"firecrawl\",\"current-catalog-service-hash\":\"4a1c50a83cf6cc4b55b6b9c53e553e3f847c876b87fb333f71f5d05db8f1a7db\",\"turbo-body-classes\":\"logged-out
|
||||
env-production page-responsive\",\"browser-stats-url\":\"https://api.github.com/_private/browser/stats\",\"browser-errors-url\":\"https://api.github.com/_private/browser/errors\",\"scrapeId\":\"65cbc300-be11-4a1a-9d20-c114fb8473a7\",\"sourceURL\":\"https://github.com/firecrawl\",\"url\":\"https://github.com/firecrawl\",\"statusCode\":200,\"contentType\":\"text/html;
|
||||
charset=utf-8\",\"proxyUsed\":\"basic\",\"cacheState\":\"hit\",\"cachedAt\":\"2025-10-27T09:17:20.756Z\"}},{\"url\":\"https://www.linkedin.com/company/firecrawl\",\"title\":\"Firecrawl
|
||||
| LinkedIn\",\"description\":\"Our Dify integration now uses Firecrawl /v2
|
||||
endpoints Scraping is 10x faster thanks to intelligent caching, plus we've
|
||||
added semantic ...\",\"position\":5}]},\"creditsUsed\":3}"
|
||||
headers:
|
||||
Access-Control-Allow-Origin:
|
||||
- '*'
|
||||
Alt-Svc:
|
||||
- h3=":443"; ma=2592000,h3-29=":443"; ma=2592000
|
||||
Content-Length:
|
||||
- '93428'
|
||||
Content-Type:
|
||||
- application/json; charset=utf-8
|
||||
Date:
|
||||
- Wed, 29 Oct 2025 14:37:39 GMT
|
||||
ETag:
|
||||
- W/"16cf4-kHwVbMu4CCVG2UIt6p1g/gz5M4M"
|
||||
Via:
|
||||
- 1.1 google
|
||||
X-Powered-By:
|
||||
- Express
|
||||
X-Response-Time:
|
||||
- 13172.495ms
|
||||
status:
|
||||
code: 200
|
||||
message: OK
|
||||
version: 1
|
||||
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
@@ -4,7 +4,7 @@ from crewai_tools.tools.firecrawl_crawl_website_tool.firecrawl_crawl_website_too
|
||||
FirecrawlCrawlWebsiteTool,
|
||||
)
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_firecrawl_crawl_tool_integration():
|
||||
tool = FirecrawlCrawlWebsiteTool(config={
|
||||
"limit": 2,
|
||||
|
||||
@@ -4,7 +4,7 @@ from crewai_tools.tools.firecrawl_scrape_website_tool.firecrawl_scrape_website_t
|
||||
FirecrawlScrapeWebsiteTool,
|
||||
)
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_firecrawl_scrape_tool_integration():
|
||||
tool = FirecrawlScrapeWebsiteTool()
|
||||
result = tool.run(url="https://firecrawl.dev")
|
||||
|
||||
@@ -3,7 +3,7 @@ import pytest
|
||||
from crewai_tools.tools.firecrawl_search_tool.firecrawl_search_tool import FirecrawlSearchTool
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_firecrawl_search_tool_integration():
|
||||
tool = FirecrawlSearchTool()
|
||||
result = tool.run(query="firecrawl")
|
||||
|
||||
@@ -48,7 +48,7 @@ Repository = "https://github.com/crewAIInc/crewAI"
|
||||
|
||||
[project.optional-dependencies]
|
||||
tools = [
|
||||
"crewai-tools==1.4.1",
|
||||
"crewai-tools==1.3.0",
|
||||
]
|
||||
embeddings = [
|
||||
"tiktoken~=0.8.0"
|
||||
|
||||
@@ -40,7 +40,7 @@ def _suppress_pydantic_deprecation_warnings() -> None:
|
||||
|
||||
_suppress_pydantic_deprecation_warnings()
|
||||
|
||||
__version__ = "1.4.1"
|
||||
__version__ = "1.3.0"
|
||||
_telemetry_submitted = False
|
||||
|
||||
|
||||
|
||||
@@ -40,16 +40,6 @@ from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
|
||||
from crewai.knowledge.utils.knowledge_utils import extract_knowledge_context
|
||||
from crewai.lite_agent import LiteAgent
|
||||
from crewai.llms.base_llm import BaseLLM
|
||||
from crewai.mcp import (
|
||||
MCPClient,
|
||||
MCPServerConfig,
|
||||
MCPServerHTTP,
|
||||
MCPServerSSE,
|
||||
MCPServerStdio,
|
||||
)
|
||||
from crewai.mcp.transports.http import HTTPTransport
|
||||
from crewai.mcp.transports.sse import SSETransport
|
||||
from crewai.mcp.transports.stdio import StdioTransport
|
||||
from crewai.memory.contextual.contextual_memory import ContextualMemory
|
||||
from crewai.rag.embeddings.types import EmbedderConfig
|
||||
from crewai.security.fingerprint import Fingerprint
|
||||
@@ -118,7 +108,6 @@ class Agent(BaseAgent):
|
||||
"""
|
||||
|
||||
_times_executed: int = PrivateAttr(default=0)
|
||||
_mcp_clients: list[Any] = PrivateAttr(default_factory=list)
|
||||
max_execution_time: int | None = Field(
|
||||
default=None,
|
||||
description="Maximum execution time for an agent to execute a task",
|
||||
@@ -537,9 +526,6 @@ class Agent(BaseAgent):
|
||||
self,
|
||||
event=AgentExecutionCompletedEvent(agent=self, task=task, output=result),
|
||||
)
|
||||
|
||||
self._cleanup_mcp_clients()
|
||||
|
||||
return result
|
||||
|
||||
def _execute_with_timeout(self, task_prompt: str, task: Task, timeout: int) -> Any:
|
||||
@@ -663,70 +649,30 @@ class Agent(BaseAgent):
|
||||
self._logger.log("error", f"Error getting platform tools: {e!s}")
|
||||
return []
|
||||
|
||||
def get_mcp_tools(self, mcps: list[str | MCPServerConfig]) -> list[BaseTool]:
|
||||
"""Convert MCP server references/configs to CrewAI tools.
|
||||
|
||||
Supports both string references (backwards compatible) and structured
|
||||
configuration objects (MCPServerStdio, MCPServerHTTP, MCPServerSSE).
|
||||
|
||||
Args:
|
||||
mcps: List of MCP server references (strings) or configurations.
|
||||
|
||||
Returns:
|
||||
List of BaseTool instances from MCP servers.
|
||||
"""
|
||||
def get_mcp_tools(self, mcps: list[str]) -> list[BaseTool]:
|
||||
"""Convert MCP server references to CrewAI tools."""
|
||||
all_tools = []
|
||||
clients = []
|
||||
|
||||
for mcp_config in mcps:
|
||||
if isinstance(mcp_config, str):
|
||||
tools = self._get_mcp_tools_from_string(mcp_config)
|
||||
else:
|
||||
tools, client = self._get_native_mcp_tools(mcp_config)
|
||||
if client:
|
||||
clients.append(client)
|
||||
for mcp_ref in mcps:
|
||||
try:
|
||||
if mcp_ref.startswith("crewai-amp:"):
|
||||
tools = self._get_amp_mcp_tools(mcp_ref)
|
||||
elif mcp_ref.startswith("https://"):
|
||||
tools = self._get_external_mcp_tools(mcp_ref)
|
||||
else:
|
||||
continue
|
||||
|
||||
all_tools.extend(tools)
|
||||
all_tools.extend(tools)
|
||||
self._logger.log(
|
||||
"info", f"Successfully loaded {len(tools)} tools from {mcp_ref}"
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
self._logger.log("warning", f"Skipping MCP {mcp_ref} due to error: {e}")
|
||||
continue
|
||||
|
||||
# Store clients for cleanup
|
||||
self._mcp_clients.extend(clients)
|
||||
return all_tools
|
||||
|
||||
def _cleanup_mcp_clients(self) -> None:
|
||||
"""Cleanup MCP client connections after task execution."""
|
||||
if not self._mcp_clients:
|
||||
return
|
||||
|
||||
async def _disconnect_all() -> None:
|
||||
for client in self._mcp_clients:
|
||||
if client and hasattr(client, "connected") and client.connected:
|
||||
await client.disconnect()
|
||||
|
||||
try:
|
||||
asyncio.run(_disconnect_all())
|
||||
except Exception as e:
|
||||
self._logger.log("error", f"Error during MCP client cleanup: {e}")
|
||||
finally:
|
||||
self._mcp_clients.clear()
|
||||
|
||||
def _get_mcp_tools_from_string(self, mcp_ref: str) -> list[BaseTool]:
|
||||
"""Get tools from legacy string-based MCP references.
|
||||
|
||||
This method maintains backwards compatibility with string-based
|
||||
MCP references (https://... and crewai-amp:...).
|
||||
|
||||
Args:
|
||||
mcp_ref: String reference to MCP server.
|
||||
|
||||
Returns:
|
||||
List of BaseTool instances.
|
||||
"""
|
||||
if mcp_ref.startswith("crewai-amp:"):
|
||||
return self._get_amp_mcp_tools(mcp_ref)
|
||||
if mcp_ref.startswith("https://"):
|
||||
return self._get_external_mcp_tools(mcp_ref)
|
||||
return []
|
||||
|
||||
def _get_external_mcp_tools(self, mcp_ref: str) -> list[BaseTool]:
|
||||
"""Get tools from external HTTPS MCP server with graceful error handling."""
|
||||
from crewai.tools.mcp_tool_wrapper import MCPToolWrapper
|
||||
@@ -785,164 +731,6 @@ class Agent(BaseAgent):
|
||||
)
|
||||
return []
|
||||
|
||||
def _get_native_mcp_tools(
|
||||
self, mcp_config: MCPServerConfig
|
||||
) -> tuple[list[BaseTool], Any | None]:
|
||||
"""Get tools from MCP server using structured configuration.
|
||||
|
||||
This method creates an MCP client based on the configuration type,
|
||||
connects to the server, discovers tools, applies filtering, and
|
||||
returns wrapped tools along with the client instance for cleanup.
|
||||
|
||||
Args:
|
||||
mcp_config: MCP server configuration (MCPServerStdio, MCPServerHTTP, or MCPServerSSE).
|
||||
|
||||
Returns:
|
||||
Tuple of (list of BaseTool instances, MCPClient instance for cleanup).
|
||||
"""
|
||||
from crewai.tools.base_tool import BaseTool
|
||||
from crewai.tools.mcp_native_tool import MCPNativeTool
|
||||
|
||||
if isinstance(mcp_config, MCPServerStdio):
|
||||
transport = StdioTransport(
|
||||
command=mcp_config.command,
|
||||
args=mcp_config.args,
|
||||
env=mcp_config.env,
|
||||
)
|
||||
server_name = f"{mcp_config.command}_{'_'.join(mcp_config.args)}"
|
||||
elif isinstance(mcp_config, MCPServerHTTP):
|
||||
transport = HTTPTransport(
|
||||
url=mcp_config.url,
|
||||
headers=mcp_config.headers,
|
||||
streamable=mcp_config.streamable,
|
||||
)
|
||||
server_name = self._extract_server_name(mcp_config.url)
|
||||
elif isinstance(mcp_config, MCPServerSSE):
|
||||
transport = SSETransport(
|
||||
url=mcp_config.url,
|
||||
headers=mcp_config.headers,
|
||||
)
|
||||
server_name = self._extract_server_name(mcp_config.url)
|
||||
else:
|
||||
raise ValueError(f"Unsupported MCP server config type: {type(mcp_config)}")
|
||||
|
||||
client = MCPClient(
|
||||
transport=transport,
|
||||
cache_tools_list=mcp_config.cache_tools_list,
|
||||
)
|
||||
|
||||
async def _setup_client_and_list_tools() -> list[dict[str, Any]]:
|
||||
"""Async helper to connect and list tools in same event loop."""
|
||||
|
||||
try:
|
||||
if not client.connected:
|
||||
await client.connect()
|
||||
|
||||
tools_list = await client.list_tools()
|
||||
|
||||
try:
|
||||
await client.disconnect()
|
||||
# Small delay to allow background tasks to finish cleanup
|
||||
# This helps prevent "cancel scope in different task" errors
|
||||
# when asyncio.run() closes the event loop
|
||||
await asyncio.sleep(0.1)
|
||||
except Exception as e:
|
||||
self._logger.log("error", f"Error during disconnect: {e}")
|
||||
|
||||
return tools_list
|
||||
except Exception as e:
|
||||
if client.connected:
|
||||
await client.disconnect()
|
||||
await asyncio.sleep(0.1)
|
||||
raise RuntimeError(
|
||||
f"Error during setup client and list tools: {e}"
|
||||
) from e
|
||||
|
||||
try:
|
||||
try:
|
||||
asyncio.get_running_loop()
|
||||
import concurrent.futures
|
||||
|
||||
with concurrent.futures.ThreadPoolExecutor() as executor:
|
||||
future = executor.submit(
|
||||
asyncio.run, _setup_client_and_list_tools()
|
||||
)
|
||||
tools_list = future.result()
|
||||
except RuntimeError:
|
||||
try:
|
||||
tools_list = asyncio.run(_setup_client_and_list_tools())
|
||||
except RuntimeError as e:
|
||||
error_msg = str(e).lower()
|
||||
if "cancel scope" in error_msg or "task" in error_msg:
|
||||
raise ConnectionError(
|
||||
"MCP connection failed due to event loop cleanup issues. "
|
||||
"This may be due to authentication errors or server unavailability."
|
||||
) from e
|
||||
except asyncio.CancelledError as e:
|
||||
raise ConnectionError(
|
||||
"MCP connection was cancelled. This may indicate an authentication "
|
||||
"error or server unavailability."
|
||||
) from e
|
||||
|
||||
if mcp_config.tool_filter:
|
||||
filtered_tools = []
|
||||
for tool in tools_list:
|
||||
if callable(mcp_config.tool_filter):
|
||||
try:
|
||||
from crewai.mcp.filters import ToolFilterContext
|
||||
|
||||
context = ToolFilterContext(
|
||||
agent=self,
|
||||
server_name=server_name,
|
||||
run_context=None,
|
||||
)
|
||||
if mcp_config.tool_filter(context, tool):
|
||||
filtered_tools.append(tool)
|
||||
except (TypeError, AttributeError):
|
||||
if mcp_config.tool_filter(tool):
|
||||
filtered_tools.append(tool)
|
||||
else:
|
||||
# Not callable - include tool
|
||||
filtered_tools.append(tool)
|
||||
tools_list = filtered_tools
|
||||
|
||||
tools = []
|
||||
for tool_def in tools_list:
|
||||
tool_name = tool_def.get("name", "")
|
||||
if not tool_name:
|
||||
continue
|
||||
|
||||
# Convert inputSchema to Pydantic model if present
|
||||
args_schema = None
|
||||
if tool_def.get("inputSchema"):
|
||||
args_schema = self._json_schema_to_pydantic(
|
||||
tool_name, tool_def["inputSchema"]
|
||||
)
|
||||
|
||||
tool_schema = {
|
||||
"description": tool_def.get("description", ""),
|
||||
"args_schema": args_schema,
|
||||
}
|
||||
|
||||
try:
|
||||
native_tool = MCPNativeTool(
|
||||
mcp_client=client,
|
||||
tool_name=tool_name,
|
||||
tool_schema=tool_schema,
|
||||
server_name=server_name,
|
||||
)
|
||||
tools.append(native_tool)
|
||||
except Exception as e:
|
||||
self._logger.log("error", f"Failed to create native MCP tool: {e}")
|
||||
continue
|
||||
|
||||
return cast(list[BaseTool], tools), client
|
||||
except Exception as e:
|
||||
if client.connected:
|
||||
asyncio.run(client.disconnect())
|
||||
|
||||
raise RuntimeError(f"Failed to get native MCP tools: {e}") from e
|
||||
|
||||
def _get_amp_mcp_tools(self, amp_ref: str) -> list[BaseTool]:
|
||||
"""Get tools from CrewAI AMP MCP marketplace."""
|
||||
# Parse: "crewai-amp:mcp-name" or "crewai-amp:mcp-name#tool_name"
|
||||
|
||||
@@ -25,7 +25,6 @@ from crewai.agents.tools_handler import ToolsHandler
|
||||
from crewai.knowledge.knowledge import Knowledge
|
||||
from crewai.knowledge.knowledge_config import KnowledgeConfig
|
||||
from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
|
||||
from crewai.mcp.config import MCPServerConfig
|
||||
from crewai.rag.embeddings.types import EmbedderConfig
|
||||
from crewai.security.security_config import SecurityConfig
|
||||
from crewai.tools.base_tool import BaseTool, Tool
|
||||
@@ -195,7 +194,7 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
|
||||
default=None,
|
||||
description="List of applications or application/action combinations that the agent can access through CrewAI Platform. Can contain app names (e.g., 'gmail') or specific actions (e.g., 'gmail/send_email')",
|
||||
)
|
||||
mcps: list[str | MCPServerConfig] | None = Field(
|
||||
mcps: list[str] | None = Field(
|
||||
default=None,
|
||||
description="List of MCP server references. Supports 'https://server.com/path' for external servers and 'crewai-amp:mcp-name' for AMP marketplace. Use '#tool_name' suffix for specific tools.",
|
||||
)
|
||||
@@ -254,36 +253,20 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
|
||||
|
||||
@field_validator("mcps")
|
||||
@classmethod
|
||||
def validate_mcps(
|
||||
cls, mcps: list[str | MCPServerConfig] | None
|
||||
) -> list[str | MCPServerConfig] | None:
|
||||
"""Validate MCP server references and configurations.
|
||||
|
||||
Supports both string references (for backwards compatibility) and
|
||||
structured configuration objects (MCPServerStdio, MCPServerHTTP, MCPServerSSE).
|
||||
"""
|
||||
def validate_mcps(cls, mcps: list[str] | None) -> list[str] | None:
|
||||
if not mcps:
|
||||
return mcps
|
||||
|
||||
validated_mcps = []
|
||||
for mcp in mcps:
|
||||
if isinstance(mcp, str):
|
||||
if mcp.startswith(("https://", "crewai-amp:")):
|
||||
validated_mcps.append(mcp)
|
||||
else:
|
||||
raise ValueError(
|
||||
f"Invalid MCP reference: {mcp}. "
|
||||
"String references must start with 'https://' or 'crewai-amp:'"
|
||||
)
|
||||
|
||||
elif isinstance(mcp, (MCPServerConfig)):
|
||||
if mcp.startswith(("https://", "crewai-amp:")):
|
||||
validated_mcps.append(mcp)
|
||||
else:
|
||||
raise ValueError(
|
||||
f"Invalid MCP configuration: {type(mcp)}. "
|
||||
"Must be a string reference or MCPServerConfig instance."
|
||||
f"Invalid MCP reference: {mcp}. Must start with 'https://' or 'crewai-amp:'"
|
||||
)
|
||||
return validated_mcps
|
||||
|
||||
return list(set(validated_mcps))
|
||||
|
||||
@model_validator(mode="after")
|
||||
def validate_and_set_attributes(self) -> Self:
|
||||
@@ -360,7 +343,7 @@ class BaseAgent(BaseModel, ABC, metaclass=AgentMeta):
|
||||
"""Get platform tools for the specified list of applications and/or application/action combinations."""
|
||||
|
||||
@abstractmethod
|
||||
def get_mcp_tools(self, mcps: list[str | MCPServerConfig]) -> list[BaseTool]:
|
||||
def get_mcp_tools(self, mcps: list[str]) -> list[BaseTool]:
|
||||
"""Get MCP tools for the specified list of MCP server references."""
|
||||
|
||||
def copy(self) -> Self: # type: ignore # Signature of "copy" incompatible with supertype "BaseModel"
|
||||
|
||||
@@ -214,7 +214,6 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
|
||||
llm=self.llm,
|
||||
callbacks=self.callbacks,
|
||||
)
|
||||
break
|
||||
|
||||
enforce_rpm_limit(self.request_within_rpm_limit)
|
||||
|
||||
@@ -227,7 +226,7 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
|
||||
from_agent=self.agent,
|
||||
response_model=self.response_model,
|
||||
)
|
||||
formatted_answer = process_llm_response(answer, self.use_stop_words) # type: ignore[assignment]
|
||||
formatted_answer = process_llm_response(answer, self.use_stop_words)
|
||||
|
||||
if isinstance(formatted_answer, AgentAction):
|
||||
# Extract agent fingerprint if available
|
||||
@@ -259,11 +258,11 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
|
||||
formatted_answer, tool_result
|
||||
)
|
||||
|
||||
self._invoke_step_callback(formatted_answer) # type: ignore[arg-type]
|
||||
self._append_message(formatted_answer.text) # type: ignore[union-attr,attr-defined]
|
||||
self._invoke_step_callback(formatted_answer)
|
||||
self._append_message(formatted_answer.text)
|
||||
|
||||
except OutputParserError as e:
|
||||
formatted_answer = handle_output_parser_exception( # type: ignore[assignment]
|
||||
except OutputParserError as e: # noqa: PERF203
|
||||
formatted_answer = handle_output_parser_exception(
|
||||
e=e,
|
||||
messages=self.messages,
|
||||
iterations=self.iterations,
|
||||
|
||||
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
|
||||
authors = [{ name = "Your Name", email = "you@example.com" }]
|
||||
requires-python = ">=3.10,<3.14"
|
||||
dependencies = [
|
||||
"crewai[tools]==1.4.1"
|
||||
"crewai[tools]==1.3.0"
|
||||
]
|
||||
|
||||
[project.scripts]
|
||||
|
||||
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
|
||||
authors = [{ name = "Your Name", email = "you@example.com" }]
|
||||
requires-python = ">=3.10,<3.14"
|
||||
dependencies = [
|
||||
"crewai[tools]==1.4.1"
|
||||
"crewai[tools]==1.3.0"
|
||||
]
|
||||
|
||||
[project.scripts]
|
||||
|
||||
@@ -16,6 +16,7 @@ from crewai.events.base_event_listener import BaseEventListener
|
||||
from crewai.events.depends import Depends
|
||||
from crewai.events.event_bus import crewai_event_bus
|
||||
from crewai.events.handler_graph import CircularDependencyError
|
||||
|
||||
from crewai.events.types.crew_events import (
|
||||
CrewKickoffCompletedEvent,
|
||||
CrewKickoffFailedEvent,
|
||||
@@ -60,14 +61,6 @@ from crewai.events.types.logging_events import (
|
||||
AgentLogsExecutionEvent,
|
||||
AgentLogsStartedEvent,
|
||||
)
|
||||
from crewai.events.types.mcp_events import (
|
||||
MCPConnectionCompletedEvent,
|
||||
MCPConnectionFailedEvent,
|
||||
MCPConnectionStartedEvent,
|
||||
MCPToolExecutionCompletedEvent,
|
||||
MCPToolExecutionFailedEvent,
|
||||
MCPToolExecutionStartedEvent,
|
||||
)
|
||||
from crewai.events.types.memory_events import (
|
||||
MemoryQueryCompletedEvent,
|
||||
MemoryQueryFailedEvent,
|
||||
@@ -160,12 +153,6 @@ __all__ = [
|
||||
"LiteAgentExecutionCompletedEvent",
|
||||
"LiteAgentExecutionErrorEvent",
|
||||
"LiteAgentExecutionStartedEvent",
|
||||
"MCPConnectionCompletedEvent",
|
||||
"MCPConnectionFailedEvent",
|
||||
"MCPConnectionStartedEvent",
|
||||
"MCPToolExecutionCompletedEvent",
|
||||
"MCPToolExecutionFailedEvent",
|
||||
"MCPToolExecutionStartedEvent",
|
||||
"MemoryQueryCompletedEvent",
|
||||
"MemoryQueryFailedEvent",
|
||||
"MemoryQueryStartedEvent",
|
||||
|
||||
@@ -65,14 +65,6 @@ from crewai.events.types.logging_events import (
|
||||
AgentLogsExecutionEvent,
|
||||
AgentLogsStartedEvent,
|
||||
)
|
||||
from crewai.events.types.mcp_events import (
|
||||
MCPConnectionCompletedEvent,
|
||||
MCPConnectionFailedEvent,
|
||||
MCPConnectionStartedEvent,
|
||||
MCPToolExecutionCompletedEvent,
|
||||
MCPToolExecutionFailedEvent,
|
||||
MCPToolExecutionStartedEvent,
|
||||
)
|
||||
from crewai.events.types.reasoning_events import (
|
||||
AgentReasoningCompletedEvent,
|
||||
AgentReasoningFailedEvent,
|
||||
@@ -623,67 +615,5 @@ class EventListener(BaseEventListener):
|
||||
event.total_turns,
|
||||
)
|
||||
|
||||
# ----------- MCP EVENTS -----------
|
||||
|
||||
@crewai_event_bus.on(MCPConnectionStartedEvent)
|
||||
def on_mcp_connection_started(source, event: MCPConnectionStartedEvent):
|
||||
self.formatter.handle_mcp_connection_started(
|
||||
event.server_name,
|
||||
event.server_url,
|
||||
event.transport_type,
|
||||
event.is_reconnect,
|
||||
event.connect_timeout,
|
||||
)
|
||||
|
||||
@crewai_event_bus.on(MCPConnectionCompletedEvent)
|
||||
def on_mcp_connection_completed(source, event: MCPConnectionCompletedEvent):
|
||||
self.formatter.handle_mcp_connection_completed(
|
||||
event.server_name,
|
||||
event.server_url,
|
||||
event.transport_type,
|
||||
event.connection_duration_ms,
|
||||
event.is_reconnect,
|
||||
)
|
||||
|
||||
@crewai_event_bus.on(MCPConnectionFailedEvent)
|
||||
def on_mcp_connection_failed(source, event: MCPConnectionFailedEvent):
|
||||
self.formatter.handle_mcp_connection_failed(
|
||||
event.server_name,
|
||||
event.server_url,
|
||||
event.transport_type,
|
||||
event.error,
|
||||
event.error_type,
|
||||
)
|
||||
|
||||
@crewai_event_bus.on(MCPToolExecutionStartedEvent)
|
||||
def on_mcp_tool_execution_started(source, event: MCPToolExecutionStartedEvent):
|
||||
self.formatter.handle_mcp_tool_execution_started(
|
||||
event.server_name,
|
||||
event.tool_name,
|
||||
event.tool_args,
|
||||
)
|
||||
|
||||
@crewai_event_bus.on(MCPToolExecutionCompletedEvent)
|
||||
def on_mcp_tool_execution_completed(
|
||||
source, event: MCPToolExecutionCompletedEvent
|
||||
):
|
||||
self.formatter.handle_mcp_tool_execution_completed(
|
||||
event.server_name,
|
||||
event.tool_name,
|
||||
event.tool_args,
|
||||
event.result,
|
||||
event.execution_duration_ms,
|
||||
)
|
||||
|
||||
@crewai_event_bus.on(MCPToolExecutionFailedEvent)
|
||||
def on_mcp_tool_execution_failed(source, event: MCPToolExecutionFailedEvent):
|
||||
self.formatter.handle_mcp_tool_execution_failed(
|
||||
event.server_name,
|
||||
event.tool_name,
|
||||
event.tool_args,
|
||||
event.error,
|
||||
event.error_type,
|
||||
)
|
||||
|
||||
|
||||
event_listener = EventListener()
|
||||
|
||||
@@ -40,14 +40,6 @@ from crewai.events.types.llm_guardrail_events import (
|
||||
LLMGuardrailCompletedEvent,
|
||||
LLMGuardrailStartedEvent,
|
||||
)
|
||||
from crewai.events.types.mcp_events import (
|
||||
MCPConnectionCompletedEvent,
|
||||
MCPConnectionFailedEvent,
|
||||
MCPConnectionStartedEvent,
|
||||
MCPToolExecutionCompletedEvent,
|
||||
MCPToolExecutionFailedEvent,
|
||||
MCPToolExecutionStartedEvent,
|
||||
)
|
||||
from crewai.events.types.memory_events import (
|
||||
MemoryQueryCompletedEvent,
|
||||
MemoryQueryFailedEvent,
|
||||
@@ -123,10 +115,4 @@ EventTypes = (
|
||||
| MemoryQueryFailedEvent
|
||||
| MemoryRetrievalStartedEvent
|
||||
| MemoryRetrievalCompletedEvent
|
||||
| MCPConnectionStartedEvent
|
||||
| MCPConnectionCompletedEvent
|
||||
| MCPConnectionFailedEvent
|
||||
| MCPToolExecutionStartedEvent
|
||||
| MCPToolExecutionCompletedEvent
|
||||
| MCPToolExecutionFailedEvent
|
||||
)
|
||||
|
||||
@@ -1,85 +0,0 @@
|
||||
from datetime import datetime
|
||||
from typing import Any
|
||||
|
||||
from crewai.events.base_events import BaseEvent
|
||||
|
||||
|
||||
class MCPEvent(BaseEvent):
|
||||
"""Base event for MCP operations."""
|
||||
|
||||
server_name: str
|
||||
server_url: str | None = None
|
||||
transport_type: str | None = None # "stdio", "http", "sse"
|
||||
agent_id: str | None = None
|
||||
agent_role: str | None = None
|
||||
from_agent: Any | None = None
|
||||
from_task: Any | None = None
|
||||
|
||||
def __init__(self, **data):
|
||||
super().__init__(**data)
|
||||
self._set_agent_params(data)
|
||||
self._set_task_params(data)
|
||||
|
||||
|
||||
class MCPConnectionStartedEvent(MCPEvent):
|
||||
"""Event emitted when starting to connect to an MCP server."""
|
||||
|
||||
type: str = "mcp_connection_started"
|
||||
connect_timeout: int | None = None
|
||||
is_reconnect: bool = (
|
||||
False # True if this is a reconnection, False for first connection
|
||||
)
|
||||
|
||||
|
||||
class MCPConnectionCompletedEvent(MCPEvent):
|
||||
"""Event emitted when successfully connected to an MCP server."""
|
||||
|
||||
type: str = "mcp_connection_completed"
|
||||
started_at: datetime | None = None
|
||||
completed_at: datetime | None = None
|
||||
connection_duration_ms: float | None = None
|
||||
is_reconnect: bool = (
|
||||
False # True if this was a reconnection, False for first connection
|
||||
)
|
||||
|
||||
|
||||
class MCPConnectionFailedEvent(MCPEvent):
|
||||
"""Event emitted when connection to an MCP server fails."""
|
||||
|
||||
type: str = "mcp_connection_failed"
|
||||
error: str
|
||||
error_type: str | None = None # "timeout", "authentication", "network", etc.
|
||||
started_at: datetime | None = None
|
||||
failed_at: datetime | None = None
|
||||
|
||||
|
||||
class MCPToolExecutionStartedEvent(MCPEvent):
|
||||
"""Event emitted when starting to execute an MCP tool."""
|
||||
|
||||
type: str = "mcp_tool_execution_started"
|
||||
tool_name: str
|
||||
tool_args: dict[str, Any] | None = None
|
||||
|
||||
|
||||
class MCPToolExecutionCompletedEvent(MCPEvent):
|
||||
"""Event emitted when MCP tool execution completes."""
|
||||
|
||||
type: str = "mcp_tool_execution_completed"
|
||||
tool_name: str
|
||||
tool_args: dict[str, Any] | None = None
|
||||
result: Any | None = None
|
||||
started_at: datetime | None = None
|
||||
completed_at: datetime | None = None
|
||||
execution_duration_ms: float | None = None
|
||||
|
||||
|
||||
class MCPToolExecutionFailedEvent(MCPEvent):
|
||||
"""Event emitted when MCP tool execution fails."""
|
||||
|
||||
type: str = "mcp_tool_execution_failed"
|
||||
tool_name: str
|
||||
tool_args: dict[str, Any] | None = None
|
||||
error: str
|
||||
error_type: str | None = None # "timeout", "validation", "server_error", etc.
|
||||
started_at: datetime | None = None
|
||||
failed_at: datetime | None = None
|
||||
@@ -2248,203 +2248,3 @@ class ConsoleFormatter:
|
||||
|
||||
self.current_a2a_conversation_branch = None
|
||||
self.current_a2a_turn_count = 0
|
||||
|
||||
# ----------- MCP EVENTS -----------
|
||||
|
||||
def handle_mcp_connection_started(
|
||||
self,
|
||||
server_name: str,
|
||||
server_url: str | None = None,
|
||||
transport_type: str | None = None,
|
||||
is_reconnect: bool = False,
|
||||
connect_timeout: int | None = None,
|
||||
) -> None:
|
||||
"""Handle MCP connection started event."""
|
||||
if not self.verbose:
|
||||
return
|
||||
|
||||
content = Text()
|
||||
reconnect_text = " (Reconnecting)" if is_reconnect else ""
|
||||
content.append(f"MCP Connection Started{reconnect_text}\n\n", style="cyan bold")
|
||||
content.append("Server: ", style="white")
|
||||
content.append(f"{server_name}\n", style="cyan")
|
||||
|
||||
if server_url:
|
||||
content.append("URL: ", style="white")
|
||||
content.append(f"{server_url}\n", style="cyan dim")
|
||||
|
||||
if transport_type:
|
||||
content.append("Transport: ", style="white")
|
||||
content.append(f"{transport_type}\n", style="cyan")
|
||||
|
||||
if connect_timeout:
|
||||
content.append("Timeout: ", style="white")
|
||||
content.append(f"{connect_timeout}s\n", style="cyan")
|
||||
|
||||
panel = self.create_panel(content, "🔌 MCP Connection", "cyan")
|
||||
self.print(panel)
|
||||
self.print()
|
||||
|
||||
def handle_mcp_connection_completed(
|
||||
self,
|
||||
server_name: str,
|
||||
server_url: str | None = None,
|
||||
transport_type: str | None = None,
|
||||
connection_duration_ms: float | None = None,
|
||||
is_reconnect: bool = False,
|
||||
) -> None:
|
||||
"""Handle MCP connection completed event."""
|
||||
if not self.verbose:
|
||||
return
|
||||
|
||||
content = Text()
|
||||
reconnect_text = " (Reconnected)" if is_reconnect else ""
|
||||
content.append(
|
||||
f"MCP Connection Completed{reconnect_text}\n\n", style="green bold"
|
||||
)
|
||||
content.append("Server: ", style="white")
|
||||
content.append(f"{server_name}\n", style="green")
|
||||
|
||||
if server_url:
|
||||
content.append("URL: ", style="white")
|
||||
content.append(f"{server_url}\n", style="green dim")
|
||||
|
||||
if transport_type:
|
||||
content.append("Transport: ", style="white")
|
||||
content.append(f"{transport_type}\n", style="green")
|
||||
|
||||
if connection_duration_ms is not None:
|
||||
content.append("Duration: ", style="white")
|
||||
content.append(f"{connection_duration_ms:.2f}ms\n", style="green")
|
||||
|
||||
panel = self.create_panel(content, "✅ MCP Connected", "green")
|
||||
self.print(panel)
|
||||
self.print()
|
||||
|
||||
def handle_mcp_connection_failed(
|
||||
self,
|
||||
server_name: str,
|
||||
server_url: str | None = None,
|
||||
transport_type: str | None = None,
|
||||
error: str = "",
|
||||
error_type: str | None = None,
|
||||
) -> None:
|
||||
"""Handle MCP connection failed event."""
|
||||
if not self.verbose:
|
||||
return
|
||||
|
||||
content = Text()
|
||||
content.append("MCP Connection Failed\n\n", style="red bold")
|
||||
content.append("Server: ", style="white")
|
||||
content.append(f"{server_name}\n", style="red")
|
||||
|
||||
if server_url:
|
||||
content.append("URL: ", style="white")
|
||||
content.append(f"{server_url}\n", style="red dim")
|
||||
|
||||
if transport_type:
|
||||
content.append("Transport: ", style="white")
|
||||
content.append(f"{transport_type}\n", style="red")
|
||||
|
||||
if error_type:
|
||||
content.append("Error Type: ", style="white")
|
||||
content.append(f"{error_type}\n", style="red")
|
||||
|
||||
if error:
|
||||
content.append("\nError: ", style="white bold")
|
||||
error_preview = error[:500] + "..." if len(error) > 500 else error
|
||||
content.append(f"{error_preview}\n", style="red")
|
||||
|
||||
panel = self.create_panel(content, "❌ MCP Connection Failed", "red")
|
||||
self.print(panel)
|
||||
self.print()
|
||||
|
||||
def handle_mcp_tool_execution_started(
|
||||
self,
|
||||
server_name: str,
|
||||
tool_name: str,
|
||||
tool_args: dict[str, Any] | None = None,
|
||||
) -> None:
|
||||
"""Handle MCP tool execution started event."""
|
||||
if not self.verbose:
|
||||
return
|
||||
|
||||
content = self.create_status_content(
|
||||
"MCP Tool Execution Started",
|
||||
tool_name,
|
||||
"yellow",
|
||||
tool_args=tool_args or {},
|
||||
Server=server_name,
|
||||
)
|
||||
|
||||
panel = self.create_panel(content, "🔧 MCP Tool", "yellow")
|
||||
self.print(panel)
|
||||
self.print()
|
||||
|
||||
def handle_mcp_tool_execution_completed(
|
||||
self,
|
||||
server_name: str,
|
||||
tool_name: str,
|
||||
tool_args: dict[str, Any] | None = None,
|
||||
result: Any | None = None,
|
||||
execution_duration_ms: float | None = None,
|
||||
) -> None:
|
||||
"""Handle MCP tool execution completed event."""
|
||||
if not self.verbose:
|
||||
return
|
||||
|
||||
content = self.create_status_content(
|
||||
"MCP Tool Execution Completed",
|
||||
tool_name,
|
||||
"green",
|
||||
tool_args=tool_args or {},
|
||||
Server=server_name,
|
||||
)
|
||||
|
||||
if execution_duration_ms is not None:
|
||||
content.append("Duration: ", style="white")
|
||||
content.append(f"{execution_duration_ms:.2f}ms\n", style="green")
|
||||
|
||||
if result is not None:
|
||||
result_str = str(result)
|
||||
if len(result_str) > 500:
|
||||
result_str = result_str[:497] + "..."
|
||||
content.append("\nResult: ", style="white bold")
|
||||
content.append(f"{result_str}\n", style="green")
|
||||
|
||||
panel = self.create_panel(content, "✅ MCP Tool Completed", "green")
|
||||
self.print(panel)
|
||||
self.print()
|
||||
|
||||
def handle_mcp_tool_execution_failed(
|
||||
self,
|
||||
server_name: str,
|
||||
tool_name: str,
|
||||
tool_args: dict[str, Any] | None = None,
|
||||
error: str = "",
|
||||
error_type: str | None = None,
|
||||
) -> None:
|
||||
"""Handle MCP tool execution failed event."""
|
||||
if not self.verbose:
|
||||
return
|
||||
|
||||
content = self.create_status_content(
|
||||
"MCP Tool Execution Failed",
|
||||
tool_name,
|
||||
"red",
|
||||
tool_args=tool_args or {},
|
||||
Server=server_name,
|
||||
)
|
||||
|
||||
if error_type:
|
||||
content.append("Error Type: ", style="white")
|
||||
content.append(f"{error_type}\n", style="red")
|
||||
|
||||
if error:
|
||||
content.append("\nError: ", style="white bold")
|
||||
error_preview = error[:500] + "..." if len(error) > 500 else error
|
||||
content.append(f"{error_preview}\n", style="red")
|
||||
|
||||
panel = self.create_panel(content, "❌ MCP Tool Failed", "red")
|
||||
self.print(panel)
|
||||
self.print()
|
||||
|
||||
@@ -15,6 +15,7 @@ import logging
|
||||
from typing import (
|
||||
Any,
|
||||
ClassVar,
|
||||
Final,
|
||||
Generic,
|
||||
Literal,
|
||||
ParamSpec,
|
||||
@@ -44,7 +45,7 @@ from crewai.events.types.flow_events import (
|
||||
MethodExecutionFinishedEvent,
|
||||
MethodExecutionStartedEvent,
|
||||
)
|
||||
from crewai.flow.constants import AND_CONDITION, OR_CONDITION
|
||||
from crewai.flow.visualization import build_flow_structure, render_interactive
|
||||
from crewai.flow.flow_wrappers import (
|
||||
FlowCondition,
|
||||
FlowConditions,
|
||||
@@ -57,16 +58,18 @@ from crewai.flow.flow_wrappers import (
|
||||
from crewai.flow.persistence.base import FlowPersistence
|
||||
from crewai.flow.types import FlowExecutionData, FlowMethodName, PendingListenerKey
|
||||
from crewai.flow.utils import (
|
||||
_extract_all_methods,
|
||||
_normalize_condition,
|
||||
get_possible_return_constants,
|
||||
is_flow_condition_dict,
|
||||
is_flow_condition_list,
|
||||
is_flow_method,
|
||||
is_flow_method_callable,
|
||||
is_flow_method_name,
|
||||
is_simple_flow_condition,
|
||||
_extract_all_methods,
|
||||
_extract_all_methods_recursive,
|
||||
_normalize_condition,
|
||||
)
|
||||
from crewai.flow.visualization import build_flow_structure, render_interactive
|
||||
from crewai.flow.constants import AND_CONDITION, OR_CONDITION
|
||||
from crewai.utilities.printer import Printer, PrinterColor
|
||||
|
||||
|
||||
@@ -428,8 +431,6 @@ class FlowMeta(type):
|
||||
possible_returns = get_possible_return_constants(attr_value)
|
||||
if possible_returns:
|
||||
router_paths[attr_name] = possible_returns
|
||||
else:
|
||||
router_paths[attr_name] = []
|
||||
|
||||
cls._start_methods = start_methods # type: ignore[attr-defined]
|
||||
cls._listeners = listeners # type: ignore[attr-defined]
|
||||
@@ -494,7 +495,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
|
||||
or should_auto_collect_first_time_traces()
|
||||
):
|
||||
trace_listener = TraceCollectionListener()
|
||||
trace_listener.setup_listeners(crewai_event_bus)
|
||||
trace_listener.setup_listeners(crewai_event_bus) # type: ignore[no-untyped-call]
|
||||
# Apply any additional kwargs
|
||||
if kwargs:
|
||||
self._initialize_state(kwargs)
|
||||
@@ -600,26 +601,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
|
||||
)
|
||||
|
||||
def _copy_state(self) -> T:
|
||||
"""Create a copy of the current state.
|
||||
|
||||
Returns:
|
||||
A copy of the current state
|
||||
"""
|
||||
if isinstance(self._state, BaseModel):
|
||||
try:
|
||||
return self._state.model_copy(deep=True)
|
||||
except (TypeError, AttributeError):
|
||||
try:
|
||||
state_dict = self._state.model_dump()
|
||||
model_class = type(self._state)
|
||||
return model_class(**state_dict)
|
||||
except Exception:
|
||||
return self._state.model_copy(deep=False)
|
||||
else:
|
||||
try:
|
||||
return copy.deepcopy(self._state)
|
||||
except (TypeError, AttributeError):
|
||||
return cast(T, self._state.copy())
|
||||
return copy.deepcopy(self._state)
|
||||
|
||||
@property
|
||||
def state(self) -> T:
|
||||
@@ -944,8 +926,8 @@ class Flow(Generic[T], metaclass=FlowMeta):
|
||||
trace_listener = TraceCollectionListener()
|
||||
if trace_listener.batch_manager.batch_owner_type == "flow":
|
||||
if trace_listener.first_time_handler.is_first_time:
|
||||
trace_listener.first_time_handler.mark_events_collected()
|
||||
trace_listener.first_time_handler.handle_execution_completion()
|
||||
trace_listener.first_time_handler.mark_events_collected() # type: ignore[no-untyped-call]
|
||||
trace_listener.first_time_handler.handle_execution_completion() # type: ignore[no-untyped-call]
|
||||
else:
|
||||
trace_listener.batch_manager.finalize_batch()
|
||||
|
||||
|
||||
@@ -21,7 +21,6 @@ P = ParamSpec("P")
|
||||
R = TypeVar("R", covariant=True)
|
||||
|
||||
FlowMethodName = NewType("FlowMethodName", str)
|
||||
FlowRouteName = NewType("FlowRouteName", str)
|
||||
PendingListenerKey = NewType(
|
||||
"PendingListenerKey",
|
||||
Annotated[str, "nested flow conditions use 'listener_name:object_id'"],
|
||||
|
||||
@@ -19,11 +19,11 @@ import ast
|
||||
from collections import defaultdict, deque
|
||||
import inspect
|
||||
import textwrap
|
||||
from typing import TYPE_CHECKING, Any
|
||||
from typing import Any, TYPE_CHECKING
|
||||
|
||||
from typing_extensions import TypeIs
|
||||
|
||||
from crewai.flow.constants import AND_CONDITION, OR_CONDITION
|
||||
from crewai.flow.constants import OR_CONDITION, AND_CONDITION
|
||||
from crewai.flow.flow_wrappers import (
|
||||
FlowCondition,
|
||||
FlowConditions,
|
||||
@@ -33,7 +33,6 @@ from crewai.flow.flow_wrappers import (
|
||||
from crewai.flow.types import FlowMethodCallable, FlowMethodName
|
||||
from crewai.utilities.printer import Printer
|
||||
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from crewai.flow.flow import Flow
|
||||
|
||||
@@ -41,22 +40,6 @@ _printer = Printer()
|
||||
|
||||
|
||||
def get_possible_return_constants(function: Any) -> list[str] | None:
|
||||
"""Extract possible string return values from a function using AST parsing.
|
||||
|
||||
This function analyzes the source code of a router method to identify
|
||||
all possible string values it might return. It handles:
|
||||
- Direct string literals: return "value"
|
||||
- Variable assignments: x = "value"; return x
|
||||
- Dictionary lookups: d = {"k": "v"}; return d[key]
|
||||
- Conditional returns: return "a" if cond else "b"
|
||||
- State attributes: return self.state.attr (infers from class context)
|
||||
|
||||
Args:
|
||||
function: The function to analyze.
|
||||
|
||||
Returns:
|
||||
List of possible string return values, or None if analysis fails.
|
||||
"""
|
||||
try:
|
||||
source = inspect.getsource(function)
|
||||
except OSError:
|
||||
@@ -99,7 +82,6 @@ def get_possible_return_constants(function: Any) -> list[str] | None:
|
||||
return_values: set[str] = set()
|
||||
dict_definitions: dict[str, list[str]] = {}
|
||||
variable_values: dict[str, list[str]] = {}
|
||||
state_attribute_values: dict[str, list[str]] = {}
|
||||
|
||||
def extract_string_constants(node: ast.expr) -> list[str]:
|
||||
"""Recursively extract all string constants from an AST node."""
|
||||
@@ -109,17 +91,6 @@ def get_possible_return_constants(function: Any) -> list[str] | None:
|
||||
elif isinstance(node, ast.IfExp):
|
||||
strings.extend(extract_string_constants(node.body))
|
||||
strings.extend(extract_string_constants(node.orelse))
|
||||
elif isinstance(node, ast.Call):
|
||||
if (
|
||||
isinstance(node.func, ast.Attribute)
|
||||
and node.func.attr == "get"
|
||||
and len(node.args) >= 2
|
||||
):
|
||||
default_arg = node.args[1]
|
||||
if isinstance(default_arg, ast.Constant) and isinstance(
|
||||
default_arg.value, str
|
||||
):
|
||||
strings.append(default_arg.value)
|
||||
return strings
|
||||
|
||||
class VariableAssignmentVisitor(ast.NodeVisitor):
|
||||
@@ -153,22 +124,6 @@ def get_possible_return_constants(function: Any) -> list[str] | None:
|
||||
|
||||
self.generic_visit(node)
|
||||
|
||||
def get_attribute_chain(node: ast.expr) -> str | None:
|
||||
"""Extract the full attribute chain from an AST node.
|
||||
|
||||
Examples:
|
||||
self.state.run_type -> "self.state.run_type"
|
||||
x.y.z -> "x.y.z"
|
||||
simple_var -> "simple_var"
|
||||
"""
|
||||
if isinstance(node, ast.Name):
|
||||
return node.id
|
||||
if isinstance(node, ast.Attribute):
|
||||
base = get_attribute_chain(node.value)
|
||||
if base:
|
||||
return f"{base}.{node.attr}"
|
||||
return None
|
||||
|
||||
class ReturnVisitor(ast.NodeVisitor):
|
||||
def visit_Return(self, node: ast.Return) -> None:
|
||||
if (
|
||||
@@ -184,94 +139,21 @@ def get_possible_return_constants(function: Any) -> list[str] | None:
|
||||
for v in dict_definitions[var_name_dict]:
|
||||
return_values.add(v)
|
||||
elif node.value:
|
||||
var_name_ret = get_attribute_chain(node.value)
|
||||
var_name_ret: str | None = None
|
||||
if isinstance(node.value, ast.Name):
|
||||
var_name_ret = node.value.id
|
||||
elif isinstance(node.value, ast.Attribute):
|
||||
var_name_ret = f"{node.value.value.id if isinstance(node.value.value, ast.Name) else '_'}.{node.value.attr}"
|
||||
|
||||
if var_name_ret and var_name_ret in variable_values:
|
||||
for v in variable_values[var_name_ret]:
|
||||
return_values.add(v)
|
||||
elif var_name_ret and var_name_ret in state_attribute_values:
|
||||
for v in state_attribute_values[var_name_ret]:
|
||||
return_values.add(v)
|
||||
|
||||
self.generic_visit(node)
|
||||
|
||||
def visit_If(self, node: ast.If) -> None:
|
||||
self.generic_visit(node)
|
||||
|
||||
# Try to get the class context to infer state attribute values
|
||||
try:
|
||||
if hasattr(function, "__self__"):
|
||||
# Method is bound, get the class
|
||||
class_obj = function.__self__.__class__
|
||||
elif hasattr(function, "__qualname__") and "." in function.__qualname__:
|
||||
# Method is unbound but we can try to get class from module
|
||||
class_name = function.__qualname__.rsplit(".", 1)[0]
|
||||
if hasattr(function, "__globals__"):
|
||||
class_obj = function.__globals__.get(class_name)
|
||||
else:
|
||||
class_obj = None
|
||||
else:
|
||||
class_obj = None
|
||||
|
||||
if class_obj is not None:
|
||||
try:
|
||||
class_source = inspect.getsource(class_obj)
|
||||
class_source = textwrap.dedent(class_source)
|
||||
class_ast = ast.parse(class_source)
|
||||
|
||||
# Look for comparisons and assignments involving state attributes
|
||||
class StateAttributeVisitor(ast.NodeVisitor):
|
||||
def visit_Compare(self, node: ast.Compare) -> None:
|
||||
"""Find comparisons like: self.state.attr == "value" """
|
||||
left_attr = get_attribute_chain(node.left)
|
||||
|
||||
if left_attr:
|
||||
for comparator in node.comparators:
|
||||
if isinstance(comparator, ast.Constant) and isinstance(
|
||||
comparator.value, str
|
||||
):
|
||||
if left_attr not in state_attribute_values:
|
||||
state_attribute_values[left_attr] = []
|
||||
if (
|
||||
comparator.value
|
||||
not in state_attribute_values[left_attr]
|
||||
):
|
||||
state_attribute_values[left_attr].append(
|
||||
comparator.value
|
||||
)
|
||||
|
||||
# Also check right side
|
||||
for comparator in node.comparators:
|
||||
right_attr = get_attribute_chain(comparator)
|
||||
if (
|
||||
right_attr
|
||||
and isinstance(node.left, ast.Constant)
|
||||
and isinstance(node.left.value, str)
|
||||
):
|
||||
if right_attr not in state_attribute_values:
|
||||
state_attribute_values[right_attr] = []
|
||||
if (
|
||||
node.left.value
|
||||
not in state_attribute_values[right_attr]
|
||||
):
|
||||
state_attribute_values[right_attr].append(
|
||||
node.left.value
|
||||
)
|
||||
|
||||
self.generic_visit(node)
|
||||
|
||||
StateAttributeVisitor().visit(class_ast)
|
||||
except Exception as e:
|
||||
_printer.print(
|
||||
f"Could not analyze class context for {function.__name__}: {e}",
|
||||
color="yellow",
|
||||
)
|
||||
except Exception as e:
|
||||
_printer.print(
|
||||
f"Could not introspect class for {function.__name__}: {e}",
|
||||
color="yellow",
|
||||
)
|
||||
|
||||
VariableAssignmentVisitor().visit(code_ast)
|
||||
ReturnVisitor().visit(code_ast)
|
||||
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -6,7 +6,6 @@
|
||||
<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
|
||||
<link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&display=swap" rel="stylesheet">
|
||||
<link rel="stylesheet" href="'{{ css_path }}'" />
|
||||
<script src="https://unpkg.com/lucide@latest"></script>
|
||||
<script src="https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/prism.min.js"></script>
|
||||
<script src="https://cdnjs.cloudflare.com/ajax/libs/prism/1.29.0/components/prism-python.min.js"></script>
|
||||
<script src="'{{ js_path }}'"></script>
|
||||
@@ -24,129 +23,93 @@
|
||||
<div class="drawer-title" id="drawer-node-name">Node Details</div>
|
||||
<div style="display: flex; align-items: center;">
|
||||
<button class="drawer-open-ide" id="drawer-open-ide" style="display: none;">
|
||||
<i data-lucide="file-code" style="width: 16px; height: 16px;"></i>
|
||||
<svg viewBox="0 0 16 16" fill="none" stroke="currentColor" stroke-width="2">
|
||||
<path d="M4 2 L12 2 L12 14 L4 14 Z" stroke-linecap="round" stroke-linejoin="round"/>
|
||||
<path d="M6 5 L10 5 M6 8 L10 8 M6 11 L10 11" stroke-linecap="round"/>
|
||||
</svg>
|
||||
Open in IDE
|
||||
</button>
|
||||
<button class="drawer-close" id="drawer-close">
|
||||
<i data-lucide="x" style="width: 20px; height: 20px;"></i>
|
||||
</button>
|
||||
<button class="drawer-close" id="drawer-close">×</button>
|
||||
</div>
|
||||
</div>
|
||||
<div class="drawer-content" id="drawer-content"></div>
|
||||
</div>
|
||||
|
||||
<div id="info">
|
||||
<div style="text-align: center;">
|
||||
<div style="text-align: center; margin-bottom: 20px;">
|
||||
<img src="https://cdn.prod.website-files.com/68de1ee6d7c127849807d7a6/68de1ee6d7c127849807d7ef_Logo.svg"
|
||||
alt="CrewAI Logo"
|
||||
style="width: 144px; height: auto;">
|
||||
style="width: 120px; height: auto;">
|
||||
</div>
|
||||
<h3>Flow Execution</h3>
|
||||
<div class="stats">
|
||||
<p><strong>Nodes:</strong> '{{ dag_nodes_count }}'</p>
|
||||
<p><strong>Edges:</strong> '{{ dag_edges_count }}'</p>
|
||||
<p><strong>Topological Paths:</strong> '{{ execution_paths }}'</p>
|
||||
</div>
|
||||
<div class="legend">
|
||||
<div class="legend-title">Node Types</div>
|
||||
<div class="legend-item">
|
||||
<div class="legend-color" style="background: '{{ CREWAI_ORANGE }}';"></div>
|
||||
<span>Start Methods</span>
|
||||
</div>
|
||||
<div class="legend-item">
|
||||
<div class="legend-color" style="background: '{{ DARK_GRAY }}'; border: 3px solid '{{ CREWAI_ORANGE }}';"></div>
|
||||
<span>Router Methods</span>
|
||||
</div>
|
||||
<div class="legend-item">
|
||||
<div class="legend-color" style="background: '{{ DARK_GRAY }}';"></div>
|
||||
<span>Listen Methods</span>
|
||||
</div>
|
||||
</div>
|
||||
<div class="legend">
|
||||
<div class="legend-title">Edge Types</div>
|
||||
<div class="legend-item">
|
||||
<svg width="24" height="12" style="margin-right: 12px;">
|
||||
<line x1="0" y1="6" x2="24" y2="6" stroke="'{{ CREWAI_ORANGE }}'" stroke-width="2" stroke-dasharray="5,5"/>
|
||||
</svg>
|
||||
<span>Router Paths</span>
|
||||
</div>
|
||||
<div class="legend-item">
|
||||
<svg width="24" height="12" style="margin-right: 12px;" class="legend-or-line">
|
||||
<line x1="0" y1="6" x2="24" y2="6" stroke="var(--edge-or-color)" stroke-width="2"/>
|
||||
</svg>
|
||||
<span>OR Conditions</span>
|
||||
</div>
|
||||
<div class="legend-item">
|
||||
<svg width="24" height="12" style="margin-right: 12px;">
|
||||
<line x1="0" y1="6" x2="24" y2="6" stroke="'{{ CREWAI_ORANGE }}'" stroke-width="2"/>
|
||||
</svg>
|
||||
<span>AND Conditions</span>
|
||||
</div>
|
||||
</div>
|
||||
<div class="instructions">
|
||||
<strong>Interactions:</strong><br>
|
||||
• Drag to pan<br>
|
||||
• Scroll to zoom<br><br>
|
||||
<strong>IDE:</strong>
|
||||
<select id="ide-selector" style="width: 100%; padding: 4px; margin-top: 4px; border-radius: 3px; border: 1px solid #e0e0e0; background: white; font-size: 12px; cursor: pointer; pointer-events: auto; position: relative; z-index: 10;">
|
||||
<option value="auto">Auto-detect</option>
|
||||
<option value="pycharm">PyCharm</option>
|
||||
<option value="vscode">VS Code</option>
|
||||
<option value="jetbrains">JetBrains (Toolbox)</option>
|
||||
</select>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
|
||||
<!-- Custom navigation controls -->
|
||||
<div class="nav-controls">
|
||||
<div class="nav-button" id="theme-toggle" title="Toggle Dark Mode">
|
||||
<i data-lucide="moon" style="width: 18px; height: 18px;"></i>
|
||||
</div>
|
||||
<div class="nav-button" id="zoom-in" title="Zoom In">
|
||||
<i data-lucide="zoom-in" style="width: 18px; height: 18px;"></i>
|
||||
</div>
|
||||
<div class="nav-button" id="zoom-out" title="Zoom Out">
|
||||
<i data-lucide="zoom-out" style="width: 18px; height: 18px;"></i>
|
||||
</div>
|
||||
<div class="nav-button" id="fit" title="Fit to Screen">
|
||||
<i data-lucide="maximize-2" style="width: 18px; height: 18px;"></i>
|
||||
</div>
|
||||
<div class="nav-button" id="export-png" title="Export to PNG">
|
||||
<i data-lucide="image" style="width: 18px; height: 18px;"></i>
|
||||
</div>
|
||||
<div class="nav-button" id="export-pdf" title="Export to PDF">
|
||||
<i data-lucide="file-text" style="width: 18px; height: 18px;"></i>
|
||||
</div>
|
||||
<!-- <div class="nav-button" id="export-json" title="Export to JSON">
|
||||
<i data-lucide="braces" style="width: 18px; height: 18px;"></i>
|
||||
</div> -->
|
||||
<div class="nav-button" id="theme-toggle" title="Toggle Dark Mode">🌙</div>
|
||||
<div class="nav-button" id="zoom-in" title="Zoom In">+</div>
|
||||
<div class="nav-button" id="zoom-out" title="Zoom Out">−</div>
|
||||
<div class="nav-button" id="fit" title="Fit to Screen">⊡</div>
|
||||
<div class="nav-button" id="export-png" title="Export to PNG">🖼</div>
|
||||
<div class="nav-button" id="export-pdf" title="Export to PDF">📄</div>
|
||||
<div class="nav-button" id="export-json" title="Export to JSON">{}</div>
|
||||
</div>
|
||||
|
||||
<div id="network-container">
|
||||
<div id="network"></div>
|
||||
</div>
|
||||
|
||||
<!-- Info panel at bottom -->
|
||||
<div id="legend-panel">
|
||||
<!-- Stats Section -->
|
||||
<div class="legend-section">
|
||||
<div class="legend-stats-row">
|
||||
<div class="legend-stat-item">
|
||||
<span class="stat-value">'{{ dag_nodes_count }}'</span>
|
||||
<span class="stat-label">Nodes</span>
|
||||
</div>
|
||||
<div class="legend-stat-item">
|
||||
<span class="stat-value">'{{ dag_edges_count }}'</span>
|
||||
<span class="stat-label">Edges</span>
|
||||
</div>
|
||||
<div class="legend-stat-item">
|
||||
<span class="stat-value">'{{ execution_paths }}'</span>
|
||||
<span class="stat-label">Paths</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Node Types Section -->
|
||||
<div class="legend-section">
|
||||
<div class="legend-group">
|
||||
<div class="legend-item-compact">
|
||||
<div class="legend-color-small" style="background: var(--node-bg-start);"></div>
|
||||
<span>Start</span>
|
||||
</div>
|
||||
<div class="legend-item-compact">
|
||||
<div class="legend-color-small" style="background: var(--node-bg-router); border: 2px solid var(--node-border-start);"></div>
|
||||
<span>Router</span>
|
||||
</div>
|
||||
<div class="legend-item-compact">
|
||||
<div class="legend-color-small" style="background: var(--node-bg-listen); border: 2px solid var(--node-border-listen);"></div>
|
||||
<span>Listen</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Edge Types Section -->
|
||||
<div class="legend-section">
|
||||
<div class="legend-group">
|
||||
<div class="legend-item-compact">
|
||||
<svg>
|
||||
<line x1="0" y1="7" x2="29" y2="7" stroke="var(--edge-router-color)" stroke-width="2" stroke-dasharray="4,4"/>
|
||||
</svg>
|
||||
<span>Router</span>
|
||||
</div>
|
||||
<div class="legend-item-compact">
|
||||
<svg class="legend-or-line">
|
||||
<line x1="0" y1="7" x2="29" y2="7" stroke="var(--edge-or-color)" stroke-width="2"/>
|
||||
</svg>
|
||||
<span>OR</span>
|
||||
</div>
|
||||
<div class="legend-item-compact">
|
||||
<svg>
|
||||
<line x1="0" y1="7" x2="29" y2="7" stroke="var(--edge-router-color)" stroke-width="2"/>
|
||||
</svg>
|
||||
<span>AND</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- IDE Selector Section -->
|
||||
<div class="legend-section">
|
||||
<div class="legend-ide-column">
|
||||
<label class="legend-ide-label">IDE</label>
|
||||
<select id="ide-selector" class="legend-ide-select">
|
||||
<option value="auto">Auto-detect</option>
|
||||
<option value="pycharm">PyCharm</option>
|
||||
<option value="vscode">VS Code</option>
|
||||
<option value="jetbrains">JetBrains</option>
|
||||
</select>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</body>
|
||||
</html>
|
||||
|
||||
@@ -13,14 +13,6 @@
|
||||
--edge-label-text: '{{ GRAY }}';
|
||||
--edge-label-bg: rgba(255, 255, 255, 0.8);
|
||||
--edge-or-color: #000000;
|
||||
--edge-router-color: '{{ CREWAI_ORANGE }}';
|
||||
--node-border-start: #C94238;
|
||||
--node-border-listen: #3D3D3D;
|
||||
--node-bg-start: #FF7066;
|
||||
--node-bg-router: #FFFFFF;
|
||||
--node-bg-listen: #FFFFFF;
|
||||
--node-text-color: #FFFFFF;
|
||||
--nav-button-hover: #f5f5f5;
|
||||
}
|
||||
|
||||
[data-theme="dark"] {
|
||||
@@ -38,14 +30,6 @@
|
||||
--edge-label-text: #c9d1d9;
|
||||
--edge-label-bg: rgba(22, 27, 34, 0.9);
|
||||
--edge-or-color: #ffffff;
|
||||
--edge-router-color: '{{ CREWAI_ORANGE }}';
|
||||
--node-border-start: #FF5A50;
|
||||
--node-border-listen: #666666;
|
||||
--node-bg-start: #B33830;
|
||||
--node-bg-router: #3D3D3D;
|
||||
--node-bg-listen: #3D3D3D;
|
||||
--node-text-color: #FFFFFF;
|
||||
--nav-button-hover: #30363d;
|
||||
}
|
||||
|
||||
@keyframes dash {
|
||||
@@ -88,10 +72,12 @@ body {
|
||||
position: absolute;
|
||||
top: 20px;
|
||||
left: 20px;
|
||||
background: transparent;
|
||||
background: var(--bg-secondary);
|
||||
padding: 20px;
|
||||
border-radius: 8px;
|
||||
box-shadow: 0 4px 12px var(--shadow-strong);
|
||||
max-width: 320px;
|
||||
border: 1px solid var(--border-color);
|
||||
z-index: 10000;
|
||||
pointer-events: auto;
|
||||
transition: background 0.3s ease, border-color 0.3s ease, box-shadow 0.3s ease;
|
||||
@@ -139,16 +125,12 @@ h3 {
|
||||
margin-right: 12px;
|
||||
border-radius: 3px;
|
||||
box-sizing: border-box;
|
||||
transition: background 0.3s ease, border-color 0.3s ease;
|
||||
}
|
||||
.legend-item span {
|
||||
color: var(--text-secondary);
|
||||
font-size: 13px;
|
||||
transition: color 0.3s ease;
|
||||
}
|
||||
.legend-item svg line {
|
||||
transition: stroke 0.3s ease;
|
||||
}
|
||||
.instructions {
|
||||
margin-top: 15px;
|
||||
padding-top: 15px;
|
||||
@@ -173,7 +155,7 @@ h3 {
|
||||
bottom: 20px;
|
||||
right: auto;
|
||||
display: grid;
|
||||
grid-template-columns: repeat(3, 40px);
|
||||
grid-template-columns: repeat(4, 40px);
|
||||
gap: 8px;
|
||||
z-index: 10002;
|
||||
pointer-events: auto;
|
||||
@@ -183,187 +165,10 @@ h3 {
|
||||
.nav-controls.drawer-open {
|
||||
}
|
||||
|
||||
#legend-panel {
|
||||
position: fixed;
|
||||
left: 164px;
|
||||
bottom: 20px;
|
||||
right: 20px;
|
||||
height: 92px;
|
||||
background: var(--bg-secondary);
|
||||
backdrop-filter: blur(12px) saturate(180%);
|
||||
-webkit-backdrop-filter: blur(12px) saturate(180%);
|
||||
border: 1px solid var(--border-subtle);
|
||||
border-radius: 6px;
|
||||
box-shadow: 0 2px 8px var(--shadow-color);
|
||||
display: grid;
|
||||
grid-template-columns: repeat(4, 1fr);
|
||||
align-items: center;
|
||||
gap: 0;
|
||||
padding: 0 24px;
|
||||
box-sizing: border-box;
|
||||
z-index: 10001;
|
||||
pointer-events: auto;
|
||||
transition: background 0.3s ease, border-color 0.3s ease, box-shadow 0.3s ease, right 0.3s cubic-bezier(0.4, 0, 0.2, 1);
|
||||
}
|
||||
|
||||
#legend-panel.drawer-open {
|
||||
right: 405px;
|
||||
}
|
||||
|
||||
.legend-section {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
min-width: 0;
|
||||
width: -webkit-fill-available;
|
||||
width: -moz-available;
|
||||
width: stretch;
|
||||
position: relative;
|
||||
}
|
||||
|
||||
.legend-section:not(:last-child)::after {
|
||||
content: '';
|
||||
position: absolute;
|
||||
right: 0;
|
||||
top: 50%;
|
||||
transform: translateY(-50%);
|
||||
width: 1px;
|
||||
height: 48px;
|
||||
background: var(--border-color);
|
||||
transition: background 0.3s ease;
|
||||
}
|
||||
|
||||
.legend-stats-row {
|
||||
display: flex;
|
||||
gap: 32px;
|
||||
justify-content: center;
|
||||
align-items: center;
|
||||
min-width: 0;
|
||||
}
|
||||
|
||||
.legend-stat-item {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
align-items: center;
|
||||
gap: 4px;
|
||||
}
|
||||
|
||||
.stat-value {
|
||||
font-size: 19px;
|
||||
font-weight: 700;
|
||||
color: var(--text-primary);
|
||||
line-height: 1;
|
||||
transition: color 0.3s ease;
|
||||
}
|
||||
|
||||
.stat-label {
|
||||
font-size: 8px;
|
||||
font-weight: 500;
|
||||
text-transform: uppercase;
|
||||
color: var(--text-secondary);
|
||||
letter-spacing: 0.5px;
|
||||
transition: color 0.3s ease;
|
||||
}
|
||||
|
||||
.legend-items-row {
|
||||
display: flex;
|
||||
gap: 16px;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
min-width: 0;
|
||||
}
|
||||
|
||||
.legend-group {
|
||||
display: flex;
|
||||
gap: 16px;
|
||||
align-items: center;
|
||||
}
|
||||
|
||||
.legend-item-compact {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: 6px;
|
||||
}
|
||||
|
||||
.legend-item-compact span {
|
||||
font-size: 12px;
|
||||
font-weight: 500;
|
||||
text-transform: uppercase;
|
||||
color: var(--text-secondary);
|
||||
letter-spacing: 0.5px;
|
||||
white-space: nowrap;
|
||||
font-family: inherit;
|
||||
line-height: 1;
|
||||
transition: color 0.3s ease;
|
||||
}
|
||||
|
||||
.legend-color-small {
|
||||
width: 17px;
|
||||
height: 17px;
|
||||
border-radius: 2px;
|
||||
box-sizing: border-box;
|
||||
flex-shrink: 0;
|
||||
transition: background 0.3s ease, border-color 0.3s ease;
|
||||
}
|
||||
|
||||
.legend-item-compact svg {
|
||||
display: block;
|
||||
flex-shrink: 0;
|
||||
width: 29px;
|
||||
height: 14px;
|
||||
}
|
||||
|
||||
.legend-item-compact svg line {
|
||||
transition: stroke 0.3s ease;
|
||||
}
|
||||
|
||||
.legend-ide-column {
|
||||
display: flex;
|
||||
flex-direction: row;
|
||||
gap: 8px;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
min-width: 0;
|
||||
width: 100%;
|
||||
}
|
||||
|
||||
.legend-ide-label {
|
||||
font-size: 12px;
|
||||
font-weight: 500;
|
||||
text-transform: uppercase;
|
||||
color: var(--text-secondary);
|
||||
letter-spacing: 0.5px;
|
||||
transition: color 0.3s ease;
|
||||
white-space: nowrap;
|
||||
}
|
||||
|
||||
.legend-ide-select {
|
||||
width: 120px;
|
||||
padding: 6px 10px;
|
||||
border-radius: 4px;
|
||||
border: 1px solid var(--border-subtle);
|
||||
background: var(--bg-primary);
|
||||
color: var(--text-primary);
|
||||
font-size: 11px;
|
||||
cursor: pointer;
|
||||
transition: all 0.3s ease;
|
||||
}
|
||||
|
||||
.legend-ide-select:hover {
|
||||
border-color: var(--text-secondary);
|
||||
}
|
||||
|
||||
.legend-ide-select:focus {
|
||||
outline: none;
|
||||
border-color: '{{ CREWAI_ORANGE }}';
|
||||
}
|
||||
|
||||
.nav-button {
|
||||
width: 40px;
|
||||
height: 40px;
|
||||
background: var(--bg-secondary);
|
||||
backdrop-filter: blur(12px) saturate(180%);
|
||||
-webkit-backdrop-filter: blur(12px) saturate(180%);
|
||||
border: 1px solid var(--border-subtle);
|
||||
border-radius: 6px;
|
||||
display: flex;
|
||||
@@ -376,12 +181,12 @@ h3 {
|
||||
user-select: none;
|
||||
pointer-events: auto;
|
||||
position: relative;
|
||||
z-index: 10002;
|
||||
z-index: 10001;
|
||||
transition: background 0.3s ease, border-color 0.3s ease, color 0.3s ease, box-shadow 0.3s ease;
|
||||
}
|
||||
|
||||
.nav-button:hover {
|
||||
background: var(--nav-button-hover);
|
||||
background: var(--border-subtle);
|
||||
}
|
||||
|
||||
#drawer {
|
||||
@@ -393,10 +198,9 @@ h3 {
|
||||
background: var(--bg-drawer);
|
||||
box-shadow: -4px 0 12px var(--shadow-strong);
|
||||
transition: right 0.3s cubic-bezier(0.4, 0, 0.2, 1), background 0.3s ease, box-shadow 0.3s ease;
|
||||
z-index: 10003;
|
||||
overflow: hidden;
|
||||
transform: translateZ(0);
|
||||
isolation: isolate;
|
||||
z-index: 2000;
|
||||
overflow-y: auto;
|
||||
padding: 24px;
|
||||
}
|
||||
|
||||
#drawer.open {
|
||||
@@ -443,22 +247,17 @@ h3 {
|
||||
justify-content: space-between;
|
||||
align-items: center;
|
||||
margin-bottom: 20px;
|
||||
padding: 24px 24px 16px 24px;
|
||||
padding-bottom: 16px;
|
||||
border-bottom: 2px solid '{{ CREWAI_ORANGE }}';
|
||||
position: relative;
|
||||
z-index: 2001;
|
||||
}
|
||||
|
||||
.drawer-title {
|
||||
font-size: 15px;
|
||||
font-size: 20px;
|
||||
font-weight: 700;
|
||||
color: var(--text-primary);
|
||||
transition: color 0.3s ease;
|
||||
overflow: hidden;
|
||||
text-overflow: ellipsis;
|
||||
white-space: nowrap;
|
||||
flex: 1;
|
||||
min-width: 0;
|
||||
}
|
||||
|
||||
.drawer-close {
|
||||
@@ -470,19 +269,12 @@ h3 {
|
||||
padding: 4px 8px;
|
||||
line-height: 1;
|
||||
transition: color 0.3s ease;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
}
|
||||
|
||||
.drawer-close:hover {
|
||||
color: '{{ CREWAI_ORANGE }}';
|
||||
}
|
||||
|
||||
.drawer-close i {
|
||||
display: block;
|
||||
}
|
||||
|
||||
.drawer-open-ide {
|
||||
background: '{{ CREWAI_ORANGE }}';
|
||||
border: none;
|
||||
@@ -500,9 +292,6 @@ h3 {
|
||||
position: relative;
|
||||
z-index: 9999;
|
||||
pointer-events: auto;
|
||||
white-space: nowrap;
|
||||
flex-shrink: 0;
|
||||
min-width: fit-content;
|
||||
}
|
||||
|
||||
.drawer-open-ide:hover {
|
||||
@@ -516,19 +305,14 @@ h3 {
|
||||
box-shadow: 0 1px 4px rgba(255, 90, 80, 0.2);
|
||||
}
|
||||
|
||||
.drawer-open-ide svg,
|
||||
.drawer-open-ide i {
|
||||
.drawer-open-ide svg {
|
||||
width: 14px;
|
||||
height: 14px;
|
||||
display: block;
|
||||
}
|
||||
|
||||
.drawer-content {
|
||||
color: '{{ DARK_GRAY }}';
|
||||
line-height: 1.6;
|
||||
padding: 0 24px 24px 24px;
|
||||
overflow-y: auto;
|
||||
height: calc(100vh - 95px);
|
||||
}
|
||||
|
||||
.drawer-section {
|
||||
@@ -544,10 +328,6 @@ h3 {
|
||||
position: relative;
|
||||
}
|
||||
|
||||
.drawer-metadata-grid:has(.drawer-section:nth-child(3):nth-last-child(1)) {
|
||||
grid-template-columns: 1fr 2fr;
|
||||
}
|
||||
|
||||
.drawer-metadata-grid::before {
|
||||
content: '';
|
||||
position: absolute;
|
||||
@@ -639,35 +419,20 @@ h3 {
|
||||
grid-column: 2;
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
justify-content: flex-start;
|
||||
align-items: flex-start;
|
||||
justify-content: center;
|
||||
}
|
||||
|
||||
.drawer-metadata-grid:has(.drawer-section:nth-child(3):nth-last-child(1))::after {
|
||||
right: 66.666%;
|
||||
}
|
||||
|
||||
.drawer-metadata-grid:has(.drawer-section:nth-child(3):nth-last-child(1))::before {
|
||||
left: 33.333%;
|
||||
}
|
||||
|
||||
.drawer-metadata-grid .drawer-section:nth-child(3):nth-last-child(1) .drawer-section-title {
|
||||
align-self: flex-start;
|
||||
}
|
||||
|
||||
.drawer-metadata-grid .drawer-section:nth-child(3):nth-last-child(1) > *:not(.drawer-section-title) {
|
||||
width: 100%;
|
||||
align-self: stretch;
|
||||
right: 50%;
|
||||
}
|
||||
|
||||
.drawer-section-title {
|
||||
font-size: 12px;
|
||||
text-transform: uppercase;
|
||||
color: var(--text-secondary);
|
||||
color: '{{ GRAY }}';
|
||||
letter-spacing: 0.5px;
|
||||
margin-bottom: 8px;
|
||||
font-weight: 600;
|
||||
transition: color 0.3s ease;
|
||||
}
|
||||
|
||||
.drawer-badge {
|
||||
@@ -700,44 +465,9 @@ h3 {
|
||||
padding: 3px 0;
|
||||
}
|
||||
|
||||
.drawer-metadata-grid .drawer-section .drawer-list {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 6px;
|
||||
}
|
||||
|
||||
.drawer-metadata-grid .drawer-section .drawer-list li {
|
||||
border-bottom: none;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
.drawer-metadata-grid .drawer-section:nth-child(3) .drawer-list li {
|
||||
border-bottom: none;
|
||||
padding: 0;
|
||||
}
|
||||
|
||||
.drawer-metadata-grid .drawer-section {
|
||||
overflow: visible;
|
||||
}
|
||||
|
||||
.drawer-metadata-grid .drawer-section .condition-group,
|
||||
.drawer-metadata-grid .drawer-section .trigger-group {
|
||||
width: 100%;
|
||||
box-sizing: border-box;
|
||||
}
|
||||
|
||||
.drawer-metadata-grid .drawer-section .condition-children {
|
||||
width: 100%;
|
||||
}
|
||||
|
||||
.drawer-metadata-grid .drawer-section .trigger-group-items {
|
||||
width: 100%;
|
||||
}
|
||||
|
||||
.drawer-metadata-grid .drawer-section .drawer-code-link {
|
||||
word-break: break-word;
|
||||
overflow-wrap: break-word;
|
||||
max-width: 100%;
|
||||
padding: 3px 0;
|
||||
}
|
||||
|
||||
.drawer-code {
|
||||
@@ -761,7 +491,6 @@ h3 {
|
||||
cursor: pointer;
|
||||
transition: all 0.2s;
|
||||
display: inline-block;
|
||||
margin: 3px 2px;
|
||||
}
|
||||
|
||||
.drawer-code-link:hover {
|
||||
|
||||
@@ -3,13 +3,12 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from collections import defaultdict
|
||||
from collections.abc import Iterable
|
||||
import inspect
|
||||
from typing import TYPE_CHECKING, Any
|
||||
|
||||
from crewai.flow.constants import AND_CONDITION, OR_CONDITION
|
||||
from crewai.flow.flow_wrappers import FlowCondition
|
||||
from crewai.flow.types import FlowMethodName, FlowRouteName
|
||||
from crewai.flow.types import FlowMethodName
|
||||
from crewai.flow.utils import (
|
||||
is_flow_condition_dict,
|
||||
is_simple_flow_condition,
|
||||
@@ -198,6 +197,8 @@ def build_flow_structure(flow: Flow[Any]) -> FlowStructure:
|
||||
node_metadata["type"] = "router"
|
||||
router_methods.append(method_name)
|
||||
|
||||
node_metadata["condition_type"] = "IF"
|
||||
|
||||
if method_name in flow._router_paths:
|
||||
node_metadata["router_paths"] = [
|
||||
str(p) for p in flow._router_paths[method_name]
|
||||
@@ -209,13 +210,9 @@ def build_flow_structure(flow: Flow[Any]) -> FlowStructure:
|
||||
]
|
||||
|
||||
if hasattr(method, "__condition_type__") and method.__condition_type__:
|
||||
node_metadata["trigger_condition_type"] = method.__condition_type__
|
||||
if "condition_type" not in node_metadata:
|
||||
node_metadata["condition_type"] = method.__condition_type__
|
||||
|
||||
if node_metadata.get("is_router") and "condition_type" not in node_metadata:
|
||||
node_metadata["condition_type"] = "IF"
|
||||
|
||||
if (
|
||||
hasattr(method, "__trigger_condition__")
|
||||
and method.__trigger_condition__ is not None
|
||||
@@ -301,9 +298,6 @@ def build_flow_structure(flow: Flow[Any]) -> FlowStructure:
|
||||
nodes[method_name] = node_metadata
|
||||
|
||||
for listener_name, condition_data in flow._listeners.items():
|
||||
if listener_name in router_methods:
|
||||
continue
|
||||
|
||||
if is_simple_flow_condition(condition_data):
|
||||
cond_type, methods = condition_data
|
||||
edges.extend(
|
||||
@@ -321,60 +315,6 @@ def build_flow_structure(flow: Flow[Any]) -> FlowStructure:
|
||||
_create_edges_from_condition(condition_data, str(listener_name), nodes)
|
||||
)
|
||||
|
||||
for method_name, node_metadata in nodes.items(): # type: ignore[assignment]
|
||||
if node_metadata.get("is_router") and "trigger_methods" in node_metadata:
|
||||
trigger_methods = node_metadata["trigger_methods"]
|
||||
condition_type = node_metadata.get("trigger_condition_type", OR_CONDITION)
|
||||
|
||||
if "trigger_condition" in node_metadata:
|
||||
edges.extend(
|
||||
_create_edges_from_condition(
|
||||
node_metadata["trigger_condition"], # type: ignore[arg-type]
|
||||
method_name,
|
||||
nodes,
|
||||
)
|
||||
)
|
||||
else:
|
||||
edges.extend(
|
||||
StructureEdge(
|
||||
source=trigger_method,
|
||||
target=method_name,
|
||||
condition_type=condition_type,
|
||||
is_router_path=False,
|
||||
)
|
||||
for trigger_method in trigger_methods
|
||||
if trigger_method in nodes
|
||||
)
|
||||
|
||||
for router_method_name in router_methods:
|
||||
if router_method_name not in flow._router_paths:
|
||||
flow._router_paths[FlowMethodName(router_method_name)] = []
|
||||
|
||||
inferred_paths: Iterable[FlowMethodName | FlowRouteName] = set(
|
||||
flow._router_paths.get(FlowMethodName(router_method_name), [])
|
||||
)
|
||||
|
||||
for condition_data in flow._listeners.values():
|
||||
trigger_strings: list[str] = []
|
||||
|
||||
if is_simple_flow_condition(condition_data):
|
||||
_, methods = condition_data
|
||||
trigger_strings = [str(m) for m in methods]
|
||||
elif is_flow_condition_dict(condition_data):
|
||||
trigger_strings = _extract_direct_or_triggers(condition_data)
|
||||
|
||||
for trigger_str in trigger_strings:
|
||||
if trigger_str not in nodes:
|
||||
# This is likely a router path output
|
||||
inferred_paths.add(trigger_str) # type: ignore[attr-defined]
|
||||
|
||||
if inferred_paths:
|
||||
flow._router_paths[FlowMethodName(router_method_name)] = list(
|
||||
inferred_paths # type: ignore[arg-type]
|
||||
)
|
||||
if router_method_name in nodes:
|
||||
nodes[router_method_name]["router_paths"] = list(inferred_paths)
|
||||
|
||||
for router_method_name in router_methods:
|
||||
if router_method_name not in flow._router_paths:
|
||||
continue
|
||||
@@ -400,7 +340,6 @@ def build_flow_structure(flow: Flow[Any]) -> FlowStructure:
|
||||
target=str(listener_name),
|
||||
condition_type=None,
|
||||
is_router_path=True,
|
||||
router_path_label=str(path),
|
||||
)
|
||||
)
|
||||
|
||||
|
||||
@@ -20,7 +20,7 @@ class CSSExtension(Extension):
|
||||
Provides {% css 'path/to/file.css' %} tag syntax.
|
||||
"""
|
||||
|
||||
tags: ClassVar[set[str]] = {"css"} # type: ignore[misc]
|
||||
tags: ClassVar[set[str]] = {"css"} # type: ignore[assignment]
|
||||
|
||||
def parse(self, parser: Parser) -> nodes.Node:
|
||||
"""Parse {% css 'styles.css' %} tag.
|
||||
@@ -53,7 +53,7 @@ class JSExtension(Extension):
|
||||
Provides {% js 'path/to/file.js' %} tag syntax.
|
||||
"""
|
||||
|
||||
tags: ClassVar[set[str]] = {"js"} # type: ignore[misc]
|
||||
tags: ClassVar[set[str]] = {"js"} # type: ignore[assignment]
|
||||
|
||||
def parse(self, parser: Parser) -> nodes.Node:
|
||||
"""Parse {% js 'script.js' %} tag.
|
||||
@@ -91,116 +91,6 @@ TEXT_PRIMARY = "#e6edf3"
|
||||
TEXT_SECONDARY = "#7d8590"
|
||||
|
||||
|
||||
def calculate_node_positions(
|
||||
dag: FlowStructure,
|
||||
) -> dict[str, dict[str, int | float]]:
|
||||
"""Calculate hierarchical positions (level, x, y) for each node.
|
||||
|
||||
Args:
|
||||
dag: FlowStructure containing nodes and edges.
|
||||
|
||||
Returns:
|
||||
Dictionary mapping node names to their position data (level, x, y).
|
||||
"""
|
||||
children: dict[str, list[str]] = {name: [] for name in dag["nodes"]}
|
||||
parents: dict[str, list[str]] = {name: [] for name in dag["nodes"]}
|
||||
|
||||
for edge in dag["edges"]:
|
||||
source = edge["source"]
|
||||
target = edge["target"]
|
||||
if source in children and target in children:
|
||||
children[source].append(target)
|
||||
parents[target].append(source)
|
||||
|
||||
levels: dict[str, int] = {}
|
||||
queue: list[tuple[str, int]] = []
|
||||
|
||||
for start_method in dag["start_methods"]:
|
||||
if start_method in dag["nodes"]:
|
||||
levels[start_method] = 0
|
||||
queue.append((start_method, 0))
|
||||
|
||||
visited: set[str] = set()
|
||||
while queue:
|
||||
node, level = queue.pop(0)
|
||||
if node in visited:
|
||||
continue
|
||||
visited.add(node)
|
||||
|
||||
if node not in levels or levels[node] < level:
|
||||
levels[node] = level
|
||||
|
||||
for child in children.get(node, []):
|
||||
if child not in visited:
|
||||
child_level = level + 1
|
||||
if child not in levels or levels[child] < child_level:
|
||||
levels[child] = child_level
|
||||
queue.append((child, child_level))
|
||||
|
||||
for name in dag["nodes"]:
|
||||
if name not in levels:
|
||||
levels[name] = 0
|
||||
|
||||
nodes_by_level: dict[int, list[str]] = {}
|
||||
for node, level in levels.items():
|
||||
if level not in nodes_by_level:
|
||||
nodes_by_level[level] = []
|
||||
nodes_by_level[level].append(node)
|
||||
|
||||
positions: dict[str, dict[str, int | float]] = {}
|
||||
level_separation = 300 # Vertical spacing between levels
|
||||
node_spacing = 400 # Horizontal spacing between nodes
|
||||
|
||||
parent_count: dict[str, int] = {}
|
||||
for node, parent_list in parents.items():
|
||||
parent_count[node] = len(parent_list)
|
||||
|
||||
for level, nodes_at_level in sorted(nodes_by_level.items()):
|
||||
y = level * level_separation
|
||||
|
||||
if level == 0:
|
||||
num_nodes = len(nodes_at_level)
|
||||
for i, node in enumerate(nodes_at_level):
|
||||
x = (i - (num_nodes - 1) / 2) * node_spacing
|
||||
positions[node] = {"level": level, "x": x, "y": y}
|
||||
else:
|
||||
for i, node in enumerate(nodes_at_level):
|
||||
parent_list = parents.get(node, [])
|
||||
parent_positions: list[float] = [
|
||||
positions[parent]["x"]
|
||||
for parent in parent_list
|
||||
if parent in positions
|
||||
]
|
||||
|
||||
if parent_positions:
|
||||
if len(parent_positions) > 1 and len(set(parent_positions)) == 1:
|
||||
base_x = parent_positions[0]
|
||||
avg_x = base_x + node_spacing * 0.4
|
||||
else:
|
||||
avg_x = sum(parent_positions) / len(parent_positions)
|
||||
else:
|
||||
avg_x = i * node_spacing * 0.5
|
||||
|
||||
positions[node] = {"level": level, "x": avg_x, "y": y}
|
||||
|
||||
nodes_at_level_sorted = sorted(
|
||||
nodes_at_level, key=lambda n: positions[n]["x"]
|
||||
)
|
||||
min_spacing = node_spacing * 0.6 # Minimum horizontal distance
|
||||
|
||||
for i in range(len(nodes_at_level_sorted) - 1):
|
||||
current_node = nodes_at_level_sorted[i]
|
||||
next_node = nodes_at_level_sorted[i + 1]
|
||||
|
||||
current_x = positions[current_node]["x"]
|
||||
next_x = positions[next_node]["x"]
|
||||
|
||||
if next_x - current_x < min_spacing:
|
||||
positions[next_node]["x"] = current_x + min_spacing
|
||||
|
||||
return positions
|
||||
|
||||
|
||||
def render_interactive(
|
||||
dag: FlowStructure,
|
||||
filename: str = "flow_dag.html",
|
||||
@@ -220,8 +110,6 @@ def render_interactive(
|
||||
Returns:
|
||||
Absolute path to generated HTML file in temporary directory.
|
||||
"""
|
||||
node_positions = calculate_node_positions(dag)
|
||||
|
||||
nodes_list: list[dict[str, Any]] = []
|
||||
for name, metadata in dag["nodes"].items():
|
||||
node_type: str = metadata.get("type", "listen")
|
||||
@@ -232,37 +120,37 @@ def render_interactive(
|
||||
|
||||
if node_type == "start":
|
||||
color_config = {
|
||||
"background": "var(--node-bg-start)",
|
||||
"border": "var(--node-border-start)",
|
||||
"highlight": {
|
||||
"background": "var(--node-bg-start)",
|
||||
"border": "var(--node-border-start)",
|
||||
},
|
||||
}
|
||||
font_color = "var(--node-text-color)"
|
||||
border_width = 3
|
||||
elif node_type == "router":
|
||||
color_config = {
|
||||
"background": "var(--node-bg-router)",
|
||||
"background": CREWAI_ORANGE,
|
||||
"border": CREWAI_ORANGE,
|
||||
"highlight": {
|
||||
"background": "var(--node-bg-router)",
|
||||
"background": CREWAI_ORANGE,
|
||||
"border": CREWAI_ORANGE,
|
||||
},
|
||||
}
|
||||
font_color = "var(--node-text-color)"
|
||||
font_color = WHITE
|
||||
border_width = 2
|
||||
elif node_type == "router":
|
||||
color_config = {
|
||||
"background": DARK_GRAY,
|
||||
"border": CREWAI_ORANGE,
|
||||
"highlight": {
|
||||
"background": DARK_GRAY,
|
||||
"border": CREWAI_ORANGE,
|
||||
},
|
||||
}
|
||||
font_color = WHITE
|
||||
border_width = 3
|
||||
else:
|
||||
color_config = {
|
||||
"background": "var(--node-bg-listen)",
|
||||
"border": "var(--node-border-listen)",
|
||||
"background": DARK_GRAY,
|
||||
"border": DARK_GRAY,
|
||||
"highlight": {
|
||||
"background": "var(--node-bg-listen)",
|
||||
"border": "var(--node-border-listen)",
|
||||
"background": DARK_GRAY,
|
||||
"border": DARK_GRAY,
|
||||
},
|
||||
}
|
||||
font_color = "var(--node-text-color)"
|
||||
border_width = 3
|
||||
font_color = WHITE
|
||||
border_width = 2
|
||||
|
||||
title_parts: list[str] = []
|
||||
|
||||
@@ -327,34 +215,25 @@ def render_interactive(
|
||||
bg_color = color_config["background"]
|
||||
border_color = color_config["border"]
|
||||
|
||||
position_data = node_positions.get(name, {"level": 0, "x": 0, "y": 0})
|
||||
|
||||
node_data: dict[str, Any] = {
|
||||
"id": name,
|
||||
"label": name,
|
||||
"title": "".join(title_parts),
|
||||
"shape": "custom",
|
||||
"size": 30,
|
||||
"level": position_data["level"],
|
||||
"nodeStyle": {
|
||||
"name": name,
|
||||
"bgColor": bg_color,
|
||||
"borderColor": border_color,
|
||||
"borderWidth": border_width,
|
||||
"fontColor": font_color,
|
||||
},
|
||||
"opacity": 1.0,
|
||||
"glowSize": 0,
|
||||
"glowColor": None,
|
||||
}
|
||||
|
||||
# Add x,y only for graphs with 3-4 nodes
|
||||
total_nodes = len(dag["nodes"])
|
||||
if 3 <= total_nodes <= 4:
|
||||
node_data["x"] = position_data["x"]
|
||||
node_data["y"] = position_data["y"]
|
||||
|
||||
nodes_list.append(node_data)
|
||||
nodes_list.append(
|
||||
{
|
||||
"id": name,
|
||||
"label": name,
|
||||
"title": "".join(title_parts),
|
||||
"shape": "custom",
|
||||
"size": 30,
|
||||
"nodeStyle": {
|
||||
"name": name,
|
||||
"bgColor": bg_color,
|
||||
"borderColor": border_color,
|
||||
"borderWidth": border_width,
|
||||
"fontColor": font_color,
|
||||
},
|
||||
"opacity": 1.0,
|
||||
"glowSize": 0,
|
||||
"glowColor": None,
|
||||
}
|
||||
)
|
||||
|
||||
execution_paths: int = calculate_execution_paths(dag)
|
||||
|
||||
@@ -367,8 +246,6 @@ def render_interactive(
|
||||
if edge["is_router_path"]:
|
||||
edge_color = CREWAI_ORANGE
|
||||
edge_dashes = [15, 10]
|
||||
if "router_path_label" in edge:
|
||||
edge_label = edge["router_path_label"]
|
||||
elif edge["condition_type"] == "AND":
|
||||
edge_label = "AND"
|
||||
edge_color = CREWAI_ORANGE
|
||||
|
||||
@@ -10,7 +10,6 @@ class NodeMetadata(TypedDict, total=False):
|
||||
is_router: bool
|
||||
router_paths: list[str]
|
||||
condition_type: str | None
|
||||
trigger_condition_type: str | None
|
||||
trigger_methods: list[str]
|
||||
trigger_condition: dict[str, Any] | None
|
||||
method_signature: dict[str, Any]
|
||||
@@ -23,14 +22,13 @@ class NodeMetadata(TypedDict, total=False):
|
||||
class_line_number: int
|
||||
|
||||
|
||||
class StructureEdge(TypedDict, total=False):
|
||||
class StructureEdge(TypedDict):
|
||||
"""Represents a connection in the flow structure."""
|
||||
|
||||
source: str
|
||||
target: str
|
||||
condition_type: str | None
|
||||
is_router_path: bool
|
||||
router_path_label: str
|
||||
|
||||
|
||||
class FlowStructure(TypedDict):
|
||||
|
||||
@@ -1,7 +1,6 @@
|
||||
import asyncio
|
||||
from collections.abc import Callable
|
||||
import inspect
|
||||
import json
|
||||
from typing import (
|
||||
Any,
|
||||
Literal,
|
||||
@@ -59,11 +58,7 @@ from crewai.utilities.agent_utils import (
|
||||
process_llm_response,
|
||||
render_text_description_and_args,
|
||||
)
|
||||
from crewai.utilities.converter import (
|
||||
Converter,
|
||||
ConverterError,
|
||||
generate_model_description,
|
||||
)
|
||||
from crewai.utilities.converter import generate_model_description
|
||||
from crewai.utilities.guardrail import process_guardrail
|
||||
from crewai.utilities.guardrail_types import GuardrailCallable, GuardrailType
|
||||
from crewai.utilities.i18n import I18N, get_i18n
|
||||
@@ -246,11 +241,7 @@ class LiteAgent(FlowTrackable, BaseModel):
|
||||
"""Return the original role for compatibility with tool interfaces."""
|
||||
return self.role
|
||||
|
||||
def kickoff(
|
||||
self,
|
||||
messages: str | list[LLMMessage],
|
||||
response_format: type[BaseModel] | None = None,
|
||||
) -> LiteAgentOutput:
|
||||
def kickoff(self, messages: str | list[LLMMessage]) -> LiteAgentOutput:
|
||||
"""
|
||||
Execute the agent with the given messages.
|
||||
|
||||
@@ -258,8 +249,6 @@ class LiteAgent(FlowTrackable, BaseModel):
|
||||
messages: Either a string query or a list of message dictionaries.
|
||||
If a string is provided, it will be converted to a user message.
|
||||
If a list is provided, each dict should have 'role' and 'content' keys.
|
||||
response_format: Optional Pydantic model for structured output. If provided,
|
||||
overrides self.response_format for this execution.
|
||||
|
||||
Returns:
|
||||
LiteAgentOutput: The result of the agent execution.
|
||||
@@ -280,13 +269,9 @@ class LiteAgent(FlowTrackable, BaseModel):
|
||||
self.tools_results = []
|
||||
|
||||
# Format messages for the LLM
|
||||
self._messages = self._format_messages(
|
||||
messages, response_format=response_format
|
||||
)
|
||||
self._messages = self._format_messages(messages)
|
||||
|
||||
return self._execute_core(
|
||||
agent_info=agent_info, response_format=response_format
|
||||
)
|
||||
return self._execute_core(agent_info=agent_info)
|
||||
|
||||
except Exception as e:
|
||||
self._printer.print(
|
||||
@@ -304,9 +289,7 @@ class LiteAgent(FlowTrackable, BaseModel):
|
||||
)
|
||||
raise e
|
||||
|
||||
def _execute_core(
|
||||
self, agent_info: dict[str, Any], response_format: type[BaseModel] | None = None
|
||||
) -> LiteAgentOutput:
|
||||
def _execute_core(self, agent_info: dict[str, Any]) -> LiteAgentOutput:
|
||||
# Emit event for agent execution start
|
||||
crewai_event_bus.emit(
|
||||
self,
|
||||
@@ -320,29 +303,15 @@ class LiteAgent(FlowTrackable, BaseModel):
|
||||
# Execute the agent using invoke loop
|
||||
agent_finish = self._invoke_loop()
|
||||
formatted_result: BaseModel | None = None
|
||||
|
||||
active_response_format = response_format or self.response_format
|
||||
if active_response_format:
|
||||
if self.response_format:
|
||||
try:
|
||||
model_schema = generate_model_description(active_response_format)
|
||||
schema = json.dumps(model_schema, indent=2)
|
||||
instructions = self.i18n.slice("formatted_task_instructions").format(
|
||||
output_format=schema
|
||||
)
|
||||
|
||||
converter = Converter(
|
||||
llm=self.llm,
|
||||
text=agent_finish.output,
|
||||
model=active_response_format,
|
||||
instructions=instructions,
|
||||
)
|
||||
|
||||
result = converter.to_pydantic()
|
||||
# Cast to BaseModel to ensure type safety
|
||||
result = self.response_format.model_validate_json(agent_finish.output)
|
||||
if isinstance(result, BaseModel):
|
||||
formatted_result = result
|
||||
except ConverterError as e:
|
||||
except Exception as e:
|
||||
self._printer.print(
|
||||
content=f"Failed to parse output into response format after retries: {e.message}",
|
||||
content=f"Failed to parse output into response format: {e!s}",
|
||||
color="yellow",
|
||||
)
|
||||
|
||||
@@ -431,14 +400,8 @@ class LiteAgent(FlowTrackable, BaseModel):
|
||||
"""
|
||||
return await asyncio.to_thread(self.kickoff, messages)
|
||||
|
||||
def _get_default_system_prompt(
|
||||
self, response_format: type[BaseModel] | None = None
|
||||
) -> str:
|
||||
"""Get the default system prompt for the agent.
|
||||
|
||||
Args:
|
||||
response_format: Optional response format to use instead of self.response_format
|
||||
"""
|
||||
def _get_default_system_prompt(self) -> str:
|
||||
"""Get the default system prompt for the agent."""
|
||||
base_prompt = ""
|
||||
if self._parsed_tools:
|
||||
# Use the prompt template for agents with tools
|
||||
@@ -459,31 +422,21 @@ class LiteAgent(FlowTrackable, BaseModel):
|
||||
goal=self.goal,
|
||||
)
|
||||
|
||||
active_response_format = response_format or self.response_format
|
||||
if active_response_format:
|
||||
model_description = generate_model_description(active_response_format)
|
||||
schema_json = json.dumps(model_description, indent=2)
|
||||
# Add response format instructions if specified
|
||||
if self.response_format:
|
||||
schema = generate_model_description(self.response_format)
|
||||
base_prompt += self.i18n.slice("lite_agent_response_format").format(
|
||||
response_format=schema_json
|
||||
response_format=schema
|
||||
)
|
||||
|
||||
return base_prompt
|
||||
|
||||
def _format_messages(
|
||||
self,
|
||||
messages: str | list[LLMMessage],
|
||||
response_format: type[BaseModel] | None = None,
|
||||
) -> list[LLMMessage]:
|
||||
"""Format messages for the LLM.
|
||||
|
||||
Args:
|
||||
messages: Input messages to format
|
||||
response_format: Optional response format to use instead of self.response_format
|
||||
"""
|
||||
def _format_messages(self, messages: str | list[LLMMessage]) -> list[LLMMessage]:
|
||||
"""Format messages for the LLM."""
|
||||
if isinstance(messages, str):
|
||||
messages = [{"role": "user", "content": messages}]
|
||||
|
||||
system_prompt = self._get_default_system_prompt(response_format=response_format)
|
||||
system_prompt = self._get_default_system_prompt()
|
||||
|
||||
# Add system message at the beginning
|
||||
formatted_messages: list[LLMMessage] = [
|
||||
@@ -553,10 +506,6 @@ class LiteAgent(FlowTrackable, BaseModel):
|
||||
|
||||
self._append_message(formatted_answer.text, role="assistant")
|
||||
except OutputParserError as e: # noqa: PERF203
|
||||
self._printer.print(
|
||||
content="Failed to parse LLM output. Retrying...",
|
||||
color="yellow",
|
||||
)
|
||||
formatted_answer = handle_output_parser_exception(
|
||||
e=e,
|
||||
messages=self._messages,
|
||||
|
||||
@@ -20,7 +20,6 @@ from typing import (
|
||||
)
|
||||
|
||||
from dotenv import load_dotenv
|
||||
import httpx
|
||||
from pydantic import BaseModel, Field
|
||||
from typing_extensions import Self
|
||||
|
||||
@@ -38,13 +37,6 @@ from crewai.events.types.tool_usage_events import (
|
||||
ToolUsageStartedEvent,
|
||||
)
|
||||
from crewai.llms.base_llm import BaseLLM
|
||||
from crewai.llms.constants import (
|
||||
ANTHROPIC_MODELS,
|
||||
AZURE_MODELS,
|
||||
BEDROCK_MODELS,
|
||||
GEMINI_MODELS,
|
||||
OPENAI_MODELS,
|
||||
)
|
||||
from crewai.utilities import InternalInstructor
|
||||
from crewai.utilities.exceptions.context_window_exceeding_exception import (
|
||||
LLMContextLengthExceededError,
|
||||
@@ -61,7 +53,6 @@ if TYPE_CHECKING:
|
||||
from litellm.utils import supports_response_schema
|
||||
|
||||
from crewai.agent.core import Agent
|
||||
from crewai.llms.hooks.base import BaseInterceptor
|
||||
from crewai.task import Task
|
||||
from crewai.tools.base_tool import BaseTool
|
||||
from crewai.utilities.types import LLMMessage
|
||||
@@ -330,67 +321,19 @@ class LLM(BaseLLM):
|
||||
completion_cost: float | None = None
|
||||
|
||||
def __new__(cls, model: str, is_litellm: bool = False, **kwargs: Any) -> LLM:
|
||||
"""Factory method that routes to native SDK or falls back to LiteLLM.
|
||||
|
||||
Routing priority:
|
||||
1. If 'provider' kwarg is present, use that provider with constants
|
||||
2. If only 'model' kwarg, use constants to infer provider
|
||||
3. If "/" in model name:
|
||||
- Check if prefix is a native provider (openai/anthropic/azure/bedrock/gemini)
|
||||
- If yes, validate model against constants
|
||||
- If valid, route to native SDK; otherwise route to LiteLLM
|
||||
"""
|
||||
"""Factory method that routes to native SDK or falls back to LiteLLM."""
|
||||
if not model or not isinstance(model, str):
|
||||
raise ValueError("Model must be a non-empty string")
|
||||
|
||||
explicit_provider = kwargs.get("provider")
|
||||
provider = model.partition("/")[0] if "/" in model else "openai"
|
||||
|
||||
if explicit_provider:
|
||||
provider = explicit_provider
|
||||
use_native = True
|
||||
model_string = model
|
||||
elif "/" in model:
|
||||
prefix, _, model_part = model.partition("/")
|
||||
|
||||
provider_mapping = {
|
||||
"openai": "openai",
|
||||
"anthropic": "anthropic",
|
||||
"claude": "anthropic",
|
||||
"azure": "azure",
|
||||
"azure_openai": "azure",
|
||||
"google": "gemini",
|
||||
"gemini": "gemini",
|
||||
"bedrock": "bedrock",
|
||||
"aws": "bedrock",
|
||||
}
|
||||
|
||||
canonical_provider = provider_mapping.get(prefix.lower())
|
||||
|
||||
if canonical_provider and cls._validate_model_in_constants(
|
||||
model_part, canonical_provider
|
||||
):
|
||||
provider = canonical_provider
|
||||
use_native = True
|
||||
model_string = model_part
|
||||
else:
|
||||
provider = prefix
|
||||
use_native = False
|
||||
model_string = model_part
|
||||
else:
|
||||
provider = cls._infer_provider_from_model(model)
|
||||
use_native = True
|
||||
model_string = model
|
||||
|
||||
native_class = cls._get_native_provider(provider) if use_native else None
|
||||
native_class = cls._get_native_provider(provider)
|
||||
if native_class and not is_litellm and provider in SUPPORTED_NATIVE_PROVIDERS:
|
||||
try:
|
||||
# Remove 'provider' from kwargs if it exists to avoid duplicate keyword argument
|
||||
kwargs_copy = {k: v for k, v in kwargs.items() if k != 'provider'}
|
||||
model_string = model.partition("/")[2] if "/" in model else model
|
||||
return cast(
|
||||
Self, native_class(model=model_string, provider=provider, **kwargs_copy)
|
||||
Self, native_class(model=model_string, provider=provider, **kwargs)
|
||||
)
|
||||
except NotImplementedError:
|
||||
raise
|
||||
except Exception as e:
|
||||
raise ImportError(f"Error importing native provider: {e}") from e
|
||||
|
||||
@@ -404,63 +347,6 @@ class LLM(BaseLLM):
|
||||
instance.is_litellm = True
|
||||
return instance
|
||||
|
||||
@classmethod
|
||||
def _validate_model_in_constants(cls, model: str, provider: str) -> bool:
|
||||
"""Validate if a model name exists in the provider's constants.
|
||||
|
||||
Args:
|
||||
model: The model name to validate
|
||||
provider: The provider to check against (canonical name)
|
||||
|
||||
Returns:
|
||||
True if the model exists in the provider's constants, False otherwise
|
||||
"""
|
||||
if provider == "openai":
|
||||
return model in OPENAI_MODELS
|
||||
|
||||
if provider == "anthropic" or provider == "claude":
|
||||
return model in ANTHROPIC_MODELS
|
||||
|
||||
if provider == "gemini":
|
||||
return model in GEMINI_MODELS
|
||||
|
||||
if provider == "bedrock":
|
||||
return model in BEDROCK_MODELS
|
||||
|
||||
if provider == "azure":
|
||||
# azure does not provide a list of available models, determine a better way to handle this
|
||||
return True
|
||||
|
||||
return False
|
||||
|
||||
@classmethod
|
||||
def _infer_provider_from_model(cls, model: str) -> str:
|
||||
"""Infer the provider from the model name.
|
||||
|
||||
Args:
|
||||
model: The model name without provider prefix
|
||||
|
||||
Returns:
|
||||
The inferred provider name, defaults to "openai"
|
||||
"""
|
||||
|
||||
if model in OPENAI_MODELS:
|
||||
return "openai"
|
||||
|
||||
if model in ANTHROPIC_MODELS:
|
||||
return "anthropic"
|
||||
|
||||
if model in GEMINI_MODELS:
|
||||
return "gemini"
|
||||
|
||||
if model in BEDROCK_MODELS:
|
||||
return "bedrock"
|
||||
|
||||
if model in AZURE_MODELS:
|
||||
return "azure"
|
||||
|
||||
return "openai"
|
||||
|
||||
@classmethod
|
||||
def _get_native_provider(cls, provider: str) -> type | None:
|
||||
"""Get native provider class if available."""
|
||||
@@ -517,7 +403,6 @@ class LLM(BaseLLM):
|
||||
callbacks: list[Any] | None = None,
|
||||
reasoning_effort: Literal["none", "low", "medium", "high"] | None = None,
|
||||
stream: bool = False,
|
||||
interceptor: BaseInterceptor[httpx.Request, httpx.Response] | None = None,
|
||||
**kwargs: Any,
|
||||
) -> None:
|
||||
"""Initialize LLM instance.
|
||||
@@ -557,7 +442,6 @@ class LLM(BaseLLM):
|
||||
self.additional_params = kwargs
|
||||
self.is_anthropic = self._is_anthropic_model(model)
|
||||
self.stream = stream
|
||||
self.interceptor = interceptor
|
||||
|
||||
litellm.drop_params = True
|
||||
|
||||
|
||||
@@ -1,558 +0,0 @@
|
||||
from typing import Literal, TypeAlias
|
||||
|
||||
|
||||
OpenAIModels: TypeAlias = Literal[
|
||||
"gpt-3.5-turbo",
|
||||
"gpt-3.5-turbo-0125",
|
||||
"gpt-3.5-turbo-0301",
|
||||
"gpt-3.5-turbo-0613",
|
||||
"gpt-3.5-turbo-1106",
|
||||
"gpt-3.5-turbo-16k",
|
||||
"gpt-3.5-turbo-16k-0613",
|
||||
"gpt-3.5-turbo-instruct",
|
||||
"gpt-3.5-turbo-instruct-0914",
|
||||
"gpt-4",
|
||||
"gpt-4-0125-preview",
|
||||
"gpt-4-0314",
|
||||
"gpt-4-0613",
|
||||
"gpt-4-1106-preview",
|
||||
"gpt-4-32k",
|
||||
"gpt-4-32k-0314",
|
||||
"gpt-4-32k-0613",
|
||||
"gpt-4-turbo",
|
||||
"gpt-4-turbo-2024-04-09",
|
||||
"gpt-4-turbo-preview",
|
||||
"gpt-4-vision-preview",
|
||||
"gpt-4.1",
|
||||
"gpt-4.1-2025-04-14",
|
||||
"gpt-4.1-mini",
|
||||
"gpt-4.1-mini-2025-04-14",
|
||||
"gpt-4.1-nano",
|
||||
"gpt-4.1-nano-2025-04-14",
|
||||
"gpt-4o",
|
||||
"gpt-4o-2024-05-13",
|
||||
"gpt-4o-2024-08-06",
|
||||
"gpt-4o-2024-11-20",
|
||||
"gpt-4o-audio-preview",
|
||||
"gpt-4o-audio-preview-2024-10-01",
|
||||
"gpt-4o-audio-preview-2024-12-17",
|
||||
"gpt-4o-audio-preview-2025-06-03",
|
||||
"gpt-4o-mini",
|
||||
"gpt-4o-mini-2024-07-18",
|
||||
"gpt-4o-mini-audio-preview",
|
||||
"gpt-4o-mini-audio-preview-2024-12-17",
|
||||
"gpt-4o-mini-realtime-preview",
|
||||
"gpt-4o-mini-realtime-preview-2024-12-17",
|
||||
"gpt-4o-mini-search-preview",
|
||||
"gpt-4o-mini-search-preview-2025-03-11",
|
||||
"gpt-4o-mini-transcribe",
|
||||
"gpt-4o-mini-tts",
|
||||
"gpt-4o-realtime-preview",
|
||||
"gpt-4o-realtime-preview-2024-10-01",
|
||||
"gpt-4o-realtime-preview-2024-12-17",
|
||||
"gpt-4o-realtime-preview-2025-06-03",
|
||||
"gpt-4o-search-preview",
|
||||
"gpt-4o-search-preview-2025-03-11",
|
||||
"gpt-4o-transcribe",
|
||||
"gpt-4o-transcribe-diarize",
|
||||
"gpt-5",
|
||||
"gpt-5-2025-08-07",
|
||||
"gpt-5-chat",
|
||||
"gpt-5-chat-latest",
|
||||
"gpt-5-codex",
|
||||
"gpt-5-mini",
|
||||
"gpt-5-mini-2025-08-07",
|
||||
"gpt-5-nano",
|
||||
"gpt-5-nano-2025-08-07",
|
||||
"gpt-5-pro",
|
||||
"gpt-5-pro-2025-10-06",
|
||||
"gpt-5-search-api",
|
||||
"gpt-5-search-api-2025-10-14",
|
||||
"gpt-audio",
|
||||
"gpt-audio-2025-08-28",
|
||||
"gpt-audio-mini",
|
||||
"gpt-audio-mini-2025-10-06",
|
||||
"gpt-image-1",
|
||||
"gpt-image-1-mini",
|
||||
"gpt-realtime",
|
||||
"gpt-realtime-2025-08-28",
|
||||
"gpt-realtime-mini",
|
||||
"gpt-realtime-mini-2025-10-06",
|
||||
"o1",
|
||||
"o1-preview",
|
||||
"o1-2024-12-17",
|
||||
"o1-mini",
|
||||
"o1-mini-2024-09-12",
|
||||
"o1-pro",
|
||||
"o1-pro-2025-03-19",
|
||||
"o3-mini",
|
||||
"o3",
|
||||
"o4-mini",
|
||||
"whisper-1",
|
||||
]
|
||||
OPENAI_MODELS: list[OpenAIModels] = [
|
||||
"gpt-3.5-turbo",
|
||||
"gpt-3.5-turbo-0125",
|
||||
"gpt-3.5-turbo-0301",
|
||||
"gpt-3.5-turbo-0613",
|
||||
"gpt-3.5-turbo-1106",
|
||||
"gpt-3.5-turbo-16k",
|
||||
"gpt-3.5-turbo-16k-0613",
|
||||
"gpt-3.5-turbo-instruct",
|
||||
"gpt-3.5-turbo-instruct-0914",
|
||||
"gpt-4",
|
||||
"gpt-4-0125-preview",
|
||||
"gpt-4-0314",
|
||||
"gpt-4-0613",
|
||||
"gpt-4-1106-preview",
|
||||
"gpt-4-32k",
|
||||
"gpt-4-32k-0314",
|
||||
"gpt-4-32k-0613",
|
||||
"gpt-4-turbo",
|
||||
"gpt-4-turbo-2024-04-09",
|
||||
"gpt-4-turbo-preview",
|
||||
"gpt-4-vision-preview",
|
||||
"gpt-4.1",
|
||||
"gpt-4.1-2025-04-14",
|
||||
"gpt-4.1-mini",
|
||||
"gpt-4.1-mini-2025-04-14",
|
||||
"gpt-4.1-nano",
|
||||
"gpt-4.1-nano-2025-04-14",
|
||||
"gpt-4o",
|
||||
"gpt-4o-2024-05-13",
|
||||
"gpt-4o-2024-08-06",
|
||||
"gpt-4o-2024-11-20",
|
||||
"gpt-4o-audio-preview",
|
||||
"gpt-4o-audio-preview-2024-10-01",
|
||||
"gpt-4o-audio-preview-2024-12-17",
|
||||
"gpt-4o-audio-preview-2025-06-03",
|
||||
"gpt-4o-mini",
|
||||
"gpt-4o-mini-2024-07-18",
|
||||
"gpt-4o-mini-audio-preview",
|
||||
"gpt-4o-mini-audio-preview-2024-12-17",
|
||||
"gpt-4o-mini-realtime-preview",
|
||||
"gpt-4o-mini-realtime-preview-2024-12-17",
|
||||
"gpt-4o-mini-search-preview",
|
||||
"gpt-4o-mini-search-preview-2025-03-11",
|
||||
"gpt-4o-mini-transcribe",
|
||||
"gpt-4o-mini-tts",
|
||||
"gpt-4o-realtime-preview",
|
||||
"gpt-4o-realtime-preview-2024-10-01",
|
||||
"gpt-4o-realtime-preview-2024-12-17",
|
||||
"gpt-4o-realtime-preview-2025-06-03",
|
||||
"gpt-4o-search-preview",
|
||||
"gpt-4o-search-preview-2025-03-11",
|
||||
"gpt-4o-transcribe",
|
||||
"gpt-4o-transcribe-diarize",
|
||||
"gpt-5",
|
||||
"gpt-5-2025-08-07",
|
||||
"gpt-5-chat",
|
||||
"gpt-5-chat-latest",
|
||||
"gpt-5-codex",
|
||||
"gpt-5-mini",
|
||||
"gpt-5-mini-2025-08-07",
|
||||
"gpt-5-nano",
|
||||
"gpt-5-nano-2025-08-07",
|
||||
"gpt-5-pro",
|
||||
"gpt-5-pro-2025-10-06",
|
||||
"gpt-5-search-api",
|
||||
"gpt-5-search-api-2025-10-14",
|
||||
"gpt-audio",
|
||||
"gpt-audio-2025-08-28",
|
||||
"gpt-audio-mini",
|
||||
"gpt-audio-mini-2025-10-06",
|
||||
"gpt-image-1",
|
||||
"gpt-image-1-mini",
|
||||
"gpt-realtime",
|
||||
"gpt-realtime-2025-08-28",
|
||||
"gpt-realtime-mini",
|
||||
"gpt-realtime-mini-2025-10-06",
|
||||
"o1",
|
||||
"o1-preview",
|
||||
"o1-2024-12-17",
|
||||
"o1-mini",
|
||||
"o1-mini-2024-09-12",
|
||||
"o1-pro",
|
||||
"o1-pro-2025-03-19",
|
||||
"o3-mini",
|
||||
"o3",
|
||||
"o4-mini",
|
||||
"whisper-1",
|
||||
]
|
||||
|
||||
|
||||
AnthropicModels: TypeAlias = Literal[
|
||||
"claude-3-7-sonnet-latest",
|
||||
"claude-3-7-sonnet-20250219",
|
||||
"claude-3-5-haiku-latest",
|
||||
"claude-3-5-haiku-20241022",
|
||||
"claude-haiku-4-5",
|
||||
"claude-haiku-4-5-20251001",
|
||||
"claude-sonnet-4-20250514",
|
||||
"claude-sonnet-4-0",
|
||||
"claude-4-sonnet-20250514",
|
||||
"claude-sonnet-4-5",
|
||||
"claude-sonnet-4-5-20250929",
|
||||
"claude-3-5-sonnet-latest",
|
||||
"claude-3-5-sonnet-20241022",
|
||||
"claude-3-5-sonnet-20240620",
|
||||
"claude-opus-4-0",
|
||||
"claude-opus-4-20250514",
|
||||
"claude-4-opus-20250514",
|
||||
"claude-opus-4-1",
|
||||
"claude-opus-4-1-20250805",
|
||||
"claude-3-opus-latest",
|
||||
"claude-3-opus-20240229",
|
||||
"claude-3-sonnet-20240229",
|
||||
"claude-3-haiku-latest",
|
||||
"claude-3-haiku-20240307",
|
||||
]
|
||||
ANTHROPIC_MODELS: list[AnthropicModels] = [
|
||||
"claude-3-7-sonnet-latest",
|
||||
"claude-3-7-sonnet-20250219",
|
||||
"claude-3-5-haiku-latest",
|
||||
"claude-3-5-haiku-20241022",
|
||||
"claude-haiku-4-5",
|
||||
"claude-haiku-4-5-20251001",
|
||||
"claude-sonnet-4-20250514",
|
||||
"claude-sonnet-4-0",
|
||||
"claude-4-sonnet-20250514",
|
||||
"claude-sonnet-4-5",
|
||||
"claude-sonnet-4-5-20250929",
|
||||
"claude-3-5-sonnet-latest",
|
||||
"claude-3-5-sonnet-20241022",
|
||||
"claude-3-5-sonnet-20240620",
|
||||
"claude-opus-4-0",
|
||||
"claude-opus-4-20250514",
|
||||
"claude-4-opus-20250514",
|
||||
"claude-opus-4-1",
|
||||
"claude-opus-4-1-20250805",
|
||||
"claude-3-opus-latest",
|
||||
"claude-3-opus-20240229",
|
||||
"claude-3-sonnet-20240229",
|
||||
"claude-3-haiku-latest",
|
||||
"claude-3-haiku-20240307",
|
||||
]
|
||||
|
||||
GeminiModels: TypeAlias = Literal[
|
||||
"gemini-2.5-pro",
|
||||
"gemini-2.5-pro-preview-03-25",
|
||||
"gemini-2.5-pro-preview-05-06",
|
||||
"gemini-2.5-pro-preview-06-05",
|
||||
"gemini-2.5-flash",
|
||||
"gemini-2.5-flash-preview-05-20",
|
||||
"gemini-2.5-flash-preview-04-17",
|
||||
"gemini-2.5-flash-image",
|
||||
"gemini-2.5-flash-image-preview",
|
||||
"gemini-2.5-flash-lite",
|
||||
"gemini-2.5-flash-lite-preview-06-17",
|
||||
"gemini-2.5-flash-preview-09-2025",
|
||||
"gemini-2.5-flash-lite-preview-09-2025",
|
||||
"gemini-2.5-flash-preview-tts",
|
||||
"gemini-2.5-pro-preview-tts",
|
||||
"gemini-2.5-computer-use-preview-10-2025",
|
||||
"gemini-2.0-flash",
|
||||
"gemini-2.0-flash-001",
|
||||
"gemini-2.0-flash-exp",
|
||||
"gemini-2.0-flash-exp-image-generation",
|
||||
"gemini-2.0-flash-lite",
|
||||
"gemini-2.0-flash-lite-001",
|
||||
"gemini-2.0-flash-lite-preview",
|
||||
"gemini-2.0-flash-lite-preview-02-05",
|
||||
"gemini-2.0-flash-preview-image-generation",
|
||||
"gemini-2.0-flash-thinking-exp",
|
||||
"gemini-2.0-flash-thinking-exp-01-21",
|
||||
"gemini-2.0-flash-thinking-exp-1219",
|
||||
"gemini-2.0-pro-exp",
|
||||
"gemini-2.0-pro-exp-02-05",
|
||||
"gemini-exp-1206",
|
||||
"gemini-1.5-pro",
|
||||
"gemini-1.5-flash",
|
||||
"gemini-1.5-flash-8b",
|
||||
"gemini-flash-latest",
|
||||
"gemini-flash-lite-latest",
|
||||
"gemini-pro-latest",
|
||||
"gemini-2.0-flash-live-001",
|
||||
"gemini-live-2.5-flash-preview",
|
||||
"gemini-2.5-flash-live-preview",
|
||||
"gemini-robotics-er-1.5-preview",
|
||||
"gemini-gemma-2-27b-it",
|
||||
"gemini-gemma-2-9b-it",
|
||||
"gemma-3-1b-it",
|
||||
"gemma-3-4b-it",
|
||||
"gemma-3-12b-it",
|
||||
"gemma-3-27b-it",
|
||||
"gemma-3n-e2b-it",
|
||||
"gemma-3n-e4b-it",
|
||||
"learnlm-2.0-flash-experimental",
|
||||
]
|
||||
GEMINI_MODELS: list[GeminiModels] = [
|
||||
"gemini-2.5-pro",
|
||||
"gemini-2.5-pro-preview-03-25",
|
||||
"gemini-2.5-pro-preview-05-06",
|
||||
"gemini-2.5-pro-preview-06-05",
|
||||
"gemini-2.5-flash",
|
||||
"gemini-2.5-flash-preview-05-20",
|
||||
"gemini-2.5-flash-preview-04-17",
|
||||
"gemini-2.5-flash-image",
|
||||
"gemini-2.5-flash-image-preview",
|
||||
"gemini-2.5-flash-lite",
|
||||
"gemini-2.5-flash-lite-preview-06-17",
|
||||
"gemini-2.5-flash-preview-09-2025",
|
||||
"gemini-2.5-flash-lite-preview-09-2025",
|
||||
"gemini-2.5-flash-preview-tts",
|
||||
"gemini-2.5-pro-preview-tts",
|
||||
"gemini-2.5-computer-use-preview-10-2025",
|
||||
"gemini-2.0-flash",
|
||||
"gemini-2.0-flash-001",
|
||||
"gemini-2.0-flash-exp",
|
||||
"gemini-2.0-flash-exp-image-generation",
|
||||
"gemini-2.0-flash-lite",
|
||||
"gemini-2.0-flash-lite-001",
|
||||
"gemini-2.0-flash-lite-preview",
|
||||
"gemini-2.0-flash-lite-preview-02-05",
|
||||
"gemini-2.0-flash-preview-image-generation",
|
||||
"gemini-2.0-flash-thinking-exp",
|
||||
"gemini-2.0-flash-thinking-exp-01-21",
|
||||
"gemini-2.0-flash-thinking-exp-1219",
|
||||
"gemini-2.0-pro-exp",
|
||||
"gemini-2.0-pro-exp-02-05",
|
||||
"gemini-exp-1206",
|
||||
"gemini-1.5-pro",
|
||||
"gemini-1.5-flash",
|
||||
"gemini-1.5-flash-8b",
|
||||
"gemini-flash-latest",
|
||||
"gemini-flash-lite-latest",
|
||||
"gemini-pro-latest",
|
||||
"gemini-2.0-flash-live-001",
|
||||
"gemini-live-2.5-flash-preview",
|
||||
"gemini-2.5-flash-live-preview",
|
||||
"gemini-robotics-er-1.5-preview",
|
||||
"gemini-gemma-2-27b-it",
|
||||
"gemini-gemma-2-9b-it",
|
||||
"gemma-3-1b-it",
|
||||
"gemma-3-4b-it",
|
||||
"gemma-3-12b-it",
|
||||
"gemma-3-27b-it",
|
||||
"gemma-3n-e2b-it",
|
||||
"gemma-3n-e4b-it",
|
||||
"learnlm-2.0-flash-experimental",
|
||||
]
|
||||
|
||||
|
||||
AzureModels: TypeAlias = Literal[
|
||||
"gpt-3.5-turbo",
|
||||
"gpt-3.5-turbo-0301",
|
||||
"gpt-3.5-turbo-0613",
|
||||
"gpt-3.5-turbo-16k",
|
||||
"gpt-3.5-turbo-16k-0613",
|
||||
"gpt-35-turbo",
|
||||
"gpt-35-turbo-0125",
|
||||
"gpt-35-turbo-1106",
|
||||
"gpt-35-turbo-16k-0613",
|
||||
"gpt-35-turbo-instruct-0914",
|
||||
"gpt-4",
|
||||
"gpt-4-0314",
|
||||
"gpt-4-0613",
|
||||
"gpt-4-1106-preview",
|
||||
"gpt-4-0125-preview",
|
||||
"gpt-4-32k",
|
||||
"gpt-4-32k-0314",
|
||||
"gpt-4-32k-0613",
|
||||
"gpt-4-turbo",
|
||||
"gpt-4-turbo-2024-04-09",
|
||||
"gpt-4-vision",
|
||||
"gpt-4o",
|
||||
"gpt-4o-2024-05-13",
|
||||
"gpt-4o-2024-08-06",
|
||||
"gpt-4o-2024-11-20",
|
||||
"gpt-4o-mini",
|
||||
"gpt-5",
|
||||
"o1",
|
||||
"o1-mini",
|
||||
"o1-preview",
|
||||
"o3-mini",
|
||||
"o3",
|
||||
"o4-mini",
|
||||
]
|
||||
AZURE_MODELS: list[AzureModels] = [
|
||||
"gpt-3.5-turbo",
|
||||
"gpt-3.5-turbo-0301",
|
||||
"gpt-3.5-turbo-0613",
|
||||
"gpt-3.5-turbo-16k",
|
||||
"gpt-3.5-turbo-16k-0613",
|
||||
"gpt-35-turbo",
|
||||
"gpt-35-turbo-0125",
|
||||
"gpt-35-turbo-1106",
|
||||
"gpt-35-turbo-16k-0613",
|
||||
"gpt-35-turbo-instruct-0914",
|
||||
"gpt-4",
|
||||
"gpt-4-0314",
|
||||
"gpt-4-0613",
|
||||
"gpt-4-1106-preview",
|
||||
"gpt-4-0125-preview",
|
||||
"gpt-4-32k",
|
||||
"gpt-4-32k-0314",
|
||||
"gpt-4-32k-0613",
|
||||
"gpt-4-turbo",
|
||||
"gpt-4-turbo-2024-04-09",
|
||||
"gpt-4-vision",
|
||||
"gpt-4o",
|
||||
"gpt-4o-2024-05-13",
|
||||
"gpt-4o-2024-08-06",
|
||||
"gpt-4o-2024-11-20",
|
||||
"gpt-4o-mini",
|
||||
"gpt-5",
|
||||
"o1",
|
||||
"o1-mini",
|
||||
"o1-preview",
|
||||
"o3-mini",
|
||||
"o3",
|
||||
"o4-mini",
|
||||
]
|
||||
|
||||
|
||||
BedrockModels: TypeAlias = Literal[
|
||||
"ai21.jamba-1-5-large-v1:0",
|
||||
"ai21.jamba-1-5-mini-v1:0",
|
||||
"amazon.nova-lite-v1:0",
|
||||
"amazon.nova-lite-v1:0:24k",
|
||||
"amazon.nova-lite-v1:0:300k",
|
||||
"amazon.nova-micro-v1:0",
|
||||
"amazon.nova-micro-v1:0:128k",
|
||||
"amazon.nova-micro-v1:0:24k",
|
||||
"amazon.nova-premier-v1:0",
|
||||
"amazon.nova-premier-v1:0:1000k",
|
||||
"amazon.nova-premier-v1:0:20k",
|
||||
"amazon.nova-premier-v1:0:8k",
|
||||
"amazon.nova-premier-v1:0:mm",
|
||||
"amazon.nova-pro-v1:0",
|
||||
"amazon.nova-pro-v1:0:24k",
|
||||
"amazon.nova-pro-v1:0:300k",
|
||||
"amazon.titan-text-express-v1",
|
||||
"amazon.titan-text-express-v1:0:8k",
|
||||
"amazon.titan-text-lite-v1",
|
||||
"amazon.titan-text-lite-v1:0:4k",
|
||||
"amazon.titan-tg1-large",
|
||||
"anthropic.claude-3-5-haiku-20241022-v1:0",
|
||||
"anthropic.claude-3-5-sonnet-20240620-v1:0",
|
||||
"anthropic.claude-3-5-sonnet-20241022-v2:0",
|
||||
"anthropic.claude-3-7-sonnet-20250219-v1:0",
|
||||
"anthropic.claude-3-haiku-20240307-v1:0",
|
||||
"anthropic.claude-3-haiku-20240307-v1:0:200k",
|
||||
"anthropic.claude-3-haiku-20240307-v1:0:48k",
|
||||
"anthropic.claude-3-opus-20240229-v1:0",
|
||||
"anthropic.claude-3-opus-20240229-v1:0:12k",
|
||||
"anthropic.claude-3-opus-20240229-v1:0:200k",
|
||||
"anthropic.claude-3-opus-20240229-v1:0:28k",
|
||||
"anthropic.claude-3-sonnet-20240229-v1:0",
|
||||
"anthropic.claude-3-sonnet-20240229-v1:0:200k",
|
||||
"anthropic.claude-3-sonnet-20240229-v1:0:28k",
|
||||
"anthropic.claude-haiku-4-5-20251001-v1:0",
|
||||
"anthropic.claude-instant-v1:2:100k",
|
||||
"anthropic.claude-opus-4-1-20250805-v1:0",
|
||||
"anthropic.claude-opus-4-20250514-v1:0",
|
||||
"anthropic.claude-sonnet-4-20250514-v1:0",
|
||||
"anthropic.claude-sonnet-4-5-20250929-v1:0",
|
||||
"anthropic.claude-v2:0:100k",
|
||||
"anthropic.claude-v2:0:18k",
|
||||
"anthropic.claude-v2:1:18k",
|
||||
"anthropic.claude-v2:1:200k",
|
||||
"cohere.command-r-plus-v1:0",
|
||||
"cohere.command-r-v1:0",
|
||||
"cohere.rerank-v3-5:0",
|
||||
"deepseek.r1-v1:0",
|
||||
"meta.llama3-1-70b-instruct-v1:0",
|
||||
"meta.llama3-1-8b-instruct-v1:0",
|
||||
"meta.llama3-2-11b-instruct-v1:0",
|
||||
"meta.llama3-2-1b-instruct-v1:0",
|
||||
"meta.llama3-2-3b-instruct-v1:0",
|
||||
"meta.llama3-2-90b-instruct-v1:0",
|
||||
"meta.llama3-3-70b-instruct-v1:0",
|
||||
"meta.llama3-70b-instruct-v1:0",
|
||||
"meta.llama3-8b-instruct-v1:0",
|
||||
"meta.llama4-maverick-17b-instruct-v1:0",
|
||||
"meta.llama4-scout-17b-instruct-v1:0",
|
||||
"mistral.mistral-7b-instruct-v0:2",
|
||||
"mistral.mistral-large-2402-v1:0",
|
||||
"mistral.mistral-small-2402-v1:0",
|
||||
"mistral.mixtral-8x7b-instruct-v0:1",
|
||||
"mistral.pixtral-large-2502-v1:0",
|
||||
"openai.gpt-oss-120b-1:0",
|
||||
"openai.gpt-oss-20b-1:0",
|
||||
"qwen.qwen3-32b-v1:0",
|
||||
"qwen.qwen3-coder-30b-a3b-v1:0",
|
||||
"twelvelabs.pegasus-1-2-v1:0",
|
||||
]
|
||||
BEDROCK_MODELS: list[BedrockModels] = [
|
||||
"ai21.jamba-1-5-large-v1:0",
|
||||
"ai21.jamba-1-5-mini-v1:0",
|
||||
"amazon.nova-lite-v1:0",
|
||||
"amazon.nova-lite-v1:0:24k",
|
||||
"amazon.nova-lite-v1:0:300k",
|
||||
"amazon.nova-micro-v1:0",
|
||||
"amazon.nova-micro-v1:0:128k",
|
||||
"amazon.nova-micro-v1:0:24k",
|
||||
"amazon.nova-premier-v1:0",
|
||||
"amazon.nova-premier-v1:0:1000k",
|
||||
"amazon.nova-premier-v1:0:20k",
|
||||
"amazon.nova-premier-v1:0:8k",
|
||||
"amazon.nova-premier-v1:0:mm",
|
||||
"amazon.nova-pro-v1:0",
|
||||
"amazon.nova-pro-v1:0:24k",
|
||||
"amazon.nova-pro-v1:0:300k",
|
||||
"amazon.titan-text-express-v1",
|
||||
"amazon.titan-text-express-v1:0:8k",
|
||||
"amazon.titan-text-lite-v1",
|
||||
"amazon.titan-text-lite-v1:0:4k",
|
||||
"amazon.titan-tg1-large",
|
||||
"anthropic.claude-3-5-haiku-20241022-v1:0",
|
||||
"anthropic.claude-3-5-sonnet-20240620-v1:0",
|
||||
"anthropic.claude-3-5-sonnet-20241022-v2:0",
|
||||
"anthropic.claude-3-7-sonnet-20250219-v1:0",
|
||||
"anthropic.claude-3-haiku-20240307-v1:0",
|
||||
"anthropic.claude-3-haiku-20240307-v1:0:200k",
|
||||
"anthropic.claude-3-haiku-20240307-v1:0:48k",
|
||||
"anthropic.claude-3-opus-20240229-v1:0",
|
||||
"anthropic.claude-3-opus-20240229-v1:0:12k",
|
||||
"anthropic.claude-3-opus-20240229-v1:0:200k",
|
||||
"anthropic.claude-3-opus-20240229-v1:0:28k",
|
||||
"anthropic.claude-3-sonnet-20240229-v1:0",
|
||||
"anthropic.claude-3-sonnet-20240229-v1:0:200k",
|
||||
"anthropic.claude-3-sonnet-20240229-v1:0:28k",
|
||||
"anthropic.claude-haiku-4-5-20251001-v1:0",
|
||||
"anthropic.claude-instant-v1:2:100k",
|
||||
"anthropic.claude-opus-4-1-20250805-v1:0",
|
||||
"anthropic.claude-opus-4-20250514-v1:0",
|
||||
"anthropic.claude-sonnet-4-20250514-v1:0",
|
||||
"anthropic.claude-sonnet-4-5-20250929-v1:0",
|
||||
"anthropic.claude-v2:0:100k",
|
||||
"anthropic.claude-v2:0:18k",
|
||||
"anthropic.claude-v2:1:18k",
|
||||
"anthropic.claude-v2:1:200k",
|
||||
"cohere.command-r-plus-v1:0",
|
||||
"cohere.command-r-v1:0",
|
||||
"cohere.rerank-v3-5:0",
|
||||
"deepseek.r1-v1:0",
|
||||
"meta.llama3-1-70b-instruct-v1:0",
|
||||
"meta.llama3-1-8b-instruct-v1:0",
|
||||
"meta.llama3-2-11b-instruct-v1:0",
|
||||
"meta.llama3-2-1b-instruct-v1:0",
|
||||
"meta.llama3-2-3b-instruct-v1:0",
|
||||
"meta.llama3-2-90b-instruct-v1:0",
|
||||
"meta.llama3-3-70b-instruct-v1:0",
|
||||
"meta.llama3-70b-instruct-v1:0",
|
||||
"meta.llama3-8b-instruct-v1:0",
|
||||
"meta.llama4-maverick-17b-instruct-v1:0",
|
||||
"meta.llama4-scout-17b-instruct-v1:0",
|
||||
"mistral.mistral-7b-instruct-v0:2",
|
||||
"mistral.mistral-large-2402-v1:0",
|
||||
"mistral.mistral-small-2402-v1:0",
|
||||
"mistral.mixtral-8x7b-instruct-v0:1",
|
||||
"mistral.pixtral-large-2502-v1:0",
|
||||
"openai.gpt-oss-120b-1:0",
|
||||
"openai.gpt-oss-20b-1:0",
|
||||
"qwen.qwen3-32b-v1:0",
|
||||
"qwen.qwen3-coder-30b-a3b-v1:0",
|
||||
"twelvelabs.pegasus-1-2-v1:0",
|
||||
]
|
||||
@@ -1,6 +0,0 @@
|
||||
"""Interceptor contracts for crewai"""
|
||||
|
||||
from crewai.llms.hooks.base import BaseInterceptor
|
||||
|
||||
|
||||
__all__ = ["BaseInterceptor"]
|
||||
@@ -1,133 +0,0 @@
|
||||
"""Base classes for LLM transport interceptors.
|
||||
|
||||
This module provides abstract base classes for intercepting and modifying
|
||||
outbound and inbound messages at the transport level.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from abc import ABC, abstractmethod
|
||||
from typing import TYPE_CHECKING, Any, Generic, TypeVar
|
||||
|
||||
from pydantic_core import core_schema
|
||||
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from pydantic import GetCoreSchemaHandler
|
||||
from pydantic_core import CoreSchema
|
||||
|
||||
|
||||
T = TypeVar("T")
|
||||
U = TypeVar("U")
|
||||
|
||||
|
||||
class BaseInterceptor(ABC, Generic[T, U]):
|
||||
"""Abstract base class for intercepting transport-level messages.
|
||||
|
||||
Provides hooks to intercept and modify outbound and inbound messages
|
||||
at the transport layer.
|
||||
|
||||
Type parameters:
|
||||
T: Outbound message type (e.g., httpx.Request)
|
||||
U: Inbound message type (e.g., httpx.Response)
|
||||
|
||||
Example:
|
||||
>>> import httpx
|
||||
>>> class CustomInterceptor(BaseInterceptor[httpx.Request, httpx.Response]):
|
||||
... def on_outbound(self, message: httpx.Request) -> httpx.Request:
|
||||
... message.headers["X-Custom-Header"] = "value"
|
||||
... return message
|
||||
...
|
||||
... def on_inbound(self, message: httpx.Response) -> httpx.Response:
|
||||
... print(f"Status: {message.status_code}")
|
||||
... return message
|
||||
"""
|
||||
|
||||
@abstractmethod
|
||||
def on_outbound(self, message: T) -> T:
|
||||
"""Intercept outbound message before sending.
|
||||
|
||||
Args:
|
||||
message: Outbound message object.
|
||||
|
||||
Returns:
|
||||
Modified message object.
|
||||
"""
|
||||
...
|
||||
|
||||
@abstractmethod
|
||||
def on_inbound(self, message: U) -> U:
|
||||
"""Intercept inbound message after receiving.
|
||||
|
||||
Args:
|
||||
message: Inbound message object.
|
||||
|
||||
Returns:
|
||||
Modified message object.
|
||||
"""
|
||||
...
|
||||
|
||||
async def aon_outbound(self, message: T) -> T:
|
||||
"""Async version of on_outbound.
|
||||
|
||||
Args:
|
||||
message: Outbound message object.
|
||||
|
||||
Returns:
|
||||
Modified message object.
|
||||
"""
|
||||
raise NotImplementedError
|
||||
|
||||
async def aon_inbound(self, message: U) -> U:
|
||||
"""Async version of on_inbound.
|
||||
|
||||
Args:
|
||||
message: Inbound message object.
|
||||
|
||||
Returns:
|
||||
Modified message object.
|
||||
"""
|
||||
raise NotImplementedError
|
||||
|
||||
@classmethod
|
||||
def __get_pydantic_core_schema__(
|
||||
cls, _source_type: Any, _handler: GetCoreSchemaHandler
|
||||
) -> CoreSchema:
|
||||
"""Generate Pydantic core schema for BaseInterceptor.
|
||||
|
||||
This allows the generic BaseInterceptor to be used in Pydantic models
|
||||
without requiring arbitrary_types_allowed=True. The schema validates
|
||||
that the value is an instance of BaseInterceptor.
|
||||
|
||||
Args:
|
||||
_source_type: The source type being validated (unused).
|
||||
_handler: Handler for generating schemas (unused).
|
||||
|
||||
Returns:
|
||||
A Pydantic core schema that validates BaseInterceptor instances.
|
||||
"""
|
||||
return core_schema.no_info_plain_validator_function(
|
||||
_validate_interceptor,
|
||||
serialization=core_schema.plain_serializer_function_ser_schema(
|
||||
lambda x: x, return_schema=core_schema.any_schema()
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
def _validate_interceptor(value: Any) -> BaseInterceptor[T, U]:
|
||||
"""Validate that the value is a BaseInterceptor instance.
|
||||
|
||||
Args:
|
||||
value: The value to validate.
|
||||
|
||||
Returns:
|
||||
The validated BaseInterceptor instance.
|
||||
|
||||
Raises:
|
||||
ValueError: If the value is not a BaseInterceptor instance.
|
||||
"""
|
||||
if not isinstance(value, BaseInterceptor):
|
||||
raise ValueError(
|
||||
f"Expected BaseInterceptor instance, got {type(value).__name__}"
|
||||
)
|
||||
return value
|
||||
@@ -1,123 +0,0 @@
|
||||
"""HTTP transport implementations for LLM request/response interception.
|
||||
|
||||
This module provides internal transport classes that integrate with BaseInterceptor
|
||||
to enable request/response modification at the transport level.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from collections.abc import Iterable
|
||||
from typing import TYPE_CHECKING, TypedDict
|
||||
|
||||
from httpx import (
|
||||
AsyncHTTPTransport as _AsyncHTTPTransport,
|
||||
HTTPTransport as _HTTPTransport,
|
||||
)
|
||||
from typing_extensions import NotRequired, Unpack
|
||||
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from ssl import SSLContext
|
||||
|
||||
from httpx import Limits, Request, Response
|
||||
from httpx._types import CertTypes, ProxyTypes
|
||||
|
||||
from crewai.llms.hooks.base import BaseInterceptor
|
||||
|
||||
|
||||
class HTTPTransportKwargs(TypedDict, total=False):
|
||||
"""Typed dictionary for httpx.HTTPTransport initialization parameters.
|
||||
|
||||
These parameters configure the underlying HTTP transport behavior including
|
||||
SSL verification, proxies, connection limits, and low-level socket options.
|
||||
"""
|
||||
|
||||
verify: bool | str | SSLContext
|
||||
cert: NotRequired[CertTypes]
|
||||
trust_env: bool
|
||||
http1: bool
|
||||
http2: bool
|
||||
limits: Limits
|
||||
proxy: NotRequired[ProxyTypes]
|
||||
uds: NotRequired[str]
|
||||
local_address: NotRequired[str]
|
||||
retries: int
|
||||
socket_options: NotRequired[
|
||||
Iterable[
|
||||
tuple[int, int, int]
|
||||
| tuple[int, int, bytes | bytearray]
|
||||
| tuple[int, int, None, int]
|
||||
]
|
||||
]
|
||||
|
||||
|
||||
class HTTPTransport(_HTTPTransport):
|
||||
"""HTTP transport that uses an interceptor for request/response modification.
|
||||
|
||||
This transport is used internally when a user provides a BaseInterceptor.
|
||||
Users should not instantiate this class directly - instead, pass an interceptor
|
||||
to the LLM client and this transport will be created automatically.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
interceptor: BaseInterceptor[Request, Response],
|
||||
**kwargs: Unpack[HTTPTransportKwargs],
|
||||
) -> None:
|
||||
"""Initialize transport with interceptor.
|
||||
|
||||
Args:
|
||||
interceptor: HTTP interceptor for modifying raw request/response objects.
|
||||
**kwargs: HTTPTransport configuration parameters (verify, cert, proxy, etc.).
|
||||
"""
|
||||
super().__init__(**kwargs)
|
||||
self.interceptor = interceptor
|
||||
|
||||
def handle_request(self, request: Request) -> Response:
|
||||
"""Handle request with interception.
|
||||
|
||||
Args:
|
||||
request: The HTTP request to handle.
|
||||
|
||||
Returns:
|
||||
The HTTP response.
|
||||
"""
|
||||
request = self.interceptor.on_outbound(request)
|
||||
response = super().handle_request(request)
|
||||
return self.interceptor.on_inbound(response)
|
||||
|
||||
|
||||
class AsyncHTTPTransport(_AsyncHTTPTransport):
|
||||
"""Async HTTP transport that uses an interceptor for request/response modification.
|
||||
|
||||
This transport is used internally when a user provides a BaseInterceptor.
|
||||
Users should not instantiate this class directly - instead, pass an interceptor
|
||||
to the LLM client and this transport will be created automatically.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
interceptor: BaseInterceptor[Request, Response],
|
||||
**kwargs: Unpack[HTTPTransportKwargs],
|
||||
) -> None:
|
||||
"""Initialize async transport with interceptor.
|
||||
|
||||
Args:
|
||||
interceptor: HTTP interceptor for modifying raw request/response objects.
|
||||
**kwargs: HTTPTransport configuration parameters (verify, cert, proxy, etc.).
|
||||
"""
|
||||
super().__init__(**kwargs)
|
||||
self.interceptor = interceptor
|
||||
|
||||
async def handle_async_request(self, request: Request) -> Response:
|
||||
"""Handle async request with interception.
|
||||
|
||||
Args:
|
||||
request: The HTTP request to handle.
|
||||
|
||||
Returns:
|
||||
The HTTP response.
|
||||
"""
|
||||
request = await self.interceptor.aon_outbound(request)
|
||||
response = await super().handle_async_request(request)
|
||||
return await self.interceptor.aon_inbound(response)
|
||||
@@ -1,15 +1,15 @@
|
||||
from __future__ import annotations
|
||||
|
||||
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
from typing import TYPE_CHECKING, Any, cast
|
||||
from typing import Any, cast
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
from crewai.events.types.llm_events import LLMCallType
|
||||
from crewai.llms.base_llm import BaseLLM
|
||||
from crewai.llms.hooks.transport import HTTPTransport
|
||||
from crewai.utilities.agent_utils import is_context_length_exceeded
|
||||
from crewai.utilities.exceptions.context_window_exceeding_exception import (
|
||||
LLMContextLengthExceededError,
|
||||
@@ -17,14 +17,10 @@ from crewai.utilities.exceptions.context_window_exceeding_exception import (
|
||||
from crewai.utilities.types import LLMMessage
|
||||
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from crewai.llms.hooks.base import BaseInterceptor
|
||||
|
||||
try:
|
||||
from anthropic import Anthropic
|
||||
from anthropic.types import Message
|
||||
from anthropic.types.tool_use_block import ToolUseBlock
|
||||
import httpx
|
||||
except ImportError:
|
||||
raise ImportError(
|
||||
'Anthropic native provider not available, to install: uv add "crewai[anthropic]"'
|
||||
@@ -51,8 +47,7 @@ class AnthropicCompletion(BaseLLM):
|
||||
stop_sequences: list[str] | None = None,
|
||||
stream: bool = False,
|
||||
client_params: dict[str, Any] | None = None,
|
||||
interceptor: BaseInterceptor[httpx.Request, httpx.Response] | None = None,
|
||||
**kwargs: Any,
|
||||
**kwargs,
|
||||
):
|
||||
"""Initialize Anthropic chat completion client.
|
||||
|
||||
@@ -68,7 +63,6 @@ class AnthropicCompletion(BaseLLM):
|
||||
stop_sequences: Stop sequences (Anthropic uses stop_sequences, not stop)
|
||||
stream: Enable streaming responses
|
||||
client_params: Additional parameters for the Anthropic client
|
||||
interceptor: HTTP interceptor for modifying requests/responses at transport level.
|
||||
**kwargs: Additional parameters
|
||||
"""
|
||||
super().__init__(
|
||||
@@ -76,7 +70,6 @@ class AnthropicCompletion(BaseLLM):
|
||||
)
|
||||
|
||||
# Client params
|
||||
self.interceptor = interceptor
|
||||
self.client_params = client_params
|
||||
self.base_url = base_url
|
||||
self.timeout = timeout
|
||||
@@ -94,30 +87,6 @@ class AnthropicCompletion(BaseLLM):
|
||||
self.is_claude_3 = "claude-3" in model.lower()
|
||||
self.supports_tools = self.is_claude_3 # Claude 3+ supports tool use
|
||||
|
||||
@property
|
||||
def stop(self) -> list[str]:
|
||||
"""Get stop sequences sent to the API."""
|
||||
return self.stop_sequences
|
||||
|
||||
@stop.setter
|
||||
def stop(self, value: list[str] | str | None) -> None:
|
||||
"""Set stop sequences.
|
||||
|
||||
Synchronizes stop_sequences to ensure values set by CrewAgentExecutor
|
||||
are properly sent to the Anthropic API.
|
||||
|
||||
Args:
|
||||
value: Stop sequences as a list, single string, or None
|
||||
"""
|
||||
if value is None:
|
||||
self.stop_sequences = []
|
||||
elif isinstance(value, str):
|
||||
self.stop_sequences = [value]
|
||||
elif isinstance(value, list):
|
||||
self.stop_sequences = value
|
||||
else:
|
||||
self.stop_sequences = []
|
||||
|
||||
def _get_client_params(self) -> dict[str, Any]:
|
||||
"""Get client parameters."""
|
||||
|
||||
@@ -133,11 +102,6 @@ class AnthropicCompletion(BaseLLM):
|
||||
"max_retries": self.max_retries,
|
||||
}
|
||||
|
||||
if self.interceptor:
|
||||
transport = HTTPTransport(interceptor=self.interceptor)
|
||||
http_client = httpx.Client(transport=transport)
|
||||
client_params["http_client"] = http_client # type: ignore[assignment]
|
||||
|
||||
if self.client_params:
|
||||
client_params.update(self.client_params)
|
||||
|
||||
@@ -146,7 +110,7 @@ class AnthropicCompletion(BaseLLM):
|
||||
def call(
|
||||
self,
|
||||
messages: str | list[LLMMessage],
|
||||
tools: list[dict[str, Any]] | None = None,
|
||||
tools: list[dict] | None = None,
|
||||
callbacks: list[Any] | None = None,
|
||||
available_functions: dict[str, Any] | None = None,
|
||||
from_task: Any | None = None,
|
||||
@@ -169,7 +133,7 @@ class AnthropicCompletion(BaseLLM):
|
||||
try:
|
||||
# Emit call started event
|
||||
self._emit_call_started_event(
|
||||
messages=messages,
|
||||
messages=messages, # type: ignore[arg-type]
|
||||
tools=tools,
|
||||
callbacks=callbacks,
|
||||
available_functions=available_functions,
|
||||
@@ -179,7 +143,7 @@ class AnthropicCompletion(BaseLLM):
|
||||
|
||||
# Format messages for Anthropic
|
||||
formatted_messages, system_message = self._format_messages_for_anthropic(
|
||||
messages
|
||||
messages # type: ignore[arg-type]
|
||||
)
|
||||
|
||||
# Prepare completion parameters
|
||||
@@ -217,7 +181,7 @@ class AnthropicCompletion(BaseLLM):
|
||||
self,
|
||||
messages: list[LLMMessage],
|
||||
system_message: str | None = None,
|
||||
tools: list[dict[str, Any]] | None = None,
|
||||
tools: list[dict] | None = None,
|
||||
) -> dict[str, Any]:
|
||||
"""Prepare parameters for Anthropic messages API.
|
||||
|
||||
@@ -254,9 +218,7 @@ class AnthropicCompletion(BaseLLM):
|
||||
|
||||
return params
|
||||
|
||||
def _convert_tools_for_interference(
|
||||
self, tools: list[dict[str, Any]]
|
||||
) -> list[dict[str, Any]]:
|
||||
def _convert_tools_for_interference(self, tools: list[dict]) -> list[dict]:
|
||||
"""Convert CrewAI tool format to Anthropic tool use format."""
|
||||
anthropic_tools = []
|
||||
|
||||
|
||||
@@ -3,7 +3,7 @@ from __future__ import annotations
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
from typing import TYPE_CHECKING, Any
|
||||
from typing import Any, TYPE_CHECKING
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
@@ -13,25 +13,23 @@ from crewai.utilities.exceptions.context_window_exceeding_exception import (
|
||||
)
|
||||
from crewai.utilities.types import LLMMessage
|
||||
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from crewai.llms.hooks.base import BaseInterceptor
|
||||
from crewai.tools.base_tool import BaseTool
|
||||
|
||||
|
||||
try:
|
||||
from azure.ai.inference import (
|
||||
from azure.ai.inference import ( # type: ignore[import-not-found]
|
||||
ChatCompletionsClient,
|
||||
)
|
||||
from azure.ai.inference.models import (
|
||||
from azure.ai.inference.models import ( # type: ignore[import-not-found]
|
||||
ChatCompletions,
|
||||
ChatCompletionsToolCall,
|
||||
StreamingChatCompletionsUpdate,
|
||||
)
|
||||
from azure.core.credentials import (
|
||||
from azure.core.credentials import ( # type: ignore[import-not-found]
|
||||
AzureKeyCredential,
|
||||
)
|
||||
from azure.core.exceptions import (
|
||||
from azure.core.exceptions import ( # type: ignore[import-not-found]
|
||||
HttpResponseError,
|
||||
)
|
||||
|
||||
@@ -66,8 +64,7 @@ class AzureCompletion(BaseLLM):
|
||||
max_tokens: int | None = None,
|
||||
stop: list[str] | None = None,
|
||||
stream: bool = False,
|
||||
interceptor: BaseInterceptor[Any, Any] | None = None,
|
||||
**kwargs: Any,
|
||||
**kwargs,
|
||||
):
|
||||
"""Initialize Azure AI Inference chat completion client.
|
||||
|
||||
@@ -85,15 +82,8 @@ class AzureCompletion(BaseLLM):
|
||||
max_tokens: Maximum tokens in response
|
||||
stop: Stop sequences
|
||||
stream: Enable streaming responses
|
||||
interceptor: HTTP interceptor (not yet supported for Azure).
|
||||
**kwargs: Additional parameters
|
||||
"""
|
||||
if interceptor is not None:
|
||||
raise NotImplementedError(
|
||||
"HTTP interceptors are not yet supported for Azure AI Inference provider. "
|
||||
"Interceptors are currently supported for OpenAI and Anthropic providers only."
|
||||
)
|
||||
|
||||
super().__init__(
|
||||
model=model, temperature=temperature, stop=stop or [], **kwargs
|
||||
)
|
||||
@@ -131,7 +121,7 @@ class AzureCompletion(BaseLLM):
|
||||
if self.api_version:
|
||||
client_kwargs["api_version"] = self.api_version
|
||||
|
||||
self.client = ChatCompletionsClient(**client_kwargs) # type: ignore[arg-type]
|
||||
self.client = ChatCompletionsClient(**client_kwargs)
|
||||
|
||||
self.top_p = top_p
|
||||
self.frequency_penalty = frequency_penalty
|
||||
@@ -259,7 +249,7 @@ class AzureCompletion(BaseLLM):
|
||||
def _prepare_completion_params(
|
||||
self,
|
||||
messages: list[LLMMessage],
|
||||
tools: list[dict[str, Any]] | None = None,
|
||||
tools: list[dict] | None = None,
|
||||
response_model: type[BaseModel] | None = None,
|
||||
) -> dict[str, Any]:
|
||||
"""Prepare parameters for Azure AI Inference chat completion.
|
||||
@@ -312,9 +302,7 @@ class AzureCompletion(BaseLLM):
|
||||
|
||||
return params
|
||||
|
||||
def _convert_tools_for_interference(
|
||||
self, tools: list[dict[str, Any]]
|
||||
) -> list[dict[str, Any]]:
|
||||
def _convert_tools_for_interference(self, tools: list[dict]) -> list[dict]:
|
||||
"""Convert CrewAI tool format to Azure OpenAI function calling format."""
|
||||
|
||||
from crewai.llms.providers.utils.common import safe_tool_conversion
|
||||
|
||||
@@ -30,8 +30,6 @@ if TYPE_CHECKING:
|
||||
ToolTypeDef,
|
||||
)
|
||||
|
||||
from crewai.llms.hooks.base import BaseInterceptor
|
||||
|
||||
|
||||
try:
|
||||
from boto3.session import Session
|
||||
@@ -159,9 +157,8 @@ class BedrockCompletion(BaseLLM):
|
||||
guardrail_config: dict[str, Any] | None = None,
|
||||
additional_model_request_fields: dict[str, Any] | None = None,
|
||||
additional_model_response_field_paths: list[str] | None = None,
|
||||
interceptor: BaseInterceptor[Any, Any] | None = None,
|
||||
**kwargs: Any,
|
||||
) -> None:
|
||||
**kwargs,
|
||||
):
|
||||
"""Initialize AWS Bedrock completion client.
|
||||
|
||||
Args:
|
||||
@@ -179,15 +176,8 @@ class BedrockCompletion(BaseLLM):
|
||||
guardrail_config: Guardrail configuration for content filtering
|
||||
additional_model_request_fields: Model-specific request parameters
|
||||
additional_model_response_field_paths: Custom response field paths
|
||||
interceptor: HTTP interceptor (not yet supported for Bedrock).
|
||||
**kwargs: Additional parameters
|
||||
"""
|
||||
if interceptor is not None:
|
||||
raise NotImplementedError(
|
||||
"HTTP interceptors are not yet supported for AWS Bedrock provider. "
|
||||
"Interceptors are currently supported for OpenAI and Anthropic providers only."
|
||||
)
|
||||
|
||||
# Extract provider from kwargs to avoid duplicate argument
|
||||
kwargs.pop("provider", None)
|
||||
|
||||
@@ -243,30 +233,6 @@ class BedrockCompletion(BaseLLM):
|
||||
# Handle inference profiles for newer models
|
||||
self.model_id = model
|
||||
|
||||
@property
|
||||
def stop(self) -> list[str]:
|
||||
"""Get stop sequences sent to the API."""
|
||||
return list(self.stop_sequences)
|
||||
|
||||
@stop.setter
|
||||
def stop(self, value: Sequence[str] | str | None) -> None:
|
||||
"""Set stop sequences.
|
||||
|
||||
Synchronizes stop_sequences to ensure values set by CrewAgentExecutor
|
||||
are properly sent to the Bedrock API.
|
||||
|
||||
Args:
|
||||
value: Stop sequences as a Sequence, single string, or None
|
||||
"""
|
||||
if value is None:
|
||||
self.stop_sequences = []
|
||||
elif isinstance(value, str):
|
||||
self.stop_sequences = [value]
|
||||
elif isinstance(value, Sequence):
|
||||
self.stop_sequences = list(value)
|
||||
else:
|
||||
self.stop_sequences = []
|
||||
|
||||
def call(
|
||||
self,
|
||||
messages: str | list[LLMMessage],
|
||||
@@ -281,7 +247,7 @@ class BedrockCompletion(BaseLLM):
|
||||
try:
|
||||
# Emit call started event
|
||||
self._emit_call_started_event(
|
||||
messages=messages,
|
||||
messages=messages, # type: ignore[arg-type]
|
||||
tools=tools,
|
||||
callbacks=callbacks,
|
||||
available_functions=available_functions,
|
||||
@@ -774,9 +740,7 @@ class BedrockCompletion(BaseLLM):
|
||||
return converse_messages, system_message
|
||||
|
||||
@staticmethod
|
||||
def _format_tools_for_converse(
|
||||
tools: list[dict[str, Any]],
|
||||
) -> list[ConverseToolTypeDef]:
|
||||
def _format_tools_for_converse(tools: list[dict]) -> list[ConverseToolTypeDef]:
|
||||
"""Convert CrewAI tools to Converse API format following AWS specification."""
|
||||
from crewai.llms.providers.utils.common import safe_tool_conversion
|
||||
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
from typing import Any, cast
|
||||
@@ -6,7 +7,6 @@ from pydantic import BaseModel
|
||||
|
||||
from crewai.events.types.llm_events import LLMCallType
|
||||
from crewai.llms.base_llm import BaseLLM
|
||||
from crewai.llms.hooks.base import BaseInterceptor
|
||||
from crewai.utilities.agent_utils import is_context_length_exceeded
|
||||
from crewai.utilities.exceptions.context_window_exceeding_exception import (
|
||||
LLMContextLengthExceededError,
|
||||
@@ -45,14 +45,13 @@ class GeminiCompletion(BaseLLM):
|
||||
stream: bool = False,
|
||||
safety_settings: dict[str, Any] | None = None,
|
||||
client_params: dict[str, Any] | None = None,
|
||||
interceptor: BaseInterceptor[Any, Any] | None = None,
|
||||
**kwargs: Any,
|
||||
**kwargs,
|
||||
):
|
||||
"""Initialize Google Gemini chat completion client.
|
||||
|
||||
Args:
|
||||
model: Gemini model name (e.g., 'gemini-2.0-flash-001', 'gemini-1.5-pro')
|
||||
api_key: Google API key (defaults to GEMINI_API_KEY or GEMINI_API_KEY env var)
|
||||
api_key: Google API key (defaults to GOOGLE_API_KEY or GEMINI_API_KEY env var)
|
||||
project: Google Cloud project ID (for Vertex AI)
|
||||
location: Google Cloud location (for Vertex AI, defaults to 'us-central1')
|
||||
temperature: Sampling temperature (0-2)
|
||||
@@ -64,15 +63,8 @@ class GeminiCompletion(BaseLLM):
|
||||
safety_settings: Safety filter settings
|
||||
client_params: Additional parameters to pass to the Google Gen AI Client constructor.
|
||||
Supports parameters like http_options, credentials, debug_config, etc.
|
||||
interceptor: HTTP interceptor (not yet supported for Gemini).
|
||||
**kwargs: Additional parameters
|
||||
"""
|
||||
if interceptor is not None:
|
||||
raise NotImplementedError(
|
||||
"HTTP interceptors are not yet supported for Google Gemini provider. "
|
||||
"Interceptors are currently supported for OpenAI and Anthropic providers only."
|
||||
)
|
||||
|
||||
super().__init__(
|
||||
model=model, temperature=temperature, stop=stop_sequences or [], **kwargs
|
||||
)
|
||||
@@ -82,7 +74,7 @@ class GeminiCompletion(BaseLLM):
|
||||
|
||||
# Get API configuration with environment variable fallbacks
|
||||
self.api_key = (
|
||||
api_key or os.getenv("GEMINI_API_KEY") or os.getenv("GEMINI_API_KEY")
|
||||
api_key or os.getenv("GOOGLE_API_KEY") or os.getenv("GEMINI_API_KEY")
|
||||
)
|
||||
self.project = project or os.getenv("GOOGLE_CLOUD_PROJECT")
|
||||
self.location = location or os.getenv("GOOGLE_CLOUD_LOCATION") or "us-central1"
|
||||
@@ -104,31 +96,7 @@ class GeminiCompletion(BaseLLM):
|
||||
self.is_gemini_1_5 = "gemini-1.5" in model.lower()
|
||||
self.supports_tools = self.is_gemini_1_5 or self.is_gemini_2
|
||||
|
||||
@property
|
||||
def stop(self) -> list[str]:
|
||||
"""Get stop sequences sent to the API."""
|
||||
return self.stop_sequences
|
||||
|
||||
@stop.setter
|
||||
def stop(self, value: list[str] | str | None) -> None:
|
||||
"""Set stop sequences.
|
||||
|
||||
Synchronizes stop_sequences to ensure values set by CrewAgentExecutor
|
||||
are properly sent to the Gemini API.
|
||||
|
||||
Args:
|
||||
value: Stop sequences as a list, single string, or None
|
||||
"""
|
||||
if value is None:
|
||||
self.stop_sequences = []
|
||||
elif isinstance(value, str):
|
||||
self.stop_sequences = [value]
|
||||
elif isinstance(value, list):
|
||||
self.stop_sequences = value
|
||||
else:
|
||||
self.stop_sequences = []
|
||||
|
||||
def _initialize_client(self, use_vertexai: bool = False) -> genai.Client: # type: ignore[no-any-unimported]
|
||||
def _initialize_client(self, use_vertexai: bool = False) -> genai.Client:
|
||||
"""Initialize the Google Gen AI client with proper parameter handling.
|
||||
|
||||
Args:
|
||||
@@ -165,7 +133,7 @@ class GeminiCompletion(BaseLLM):
|
||||
return genai.Client(**client_params)
|
||||
except Exception as e:
|
||||
raise ValueError(
|
||||
"Either GEMINI_API_KEY/GEMINI_API_KEY (for Gemini API) or "
|
||||
"Either GOOGLE_API_KEY/GEMINI_API_KEY (for Gemini API) or "
|
||||
"GOOGLE_CLOUD_PROJECT (for Vertex AI) must be set"
|
||||
) from e
|
||||
|
||||
@@ -203,7 +171,7 @@ class GeminiCompletion(BaseLLM):
|
||||
def call(
|
||||
self,
|
||||
messages: str | list[LLMMessage],
|
||||
tools: list[dict[str, Any]] | None = None,
|
||||
tools: list[dict] | None = None,
|
||||
callbacks: list[Any] | None = None,
|
||||
available_functions: dict[str, Any] | None = None,
|
||||
from_task: Any | None = None,
|
||||
@@ -225,7 +193,7 @@ class GeminiCompletion(BaseLLM):
|
||||
"""
|
||||
try:
|
||||
self._emit_call_started_event(
|
||||
messages=messages,
|
||||
messages=messages, # type: ignore[arg-type]
|
||||
tools=tools,
|
||||
callbacks=callbacks,
|
||||
available_functions=available_functions,
|
||||
@@ -235,7 +203,7 @@ class GeminiCompletion(BaseLLM):
|
||||
self.tools = tools
|
||||
|
||||
formatted_content, system_instruction = self._format_messages_for_gemini(
|
||||
messages
|
||||
messages # type: ignore[arg-type]
|
||||
)
|
||||
|
||||
config = self._prepare_generation_config(
|
||||
@@ -277,10 +245,10 @@ class GeminiCompletion(BaseLLM):
|
||||
)
|
||||
raise
|
||||
|
||||
def _prepare_generation_config( # type: ignore[no-any-unimported]
|
||||
def _prepare_generation_config(
|
||||
self,
|
||||
system_instruction: str | None = None,
|
||||
tools: list[dict[str, Any]] | None = None,
|
||||
tools: list[dict] | None = None,
|
||||
response_model: type[BaseModel] | None = None,
|
||||
) -> types.GenerateContentConfig:
|
||||
"""Prepare generation config for Google Gemini API.
|
||||
@@ -329,9 +297,7 @@ class GeminiCompletion(BaseLLM):
|
||||
|
||||
return types.GenerateContentConfig(**config_params)
|
||||
|
||||
def _convert_tools_for_interference( # type: ignore[no-any-unimported]
|
||||
self, tools: list[dict[str, Any]]
|
||||
) -> list[types.Tool]:
|
||||
def _convert_tools_for_interference(self, tools: list[dict]) -> list[types.Tool]:
|
||||
"""Convert CrewAI tool format to Gemini function declaration format."""
|
||||
gemini_tools = []
|
||||
|
||||
@@ -354,7 +320,7 @@ class GeminiCompletion(BaseLLM):
|
||||
|
||||
return gemini_tools
|
||||
|
||||
def _format_messages_for_gemini( # type: ignore[no-any-unimported]
|
||||
def _format_messages_for_gemini(
|
||||
self, messages: str | list[LLMMessage]
|
||||
) -> tuple[list[types.Content], str | None]:
|
||||
"""Format messages for Gemini API.
|
||||
@@ -398,7 +364,7 @@ class GeminiCompletion(BaseLLM):
|
||||
|
||||
return contents, system_instruction
|
||||
|
||||
def _handle_completion( # type: ignore[no-any-unimported]
|
||||
def _handle_completion(
|
||||
self,
|
||||
contents: list[types.Content],
|
||||
system_instruction: str | None,
|
||||
@@ -465,7 +431,7 @@ class GeminiCompletion(BaseLLM):
|
||||
|
||||
return content
|
||||
|
||||
def _handle_streaming_completion( # type: ignore[no-any-unimported]
|
||||
def _handle_streaming_completion(
|
||||
self,
|
||||
contents: list[types.Content],
|
||||
config: types.GenerateContentConfig,
|
||||
@@ -594,9 +560,8 @@ class GeminiCompletion(BaseLLM):
|
||||
}
|
||||
return {"total_tokens": 0}
|
||||
|
||||
def _convert_contents_to_dict( # type: ignore[no-any-unimported]
|
||||
self,
|
||||
contents: list[types.Content],
|
||||
def _convert_contents_to_dict(
|
||||
self, contents: list[types.Content]
|
||||
) -> list[dict[str, str]]:
|
||||
"""Convert contents to dict format."""
|
||||
return [
|
||||
|
||||
@@ -6,7 +6,6 @@ import logging
|
||||
import os
|
||||
from typing import TYPE_CHECKING, Any
|
||||
|
||||
import httpx
|
||||
from openai import APIConnectionError, NotFoundError, OpenAI
|
||||
from openai.types.chat import ChatCompletion, ChatCompletionChunk
|
||||
from openai.types.chat.chat_completion import Choice
|
||||
@@ -15,7 +14,6 @@ from pydantic import BaseModel
|
||||
|
||||
from crewai.events.types.llm_events import LLMCallType
|
||||
from crewai.llms.base_llm import BaseLLM
|
||||
from crewai.llms.hooks.transport import HTTPTransport
|
||||
from crewai.utilities.agent_utils import is_context_length_exceeded
|
||||
from crewai.utilities.exceptions.context_window_exceeding_exception import (
|
||||
LLMContextLengthExceededError,
|
||||
@@ -25,7 +23,6 @@ from crewai.utilities.types import LLMMessage
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from crewai.agent.core import Agent
|
||||
from crewai.llms.hooks.base import BaseInterceptor
|
||||
from crewai.task import Task
|
||||
from crewai.tools.base_tool import BaseTool
|
||||
|
||||
@@ -62,7 +59,6 @@ class OpenAICompletion(BaseLLM):
|
||||
top_logprobs: int | None = None,
|
||||
reasoning_effort: str | None = None,
|
||||
provider: str | None = None,
|
||||
interceptor: BaseInterceptor[httpx.Request, httpx.Response] | None = None,
|
||||
**kwargs: Any,
|
||||
) -> None:
|
||||
"""Initialize OpenAI chat completion client."""
|
||||
@@ -70,7 +66,6 @@ class OpenAICompletion(BaseLLM):
|
||||
if provider is None:
|
||||
provider = kwargs.pop("provider", "openai")
|
||||
|
||||
self.interceptor = interceptor
|
||||
# Client configuration attributes
|
||||
self.organization = organization
|
||||
self.project = project
|
||||
@@ -93,11 +88,6 @@ class OpenAICompletion(BaseLLM):
|
||||
)
|
||||
|
||||
client_config = self._get_client_params()
|
||||
if self.interceptor:
|
||||
transport = HTTPTransport(interceptor=self.interceptor)
|
||||
http_client = httpx.Client(transport=transport)
|
||||
client_config["http_client"] = http_client
|
||||
|
||||
self.client = OpenAI(**client_config)
|
||||
|
||||
# Completion parameters
|
||||
|
||||
@@ -1,37 +0,0 @@
|
||||
"""MCP (Model Context Protocol) client support for CrewAI agents.
|
||||
|
||||
This module provides native MCP client functionality, allowing CrewAI agents
|
||||
to connect to any MCP-compliant server using various transport types.
|
||||
"""
|
||||
|
||||
from crewai.mcp.client import MCPClient
|
||||
from crewai.mcp.config import (
|
||||
MCPServerConfig,
|
||||
MCPServerHTTP,
|
||||
MCPServerSSE,
|
||||
MCPServerStdio,
|
||||
)
|
||||
from crewai.mcp.filters import (
|
||||
StaticToolFilter,
|
||||
ToolFilter,
|
||||
ToolFilterContext,
|
||||
create_dynamic_tool_filter,
|
||||
create_static_tool_filter,
|
||||
)
|
||||
from crewai.mcp.transports.base import BaseTransport, TransportType
|
||||
|
||||
|
||||
__all__ = [
|
||||
"BaseTransport",
|
||||
"MCPClient",
|
||||
"MCPServerConfig",
|
||||
"MCPServerHTTP",
|
||||
"MCPServerSSE",
|
||||
"MCPServerStdio",
|
||||
"StaticToolFilter",
|
||||
"ToolFilter",
|
||||
"ToolFilterContext",
|
||||
"TransportType",
|
||||
"create_dynamic_tool_filter",
|
||||
"create_static_tool_filter",
|
||||
]
|
||||
@@ -1,742 +0,0 @@
|
||||
"""MCP client with session management for CrewAI agents."""
|
||||
|
||||
import asyncio
|
||||
from collections.abc import Callable
|
||||
from contextlib import AsyncExitStack
|
||||
from datetime import datetime
|
||||
import logging
|
||||
import time
|
||||
from typing import Any
|
||||
|
||||
from typing_extensions import Self
|
||||
|
||||
|
||||
# BaseExceptionGroup is available in Python 3.11+
|
||||
try:
|
||||
from builtins import BaseExceptionGroup
|
||||
except ImportError:
|
||||
# Fallback for Python < 3.11 (shouldn't happen in practice)
|
||||
BaseExceptionGroup = Exception
|
||||
|
||||
from crewai.events.event_bus import crewai_event_bus
|
||||
from crewai.events.types.mcp_events import (
|
||||
MCPConnectionCompletedEvent,
|
||||
MCPConnectionFailedEvent,
|
||||
MCPConnectionStartedEvent,
|
||||
MCPToolExecutionCompletedEvent,
|
||||
MCPToolExecutionFailedEvent,
|
||||
MCPToolExecutionStartedEvent,
|
||||
)
|
||||
from crewai.mcp.transports.base import BaseTransport
|
||||
from crewai.mcp.transports.http import HTTPTransport
|
||||
from crewai.mcp.transports.sse import SSETransport
|
||||
from crewai.mcp.transports.stdio import StdioTransport
|
||||
|
||||
|
||||
# MCP Connection timeout constants (in seconds)
|
||||
MCP_CONNECTION_TIMEOUT = 30 # Increased for slow servers
|
||||
MCP_TOOL_EXECUTION_TIMEOUT = 30
|
||||
MCP_DISCOVERY_TIMEOUT = 30 # Increased for slow servers
|
||||
MCP_MAX_RETRIES = 3
|
||||
|
||||
# Simple in-memory cache for MCP tool schemas (duration: 5 minutes)
|
||||
_mcp_schema_cache: dict[str, tuple[dict[str, Any], float]] = {}
|
||||
_cache_ttl = 300 # 5 minutes
|
||||
|
||||
|
||||
class MCPClient:
|
||||
"""MCP client with session management.
|
||||
|
||||
This client manages connections to MCP servers and provides a high-level
|
||||
interface for interacting with MCP tools, prompts, and resources.
|
||||
|
||||
Example:
|
||||
```python
|
||||
transport = StdioTransport(command="python", args=["server.py"])
|
||||
client = MCPClient(transport)
|
||||
async with client:
|
||||
tools = await client.list_tools()
|
||||
result = await client.call_tool("tool_name", {"arg": "value"})
|
||||
```
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
transport: BaseTransport,
|
||||
connect_timeout: int = MCP_CONNECTION_TIMEOUT,
|
||||
execution_timeout: int = MCP_TOOL_EXECUTION_TIMEOUT,
|
||||
discovery_timeout: int = MCP_DISCOVERY_TIMEOUT,
|
||||
max_retries: int = MCP_MAX_RETRIES,
|
||||
cache_tools_list: bool = False,
|
||||
logger: logging.Logger | None = None,
|
||||
) -> None:
|
||||
"""Initialize MCP client.
|
||||
|
||||
Args:
|
||||
transport: Transport instance for MCP server connection.
|
||||
connect_timeout: Connection timeout in seconds.
|
||||
execution_timeout: Tool execution timeout in seconds.
|
||||
discovery_timeout: Tool discovery timeout in seconds.
|
||||
max_retries: Maximum retry attempts for operations.
|
||||
cache_tools_list: Whether to cache tool list results.
|
||||
logger: Optional logger instance.
|
||||
"""
|
||||
self.transport = transport
|
||||
self.connect_timeout = connect_timeout
|
||||
self.execution_timeout = execution_timeout
|
||||
self.discovery_timeout = discovery_timeout
|
||||
self.max_retries = max_retries
|
||||
self.cache_tools_list = cache_tools_list
|
||||
# self._logger = logger or logging.getLogger(__name__)
|
||||
self._session: Any = None
|
||||
self._initialized = False
|
||||
self._exit_stack = AsyncExitStack()
|
||||
self._was_connected = False
|
||||
|
||||
@property
|
||||
def connected(self) -> bool:
|
||||
"""Check if client is connected to server."""
|
||||
return self.transport.connected and self._initialized
|
||||
|
||||
@property
|
||||
def session(self) -> Any:
|
||||
"""Get the MCP session."""
|
||||
if self._session is None:
|
||||
raise RuntimeError("Client not connected. Call connect() first.")
|
||||
return self._session
|
||||
|
||||
def _get_server_info(self) -> tuple[str, str | None, str | None]:
|
||||
"""Get server information for events.
|
||||
|
||||
Returns:
|
||||
Tuple of (server_name, server_url, transport_type).
|
||||
"""
|
||||
if isinstance(self.transport, StdioTransport):
|
||||
server_name = f"{self.transport.command} {' '.join(self.transport.args)}"
|
||||
server_url = None
|
||||
transport_type = self.transport.transport_type.value
|
||||
elif isinstance(self.transport, HTTPTransport):
|
||||
server_name = self.transport.url
|
||||
server_url = self.transport.url
|
||||
transport_type = self.transport.transport_type.value
|
||||
elif isinstance(self.transport, SSETransport):
|
||||
server_name = self.transport.url
|
||||
server_url = self.transport.url
|
||||
transport_type = self.transport.transport_type.value
|
||||
else:
|
||||
server_name = "Unknown MCP Server"
|
||||
server_url = None
|
||||
transport_type = (
|
||||
self.transport.transport_type.value
|
||||
if hasattr(self.transport, "transport_type")
|
||||
else None
|
||||
)
|
||||
|
||||
return server_name, server_url, transport_type
|
||||
|
||||
async def connect(self) -> Self:
|
||||
"""Connect to MCP server and initialize session.
|
||||
|
||||
Returns:
|
||||
Self for method chaining.
|
||||
|
||||
Raises:
|
||||
ConnectionError: If connection fails.
|
||||
ImportError: If MCP SDK not available.
|
||||
"""
|
||||
if self.connected:
|
||||
return self
|
||||
|
||||
# Get server info for events
|
||||
server_name, server_url, transport_type = self._get_server_info()
|
||||
is_reconnect = self._was_connected
|
||||
|
||||
# Emit connection started event
|
||||
started_at = datetime.now()
|
||||
crewai_event_bus.emit(
|
||||
self,
|
||||
MCPConnectionStartedEvent(
|
||||
server_name=server_name,
|
||||
server_url=server_url,
|
||||
transport_type=transport_type,
|
||||
is_reconnect=is_reconnect,
|
||||
connect_timeout=self.connect_timeout,
|
||||
),
|
||||
)
|
||||
|
||||
try:
|
||||
from mcp import ClientSession
|
||||
|
||||
# Use AsyncExitStack to manage transport and session contexts together
|
||||
# This ensures they're in the same async scope and prevents cancel scope errors
|
||||
# Always enter transport context via exit stack (it handles already-connected state)
|
||||
await self._exit_stack.enter_async_context(self.transport)
|
||||
|
||||
# Create ClientSession with transport streams
|
||||
self._session = ClientSession(
|
||||
self.transport.read_stream,
|
||||
self.transport.write_stream,
|
||||
)
|
||||
|
||||
# Enter the session's async context manager via exit stack
|
||||
await self._exit_stack.enter_async_context(self._session)
|
||||
|
||||
# Initialize the session (required by MCP protocol)
|
||||
try:
|
||||
await asyncio.wait_for(
|
||||
self._session.initialize(),
|
||||
timeout=self.connect_timeout,
|
||||
)
|
||||
except asyncio.CancelledError:
|
||||
# If initialization was cancelled (e.g., event loop closing),
|
||||
# cleanup and re-raise - don't suppress cancellation
|
||||
await self._cleanup_on_error()
|
||||
raise
|
||||
except BaseExceptionGroup as eg:
|
||||
# Handle exception groups from anyio task groups
|
||||
# Extract the actual meaningful error (not GeneratorExit)
|
||||
actual_error = None
|
||||
for exc in eg.exceptions:
|
||||
if isinstance(exc, Exception) and not isinstance(
|
||||
exc, GeneratorExit
|
||||
):
|
||||
# Check if it's an HTTP error (like 401)
|
||||
error_msg = str(exc).lower()
|
||||
if "401" in error_msg or "unauthorized" in error_msg:
|
||||
actual_error = exc
|
||||
break
|
||||
if "cancel scope" not in error_msg and "task" not in error_msg:
|
||||
actual_error = exc
|
||||
break
|
||||
|
||||
await self._cleanup_on_error()
|
||||
if actual_error:
|
||||
raise ConnectionError(
|
||||
f"Failed to connect to MCP server: {actual_error}"
|
||||
) from actual_error
|
||||
raise ConnectionError(f"Failed to connect to MCP server: {eg}") from eg
|
||||
|
||||
self._initialized = True
|
||||
self._was_connected = True
|
||||
|
||||
completed_at = datetime.now()
|
||||
connection_duration_ms = (completed_at - started_at).total_seconds() * 1000
|
||||
crewai_event_bus.emit(
|
||||
self,
|
||||
MCPConnectionCompletedEvent(
|
||||
server_name=server_name,
|
||||
server_url=server_url,
|
||||
transport_type=transport_type,
|
||||
started_at=started_at,
|
||||
completed_at=completed_at,
|
||||
connection_duration_ms=connection_duration_ms,
|
||||
is_reconnect=is_reconnect,
|
||||
),
|
||||
)
|
||||
|
||||
return self
|
||||
except ImportError as e:
|
||||
await self._cleanup_on_error()
|
||||
error_msg = (
|
||||
"MCP library not available. Please install with: pip install mcp"
|
||||
)
|
||||
self._emit_connection_failed(
|
||||
server_name,
|
||||
server_url,
|
||||
transport_type,
|
||||
error_msg,
|
||||
"import_error",
|
||||
started_at,
|
||||
)
|
||||
raise ImportError(error_msg) from e
|
||||
except asyncio.TimeoutError as e:
|
||||
await self._cleanup_on_error()
|
||||
error_msg = f"MCP connection timed out after {self.connect_timeout} seconds. The server may be slow or unreachable."
|
||||
self._emit_connection_failed(
|
||||
server_name,
|
||||
server_url,
|
||||
transport_type,
|
||||
error_msg,
|
||||
"timeout",
|
||||
started_at,
|
||||
)
|
||||
raise ConnectionError(error_msg) from e
|
||||
except asyncio.CancelledError:
|
||||
# Re-raise cancellation - don't suppress it
|
||||
await self._cleanup_on_error()
|
||||
self._emit_connection_failed(
|
||||
server_name,
|
||||
server_url,
|
||||
transport_type,
|
||||
"Connection cancelled",
|
||||
"cancelled",
|
||||
started_at,
|
||||
)
|
||||
raise
|
||||
except BaseExceptionGroup as eg:
|
||||
# Handle exception groups from anyio task groups at outer level
|
||||
actual_error = None
|
||||
for exc in eg.exceptions:
|
||||
if isinstance(exc, Exception) and not isinstance(exc, GeneratorExit):
|
||||
error_msg = str(exc).lower()
|
||||
if "401" in error_msg or "unauthorized" in error_msg:
|
||||
actual_error = exc
|
||||
break
|
||||
if "cancel scope" not in error_msg and "task" not in error_msg:
|
||||
actual_error = exc
|
||||
break
|
||||
|
||||
await self._cleanup_on_error()
|
||||
error_type = (
|
||||
"authentication"
|
||||
if actual_error
|
||||
and (
|
||||
"401" in str(actual_error).lower()
|
||||
or "unauthorized" in str(actual_error).lower()
|
||||
)
|
||||
else "network"
|
||||
)
|
||||
error_msg = str(actual_error) if actual_error else str(eg)
|
||||
self._emit_connection_failed(
|
||||
server_name,
|
||||
server_url,
|
||||
transport_type,
|
||||
error_msg,
|
||||
error_type,
|
||||
started_at,
|
||||
)
|
||||
if actual_error:
|
||||
raise ConnectionError(
|
||||
f"Failed to connect to MCP server: {actual_error}"
|
||||
) from actual_error
|
||||
raise ConnectionError(f"Failed to connect to MCP server: {eg}") from eg
|
||||
except Exception as e:
|
||||
await self._cleanup_on_error()
|
||||
error_type = (
|
||||
"authentication"
|
||||
if "401" in str(e).lower() or "unauthorized" in str(e).lower()
|
||||
else "network"
|
||||
)
|
||||
self._emit_connection_failed(
|
||||
server_name, server_url, transport_type, str(e), error_type, started_at
|
||||
)
|
||||
raise ConnectionError(f"Failed to connect to MCP server: {e}") from e
|
||||
|
||||
def _emit_connection_failed(
|
||||
self,
|
||||
server_name: str,
|
||||
server_url: str | None,
|
||||
transport_type: str | None,
|
||||
error: str,
|
||||
error_type: str,
|
||||
started_at: datetime,
|
||||
) -> None:
|
||||
"""Emit connection failed event."""
|
||||
failed_at = datetime.now()
|
||||
crewai_event_bus.emit(
|
||||
self,
|
||||
MCPConnectionFailedEvent(
|
||||
server_name=server_name,
|
||||
server_url=server_url,
|
||||
transport_type=transport_type,
|
||||
error=error,
|
||||
error_type=error_type,
|
||||
started_at=started_at,
|
||||
failed_at=failed_at,
|
||||
),
|
||||
)
|
||||
|
||||
async def _cleanup_on_error(self) -> None:
|
||||
"""Cleanup resources when an error occurs during connection."""
|
||||
try:
|
||||
await self._exit_stack.aclose()
|
||||
|
||||
except Exception as e:
|
||||
# Best effort cleanup - ignore all other errors
|
||||
raise RuntimeError(f"Error during MCP client cleanup: {e}") from e
|
||||
finally:
|
||||
self._session = None
|
||||
self._initialized = False
|
||||
self._exit_stack = AsyncExitStack()
|
||||
|
||||
async def disconnect(self) -> None:
|
||||
"""Disconnect from MCP server and cleanup resources."""
|
||||
if not self.connected:
|
||||
return
|
||||
|
||||
try:
|
||||
await self._exit_stack.aclose()
|
||||
except Exception as e:
|
||||
raise RuntimeError(f"Error during MCP client disconnect: {e}") from e
|
||||
finally:
|
||||
self._session = None
|
||||
self._initialized = False
|
||||
self._exit_stack = AsyncExitStack()
|
||||
|
||||
async def list_tools(self, use_cache: bool | None = None) -> list[dict[str, Any]]:
|
||||
"""List available tools from MCP server.
|
||||
|
||||
Args:
|
||||
use_cache: Whether to use cached results. If None, uses
|
||||
client's cache_tools_list setting.
|
||||
|
||||
Returns:
|
||||
List of tool definitions with name, description, and inputSchema.
|
||||
"""
|
||||
if not self.connected:
|
||||
await self.connect()
|
||||
|
||||
# Check cache if enabled
|
||||
use_cache = use_cache if use_cache is not None else self.cache_tools_list
|
||||
if use_cache:
|
||||
cache_key = self._get_cache_key("tools")
|
||||
if cache_key in _mcp_schema_cache:
|
||||
cached_data, cache_time = _mcp_schema_cache[cache_key]
|
||||
if time.time() - cache_time < _cache_ttl:
|
||||
# Logger removed - return cached data
|
||||
return cached_data
|
||||
|
||||
# List tools with timeout and retries
|
||||
tools = await self._retry_operation(
|
||||
self._list_tools_impl,
|
||||
timeout=self.discovery_timeout,
|
||||
)
|
||||
|
||||
# Cache results if enabled
|
||||
if use_cache:
|
||||
cache_key = self._get_cache_key("tools")
|
||||
_mcp_schema_cache[cache_key] = (tools, time.time())
|
||||
|
||||
return tools
|
||||
|
||||
async def _list_tools_impl(self) -> list[dict[str, Any]]:
|
||||
"""Internal implementation of list_tools."""
|
||||
tools_result = await asyncio.wait_for(
|
||||
self.session.list_tools(),
|
||||
timeout=self.discovery_timeout,
|
||||
)
|
||||
|
||||
return [
|
||||
{
|
||||
"name": tool.name,
|
||||
"description": getattr(tool, "description", ""),
|
||||
"inputSchema": getattr(tool, "inputSchema", {}),
|
||||
}
|
||||
for tool in tools_result.tools
|
||||
]
|
||||
|
||||
async def call_tool(
|
||||
self, tool_name: str, arguments: dict[str, Any] | None = None
|
||||
) -> Any:
|
||||
"""Call a tool on the MCP server.
|
||||
|
||||
Args:
|
||||
tool_name: Name of the tool to call.
|
||||
arguments: Tool arguments.
|
||||
|
||||
Returns:
|
||||
Tool execution result.
|
||||
"""
|
||||
if not self.connected:
|
||||
await self.connect()
|
||||
|
||||
arguments = arguments or {}
|
||||
cleaned_arguments = self._clean_tool_arguments(arguments)
|
||||
|
||||
# Get server info for events
|
||||
server_name, server_url, transport_type = self._get_server_info()
|
||||
|
||||
# Emit tool execution started event
|
||||
started_at = datetime.now()
|
||||
crewai_event_bus.emit(
|
||||
self,
|
||||
MCPToolExecutionStartedEvent(
|
||||
server_name=server_name,
|
||||
server_url=server_url,
|
||||
transport_type=transport_type,
|
||||
tool_name=tool_name,
|
||||
tool_args=cleaned_arguments,
|
||||
),
|
||||
)
|
||||
|
||||
try:
|
||||
result = await self._retry_operation(
|
||||
lambda: self._call_tool_impl(tool_name, cleaned_arguments),
|
||||
timeout=self.execution_timeout,
|
||||
)
|
||||
|
||||
completed_at = datetime.now()
|
||||
execution_duration_ms = (completed_at - started_at).total_seconds() * 1000
|
||||
crewai_event_bus.emit(
|
||||
self,
|
||||
MCPToolExecutionCompletedEvent(
|
||||
server_name=server_name,
|
||||
server_url=server_url,
|
||||
transport_type=transport_type,
|
||||
tool_name=tool_name,
|
||||
tool_args=cleaned_arguments,
|
||||
result=result,
|
||||
started_at=started_at,
|
||||
completed_at=completed_at,
|
||||
execution_duration_ms=execution_duration_ms,
|
||||
),
|
||||
)
|
||||
|
||||
return result
|
||||
except Exception as e:
|
||||
failed_at = datetime.now()
|
||||
error_type = (
|
||||
"timeout"
|
||||
if isinstance(e, (asyncio.TimeoutError, ConnectionError))
|
||||
and "timeout" in str(e).lower()
|
||||
else "server_error"
|
||||
)
|
||||
crewai_event_bus.emit(
|
||||
self,
|
||||
MCPToolExecutionFailedEvent(
|
||||
server_name=server_name,
|
||||
server_url=server_url,
|
||||
transport_type=transport_type,
|
||||
tool_name=tool_name,
|
||||
tool_args=cleaned_arguments,
|
||||
error=str(e),
|
||||
error_type=error_type,
|
||||
started_at=started_at,
|
||||
failed_at=failed_at,
|
||||
),
|
||||
)
|
||||
raise
|
||||
|
||||
def _clean_tool_arguments(self, arguments: dict[str, Any]) -> dict[str, Any]:
|
||||
"""Clean tool arguments by removing None values and fixing formats.
|
||||
|
||||
Args:
|
||||
arguments: Raw tool arguments.
|
||||
|
||||
Returns:
|
||||
Cleaned arguments ready for MCP server.
|
||||
"""
|
||||
cleaned = {}
|
||||
|
||||
for key, value in arguments.items():
|
||||
# Skip None values
|
||||
if value is None:
|
||||
continue
|
||||
|
||||
# Fix sources array format: convert ["web"] to [{"type": "web"}]
|
||||
if key == "sources" and isinstance(value, list):
|
||||
fixed_sources = []
|
||||
for item in value:
|
||||
if isinstance(item, str):
|
||||
# Convert string to object format
|
||||
fixed_sources.append({"type": item})
|
||||
elif isinstance(item, dict):
|
||||
# Already in correct format
|
||||
fixed_sources.append(item)
|
||||
else:
|
||||
# Keep as is if unknown format
|
||||
fixed_sources.append(item)
|
||||
if fixed_sources:
|
||||
cleaned[key] = fixed_sources
|
||||
continue
|
||||
|
||||
# Recursively clean nested dictionaries
|
||||
if isinstance(value, dict):
|
||||
nested_cleaned = self._clean_tool_arguments(value)
|
||||
if nested_cleaned: # Only add if not empty
|
||||
cleaned[key] = nested_cleaned
|
||||
elif isinstance(value, list):
|
||||
# Clean list items
|
||||
cleaned_list = []
|
||||
for item in value:
|
||||
if isinstance(item, dict):
|
||||
cleaned_item = self._clean_tool_arguments(item)
|
||||
if cleaned_item:
|
||||
cleaned_list.append(cleaned_item)
|
||||
elif item is not None:
|
||||
cleaned_list.append(item)
|
||||
if cleaned_list:
|
||||
cleaned[key] = cleaned_list
|
||||
else:
|
||||
# Keep primitive values
|
||||
cleaned[key] = value
|
||||
|
||||
return cleaned
|
||||
|
||||
async def _call_tool_impl(self, tool_name: str, arguments: dict[str, Any]) -> Any:
|
||||
"""Internal implementation of call_tool."""
|
||||
result = await asyncio.wait_for(
|
||||
self.session.call_tool(tool_name, arguments),
|
||||
timeout=self.execution_timeout,
|
||||
)
|
||||
|
||||
# Extract result content
|
||||
if hasattr(result, "content") and result.content:
|
||||
if isinstance(result.content, list) and len(result.content) > 0:
|
||||
content_item = result.content[0]
|
||||
if hasattr(content_item, "text"):
|
||||
return str(content_item.text)
|
||||
return str(content_item)
|
||||
return str(result.content)
|
||||
|
||||
return str(result)
|
||||
|
||||
async def list_prompts(self) -> list[dict[str, Any]]:
|
||||
"""List available prompts from MCP server.
|
||||
|
||||
Returns:
|
||||
List of prompt definitions.
|
||||
"""
|
||||
if not self.connected:
|
||||
await self.connect()
|
||||
|
||||
return await self._retry_operation(
|
||||
self._list_prompts_impl,
|
||||
timeout=self.discovery_timeout,
|
||||
)
|
||||
|
||||
async def _list_prompts_impl(self) -> list[dict[str, Any]]:
|
||||
"""Internal implementation of list_prompts."""
|
||||
prompts_result = await asyncio.wait_for(
|
||||
self.session.list_prompts(),
|
||||
timeout=self.discovery_timeout,
|
||||
)
|
||||
|
||||
return [
|
||||
{
|
||||
"name": prompt.name,
|
||||
"description": getattr(prompt, "description", ""),
|
||||
"arguments": getattr(prompt, "arguments", []),
|
||||
}
|
||||
for prompt in prompts_result.prompts
|
||||
]
|
||||
|
||||
async def get_prompt(
|
||||
self, prompt_name: str, arguments: dict[str, Any] | None = None
|
||||
) -> dict[str, Any]:
|
||||
"""Get a prompt from the MCP server.
|
||||
|
||||
Args:
|
||||
prompt_name: Name of the prompt to get.
|
||||
arguments: Optional prompt arguments.
|
||||
|
||||
Returns:
|
||||
Prompt content and metadata.
|
||||
"""
|
||||
if not self.connected:
|
||||
await self.connect()
|
||||
|
||||
arguments = arguments or {}
|
||||
|
||||
return await self._retry_operation(
|
||||
lambda: self._get_prompt_impl(prompt_name, arguments),
|
||||
timeout=self.execution_timeout,
|
||||
)
|
||||
|
||||
async def _get_prompt_impl(
|
||||
self, prompt_name: str, arguments: dict[str, Any]
|
||||
) -> dict[str, Any]:
|
||||
"""Internal implementation of get_prompt."""
|
||||
result = await asyncio.wait_for(
|
||||
self.session.get_prompt(prompt_name, arguments),
|
||||
timeout=self.execution_timeout,
|
||||
)
|
||||
|
||||
return {
|
||||
"name": prompt_name,
|
||||
"messages": [
|
||||
{
|
||||
"role": msg.role,
|
||||
"content": msg.content,
|
||||
}
|
||||
for msg in result.messages
|
||||
],
|
||||
"arguments": arguments,
|
||||
}
|
||||
|
||||
async def _retry_operation(
|
||||
self,
|
||||
operation: Callable[[], Any],
|
||||
timeout: int | None = None,
|
||||
) -> Any:
|
||||
"""Retry an operation with exponential backoff.
|
||||
|
||||
Args:
|
||||
operation: Async operation to retry.
|
||||
timeout: Operation timeout in seconds.
|
||||
|
||||
Returns:
|
||||
Operation result.
|
||||
"""
|
||||
last_error = None
|
||||
timeout = timeout or self.execution_timeout
|
||||
|
||||
for attempt in range(self.max_retries):
|
||||
try:
|
||||
if timeout:
|
||||
return await asyncio.wait_for(operation(), timeout=timeout)
|
||||
return await operation()
|
||||
|
||||
except asyncio.TimeoutError as e: # noqa: PERF203
|
||||
last_error = f"Operation timed out after {timeout} seconds"
|
||||
if attempt < self.max_retries - 1:
|
||||
wait_time = 2**attempt
|
||||
await asyncio.sleep(wait_time)
|
||||
else:
|
||||
raise ConnectionError(last_error) from e
|
||||
|
||||
except Exception as e:
|
||||
error_str = str(e).lower()
|
||||
|
||||
# Classify errors as retryable or non-retryable
|
||||
if "authentication" in error_str or "unauthorized" in error_str:
|
||||
raise ConnectionError(f"Authentication failed: {e}") from e
|
||||
|
||||
if "not found" in error_str:
|
||||
raise ValueError(f"Resource not found: {e}") from e
|
||||
|
||||
# Retryable errors
|
||||
last_error = str(e)
|
||||
if attempt < self.max_retries - 1:
|
||||
wait_time = 2**attempt
|
||||
await asyncio.sleep(wait_time)
|
||||
else:
|
||||
raise ConnectionError(
|
||||
f"Operation failed after {self.max_retries} attempts: {last_error}"
|
||||
) from e
|
||||
|
||||
raise ConnectionError(f"Operation failed: {last_error}")
|
||||
|
||||
def _get_cache_key(self, resource_type: str) -> str:
|
||||
"""Generate cache key for resource.
|
||||
|
||||
Args:
|
||||
resource_type: Type of resource (e.g., "tools", "prompts").
|
||||
|
||||
Returns:
|
||||
Cache key string.
|
||||
"""
|
||||
# Use transport type and URL/command as cache key
|
||||
if isinstance(self.transport, StdioTransport):
|
||||
key = f"stdio:{self.transport.command}:{':'.join(self.transport.args)}"
|
||||
elif isinstance(self.transport, HTTPTransport):
|
||||
key = f"http:{self.transport.url}"
|
||||
elif isinstance(self.transport, SSETransport):
|
||||
key = f"sse:{self.transport.url}"
|
||||
else:
|
||||
key = f"{self.transport.transport_type}:unknown"
|
||||
|
||||
return f"mcp:{key}:{resource_type}"
|
||||
|
||||
async def __aenter__(self) -> Self:
|
||||
"""Async context manager entry."""
|
||||
return await self.connect()
|
||||
|
||||
async def __aexit__(
|
||||
self,
|
||||
exc_type: type[BaseException] | None,
|
||||
exc_val: BaseException | None,
|
||||
exc_tb: Any,
|
||||
) -> None:
|
||||
"""Async context manager exit."""
|
||||
await self.disconnect()
|
||||
@@ -1,124 +0,0 @@
|
||||
"""MCP server configuration models for CrewAI agents.
|
||||
|
||||
This module provides Pydantic models for configuring MCP servers with
|
||||
various transport types, similar to OpenAI's Agents SDK.
|
||||
"""
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
from crewai.mcp.filters import ToolFilter
|
||||
|
||||
|
||||
class MCPServerStdio(BaseModel):
|
||||
"""Stdio MCP server configuration.
|
||||
|
||||
This configuration is used for connecting to local MCP servers
|
||||
that run as processes and communicate via standard input/output.
|
||||
|
||||
Example:
|
||||
```python
|
||||
mcp_server = MCPServerStdio(
|
||||
command="python",
|
||||
args=["path/to/server.py"],
|
||||
env={"API_KEY": "..."},
|
||||
tool_filter=create_static_tool_filter(
|
||||
allowed_tool_names=["read_file", "write_file"]
|
||||
),
|
||||
)
|
||||
```
|
||||
"""
|
||||
|
||||
command: str = Field(
|
||||
...,
|
||||
description="Command to execute (e.g., 'python', 'node', 'npx', 'uvx').",
|
||||
)
|
||||
args: list[str] = Field(
|
||||
default_factory=list,
|
||||
description="Command arguments (e.g., ['server.py'] or ['-y', '@mcp/server']).",
|
||||
)
|
||||
env: dict[str, str] | None = Field(
|
||||
default=None,
|
||||
description="Environment variables to pass to the process.",
|
||||
)
|
||||
tool_filter: ToolFilter | None = Field(
|
||||
default=None,
|
||||
description="Optional tool filter for filtering available tools.",
|
||||
)
|
||||
cache_tools_list: bool = Field(
|
||||
default=False,
|
||||
description="Whether to cache the tool list for faster subsequent access.",
|
||||
)
|
||||
|
||||
|
||||
class MCPServerHTTP(BaseModel):
|
||||
"""HTTP/Streamable HTTP MCP server configuration.
|
||||
|
||||
This configuration is used for connecting to remote MCP servers
|
||||
over HTTP/HTTPS using streamable HTTP transport.
|
||||
|
||||
Example:
|
||||
```python
|
||||
mcp_server = MCPServerHTTP(
|
||||
url="https://api.example.com/mcp",
|
||||
headers={"Authorization": "Bearer ..."},
|
||||
cache_tools_list=True,
|
||||
)
|
||||
```
|
||||
"""
|
||||
|
||||
url: str = Field(
|
||||
..., description="Server URL (e.g., 'https://api.example.com/mcp')."
|
||||
)
|
||||
headers: dict[str, str] | None = Field(
|
||||
default=None,
|
||||
description="Optional HTTP headers for authentication or other purposes.",
|
||||
)
|
||||
streamable: bool = Field(
|
||||
default=True,
|
||||
description="Whether to use streamable HTTP transport (default: True).",
|
||||
)
|
||||
tool_filter: ToolFilter | None = Field(
|
||||
default=None,
|
||||
description="Optional tool filter for filtering available tools.",
|
||||
)
|
||||
cache_tools_list: bool = Field(
|
||||
default=False,
|
||||
description="Whether to cache the tool list for faster subsequent access.",
|
||||
)
|
||||
|
||||
|
||||
class MCPServerSSE(BaseModel):
|
||||
"""Server-Sent Events (SSE) MCP server configuration.
|
||||
|
||||
This configuration is used for connecting to remote MCP servers
|
||||
using Server-Sent Events for real-time streaming communication.
|
||||
|
||||
Example:
|
||||
```python
|
||||
mcp_server = MCPServerSSE(
|
||||
url="https://api.example.com/mcp/sse",
|
||||
headers={"Authorization": "Bearer ..."},
|
||||
)
|
||||
```
|
||||
"""
|
||||
|
||||
url: str = Field(
|
||||
...,
|
||||
description="Server URL (e.g., 'https://api.example.com/mcp/sse').",
|
||||
)
|
||||
headers: dict[str, str] | None = Field(
|
||||
default=None,
|
||||
description="Optional HTTP headers for authentication or other purposes.",
|
||||
)
|
||||
tool_filter: ToolFilter | None = Field(
|
||||
default=None,
|
||||
description="Optional tool filter for filtering available tools.",
|
||||
)
|
||||
cache_tools_list: bool = Field(
|
||||
default=False,
|
||||
description="Whether to cache the tool list for faster subsequent access.",
|
||||
)
|
||||
|
||||
|
||||
# Type alias for all MCP server configurations
|
||||
MCPServerConfig = MCPServerStdio | MCPServerHTTP | MCPServerSSE
|
||||
@@ -1,166 +0,0 @@
|
||||
"""Tool filtering support for MCP servers.
|
||||
|
||||
This module provides utilities for filtering tools from MCP servers,
|
||||
including static allow/block lists and dynamic context-aware filtering.
|
||||
"""
|
||||
|
||||
from collections.abc import Callable
|
||||
from typing import TYPE_CHECKING, Any
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
|
||||
if TYPE_CHECKING:
|
||||
pass
|
||||
|
||||
|
||||
class ToolFilterContext(BaseModel):
|
||||
"""Context for dynamic tool filtering.
|
||||
|
||||
This context is passed to dynamic tool filters to provide
|
||||
information about the agent, run context, and server.
|
||||
"""
|
||||
|
||||
agent: Any = Field(..., description="The agent requesting tools.")
|
||||
server_name: str = Field(..., description="Name of the MCP server.")
|
||||
run_context: dict[str, Any] | None = Field(
|
||||
default=None,
|
||||
description="Optional run context for additional filtering logic.",
|
||||
)
|
||||
|
||||
|
||||
# Type alias for tool filter functions
|
||||
ToolFilter = (
|
||||
Callable[[ToolFilterContext, dict[str, Any]], bool]
|
||||
| Callable[[dict[str, Any]], bool]
|
||||
)
|
||||
|
||||
|
||||
class StaticToolFilter:
|
||||
"""Static tool filter with allow/block lists.
|
||||
|
||||
This filter provides simple allow/block list filtering based on
|
||||
tool names. Useful for restricting which tools are available
|
||||
from an MCP server.
|
||||
|
||||
Example:
|
||||
```python
|
||||
filter = StaticToolFilter(
|
||||
allowed_tool_names=["read_file", "write_file"],
|
||||
blocked_tool_names=["delete_file"],
|
||||
)
|
||||
```
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
allowed_tool_names: list[str] | None = None,
|
||||
blocked_tool_names: list[str] | None = None,
|
||||
) -> None:
|
||||
"""Initialize static tool filter.
|
||||
|
||||
Args:
|
||||
allowed_tool_names: List of tool names to allow. If None,
|
||||
all tools are allowed (unless blocked).
|
||||
blocked_tool_names: List of tool names to block. Blocked tools
|
||||
take precedence over allowed tools.
|
||||
"""
|
||||
self.allowed_tool_names = set(allowed_tool_names or [])
|
||||
self.blocked_tool_names = set(blocked_tool_names or [])
|
||||
|
||||
def __call__(self, tool: dict[str, Any]) -> bool:
|
||||
"""Filter tool based on allow/block lists.
|
||||
|
||||
Args:
|
||||
tool: Tool definition dictionary with at least 'name' key.
|
||||
|
||||
Returns:
|
||||
True if tool should be included, False otherwise.
|
||||
"""
|
||||
tool_name = tool.get("name", "")
|
||||
|
||||
# Blocked tools take precedence
|
||||
if self.blocked_tool_names and tool_name in self.blocked_tool_names:
|
||||
return False
|
||||
|
||||
# If allow list exists, tool must be in it
|
||||
if self.allowed_tool_names:
|
||||
return tool_name in self.allowed_tool_names
|
||||
|
||||
# No restrictions - allow all
|
||||
return True
|
||||
|
||||
|
||||
def create_static_tool_filter(
|
||||
allowed_tool_names: list[str] | None = None,
|
||||
blocked_tool_names: list[str] | None = None,
|
||||
) -> Callable[[dict[str, Any]], bool]:
|
||||
"""Create a static tool filter function.
|
||||
|
||||
This is a convenience function for creating static tool filters
|
||||
with allow/block lists.
|
||||
|
||||
Args:
|
||||
allowed_tool_names: List of tool names to allow. If None,
|
||||
all tools are allowed (unless blocked).
|
||||
blocked_tool_names: List of tool names to block. Blocked tools
|
||||
take precedence over allowed tools.
|
||||
|
||||
Returns:
|
||||
Tool filter function that returns True for allowed tools.
|
||||
|
||||
Example:
|
||||
```python
|
||||
filter_fn = create_static_tool_filter(
|
||||
allowed_tool_names=["read_file", "write_file"],
|
||||
blocked_tool_names=["delete_file"],
|
||||
)
|
||||
|
||||
# Use in MCPServerStdio
|
||||
mcp_server = MCPServerStdio(
|
||||
command="npx",
|
||||
args=["-y", "@modelcontextprotocol/server-filesystem"],
|
||||
tool_filter=filter_fn,
|
||||
)
|
||||
```
|
||||
"""
|
||||
return StaticToolFilter(
|
||||
allowed_tool_names=allowed_tool_names,
|
||||
blocked_tool_names=blocked_tool_names,
|
||||
)
|
||||
|
||||
|
||||
def create_dynamic_tool_filter(
|
||||
filter_func: Callable[[ToolFilterContext, dict[str, Any]], bool],
|
||||
) -> Callable[[ToolFilterContext, dict[str, Any]], bool]:
|
||||
"""Create a dynamic tool filter function.
|
||||
|
||||
This function wraps a dynamic filter function that has access
|
||||
to the tool filter context (agent, server, run context).
|
||||
|
||||
Args:
|
||||
filter_func: Function that takes (context, tool) and returns bool.
|
||||
|
||||
Returns:
|
||||
Tool filter function that can be used with MCP server configs.
|
||||
|
||||
Example:
|
||||
```python
|
||||
async def context_aware_filter(
|
||||
context: ToolFilterContext, tool: dict[str, Any]
|
||||
) -> bool:
|
||||
# Block dangerous tools for code reviewers
|
||||
if context.agent.role == "Code Reviewer":
|
||||
if tool["name"].startswith("danger_"):
|
||||
return False
|
||||
return True
|
||||
|
||||
|
||||
filter_fn = create_dynamic_tool_filter(context_aware_filter)
|
||||
|
||||
mcp_server = MCPServerStdio(
|
||||
command="python", args=["server.py"], tool_filter=filter_fn
|
||||
)
|
||||
```
|
||||
"""
|
||||
return filter_func
|
||||
@@ -1,15 +0,0 @@
|
||||
"""MCP transport implementations for various connection types."""
|
||||
|
||||
from crewai.mcp.transports.base import BaseTransport, TransportType
|
||||
from crewai.mcp.transports.http import HTTPTransport
|
||||
from crewai.mcp.transports.sse import SSETransport
|
||||
from crewai.mcp.transports.stdio import StdioTransport
|
||||
|
||||
|
||||
__all__ = [
|
||||
"BaseTransport",
|
||||
"HTTPTransport",
|
||||
"SSETransport",
|
||||
"StdioTransport",
|
||||
"TransportType",
|
||||
]
|
||||
@@ -1,125 +0,0 @@
|
||||
"""Base transport interface for MCP connections."""
|
||||
|
||||
from abc import ABC, abstractmethod
|
||||
from enum import Enum
|
||||
from typing import Any, Protocol
|
||||
|
||||
from typing_extensions import Self
|
||||
|
||||
|
||||
class TransportType(str, Enum):
|
||||
"""MCP transport types."""
|
||||
|
||||
STDIO = "stdio"
|
||||
HTTP = "http"
|
||||
STREAMABLE_HTTP = "streamable-http"
|
||||
SSE = "sse"
|
||||
|
||||
|
||||
class ReadStream(Protocol):
|
||||
"""Protocol for read streams."""
|
||||
|
||||
async def read(self, n: int = -1) -> bytes:
|
||||
"""Read bytes from stream."""
|
||||
...
|
||||
|
||||
|
||||
class WriteStream(Protocol):
|
||||
"""Protocol for write streams."""
|
||||
|
||||
async def write(self, data: bytes) -> None:
|
||||
"""Write bytes to stream."""
|
||||
...
|
||||
|
||||
|
||||
class BaseTransport(ABC):
|
||||
"""Base class for MCP transport implementations.
|
||||
|
||||
This abstract base class defines the interface that all transport
|
||||
implementations must follow. Transports handle the low-level communication
|
||||
with MCP servers.
|
||||
"""
|
||||
|
||||
def __init__(self, **kwargs: Any) -> None:
|
||||
"""Initialize the transport.
|
||||
|
||||
Args:
|
||||
**kwargs: Transport-specific configuration options.
|
||||
"""
|
||||
self._read_stream: ReadStream | None = None
|
||||
self._write_stream: WriteStream | None = None
|
||||
self._connected = False
|
||||
|
||||
@property
|
||||
@abstractmethod
|
||||
def transport_type(self) -> TransportType:
|
||||
"""Return the transport type."""
|
||||
...
|
||||
|
||||
@property
|
||||
def connected(self) -> bool:
|
||||
"""Check if transport is connected."""
|
||||
return self._connected
|
||||
|
||||
@property
|
||||
def read_stream(self) -> ReadStream:
|
||||
"""Get the read stream."""
|
||||
if self._read_stream is None:
|
||||
raise RuntimeError("Transport not connected. Call connect() first.")
|
||||
return self._read_stream
|
||||
|
||||
@property
|
||||
def write_stream(self) -> WriteStream:
|
||||
"""Get the write stream."""
|
||||
if self._write_stream is None:
|
||||
raise RuntimeError("Transport not connected. Call connect() first.")
|
||||
return self._write_stream
|
||||
|
||||
@abstractmethod
|
||||
async def connect(self) -> Self:
|
||||
"""Establish connection to MCP server.
|
||||
|
||||
Returns:
|
||||
Self for method chaining.
|
||||
|
||||
Raises:
|
||||
ConnectionError: If connection fails.
|
||||
"""
|
||||
...
|
||||
|
||||
@abstractmethod
|
||||
async def disconnect(self) -> None:
|
||||
"""Close connection to MCP server."""
|
||||
...
|
||||
|
||||
@abstractmethod
|
||||
async def __aenter__(self) -> Self:
|
||||
"""Async context manager entry."""
|
||||
...
|
||||
|
||||
@abstractmethod
|
||||
async def __aexit__(
|
||||
self,
|
||||
exc_type: type[BaseException] | None,
|
||||
exc_val: BaseException | None,
|
||||
exc_tb: Any,
|
||||
) -> None:
|
||||
"""Async context manager exit."""
|
||||
...
|
||||
|
||||
def _set_streams(self, read: ReadStream, write: WriteStream) -> None:
|
||||
"""Set the read and write streams.
|
||||
|
||||
Args:
|
||||
read: Read stream.
|
||||
write: Write stream.
|
||||
"""
|
||||
self._read_stream = read
|
||||
self._write_stream = write
|
||||
self._connected = True
|
||||
|
||||
def _clear_streams(self) -> None:
|
||||
"""Clear the read and write streams."""
|
||||
self._read_stream = None
|
||||
self._write_stream = None
|
||||
self._connected = False
|
||||
@@ -1,174 +0,0 @@
|
||||
"""HTTP and Streamable HTTP transport for MCP servers."""
|
||||
|
||||
import asyncio
|
||||
from typing import Any
|
||||
|
||||
from typing_extensions import Self
|
||||
|
||||
|
||||
# BaseExceptionGroup is available in Python 3.11+
|
||||
try:
|
||||
from builtins import BaseExceptionGroup
|
||||
except ImportError:
|
||||
# Fallback for Python < 3.11 (shouldn't happen in practice)
|
||||
BaseExceptionGroup = Exception
|
||||
|
||||
from crewai.mcp.transports.base import BaseTransport, TransportType
|
||||
|
||||
|
||||
class HTTPTransport(BaseTransport):
|
||||
"""HTTP/Streamable HTTP transport for connecting to remote MCP servers.
|
||||
|
||||
This transport connects to MCP servers over HTTP/HTTPS using the
|
||||
streamable HTTP client from the MCP SDK.
|
||||
|
||||
Example:
|
||||
```python
|
||||
transport = HTTPTransport(
|
||||
url="https://api.example.com/mcp",
|
||||
headers={"Authorization": "Bearer ..."}
|
||||
)
|
||||
async with transport:
|
||||
# Use transport...
|
||||
```
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
url: str,
|
||||
headers: dict[str, str] | None = None,
|
||||
streamable: bool = True,
|
||||
**kwargs: Any,
|
||||
) -> None:
|
||||
"""Initialize HTTP transport.
|
||||
|
||||
Args:
|
||||
url: Server URL (e.g., "https://api.example.com/mcp").
|
||||
headers: Optional HTTP headers.
|
||||
streamable: Whether to use streamable HTTP (default: True).
|
||||
**kwargs: Additional transport options.
|
||||
"""
|
||||
super().__init__(**kwargs)
|
||||
self.url = url
|
||||
self.headers = headers or {}
|
||||
self.streamable = streamable
|
||||
self._transport_context: Any = None
|
||||
|
||||
@property
|
||||
def transport_type(self) -> TransportType:
|
||||
"""Return the transport type."""
|
||||
return TransportType.STREAMABLE_HTTP if self.streamable else TransportType.HTTP
|
||||
|
||||
async def connect(self) -> Self:
|
||||
"""Establish HTTP connection to MCP server.
|
||||
|
||||
Returns:
|
||||
Self for method chaining.
|
||||
|
||||
Raises:
|
||||
ConnectionError: If connection fails.
|
||||
ImportError: If MCP SDK not available.
|
||||
"""
|
||||
if self._connected:
|
||||
return self
|
||||
|
||||
try:
|
||||
from mcp.client.streamable_http import streamablehttp_client
|
||||
|
||||
self._transport_context = streamablehttp_client(
|
||||
self.url,
|
||||
headers=self.headers if self.headers else None,
|
||||
terminate_on_close=True,
|
||||
)
|
||||
|
||||
try:
|
||||
read, write, _ = await asyncio.wait_for(
|
||||
self._transport_context.__aenter__(), timeout=30.0
|
||||
)
|
||||
except asyncio.TimeoutError as e:
|
||||
self._transport_context = None
|
||||
raise ConnectionError(
|
||||
"Transport context entry timed out after 30 seconds. "
|
||||
"Server may be slow or unreachable."
|
||||
) from e
|
||||
except Exception as e:
|
||||
self._transport_context = None
|
||||
raise ConnectionError(f"Failed to enter transport context: {e}") from e
|
||||
self._set_streams(read=read, write=write)
|
||||
return self
|
||||
|
||||
except ImportError as e:
|
||||
raise ImportError(
|
||||
"MCP library not available. Please install with: pip install mcp"
|
||||
) from e
|
||||
except Exception as e:
|
||||
self._clear_streams()
|
||||
if self._transport_context is not None:
|
||||
self._transport_context = None
|
||||
raise ConnectionError(f"Failed to connect to MCP server: {e}") from e
|
||||
|
||||
async def disconnect(self) -> None:
|
||||
"""Close HTTP connection."""
|
||||
if not self._connected:
|
||||
return
|
||||
|
||||
try:
|
||||
# Clear streams first
|
||||
self._clear_streams()
|
||||
# await self._exit_stack.aclose()
|
||||
|
||||
# Exit transport context - this will clean up background tasks
|
||||
# Give a small delay to allow background tasks to complete
|
||||
if self._transport_context is not None:
|
||||
try:
|
||||
# Wait a tiny bit for any pending operations
|
||||
await asyncio.sleep(0.1)
|
||||
await self._transport_context.__aexit__(None, None, None)
|
||||
except (RuntimeError, asyncio.CancelledError) as e:
|
||||
# Ignore "exit cancel scope in different task" errors and cancellation
|
||||
# These happen when asyncio.run() closes the event loop
|
||||
# while background tasks are still running
|
||||
error_msg = str(e).lower()
|
||||
if "cancel scope" not in error_msg and "task" not in error_msg:
|
||||
# Only suppress cancel scope/task errors, re-raise others
|
||||
if isinstance(e, RuntimeError):
|
||||
raise
|
||||
# For CancelledError, just suppress it
|
||||
except BaseExceptionGroup as eg:
|
||||
# Handle exception groups from anyio task groups
|
||||
# Suppress if they contain cancel scope errors
|
||||
should_suppress = False
|
||||
for exc in eg.exceptions:
|
||||
error_msg = str(exc).lower()
|
||||
if "cancel scope" in error_msg or "task" in error_msg:
|
||||
should_suppress = True
|
||||
break
|
||||
if not should_suppress:
|
||||
raise
|
||||
except Exception as e:
|
||||
raise RuntimeError(
|
||||
f"Error during HTTP transport disconnect: {e}"
|
||||
) from e
|
||||
|
||||
self._connected = False
|
||||
|
||||
except Exception as e:
|
||||
# Log but don't raise - cleanup should be best effort
|
||||
import logging
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
logger.warning(f"Error during HTTP transport disconnect: {e}")
|
||||
|
||||
async def __aenter__(self) -> Self:
|
||||
"""Async context manager entry."""
|
||||
return await self.connect()
|
||||
|
||||
async def __aexit__(
|
||||
self,
|
||||
exc_type: type[BaseException] | None,
|
||||
exc_val: BaseException | None,
|
||||
exc_tb: Any,
|
||||
) -> None:
|
||||
"""Async context manager exit."""
|
||||
|
||||
await self.disconnect()
|
||||
@@ -1,113 +0,0 @@
|
||||
"""Server-Sent Events (SSE) transport for MCP servers."""
|
||||
|
||||
from typing import Any
|
||||
|
||||
from typing_extensions import Self
|
||||
|
||||
from crewai.mcp.transports.base import BaseTransport, TransportType
|
||||
|
||||
|
||||
class SSETransport(BaseTransport):
|
||||
"""SSE transport for connecting to remote MCP servers.
|
||||
|
||||
This transport connects to MCP servers using Server-Sent Events (SSE)
|
||||
for real-time streaming communication.
|
||||
|
||||
Example:
|
||||
```python
|
||||
transport = SSETransport(
|
||||
url="https://api.example.com/mcp/sse",
|
||||
headers={"Authorization": "Bearer ..."}
|
||||
)
|
||||
async with transport:
|
||||
# Use transport...
|
||||
```
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
url: str,
|
||||
headers: dict[str, str] | None = None,
|
||||
**kwargs: Any,
|
||||
) -> None:
|
||||
"""Initialize SSE transport.
|
||||
|
||||
Args:
|
||||
url: Server URL (e.g., "https://api.example.com/mcp/sse").
|
||||
headers: Optional HTTP headers.
|
||||
**kwargs: Additional transport options.
|
||||
"""
|
||||
super().__init__(**kwargs)
|
||||
self.url = url
|
||||
self.headers = headers or {}
|
||||
self._transport_context: Any = None
|
||||
|
||||
@property
|
||||
def transport_type(self) -> TransportType:
|
||||
"""Return the transport type."""
|
||||
return TransportType.SSE
|
||||
|
||||
async def connect(self) -> Self:
|
||||
"""Establish SSE connection to MCP server.
|
||||
|
||||
Returns:
|
||||
Self for method chaining.
|
||||
|
||||
Raises:
|
||||
ConnectionError: If connection fails.
|
||||
ImportError: If MCP SDK not available.
|
||||
"""
|
||||
if self._connected:
|
||||
return self
|
||||
|
||||
try:
|
||||
from mcp.client.sse import sse_client
|
||||
|
||||
self._transport_context = sse_client(
|
||||
self.url,
|
||||
headers=self.headers if self.headers else None,
|
||||
terminate_on_close=True,
|
||||
)
|
||||
|
||||
read, write = await self._transport_context.__aenter__()
|
||||
|
||||
self._set_streams(read=read, write=write)
|
||||
|
||||
return self
|
||||
|
||||
except ImportError as e:
|
||||
raise ImportError(
|
||||
"MCP library not available. Please install with: pip install mcp"
|
||||
) from e
|
||||
except Exception as e:
|
||||
self._clear_streams()
|
||||
raise ConnectionError(f"Failed to connect to SSE MCP server: {e}") from e
|
||||
|
||||
async def disconnect(self) -> None:
|
||||
"""Close SSE connection."""
|
||||
if not self._connected:
|
||||
return
|
||||
|
||||
try:
|
||||
self._clear_streams()
|
||||
if self._transport_context is not None:
|
||||
await self._transport_context.__aexit__(None, None, None)
|
||||
|
||||
except Exception as e:
|
||||
import logging
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
logger.warning(f"Error during SSE transport disconnect: {e}")
|
||||
|
||||
async def __aenter__(self) -> Self:
|
||||
"""Async context manager entry."""
|
||||
return await self.connect()
|
||||
|
||||
async def __aexit__(
|
||||
self,
|
||||
exc_type: type[BaseException] | None,
|
||||
exc_val: BaseException | None,
|
||||
exc_tb: Any,
|
||||
) -> None:
|
||||
"""Async context manager exit."""
|
||||
await self.disconnect()
|
||||
@@ -1,153 +0,0 @@
|
||||
"""Stdio transport for MCP servers running as local processes."""
|
||||
|
||||
import asyncio
|
||||
import os
|
||||
import subprocess
|
||||
from typing import Any
|
||||
|
||||
from typing_extensions import Self
|
||||
|
||||
from crewai.mcp.transports.base import BaseTransport, TransportType
|
||||
|
||||
|
||||
class StdioTransport(BaseTransport):
|
||||
"""Stdio transport for connecting to local MCP servers.
|
||||
|
||||
This transport connects to MCP servers running as local processes,
|
||||
communicating via standard input/output streams. Supports Python,
|
||||
Node.js, and other command-line servers.
|
||||
|
||||
Example:
|
||||
```python
|
||||
transport = StdioTransport(
|
||||
command="python",
|
||||
args=["path/to/server.py"],
|
||||
env={"API_KEY": "..."}
|
||||
)
|
||||
async with transport:
|
||||
# Use transport...
|
||||
```
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
command: str,
|
||||
args: list[str] | None = None,
|
||||
env: dict[str, str] | None = None,
|
||||
**kwargs: Any,
|
||||
) -> None:
|
||||
"""Initialize stdio transport.
|
||||
|
||||
Args:
|
||||
command: Command to execute (e.g., "python", "node", "npx").
|
||||
args: Command arguments (e.g., ["server.py"] or ["-y", "@mcp/server"]).
|
||||
env: Environment variables to pass to the process.
|
||||
**kwargs: Additional transport options.
|
||||
"""
|
||||
super().__init__(**kwargs)
|
||||
self.command = command
|
||||
self.args = args or []
|
||||
self.env = env or {}
|
||||
self._process: subprocess.Popen[bytes] | None = None
|
||||
self._transport_context: Any = None
|
||||
|
||||
@property
|
||||
def transport_type(self) -> TransportType:
|
||||
"""Return the transport type."""
|
||||
return TransportType.STDIO
|
||||
|
||||
async def connect(self) -> Self:
|
||||
"""Start the MCP server process and establish connection.
|
||||
|
||||
Returns:
|
||||
Self for method chaining.
|
||||
|
||||
Raises:
|
||||
ConnectionError: If process fails to start.
|
||||
ImportError: If MCP SDK not available.
|
||||
"""
|
||||
if self._connected:
|
||||
return self
|
||||
|
||||
try:
|
||||
from mcp import StdioServerParameters
|
||||
from mcp.client.stdio import stdio_client
|
||||
|
||||
process_env = os.environ.copy()
|
||||
process_env.update(self.env)
|
||||
|
||||
server_params = StdioServerParameters(
|
||||
command=self.command,
|
||||
args=self.args,
|
||||
env=process_env if process_env else None,
|
||||
)
|
||||
self._transport_context = stdio_client(server_params)
|
||||
|
||||
try:
|
||||
read, write = await self._transport_context.__aenter__()
|
||||
except Exception as e:
|
||||
import traceback
|
||||
|
||||
traceback.print_exc()
|
||||
self._transport_context = None
|
||||
raise ConnectionError(
|
||||
f"Failed to enter stdio transport context: {e}"
|
||||
) from e
|
||||
|
||||
self._set_streams(read=read, write=write)
|
||||
|
||||
return self
|
||||
|
||||
except ImportError as e:
|
||||
raise ImportError(
|
||||
"MCP library not available. Please install with: pip install mcp"
|
||||
) from e
|
||||
except Exception as e:
|
||||
self._clear_streams()
|
||||
if self._transport_context is not None:
|
||||
self._transport_context = None
|
||||
raise ConnectionError(f"Failed to start MCP server process: {e}") from e
|
||||
|
||||
async def disconnect(self) -> None:
|
||||
"""Terminate the MCP server process and close connection."""
|
||||
if not self._connected:
|
||||
return
|
||||
|
||||
try:
|
||||
self._clear_streams()
|
||||
|
||||
if self._transport_context is not None:
|
||||
await self._transport_context.__aexit__(None, None, None)
|
||||
|
||||
if self._process is not None:
|
||||
try:
|
||||
self._process.terminate()
|
||||
try:
|
||||
await asyncio.wait_for(self._process.wait(), timeout=5.0)
|
||||
except asyncio.TimeoutError:
|
||||
self._process.kill()
|
||||
await self._process.wait()
|
||||
# except ProcessLookupError:
|
||||
# pass
|
||||
finally:
|
||||
self._process = None
|
||||
|
||||
except Exception as e:
|
||||
# Log but don't raise - cleanup should be best effort
|
||||
import logging
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
logger.warning(f"Error during stdio transport disconnect: {e}")
|
||||
|
||||
async def __aenter__(self) -> Self:
|
||||
"""Async context manager entry."""
|
||||
return await self.connect()
|
||||
|
||||
async def __aexit__(
|
||||
self,
|
||||
exc_type: type[BaseException] | None,
|
||||
exc_val: BaseException | None,
|
||||
exc_tb: Any,
|
||||
) -> None:
|
||||
"""Async context manager exit."""
|
||||
await self.disconnect()
|
||||
@@ -1,75 +1,21 @@
|
||||
"""Utility functions for the crewai project module."""
|
||||
|
||||
from collections.abc import Callable
|
||||
from functools import wraps
|
||||
from typing import Any, ParamSpec, TypeVar, cast
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
from crewai.agents.cache.cache_handler import CacheHandler
|
||||
from functools import lru_cache
|
||||
from typing import ParamSpec, TypeVar, cast
|
||||
|
||||
|
||||
P = ParamSpec("P")
|
||||
R = TypeVar("R")
|
||||
cache = CacheHandler()
|
||||
|
||||
|
||||
def _make_hashable(arg: Any) -> Any:
|
||||
"""Convert argument to hashable form for caching.
|
||||
|
||||
Args:
|
||||
arg: The argument to convert.
|
||||
|
||||
Returns:
|
||||
Hashable representation of the argument.
|
||||
"""
|
||||
if isinstance(arg, BaseModel):
|
||||
return arg.model_dump_json()
|
||||
if isinstance(arg, dict):
|
||||
return tuple(sorted((k, _make_hashable(v)) for k, v in arg.items()))
|
||||
if isinstance(arg, list):
|
||||
return tuple(_make_hashable(item) for item in arg)
|
||||
if hasattr(arg, "__dict__"):
|
||||
return ("__instance__", id(arg))
|
||||
return arg
|
||||
|
||||
|
||||
def memoize(meth: Callable[P, R]) -> Callable[P, R]:
|
||||
"""Memoize a method by caching its results based on arguments.
|
||||
|
||||
Handles Pydantic BaseModel instances by converting them to JSON strings
|
||||
before hashing for cache lookup.
|
||||
|
||||
Args:
|
||||
meth: The method to memoize.
|
||||
|
||||
Returns:
|
||||
A memoized version of the method that caches results.
|
||||
"""
|
||||
|
||||
@wraps(meth)
|
||||
def wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
|
||||
"""Wrapper that converts arguments to hashable form before caching.
|
||||
|
||||
Args:
|
||||
*args: Positional arguments to the memoized method.
|
||||
**kwargs: Keyword arguments to the memoized method.
|
||||
|
||||
Returns:
|
||||
The result of the memoized method call.
|
||||
"""
|
||||
hashable_args = tuple(_make_hashable(arg) for arg in args)
|
||||
hashable_kwargs = tuple(
|
||||
sorted((k, _make_hashable(v)) for k, v in kwargs.items())
|
||||
)
|
||||
cache_key = str((hashable_args, hashable_kwargs))
|
||||
|
||||
cached_result: R | None = cache.read(tool=meth.__name__, input=cache_key)
|
||||
if cached_result is not None:
|
||||
return cached_result
|
||||
|
||||
result = meth(*args, **kwargs)
|
||||
cache.add(tool=meth.__name__, input=cache_key, output=result)
|
||||
return result
|
||||
|
||||
return cast(Callable[P, R], wrapper)
|
||||
return cast(Callable[P, R], lru_cache(typed=True)(meth))
|
||||
|
||||
@@ -67,44 +67,31 @@ def _prepare_documents_for_chromadb(
|
||||
ids: list[str] = []
|
||||
texts: list[str] = []
|
||||
metadatas: list[Mapping[str, str | int | float | bool]] = []
|
||||
seen_ids: dict[str, int] = {}
|
||||
|
||||
try:
|
||||
for doc in documents:
|
||||
if "doc_id" in doc:
|
||||
doc_id = str(doc["doc_id"])
|
||||
else:
|
||||
metadata = doc.get("metadata")
|
||||
if metadata and isinstance(metadata, dict) and "doc_id" in metadata:
|
||||
doc_id = str(metadata["doc_id"])
|
||||
else:
|
||||
content_for_hash = doc["content"]
|
||||
if metadata:
|
||||
metadata_str = json.dumps(metadata, sort_keys=True)
|
||||
content_for_hash = f"{content_for_hash}|{metadata_str}"
|
||||
doc_id = hashlib.sha256(content_for_hash.encode()).hexdigest()
|
||||
|
||||
for doc in documents:
|
||||
if "doc_id" in doc:
|
||||
ids.append(doc["doc_id"])
|
||||
else:
|
||||
content_for_hash = doc["content"]
|
||||
metadata = doc.get("metadata")
|
||||
if metadata:
|
||||
if isinstance(metadata, list):
|
||||
processed_metadata = metadata[0] if metadata and metadata[0] else {}
|
||||
else:
|
||||
processed_metadata = metadata
|
||||
else:
|
||||
processed_metadata = {}
|
||||
metadata_str = json.dumps(metadata, sort_keys=True)
|
||||
content_for_hash = f"{content_for_hash}|{metadata_str}"
|
||||
|
||||
if doc_id in seen_ids:
|
||||
idx = seen_ids[doc_id]
|
||||
texts[idx] = doc["content"]
|
||||
metadatas[idx] = processed_metadata
|
||||
content_hash = hashlib.blake2b(
|
||||
content_for_hash.encode(), digest_size=32
|
||||
).hexdigest()
|
||||
ids.append(content_hash)
|
||||
|
||||
texts.append(doc["content"])
|
||||
metadata = doc.get("metadata")
|
||||
if metadata:
|
||||
if isinstance(metadata, list):
|
||||
metadatas.append(metadata[0] if metadata and metadata[0] else {})
|
||||
else:
|
||||
idx = len(ids)
|
||||
ids.append(doc_id)
|
||||
texts.append(doc["content"])
|
||||
metadatas.append(processed_metadata)
|
||||
seen_ids[doc_id] = idx
|
||||
except Exception as e:
|
||||
raise ValueError(f"Error preparing documents for ChromaDB: {e}") from e
|
||||
metadatas.append(metadata)
|
||||
else:
|
||||
metadatas.append({})
|
||||
|
||||
return PreparedDocuments(ids, texts, metadatas)
|
||||
|
||||
|
||||
@@ -21,7 +21,7 @@ class GenerativeAiProvider(BaseEmbeddingsProvider[GoogleGenerativeAiEmbeddingFun
|
||||
validation_alias="EMBEDDINGS_GOOGLE_GENERATIVE_AI_MODEL_NAME",
|
||||
)
|
||||
api_key: str = Field(
|
||||
description="Google API key", validation_alias="EMBEDDINGS_GEMINI_API_KEY"
|
||||
description="Google API key", validation_alias="EMBEDDINGS_GOOGLE_API_KEY"
|
||||
)
|
||||
task_type: str = Field(
|
||||
default="RETRIEVAL_DOCUMENT",
|
||||
|
||||
@@ -525,11 +525,7 @@ class Task(BaseModel):
|
||||
tools=tools,
|
||||
)
|
||||
|
||||
if not self._guardrails and not self._guardrail:
|
||||
pydantic_output, json_output = self._export_output(result)
|
||||
else:
|
||||
pydantic_output, json_output = None, None
|
||||
|
||||
pydantic_output, json_output = self._export_output(result)
|
||||
task_output = TaskOutput(
|
||||
name=self.name or self.description,
|
||||
description=self.description,
|
||||
|
||||
@@ -1,162 +0,0 @@
|
||||
"""Native MCP tool wrapper for CrewAI agents.
|
||||
|
||||
This module provides a tool wrapper that reuses existing MCP client sessions
|
||||
for better performance and connection management.
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
from typing import Any
|
||||
|
||||
from crewai.tools import BaseTool
|
||||
|
||||
|
||||
class MCPNativeTool(BaseTool):
|
||||
"""Native MCP tool that reuses client sessions.
|
||||
|
||||
This tool wrapper is used when agents connect to MCP servers using
|
||||
structured configurations. It reuses existing client sessions for
|
||||
better performance and proper connection lifecycle management.
|
||||
|
||||
Unlike MCPToolWrapper which connects on-demand, this tool uses
|
||||
a shared MCP client instance that maintains a persistent connection.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
mcp_client: Any,
|
||||
tool_name: str,
|
||||
tool_schema: dict[str, Any],
|
||||
server_name: str,
|
||||
) -> None:
|
||||
"""Initialize native MCP tool.
|
||||
|
||||
Args:
|
||||
mcp_client: MCPClient instance with active session.
|
||||
tool_name: Original name of the tool on the MCP server.
|
||||
tool_schema: Schema information for the tool.
|
||||
server_name: Name of the MCP server for prefixing.
|
||||
"""
|
||||
# Create tool name with server prefix to avoid conflicts
|
||||
prefixed_name = f"{server_name}_{tool_name}"
|
||||
|
||||
# Handle args_schema properly - BaseTool expects a BaseModel subclass
|
||||
args_schema = tool_schema.get("args_schema")
|
||||
|
||||
# Only pass args_schema if it's provided
|
||||
kwargs = {
|
||||
"name": prefixed_name,
|
||||
"description": tool_schema.get(
|
||||
"description", f"Tool {tool_name} from {server_name}"
|
||||
),
|
||||
}
|
||||
|
||||
if args_schema is not None:
|
||||
kwargs["args_schema"] = args_schema
|
||||
|
||||
super().__init__(**kwargs)
|
||||
|
||||
# Set instance attributes after super().__init__
|
||||
self._mcp_client = mcp_client
|
||||
self._original_tool_name = tool_name
|
||||
self._server_name = server_name
|
||||
# self._logger = logging.getLogger(__name__)
|
||||
|
||||
@property
|
||||
def mcp_client(self) -> Any:
|
||||
"""Get the MCP client instance."""
|
||||
return self._mcp_client
|
||||
|
||||
@property
|
||||
def original_tool_name(self) -> str:
|
||||
"""Get the original tool name."""
|
||||
return self._original_tool_name
|
||||
|
||||
@property
|
||||
def server_name(self) -> str:
|
||||
"""Get the server name."""
|
||||
return self._server_name
|
||||
|
||||
def _run(self, **kwargs) -> str:
|
||||
"""Execute tool using the MCP client session.
|
||||
|
||||
Args:
|
||||
**kwargs: Arguments to pass to the MCP tool.
|
||||
|
||||
Returns:
|
||||
Result from the MCP tool execution.
|
||||
"""
|
||||
try:
|
||||
try:
|
||||
asyncio.get_running_loop()
|
||||
|
||||
import concurrent.futures
|
||||
|
||||
with concurrent.futures.ThreadPoolExecutor() as executor:
|
||||
coro = self._run_async(**kwargs)
|
||||
future = executor.submit(asyncio.run, coro)
|
||||
return future.result()
|
||||
except RuntimeError:
|
||||
return asyncio.run(self._run_async(**kwargs))
|
||||
|
||||
except Exception as e:
|
||||
raise RuntimeError(
|
||||
f"Error executing MCP tool {self.original_tool_name}: {e!s}"
|
||||
) from e
|
||||
|
||||
async def _run_async(self, **kwargs) -> str:
|
||||
"""Async implementation of tool execution.
|
||||
|
||||
Args:
|
||||
**kwargs: Arguments to pass to the MCP tool.
|
||||
|
||||
Returns:
|
||||
Result from the MCP tool execution.
|
||||
"""
|
||||
# Note: Since we use asyncio.run() which creates a new event loop each time,
|
||||
# Always reconnect on-demand because asyncio.run() creates new event loops per call
|
||||
# All MCP transport context managers (stdio, streamablehttp_client, sse_client)
|
||||
# use anyio.create_task_group() which can't span different event loops
|
||||
if self._mcp_client.connected:
|
||||
await self._mcp_client.disconnect()
|
||||
|
||||
await self._mcp_client.connect()
|
||||
|
||||
try:
|
||||
result = await self._mcp_client.call_tool(self.original_tool_name, kwargs)
|
||||
|
||||
except Exception as e:
|
||||
error_str = str(e).lower()
|
||||
if (
|
||||
"not connected" in error_str
|
||||
or "connection" in error_str
|
||||
or "send" in error_str
|
||||
):
|
||||
await self._mcp_client.disconnect()
|
||||
await self._mcp_client.connect()
|
||||
# Retry the call
|
||||
result = await self._mcp_client.call_tool(
|
||||
self.original_tool_name, kwargs
|
||||
)
|
||||
else:
|
||||
raise
|
||||
|
||||
finally:
|
||||
# Always disconnect after tool call to ensure clean context manager lifecycle
|
||||
# This prevents "exit cancel scope in different task" errors
|
||||
# All transport context managers must be exited in the same event loop they were entered
|
||||
await self._mcp_client.disconnect()
|
||||
|
||||
# Extract result content
|
||||
if isinstance(result, str):
|
||||
return result
|
||||
|
||||
# Handle various result formats
|
||||
if hasattr(result, "content") and result.content:
|
||||
if isinstance(result.content, list) and len(result.content) > 0:
|
||||
content_item = result.content[0]
|
||||
if hasattr(content_item, "text"):
|
||||
return str(content_item.text)
|
||||
return str(content_item)
|
||||
return str(result.content)
|
||||
|
||||
return str(result)
|
||||
@@ -22,12 +22,12 @@
|
||||
"summarize_instruction": "Summarize the following text, make sure to include all the important information: {group}",
|
||||
"summary": "This is a summary of our conversation so far:\n{merged_summary}",
|
||||
"manager_request": "Your best answer to your coworker asking you this, accounting for the context shared.",
|
||||
"formatted_task_instructions": "Ensure your final answer strictly adheres to the following OpenAPI schema: {output_format}\n\nDo not include the OpenAPI schema in the final output. Ensure the final output does not include any code block markers like ```json or ```python.",
|
||||
"formatted_task_instructions": "Ensure your final answer contains only the content in the following format: {output_format}\n\nEnsure the final output does not include any code block markers like ```json or ```python.",
|
||||
"conversation_history_instruction": "You are a member of a crew collaborating to achieve a common goal. Your task is a specific action that contributes to this larger objective. For additional context, please review the conversation history between you and the user that led to the initiation of this crew. Use any relevant information or feedback from the conversation to inform your task execution and ensure your response aligns with both the immediate task and the crew's overall goals.",
|
||||
"feedback_instructions": "User feedback: {feedback}\nInstructions: Use this feedback to enhance the next output iteration.\nNote: Do not respond or add commentary.",
|
||||
"lite_agent_system_prompt_with_tools": "You are {role}. {backstory}\nYour personal goal is: {goal}\n\nYou ONLY have access to the following tools, and should NEVER make up tools that are not listed here:\n\n{tools}\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: you should always think about what to do\nAction: the action to take, only one name of [{tool_names}], just the name, exactly as it's written.\nAction Input: the input to the action, just a simple JSON object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce all necessary information is gathered, return the following format:\n\n```\nThought: I now know the final answer\nFinal Answer: the final answer to the original input question\n```",
|
||||
"lite_agent_system_prompt_without_tools": "You are {role}. {backstory}\nYour personal goal is: {goal}\n\nTo give my best complete final answer to the task respond using the exact following format:\n\nThought: I now can give a great answer\nFinal Answer: Your final answer must be the great and the most complete as possible, it must be outcome described.\n\nI MUST use these formats, my job depends on it!",
|
||||
"lite_agent_response_format": "Ensure your final answer strictly adheres to the following OpenAPI schema: {response_format}\n\nDo not include the OpenAPI schema in the final output. Ensure the final output does not include any code block markers like ```json or ```python.",
|
||||
"lite_agent_response_format": "\nIMPORTANT: Your final answer MUST contain all the information requested in the following format: {response_format}\n\nIMPORTANT: Ensure the final output does not include any code block markers like ```json or ```python.",
|
||||
"knowledge_search_query": "The original query is: {task_prompt}.",
|
||||
"knowledge_search_query_system_prompt": "Your goal is to rewrite the user query so that it is optimized for retrieval from a vector database. Consider how the query will be used to find relevant documents, and aim to make it more specific and context-aware. \n\n Do not include any other text than the rewritten query, especially any preamble or postamble and only add expected output format if its relevant to the rewritten query. \n\n Focus on the key words of the intended task and to retrieve the most relevant information. \n\n There will be some extra context provided that might need to be removed such as expected_output formats structured_outputs and other instructions."
|
||||
},
|
||||
|
||||
@@ -127,7 +127,7 @@ def handle_max_iterations_exceeded(
|
||||
messages: list[LLMMessage],
|
||||
llm: LLM | BaseLLM,
|
||||
callbacks: list[TokenCalcHandler],
|
||||
) -> AgentFinish:
|
||||
) -> AgentAction | AgentFinish:
|
||||
"""Handles the case when the maximum number of iterations is exceeded. Performs one more LLM call to get the final answer.
|
||||
|
||||
Args:
|
||||
@@ -139,7 +139,7 @@ def handle_max_iterations_exceeded(
|
||||
callbacks: List of callbacks for the LLM call.
|
||||
|
||||
Returns:
|
||||
AgentFinish with the final answer after exceeding max iterations.
|
||||
The final formatted answer after exceeding max iterations.
|
||||
"""
|
||||
printer.print(
|
||||
content="Maximum iterations reached. Requesting final answer.",
|
||||
@@ -157,7 +157,7 @@ def handle_max_iterations_exceeded(
|
||||
|
||||
# Perform one more LLM call to get the final answer
|
||||
answer = llm.call(
|
||||
messages,
|
||||
messages, # type: ignore[arg-type]
|
||||
callbacks=callbacks,
|
||||
)
|
||||
|
||||
@@ -168,16 +168,8 @@ def handle_max_iterations_exceeded(
|
||||
)
|
||||
raise ValueError("Invalid response from LLM call - None or empty.")
|
||||
|
||||
formatted = format_answer(answer=answer)
|
||||
|
||||
# If format_answer returned an AgentAction, convert it to AgentFinish
|
||||
if isinstance(formatted, AgentFinish):
|
||||
return formatted
|
||||
return AgentFinish(
|
||||
thought=formatted.thought,
|
||||
output=formatted.text,
|
||||
text=formatted.text,
|
||||
)
|
||||
# Return the formatted answer, regardless of its type
|
||||
return format_answer(answer=answer)
|
||||
|
||||
|
||||
def format_message_for_llm(
|
||||
@@ -257,10 +249,10 @@ def get_llm_response(
|
||||
"""
|
||||
try:
|
||||
answer = llm.call(
|
||||
messages,
|
||||
messages, # type: ignore[arg-type]
|
||||
callbacks=callbacks,
|
||||
from_task=from_task,
|
||||
from_agent=from_agent, # type: ignore[arg-type]
|
||||
from_agent=from_agent,
|
||||
response_model=response_model,
|
||||
)
|
||||
except Exception as e:
|
||||
@@ -302,8 +294,8 @@ def handle_agent_action_core(
|
||||
formatted_answer: AgentAction,
|
||||
tool_result: ToolResult,
|
||||
messages: list[LLMMessage] | None = None,
|
||||
step_callback: Callable | None = None, # type: ignore[type-arg]
|
||||
show_logs: Callable | None = None, # type: ignore[type-arg]
|
||||
step_callback: Callable | None = None,
|
||||
show_logs: Callable | None = None,
|
||||
) -> AgentAction | AgentFinish:
|
||||
"""Core logic for handling agent actions and tool results.
|
||||
|
||||
@@ -489,7 +481,7 @@ def summarize_messages(
|
||||
),
|
||||
]
|
||||
summary = llm.call(
|
||||
messages,
|
||||
messages, # type: ignore[arg-type]
|
||||
callbacks=callbacks,
|
||||
)
|
||||
summarized_contents.append({"content": str(summary)})
|
||||
|
||||
@@ -10,9 +10,9 @@ from pydantic import BaseModel, ValidationError
|
||||
from typing_extensions import Unpack
|
||||
|
||||
from crewai.agents.agent_builder.utilities.base_output_converter import OutputConverter
|
||||
from crewai.utilities.i18n import get_i18n
|
||||
from crewai.utilities.internal_instructor import InternalInstructor
|
||||
from crewai.utilities.printer import Printer
|
||||
from crewai.utilities.pydantic_schema_parser import PydanticSchemaParser
|
||||
|
||||
|
||||
if TYPE_CHECKING:
|
||||
@@ -22,7 +22,6 @@ if TYPE_CHECKING:
|
||||
from crewai.llms.base_llm import BaseLLM
|
||||
|
||||
_JSON_PATTERN: Final[re.Pattern[str]] = re.compile(r"({.*})", re.DOTALL)
|
||||
_I18N = get_i18n()
|
||||
|
||||
|
||||
class ConverterError(Exception):
|
||||
@@ -88,7 +87,8 @@ class Converter(OutputConverter):
|
||||
result = self.model.model_validate(result)
|
||||
elif isinstance(result, str):
|
||||
try:
|
||||
result = self.model.model_validate_json(result)
|
||||
parsed = json.loads(result)
|
||||
result = self.model.model_validate(parsed)
|
||||
except Exception as parse_err:
|
||||
raise ConverterError(
|
||||
f"Failed to convert partial JSON result into Pydantic: {parse_err}"
|
||||
@@ -172,16 +172,6 @@ def convert_to_model(
|
||||
model = output_pydantic or output_json
|
||||
if model is None:
|
||||
return result
|
||||
|
||||
if converter_cls:
|
||||
return convert_with_instructions(
|
||||
result=result,
|
||||
model=model,
|
||||
is_json_output=bool(output_json),
|
||||
agent=agent,
|
||||
converter_cls=converter_cls,
|
||||
)
|
||||
|
||||
try:
|
||||
escaped_result = json.dumps(json.loads(result, strict=False))
|
||||
return validate_model(
|
||||
@@ -261,7 +251,7 @@ def handle_partial_json(
|
||||
except json.JSONDecodeError:
|
||||
pass
|
||||
except ValidationError:
|
||||
raise
|
||||
pass
|
||||
except Exception as e:
|
||||
Printer().print(
|
||||
content=f"Unexpected error during partial JSON handling: {type(e).__name__}: {e}. Attempting alternative conversion method.",
|
||||
@@ -345,26 +335,25 @@ def get_conversion_instructions(
|
||||
Returns:
|
||||
|
||||
"""
|
||||
instructions = ""
|
||||
instructions = "Please convert the following text into valid JSON."
|
||||
if (
|
||||
llm
|
||||
and not isinstance(llm, str)
|
||||
and hasattr(llm, "supports_function_calling")
|
||||
and llm.supports_function_calling()
|
||||
):
|
||||
schema_dict = generate_model_description(model)
|
||||
schema = json.dumps(schema_dict, indent=2)
|
||||
formatted_task_instructions = _I18N.slice("formatted_task_instructions").format(
|
||||
output_format=schema
|
||||
model_schema = PydanticSchemaParser(model=model).get_schema()
|
||||
instructions += (
|
||||
f"\n\nOutput ONLY the valid JSON and nothing else.\n\n"
|
||||
f"Use this format exactly:\n```json\n{model_schema}\n```"
|
||||
)
|
||||
instructions += formatted_task_instructions
|
||||
else:
|
||||
model_description = generate_model_description(model)
|
||||
schema_json = json.dumps(model_description, indent=2)
|
||||
formatted_task_instructions = _I18N.slice("formatted_task_instructions").format(
|
||||
output_format=schema_json
|
||||
schema_json = json.dumps(model_description["json_schema"]["schema"], indent=2)
|
||||
instructions += (
|
||||
f"\n\nOutput ONLY the valid JSON and nothing else.\n\n"
|
||||
f"Use this format exactly:\n```json\n{schema_json}\n```"
|
||||
)
|
||||
instructions += formatted_task_instructions
|
||||
return instructions
|
||||
|
||||
|
||||
|
||||
@@ -147,7 +147,7 @@ def test_custom_llm():
|
||||
assert agent.llm.model == "gpt-4"
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_execution():
|
||||
agent = Agent(
|
||||
role="test role",
|
||||
@@ -166,7 +166,7 @@ def test_agent_execution():
|
||||
assert output == "1 + 1 is 2"
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_execution_with_tools():
|
||||
@tool
|
||||
def multiplier(first_number: int, second_number: int) -> float:
|
||||
@@ -211,7 +211,7 @@ def test_agent_execution_with_tools():
|
||||
assert received_events[0].tool_args == {"first_number": 3, "second_number": 4}
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_logging_tool_usage():
|
||||
@tool
|
||||
def multiplier(first_number: int, second_number: int) -> float:
|
||||
@@ -245,7 +245,7 @@ def test_logging_tool_usage():
|
||||
assert agent.tools_handler.last_used_tool.arguments == tool_usage.arguments
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_cache_hitting():
|
||||
@tool
|
||||
def multiplier(first_number: int, second_number: int) -> float:
|
||||
@@ -330,7 +330,7 @@ def test_cache_hitting():
|
||||
assert received_events[0].from_cache
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_disabling_cache_for_agent():
|
||||
@tool
|
||||
def multiplier(first_number: int, second_number: int) -> float:
|
||||
@@ -394,7 +394,7 @@ def test_disabling_cache_for_agent():
|
||||
read.assert_not_called()
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_execution_with_specific_tools():
|
||||
@tool
|
||||
def multiplier(first_number: int, second_number: int) -> float:
|
||||
@@ -417,7 +417,7 @@ def test_agent_execution_with_specific_tools():
|
||||
assert output == "The result of the multiplication is 12."
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_powered_by_new_o_model_family_that_allows_skipping_tool():
|
||||
@tool
|
||||
def multiplier(first_number: int, second_number: int) -> float:
|
||||
@@ -443,7 +443,7 @@ def test_agent_powered_by_new_o_model_family_that_allows_skipping_tool():
|
||||
assert output == "12"
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_powered_by_new_o_model_family_that_uses_tool():
|
||||
@tool
|
||||
def comapny_customer_data() -> str:
|
||||
@@ -469,7 +469,7 @@ def test_agent_powered_by_new_o_model_family_that_uses_tool():
|
||||
assert output == "42"
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_custom_max_iterations():
|
||||
@tool
|
||||
def get_final_answer() -> float:
|
||||
@@ -508,50 +508,10 @@ def test_agent_custom_max_iterations():
|
||||
assert isinstance(result, str)
|
||||
assert len(result) > 0
|
||||
assert call_count > 0
|
||||
# With max_iter=1, expect 2 calls:
|
||||
# - Call 1: iteration 0
|
||||
# - Call 2: iteration 1 (max reached, handle_max_iterations_exceeded called, then loop breaks)
|
||||
assert call_count == 2
|
||||
assert call_count == 3
|
||||
|
||||
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
@pytest.mark.timeout(30)
|
||||
def test_agent_max_iterations_stops_loop():
|
||||
"""Test that agent execution terminates when max_iter is reached."""
|
||||
|
||||
@tool
|
||||
def get_data(step: str) -> str:
|
||||
"""Get data for a step. Always returns data requiring more steps."""
|
||||
return f"Data for {step}: incomplete, need to query more steps."
|
||||
|
||||
agent = Agent(
|
||||
role="data collector",
|
||||
goal="collect data using the get_data tool",
|
||||
backstory="You must use the get_data tool extensively",
|
||||
max_iter=2,
|
||||
allow_delegation=False,
|
||||
)
|
||||
|
||||
task = Task(
|
||||
description="Use get_data tool for step1, step2, step3, step4, step5, step6, step7, step8, step9, and step10. Do NOT stop until you've called it for ALL steps.",
|
||||
expected_output="A summary of all data collected",
|
||||
)
|
||||
|
||||
result = agent.execute_task(
|
||||
task=task,
|
||||
tools=[get_data],
|
||||
)
|
||||
|
||||
assert result is not None
|
||||
assert isinstance(result, str)
|
||||
|
||||
assert agent.agent_executor.iterations <= agent.max_iter + 2, (
|
||||
f"Agent ran {agent.agent_executor.iterations} iterations "
|
||||
f"but should stop around {agent.max_iter + 1}. "
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
def test_agent_repeated_tool_usage(capsys):
|
||||
"""Test that agents handle repeated tool usage appropriately.
|
||||
|
||||
@@ -600,7 +560,7 @@ def test_agent_repeated_tool_usage(capsys):
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_repeated_tool_usage_check_even_with_disabled_cache(capsys):
|
||||
@tool
|
||||
def get_final_answer(anything: str) -> float:
|
||||
@@ -643,7 +603,7 @@ def test_agent_repeated_tool_usage_check_even_with_disabled_cache(capsys):
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_moved_on_after_max_iterations():
|
||||
@tool
|
||||
def get_final_answer() -> float:
|
||||
@@ -670,7 +630,7 @@ def test_agent_moved_on_after_max_iterations():
|
||||
assert output == "42"
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_respect_the_max_rpm_set(capsys):
|
||||
@tool
|
||||
def get_final_answer() -> float:
|
||||
@@ -704,7 +664,7 @@ def test_agent_respect_the_max_rpm_set(capsys):
|
||||
moveon.assert_called()
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_respect_the_max_rpm_set_over_crew_rpm(capsys):
|
||||
from unittest.mock import patch
|
||||
|
||||
@@ -742,7 +702,7 @@ def test_agent_respect_the_max_rpm_set_over_crew_rpm(capsys):
|
||||
moveon.assert_not_called()
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_without_max_rpm_respects_crew_rpm(capsys):
|
||||
from unittest.mock import patch
|
||||
|
||||
@@ -802,7 +762,7 @@ def test_agent_without_max_rpm_respects_crew_rpm(capsys):
|
||||
moveon.assert_called_once()
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_error_on_parsing_tool(capsys):
|
||||
from unittest.mock import patch
|
||||
|
||||
@@ -845,7 +805,7 @@ def test_agent_error_on_parsing_tool(capsys):
|
||||
assert "Error on parsing tool." in captured.out
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_remembers_output_format_after_using_tools_too_many_times():
|
||||
from unittest.mock import patch
|
||||
|
||||
@@ -880,7 +840,7 @@ def test_agent_remembers_output_format_after_using_tools_too_many_times():
|
||||
remember_format.assert_called()
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_use_specific_tasks_output_as_context(capsys):
|
||||
agent1 = Agent(role="test role", goal="test goal", backstory="test backstory")
|
||||
agent2 = Agent(role="test role2", goal="test goal2", backstory="test backstory2")
|
||||
@@ -907,7 +867,7 @@ def test_agent_use_specific_tasks_output_as_context(capsys):
|
||||
assert "hi" in result.raw.lower() or "hello" in result.raw.lower()
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_step_callback():
|
||||
class StepCallback:
|
||||
def callback(self, step):
|
||||
@@ -941,7 +901,7 @@ def test_agent_step_callback():
|
||||
callback.assert_called()
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_function_calling_llm():
|
||||
from crewai.llm import LLM
|
||||
llm = LLM(model="gpt-4o", is_litellm=True)
|
||||
@@ -988,7 +948,7 @@ def test_agent_function_calling_llm():
|
||||
mock_original_tool_calling.assert_called()
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_tool_result_as_answer_is_the_final_answer_for_the_agent():
|
||||
from crewai.tools import BaseTool
|
||||
|
||||
@@ -1018,7 +978,7 @@ def test_tool_result_as_answer_is_the_final_answer_for_the_agent():
|
||||
assert result.raw == "Howdy!"
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_tool_usage_information_is_appended_to_agent():
|
||||
from crewai.tools import BaseTool
|
||||
|
||||
@@ -1073,7 +1033,7 @@ def test_agent_definition_based_on_dict():
|
||||
|
||||
|
||||
# test for human input
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_human_input():
|
||||
# Agent configuration
|
||||
config = {
|
||||
@@ -1221,7 +1181,7 @@ Thought:<|eot_id|>
|
||||
assert mock_format_prompt.return_value == expected_prompt
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_task_allow_crewai_trigger_context():
|
||||
from crewai import Crew
|
||||
|
||||
@@ -1242,7 +1202,7 @@ def test_task_allow_crewai_trigger_context():
|
||||
assert "Trigger Payload: Important context data" in prompt
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_task_without_allow_crewai_trigger_context():
|
||||
from crewai import Crew
|
||||
|
||||
@@ -1265,7 +1225,7 @@ def test_task_without_allow_crewai_trigger_context():
|
||||
assert "Important context data" not in prompt
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_task_allow_crewai_trigger_context_no_payload():
|
||||
from crewai import Crew
|
||||
|
||||
@@ -1287,7 +1247,7 @@ def test_task_allow_crewai_trigger_context_no_payload():
|
||||
assert "Trigger Payload:" not in prompt
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_do_not_allow_crewai_trigger_context_for_first_task_hierarchical():
|
||||
from crewai import Crew
|
||||
|
||||
@@ -1316,7 +1276,7 @@ def test_do_not_allow_crewai_trigger_context_for_first_task_hierarchical():
|
||||
assert "Trigger Payload: Initial context data" not in first_prompt
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_first_task_auto_inject_trigger():
|
||||
from crewai import Crew
|
||||
|
||||
@@ -1349,7 +1309,7 @@ def test_first_task_auto_inject_trigger():
|
||||
assert "Trigger Payload:" not in second_prompt
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_ensure_first_task_allow_crewai_trigger_context_is_false_does_not_inject():
|
||||
from crewai import Crew
|
||||
|
||||
@@ -1554,7 +1514,7 @@ def test_agent_with_additional_kwargs():
|
||||
assert agent.llm.frequency_penalty == 0.1
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_llm_call():
|
||||
llm = LLM(model="gpt-3.5-turbo")
|
||||
messages = [{"role": "user", "content": "Say 'Hello, World!'"}]
|
||||
@@ -1563,7 +1523,7 @@ def test_llm_call():
|
||||
assert "Hello, World!" in response
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_llm_call_with_error():
|
||||
llm = LLM(model="non-existent-model")
|
||||
messages = [{"role": "user", "content": "This should fail"}]
|
||||
@@ -1572,7 +1532,7 @@ def test_llm_call_with_error():
|
||||
llm.call(messages)
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_handle_context_length_exceeds_limit():
|
||||
# Import necessary modules
|
||||
from crewai.utilities.agent_utils import handle_context_length
|
||||
@@ -1625,7 +1585,7 @@ def test_handle_context_length_exceeds_limit():
|
||||
mock_summarize.assert_called_once()
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_handle_context_length_exceeds_limit_cli_no():
|
||||
agent = Agent(
|
||||
role="test role",
|
||||
@@ -1700,7 +1660,7 @@ def test_agent_with_all_llm_attributes():
|
||||
assert agent.llm.api_key == "sk-your-api-key-here"
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_llm_call_with_all_attributes():
|
||||
llm = LLM(
|
||||
model="gpt-3.5-turbo",
|
||||
@@ -1717,7 +1677,7 @@ def test_llm_call_with_all_attributes():
|
||||
assert "STOP" not in response
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_with_ollama_llama3():
|
||||
agent = Agent(
|
||||
role="test role",
|
||||
@@ -1738,7 +1698,7 @@ def test_agent_with_ollama_llama3():
|
||||
assert "Llama3" in response or "AI" in response or "language model" in response
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_llm_call_with_ollama_llama3():
|
||||
llm = LLM(
|
||||
model="ollama/llama3.2:3b",
|
||||
@@ -1757,7 +1717,7 @@ def test_llm_call_with_ollama_llama3():
|
||||
assert "Llama3" in response or "AI" in response or "language model" in response
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_execute_task_basic():
|
||||
agent = Agent(
|
||||
role="test role",
|
||||
@@ -1776,7 +1736,7 @@ def test_agent_execute_task_basic():
|
||||
assert "4" in result
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_execute_task_with_context():
|
||||
agent = Agent(
|
||||
role="test role",
|
||||
@@ -1798,7 +1758,7 @@ def test_agent_execute_task_with_context():
|
||||
assert "fox" in result.lower() and "dog" in result.lower()
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_execute_task_with_tool():
|
||||
@tool
|
||||
def dummy_tool(query: str) -> str:
|
||||
@@ -1823,7 +1783,7 @@ def test_agent_execute_task_with_tool():
|
||||
assert "Dummy result for: test query" in result
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_execute_task_with_custom_llm():
|
||||
agent = Agent(
|
||||
role="test role",
|
||||
@@ -1844,7 +1804,7 @@ def test_agent_execute_task_with_custom_llm():
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_execute_task_with_ollama():
|
||||
agent = Agent(
|
||||
role="test role",
|
||||
@@ -1864,7 +1824,7 @@ def test_agent_execute_task_with_ollama():
|
||||
assert "AI" in result or "artificial intelligence" in result.lower()
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_with_knowledge_sources():
|
||||
content = "Brandon's favorite color is red and he likes Mexican food."
|
||||
string_source = StringKnowledgeSource(content=content)
|
||||
@@ -1896,7 +1856,7 @@ def test_agent_with_knowledge_sources():
|
||||
assert "red" in result.raw.lower()
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_with_knowledge_sources_with_query_limit_and_score_threshold():
|
||||
content = "Brandon's favorite color is red and he likes Mexican food."
|
||||
string_source = StringKnowledgeSource(content=content)
|
||||
@@ -1944,7 +1904,7 @@ def test_agent_with_knowledge_sources_with_query_limit_and_score_threshold():
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_with_knowledge_sources_with_query_limit_and_score_threshold_default():
|
||||
content = "Brandon's favorite color is red and he likes Mexican food."
|
||||
string_source = StringKnowledgeSource(content=content)
|
||||
@@ -1993,7 +1953,7 @@ def test_agent_with_knowledge_sources_with_query_limit_and_score_threshold_defau
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_with_knowledge_sources_extensive_role():
|
||||
content = "Brandon's favorite color is red and he likes Mexican food."
|
||||
string_source = StringKnowledgeSource(content=content)
|
||||
@@ -2029,7 +1989,7 @@ def test_agent_with_knowledge_sources_extensive_role():
|
||||
assert "red" in result.raw.lower()
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_with_knowledge_sources_works_with_copy():
|
||||
content = "Brandon's favorite color is red and he likes Mexican food."
|
||||
string_source = StringKnowledgeSource(content=content)
|
||||
@@ -2068,7 +2028,7 @@ def test_agent_with_knowledge_sources_works_with_copy():
|
||||
assert isinstance(agent_copy.llm, BaseLLM)
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_with_knowledge_sources_generate_search_query():
|
||||
content = "Brandon's favorite color is red and he likes Mexican food."
|
||||
string_source = StringKnowledgeSource(content=content)
|
||||
@@ -2157,14 +2117,15 @@ def test_agent_with_only_crewai_knowledge():
|
||||
goal="Provide information based on knowledge sources",
|
||||
backstory="You have access to specific knowledge sources.",
|
||||
llm=LLM(
|
||||
model="gpt-4o-mini",
|
||||
model="openrouter/openai/gpt-4o-mini",
|
||||
api_key=os.getenv("OPENROUTER_API_KEY"),
|
||||
),
|
||||
)
|
||||
|
||||
# Create a task that requires the agent to use the knowledge
|
||||
task = Task(
|
||||
description="What is Vidit's favorite color?",
|
||||
expected_output="Vidit's favorite color.",
|
||||
expected_output="Vidit's favorclearite color.",
|
||||
agent=agent,
|
||||
)
|
||||
|
||||
@@ -2202,7 +2163,7 @@ def test_agent_knowledege_with_crewai_knowledge():
|
||||
crew_knowledge.query.assert_called_once()
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_litellm_auth_error_handling():
|
||||
"""Test that LiteLLM authentication errors are handled correctly and not retried."""
|
||||
from litellm import AuthenticationError as LiteLLMAuthenticationError
|
||||
@@ -2331,7 +2292,7 @@ def test_litellm_anthropic_error_handling():
|
||||
mock_llm_call.assert_called_once()
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_get_knowledge_search_query():
|
||||
"""Test that _get_knowledge_search_query calls the LLM with the correct prompts."""
|
||||
from crewai.utilities.i18n import I18N
|
||||
|
||||
@@ -1,9 +1,18 @@
|
||||
"""Test A2A wrapper is only applied when a2a is passed to Agent."""
|
||||
|
||||
from unittest.mock import patch
|
||||
|
||||
import pytest
|
||||
|
||||
from crewai import Agent
|
||||
from crewai.a2a.config import A2AConfig
|
||||
|
||||
import a2a # noqa: F401
|
||||
try:
|
||||
import a2a # noqa: F401
|
||||
|
||||
A2A_SDK_INSTALLED = True
|
||||
except ImportError:
|
||||
A2A_SDK_INSTALLED = False
|
||||
|
||||
|
||||
def test_agent_without_a2a_has_no_wrapper():
|
||||
@@ -18,6 +27,10 @@ def test_agent_without_a2a_has_no_wrapper():
|
||||
assert callable(agent.execute_task)
|
||||
|
||||
|
||||
@pytest.mark.skipif(
|
||||
True,
|
||||
reason="Requires a2a-sdk to be installed. This test verifies wrapper is applied when a2a is set.",
|
||||
)
|
||||
def test_agent_with_a2a_has_wrapper():
|
||||
"""Verify that agents with a2a get the wrapper applied."""
|
||||
a2a_config = A2AConfig(
|
||||
@@ -36,6 +49,7 @@ def test_agent_with_a2a_has_wrapper():
|
||||
assert callable(agent.execute_task)
|
||||
|
||||
|
||||
@pytest.mark.skipif(not A2A_SDK_INSTALLED, reason="Requires a2a-sdk to be installed")
|
||||
def test_agent_with_a2a_creates_successfully():
|
||||
"""Verify that creating an agent with a2a succeeds and applies wrapper."""
|
||||
a2a_config = A2AConfig(
|
||||
@@ -75,6 +89,7 @@ def test_multiple_agents_without_a2a():
|
||||
assert callable(agent2.execute_task)
|
||||
|
||||
|
||||
@pytest.mark.skipif(not A2A_SDK_INSTALLED, reason="Requires a2a-sdk to be installed")
|
||||
def test_wrapper_is_applied_differently_per_instance():
|
||||
"""Verify that agents with and without a2a have different execute_task methods."""
|
||||
agent_without_a2a = Agent(
|
||||
|
||||
@@ -70,7 +70,7 @@ class ResearchResult(BaseModel):
|
||||
sources: list[str] = Field(description="List of sources used")
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
@pytest.mark.parametrize("verbose", [True, False])
|
||||
def test_lite_agent_created_with_correct_parameters(monkeypatch, verbose):
|
||||
"""Test that LiteAgent is created with the correct parameters when Agent.kickoff() is called."""
|
||||
@@ -130,7 +130,7 @@ def test_lite_agent_created_with_correct_parameters(monkeypatch, verbose):
|
||||
assert created_lite_agent["response_format"] == TestResponse
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_lite_agent_with_tools():
|
||||
"""Test that Agent can use tools."""
|
||||
# Create a LiteAgent with tools
|
||||
@@ -174,7 +174,7 @@ def test_lite_agent_with_tools():
|
||||
assert event.tool_name == "search_web"
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_lite_agent_structured_output():
|
||||
"""Test that Agent can return a simple structured output."""
|
||||
|
||||
@@ -217,7 +217,7 @@ def test_lite_agent_structured_output():
|
||||
return result
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_lite_agent_returns_usage_metrics():
|
||||
"""Test that LiteAgent returns usage metrics."""
|
||||
llm = LLM(model="gpt-4o-mini")
|
||||
@@ -238,7 +238,7 @@ def test_lite_agent_returns_usage_metrics():
|
||||
assert result.usage_metrics["total_tokens"] > 0
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
@pytest.mark.asyncio
|
||||
async def test_lite_agent_returns_usage_metrics_async():
|
||||
"""Test that LiteAgent returns usage metrics when run asynchronously."""
|
||||
@@ -261,6 +261,25 @@ async def test_lite_agent_returns_usage_metrics_async():
|
||||
assert result.usage_metrics["total_tokens"] > 0
|
||||
|
||||
|
||||
class TestFlow(Flow):
|
||||
"""A test flow that creates and runs an agent."""
|
||||
|
||||
def __init__(self, llm, tools):
|
||||
self.llm = llm
|
||||
self.tools = tools
|
||||
super().__init__()
|
||||
|
||||
@start()
|
||||
def start(self):
|
||||
agent = Agent(
|
||||
role="Test Agent",
|
||||
goal="Test Goal",
|
||||
backstory="Test Backstory",
|
||||
llm=self.llm,
|
||||
tools=self.tools,
|
||||
)
|
||||
return agent.kickoff("Test query")
|
||||
|
||||
|
||||
def verify_agent_parent_flow(result, agent, flow):
|
||||
"""Verify that both the result and agent have the correct parent flow."""
|
||||
@@ -314,7 +333,7 @@ def test_sets_parent_flow_when_inside_flow():
|
||||
assert captured_agent.parent_flow is flow
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_guardrail_is_called_using_string():
|
||||
guardrail_events = defaultdict(list)
|
||||
from crewai.events.event_types import (
|
||||
@@ -363,12 +382,12 @@ def test_guardrail_is_called_using_string():
|
||||
assert not guardrail_events["completed"][0].success
|
||||
assert guardrail_events["completed"][1].success
|
||||
assert (
|
||||
"top 10 best Brazilian soccer players" in result.raw or
|
||||
"Brazilian players" in result.raw
|
||||
"Here are the top 10 best soccer players in the world, focusing exclusively on Brazilian players"
|
||||
in result.raw
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_guardrail_is_called_using_callable():
|
||||
guardrail_events = defaultdict(list)
|
||||
from crewai.events.event_types import (
|
||||
@@ -414,7 +433,7 @@ def test_guardrail_is_called_using_callable():
|
||||
assert "Pelé - Santos, 1958" in result.raw
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_guardrail_reached_attempt_limit():
|
||||
guardrail_events = defaultdict(list)
|
||||
from crewai.events.event_types import (
|
||||
@@ -468,7 +487,7 @@ def test_guardrail_reached_attempt_limit():
|
||||
assert not guardrail_events["completed"][2].success
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_output_when_guardrail_returns_base_model():
|
||||
class Player(BaseModel):
|
||||
name: str
|
||||
@@ -559,7 +578,7 @@ def test_lite_agent_with_custom_llm_and_guardrails():
|
||||
assert result2.raw == "Modified by guardrail"
|
||||
|
||||
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_lite_agent_with_invalid_llm():
|
||||
"""Test that LiteAgent raises proper error when create_llm returns None."""
|
||||
with patch("crewai.lite_agent.create_llm", return_value=None):
|
||||
@@ -575,7 +594,7 @@ def test_lite_agent_with_invalid_llm():
|
||||
|
||||
@patch.dict("os.environ", {"CREWAI_PLATFORM_INTEGRATION_TOKEN": "test_token"})
|
||||
@patch("crewai_tools.tools.crewai_platform_tools.crewai_platform_tool_builder.requests.get")
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_kickoff_with_platform_tools(mock_get):
|
||||
"""Test that Agent.kickoff() properly integrates platform tools with LiteAgent"""
|
||||
mock_response = Mock()
|
||||
@@ -617,7 +636,7 @@ def test_agent_kickoff_with_platform_tools(mock_get):
|
||||
|
||||
@patch.dict("os.environ", {"EXA_API_KEY": "test_exa_key"})
|
||||
@patch("crewai.agent.Agent._get_external_mcp_tools")
|
||||
@pytest.mark.vcr()
|
||||
@pytest.mark.vcr(filter_headers=["authorization"])
|
||||
def test_agent_kickoff_with_mcp_tools(mock_get_mcp_tools):
|
||||
"""Test that Agent.kickoff() properly integrates MCP tools with LiteAgent"""
|
||||
# Setup mock MCP tools - create a proper BaseTool instance
|
||||
|
||||
@@ -0,0 +1,237 @@
|
||||
interactions:
|
||||
- request:
|
||||
body: '{"messages": [{"role": "system", "content": "You are Test Agent. An agent
|
||||
created for testing purposes\nYour personal goal is: Complete test tasks successfully\n\nTo
|
||||
give my best complete final answer to the task respond using the exact following
|
||||
format:\n\nThought: I now can give a great answer\nFinal Answer: Your final
|
||||
answer must be the great and the most complete as possible, it must be outcome
|
||||
described.\n\nI MUST use these formats, my job depends on it!"}, {"role": "user",
|
||||
"content": "Complete this task successfully"}], "model": "gpt-4o-mini", "stop":
|
||||
["\nObservation:"]}'
|
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headers:
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x-stainless-arch:
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x-stainless-async:
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x-stainless-os:
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x-stainless-package-version:
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