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Documentation Index

Fetch the complete documentation index at: https://docs.bigdata.com/llms.txt

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We are sunsetting our SDKs and will no longer add new features, security patches, bug fixes, or technical support for them. To access the latest capabilities and ongoing improvements, we encourage you to migrate to our RESTful API.SDK support will officially end on December 31, 2026. On this date, the underlying endpoints used by the SDKs and related documentation will be decommissioned.To avoid any disruption to your services, please ensure your migration is complete by that date.For migration assistance, please contact us at support@bigdata.com.
It provides methods to interact with Chat objects, and is accesible from a Bigdata instance

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Methods

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new(name, formatter=None)

Create a new chat. Parameters:
​
name
string
required
Chat’s name.
​
formatter
InlineAttributionFormatter | None
Format of the response inline attributions: InlineAttributionFormatter
Return type: Chat

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list(formatter=None)

Return a list with all chats Parameters:
​
formatter
InlineAttributionFormatter | None
Format of the response inline attributions: InlineAttributionFormatter
Return type: list[Chat]

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get(id_, formatter=None)

Return a chat by its identifier. Parameters:
​
id_
string
required
Unique chat identifier.
​
formatter
InlineAttributionFormatter | None
Format of the response inline attributions: InlineAttributionFormatter.
Return type: Chat

​
delete(id_)

Delete a chat by its identifier Parameters:
​
id_
string
required
Unique chat identifier
# Import classes from the bigdata-client Python SDK        
from bigdata_client import Bigdata
from bigdata_client.models.chat import MarkdownLinkFormatter
from bigdata_client.models.chat import ChatScope

# Log in to Bigdata
bigdata = Bigdata("YOUR_USERNAME", "YOUR_PASSWORD")

# Create a new chat with a format for the inline attribution in reponses
formatter = MarkdownLinkFormatter()
chat = bigdata.chat.new("Pfizer company analysis", formatter)

# First question
response = chat.ask("Evaluate the experience and reputation of the management team of Pfizer in 2024", streaming=True, scope=ChatScope.NEWS)

print(f"\nQuestion:\n - {response.question}")
print(f"\nAnswer:")
for streamingChatInteraction in response:
  print(streamingChatInteraction, end="")

# Follow up question
response = chat.ask("Has it hired any senior AI expert?", streaming=True, scope=ChatScope.NEWS)

print(f"\nQuestion:\n - {response.question}")
print(f"\nAnswer:")
for streamingChatInteraction in response:
  print(streamingChatInteraction, end="")

# Delete chat
bigdata.chat.delete(chat.id)