community[minor]: CogniSwitch Agent Toolkit for LangChain (#17312)

**Description**: CogniSwitch focusses on making GenAI usage more
reliable. It abstracts out the complexity & decision making required for
tuning processing, storage & retrieval. Using simple APIs documents /
URLs can be processed into a Knowledge Graph that can then be used to
answer questions.

**Dependencies**: No dependencies. Just network calls & API key required
**Tag maintainer**: @hwchase17
**Twitter handle**: https://github.com/CogniSwitch
**Documentation**: Please check
`docs/docs/integrations/toolkits/cogniswitch.ipynb`
**Tests**: The usual tool & toolkits tests using `test_imports.py`

PR has passed linting and testing before this submission.

---------

Co-authored-by: Saicharan Sridhara <145636106+saiCogniswitch@users.noreply.github.com>
This commit is contained in:
CogniJT
2024-02-20 00:24:13 +05:30
committed by GitHub
parent 6275d8b1bf
commit 919ebcc596
10 changed files with 816 additions and 0 deletions

View File

@@ -18,6 +18,7 @@ from langchain_community.agent_toolkits.amadeus.toolkit import AmadeusToolkit
from langchain_community.agent_toolkits.azure_cognitive_services import (
AzureCognitiveServicesToolkit,
)
from langchain_community.agent_toolkits.cogniswitch.toolkit import CogniswitchToolkit
from langchain_community.agent_toolkits.connery import ConneryToolkit
from langchain_community.agent_toolkits.file_management.toolkit import (
FileManagementToolkit,
@@ -51,6 +52,7 @@ __all__ = [
"AINetworkToolkit",
"AmadeusToolkit",
"AzureCognitiveServicesToolkit",
"CogniswitchToolkit",
"ConneryToolkit",
"FileManagementToolkit",
"GmailToolkit",

View File

@@ -0,0 +1 @@
"""CogniSwitch Toolkit"""

View File

@@ -0,0 +1,40 @@
from typing import List
from langchain_community.agent_toolkits.base import BaseToolkit
from langchain_community.tools import BaseTool
from langchain_community.tools.cogniswitch.tool import (
CogniswitchKnowledgeRequest,
CogniswitchKnowledgeSourceFile,
CogniswitchKnowledgeSourceURL,
CogniswitchKnowledgeStatus,
)
class CogniswitchToolkit(BaseToolkit):
"""
Toolkit for CogniSwitch.
Use the toolkit to get all the tools present in the cogniswitch and
use them to interact with your knowledge
"""
cs_token: str # cogniswitch token
OAI_token: str # OpenAI API token
apiKey: str # Cogniswitch OAuth token
def get_tools(self) -> List[BaseTool]:
"""Get the tools in the toolkit."""
return [
CogniswitchKnowledgeStatus(
cs_token=self.cs_token, OAI_token=self.OAI_token, apiKey=self.apiKey
),
CogniswitchKnowledgeRequest(
cs_token=self.cs_token, OAI_token=self.OAI_token, apiKey=self.apiKey
),
CogniswitchKnowledgeSourceFile(
cs_token=self.cs_token, OAI_token=self.OAI_token, apiKey=self.apiKey
),
CogniswitchKnowledgeSourceURL(
cs_token=self.cs_token, OAI_token=self.OAI_token, apiKey=self.apiKey
),
]

View File

@@ -118,6 +118,32 @@ def _import_brave_search_tool() -> Any:
return BraveSearch
def _import_cogniswitch_store_file_tool() -> Any:
from langchain_community.tools.cogniswitch.tool import (
CogniswitchKnowledgeSourceFile,
)
return CogniswitchKnowledgeSourceFile
def _import_cogniswitch_store_url_tool() -> Any:
from langchain_community.tools.cogniswitch.tool import CogniswitchKnowledgeSourceURL
return CogniswitchKnowledgeSourceURL
def _import_cogniswitch_answer_tool() -> Any:
from langchain_community.tools.cogniswitch.tool import CogniswitchKnowledgeRequest
return CogniswitchKnowledgeRequest
def _import_cogniswitch_knowledge_status_tool() -> Any:
from langchain_community.tools.cogniswitch.tool import CogniswitchKnowledgeStatus
return CogniswitchKnowledgeStatus
def _import_connery_tool() -> Any:
from langchain_community.tools.connery import ConneryAction
@@ -803,6 +829,14 @@ def __getattr__(name: str) -> Any:
return _import_bing_search_tool_BingSearchRun()
elif name == "BraveSearch":
return _import_brave_search_tool()
elif name == "CogniswitchKnowledgeSourceFile":
return _import_cogniswitch_store_file_tool()
elif name == "CogniswitchKnowledgeSourceURL":
return _import_cogniswitch_store_url_tool()
elif name == "CogniswitchKnowledgeRequest":
return _import_cogniswitch_answer_tool()
elif name == "CogniswitchKnowledgeStatus":
return _import_cogniswitch_knowledge_status_tool()
elif name == "ConneryAction":
return _import_connery_tool()
elif name == "DuckDuckGoSearchResults":
@@ -1043,6 +1077,10 @@ __all__ = [
"BingSearchRun",
"BraveSearch",
"ClickTool",
"CogniswitchKnowledgeSourceFile",
"CogniswitchKnowledgeSourceURL",
"CogniswitchKnowledgeRequest",
"CogniswitchKnowledgeStatus",
"ConneryAction",
"CopyFileTool",
"CurrentWebPageTool",

View File

@@ -0,0 +1 @@
"Cogniswitch Tools"

View File

@@ -0,0 +1,399 @@
from __future__ import annotations
from typing import Any, Dict, Optional
import requests
from langchain_core.callbacks import CallbackManagerForToolRun
from langchain_core.tools import BaseTool
class CogniswitchKnowledgeRequest(BaseTool):
"""
A tool for interacting with the Cogniswitch service to answer questions.
name: str = "cogniswitch_knowledge_request"
description: str = (
"A wrapper around cogniswitch service to answer the question
from the knowledge base."
"Input should be a search query."
)
"""
name: str = "cogniswitch_knowledge_request"
description: str = """A wrapper around cogniswitch service to
answer the question from the knowledge base."""
cs_token: str
OAI_token: str
apiKey: str
api_url = "https://api.cogniswitch.ai:8243/cs-api/0.0.1/cs/knowledgeRequest"
def _run(
self,
query: str,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> Dict[str, Any]:
"""
Use the tool to answer a query.
Args:
query (str): Natural language query,
that you would like to ask to your knowledge graph.
run_manager (Optional[CallbackManagerForChainRun]):
Manager for chain run callbacks.
Returns:
Dict[str, Any]: Output dictionary containing
the 'response' from the service.
"""
response = self.answer_cs(self.cs_token, self.OAI_token, query, self.apiKey)
return response
def answer_cs(self, cs_token: str, OAI_token: str, query: str, apiKey: str) -> dict:
"""
Send a query to the Cogniswitch service and retrieve the response.
Args:
cs_token (str): Cogniswitch token.
OAI_token (str): OpenAI token.
apiKey (str): OAuth token.
query (str): Query to be answered.
Returns:
dict: Response JSON from the Cogniswitch service.
"""
if not cs_token:
raise ValueError("Missing cs_token")
if not OAI_token:
raise ValueError("Missing OpenAI token")
if not apiKey:
raise ValueError("Missing cogniswitch OAuth token")
if not query:
raise ValueError("Missing input query")
headers = {
"apiKey": apiKey,
"platformToken": cs_token,
"openAIToken": OAI_token,
}
data = {"query": query}
response = requests.post(self.api_url, headers=headers, verify=False, data=data)
return response.json()
class CogniswitchKnowledgeStatus(BaseTool):
"""
A cogniswitch tool for interacting with the Cogniswitch services to know the
status of the document or url uploaded.
name: str = "cogniswitch_knowledge_status"
description: str = (
"A wrapper around cogniswitch services to know the status of
the document uploaded from a url or a file. "
"Input should be a file name or the url link"
)
"""
name: str = "cogniswitch_knowledge_status"
description: str = """A wrapper around cogniswitch services to know
the status of the document uploaded from a url or a file."""
cs_token: str
OAI_token: str
apiKey: str
knowledge_status_url = (
"https://api.cogniswitch.ai:8243/cs-api/0.0.1/cs/knowledgeSource/status"
)
def _run(
self,
document_name: str,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> Dict[str, Any]:
"""
Use the tool to know the status of the document uploaded.
Args:
document_name (str): name of the document or
the url uploaded
run_manager (Optional[CallbackManagerForChainRun]):
Manager for chain run callbacks.
Returns:
Dict[str, Any]: Output dictionary containing
the 'response' from the service.
"""
response = self.knowledge_status(document_name)
return response
def knowledge_status(self, document_name: str) -> dict:
"""
Use this function to know the status of the document or the URL uploaded
Args:
document_name (str): The document name or the url that is uploaded.
Returns:
dict: Response JSON from the Cogniswitch service.
"""
params = {"docName": document_name, "platformToken": self.cs_token}
headers = {
"apiKey": self.apiKey,
"openAIToken": self.OAI_token,
"platformToken": self.cs_token,
}
response = requests.get(
self.knowledge_status_url,
headers=headers,
params=params,
verify=False,
)
if response.status_code == 200:
source_info = response.json()
source_data = dict(source_info[-1])
status = source_data.get("status")
if status == 0:
source_data["status"] = "SUCCESS"
elif status == 1:
source_data["status"] = "PROCESSING"
elif status == 2:
source_data["status"] = "UPLOADED"
elif status == 3:
source_data["status"] = "FAILURE"
elif status == 4:
source_data["status"] = "UPLOAD_FAILURE"
elif status == 5:
source_data["status"] = "REJECTED"
if "filePath" in source_data.keys():
source_data.pop("filePath")
if "savedFileName" in source_data.keys():
source_data.pop("savedFileName")
if "integrationConfigId" in source_data.keys():
source_data.pop("integrationConfigId")
if "metaData" in source_data.keys():
source_data.pop("metaData")
if "docEntryId" in source_data.keys():
source_data.pop("docEntryId")
return source_data
else:
# error_message = response.json()["message"]
return {
"message": response.status_code,
}
class CogniswitchKnowledgeSourceFile(BaseTool):
"""
A cogniswitch tool for interacting with the Cogniswitch services to store data.
name: str = "cogniswitch_knowledge_source_file"
description: str = (
"This calls the CogniSwitch services to analyze & store data from a file.
If the input looks like a file path, assign that string value to file key.
Assign document name & description only if provided in input."
)
"""
name: str = "cogniswitch_knowledge_source_file"
description: str = """
This calls the CogniSwitch services to analyze & store data from a file.
If the input looks like a file path, assign that string value to file key.
Assign document name & description only if provided in input.
"""
cs_token: str
OAI_token: str
apiKey: str
knowledgesource_file = (
"https://api.cogniswitch.ai:8243/cs-api/0.0.1/cs/knowledgeSource/file"
)
def _run(
self,
file: Optional[str] = None,
document_name: Optional[str] = None,
document_description: Optional[str] = None,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> Dict[str, Any]:
"""
Execute the tool to store the data given from a file.
This calls the CogniSwitch services to analyze & store data from a file.
If the input looks like a file path, assign that string value to file key.
Assign document name & description only if provided in input.
Args:
file Optional[str]: The file path of your knowledge
document_name Optional[str]: Name of your knowledge document
document_description Optional[str]: Description of your knowledge document
run_manager (Optional[CallbackManagerForChainRun]):
Manager for chain run callbacks.
Returns:
Dict[str, Any]: Output dictionary containing
the 'response' from the service.
"""
if not file:
return {
"message": "No input provided",
}
else:
response = self.store_data(
file=file,
document_name=document_name,
document_description=document_description,
)
return response
def store_data(
self,
file: Optional[str],
document_name: Optional[str],
document_description: Optional[str],
) -> dict:
"""
Store data using the Cogniswitch service.
This calls the CogniSwitch services to analyze & store data from a file.
If the input looks like a file path, assign that string value to file key.
Assign document name & description only if provided in input.
Args:
file (Optional[str]): file path of your file.
the current files supported by the files are
.txt, .pdf, .docx, .doc, .html
document_name (Optional[str]): Name of the document you are uploading.
document_description (Optional[str]): Description of the document.
Returns:
dict: Response JSON from the Cogniswitch service.
"""
headers = {
"apiKey": self.apiKey,
"openAIToken": self.OAI_token,
"platformToken": self.cs_token,
}
data: Dict[str, Any]
if not document_name:
document_name = ""
if not document_description:
document_description = ""
if file is not None:
files = {"file": open(file, "rb")}
data = {
"documentName": document_name,
"documentDescription": document_description,
}
response = requests.post(
self.knowledgesource_file,
headers=headers,
verify=False,
data=data,
files=files,
)
if response.status_code == 200:
return response.json()
else:
return {"message": "Bad Request"}
class CogniswitchKnowledgeSourceURL(BaseTool):
"""
A cogniswitch tool for interacting with the Cogniswitch services to store data.
name: str = "cogniswitch_knowledge_source_url"
description: str = (
"This calls the CogniSwitch services to analyze & store data from a url.
the URL is provided in input, assign that value to the url key.
Assign document name & description only if provided in input"
)
"""
name: str = "cogniswitch_knowledge_source_url"
description: str = """
This calls the CogniSwitch services to analyze & store data from a url.
the URL is provided in input, assign that value to the url key.
Assign document name & description only if provided in input"""
cs_token: str
OAI_token: str
apiKey: str
knowledgesource_url = (
"https://api.cogniswitch.ai:8243/cs-api/0.0.1/cs/knowledgeSource/url"
)
def _run(
self,
url: Optional[str] = None,
document_name: Optional[str] = None,
document_description: Optional[str] = None,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> Dict[str, Any]:
"""
Execute the tool to store the data given from a url.
This calls the CogniSwitch services to analyze & store data from a url.
the URL is provided in input, assign that value to the url key.
Assign document name & description only if provided in input.
Args:
url Optional[str]: The website/url link of your knowledge
document_name Optional[str]: Name of your knowledge document
document_description Optional[str]: Description of your knowledge document
run_manager (Optional[CallbackManagerForChainRun]):
Manager for chain run callbacks.
Returns:
Dict[str, Any]: Output dictionary containing
the 'response' from the service.
"""
if not url:
return {
"message": "No input provided",
}
response = self.store_data(
url=url,
document_name=document_name,
document_description=document_description,
)
return response
def store_data(
self,
url: Optional[str],
document_name: Optional[str],
document_description: Optional[str],
) -> dict:
"""
Store data using the Cogniswitch service.
This calls the CogniSwitch services to analyze & store data from a url.
the URL is provided in input, assign that value to the url key.
Assign document name & description only if provided in input.
Args:
url (Optional[str]): URL link.
document_name (Optional[str]): Name of the document you are uploading.
document_description (Optional[str]): Description of the document.
Returns:
dict: Response JSON from the Cogniswitch service.
"""
headers = {
"apiKey": self.apiKey,
"openAIToken": self.OAI_token,
"platformToken": self.cs_token,
}
data: Dict[str, Any]
if not document_name:
document_name = ""
if not document_description:
document_description = ""
if not url:
return {
"message": "No input provided",
}
else:
data = {"url": url}
response = requests.post(
self.knowledgesource_url,
headers=headers,
verify=False,
data=data,
)
if response.status_code == 200:
return response.json()
else:
return {"message": "Bad Request"}

View File

@@ -28,6 +28,7 @@ EXPECTED_ALL = [
"create_pbi_chat_agent",
"create_spark_sql_agent",
"create_sql_agent",
"CogniswitchToolkit",
]

View File

@@ -24,6 +24,10 @@ EXPECTED_ALL = [
"BingSearchRun",
"BraveSearch",
"ClickTool",
"CogniswitchKnowledgeSourceFile",
"CogniswitchKnowledgeSourceURL",
"CogniswitchKnowledgeRequest",
"CogniswitchKnowledgeStatus",
"ConneryAction",
"CopyFileTool",
"CurrentWebPageTool",

View File

@@ -25,6 +25,10 @@ _EXPECTED = [
"BingSearchRun",
"BraveSearch",
"ClickTool",
"CogniswitchKnowledgeSourceFile",
"CogniswitchKnowledgeStatus",
"CogniswitchKnowledgeSourceURL",
"CogniswitchKnowledgeRequest",
"ConneryAction",
"CopyFileTool",
"CurrentWebPageTool",