## OpenAPI

We can construct agents to consume arbitrary APIs, here APIs conformant to the `OpenAPI`/`Swagger` specification.

```
# NOTE: In this example. We must set `allow_dangerous_request=True` to enable the OpenAPI Agent to automatically use the Request Tool.# This can be dangerous for calling unwanted requests. Please make sure your custom OpenAPI spec (yaml) is safe.ALLOW_DANGEROUS_REQUEST = True
```

## 1st example: hierarchical planning agent[​](#st-example-hierarchical-planning-agent "Direct link to 1st example: hierarchical planning agent")

In this example, we’ll consider an approach called hierarchical planning, common in robotics and appearing in recent works for LLMs X robotics. We’ll see it’s a viable approach to start working with a massive API spec AND to assist with user queries that require multiple steps against the API.

The idea is simple: to get coherent agent behavior over long sequences behavior & to save on tokens, we’ll separate concerns: a “planner” will be responsible for what endpoints to call and a “controller” will be responsible for how to call them.

In the initial implementation, the planner is an LLM chain that has the name and a short description for each endpoint in context. The controller is an LLM agent that is instantiated with documentation for only the endpoints for a particular plan. There’s a lot left to get this working very robustly :)

* * *

### To start, let’s collect some OpenAPI specs.[​](#to-start-lets-collect-some-openapi-specs. "Direct link to To start, let’s collect some OpenAPI specs.")

You will be able to get OpenAPI specs from here: [APIs-guru/openapi-directory](https://github.com/APIs-guru/openapi-directory)

```
!wget https://raw.githubusercontent.com/openai/openai-openapi/master/openapi.yaml -O openai_openapi.yaml!wget https://www.klarna.com/us/shopping/public/openai/v0/api-docs -O klarna_openapi.yaml!wget https://raw.githubusercontent.com/APIs-guru/openapi-directory/main/APIs/spotify.com/1.0.0/openapi.yaml -O spotify_openapi.yaml
```

```
--2023-03-31 15:45:56--  https://raw.githubusercontent.com/openai/openai-openapi/master/openapi.yamlResolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.110.133, 185.199.109.133, 185.199.111.133, ...Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.110.133|:443... connected.HTTP request sent, awaiting response... 200 OKLength: 122995 (120K) [text/plain]Saving to: ‘openapi.yaml’openapi.yaml        100%[===================>] 120.11K  --.-KB/s    in 0.01s   2023-03-31 15:45:56 (10.4 MB/s) - ‘openapi.yaml’ saved [122995/122995]--2023-03-31 15:45:57--  https://www.klarna.com/us/shopping/public/openai/v0/api-docsResolving www.klarna.com (www.klarna.com)... 52.84.150.34, 52.84.150.46, 52.84.150.61, ...Connecting to www.klarna.com (www.klarna.com)|52.84.150.34|:443... connected.HTTP request sent, awaiting response... 200 OKLength: unspecified [application/json]Saving to: ‘api-docs’api-docs                [ <=>                ]   1.87K  --.-KB/s    in 0s      2023-03-31 15:45:57 (261 MB/s) - ‘api-docs’ saved [1916]--2023-03-31 15:45:57--  https://raw.githubusercontent.com/APIs-guru/openapi-directory/main/APIs/spotify.com/1.0.0/openapi.yamlResolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.110.133, 185.199.109.133, 185.199.111.133, ...Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.110.133|:443... connected.HTTP request sent, awaiting response... 200 OKLength: 286747 (280K) [text/plain]Saving to: ‘openapi.yaml’openapi.yaml        100%[===================>] 280.03K  --.-KB/s    in 0.02s   2023-03-31 15:45:58 (13.3 MB/s) - ‘openapi.yaml’ saved [286747/286747]
```

```
from langchain_community.agent_toolkits.openapi.spec import reduce_openapi_spec
```

```
with open("openai_openapi.yaml") as f:    raw_openai_api_spec = yaml.load(f, Loader=yaml.Loader)openai_api_spec = reduce_openapi_spec(raw_openai_api_spec)with open("klarna_openapi.yaml") as f:    raw_klarna_api_spec = yaml.load(f, Loader=yaml.Loader)klarna_api_spec = reduce_openapi_spec(raw_klarna_api_spec)with open("spotify_openapi.yaml") as f:    raw_spotify_api_spec = yaml.load(f, Loader=yaml.Loader)spotify_api_spec = reduce_openapi_spec(raw_spotify_api_spec)
```

* * *

We’ll work with the Spotify API as one of the examples of a somewhat complex API. There’s a bit of auth-related setup to do if you want to replicate this.

*   You’ll have to set up an application in the Spotify developer console, documented [here](https://developer.spotify.com/documentation/general/guides/authorization/), to get credentials: `CLIENT_ID`, `CLIENT_SECRET`, and `REDIRECT_URI`.
*   To get an access tokens (and keep them fresh), you can implement the oauth flows, or you can use `spotipy`. If you’ve set your Spotify creedentials as environment variables `SPOTIPY_CLIENT_ID`, `SPOTIPY_CLIENT_SECRET`, and `SPOTIPY_REDIRECT_URI`, you can use the helper functions below:

```
import spotipy.util as utilfrom langchain.requests import RequestsWrapperdef construct_spotify_auth_headers(raw_spec: dict):    scopes = list(        raw_spec["components"]["securitySchemes"]["oauth_2_0"]["flows"][            "authorizationCode"        ]["scopes"].keys()    )    access_token = util.prompt_for_user_token(scope=",".join(scopes))    return {"Authorization": f"Bearer {access_token}"}# Get API credentials.headers = construct_spotify_auth_headers(raw_spotify_api_spec)requests_wrapper = RequestsWrapper(headers=headers)
```

### How big is this spec?[​](#how-big-is-this-spec "Direct link to How big is this spec?")

```
endpoints = [    (route, operation)    for route, operations in raw_spotify_api_spec["paths"].items()    for operation in operations    if operation in ["get", "post"]]len(endpoints)
```

```
import tiktokenenc = tiktoken.encoding_for_model("gpt-4")def count_tokens(s):    return len(enc.encode(s))count_tokens(yaml.dump(raw_spotify_api_spec))
```

### Let’s see some examples![​](#lets-see-some-examples "Direct link to Let’s see some examples!")

Starting with GPT-4. (Some robustness iterations under way for GPT-3 family.)

```
from langchain_community.agent_toolkits.openapi import plannerfrom langchain_openai import ChatOpenAIllm = ChatOpenAI(model_name="gpt-4", temperature=0.0)
```

```
/Users/jeremywelborn/src/langchain/langchain/llms/openai.py:169: UserWarning: You are trying to use a chat model. This way of initializing it is no longer supported. Instead, please use: `from langchain_openai import ChatOpenAI`  warnings.warn(/Users/jeremywelborn/src/langchain/langchain/llms/openai.py:608: UserWarning: You are trying to use a chat model. This way of initializing it is no longer supported. Instead, please use: `from langchain_openai import ChatOpenAI`  warnings.warn(
```

```
# NOTE: set allow_dangerous_requests manually for security concern https://python.langchain.com/docs/securityspotify_agent = planner.create_openapi_agent(    spotify_api_spec,    requests_wrapper,    llm,    allow_dangerous_requests=ALLOW_DANGEROUS_REQUEST,)user_query = (    "make me a playlist with the first song from kind of blue. call it machine blues.")spotify_agent.invoke(user_query)
```

```
> Entering new AgentExecutor chain...Action: api_plannerAction Input: I need to find the right API calls to create a playlist with the first song from Kind of Blue and name it Machine BluesObservation: 1. GET /search to search for the album "Kind of Blue"2. GET /albums/{id}/tracks to get the tracks from the "Kind of Blue" album3. GET /me to get the current user's information4. POST /users/{user_id}/playlists to create a new playlist named "Machine Blues" for the current user5. POST /playlists/{playlist_id}/tracks to add the first song from "Kind of Blue" to the "Machine Blues" playlistThought:I have the plan, now I need to execute the API calls.Action: api_controllerAction Input: 1. GET /search to search for the album "Kind of Blue"2. GET /albums/{id}/tracks to get the tracks from the "Kind of Blue" album3. GET /me to get the current user's information4. POST /users/{user_id}/playlists to create a new playlist named "Machine Blues" for the current user5. POST /playlists/{playlist_id}/tracks to add the first song from "Kind of Blue" to the "Machine Blues" playlist> Entering new AgentExecutor chain...Action: requests_getAction 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: 1weenld61qoidwYuZ1GESAThought:Action: requests_getAction Input: {"url": "https://api.spotify.com/v1/albums/1weenld61qoidwYuZ1GESA/tracks", "output_instructions": "Extract the id of the first track in the album"}Observation: 7q3kkfAVpmcZ8g6JUThi3oThought:Action: requests_getAction Input: {"url": "https://api.spotify.com/v1/me", "output_instructions": "Extract the id of the current user"}Observation: 22rhrz4m4kvpxlsb5hezokzwiThought:Action: requests_postAction Input: {"url": "https://api.spotify.com/v1/users/22rhrz4m4kvpxlsb5hezokzwi/playlists", "data": {"name": "Machine Blues"}, "output_instructions": "Extract the id of the created playlist"}Observation: 7lzoEi44WOISnFYlrAIqyXThought:Action: requests_postAction Input: {"url": "https://api.spotify.com/v1/playlists/7lzoEi44WOISnFYlrAIqyX/tracks", "data": {"uris": ["spotify:track:7q3kkfAVpmcZ8g6JUThi3o"]}, "output_instructions": "Confirm that the track was added to the playlist"}Observation: The track was added to the playlist, confirmed by the snapshot_id: MiwxODMxNTMxZTFlNzg3ZWFlZmMxYTlmYWQyMDFiYzUwNDEwMTAwZmE1.Thought:I am finished executing the plan.Final Answer: The first song from the "Kind of Blue" album has been added to the "Machine Blues" playlist.> Finished chain.Observation: The first song from the "Kind of Blue" album has been added to the "Machine Blues" playlist.Thought:I am finished executing the plan and have created the playlist with the first song from Kind of Blue.Final Answer: I have created a playlist called "Machine Blues" with the first song from the "Kind of Blue" album.> Finished chain.
```

```
'I have created a playlist called "Machine Blues" with the first song from the "Kind of Blue" album.'
```

```
user_query = "give me a song I'd like, make it blues-ey"spotify_agent.invoke(user_query)
```

```
> Entering new AgentExecutor chain...Action: api_plannerAction Input: I need to find the right API calls to get a blues song recommendation for the userObservation: 1. GET /me to get the current user's information2. GET /recommendations/available-genre-seeds to retrieve a list of available genres3. GET /recommendations with the seed_genre parameter set to "blues" to get a blues song recommendation for the userThought:I have the plan, now I need to execute the API calls.Action: api_controllerAction Input: 1. GET /me to get the current user's information2. GET /recommendations/available-genre-seeds to retrieve a list of available genres3. GET /recommendations with the seed_genre parameter set to "blues" to get a blues song recommendation for the user> Entering new AgentExecutor chain...Action: requests_getAction Input: {"url": "https://api.spotify.com/v1/me", "output_instructions": "Extract the user's id and username"}Observation: ID: 22rhrz4m4kvpxlsb5hezokzwi, Username: Jeremy WelbornThought:Action: requests_getAction Input: {"url": "https://api.spotify.com/v1/recommendations/available-genre-seeds", "output_instructions": "Extract the list of available genres"}Observation: acoustic, afrobeat, alt-rock, alternative, ambient, anime, black-metal, bluegrass, blues, bossanova, brazil, breakbeat, british, cantopop, chicago-house, children, chill, classical, club, comedy, country, dance, dancehall, death-metal, deep-house, detroit-techno, disco, disney, drum-and-bass, dub, dubstep, edm, electro, electronic, emo, folk, forro, french, funk, garage, german, gospel, goth, grindcore, groove, grunge, guitar, happy, hard-rock, hardcore, hardstyle, heavy-metal, hip-hop, holidays, honky-tonk, house, idm, indian, indie, indie-pop, industrial, iranian, j-dance, j-idol, j-pop, j-rock, jazz, k-pop, kids, latin, latino, malay, mandopop, metal, metal-misc, metalcore, minimal-techno, movies, mpb, new-age, new-release, opera, pagode, party, philippines-Thought:Action: requests_getAction Input: {"url": "https://api.spotify.com/v1/recommendations?seed_genres=blues", "output_instructions": "Extract the list of recommended tracks with their ids and names"}Observation: [  {    id: '03lXHmokj9qsXspNsPoirR',    name: 'Get Away Jordan'  }]Thought:I am finished executing the plan.Final Answer: The recommended blues song for user Jeremy Welborn (ID: 22rhrz4m4kvpxlsb5hezokzwi) is "Get Away Jordan" with the track ID: 03lXHmokj9qsXspNsPoirR.> Finished chain.Observation: The recommended blues song for user Jeremy Welborn (ID: 22rhrz4m4kvpxlsb5hezokzwi) is "Get Away Jordan" with the track ID: 03lXHmokj9qsXspNsPoirR.Thought:I am finished executing the plan and have the information the user asked for.Final Answer: The recommended blues song for you is "Get Away Jordan" with the track ID: 03lXHmokj9qsXspNsPoirR.> Finished chain.
```

```
Retrying langchain.llms.openai.completion_with_retry.<locals>._completion_with_retry in 4.0 seconds as it raised RateLimitError: That model is currently overloaded with other requests. You can retry your request, or contact us through our help center at help.openai.com if the error persists. (Please include the request ID 2167437a0072228238f3c0c5b3882764 in your message.).
```

```
'The recommended blues song for you is "Get Away Jordan" with the track ID: 03lXHmokj9qsXspNsPoirR.'
```

#### Try another API.[​](#try-another-api. "Direct link to Try another API.")

```
headers = {"Authorization": f"Bearer {os.getenv('OPENAI_API_KEY')}"}openai_requests_wrapper = RequestsWrapper(headers=headers)
```

```
# Meta!llm = ChatOpenAI(model_name="gpt-4", temperature=0.25)openai_agent = planner.create_openapi_agent(    openai_api_spec, openai_requests_wrapper, llm)user_query = "generate a short piece of advice"openai_agent.invoke(user_query)
```

```
> Entering new AgentExecutor chain...Action: api_plannerAction Input: I need to find the right API calls to generate a short piece of adviceObservation: 1. GET /engines to retrieve the list of available engines2. POST /completions with the selected engine and a prompt for generating a short piece of adviceThought:I have the plan, now I need to execute the API calls.Action: api_controllerAction Input: 1. GET /engines to retrieve the list of available engines2. POST /completions with the selected engine and a prompt for generating a short piece of advice> Entering new AgentExecutor chain...Action: requests_getAction Input: {"url": "https://api.openai.com/v1/engines", "output_instructions": "Extract the ids of the engines"}Observation: babbage, davinci, text-davinci-edit-001, babbage-code-search-code, text-similarity-babbage-001, code-davinci-edit-001, text-davinci-001, ada, babbage-code-search-text, babbage-similarity, whisper-1, code-search-babbage-text-001, text-curie-001, code-search-babbage-code-001, text-ada-001, text-embedding-ada-002, text-similarity-ada-001, curie-instruct-beta, ada-code-search-code, ada-similarity, text-davinci-003, code-search-ada-text-001, text-search-ada-query-001, davinci-search-document, ada-code-search-text, text-search-ada-doc-001, davinci-instruct-beta, text-similarity-curie-001, code-search-ada-code-001Thought:I will use the "davinci" engine to generate a short piece of advice.Action: requests_postAction Input: {"url": "https://api.openai.com/v1/completions", "data": {"engine": "davinci", "prompt": "Give me a short piece of advice on how to be more productive."}, "output_instructions": "Extract the text from the first choice"}Observation: "you must provide a model parameter"Thought:!! Could not _extract_tool_and_input from "I cannot finish executing the plan without knowing how to provide the model parameter correctly." in _get_next_actionI cannot finish executing the plan without knowing how to provide the model parameter correctly.> Finished chain.Observation: I need more information on how to provide the model parameter correctly in the POST request to generate a short piece of advice.Thought:I need to adjust my plan to include the model parameter in the POST request.Action: api_plannerAction Input: I need to find the right API calls to generate a short piece of advice, including the model parameter in the POST requestObservation: 1. GET /models to retrieve the list of available models2. Choose a suitable model from the list3. POST /completions with the chosen model as a parameter to generate a short piece of adviceThought:I have an updated plan, now I need to execute the API calls.Action: api_controllerAction Input: 1. GET /models to retrieve the list of available models2. Choose a suitable model from the list3. POST /completions with the chosen model as a parameter to generate a short piece of advice> Entering new AgentExecutor chain...Action: requests_getAction Input: {"url": "https://api.openai.com/v1/models", "output_instructions": "Extract the ids of the available models"}Observation: babbage, davinci, text-davinci-edit-001, babbage-code-search-code, text-similarity-babbage-001, code-davinci-edit-001, text-davinci-edit-001, adaThought:Action: requests_postAction Input: {"url": "https://api.openai.com/v1/completions", "data": {"model": "davinci", "prompt": "Give me a short piece of advice on how to improve communication skills."}, "output_instructions": "Extract the text from the first choice"}Observation: "I'd like to broaden my horizon.\n\nI was trying to"Thought:I cannot finish executing the plan without knowing some other information.Final Answer: The generated text is not a piece of advice on improving communication skills. I would need to retry the API call with a different prompt or model to get a more relevant response.> Finished chain.Observation: The generated text is not a piece of advice on improving communication skills. I would need to retry the API call with a different prompt or model to get a more relevant response.Thought:I need to adjust my plan to include a more specific prompt for generating a short piece of advice on improving communication skills.Action: api_plannerAction Input: I need to find the right API calls to generate a short piece of advice on improving communication skills, including the model parameter in the POST requestObservation: 1. GET /models to retrieve the list of available models2. Choose a suitable model for generating text (e.g., text-davinci-002)3. POST /completions with the chosen model and a prompt related to improving communication skills to generate a short piece of adviceThought:I have an updated plan, now I need to execute the API calls.Action: api_controllerAction Input: 1. GET /models to retrieve the list of available models2. Choose a suitable model for generating text (e.g., text-davinci-002)3. POST /completions with the chosen model and a prompt related to improving communication skills to generate a short piece of advice> Entering new AgentExecutor chain...Action: requests_getAction Input: {"url": "https://api.openai.com/v1/models", "output_instructions": "Extract the names of the models"}Observation: babbage, davinci, text-davinci-edit-001, babbage-code-search-code, text-similarity-babbage-001, code-davinci-edit-001, text-davinci-edit-001, adaThought:Action: requests_postAction Input: {"url": "https://api.openai.com/v1/completions", "data": {"model": "text-davinci-002", "prompt": "Give a short piece of advice on how to improve communication skills"}, "output_instructions": "Extract the text from the first choice"}Observation: "Some basic advice for improving communication skills would be to make sure to listen"Thought:I am finished executing the plan.Final Answer: Some basic advice for improving communication skills would be to make sure to listen.> Finished chain.Observation: Some basic advice for improving communication skills would be to make sure to listen.Thought:I am finished executing the plan and have the information the user asked for.Final Answer: A short piece of advice for improving communication skills is to make sure to listen.> Finished chain.
```

```
'A short piece of advice for improving communication skills is to make sure to listen.'
```

Takes awhile to get there!

## 2nd example: “json explorer” agent[​](#nd-example-json-explorer-agent "Direct link to 2nd example: “json explorer” agent")

Here’s an agent that’s not particularly practical, but neat! The agent has access to 2 toolkits. One comprises tools to interact with json: one tool to list the keys of a json object and another tool to get the value for a given key. The other toolkit comprises `requests` wrappers to send GET and POST requests. This agent consumes a lot calls to the language model, but does a surprisingly decent job.

```
from langchain.agents import create_openapi_agentfrom langchain_community.agent_toolkits import OpenAPIToolkitfrom langchain_community.tools.json.tool import JsonSpecfrom langchain_openai import OpenAI
```

```
with open("openai_openapi.yaml") as f:    data = yaml.load(f, Loader=yaml.FullLoader)json_spec = JsonSpec(dict_=data, max_value_length=4000)openapi_toolkit = OpenAPIToolkit.from_llm(    OpenAI(temperature=0), json_spec, openai_requests_wrapper, verbose=True)openapi_agent_executor = create_openapi_agent(    llm=OpenAI(temperature=0),    toolkit=openapi_toolkit,    allow_dangerous_requests=ALLOW_DANGEROUS_REQUEST,    verbose=True,)
```

```
openapi_agent_executor.run(    "Make a post request to openai /completions. The prompt should be 'tell me a joke.'")
```

```
> Entering new AgentExecutor chain...Action: json_explorerAction Input: What is the base url for the API?> Entering new AgentExecutor chain...Action: json_spec_list_keysAction Input: dataObservation: ['openapi', 'info', 'servers', 'tags', 'paths', 'components', 'x-oaiMeta']Thought: I should look at the servers key to see what the base url isAction: json_spec_list_keysAction Input: data["servers"][0]Observation: ValueError('Value at path `data["servers"][0]` is not a dict, get the value directly.')Thought: I should get the value of the servers keyAction: json_spec_get_valueAction Input: data["servers"][0]Observation: {'url': 'https://api.openai.com/v1'}Thought: I now know the base url for the APIFinal Answer: The base url for the API is https://api.openai.com/v1> Finished chain.Observation: The base url for the API is https://api.openai.com/v1Thought: I should find the path for the /completions endpoint.Action: json_explorerAction Input: What is the path for the /completions endpoint?> Entering new AgentExecutor chain...Action: json_spec_list_keysAction Input: dataObservation: ['openapi', 'info', 'servers', 'tags', 'paths', 'components', 'x-oaiMeta']Thought: I should look at the paths key to see what endpoints existAction: json_spec_list_keysAction Input: data["paths"]Observation: ['/engines', '/engines/{engine_id}', '/completions', '/chat/completions', '/edits', '/images/generations', '/images/edits', '/images/variations', '/embeddings', '/audio/transcriptions', '/audio/translations', '/engines/{engine_id}/search', '/files', '/files/{file_id}', '/files/{file_id}/content', '/answers', '/classifications', '/fine-tunes', '/fine-tunes/{fine_tune_id}', '/fine-tunes/{fine_tune_id}/cancel', '/fine-tunes/{fine_tune_id}/events', '/models', '/models/{model}', '/moderations']Thought: I now know the path for the /completions endpointFinal Answer: The path for the /completions endpoint is data["paths"][2]> Finished chain.Observation: The path for the /completions endpoint is data["paths"][2]Thought: I should find the required parameters for the POST request.Action: json_explorerAction Input: What are the required parameters for a POST request to the /completions endpoint?> Entering new AgentExecutor chain...Action: json_spec_list_keysAction Input: dataObservation: ['openapi', 'info', 'servers', 'tags', 'paths', 'components', 'x-oaiMeta']Thought: I should look at the paths key to see what endpoints existAction: json_spec_list_keysAction Input: data["paths"]Observation: ['/engines', '/engines/{engine_id}', '/completions', '/chat/completions', '/edits', '/images/generations', '/images/edits', '/images/variations', '/embeddings', '/audio/transcriptions', '/audio/translations', '/engines/{engine_id}/search', '/files', '/files/{file_id}', '/files/{file_id}/content', '/answers', '/classifications', '/fine-tunes', '/fine-tunes/{fine_tune_id}', '/fine-tunes/{fine_tune_id}/cancel', '/fine-tunes/{fine_tune_id}/events', '/models', '/models/{model}', '/moderations']Thought: I should look at the /completions endpoint to see what parameters are requiredAction: json_spec_list_keysAction Input: data["paths"]["/completions"]Observation: ['post']Thought: I should look at the post key to see what parameters are requiredAction: json_spec_list_keysAction Input: data["paths"]["/completions"]["post"]Observation: ['operationId', 'tags', 'summary', 'requestBody', 'responses', 'x-oaiMeta']Thought: I should look at the requestBody key to see what parameters are requiredAction: json_spec_list_keysAction Input: data["paths"]["/completions"]["post"]["requestBody"]Observation: ['required', 'content']Thought: I should look at the content key to see what parameters are requiredAction: json_spec_list_keysAction Input: data["paths"]["/completions"]["post"]["requestBody"]["content"]Observation: ['application/json']Thought: I should look at the application/json key to see what parameters are requiredAction: json_spec_list_keysAction Input: data["paths"]["/completions"]["post"]["requestBody"]["content"]["application/json"]Observation: ['schema']Thought: I should look at the schema key to see what parameters are requiredAction: json_spec_list_keysAction Input: data["paths"]["/completions"]["post"]["requestBody"]["content"]["application/json"]["schema"]Observation: ['$ref']Thought: I should look at the $ref key to see what parameters are requiredAction: json_spec_list_keysAction Input: data["paths"]["/completions"]["post"]["requestBody"]["content"]["application/json"]["schema"]["$ref"]Observation: ValueError('Value at path `data["paths"]["/completions"]["post"]["requestBody"]["content"]["application/json"]["schema"]["$ref"]` is not a dict, get the value directly.')Thought: I should look at the $ref key to get the value directlyAction: json_spec_get_valueAction Input: data["paths"]["/completions"]["post"]["requestBody"]["content"]["application/json"]["schema"]["$ref"]Observation: #/components/schemas/CreateCompletionRequestThought: I should look at the CreateCompletionRequest schema to see what parameters are requiredAction: json_spec_list_keysAction Input: data["components"]["schemas"]["CreateCompletionRequest"]Observation: ['type', 'properties', 'required']Thought: I should look at the required key to see what parameters are requiredAction: json_spec_get_valueAction Input: data["components"]["schemas"]["CreateCompletionRequest"]["required"]Observation: ['model']Thought: I now know the final answerFinal Answer: The required parameters for a POST request to the /completions endpoint are 'model'.> Finished chain.Observation: The required parameters for a POST request to the /completions endpoint are 'model'.Thought: I now know the parameters needed to make the request.Action: requests_postAction Input: { "url": "https://api.openai.com/v1/completions", "data": { "model": "davinci", "prompt": "tell me a joke" } }Observation: {"id":"cmpl-70Ivzip3dazrIXU8DSVJGzFJj2rdv","object":"text_completion","created":1680307139,"model":"davinci","choices":[{"text":" with mummy not there”\n\nYou dig deep and come up with,","index":0,"logprobs":null,"finish_reason":"length"}],"usage":{"prompt_tokens":4,"completion_tokens":16,"total_tokens":20}}Thought: I now know the final answer.Final Answer: The response of the POST request is {"id":"cmpl-70Ivzip3dazrIXU8DSVJGzFJj2rdv","object":"text_completion","created":1680307139,"model":"davinci","choices":[{"text":" with mummy not there”\n\nYou dig deep and come up with,","index":0,"logprobs":null,"finish_reason":"length"}],"usage":{"prompt_tokens":4,"completion_tokens":16,"total_tokens":20}}> Finished chain.
```

```
'The response of the POST request is {"id":"cmpl-70Ivzip3dazrIXU8DSVJGzFJj2rdv","object":"text_completion","created":1680307139,"model":"davinci","choices":[{"text":" with mummy not there”\\n\\nYou dig deep and come up with,","index":0,"logprobs":null,"finish_reason":"length"}],"usage":{"prompt_tokens":4,"completion_tokens":16,"total_tokens":20}}'
```