Python SDK for using Conva AI co-pilots
Project description
Python Library for Conva AI
This is the python library for using Conva AI Co-pilots
Examples
1. A simple example for generating response using Conva Co-pilot
from conva_ai import AsyncConvaAI
client = AsyncConvaAI(
copilot_id="<YOUR_COPILOT_ID>",
copilot_version="<YOUR_COPILOT_VERSION>",
api_key="<YOUR_API_KEY>"
)
async def generate(client: AsyncConvaAI, query: str, stream: bool):
response = client.invoke_capability(query, stream=stream)
out = ""
async for res in response:
out = res.model_dump_json(indent=4)
return out
final_response = asyncio.run(generate(client, "how are you", True))
print(final_response)
2. How to clear history
Conva AI client, by default keeps track of your conversation history and uses it as the context for responding intelligently
You can clear conversation history by executing the below code:
from conva_ai.client import AsyncConvaAI
client = AsyncConvaAI(
copilot_id="<YOUR_COPILOT_ID>",
copilot_version="<YOUR_COPILOT_VERSION>",
api_key="<YOUR_API_KEY>"
)
client.clear_history()
In case you are buliding an application where you don't want to track conversation history, you can disable history tracking
client.use_history(False)
You can enable history by
client.use_history(True)
3. Debugging responses
Conva AI uses generative AI to give you the response to your query. In order for you to understand the reasoning behind the response. We also provide you with AI's reasoning
import asyncio
from conva_ai.client import AsyncConvaAI
client = AsyncConvaAI(
copilot_id="<YOUR_COPILOT_ID>",
copilot_version="<YOUR_COPILOT_VERSION>",
api_key="<YOUR_API_KEY>"
)
async def generate(client: AsyncConvaAI, query: str, stream: bool):
response = client.invoke_capability(query, stream=stream)
out=""
async for res in response:
out = res
return out
final_response = asyncio.run(generate("how are you", True))
print(final_response.reason)
How to use capability groups
Capability Groups are used to control the list of Capabilities that Co pilot will have access.
You can make use of the capability group while using the invoke_capability
method
async def generate(client: AsyncConvaAI, query: str, stream: bool):
response = client.client.invoke_capability(query, stream=stream, capability_group="<CAPABILITY_GROUP_NAME>")
out=""
async for res in response:
out = res
return out
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