> ## Documentation Index
> Fetch the complete documentation index at: https://docs.tako.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Answer
export const CodingAgentCTA = ({description, href}) =>
{description} Building with a coding agent?{" "}
Give your agent the full reference →
;
export const PlaygroundButton = ({href = "https://tako.com/playground", label = "Try in Playground"}) => ;
## Capabilities
Answer is the **fastest way to get a written, source-attributed answer** from Tako. It runs the same retrieval as [Search](/documentation/integrating-tako/search/overview) — Tako's structured knowledge cards **and** the live web — and **synthesizes the best answer from both** into one response, returned in a single synchronous call you can use inline.
A single request returns a finished `answer` — no dispatching, polling, or retrieval to orchestrate. Fast enough to drop inline into a chat, an assistant, or an agentic loop.
Answer grounds on the same retrieval as [Search](/documentation/integrating-tako/search/overview) — structured knowledge cards plus the live web — then writes the answer over them, so you get prose *and* the results that produced it in one call.
Every answer ships with the Tako `cards` **and web results** that back it — named sources and methodology — so it's citable, auditable, and safe to drop straight into a user-facing surface.
Choosing between Tako's surfaces (see the [full comparison](/documentation/integrating-tako/agent/overview#choosing-a-tako-surface)):
| Surface | What it's for |
| ---------------------------------------------------------------- | ----------------------------------------------------------------------------- |
| **[Answer](/api-reference/answer)** | A written, source-attributed answer in one call. |
| **[Search](/documentation/integrating-tako/search/overview)** | Fast, parallel retrieval of structured data and cards, no synthesized answer. |
| **[Answer Agent](/documentation/integrating-tako/agent/answer)** | Deep research synthesizing a cited answer backed by visualizations. |
| **[Search Agent](/documentation/integrating-tako/agent/search)** | Multi-step research returning schema-defined structured data and cards. |
## Example
```bash theme={null}
curl -X POST https://tako.com/api/v1/answer \
-H "X-API-Key: YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"query": "How have Nvidia and AMD headcount changed since 2013?"
}'
```
```bash theme={null}
pip install tako-sdk
```
```python theme={null}
import os
from tako import Configuration, SearchRequest
from tako.lib import Tako
config = Configuration()
config.api_key["apiKey"] = os.environ["TAKO_API_KEY"]
client = Tako(config)
response = client.answer(SearchRequest(query="How have Nvidia and AMD headcount changed since 2013?"))
print(response.answer)
for card in response.cards or []:
print(card.title, card.webpage_url)
```
Answer: "Nvidia has grown to about 36,000 full-time employees as of the end of 2024 — up roughly 309% from about 8,800 in 2013. AMD reached about 28,000 over the same period, giving Nvidia both the larger workforce and the faster growth of the two."
## Use cases
Return one synthesized, source-attributed answer in a single call.
```python theme={null}
response = client.answer(SearchRequest(query="What is the weather in San Francisco?"))
print(response.answer)
```
Re-run the same query to refresh prose that stays grounded in live data.
```python theme={null}
response = client.answer(SearchRequest(query="Latest US CPI, year over year"))
print(response.answer)
```
Use the backing cards' sources and methodology to cite the answer.
```python theme={null}
response = client.answer(SearchRequest(query="Nvidia revenue growth"))
for card in response.cards or []:
print(card.title, card.sources)
```
Limit the answer to Tako's authoritative sources, skipping the web.
```python theme={null}
response = client.answer(SearchRequest(query="Global military spending in 2024", sources={"data": {}}))
```
**Want the data behind a card as CSV?** Pass a card's URL to [Contents](/documentation/integrating-tako/contents/overview) to download its underlying data — or inline it here with `include_contents`.
By consuming the answer and its grounding information, you can keep your content always up to date and accurate.