Add Multi-CSV/DF support in CSV and DataFrame Toolkits
* CSV and DataFrame toolkits now accept list of CSVs/DFs
* Add default prompts for many dataframes in `pandas_dataframe` toolkit
Fixes#1958
Potentially fixes#4423
## Testing
* Add single and multi-dataframe integration tests for
`pandas_dataframe` toolkit with permutations of `include_df_in_prompt`
* Add single and multi-CSV integration tests for csv toolkit
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
# Add AzureCognitiveServicesToolkit to call Azure Cognitive Services
API: achieve some multimodal capabilities
This PR adds a toolkit named AzureCognitiveServicesToolkit which bundles
the following tools:
- AzureCogsImageAnalysisTool: calls Azure Cognitive Services image
analysis API to extract caption, objects, tags, and text from images.
- AzureCogsFormRecognizerTool: calls Azure Cognitive Services form
recognizer API to extract text, tables, and key-value pairs from
documents.
- AzureCogsSpeech2TextTool: calls Azure Cognitive Services speech to
text API to transcribe speech to text.
- AzureCogsText2SpeechTool: calls Azure Cognitive Services text to
speech API to synthesize text to speech.
This toolkit can be used to process image, document, and audio inputs.
---------
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
# Powerbi API wrapper bug fix + integration tests
- Bug fix by removing `TYPE_CHECKING` in in utilities/powerbi.py
- Added integration test for power bi api in
utilities/test_powerbi_api.py
- Added integration test for power bi agent in
agent/test_powerbi_agent.py
- Edited .env.examples to help set up power bi related environment
variables
- Updated demo notebook with working code in
docs../examples/powerbi.ipynb - AzureOpenAI -> ChatOpenAI
Notes:
Chat models (gpt3.5, gpt4) are much more capable than davinci at writing
DAX queries, so that is important to getting the agent to work properly.
Interestingly, gpt3.5-turbo needed the examples=DEFAULT_FEWSHOT_EXAMPLES
to write consistent DAX queries, so gpt4 seems necessary as the smart
llm.
Fixes#4325
## Before submitting
Azure-core and Azure-identity are necessary dependencies
check integration tests with the following:
`pytest tests/integration_tests/utilities/test_powerbi_api.py`
`pytest tests/integration_tests/agent/test_powerbi_agent.py`
You will need a power bi account with a dataset id + table name in order
to test. See .env.examples for details.
## Who can review?
@hwchase17
@vowelparrot
---------
Co-authored-by: aditya-pethe <adityapethe1@gmail.com>
# Add Spark SQL support
* Add Spark SQL support. It can connect to Spark via building a
local/remote SparkSession.
* Include a notebook example
I tried some complicated queries (window function, table joins), and the
tool works well.
Compared to the [Spark Dataframe
agent](https://python.langchain.com/en/latest/modules/agents/toolkits/examples/spark.html),
this tool is able to generate queries across multiple tables.
---------
# Your PR Title (What it does)
<!--
Thank you for contributing to LangChain! Your PR will appear in our next
release under the title you set. Please make sure it highlights your
valuable contribution.
Replace this with a description of the change, the issue it fixes (if
applicable), and relevant context. List any dependencies required for
this change.
After you're done, someone will review your PR. They may suggest
improvements. If no one reviews your PR within a few days, feel free to
@-mention the same people again, as notifications can get lost.
-->
<!-- Remove if not applicable -->
Fixes # (issue)
## Before submitting
<!-- If you're adding a new integration, include an integration test and
an example notebook showing its use! -->
## Who can review?
Community members can review the PR once tests pass. Tag
maintainers/contributors who might be interested:
<!-- For a quicker response, figure out the right person to tag with @
@hwchase17 - project lead
Tracing / Callbacks
- @agola11
Async
- @agola11
DataLoaders
- @eyurtsev
Models
- @hwchase17
- @agola11
Agents / Tools / Toolkits
- @vowelparrot
VectorStores / Retrievers / Memory
- @dev2049
-->
---------
Co-authored-by: Gengliang Wang <gengliang@apache.org>
Co-authored-by: Mike W <62768671+skcoirz@users.noreply.github.com>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Co-authored-by: UmerHA <40663591+UmerHA@users.noreply.github.com>
Co-authored-by: 张城铭 <z@hyperf.io>
Co-authored-by: assert <zhangchengming@kkguan.com>
Co-authored-by: blob42 <spike@w530>
Co-authored-by: Yuekai Zhang <zhangyuekai@foxmail.com>
Co-authored-by: Richard He <he.yucheng@outlook.com>
Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
Co-authored-by: Leonid Ganeline <leo.gan.57@gmail.com>
Co-authored-by: Alexey Nominas <60900649+Chae4ek@users.noreply.github.com>
Co-authored-by: elBarkey <elbarkey@gmail.com>
Co-authored-by: Davis Chase <130488702+dev2049@users.noreply.github.com>
Co-authored-by: Jeffrey D <1289344+verygoodsoftwarenotvirus@users.noreply.github.com>
Co-authored-by: so2liu <yangliu35@outlook.com>
Co-authored-by: Viswanadh Rayavarapu <44315599+vishwa-rn@users.noreply.github.com>
Co-authored-by: Chakib Ben Ziane <contact@blob42.xyz>
Co-authored-by: Daniel Chalef <131175+danielchalef@users.noreply.github.com>
Co-authored-by: Daniel Chalef <daniel.chalef@private.org>
Co-authored-by: Jari Bakken <jari.bakken@gmail.com>
Co-authored-by: escafati <scafatieugenio@gmail.com>
Adds a PlayWright web browser toolkit with the following tools:
- NavigateTool (navigate_browser) - navigate to a URL
- NavigateBackTool (previous_page) - wait for an element to appear
- ClickTool (click_element) - click on an element (specified by
selector)
- ExtractTextTool (extract_text) - use beautiful soup to extract text
from the current web page
- ExtractHyperlinksTool (extract_hyperlinks) - use beautiful soup to
extract hyperlinks from the current web page
- GetElementsTool (get_elements) - select elements by CSS selector
- CurrentPageTool (current_page) - get the current page URL
The specs used in chat-gpt plugins have only a few endpoints and have
unrealistically small specifications. By contrast, a spec like spotify's
has 60+ endpoints and is comprised 100k+ tokens.
Here are some impressive traces from gpt-4 that string together
non-trivial sequences of API calls. As noted in `planner.py`, gpt-3 is
not as robust but can be improved with i) better retry, self-reflect,
etc. logic and ii) better few-shots iii) etc. This PR's just a first
attempt probing a few different directions that eventually can be made
more core.
`make me a playlist with songs from kind of blue. call it machine
blues.`
```
> Entering new AgentExecutor chain...
Action: api_planner
Action Input: I need to find the right API calls to create a playlist with songs from Kind of Blue and name it Machine Blues
Observation: 1. GET /search to find the album ID for "Kind of Blue".
2. GET /albums/{id}/tracks to get the tracks from the "Kind of Blue" album.
3. GET /me to get the current user's ID.
4. POST /users/{user_id}/playlists to create a new playlist named "Machine Blues" for the current user.
5. POST /playlists/{playlist_id}/tracks to add the tracks from "Kind of Blue" to the newly created "Machine Blues" playlist.
Thought:I have a plan to create the playlist. Now, I will execute the API calls.
Action: api_controller
Action Input: 1. GET /search to find the album ID for "Kind of Blue".
2. GET /albums/{id}/tracks to get the tracks from the "Kind of Blue" album.
3. GET /me to get the current user's ID.
4. POST /users/{user_id}/playlists to create a new playlist named "Machine Blues" for the current user.
5. POST /playlists/{playlist_id}/tracks to add the tracks from "Kind of Blue" to the newly created "Machine Blues" playlist.
> Entering new AgentExecutor chain...
Action: requests_get
Action Input: {"url": "https://api.spotify.com/v1/search?q=Kind%20of%20Blue&type=album", "output_instructions": "Extract the id of the first album in the search results"}
Observation: 1weenld61qoidwYuZ1GESA
Thought:Action: requests_get
Action Input: {"url": "https://api.spotify.com/v1/albums/1weenld61qoidwYuZ1GESA/tracks", "output_instructions": "Extract the ids of all the tracks in the album"}
Observation: ["7q3kkfAVpmcZ8g6JUThi3o"]
Thought:Action: requests_get
Action Input: {"url": "https://api.spotify.com/v1/me", "output_instructions": "Extract the id of the current user"}
Observation: 22rhrz4m4kvpxlsb5hezokzwi
Thought:Action: requests_post
Action Input: {"url": "https://api.spotify.com/v1/users/22rhrz4m4kvpxlsb5hezokzwi/playlists", "data": {"name": "Machine Blues"}, "output_instructions": "Extract the id of the newly created playlist"}
Observation: 48YP9TMcEtFu9aGN8n10lg
Thought:Action: requests_post
Action Input: {"url": "https://api.spotify.com/v1/playlists/48YP9TMcEtFu9aGN8n10lg/tracks", "data": {"uris": ["spotify:track:7q3kkfAVpmcZ8g6JUThi3o"]}, "output_instructions": "Confirm that the tracks were added to the playlist"}
Observation: The tracks were added to the playlist. The snapshot_id is "Miw4NTdmMWUxOGU5YWMxMzVmYmE3ZWE5MWZlYWNkMTc2NGVmNTI1ZjY5".
Thought:I am finished executing the plan.
Final Answer: The tracks from the "Kind of Blue" album have been added to the newly created "Machine Blues" playlist. The playlist ID is 48YP9TMcEtFu9aGN8n10lg.
> Finished chain.
Observation: The tracks from the "Kind of Blue" album have been added to the newly created "Machine Blues" playlist. The playlist ID is 48YP9TMcEtFu9aGN8n10lg.
Thought:I am finished executing the plan and have created the playlist with songs from Kind of Blue, named Machine Blues.
Final Answer: I have created a playlist called "Machine Blues" with songs from the "Kind of Blue" album. The playlist ID is 48YP9TMcEtFu9aGN8n10lg.
> Finished chain.
```
or
`give me a song in the style of tobe nwige`
```
> Entering new AgentExecutor chain...
Action: api_planner
Action Input: I need to find the right API calls to get a song in the style of Tobe Nwigwe
Observation: 1. GET /search to find the artist ID for Tobe Nwigwe.
2. GET /artists/{id}/related-artists to find similar artists to Tobe Nwigwe.
3. Pick one of the related artists and use their artist ID in the next step.
4. GET /artists/{id}/top-tracks to get the top tracks of the chosen related artist.
Thought:
I'm ready to execute the API calls.
Action: api_controller
Action Input: 1. GET /search to find the artist ID for Tobe Nwigwe.
2. GET /artists/{id}/related-artists to find similar artists to Tobe Nwigwe.
3. Pick one of the related artists and use their artist ID in the next step.
4. GET /artists/{id}/top-tracks to get the top tracks of the chosen related artist.
> Entering new AgentExecutor chain...
Action: requests_get
Action Input: {"url": "https://api.spotify.com/v1/search?q=Tobe%20Nwigwe&type=artist", "output_instructions": "Extract the artist id for Tobe Nwigwe"}
Observation: 3Qh89pgJeZq6d8uM1bTot3
Thought:Action: requests_get
Action Input: {"url": "https://api.spotify.com/v1/artists/3Qh89pgJeZq6d8uM1bTot3/related-artists", "output_instructions": "Extract the ids and names of the related artists"}
Observation: [
{
"id": "75WcpJKWXBV3o3cfluWapK",
"name": "Lute"
},
{
"id": "5REHfa3YDopGOzrxwTsPvH",
"name": "Deante' Hitchcock"
},
{
"id": "6NL31G53xThQXkFs7lDpL5",
"name": "Rapsody"
},
{
"id": "5MbNzCW3qokGyoo9giHA3V",
"name": "EARTHGANG"
},
{
"id": "7Hjbimq43OgxaBRpFXic4x",
"name": "Saba"
},
{
"id": "1ewyVtTZBqFYWIcepopRhp",
"name": "Mick Jenkins"
}
]
Thought:Action: requests_get
Action Input: {"url": "https://api.spotify.com/v1/artists/75WcpJKWXBV3o3cfluWapK/top-tracks?country=US", "output_instructions": "Extract the ids and names of the top tracks"}
Observation: [
{
"id": "6MF4tRr5lU8qok8IKaFOBE",
"name": "Under The Sun (with J. Cole & Lute feat. DaBaby)"
}
]
Thought:I am finished executing the plan.
Final Answer: The top track of the related artist Lute is "Under The Sun (with J. Cole & Lute feat. DaBaby)" with the track ID "6MF4tRr5lU8qok8IKaFOBE".
> Finished chain.
Observation: The top track of the related artist Lute is "Under The Sun (with J. Cole & Lute feat. DaBaby)" with the track ID "6MF4tRr5lU8qok8IKaFOBE".
Thought:I am finished executing the plan and have the information the user asked for.
Final Answer: The song "Under The Sun (with J. Cole & Lute feat. DaBaby)" by Lute is in the style of Tobe Nwigwe.
> Finished chain.
```
---------
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>