POST
/
chat
/
{assistant_name}
/
context
# To use the Python SDK, install the plugin:
# pip install --upgrade pinecone pinecone-plugin-assistant

from pinecone import Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")
assistant = pc.assistant.Assistant(assistant_name="example-assistant")

response = assistant.context(query="Who is the CFO of Netflix?")

for snippet in response.snippets:
    print(snippet)

{
    "snippets":
    [
        {
            "type":"text",
            "content":"EXHIBIT 31.3\nCERTIFICATION OF CHIEF FINANCIAL OFFICER\nPURSUANT TO SECTION 302 OF THE SARBANES-OXLEY ACT OF 2002\nI, Spencer Neumann, certify that: ...",
            "score":0.9960699,
            "reference":
            {
                "type":"pdf",
                "file":
                {
                    "status":"Available","id":"e6034e51-0bb9-4926-84c6-70597dbd07a7",
                    "name":"Netflix-10-K-01262024.pdf", 
                    "size":1073470,
                    "metadata":null,
                    "updated_on":"2024-11-21T22:59:10.426001030Z",
                    "created_on":"2024-11-21T22:58:35.879120257Z", 
                    "percent_done":1.0,
                    "signed_url":"https://storage.googleapis.com...",
                    "error_message":null
                    },
                "pages":[78]
            }
        },
{
    "type":"text",
    "content":"EXHIBIT 32.1\n..."
...

# To use the Python SDK, install the plugin:
# pip install --upgrade pinecone pinecone-plugin-assistant

from pinecone import Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")
assistant = pc.assistant.Assistant(assistant_name="example-assistant")

response = assistant.context(query="Who is the CFO of Netflix?")

for snippet in response.snippets:
    print(snippet)

{
    "snippets":
    [
        {
            "type":"text",
            "content":"EXHIBIT 31.3\nCERTIFICATION OF CHIEF FINANCIAL OFFICER\nPURSUANT TO SECTION 302 OF THE SARBANES-OXLEY ACT OF 2002\nI, Spencer Neumann, certify that: ...",
            "score":0.9960699,
            "reference":
            {
                "type":"pdf",
                "file":
                {
                    "status":"Available","id":"e6034e51-0bb9-4926-84c6-70597dbd07a7",
                    "name":"Netflix-10-K-01262024.pdf", 
                    "size":1073470,
                    "metadata":null,
                    "updated_on":"2024-11-21T22:59:10.426001030Z",
                    "created_on":"2024-11-21T22:58:35.879120257Z", 
                    "percent_done":1.0,
                    "signed_url":"https://storage.googleapis.com...",
                    "error_message":null
                    },
                "pages":[78]
            }
        },
{
    "type":"text",
    "content":"EXHIBIT 32.1\n..."
...

Authorizations

​
Api-Key
string
header
required

Pinecone API Key

Path Parameters

​
assistant_name
string
required

The name of the assistant to be described.

Body

application/json
The desired configuration to retrieve context from an assistant.

Parameters to retrieve context from an assistant.

​
query
string

The query that is used to generate the context. Exactly one of query or messages should be provided.

​
filter
object

Optionally filter which documents can be retrieved using the following metadata fields.

Example:
{ "genre": { "$ne": "documentary" } }
​
messages
object[]

The list of messages to use for generating the context. Exactly one of query or messages should be provided.

The MessageModel describes the format of a message in a chat.

​
top_k
integer

The number of context snippets to return. Default is 15.

Example:

20

Response

200
application/json
Context retrieval process successful.

The response format containing the context from an assistant.

​
snippets
object[]
required

The SnippetModel represents a part of a document that is relevant to the user query.

​
usage
object
required

The UsageModel describes the usage of a chat completion.

​
id
string

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