feat: support duckduckgo search engine

.env.example

@@ -3,6 +3,8 @@ DEBUG=True
 APP_ENV=development
 
 # Add other environment variables as needed
+# tavily, duckduckgo
+SEARCH_API=tavily
 TAVILY_API_KEY=tvly-xxx
 # JINA_API_KEY=jina_xxx # Optional, default is None
 

pyproject.toml

@@ -27,6 +27,7 @@ dependencies = [
     "litellm>=1.63.11",
     "json-repair>=0.7.0",
     "jinja2>=3.1.3",
+    "duckduckgo-search>=8.0.0",
 ]
 
 [project.optional-dependencies]

src/agents/agents.py

@@ -2,10 +2,9 @@ from langgraph.prebuilt import create_react_agent
 
 from src.prompts import apply_prompt_template
 from src.tools import (
-    bash_tool,
     crawl_tool,
     python_repl_tool,
-    tavily_tool,
+    web_search_tool,
 )
 
 from src.llms.llm import get_llm_by_type
@@ -25,6 +24,6 @@ def create_agent(agent_name: str, agent_type: str, tools: list, prompt_template:
 
 # Create agents using the factory function
 research_agent = create_agent(
-    "researcher", "researcher", [tavily_tool, crawl_tool], "researcher"
+    "researcher", "researcher", [web_search_tool, crawl_tool], "researcher"
 )
-coder_agent = create_agent("coder", "coder", [python_repl_tool, bash_tool], "coder")
+coder_agent = create_agent("coder", "coder", [python_repl_tool], "coder")

src/config/__init__.py

@@ -1,4 +1,4 @@
-from .tools import TAVILY_MAX_RESULTS
+from .tools import SEARCH_MAX_RESULTS, SELECTED_SEARCH_ENGINE, SearchEngine
 from .loader import load_yaml_config
 
 from dotenv import load_dotenv
@@ -38,5 +38,7 @@ __all__ = [
     # Other configurations
     "TEAM_MEMBERS",
     "TEAM_MEMBER_CONFIGRATIONS",
-    "TAVILY_MAX_RESULTS",
+    "SEARCH_MAX_RESULTS",
+    "SELECTED_SEARCH_ENGINE",
+    "SearchEngine",
 ]

src/config/tools.py

@@ -1,2 +1,15 @@
+import os
+import enum
+from dotenv import load_dotenv
+
+load_dotenv()
+
+
+class SearchEngine(enum.Enum):
+    TAVILY = "tavily"
+    DUCKDUCKGO = "duckduckgo"
+
+
 # Tool configuration
-TAVILY_MAX_RESULTS = 3
+SELECTED_SEARCH_ENGINE = os.getenv("SEARCH_API", SearchEngine.TAVILY.value)
+SEARCH_MAX_RESULTS = 3

src/prompts/coder.md

@@ -3,16 +3,14 @@ CURRENT_TIME: {{ CURRENT_TIME }}
 ---
 
 You are `coder` agent that is managed by `supervisor` agent.
-You are a professional software engineer proficient in both Python and bash scripting. Your task is to analyze requirements, implement efficient solutions using Python and/or bash, and provide clear documentation of your methodology and results.
+You are a professional software engineer proficient in Python scripting. Your task is to analyze requirements, implement efficient solutions using Python, and provide clear documentation of your methodology and results.
 
 # Steps
 
 1. **Analyze Requirements**: Carefully review the task description to understand the objectives, constraints, and expected outcomes.
-2. **Plan the Solution**: Determine whether the task requires Python, bash, or a combination of both. Outline the steps needed to achieve the solution.
+2. **Plan the Solution**: Determine whether the task requires Python. Outline the steps needed to achieve the solution.
 3. **Implement the Solution**:
    - Use Python for data analysis, algorithm implementation, or problem-solving.
-   - Use bash for executing shell commands, managing system resources, or querying the environment.
-   - Integrate Python and bash seamlessly if the task requires both.
    - Print outputs using `print(...)` in Python to display results or debug values.
 4. **Test the Solution**: Verify the implementation to ensure it meets the requirements and handles edge cases.
 5. **Document the Methodology**: Provide a clear explanation of your approach, including the reasoning behind your choices and any assumptions made.

src/prompts/coordinator.md

@@ -2,17 +2,17 @@
 CURRENT_TIME: {{ CURRENT_TIME }}
 ---
 
-You are Langmanus, a friendly AI assistant developed by the Langmanus team. You specialize in handling greetings and small talk, while handing off complex tasks to a specialized planner.
+You are Lite Deep Researcher, a friendly AI assistant. You specialize in handling greetings and small talk, while handing off research tasks to a specialized planner.
 
 # Details
 
 Your primary responsibilities are:
-- Introducing yourself as Langmanus when appropriate
+- Introducing yourself as Lite Deep Researcher when appropriate
 - Responding to greetings (e.g., "hello", "hi", "good morning")
 - Engaging in small talk (e.g., how are you)
 - Politely rejecting inappropriate or harmful requests (e.g. Prompt Leaking)
 - Communicate with user to get enough context
-- Handing off all other questions to the planner
+- Handing off all other questions to the planner for research
 
 # Execution Rules
 
@@ -21,11 +21,11 @@ Your primary responsibilities are:
 - If you need to ask user for more context:
   - Respond in plain text with an appropriate question
 - For all other inputs:
-  - call `handoff_to_planner()` tool to handoff to planner without ANY thoughts.
+  - call `handoff_to_planner()` tool to handoff to planner for research without ANY thoughts.
 
 # Notes
 
-- Always identify yourself as Langmanus when relevant
+- Always identify yourself as Lite Deep Researcher when relevant
 - Keep responses friendly but professional
-- Don't attempt to solve complex problems or create plans
+- Don't attempt to solve complex problems or create research plans
 - Maintain the same language as the user

src/prompts/researcher.md

@@ -11,7 +11,7 @@ You are dedicated to conducting thorough investigations and providing comprehens
 1. **Understand the Problem**: Carefully read the problem statement to identify the key information needed.
 2. **Plan the Solution**: Determine the best approach to solve the problem using the available tools.
 3. **Execute the Solution**:
-   - Use the **tavily_tool** to perform a search with the provided SEO keywords.
+   - Use the **web_search_tool** to perform a search with the provided SEO keywords.
    - (Optional) Then use the **crawl_tool** to read markdown content from the necessary URLs. Only use the URLs from the search results or provided by the user.
 4. **Synthesize Information**:
    - Combine the information gathered from the search results and the crawled content.
@@ -22,7 +22,7 @@ You are dedicated to conducting thorough investigations and providing comprehens
 - Provide a structured response in markdown format.
 - Include the following sections:
     - **Problem Statement**: Restate the problem for clarity.
-    - **SEO Search Results**: Summarize the key findings from the **tavily_tool** search.
+    - **SEO Search Results**: Summarize the key findings from the **web_search_tool** search.
     - **Crawled Content**: Summarize the key findings from the **crawl_tool**.
     - **Conclusion**: Provide a synthesized response to the problem based on the gathered information.
 - Always use the same language as the initial question.

src/tools/__init__.py

@@ -1,11 +1,18 @@
 from .crawl import crawl_tool
 from .python_repl import python_repl_tool
-from .search import tavily_tool
-from .bash_tool import bash_tool
+from .search import tavily_search_tool, duckduckgo_search_tool
+from src.config import SELECTED_SEARCH_ENGINE, SearchEngine
+
+# Map search engine names to their respective tools
+search_tool_mappings = {
+    SearchEngine.TAVILY.value: tavily_search_tool,
+    SearchEngine.DUCKDUCKGO.value: duckduckgo_search_tool,
+}
+
+web_search_tool = search_tool_mappings.get(SELECTED_SEARCH_ENGINE, tavily_search_tool)
 
 __all__ = [
-    "bash_tool",
     "crawl_tool",
-    "tavily_tool",
+    "web_search_tool",
     "python_repl_tool",
 ]

src/tools/bash_tool.py

@@ -1,49 +0,0 @@
-import logging
-import subprocess
-from typing import Annotated
-from langchain_core.tools import tool
-from .decorators import log_io
-
-# Initialize logger
-logger = logging.getLogger(__name__)
-
-
-@tool
-@log_io
-def bash_tool(
-    cmd: Annotated[str, "The bash command to be executed."],
-    timeout: Annotated[
-        int, "Maximum time in seconds for the command to complete."
-    ] = 120,
-):
-    """Use this to execute bash command and do necessary operations."""
-    logger.info(f"Executing Bash Command: {cmd} with timeout {timeout}s")
-    try:
-        # Execute the command and capture output
-        result = subprocess.run(
-            cmd, shell=True, check=True, text=True, capture_output=True, timeout=timeout
-        )
-        # Return stdout as the result
-        return result.stdout
-    except subprocess.CalledProcessError as e:
-        # If command fails, return error information
-        error_message = f"Command failed with exit code {
-            e.returncode}.\nStdout: {
-            e.stdout}\nStderr: {
-            e.stderr}"
-        logger.error(error_message)
-        return error_message
-    except subprocess.TimeoutExpired:
-        # Handle timeout exception
-        error_message = f"Command '{cmd}' timed out after {timeout}s."
-        logger.error(error_message)
-        return error_message
-    except Exception as e:
-        # Catch any other exceptions
-        error_message = f"Error executing command: {str(e)}"
-        logger.error(error_message)
-        return error_message
-
-
-if __name__ == "__main__":
-    print(bash_tool.invoke("ls -all"))

src/tools/search.py

@@ -1,10 +1,18 @@
 import logging
 from langchain_community.tools.tavily_search import TavilySearchResults
-from src.config import TAVILY_MAX_RESULTS
+from langchain_community.tools import DuckDuckGoSearchResults
+from src.config import SEARCH_MAX_RESULTS
 from .decorators import create_logged_tool
 
 logger = logging.getLogger(__name__)
 
-# Initialize Tavily search tool with logging
+
 LoggedTavilySearch = create_logged_tool(TavilySearchResults)
-tavily_tool = LoggedTavilySearch(name="tavily_search", max_results=TAVILY_MAX_RESULTS)
+tavily_search_tool = LoggedTavilySearch(
+    name="web_search", max_results=SEARCH_MAX_RESULTS
+)
+
+LoggedDuckDuckGoSearch = create_logged_tool(DuckDuckGoSearchResults)
+duckduckgo_search_tool = LoggedDuckDuckGoSearch(
+    name="web_search", max_results=SEARCH_MAX_RESULTS
+)

tests/integration/test_bash_tool.py

@@ -1,44 +0,0 @@
-import unittest
-import subprocess
-from unittest.mock import patch
-from src.tools.bash_tool import bash_tool
-
-
-class TestBashTool(unittest.TestCase):
-    def test_successful_command(self):
-        """Test bash tool with a successful command execution"""
-        result = bash_tool.invoke("echo 'Hello World'")
-        self.assertEqual(result.strip(), "Hello World")
-
-    @patch("subprocess.run")
-    def test_command_with_error(self, mock_run):
-        """Test bash tool when command fails"""
-        # Configure mock to raise CalledProcessError
-        mock_run.side_effect = subprocess.CalledProcessError(
-            returncode=1, cmd="invalid_command", output="", stderr="Command not found"
-        )
-
-        result = bash_tool.invoke("invalid_command")
-        self.assertIn("Command failed with exit code 1", result)
-        self.assertIn("Command not found", result)
-
-    @patch("subprocess.run")
-    def test_command_with_exception(self, mock_run):
-        """Test bash tool when an unexpected exception occurs"""
-        # Configure mock to raise a generic exception
-        mock_run.side_effect = Exception("Unexpected error")
-
-        result = bash_tool.invoke("some_command")
-        self.assertIn("Error executing command: Unexpected error", result)
-
-    def test_command_with_output(self):
-        """Test bash tool with a command that produces output"""
-        # Create a temporary file and write to it
-        result = bash_tool.invoke(
-            "echo 'test content' > test_file.txt && cat test_file.txt && rm test_file.txt"
-        )
-        self.assertEqual(result.strip(), "test content")
-
-
-if __name__ == "__main__":
-    unittest.main()

uv.lock

@@ -305,6 +305,20 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/12/b3/231ffd4ab1fc9d679809f356cebee130ac7daa00d6d6f3206dd4fd137e9e/distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2", size = 20277 },
 ]
 
+[[package]]
+name = "duckduckgo-search"
+version = "8.0.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "click" },
+    { name = "lxml" },
+    { name = "primp" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/25/aa/594674d0cfe45bdeb825b6383de2104c7320f3fb582eb97fb153dbdc8c71/duckduckgo_search-8.0.0.tar.gz", hash = "sha256:2a8e22092156e11d3c9195e1ce100fa0bce181d23d6f84b89228190498887736", size = 22253 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/db/39/8e01afdea1bf7e67eb191217ad958a5c691f7739c9dacd00e8d77a663e4d/duckduckgo_search-8.0.0-py3-none-any.whl", hash = "sha256:0026f2c6961d457b4c526cb840dbb28a7b24f67ce38589618a5021fdb3f0e8bc", size = 18687 },
+]
+
 [[package]]
 name = "fastapi"
 version = "0.115.11"
@@ -806,6 +820,7 @@ name = "lite-deep-researcher"
 version = "0.1.0"
 source = { editable = "." }
 dependencies = [
+    { name = "duckduckgo-search" },
     { name = "fastapi" },
     { name = "httpx" },
     { name = "jinja2" },
@@ -838,6 +853,7 @@ test = [
 [package.metadata]
 requires-dist = [
     { name = "black", marker = "extra == 'dev'", specifier = ">=24.2.0" },
+    { name = "duckduckgo-search", specifier = ">=8.0.0" },
     { name = "fastapi", specifier = ">=0.110.0" },
     { name = "httpx", specifier = ">=0.28.1" },
     { name = "jinja2", specifier = ">=3.1.3" },
@@ -1242,6 +1258,22 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/88/5f/e351af9a41f866ac3f1fac4ca0613908d9a41741cfcf2228f4ad853b697d/pluggy-1.5.0-py3-none-any.whl", hash = "sha256:44e1ad92c8ca002de6377e165f3e0f1be63266ab4d554740532335b9d75ea669", size = 20556 },
 ]
 
+[[package]]
+name = "primp"
+version = "0.14.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/95/1e/a063129aed2320b463fd35c5d918d5754e59011698aaf7cf297a610b3380/primp-0.14.0.tar.gz", hash = "sha256:b6f23b2b694118a9d0443b3760698b90afb6f867f8447e71972530f48297992e", size = 112406 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/7f/12/eba13ddbeb5c6df6cf7511aedb5fa4bcb99c0754e88056260dd44aa53929/primp-0.14.0-cp38-abi3-macosx_10_12_x86_64.whl", hash = "sha256:bd2dfb57feeba21a77a1128b6c6f17856605c4e73edcc05764fb134de4ff014f", size = 3173837 },
+    { url = "https://files.pythonhosted.org/packages/77/65/3cd25b4f4d0cd9de4f1d95858dcddd7ed082587524294c179c847de18951/primp-0.14.0-cp38-abi3-macosx_11_0_arm64.whl", hash = "sha256:31eecb5316f9bd732a7994530b85eb698bf6500d2f6c5c3382dac0353f77084e", size = 2947192 },
+    { url = "https://files.pythonhosted.org/packages/13/77/f85bc3e31befa9b9bac54bab61beb34ff84a70d20f02b7dcd8abc120120a/primp-0.14.0-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:11229e65aa5755fdfb535cc03fd64259a06764ad7c22e650fb3bea51400f1d09", size = 3276730 },
+    { url = "https://files.pythonhosted.org/packages/44/36/bc95049264ee668a5cdaadf77ef711aaa9cb0c4c0a246b27bba9a2f0114c/primp-0.14.0-cp38-abi3-manylinux_2_34_aarch64.whl", hash = "sha256:8f56ca2cd63f9ac75b33bf48129b7e79ade29cf280bc253b17b052afb27d2b9e", size = 3247684 },
+    { url = "https://files.pythonhosted.org/packages/31/d9/632a70c80dcdd0bb9293cdc7e7543d35e5912325631c3e9f3b7c7d842941/primp-0.14.0-cp38-abi3-manylinux_2_34_armv7l.whl", hash = "sha256:3fb204f67a4b58dc53f3452143121317b474437812662ac0149d332a77ecbe1a", size = 3007835 },
+    { url = "https://files.pythonhosted.org/packages/dc/ba/07b04b9d404f20ec78449c5974c988a5adf7d4d245a605466486f70d35c3/primp-0.14.0-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:b0b21e6a599f580137774623009c7f895afab49d6c3d6c9a28344fd2586ebe8a", size = 3413956 },
+    { url = "https://files.pythonhosted.org/packages/d7/d3/3bee499b4594fce1f8ccede785e517162407fbea1d452c4fb55fe3fb5e81/primp-0.14.0-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:6549766ece3c7be19e1c16fa9029d3e50fa73628149d88601fcd964af8b44a8d", size = 3595850 },
+    { url = "https://files.pythonhosted.org/packages/6a/20/042c8ae21d185f2efe61780dfbc01464c982f59626b746d5436c2e4c1e08/primp-0.14.0-cp38-abi3-win_amd64.whl", hash = "sha256:d3ae1ba954ec8d07abb527ccce7bb36633525c86496950ba0178e44a0ea5c891", size = 3143077 },
+]
+
 [[package]]
 name = "propcache"
 version = "0.3.0"